code stringlengths 1 2.06M | language stringclasses 1 value |
|---|---|
/**********************************************************************
* File: memry.c (Formerly memory.c)
* Description: Memory allocation with builtin safety checks.
* Author: Ray Smith
* Created: Wed Jan 22 09:43:33 GMT 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "memry.h"
#include <stdlib.h>
// With improvements in OS memory allocators, internal memory management
// is no longer required, so all these functions now map to their malloc
// family equivalents.
// TODO(rays) further cleanup by redirecting calls to new and creating proper
// constructors.
char *alloc_string(inT32 count) {
// Round up the amount allocated to a multiple of 4
return static_cast<char*>(malloc((count + 3) & ~3));
}
void free_string(char *string) {
free(string);
}
void* alloc_struct(inT32 count, const char *) {
return malloc(count);
}
void free_struct(void *deadstruct, inT32, const char *) {
free(deadstruct);
}
void *alloc_mem(inT32 count) {
return malloc(static_cast<size_t>(count));
}
void *alloc_big_zeros(inT32 count) {
return calloc(static_cast<size_t>(count), 1);
}
void free_mem(void *oldchunk) {
free(oldchunk);
}
void free_big_mem(void *oldchunk) {
free(oldchunk);
}
| C++ |
// Copyright 2011 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: bitvector.h
// Description: Class replacement for BITVECTOR.
// Author: Ray Smith
// Created: Mon Jan 10 17:44:01 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCUTIL_BITVECTOR_H__
#define TESSERACT_CCUTIL_BITVECTOR_H__
#include <assert.h>
#include <stdio.h>
#include "host.h"
namespace tesseract {
// Trivial class to encapsulate a fixed-length array of bits, with
// Serialize/DeSerialize. Replaces the old macros.
class BitVector {
public:
// Fast lookup table to get the first least significant set bit in a byte.
// For zero, the table has 255, but since it is a special case, most code
// that uses this table will check for zero before looking up lsb_index_.
static const uinT8 lsb_index_[256];
// Fast lookup table to get the residual bits after zeroing the least
// significant set bit in a byte.
static const uinT8 lsb_eroded_[256];
// Fast lookup table to give the number of set bits in a byte.
static const int hamming_table_[256];
BitVector();
// Initializes the array to length * false.
explicit BitVector(int length);
BitVector(const BitVector& src);
BitVector& operator=(const BitVector& src);
~BitVector();
// Initializes the array to length * false.
void Init(int length);
// Returns the number of bits that are accessible in the vector.
int size() const {
return bit_size_;
}
// Writes to the given file. Returns false in case of error.
bool Serialize(FILE* fp) const;
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, FILE* fp);
void SetAllFalse();
void SetAllTrue();
// Accessors to set/reset/get bits.
// The range of index is [0, size()-1].
// There is debug-only bounds checking.
void SetBit(int index) {
array_[WordIndex(index)] |= BitMask(index);
}
void ResetBit(int index) {
array_[WordIndex(index)] &= ~BitMask(index);
}
void SetValue(int index, bool value) {
if (value)
SetBit(index);
else
ResetBit(index);
}
bool At(int index) const {
return (array_[WordIndex(index)] & BitMask(index)) != 0;
}
bool operator[](int index) const {
return (array_[WordIndex(index)] & BitMask(index)) != 0;
}
// Returns the index of the next set bit after the given index.
// Useful for quickly iterating through the set bits in a sparse vector.
int NextSetBit(int prev_bit) const;
// Returns the number of set bits in the vector.
int NumSetBits() const;
// Logical in-place operations on whole bit vectors. Tries to do something
// sensible if they aren't the same size, but they should be really.
void operator|=(const BitVector& other);
void operator&=(const BitVector& other);
void operator^=(const BitVector& other);
// Set subtraction *this = v1 - v2.
void SetSubtract(const BitVector& v1, const BitVector& v2);
private:
// Allocates memory for a vector of the given length.
void Alloc(int length);
// Computes the index to array_ for the given index, with debug range
// checking.
int WordIndex(int index) const {
assert(0 <= index && index < bit_size_);
return index / kBitFactor;
}
// Returns a mask to select the appropriate bit for the given index.
uinT32 BitMask(int index) const {
return 1 << (index & (kBitFactor - 1));
}
// Returns the number of array elements needed to represent the current
// bit_size_.
int WordLength() const {
return (bit_size_ + kBitFactor - 1) / kBitFactor;
}
// Returns the number of bytes consumed by the array_.
int ByteLength() const {
return WordLength() * sizeof(*array_);
}
// Number of bits in this BitVector.
inT32 bit_size_;
// Array of words used to pack the bits.
// Bits are stored little-endian by uinT32 word, ie by word first and then
// starting with the least significant bit in each word.
uinT32* array_;
// Number of bits in an array_ element.
static const int kBitFactor = sizeof(uinT32) * 8;
};
} // namespace tesseract.
#endif // TESSERACT_CCUTIL_BITVECTOR_H__
| C++ |
/**********************************************************************
* File: strngs.h (Formerly strings.h)
* Description: STRING class definition.
* Author: Ray Smith
* Created: Fri Feb 15 09:15:01 GMT 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef STRNGS_H
#define STRNGS_H
#include <stdio.h>
#include <string.h>
#include "platform.h"
#include "memry.h"
namespace tesseract {
class TFile;
} // namespace tesseract.
// STRING_IS_PROTECTED means that string[index] = X is invalid
// because you have to go through strings interface to modify it.
// This allows the string to ensure internal integrity and maintain
// its own string length. Unfortunately this is not possible because
// STRINGS are used as direct-manipulation data buffers for things
// like length arrays and many places cast away the const on string()
// to mutate the string. Turning this off means that internally we
// cannot assume we know the strlen.
#define STRING_IS_PROTECTED 0
template <typename T> class GenericVector;
class TESS_API STRING
{
public:
STRING();
STRING(const STRING &string);
STRING(const char *string);
STRING(const char *data, int length);
~STRING ();
// Writes to the given file. Returns false in case of error.
bool Serialize(FILE* fp) const;
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, FILE* fp);
// Writes to the given file. Returns false in case of error.
bool Serialize(tesseract::TFile* fp) const;
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, tesseract::TFile* fp);
BOOL8 contains(const char c) const;
inT32 length() const;
inT32 size() const { return length(); }
const char *string() const;
const char *c_str() const;
inline char* strdup() const {
inT32 len = length() + 1;
return strncpy(new char[len], GetCStr(), len);
}
#if STRING_IS_PROTECTED
const char &operator[] (inT32 index) const;
// len is number of chars in s to insert starting at index in this string
void insert_range(inT32 index, const char*s, int len);
void erase_range(inT32 index, int len);
#else
char &operator[] (inT32 index) const;
#endif
void split(const char c, GenericVector<STRING> *splited);
void truncate_at(inT32 index);
BOOL8 operator== (const STRING & string) const;
BOOL8 operator!= (const STRING & string) const;
BOOL8 operator!= (const char *string) const;
STRING & operator= (const char *string);
STRING & operator= (const STRING & string);
STRING operator+ (const STRING & string) const;
STRING operator+ (const char ch) const;
STRING & operator+= (const char *string);
STRING & operator+= (const STRING & string);
STRING & operator+= (const char ch);
// Assignment for strings which are not null-terminated.
void assign(const char *cstr, int len);
// Appends the given string and int (as a %d) to this.
// += cannot be used for ints as there as a char += operator that would
// be ambiguous, and ints usually need a string before or between them
// anyway.
void add_str_int(const char* str, int number);
// Appends the given string and double (as a %.8g) to this.
void add_str_double(const char* str, double number);
// ensure capacity but keep pointer encapsulated
inline void ensure(inT32 min_capacity) { ensure_cstr(min_capacity); }
private:
typedef struct STRING_HEADER {
// How much space was allocated in the string buffer for char data.
int capacity_;
// used_ is how much of the capacity is currently being used,
// including a '\0' terminator.
//
// If used_ is 0 then string is NULL (not even the '\0')
// else if used_ > 0 then it is strlen() + 1 (because it includes '\0')
// else strlen is >= 0 (not NULL) but needs to be computed.
// this condition is set when encapsulation is violated because
// an API returned a mutable string.
//
// capacity_ - used_ = excess capacity that the string can grow
// without reallocating
mutable int used_;
} STRING_HEADER;
// To preserve the behavior of the old serialization, we only have space
// for one pointer in this structure. So we are embedding a data structure
// at the start of the storage that will hold additional state variables,
// then storing the actual string contents immediately after.
STRING_HEADER* data_;
// returns the header part of the storage
inline STRING_HEADER* GetHeader() {
return data_;
}
inline const STRING_HEADER* GetHeader() const {
return data_;
}
// returns the string data part of storage
inline char* GetCStr() {
return ((char *)data_) + sizeof(STRING_HEADER);
};
inline const char* GetCStr() const {
return ((const char *)data_) + sizeof(STRING_HEADER);
};
inline bool InvariantOk() const {
#if STRING_IS_PROTECTED
return (GetHeader()->used_ == 0) ?
(string() == NULL) : (GetHeader()->used_ == (strlen(string()) + 1));
#else
return true;
#endif
}
// Ensure string has requested capacity as optimization
// to avoid unnecessary reallocations.
// The return value is a cstr buffer with at least requested capacity
char* ensure_cstr(inT32 min_capacity);
void FixHeader() const; // make used_ non-negative, even if const
char* AllocData(int used, int capacity);
void DiscardData();
};
#endif
| C++ |
// Copyright 2012 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: doubleptr.h
// Description: Double-ended pointer that keeps pointing correctly even
// when reallocated or copied.
// Author: Ray Smith
// Created: Wed Mar 14 12:22:57 PDT 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCUTIL_DOUBLEPTR_H_
#define TESSERACT_CCUTIL_DOUBLEPTR_H_
#include "errcode.h"
namespace tesseract {
// A smart pointer class that implements a double-ended pointer. Each end
// points to the other end. The copy constructor and operator= have MOVE
// semantics, meaning that the relationship with the other end moves to the
// destination of the copy, leaving the source unattached.
// For this reason both the copy constructor and the operator= take a non-const
// reference argument, and the const reference versions cannot be used.
// DoublePtr is useful to incorporate into structures that are part of a
// collection such as GenericVector or STL containers, where reallocs can
// relocate the members. DoublePtr is also useful in a GenericHeap, where it
// can correctly maintain the pointer to an element of the heap despite it
// getting moved around on the heap.
class DoublePtr {
public:
DoublePtr() : other_end_(NULL) {}
// Copy constructor steals the partner off src and is therefore a non
// const reference arg.
// Copying a const DoublePtr generates a compiler error.
DoublePtr(DoublePtr& src) {
other_end_ = src.other_end_;
if (other_end_ != NULL) {
other_end_->other_end_ = this;
src.other_end_ = NULL;
}
}
// Operator= steals the partner off src, and therefore needs src to be a non-
// const reference.
// Assigning from a const DoublePtr generates a compiler error.
void operator=(DoublePtr& src) {
Disconnect();
other_end_ = src.other_end_;
if (other_end_ != NULL) {
other_end_->other_end_ = this;
src.other_end_ = NULL;
}
}
// Connects this and other, discarding any existing connections.
void Connect(DoublePtr* other) {
other->Disconnect();
Disconnect();
other->other_end_ = this;
other_end_ = other;
}
// Disconnects this and other, making OtherEnd() return NULL for both.
void Disconnect() {
if (other_end_ != NULL) {
other_end_->other_end_ = NULL;
other_end_ = NULL;
}
}
// Returns the pointer to the other end of the double pointer.
DoublePtr* OtherEnd() const {
return other_end_;
}
private:
// Pointer to the other end of the link. It is always true that either
// other_end_ == NULL or other_end_->other_end_ == this.
DoublePtr* other_end_;
};
} // namespace tesseract.
#endif // THIRD_PARTY_TESSERACT_CCUTIL_DOUBLEPTR_H_
| C++ |
/**********************************************************************
* File: serialis.h (Formerly serialmac.h)
* Description: Inline routines and macros for serialisation functions
* Author: Phil Cheatle
* Created: Tue Oct 08 08:33:12 BST 1991
*
* (C) Copyright 1990, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "serialis.h"
#include <stdio.h>
#include "genericvector.h"
namespace tesseract {
TFile::TFile()
: offset_(0), data_(NULL), data_is_owned_(false), is_writing_(false) {
}
TFile::~TFile() {
if (data_is_owned_)
delete data_;
}
bool TFile::Open(const STRING& filename, FileReader reader) {
if (!data_is_owned_) {
data_ = new GenericVector<char>;
data_is_owned_ = true;
}
offset_ = 0;
is_writing_ = false;
if (reader == NULL)
return LoadDataFromFile(filename, data_);
else
return (*reader)(filename, data_);
}
bool TFile::Open(const char* data, int size) {
offset_ = 0;
if (!data_is_owned_) {
data_ = new GenericVector<char>;
data_is_owned_ = true;
}
is_writing_ = false;
data_->init_to_size(size, 0);
memcpy(&(*data_)[0], data, size);
return true;
}
bool TFile::Open(FILE* fp, inT64 end_offset) {
offset_ = 0;
inT64 current_pos = ftell(fp);
if (end_offset < 0) {
if (fseek(fp, 0, SEEK_END))
return false;
end_offset = ftell(fp);
if (fseek(fp, current_pos, SEEK_SET))
return false;
}
int size = end_offset - current_pos;
is_writing_ = false;
if (!data_is_owned_) {
data_ = new GenericVector<char>;
data_is_owned_ = true;
}
data_->init_to_size(size, 0);
return static_cast<int>(fread(&(*data_)[0], 1, size, fp)) == size;
}
char* TFile::FGets(char* buffer, int buffer_size) {
ASSERT_HOST(!is_writing_);
int size = 0;
while (size + 1 < buffer_size && offset_ < data_->size()) {
buffer[size++] = (*data_)[offset_++];
if ((*data_)[offset_ - 1] == '\n') break;
}
if (size < buffer_size) buffer[size] = '\0';
return size > 0 ? buffer : NULL;
}
int TFile::FRead(void* buffer, int size, int count) {
ASSERT_HOST(!is_writing_);
int required_size = size * count;
if (required_size <= 0) return 0;
char* char_buffer = reinterpret_cast<char*>(buffer);
if (data_->size() - offset_ < required_size)
required_size = data_->size() - offset_;
if (required_size > 0)
memcpy(char_buffer, &(*data_)[offset_], required_size);
offset_ += required_size;
return required_size / size;
}
void TFile::Rewind() {
ASSERT_HOST(!is_writing_);
offset_ = 0;
}
void TFile::OpenWrite(GenericVector<char>* data) {
offset_ = 0;
if (data != NULL) {
if (data_is_owned_) delete data_;
data_ = data;
data_is_owned_ = false;
} else if (!data_is_owned_) {
data_ = new GenericVector<char>;
data_is_owned_ = true;
}
is_writing_ = true;
data_->truncate(0);
}
bool TFile::CloseWrite(const STRING& filename, FileWriter writer) {
ASSERT_HOST(is_writing_);
if (writer == NULL)
return SaveDataToFile(*data_, filename);
else
return (*writer)(*data_, filename);
}
int TFile::FWrite(const void* buffer, int size, int count) {
ASSERT_HOST(is_writing_);
int total = size * count;
if (total <= 0) return 0;
const char* buf = reinterpret_cast<const char*>(buffer);
// This isn't very efficient, but memory is so fast compared to disk
// that it is relatively unimportant, and very simple.
for (int i = 0; i < total; ++i)
data_->push_back(buf[i]);
return count;
}
} // namespace tesseract.
| C++ |
/******************************************************************************
** Filename: Host.h
** Purpose: This is the system independent typedefs and defines
** Author: MN, JG, MD
** Version: 5.4.1
** History: 11/7/94 MCD received the modification that Lennart made
** to port to 32 bit world and modify this file so that it
** will be shared between platform.
** 11/9/94 MCD Make MSW32 subset of MSW. Now MSW means
** MicroSoft Window and MSW32 means the 32 bit worlds
** of MicroSoft Window. Therefore you want the environment
** to be MicroSoft Window and in the 32 bit world -
** _WIN32 must be defined by your compiler.
** 11/30/94 MCD Incorporated comments received for more
** readability and the missing typedef for FLOAT.
** 12/1/94 MCD Added PFVOID typedef
** 5/1/95 MCD. Made many changes based on the inputs.
** Changes:
** 1) Rearrange the #ifdef so that there're definitions for
** particular platforms.
** 2) Took out the #define for computer and environment
** that developer can uncomment
** 3) Added __OLDCODE__ where the defines will be
** obsoleted in the next version and advise not to use.
** 4) Added the definitions for the following:
** FILE_HANDLE, MEMORY_HANDLE, BOOL8,
** MAX_INT8, MAX_INT16, MAX_INT32, MAX_UINT8
** MAX_UINT16, MAX_UINT32, MAX_FLOAT32
** 06/19/96 MCD. Took out MAX_FLOAT32
** 07/15/96 MCD. Fixed the comments error
** Add back BOOL8.
**
** (c) Copyright Hewlett-Packard Company, 1988-1996.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*/
#ifndef __HOST__
#define __HOST__
/******************************************************************************
** IMPORTANT!!! **
** **
** Defines either _WIN32, __MAC__, __UNIX__, __OS2__, __PM__ to
** use the specified definitions indicated below in the preprocessor settings. **
** **
** Also define either __FarProc__ or __FarData__ and __MOTO__ to use the
** specified definitions indicated below in the preprocessor settings. **
** **
** If a preprocessor settings is not allow in the compiler that is being use,
** then it is recommended that a "platform.h" is created with the definition
** of the computer and/or operating system.
******************************************************************************/
#include "platform.h"
/* _WIN32 */
#ifdef _WIN32
#include <windows.h>
#include <winbase.h> // winbase.h contains windows.h
#endif
/********************************************************/
/* __MAC__ */
#ifdef __MAC__
#include <Types.h>
/*----------------------------*/
/*----------------------------*/
#endif
/********************************************************/
#if defined(__UNIX__) || defined( __DOS__ ) || defined(__OS2__) || defined(__PM__)
/*----------------------------*/
/* FarProc and FarData */
/*----------------------------*/
/*----------------------------*/
#endif
/*****************************************************************************
**
** Standard GHC Definitions
**
*****************************************************************************/
#ifdef __MOTO__
#define __NATIVE__ MOTO
#else
#define __NATIVE__ INTEL
#endif
//typedef HANDLE FD* PHANDLE;
// definitions of portable data types (numbers and characters)
typedef SIGNED char inT8;
typedef unsigned char uinT8;
typedef short inT16;
typedef unsigned short uinT16;
typedef int inT32;
typedef unsigned int uinT32;
#if (_MSC_VER >= 1200) //%%% vkr for VC 6.0
typedef INT64 inT64;
typedef UINT64 uinT64;
#else
typedef long long int inT64;
typedef unsigned long long int uinT64;
#endif //%%% vkr for VC 6.0
typedef float FLOAT32;
typedef double FLOAT64;
typedef unsigned char BOOL8;
#define INT32FORMAT "%d"
#define INT64FORMAT "%lld"
#define MAX_INT8 0x7f
#define MAX_INT16 0x7fff
#define MAX_INT32 0x7fffffff
#define MAX_UINT8 0xff
#define MAX_UINT16 0xffff
#define MAX_UINT32 0xffffffff
#define MAX_FLOAT32 ((float)3.40282347e+38)
#define MIN_INT8 0x80
#define MIN_INT16 0x8000
#define MIN_INT32 static_cast<int>(0x80000000)
#define MIN_UINT8 0x00
#define MIN_UINT16 0x0000
#define MIN_UINT32 0x00000000
#define MIN_FLOAT32 ((float)1.17549435e-38)
// Defines
#ifndef TRUE
#define TRUE 1
#endif
#ifndef FALSE
#define FALSE 0
#endif
#ifndef NULL
#define NULL 0L
#endif
// Return true if x is within tolerance of y
template<class T> bool NearlyEqual(T x, T y, T tolerance) {
T diff = x - y;
return diff <= tolerance && -diff <= tolerance;
}
#endif
| C++ |
/**********************************************************************
* File: elst2.c (Formerly elist2.c)
* Description: Doubly linked embedded list code not in the include file.
* Author: Phil Cheatle
* Created: Wed Jan 23 11:04:47 GMT 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <stdlib.h>
#include "host.h"
#include "elst2.h"
/***********************************************************************
* MEMBER FUNCTIONS OF CLASS: ELIST2
* =================================
**********************************************************************/
/***********************************************************************
* ELIST2::internal_clear
*
* Used by the destructor and the "clear" member function of derived list
* classes to destroy all the elements on the list.
* The calling function passes a "zapper" function which can be called to
* delete each element of the list, regardless of its derived type. This
* technique permits a generic clear function to destroy elements of
* different derived types correctly, without requiring virtual functions and
* the consequential memory overhead.
**********************************************************************/
void
ELIST2::internal_clear ( //destroy all links
void (*zapper) (ELIST2_LINK *)) {
//ptr to zapper functn
ELIST2_LINK *ptr;
ELIST2_LINK *next;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2::internal_clear", ABORT, NULL);
#endif
if (!empty ()) {
ptr = last->next; //set to first
last->next = NULL; //break circle
last = NULL; //set list empty
while (ptr) {
next = ptr->next;
zapper(ptr);
ptr = next;
}
}
}
/***********************************************************************
* ELIST2::assign_to_sublist
*
* The list is set to a sublist of another list. "This" list must be empty
* before this function is invoked. The two iterators passed must refer to
* the same list, different from "this" one. The sublist removed is the
* inclusive list from start_it's current position to end_it's current
* position. If this range passes over the end of the source list then the
* source list has its end set to the previous element of start_it. The
* extracted sublist is unaffected by the end point of the source list, its
* end point is always the end_it position.
**********************************************************************/
void ELIST2::assign_to_sublist( //to this list
ELIST2_ITERATOR *start_it, //from list start
ELIST2_ITERATOR *end_it) { //from list end
const ERRCODE LIST_NOT_EMPTY =
"Destination list must be empty before extracting a sublist";
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2::assign_to_sublist", ABORT, NULL);
#endif
if (!empty ())
LIST_NOT_EMPTY.error ("ELIST2.assign_to_sublist", ABORT, NULL);
last = start_it->extract_sublist (end_it);
}
/***********************************************************************
* ELIST2::length
*
* Return count of elements on list
**********************************************************************/
inT32 ELIST2::length() const { // count elements
ELIST2_ITERATOR it(const_cast<ELIST2*>(this));
inT32 count = 0;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2::length", ABORT, NULL);
#endif
for (it.mark_cycle_pt (); !it.cycled_list (); it.forward ())
count++;
return count;
}
/***********************************************************************
* ELIST2::sort
*
* Sort elements on list
* NB If you dont like the const declarations in the comparator, coerce yours:
* ( int (*)(const void *, const void *)
**********************************************************************/
void
ELIST2::sort ( //sort elements
int comparator ( //comparison routine
const void *, const void *)) {
ELIST2_ITERATOR it(this);
inT32 count;
ELIST2_LINK **base; //ptr array to sort
ELIST2_LINK **current;
inT32 i;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2::sort", ABORT, NULL);
#endif
/* Allocate an array of pointers, one per list element */
count = length ();
base = (ELIST2_LINK **) malloc (count * sizeof (ELIST2_LINK *));
/* Extract all elements, putting the pointers in the array */
current = base;
for (it.mark_cycle_pt (); !it.cycled_list (); it.forward ()) {
*current = it.extract ();
current++;
}
/* Sort the pointer array */
qsort ((char *) base, count, sizeof (*base), comparator);
/* Rebuild the list from the sorted pointers */
current = base;
for (i = 0; i < count; i++) {
it.add_to_end (*current);
current++;
}
free(base);
}
// Assuming list has been sorted already, insert new_link to
// keep the list sorted according to the same comparison function.
// Comparision function is the same as used by sort, i.e. uses double
// indirection. Time is O(1) to add to beginning or end.
// Time is linear to add pre-sorted items to an empty list.
void ELIST2::add_sorted(int comparator(const void*, const void*),
ELIST2_LINK* new_link) {
// Check for adding at the end.
if (last == NULL || comparator(&last, &new_link) < 0) {
if (last == NULL) {
new_link->next = new_link;
new_link->prev = new_link;
} else {
new_link->next = last->next;
new_link->prev = last;
last->next = new_link;
new_link->next->prev = new_link;
}
last = new_link;
} else {
// Need to use an iterator.
ELIST2_ITERATOR it(this);
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward()) {
ELIST2_LINK* link = it.data();
if (comparator(&link, &new_link) > 0)
break;
}
if (it.cycled_list())
it.add_to_end(new_link);
else
it.add_before_then_move(new_link);
}
}
/***********************************************************************
* MEMBER FUNCTIONS OF CLASS: ELIST2_ITERATOR
* ==========================================
**********************************************************************/
/***********************************************************************
* ELIST2_ITERATOR::forward
*
* Move the iterator to the next element of the list.
* REMEMBER: ALL LISTS ARE CIRCULAR.
**********************************************************************/
ELIST2_LINK *ELIST2_ITERATOR::forward() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2_ITERATOR::forward", ABORT, NULL);
if (!list)
NO_LIST.error ("ELIST2_ITERATOR::forward", ABORT, NULL);
#endif
if (list->empty ())
return NULL;
if (current) { //not removed so
//set previous
prev = current;
started_cycling = TRUE;
// In case next is deleted by another iterator, get it from the current.
current = current->next;
}
else {
if (ex_current_was_cycle_pt)
cycle_pt = next;
current = next;
}
next = current->next;
#ifndef NDEBUG
if (!current)
NULL_DATA.error ("ELIST2_ITERATOR::forward", ABORT, NULL);
if (!next)
NULL_NEXT.error ("ELIST2_ITERATOR::forward", ABORT,
"This is: %p Current is: %p", this, current);
#endif
return current;
}
/***********************************************************************
* ELIST2_ITERATOR::backward
*
* Move the iterator to the previous element of the list.
* REMEMBER: ALL LISTS ARE CIRCULAR.
**********************************************************************/
ELIST2_LINK *ELIST2_ITERATOR::backward() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2_ITERATOR::backward", ABORT, NULL);
if (!list)
NO_LIST.error ("ELIST2_ITERATOR::backward", ABORT, NULL);
#endif
if (list->empty ())
return NULL;
if (current) { //not removed so
//set previous
next = current;
started_cycling = TRUE;
// In case prev is deleted by another iterator, get it from current.
current = current->prev;
} else {
if (ex_current_was_cycle_pt)
cycle_pt = prev;
current = prev;
}
prev = current->prev;
#ifndef NDEBUG
if (!current)
NULL_DATA.error ("ELIST2_ITERATOR::backward", ABORT, NULL);
if (!prev)
NULL_PREV.error ("ELIST2_ITERATOR::backward", ABORT,
"This is: %p Current is: %p", this, current);
#endif
return current;
}
/***********************************************************************
* ELIST2_ITERATOR::data_relative
*
* Return the data pointer to the element "offset" elements from current.
* (This function can't be INLINEd because it contains a loop)
**********************************************************************/
ELIST2_LINK *ELIST2_ITERATOR::data_relative( //get data + or - ..
inT8 offset) { //offset from current
ELIST2_LINK *ptr;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2_ITERATOR::data_relative", ABORT, NULL);
if (!list)
NO_LIST.error ("ELIST2_ITERATOR::data_relative", ABORT, NULL);
if (list->empty ())
EMPTY_LIST.error ("ELIST2_ITERATOR::data_relative", ABORT, NULL);
#endif
if (offset < 0)
for (ptr = current ? current : next; offset++ < 0; ptr = ptr->prev);
else
for (ptr = current ? current : prev; offset-- > 0; ptr = ptr->next);
#ifndef NDEBUG
if (!ptr)
NULL_DATA.error ("ELIST2_ITERATOR::data_relative", ABORT, NULL);
#endif
return ptr;
}
/***********************************************************************
* ELIST2_ITERATOR::exchange()
*
* Given another iterator, whose current element is a different element on
* the same list list OR an element of another list, exchange the two current
* elements. On return, each iterator points to the element which was the
* other iterators current on entry.
* (This function hasn't been in-lined because its a bit big!)
**********************************************************************/
void ELIST2_ITERATOR::exchange( //positions of 2 links
ELIST2_ITERATOR *other_it) { //other iterator
const ERRCODE DONT_EXCHANGE_DELETED =
"Can't exchange deleted elements of lists";
ELIST2_LINK *old_current;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2_ITERATOR::exchange", ABORT, NULL);
if (!list)
NO_LIST.error ("ELIST2_ITERATOR::exchange", ABORT, NULL);
if (!other_it)
BAD_PARAMETER.error ("ELIST2_ITERATOR::exchange", ABORT, "other_it NULL");
if (!(other_it->list))
NO_LIST.error ("ELIST2_ITERATOR::exchange", ABORT, "other_it");
#endif
/* Do nothing if either list is empty or if both iterators reference the same
link */
if ((list->empty ()) ||
(other_it->list->empty ()) || (current == other_it->current))
return;
/* Error if either current element is deleted */
if (!current || !other_it->current)
DONT_EXCHANGE_DELETED.error ("ELIST2_ITERATOR.exchange", ABORT, NULL);
/* Now handle the 4 cases: doubleton list; non-doubleton adjacent elements
(other before this); non-doubleton adjacent elements (this before other);
non-adjacent elements. */
//adjacent links
if ((next == other_it->current) ||
(other_it->next == current)) {
//doubleton list
if ((next == other_it->current) &&
(other_it->next == current)) {
prev = next = current;
other_it->prev = other_it->next = other_it->current;
}
else { //non-doubleton with
//adjacent links
//other before this
if (other_it->next == current) {
other_it->prev->next = current;
other_it->current->next = next;
other_it->current->prev = current;
current->next = other_it->current;
current->prev = other_it->prev;
next->prev = other_it->current;
other_it->next = other_it->current;
prev = current;
}
else { //this before other
prev->next = other_it->current;
current->next = other_it->next;
current->prev = other_it->current;
other_it->current->next = current;
other_it->current->prev = prev;
other_it->next->prev = current;
next = current;
other_it->prev = other_it->current;
}
}
}
else { //no overlap
prev->next = other_it->current;
current->next = other_it->next;
current->prev = other_it->prev;
next->prev = other_it->current;
other_it->prev->next = current;
other_it->current->next = next;
other_it->current->prev = prev;
other_it->next->prev = current;
}
/* update end of list pointer when necessary (remember that the 2 iterators
may iterate over different lists!) */
if (list->last == current)
list->last = other_it->current;
if (other_it->list->last == other_it->current)
other_it->list->last = current;
if (current == cycle_pt)
cycle_pt = other_it->cycle_pt;
if (other_it->current == other_it->cycle_pt)
other_it->cycle_pt = cycle_pt;
/* The actual exchange - in all cases*/
old_current = current;
current = other_it->current;
other_it->current = old_current;
}
/***********************************************************************
* ELIST2_ITERATOR::extract_sublist()
*
* This is a private member, used only by ELIST2::assign_to_sublist.
* Given another iterator for the same list, extract the links from THIS to
* OTHER inclusive, link them into a new circular list, and return a
* pointer to the last element.
* (Can't inline this function because it contains a loop)
**********************************************************************/
ELIST2_LINK *ELIST2_ITERATOR::extract_sublist( //from this current
ELIST2_ITERATOR *other_it) { //to other current
#ifndef NDEBUG
const ERRCODE BAD_EXTRACTION_PTS =
"Can't extract sublist from points on different lists";
const ERRCODE DONT_EXTRACT_DELETED =
"Can't extract a sublist marked by deleted points";
#endif
const ERRCODE BAD_SUBLIST = "Can't find sublist end point in original list";
ELIST2_ITERATOR temp_it = *this;
ELIST2_LINK *end_of_new_list;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("ELIST2_ITERATOR::extract_sublist", ABORT, NULL);
if (!other_it)
BAD_PARAMETER.error ("ELIST2_ITERATOR::extract_sublist", ABORT,
"other_it NULL");
if (!list)
NO_LIST.error ("ELIST2_ITERATOR::extract_sublist", ABORT, NULL);
if (list != other_it->list)
BAD_EXTRACTION_PTS.error ("ELIST2_ITERATOR.extract_sublist", ABORT, NULL);
if (list->empty ())
EMPTY_LIST.error ("ELIST2_ITERATOR::extract_sublist", ABORT, NULL);
if (!current || !other_it->current)
DONT_EXTRACT_DELETED.error ("ELIST2_ITERATOR.extract_sublist", ABORT,
NULL);
#endif
ex_current_was_last = other_it->ex_current_was_last = FALSE;
ex_current_was_cycle_pt = FALSE;
other_it->ex_current_was_cycle_pt = FALSE;
temp_it.mark_cycle_pt ();
do { //walk sublist
if (temp_it.cycled_list ()) //cant find end pt
BAD_SUBLIST.error ("ELIST2_ITERATOR.extract_sublist", ABORT, NULL);
if (temp_it.at_last ()) {
list->last = prev;
ex_current_was_last = other_it->ex_current_was_last = TRUE;
}
if (temp_it.current == cycle_pt)
ex_current_was_cycle_pt = TRUE;
if (temp_it.current == other_it->cycle_pt)
other_it->ex_current_was_cycle_pt = TRUE;
temp_it.forward ();
}
//do INCLUSIVE list
while (temp_it.prev != other_it->current);
//circularise sublist
other_it->current->next = current;
//circularise sublist
current->prev = other_it->current;
end_of_new_list = other_it->current;
//sublist = whole list
if (prev == other_it->current) {
list->last = NULL;
prev = current = next = NULL;
other_it->prev = other_it->current = other_it->next = NULL;
}
else {
prev->next = other_it->next;
other_it->next->prev = prev;
current = other_it->current = NULL;
next = other_it->next;
other_it->prev = prev;
}
return end_of_new_list;
}
| C++ |
// Copyright 2012 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: genericheap.h
// Description: Template heap class.
// Author: Ray Smith, based on Dan Johnson's original code.
// Created: Wed Mar 14 08:13:00 PDT 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "errcode.h"
#include "genericvector.h"
#ifndef TESSERACT_CCUTIL_GENERICHEAP_H_
#define TESSERACT_CCUTIL_GENERICHEAP_H_
namespace tesseract {
// GenericHeap requires 1 template argument:
// Pair will normally be either KDPairInc<Key, Data> or KDPairDec<Key, Data>
// for some arbitrary Key and scalar, smart pointer, or non-ownership pointer
// Data type, according to whether a MIN heap or a MAX heap is desired,
// respectively. Using KDPtrPairInc<Key, Data> or KDPtrPairDec<Key, Data>,
// GenericHeap can also handle simple Data pointers and own them.
// If no additional data is required, Pair can also be a scalar, since
// GenericHeap doesn't look inside it except for operator<.
//
// The heap is stored as a packed binary tree in an array hosted by a
// GenericVector<Pair>, with the invariant that the children of each node are
// both NOT Pair::operator< the parent node. KDPairInc defines Pair::operator<
// to use Key::operator< to generate a MIN heap and KDPairDec defines
// Pair::operator< to use Key::operator> to generate a MAX heap by reversing
// all the comparisons.
// See http://en.wikipedia.org/wiki/Heap_(data_structure) for more detail on
// the basic heap implementation.
//
// Insertion and removal are both O(log n) and, unlike the STL heap, an
// explicit Reshuffle function allows a node to be repositioned in time O(log n)
// after changing its value.
//
// Accessing the element for revaluation is a more complex matter, since the
// index and pointer can be changed arbitrarily by heap operations.
// Revaluation can be done by making the Data type in the Pair derived from or
// contain a DoublePtr as its first data element, making it possible to convert
// the pointer to a Pair using KDPairInc::RecastDataPointer.
template <typename Pair>
class GenericHeap {
public:
GenericHeap() {}
// The initial size is only a GenericVector::reserve. It is not enforced as
// the size limit of the heap. Caller must implement their own enforcement.
explicit GenericHeap(int initial_size) {
heap_.reserve(initial_size);
}
// Simple accessors.
bool empty() const {
return heap_.empty();
}
int size() const {
return heap_.size();
}
int size_reserved() const {
return heap_.size_reserved();
}
void clear() {
// Clear truncates to 0 to keep the number reserved in tact.
heap_.truncate(0);
}
// Provides access to the underlying vector.
// Caution! any changes that modify the keys will invalidate the heap!
GenericVector<Pair>* heap() {
return &heap_;
}
// Provides read-only access to an element of the underlying vector.
const Pair& get(int index) const {
return heap_[index];
}
// Add entry to the heap, keeping the smallest item at the top, by operator<.
// Note that *entry is used as the source of operator=, but it is non-const
// to allow for a smart pointer to be contained within.
// Time = O(log n).
void Push(Pair* entry) {
int hole_index = heap_.size();
// Make a hole in the end of heap_ and sift it up to be the correct
// location for the new *entry. To avoid needing a default constructor
// for primitive types, and to allow for use of DoublePtr in the Pair
// somewhere, we have to incur a double copy here.
heap_.push_back(*entry);
*entry = heap_.back();
hole_index = SiftUp(hole_index, *entry);
heap_[hole_index] = *entry;
}
// Get the value of the top (smallest, defined by operator< ) element.
const Pair& PeekTop() const {
return heap_[0];
}
// Removes the top element of the heap. If entry is not NULL, the element
// is copied into *entry, otherwise it is discarded.
// Returns false if the heap was already empty.
// Time = O(log n).
bool Pop(Pair* entry) {
int new_size = heap_.size() - 1;
if (new_size < 0)
return false; // Already empty.
if (entry != NULL)
*entry = heap_[0];
if (new_size > 0) {
// Sift the hole at the start of the heap_ downwards to match the last
// element.
Pair hole_pair = heap_[new_size];
heap_.truncate(new_size);
int hole_index = SiftDown(0, hole_pair);
heap_[hole_index] = hole_pair;
} else {
heap_.truncate(new_size);
}
return true;
}
// Removes the MAXIMUM element of the heap. (MIN from a MAX heap.) If entry is
// not NULL, the element is copied into *entry, otherwise it is discarded.
// Time = O(n). Returns false if the heap was already empty.
bool PopWorst(Pair* entry) {
int heap_size = heap_.size();
if (heap_size == 0) return false; // It cannot be empty!
// Find the maximum element. Its index is guaranteed to be greater than
// the index of the parent of the last element, since by the heap invariant
// the parent must be less than or equal to the children.
int worst_index = heap_size - 1;
int end_parent = ParentNode(worst_index);
for (int i = worst_index - 1; i > end_parent; --i) {
if (heap_[worst_index] < heap_[i])
worst_index = i;
}
// Extract the worst element from the heap, leaving a hole at worst_index.
if (entry != NULL)
*entry = heap_[worst_index];
--heap_size;
if (heap_size > 0) {
// Sift the hole upwards to match the last element of the heap_
Pair hole_pair = heap_[heap_size];
int hole_index = SiftUp(worst_index, hole_pair);
heap_[hole_index] = hole_pair;
}
heap_.truncate(heap_size);
return true;
}
// The pointed-to Pair has changed its key value, so the location of pair
// is reshuffled to maintain the heap invariant.
// Must be a valid pointer to an element of the heap_!
// Caution! Since GenericHeap is based on GenericVector, reallocs may occur
// whenever the vector is extended and elements may get shuffled by any
// Push or Pop operation. Therefore use this function only if Data in Pair is
// of type DoublePtr, derived (first) from DoublePtr, or has a DoublePtr as
// its first element. Reshuffles the heap to maintain the invariant.
// Time = O(log n).
void Reshuffle(Pair* pair) {
int index = pair - &heap_[0];
Pair hole_pair = heap_[index];
index = SiftDown(index, hole_pair);
index = SiftUp(index, hole_pair);
heap_[index] = hole_pair;
}
private:
// A hole in the heap exists at hole_index, and we want to fill it with the
// given pair. SiftUp sifts the hole upward to the correct position and
// returns the destination index without actually putting pair there.
int SiftUp(int hole_index, const Pair& pair) {
int parent;
while (hole_index > 0 && pair < heap_[parent = ParentNode(hole_index)]) {
heap_[hole_index] = heap_[parent];
hole_index = parent;
}
return hole_index;
}
// A hole in the heap exists at hole_index, and we want to fill it with the
// given pair. SiftDown sifts the hole downward to the correct position and
// returns the destination index without actually putting pair there.
int SiftDown(int hole_index, const Pair& pair) {
int heap_size = heap_.size();
int child;
while ((child = LeftChild(hole_index)) < heap_size) {
if (child + 1 < heap_size && heap_[child + 1] < heap_[child])
++child;
if (heap_[child] < pair) {
heap_[hole_index] = heap_[child];
hole_index = child;
} else {
break;
}
}
return hole_index;
}
// Functions to navigate the tree. Unlike the original implementation, we
// store the root at index 0.
int ParentNode(int index) const {
return (index + 1) / 2 - 1;
}
int LeftChild(int index) const {
return index * 2 + 1;
}
private:
GenericVector<Pair> heap_;
};
} // namespace tesseract
#endif // TESSERACT_CCUTIL_GENERICHEAP_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: tessdatamanager.cpp
// Description: Functions to handle loading/combining tesseract data files.
// Author: Daria Antonova
// Created: Wed Jun 03 11:26:43 PST 2009
//
// (C) Copyright 2009, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
#include "tessdatamanager.h"
#include <stdio.h>
#include "helpers.h"
#include "serialis.h"
#include "strngs.h"
#include "tprintf.h"
#include "params.h"
namespace tesseract {
bool TessdataManager::Init(const char *data_file_name, int debug_level) {
int i;
debug_level_ = debug_level;
data_file_name_ = data_file_name;
data_file_ = fopen(data_file_name, "rb");
if (data_file_ == NULL) {
tprintf("Error opening data file %s\n", data_file_name);
tprintf("Please make sure the TESSDATA_PREFIX environment variable is set "
"to the parent directory of your \"tessdata\" directory.\n");
return false;
}
fread(&actual_tessdata_num_entries_, sizeof(inT32), 1, data_file_);
swap_ = (actual_tessdata_num_entries_ > kMaxNumTessdataEntries);
if (swap_) {
ReverseN(&actual_tessdata_num_entries_,
sizeof(actual_tessdata_num_entries_));
}
ASSERT_HOST(actual_tessdata_num_entries_ <= TESSDATA_NUM_ENTRIES);
fread(offset_table_, sizeof(inT64),
actual_tessdata_num_entries_, data_file_);
if (swap_) {
for (i = 0 ; i < actual_tessdata_num_entries_; ++i) {
ReverseN(&offset_table_[i], sizeof(offset_table_[i]));
}
}
if (debug_level_) {
tprintf("TessdataManager loaded %d types of tesseract data files.\n",
actual_tessdata_num_entries_);
for (i = 0; i < actual_tessdata_num_entries_; ++i) {
tprintf("Offset for type %d is %lld\n", i, offset_table_[i]);
}
}
return true;
}
void TessdataManager::CopyFile(FILE *input_file, FILE *output_file,
bool newline_end, inT64 num_bytes_to_copy) {
if (num_bytes_to_copy == 0) return;
int buffer_size = 1024;
if (num_bytes_to_copy > 0 && buffer_size > num_bytes_to_copy) {
buffer_size = num_bytes_to_copy;
}
inT64 num_bytes_copied = 0;
char *chunk = new char[buffer_size];
int bytes_read;
char last_char = 0x0;
while ((bytes_read = fread(chunk, sizeof(char),
buffer_size, input_file))) {
fwrite(chunk, sizeof(char), bytes_read, output_file);
last_char = chunk[bytes_read-1];
if (num_bytes_to_copy > 0) {
num_bytes_copied += bytes_read;
if (num_bytes_copied == num_bytes_to_copy) break;
if (num_bytes_copied + buffer_size > num_bytes_to_copy) {
buffer_size = num_bytes_to_copy - num_bytes_copied;
}
}
}
if (newline_end) ASSERT_HOST(last_char == '\n');
delete[] chunk;
}
bool TessdataManager::WriteMetadata(inT64 *offset_table,
const char * language_data_path_prefix,
FILE *output_file) {
inT32 num_entries = TESSDATA_NUM_ENTRIES;
bool result = true;
if (fseek(output_file, 0, SEEK_SET) != 0 ||
fwrite(&num_entries, sizeof(inT32), 1, output_file) != 1 ||
fwrite(offset_table, sizeof(inT64), TESSDATA_NUM_ENTRIES,
output_file) != TESSDATA_NUM_ENTRIES) {
fclose(output_file);
result = false;
tprintf("WriteMetadata failed in TessdataManager!\n");
} else if (fclose(output_file)) {
result = false;
tprintf("WriteMetadata failed to close file!\n");
} else {
tprintf("TessdataManager combined tesseract data files.\n");
for (int i = 0; i < TESSDATA_NUM_ENTRIES; ++i) {
tprintf("Offset for type %2d (%s%-22s) is %lld\n", i,
language_data_path_prefix, kTessdataFileSuffixes[i],
offset_table[i]);
}
}
return result;
}
bool TessdataManager::CombineDataFiles(
const char *language_data_path_prefix,
const char *output_filename) {
int i;
inT64 offset_table[TESSDATA_NUM_ENTRIES];
for (i = 0; i < TESSDATA_NUM_ENTRIES; ++i) offset_table[i] = -1;
FILE *output_file = fopen(output_filename, "wb");
if (output_file == NULL) {
tprintf("Error opening %s for writing\n", output_filename);
return false;
}
// Leave some space for recording the offset_table.
if (fseek(output_file,
sizeof(inT32) + sizeof(inT64) * TESSDATA_NUM_ENTRIES, SEEK_SET)) {
tprintf("Error seeking %s\n", output_filename);
return false;
}
TessdataType type = TESSDATA_NUM_ENTRIES;
bool text_file = false;
FILE *file_ptr[TESSDATA_NUM_ENTRIES];
// Load individual tessdata components from files.
for (i = 0; i < TESSDATA_NUM_ENTRIES; ++i) {
ASSERT_HOST(TessdataTypeFromFileSuffix(
kTessdataFileSuffixes[i], &type, &text_file));
STRING filename = language_data_path_prefix;
filename += kTessdataFileSuffixes[i];
file_ptr[i] = fopen(filename.string(), "rb");
if (file_ptr[i] != NULL) {
offset_table[type] = ftell(output_file);
CopyFile(file_ptr[i], output_file, text_file, -1);
fclose(file_ptr[i]);
}
}
// Make sure that the required components are present.
if (file_ptr[TESSDATA_UNICHARSET] == NULL) {
tprintf("Error opening %sunicharset file\n", language_data_path_prefix);
fclose(output_file);
return false;
}
if (file_ptr[TESSDATA_INTTEMP] != NULL &&
(file_ptr[TESSDATA_PFFMTABLE] == NULL ||
file_ptr[TESSDATA_NORMPROTO] == NULL)) {
tprintf("Error opening %spffmtable and/or %snormproto files"
" while %sinttemp file was present\n", language_data_path_prefix,
language_data_path_prefix, language_data_path_prefix);
fclose(output_file);
return false;
}
return WriteMetadata(offset_table, language_data_path_prefix, output_file);
}
bool TessdataManager::OverwriteComponents(
const char *new_traineddata_filename,
char **component_filenames,
int num_new_components) {
int i;
inT64 offset_table[TESSDATA_NUM_ENTRIES];
TessdataType type = TESSDATA_NUM_ENTRIES;
bool text_file = false;
FILE *file_ptr[TESSDATA_NUM_ENTRIES];
for (i = 0; i < TESSDATA_NUM_ENTRIES; ++i) {
offset_table[i] = -1;
file_ptr[i] = NULL;
}
FILE *output_file = fopen(new_traineddata_filename, "wb");
if (output_file == NULL) {
tprintf("Error opening %s for writing\n", new_traineddata_filename);
return false;
}
// Leave some space for recording the offset_table.
if (fseek(output_file,
sizeof(inT32) + sizeof(inT64) * TESSDATA_NUM_ENTRIES, SEEK_SET)) {
fclose(output_file);
tprintf("Error seeking %s\n", new_traineddata_filename);
return false;
}
// Open the files with the new components.
for (i = 0; i < num_new_components; ++i) {
if (TessdataTypeFromFileName(component_filenames[i], &type, &text_file))
file_ptr[type] = fopen(component_filenames[i], "rb");
}
// Write updated data to the output traineddata file.
for (i = 0; i < TESSDATA_NUM_ENTRIES; ++i) {
if (file_ptr[i] != NULL) {
// Get the data from the opened component file.
offset_table[i] = ftell(output_file);
CopyFile(file_ptr[i], output_file, kTessdataFileIsText[i], -1);
fclose(file_ptr[i]);
} else {
// Get this data component from the loaded data file.
if (SeekToStart(static_cast<TessdataType>(i))) {
offset_table[i] = ftell(output_file);
CopyFile(data_file_, output_file, kTessdataFileIsText[i],
GetEndOffset(static_cast<TessdataType>(i)) -
ftell(data_file_) + 1);
}
}
}
const char *language_data_path_prefix = strchr(new_traineddata_filename, '.');
return WriteMetadata(offset_table, language_data_path_prefix, output_file);
}
bool TessdataManager::TessdataTypeFromFileSuffix(
const char *suffix, TessdataType *type, bool *text_file) {
for (int i = 0; i < TESSDATA_NUM_ENTRIES; ++i) {
if (strcmp(kTessdataFileSuffixes[i], suffix) == 0) {
*type = static_cast<TessdataType>(i);
*text_file = kTessdataFileIsText[i];
return true;
}
}
tprintf("TessdataManager can't determine which tessdata"
" component is represented by %s\n", suffix);
return false;
}
bool TessdataManager::TessdataTypeFromFileName(
const char *filename, TessdataType *type, bool *text_file) {
// Get the file suffix (extension)
const char *suffix = strrchr(filename, '.');
if (suffix == NULL || *(++suffix) == '\0') return false;
return TessdataTypeFromFileSuffix(suffix, type, text_file);
}
bool TessdataManager::ExtractToFile(const char *filename) {
TessdataType type = TESSDATA_NUM_ENTRIES;
bool text_file = false;
ASSERT_HOST(tesseract::TessdataManager::TessdataTypeFromFileName(
filename, &type, &text_file));
if (!SeekToStart(type)) return false;
FILE *output_file = fopen(filename, "wb");
if (output_file == NULL) {
tprintf("Error opening %s\n", filename);
exit(1);
}
inT64 begin_offset = ftell(GetDataFilePtr());
inT64 end_offset = GetEndOffset(type);
tesseract::TessdataManager::CopyFile(
GetDataFilePtr(), output_file, text_file,
end_offset - begin_offset + 1);
fclose(output_file);
return true;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: basedir.c (Formerly getpath.c)
* Description: Find the directory location of the current executable using PATH.
* Author: Ray Smith
* Created: Mon Jul 09 09:06:39 BST 1990
*
* (C) Copyright 1990, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "basedir.h"
#include <stdlib.h>
// Assuming that code_path is the name of some file in a desired directory,
// returns the given code_path stripped back to the last slash, leaving
// the last slash in place. If there is no slash, returns ./ assuming that
// the input was the name of something in the current directory.
// Useful for getting to the directory of argv[0], but does not search
// any paths.
TESS_API void truncate_path(const char *code_path, STRING* trunc_path) {
int trunc_index = -1;
if (code_path != NULL) {
const char* last_slash = strrchr(code_path, '/');
if (last_slash != NULL && last_slash + 1 - code_path > trunc_index)
trunc_index = last_slash + 1 - code_path;
last_slash = strrchr(code_path, '\\');
if (last_slash != NULL && last_slash + 1 - code_path > trunc_index)
trunc_index = last_slash + 1 - code_path;
}
*trunc_path = code_path;
if (trunc_index >= 0)
trunc_path->truncate_at(trunc_index);
else
*trunc_path = "./";
}
| C++ |
/**********************************************************************
* File: errcode.h (Formerly error.h)
* Description: Header file for generic error handler class
* Author: Ray Smith
* Created: Tue May 1 16:23:36 BST 1990
*
* (C) Copyright 1990, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef ERRCODE_H
#define ERRCODE_H
#include "host.h"
/*Control parameters for error()*/
enum TessErrorLogCode {
DBG = -1, /*log without alert */
TESSLOG = 0, /*alert user */
TESSEXIT = 1, /*exit after erro */
ABORT = 2 /*abort after error */
};
/* Explicit Error Abort codes */
#define NO_ABORT_CODE 0
#define LIST_ABORT 1
#define MEMORY_ABORT 2
#define FILE_ABORT 3
/* Location of code at error codes Reserve 0..2 (status codes 0..23 for UNLV)*/
#define LOC_UNUSED0 0
#define LOC_UNUSED1 1
#define LOC_UNUSED2 2
#define LOC_INIT 3
#define LOC_EDGE_PROG 4
#define LOC_TEXT_ORD_ROWS 5
#define LOC_TEXT_ORD_WORDS 6
#define LOC_PASS1 7
#define LOC_PASS2 8
/* Reserve up to 8..13 for adding subloc 0/3 plus subsubloc 0/1/2 */
#define LOC_FUZZY_SPACE 14
/* Reserve up to 14..20 for adding subloc 0/3 plus subsubloc 0/1/2 */
#define LOC_MM_ADAPT 21
#define LOC_DOC_BLK_REJ 22
#define LOC_WRITE_RESULTS 23
#define LOC_ADAPTIVE 24
/* DONT DEFINE ANY LOCATION > 31 !!! */
/* Sub locatation determines whether pass2 was in normal mode or fix xht mode*/
#define SUBLOC_NORM 0
#define SUBLOC_FIX_XHT 3
/* Sub Sub locatation determines whether match_word_pass2 was in Tess
matcher, NN matcher or somewhere else */
#define SUBSUBLOC_OTHER 0
#define SUBSUBLOC_TESS 1
#define SUBSUBLOC_NN 2
class TESS_API ERRCODE { // error handler class
const char *message; // error message
public:
void error( // error print function
const char *caller, // function location
TessErrorLogCode action, // action to take
const char *format, ... // fprintf format
) const;
ERRCODE(const char *string) {
message = string;
} // initialize with string
};
const ERRCODE ASSERT_FAILED = "Assert failed";
#define ASSERT_HOST(x) if (!(x)) \
{ \
ASSERT_FAILED.error(#x, ABORT, "in file %s, line %d", \
__FILE__, __LINE__); \
}
#ifdef _MSC_VER
#define ASSERT_HOST_MSG(x, msg, ...) if (!(x)) \
{ \
tprintf(msg); \
ASSERT_FAILED.error(#x, ABORT, "in file %s, line %d", \
__FILE__, __LINE__); \
}
#else
#define ASSERT_HOST_MSG(x, msg...) if (!(x)) \
{ \
tprintf(msg); \
ASSERT_FAILED.error(#x, ABORT, "in file %s, line %d", \
__FILE__, __LINE__); \
}
#endif
void signal_exit(int signal_code);
void set_global_loc_code(int loc_code);
void set_global_subloc_code(int loc_code);
void set_global_subsubloc_code(int loc_code);
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: universalambigs.h
// Description: Data for a universal ambigs file that is useful for
// any language.
// Author: Ray Smith
// Created: Mon Mar 18 11:26:00 PDT 2013
//
// (C) Copyright 2013, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
namespace tesseract {
extern const char kUniversalAmbigsFile[];
extern const int ksizeofUniversalAmbigsFile;
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: unicharmap.cpp
// Description: Unicode character/ligature to integer id class.
// Author: Thomas Kielbus
// Created: Wed Jun 28 17:05:01 PDT 2006
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include <assert.h>
#include "unichar.h"
#include "host.h"
#include "unicharmap.h"
UNICHARMAP::UNICHARMAP() :
nodes(0) {
}
UNICHARMAP::~UNICHARMAP() {
if (nodes != 0)
delete[] nodes;
}
// Search the given unichar representation in the tree. Each character in the
// string is interpreted as an index in an array of nodes.
UNICHAR_ID UNICHARMAP::unichar_to_id(const char* const unichar_repr) const {
const char* current_char = unichar_repr;
UNICHARMAP_NODE* current_nodes = nodes;
assert(*unichar_repr != '\0');
do {
if (*(current_char + 1) == '\0')
return current_nodes[static_cast<unsigned char>(*current_char)].id;
current_nodes =
current_nodes[static_cast<unsigned char>(*current_char)].children;
++current_char;
} while (true);
}
// Search the given unichar representation in the tree, using length characters
// from it maximum. Each character in the string is interpreted as an index in
// an array of nodes.
UNICHAR_ID UNICHARMAP::unichar_to_id(const char* const unichar_repr,
int length) const {
const char* current_char = unichar_repr;
UNICHARMAP_NODE* current_nodes = nodes;
assert(*unichar_repr != '\0');
assert(length > 0 && length <= UNICHAR_LEN);
do {
if (length == 1 || *(current_char + 1) == '\0')
return current_nodes[static_cast<unsigned char>(*current_char)].id;
current_nodes =
current_nodes[static_cast<unsigned char>(*current_char)].children;
++current_char;
--length;
} while (true);
}
// Search the given unichar representation in the tree, creating the possibly
// missing nodes. Once the right place has been found, insert the given id and
// update the inserted flag to keep track of the insert. Each character in the
// string is interpreted as an index in an array of nodes.
void UNICHARMAP::insert(const char* const unichar_repr, UNICHAR_ID id) {
const char* current_char = unichar_repr;
UNICHARMAP_NODE** current_nodes_pointer = &nodes;
assert(*unichar_repr != '\0');
assert(id >= 0);
do {
if (*current_nodes_pointer == 0)
*current_nodes_pointer = new UNICHARMAP_NODE[256];
if (*(current_char + 1) == '\0') {
(*current_nodes_pointer)
[static_cast<unsigned char>(*current_char)].id = id;
return;
}
current_nodes_pointer =
&((*current_nodes_pointer)
[static_cast<unsigned char>(*current_char)].children);
++current_char;
} while (true);
}
// Search the given unichar representation in the tree. Each character in the
// string is interpreted as an index in an array of nodes. Stop once the tree
// does not have anymore nodes or once we found the right unichar_repr.
bool UNICHARMAP::contains(const char* const unichar_repr) const {
if (unichar_repr == NULL || *unichar_repr == '\0') return false;
const char* current_char = unichar_repr;
UNICHARMAP_NODE* current_nodes = nodes;
while (current_nodes != 0 && *(current_char + 1) != '\0') {
current_nodes =
current_nodes[static_cast<unsigned char>(*current_char)].children;
++current_char;
}
return current_nodes != 0 && *(current_char + 1) == '\0' &&
current_nodes[static_cast<unsigned char>(*current_char)].id >= 0;
}
// Search the given unichar representation in the tree, using length characters
// from it maximum. Each character in the string is interpreted as an index in
// an array of nodes. Stop once the tree does not have anymore nodes or once we
// found the right unichar_repr.
bool UNICHARMAP::contains(const char* const unichar_repr,
int length) const {
if (unichar_repr == NULL || *unichar_repr == '\0') return false;
if (length <= 0 || length > UNICHAR_LEN) return false;
const char* current_char = unichar_repr;
UNICHARMAP_NODE* current_nodes = nodes;
while (current_nodes != 0 && (length > 1 && *(current_char + 1) != '\0')) {
current_nodes =
current_nodes[static_cast<unsigned char>(*current_char)].children;
--length;
++current_char;
}
return current_nodes != 0 && (length == 1 || *(current_char + 1) == '\0') &&
current_nodes[static_cast<unsigned char>(*current_char)].id >= 0;
}
// Return the minimum number of characters that must be used from this string
// to obtain a match in the UNICHARMAP.
int UNICHARMAP::minmatch(const char* const unichar_repr) const {
const char* current_char = unichar_repr;
UNICHARMAP_NODE* current_nodes = nodes;
while (current_nodes != NULL && *current_char != '\0') {
if (current_nodes[static_cast<unsigned char>(*current_char)].id >= 0)
return current_char + 1 - unichar_repr;
current_nodes =
current_nodes[static_cast<unsigned char>(*current_char)].children;
++current_char;
}
return 0;
}
void UNICHARMAP::clear() {
if (nodes != 0)
{
delete[] nodes;
nodes = 0;
}
}
UNICHARMAP::UNICHARMAP_NODE::UNICHARMAP_NODE() :
children(0),
id(-1) {
}
// Recursively delete the children
UNICHARMAP::UNICHARMAP_NODE::~UNICHARMAP_NODE() {
if (children != 0) {
delete[] children;
}
}
| C++ |
/**********************************************************************
* File: clst.c (Formerly clist.c)
* Description: CONS cell list handling code which is not in the include file.
* Author: Phil Cheatle
* Created: Mon Jan 28 08:33:13 GMT 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <stdlib.h>
#include "clst.h"
/***********************************************************************
* MEMBER FUNCTIONS OF CLASS: CLIST
* ================================
**********************************************************************/
/***********************************************************************
* CLIST::internal_deep_clear
*
* Used by the "deep_clear" member function of derived list
* classes to destroy all the elements on the list.
* The calling function passes a "zapper" function which can be called to
* delete each data element of the list, regardless of its class. This
* technique permits a generic clear function to destroy elements of
* different derived types correctly, without requiring virtual functions and
* the consequential memory overhead.
**********************************************************************/
void
CLIST::internal_deep_clear ( //destroy all links
void (*zapper) (void *)) { //ptr to zapper functn
CLIST_LINK *ptr;
CLIST_LINK *next;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST::internal_deep_clear", ABORT, NULL);
#endif
if (!empty ()) {
ptr = last->next; //set to first
last->next = NULL; //break circle
last = NULL; //set list empty
while (ptr) {
next = ptr->next;
zapper (ptr->data);
delete(ptr);
ptr = next;
}
}
}
/***********************************************************************
* CLIST::shallow_clear
*
* Used by the destructor and the "shallow_clear" member function of derived
* list classes to destroy the list.
* The data elements are NOT destroyed.
*
**********************************************************************/
void CLIST::shallow_clear() { //destroy all links
CLIST_LINK *ptr;
CLIST_LINK *next;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST::shallow_clear", ABORT, NULL);
#endif
if (!empty ()) {
ptr = last->next; //set to first
last->next = NULL; //break circle
last = NULL; //set list empty
while (ptr) {
next = ptr->next;
delete(ptr);
ptr = next;
}
}
}
/***********************************************************************
* CLIST::assign_to_sublist
*
* The list is set to a sublist of another list. "This" list must be empty
* before this function is invoked. The two iterators passed must refer to
* the same list, different from "this" one. The sublist removed is the
* inclusive list from start_it's current position to end_it's current
* position. If this range passes over the end of the source list then the
* source list has its end set to the previous element of start_it. The
* extracted sublist is unaffected by the end point of the source list, its
* end point is always the end_it position.
**********************************************************************/
void CLIST::assign_to_sublist( //to this list
CLIST_ITERATOR *start_it, //from list start
CLIST_ITERATOR *end_it) { //from list end
const ERRCODE LIST_NOT_EMPTY =
"Destination list must be empty before extracting a sublist";
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST::assign_to_sublist", ABORT, NULL);
#endif
if (!empty ())
LIST_NOT_EMPTY.error ("CLIST.assign_to_sublist", ABORT, NULL);
last = start_it->extract_sublist (end_it);
}
/***********************************************************************
* CLIST::length
*
* Return count of elements on list
**********************************************************************/
inT32 CLIST::length() const { //count elements
CLIST_ITERATOR it(const_cast<CLIST*>(this));
inT32 count = 0;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST::length", ABORT, NULL);
#endif
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward())
count++;
return count;
}
/***********************************************************************
* CLIST::sort
*
* Sort elements on list
**********************************************************************/
void
CLIST::sort ( //sort elements
int comparator ( //comparison routine
const void *, const void *)) {
CLIST_ITERATOR it(this);
inT32 count;
void **base; //ptr array to sort
void **current;
inT32 i;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST::sort", ABORT, NULL);
#endif
/* Allocate an array of pointers, one per list element */
count = length ();
base = (void **) malloc (count * sizeof (void *));
/* Extract all elements, putting the pointers in the array */
current = base;
for (it.mark_cycle_pt (); !it.cycled_list (); it.forward ()) {
*current = it.extract ();
current++;
}
/* Sort the pointer array */
qsort ((char *) base, count, sizeof (*base), comparator);
/* Rebuild the list from the sorted pointers */
current = base;
for (i = 0; i < count; i++) {
it.add_to_end (*current);
current++;
}
free(base);
}
// Assuming list has been sorted already, insert new_data to
// keep the list sorted according to the same comparison function.
// Comparision function is the same as used by sort, i.e. uses double
// indirection. Time is O(1) to add to beginning or end.
// Time is linear to add pre-sorted items to an empty list.
// If unique, then don't add duplicate entries.
// Returns true if the element was added to the list.
bool CLIST::add_sorted(int comparator(const void*, const void*),
bool unique, void* new_data) {
// Check for adding at the end.
if (last == NULL || comparator(&last->data, &new_data) < 0) {
CLIST_LINK* new_element = new CLIST_LINK;
new_element->data = new_data;
if (last == NULL) {
new_element->next = new_element;
} else {
new_element->next = last->next;
last->next = new_element;
}
last = new_element;
return true;
} else if (!unique || last->data != new_data) {
// Need to use an iterator.
CLIST_ITERATOR it(this);
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward()) {
void* data = it.data();
if (data == new_data && unique)
return false;
if (comparator(&data, &new_data) > 0)
break;
}
if (it.cycled_list())
it.add_to_end(new_data);
else
it.add_before_then_move(new_data);
return true;
}
return false;
}
// Assuming that the minuend and subtrahend are already sorted with
// the same comparison function, shallow clears this and then copies
// the set difference minuend - subtrahend to this, being the elements
// of minuend that do not compare equal to anything in subtrahend.
// If unique is true, any duplicates in minuend are also eliminated.
void CLIST::set_subtract(int comparator(const void*, const void*),
bool unique,
CLIST* minuend, CLIST* subtrahend) {
shallow_clear();
CLIST_ITERATOR m_it(minuend);
CLIST_ITERATOR s_it(subtrahend);
// Since both lists are sorted, finding the subtras that are not
// minus is a case of a parallel iteration.
for (m_it.mark_cycle_pt(); !m_it.cycled_list(); m_it.forward()) {
void* minu = m_it.data();
void* subtra = NULL;
if (!s_it.empty()) {
subtra = s_it.data();
while (!s_it.at_last() &&
comparator(&subtra, &minu) < 0) {
s_it.forward();
subtra = s_it.data();
}
}
if (subtra == NULL || comparator(&subtra, &minu) != 0)
add_sorted(comparator, unique, minu);
}
}
/***********************************************************************
* MEMBER FUNCTIONS OF CLASS: CLIST_ITERATOR
* =========================================
**********************************************************************/
/***********************************************************************
* CLIST_ITERATOR::forward
*
* Move the iterator to the next element of the list.
* REMEMBER: ALL LISTS ARE CIRCULAR.
**********************************************************************/
void *CLIST_ITERATOR::forward() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::forward", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::forward", ABORT, NULL);
#endif
if (list->empty ())
return NULL;
if (current) { //not removed so
//set previous
prev = current;
started_cycling = TRUE;
// In case next is deleted by another iterator, get next from current.
current = current->next;
} else {
if (ex_current_was_cycle_pt)
cycle_pt = next;
current = next;
}
next = current->next;
#ifndef NDEBUG
if (!current)
NULL_DATA.error ("CLIST_ITERATOR::forward", ABORT, NULL);
if (!next)
NULL_NEXT.error ("CLIST_ITERATOR::forward", ABORT,
"This is: %p Current is: %p", this, current);
#endif
return current->data;
}
/***********************************************************************
* CLIST_ITERATOR::data_relative
*
* Return the data pointer to the element "offset" elements from current.
* "offset" must not be less than -1.
* (This function can't be INLINEd because it contains a loop)
**********************************************************************/
void *CLIST_ITERATOR::data_relative( //get data + or - ...
inT8 offset) { //offset from current
CLIST_LINK *ptr;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::data_relative", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::data_relative", ABORT, NULL);
if (list->empty ())
EMPTY_LIST.error ("CLIST_ITERATOR::data_relative", ABORT, NULL);
if (offset < -1)
BAD_PARAMETER.error ("CLIST_ITERATOR::data_relative", ABORT,
"offset < -l");
#endif
if (offset == -1)
ptr = prev;
else
for (ptr = current ? current : prev; offset-- > 0; ptr = ptr->next);
#ifndef NDEBUG
if (!ptr)
NULL_DATA.error ("CLIST_ITERATOR::data_relative", ABORT, NULL);
#endif
return ptr->data;
}
/***********************************************************************
* CLIST_ITERATOR::move_to_last()
*
* Move current so that it is set to the end of the list.
* Return data just in case anyone wants it.
* (This function can't be INLINEd because it contains a loop)
**********************************************************************/
void *CLIST_ITERATOR::move_to_last() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::move_to_last", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::move_to_last", ABORT, NULL);
#endif
while (current != list->last)
forward();
if (current == NULL)
return NULL;
else
return current->data;
}
/***********************************************************************
* CLIST_ITERATOR::exchange()
*
* Given another iterator, whose current element is a different element on
* the same list list OR an element of another list, exchange the two current
* elements. On return, each iterator points to the element which was the
* other iterators current on entry.
* (This function hasn't been in-lined because its a bit big!)
**********************************************************************/
void CLIST_ITERATOR::exchange( //positions of 2 links
CLIST_ITERATOR *other_it) { //other iterator
const ERRCODE DONT_EXCHANGE_DELETED =
"Can't exchange deleted elements of lists";
CLIST_LINK *old_current;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::exchange", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::exchange", ABORT, NULL);
if (!other_it)
BAD_PARAMETER.error ("CLIST_ITERATOR::exchange", ABORT, "other_it NULL");
if (!(other_it->list))
NO_LIST.error ("CLIST_ITERATOR::exchange", ABORT, "other_it");
#endif
/* Do nothing if either list is empty or if both iterators reference the same
link */
if ((list->empty ()) ||
(other_it->list->empty ()) || (current == other_it->current))
return;
/* Error if either current element is deleted */
if (!current || !other_it->current)
DONT_EXCHANGE_DELETED.error ("CLIST_ITERATOR.exchange", ABORT, NULL);
/* Now handle the 4 cases: doubleton list; non-doubleton adjacent elements
(other before this); non-doubleton adjacent elements (this before other);
non-adjacent elements. */
//adjacent links
if ((next == other_it->current) ||
(other_it->next == current)) {
//doubleton list
if ((next == other_it->current) &&
(other_it->next == current)) {
prev = next = current;
other_it->prev = other_it->next = other_it->current;
}
else { //non-doubleton with
//adjacent links
//other before this
if (other_it->next == current) {
other_it->prev->next = current;
other_it->current->next = next;
current->next = other_it->current;
other_it->next = other_it->current;
prev = current;
}
else { //this before other
prev->next = other_it->current;
current->next = other_it->next;
other_it->current->next = current;
next = current;
other_it->prev = other_it->current;
}
}
}
else { //no overlap
prev->next = other_it->current;
current->next = other_it->next;
other_it->prev->next = current;
other_it->current->next = next;
}
/* update end of list pointer when necessary (remember that the 2 iterators
may iterate over different lists!) */
if (list->last == current)
list->last = other_it->current;
if (other_it->list->last == other_it->current)
other_it->list->last = current;
if (current == cycle_pt)
cycle_pt = other_it->cycle_pt;
if (other_it->current == other_it->cycle_pt)
other_it->cycle_pt = cycle_pt;
/* The actual exchange - in all cases*/
old_current = current;
current = other_it->current;
other_it->current = old_current;
}
/***********************************************************************
* CLIST_ITERATOR::extract_sublist()
*
* This is a private member, used only by CLIST::assign_to_sublist.
* Given another iterator for the same list, extract the links from THIS to
* OTHER inclusive, link them into a new circular list, and return a
* pointer to the last element.
* (Can't inline this function because it contains a loop)
**********************************************************************/
CLIST_LINK *CLIST_ITERATOR::extract_sublist( //from this current
CLIST_ITERATOR *other_it) { //to other current
CLIST_ITERATOR temp_it = *this;
CLIST_LINK *end_of_new_list;
const ERRCODE BAD_SUBLIST = "Can't find sublist end point in original list";
#ifndef NDEBUG
const ERRCODE BAD_EXTRACTION_PTS =
"Can't extract sublist from points on different lists";
const ERRCODE DONT_EXTRACT_DELETED =
"Can't extract a sublist marked by deleted points";
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::extract_sublist", ABORT, NULL);
if (!other_it)
BAD_PARAMETER.error ("CLIST_ITERATOR::extract_sublist", ABORT,
"other_it NULL");
if (!list)
NO_LIST.error ("CLIST_ITERATOR::extract_sublist", ABORT, NULL);
if (list != other_it->list)
BAD_EXTRACTION_PTS.error ("CLIST_ITERATOR.extract_sublist", ABORT, NULL);
if (list->empty ())
EMPTY_LIST.error ("CLIST_ITERATOR::extract_sublist", ABORT, NULL);
if (!current || !other_it->current)
DONT_EXTRACT_DELETED.error ("CLIST_ITERATOR.extract_sublist", ABORT,
NULL);
#endif
ex_current_was_last = other_it->ex_current_was_last = FALSE;
ex_current_was_cycle_pt = FALSE;
other_it->ex_current_was_cycle_pt = FALSE;
temp_it.mark_cycle_pt ();
do { //walk sublist
if (temp_it.cycled_list ()) //cant find end pt
BAD_SUBLIST.error ("CLIST_ITERATOR.extract_sublist", ABORT, NULL);
if (temp_it.at_last ()) {
list->last = prev;
ex_current_was_last = other_it->ex_current_was_last = TRUE;
}
if (temp_it.current == cycle_pt)
ex_current_was_cycle_pt = TRUE;
if (temp_it.current == other_it->cycle_pt)
other_it->ex_current_was_cycle_pt = TRUE;
temp_it.forward ();
}
while (temp_it.prev != other_it->current);
//circularise sublist
other_it->current->next = current;
end_of_new_list = other_it->current;
//sublist = whole list
if (prev == other_it->current) {
list->last = NULL;
prev = current = next = NULL;
other_it->prev = other_it->current = other_it->next = NULL;
}
else {
prev->next = other_it->next;
current = other_it->current = NULL;
next = other_it->next;
other_it->prev = prev;
}
return end_of_new_list;
}
| C++ |
// Copyright 2006 Google Inc.
// All Rights Reserved.
// Author: renn
//
// The fscanf, vfscanf and creat functions are implemented so that their
// functionality is mostly like their stdio counterparts. However, currently
// these functions do not use any buffering, making them rather slow.
// File streams are thus processed one character at a time.
// Although the implementations of the scanf functions do lack a few minor
// features, they should be sufficient for their use in tesseract.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <ctype.h>
#include <math.h>
#include <stdarg.h>
#include <stddef.h>
#include <string.h>
#include <limits.h>
#include <stdio.h>
#include <sys/types.h>
#include <sys/stat.h>
#include <fcntl.h>
#include "scanutils.h"
#include "tprintf.h"
// workaround for "'off_t' was not declared in this scope" with -std=c++11
#if !defined(off_t) && !defined(__APPLE__) && !defined(__CYGWIN__)
typedef long off_t;
#endif // off_t
enum Flags {
FL_SPLAT = 0x01, // Drop the value, do not assign
FL_INV = 0x02, // Character-set with inverse
FL_WIDTH = 0x04, // Field width specified
FL_MINUS = 0x08, // Negative number
};
enum Ranks {
RANK_CHAR = -2,
RANK_SHORT = -1,
RANK_INT = 0,
RANK_LONG = 1,
RANK_LONGLONG = 2,
RANK_PTR = INT_MAX // Special value used for pointers
};
const enum Ranks kMinRank = RANK_CHAR;
const enum Ranks kMaxRank = RANK_LONGLONG;
const enum Ranks kIntMaxRank = RANK_LONGLONG;
const enum Ranks kSizeTRank = RANK_LONG;
const enum Ranks kPtrDiffRank = RANK_LONG;
enum Bail {
BAIL_NONE = 0, // No error condition
BAIL_EOF, // Hit EOF
BAIL_ERR // Conversion mismatch
};
// Helper functions ------------------------------------------------------------
inline size_t LongBit() {
return CHAR_BIT * sizeof(long);
}
static inline int
SkipSpace(FILE *s) {
int p;
while (isspace(p = fgetc(s)));
ungetc(p, s); // Make sure next char is available for reading
return p;
}
static inline void
SetBit(unsigned long *bitmap, unsigned int bit) {
bitmap[bit/LongBit()] |= 1UL << (bit%LongBit());
}
static inline int
TestBit(unsigned long *bitmap, unsigned int bit) {
return static_cast<int>(bitmap[bit/LongBit()] >> (bit%LongBit())) & 1;
}
static inline int DigitValue(int ch, int base) {
if (ch >= '0' && ch <= '9') {
if (base >= 10 || ch <= '7')
return ch-'0';
} else if (ch >= 'A' && ch <= 'Z' && base == 16) {
return ch-'A'+10;
} else if (ch >= 'a' && ch <= 'z' && base == 16) {
return ch-'a'+10;
}
return -1;
}
// IO (re-)implementations -----------------------------------------------------
uintmax_t streamtoumax(FILE* s, int base) {
int minus = 0;
uintmax_t v = 0;
int d, c = 0;
for (c = fgetc(s);
isspace(static_cast<unsigned char>(c)) && (c != EOF);
c = fgetc(s)) {}
// Single optional + or -
if (c == '-' || c == '+') {
minus = (c == '-');
c = fgetc(s);
}
// Assign correct base
if (base == 0) {
if (c == '0') {
c = fgetc(s);
if (c == 'x' || c == 'X') {
base = 16;
c = fgetc(s);
} else {
base = 8;
}
}
} else if (base == 16) {
if (c == '0') {
c = fgetc(s);
if (c == 'x' || c == 'X') c = fgetc(s);
}
}
// Actual number parsing
for (; (c != EOF) && (d = DigitValue(c, base)) >= 0; c = fgetc(s))
v = v*base + d;
ungetc(c, s);
return minus ? -v : v;
}
double streamtofloat(FILE* s) {
int minus = 0;
int v = 0;
int d, c = 0;
int k = 1;
int w = 0;
for (c = fgetc(s);
isspace(static_cast<unsigned char>(c)) && (c != EOF);
c = fgetc(s));
// Single optional + or -
if (c == '-' || c == '+') {
minus = (c == '-');
c = fgetc(s);
}
// Actual number parsing
for (; c != EOF && (d = DigitValue(c, 10)) >= 0; c = fgetc(s))
v = v*10 + d;
if (c == '.') {
for (c = fgetc(s); c != EOF && (d = DigitValue(c, 10)) >= 0; c = fgetc(s)) {
w = w*10 + d;
k *= 10;
}
}
double f = static_cast<double>(v)
+ static_cast<double>(w) / static_cast<double>(k);
if (c == 'e' || c == 'E') {
c = fgetc(s);
int expsign = 1;
if (c == '-' || c == '+') {
expsign = (c == '-') ? -1 : 1;
c = fgetc(s);
}
int exponent = 0;
for (; (c != EOF) && (d = DigitValue(c, 10)) >= 0; c = fgetc(s)) {
exponent = exponent * 10 + d;
}
exponent *= expsign;
f *= pow(10.0, static_cast<double>(exponent));
}
ungetc(c, s);
return minus ? -f : f;
}
double strtofloat(const char* s) {
int minus = 0;
int v = 0;
int d;
int k = 1;
int w = 0;
while(*s && isspace(static_cast<unsigned char>(*s))) s++;
// Single optional + or -
if (*s == '-' || *s == '+') {
minus = (*s == '-');
s++;
}
// Actual number parsing
for (; *s && (d = DigitValue(*s, 10)) >= 0; s++)
v = v*10 + d;
if (*s == '.') {
for (++s; *s && (d = DigitValue(*s, 10)) >= 0; s++) {
w = w*10 + d;
k *= 10;
}
}
if (*s == 'e' || *s == 'E')
tprintf("WARNING: Scientific Notation not supported!");
double f = static_cast<double>(v)
+ static_cast<double>(w) / static_cast<double>(k);
return minus ? -f : f;
}
static int tvfscanf(FILE* stream, const char *format, va_list ap);
int tfscanf(FILE* stream, const char *format, ...) {
va_list ap;
int rv;
va_start(ap, format);
rv = tvfscanf(stream, format, ap);
va_end(ap);
return rv;
}
#ifdef EMBEDDED
int fscanf(FILE* stream, const char *format, ...) {
va_list ap;
int rv;
va_start(ap, format);
rv = tvfscanf(stream, format, ap);
va_end(ap);
return rv;
}
int vfscanf(FILE* stream, const char *format, ...) {
va_list ap;
int rv;
va_start(ap, format);
rv = tvfscanf(stream, format, ap);
va_end(ap);
return rv;
}
#endif
static int tvfscanf(FILE* stream, const char *format, va_list ap) {
const char *p = format;
char ch;
int q = 0;
uintmax_t val = 0;
int rank = RANK_INT; // Default rank
unsigned int width = UINT_MAX;
int base;
int flags = 0;
enum {
ST_NORMAL, // Ground state
ST_FLAGS, // Special flags
ST_WIDTH, // Field width
ST_MODIFIERS, // Length or conversion modifiers
ST_MATCH_INIT, // Initial state of %[ sequence
ST_MATCH, // Main state of %[ sequence
ST_MATCH_RANGE, // After - in a %[ sequence
} state = ST_NORMAL;
char *sarg = NULL; // %s %c or %[ string argument
enum Bail bail = BAIL_NONE;
int sign;
int converted = 0; // Successful conversions
unsigned long matchmap[((1 << CHAR_BIT)+(CHAR_BIT * sizeof(long) - 1)) /
(CHAR_BIT * sizeof(long))];
int matchinv = 0; // Is match map inverted?
unsigned char range_start = 0;
off_t start_off = ftell(stream);
// Skip leading spaces
SkipSpace(stream);
while ((ch = *p++) && !bail) {
switch (state) {
case ST_NORMAL:
if (ch == '%') {
state = ST_FLAGS;
flags = 0; rank = RANK_INT; width = UINT_MAX;
} else if (isspace(static_cast<unsigned char>(ch))) {
SkipSpace(stream);
} else {
if (fgetc(stream) != ch)
bail = BAIL_ERR; // Match failure
}
break;
case ST_FLAGS:
if (ch == '*') {
flags |= FL_SPLAT;
} else if ('0' <= ch && ch <= '9') {
width = (ch-'0');
state = ST_WIDTH;
flags |= FL_WIDTH;
} else {
state = ST_MODIFIERS;
p--; // Process this character again
}
break;
case ST_WIDTH:
if (ch >= '0' && ch <= '9') {
width = width*10+(ch-'0');
} else {
state = ST_MODIFIERS;
p--; // Process this character again
}
break;
case ST_MODIFIERS:
switch (ch) {
// Length modifiers - nonterminal sequences
case 'h':
rank--; // Shorter rank
break;
case 'l':
rank++; // Longer rank
break;
case 'j':
rank = kIntMaxRank;
break;
case 'z':
rank = kSizeTRank;
break;
case 't':
rank = kPtrDiffRank;
break;
case 'L':
case 'q':
rank = RANK_LONGLONG; // long double/long long
break;
default:
// Output modifiers - terminal sequences
state = ST_NORMAL; // Next state will be normal
if (rank < kMinRank) // Canonicalize rank
rank = kMinRank;
else if (rank > kMaxRank)
rank = kMaxRank;
switch (ch) {
case 'P': // Upper case pointer
case 'p': // Pointer
rank = RANK_PTR;
base = 0; sign = 0;
goto scan_int;
case 'i': // Base-independent integer
base = 0; sign = 1;
goto scan_int;
case 'd': // Decimal integer
base = 10; sign = 1;
goto scan_int;
case 'o': // Octal integer
base = 8; sign = 0;
goto scan_int;
case 'u': // Unsigned decimal integer
base = 10; sign = 0;
goto scan_int;
case 'x': // Hexadecimal integer
case 'X':
base = 16; sign = 0;
goto scan_int;
case 'n': // Number of characters consumed
val = ftell(stream) - start_off;
goto set_integer;
scan_int:
q = SkipSpace(stream);
if ( q <= 0 ) {
bail = BAIL_EOF;
break;
}
val = streamtoumax(stream, base);
// fall through
set_integer:
if (!(flags & FL_SPLAT)) {
converted++;
switch(rank) {
case RANK_CHAR:
*va_arg(ap, unsigned char *)
= static_cast<unsigned char>(val);
break;
case RANK_SHORT:
*va_arg(ap, unsigned short *)
= static_cast<unsigned short>(val);
break;
case RANK_INT:
*va_arg(ap, unsigned int *)
= static_cast<unsigned int>(val);
break;
case RANK_LONG:
*va_arg(ap, unsigned long *)
= static_cast<unsigned long>(val);
break;
case RANK_LONGLONG:
*va_arg(ap, unsigned long long *)
= static_cast<unsigned long long>(val);
break;
case RANK_PTR:
*va_arg(ap, void **)
= reinterpret_cast<void *>(static_cast<uintptr_t>(val));
break;
}
}
break;
case 'f': // Preliminary float value parsing
case 'g':
case 'G':
case 'e':
case 'E':
q = SkipSpace(stream);
if (q <= 0) {
bail = BAIL_EOF;
break;
}
{
double fval = streamtofloat(stream);
if (!(flags & FL_SPLAT)) {
if (rank == RANK_INT)
*va_arg(ap, float *) = static_cast<float>(fval);
else if (rank == RANK_LONG)
*va_arg(ap, double *) = static_cast<double>(fval);
converted++;
}
}
break;
case 'c': // Character
width = (flags & FL_WIDTH) ? width : 1; // Default width == 1
sarg = va_arg(ap, char *);
while (width--) {
if ((q = fgetc(stream)) <= 0) {
bail = BAIL_EOF;
break;
}
if (!(flags & FL_SPLAT)) {
*sarg++ = q;
converted++;
}
}
break;
case 's': // String
{
char *sp;
sp = sarg = va_arg(ap, char *);
while (width--) {
q = fgetc(stream);
if (isspace(static_cast<unsigned char>(q)) || q <= 0) {
ungetc(q, stream);
break;
}
if (!(flags & FL_SPLAT)) *sp = q;
sp++;
}
if (sarg == sp) {
bail = BAIL_EOF;
} else if (!(flags & FL_SPLAT)) {
*sp = '\0'; // Terminate output
converted++;
} else {
}
}
break;
case '[': // Character range
sarg = va_arg(ap, char *);
state = ST_MATCH_INIT;
matchinv = 0;
memset(matchmap, 0, sizeof matchmap);
break;
case '%': // %% sequence
if (fgetc(stream) != '%' )
bail = BAIL_ERR;
break;
default: // Anything else
bail = BAIL_ERR; // Unknown sequence
break;
}
}
break;
case ST_MATCH_INIT: // Initial state for %[ match
if (ch == '^' && !(flags & FL_INV)) {
matchinv = 1;
} else {
SetBit(matchmap, static_cast<unsigned char>(ch));
state = ST_MATCH;
}
break;
case ST_MATCH: // Main state for %[ match
if (ch == ']') {
goto match_run;
} else if (ch == '-') {
range_start = static_cast<unsigned char>(ch);
state = ST_MATCH_RANGE;
} else {
SetBit(matchmap, static_cast<unsigned char>(ch));
}
break;
case ST_MATCH_RANGE: // %[ match after -
if (ch == ']') {
SetBit(matchmap, static_cast<unsigned char>('-'));
goto match_run;
} else {
int i;
for (i = range_start ; i < (static_cast<unsigned char>(ch)) ; i++)
SetBit(matchmap, i);
state = ST_MATCH;
}
break;
match_run: // Match expression finished
char* oarg = sarg;
while (width) {
q = fgetc(stream);
unsigned char qc = static_cast<unsigned char>(q);
if (q <= 0 || !(TestBit(matchmap, qc)^matchinv)) {
ungetc(q, stream);
break;
}
if (!(flags & FL_SPLAT)) *sarg = q;
sarg++;
}
if (oarg == sarg) {
bail = (q <= 0) ? BAIL_EOF : BAIL_ERR;
} else if (!(flags & FL_SPLAT)) {
*sarg = '\0';
converted++;
}
break;
}
}
if (bail == BAIL_EOF && !converted)
converted = -1; // Return EOF (-1)
return converted;
}
#ifdef EMBEDDED
int creat(const char *pathname, mode_t mode) {
return open(pathname, O_CREAT | O_TRUNC | O_WRONLY, mode);
}
#endif // EMBEDDED
| C++ |
///////////////////////////////////////////////////////////////////////
// File: universalambigs.cpp
// Description: Data for a universal ambigs file that is useful for
// any language.
// Author: Ray Smith
// Created: Mon Mar 18 11:26:00 PDT 2013
//
// (C) Copyright 2013, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
namespace tesseract {
extern const char kUniversalAmbigsFile[] = {
'\166', '\062', '\012', '\047', '\047', '\040', '\042', '\040',
'\061', '\012', '\140', '\047', '\040', '\042', '\040', '\061',
'\012', '\047', '\140', '\040', '\042', '\040', '\061', '\012',
'\342', '\200', '\230', '\047', '\040', '\042', '\040', '\061',
'\012', '\047', '\342', '\200', '\230', '\040', '\042', '\040',
'\061', '\012', '\342', '\200', '\231', '\047', '\040', '\042',
'\040', '\061', '\012', '\047', '\342', '\200', '\231', '\040',
'\042', '\040', '\061', '\012', '\140', '\140', '\040', '\042',
'\040', '\061', '\012', '\140', '\342', '\200', '\230', '\040',
'\042', '\040', '\061', '\012', '\342', '\200', '\230', '\140',
'\040', '\042', '\040', '\061', '\012', '\140', '\342', '\200',
'\231', '\040', '\042', '\040', '\061', '\012', '\342', '\200',
'\231', '\140', '\040', '\042', '\040', '\061', '\012', '\342',
'\200', '\230', '\342', '\200', '\230', '\040', '\342', '\200',
'\234', '\040', '\061', '\012', '\342', '\200', '\230', '\342',
'\200', '\231', '\040', '\042', '\040', '\061', '\012', '\342',
'\200', '\231', '\342', '\200', '\230', '\040', '\042', '\040',
'\061', '\012', '\342', '\200', '\231', '\342', '\200', '\231',
'\040', '\342', '\200', '\235', '\040', '\061', '\012', '\054',
'\054', '\040', '\342', '\200', '\236', '\040', '\061', '\012',
'\155', '\040', '\162', '\156', '\040', '\060', '\012', '\162',
'\156', '\040', '\155', '\040', '\060', '\012', '\155', '\040',
'\151', '\156', '\040', '\060', '\012', '\151', '\156', '\040',
'\155', '\040', '\060', '\012', '\144', '\040', '\143', '\154',
'\040', '\060', '\012', '\143', '\154', '\040', '\144', '\040',
'\060', '\012', '\156', '\156', '\040', '\162', '\155', '\040',
'\060', '\012', '\162', '\155', '\040', '\156', '\156', '\040',
'\060', '\012', '\156', '\040', '\162', '\151', '\040', '\060',
'\012', '\162', '\151', '\040', '\156', '\040', '\060', '\012',
'\154', '\151', '\040', '\150', '\040', '\060', '\012', '\154',
'\162', '\040', '\150', '\040', '\060', '\012', '\151', '\151',
'\040', '\165', '\040', '\060', '\012', '\151', '\151', '\040',
'\156', '\040', '\060', '\012', '\156', '\151', '\040', '\155',
'\040', '\060', '\012', '\151', '\151', '\151', '\040', '\155',
'\040', '\060', '\012', '\154', '\154', '\040', '\110', '\040',
'\060', '\012', '\111', '\055', '\111', '\040', '\110', '\040',
'\060', '\012', '\166', '\166', '\040', '\167', '\040', '\060',
'\012', '\126', '\126', '\040', '\127', '\040', '\060', '\012',
'\164', '\040', '\146', '\040', '\060', '\012', '\146', '\040',
'\164', '\040', '\060', '\012', '\141', '\040', '\157', '\040',
'\060', '\012', '\157', '\040', '\141', '\040', '\060', '\012',
'\145', '\040', '\143', '\040', '\060', '\012', '\143', '\040',
'\145', '\040', '\060', '\012', '\162', '\162', '\040', '\156',
'\040', '\060', '\012', '\105', '\040', '\146', '\151', '\040',
'\060', '\012', '\154', '\074', '\040', '\153', '\040', '\060',
'\012', '\154', '\144', '\040', '\153', '\151', '\040', '\060',
'\012', '\154', '\170', '\040', '\150', '\040', '\060', '\012',
'\170', '\156', '\040', '\155', '\040', '\060', '\012', '\165',
'\170', '\040', '\151', '\156', '\040', '\060', '\012', '\162',
'\040', '\164', '\040', '\060', '\012', '\144', '\040', '\164',
'\154', '\040', '\060', '\012', '\144', '\151', '\040', '\164',
'\150', '\040', '\060', '\012', '\165', '\162', '\040', '\151',
'\156', '\040', '\060', '\012', '\165', '\156', '\040', '\151',
'\155', '\040', '\060', '\012', '\165', '\040', '\141', '\040',
'\060', '\012', '\157', '\040', '\303', '\263', '\040', '\060',
'\012', '\303', '\263', '\040', '\157', '\040', '\060', '\012',
'\151', '\040', '\303', '\255', '\040', '\060', '\012', '\303',
'\255', '\040', '\151', '\040', '\060', '\012', '\141', '\040',
'\303', '\241', '\040', '\060', '\012', '\303', '\241', '\040',
'\141', '\040', '\060', '\012', '\145', '\040', '\303', '\251',
'\040', '\060', '\012', '\303', '\251', '\040', '\145', '\040',
'\060', '\012', '\165', '\040', '\303', '\272', '\040', '\060',
'\012', '\303', '\272', '\040', '\165', '\040', '\060', '\012',
'\156', '\040', '\303', '\261', '\040', '\060', '\012', '\303',
'\261', '\040', '\156', '\040', '\060', '\012', '\060', '\040',
'\157', '\040', '\060', '\012', '\144', '\040', '\164', '\162',
'\040', '\060', '\012', '\156', '\040', '\164', '\162', '\040',
'\060', '\012', '\303', '\261', '\040', '\146', '\151', '\040',
'\060', '\012', '\165', '\040', '\164', '\151', '\040', '\060',
'\012', '\303', '\261', '\040', '\164', '\151', '\040', '\060',
'\012', '\144', '\040', '\164', '\151', '\040', '\060', '\012',
'\144', '\040', '\164', '\303', '\255', '\040', '\060', '\012',
'\144', '\040', '\162', '\303', '\255', '\040', '\060', '\012',
'\141', '\040', '\303', '\240', '\040', '\060', '\012', '\145',
'\040', '\303', '\250', '\040', '\060', '\012', '\156', '\040',
'\151', '\152', '\040', '\060', '\012', '\147', '\040', '\151',
'\152', '\040', '\060', '\012', '\157', '\040', '\303', '\262',
'\040', '\060', '\012', '\105', '\040', '\303', '\211', '\040',
'\060', '\012', '\105', '\040', '\303', '\210', '\040', '\060',
'\012', '\165', '\040', '\303', '\274', '\040', '\060', '\012',
'\170', '\156', '\105', '\040', '\141', '\156', '\040', '\061',
'\012', '\155', '\131', '\170', '\040', '\155', '\145', '\040',
'\061', '\012', '\161', '\164', '\105', '\040', '\156', '\164',
'\040', '\061', '\012', '\124', '\154', '\142', '\040', '\154',
'\145', '\040', '\061', '\012', '\166', '\170', '\116', '\040',
'\166', '\141', '\040', '\061', '\012', '\147', '\152', '\121',
'\040', '\156', '\147', '\040', '\061', '\012', '\152', '\160',
'\106', '\040', '\151', '\152', '\040', '\061', '\012', '\131',
'\162', '\154', '\040', '\154', '\145', '\040', '\061', '\012',
'\141', '\161', '\131', '\040', '\141', '\156', '\040', '\061',
'\012', '\172', '\166', '\112', '\040', '\166', '\141', '\040',
'\061', '\012', '\146', '\142', '\114', '\040', '\142', '\145',
'\040', '\061', '\012', '\116', '\166', '\153', '\040', '\166',
'\141', '\040', '\061', '\012', '\146', '\112', '\160', '\040',
'\160', '\162', '\040', '\061', '\012', '\167', '\170', '\103',
'\040', '\167', '\141', '\040', '\061', '\012', '\143', '\165',
'\112', '\040', '\161', '\165', '\040', '\061', '\012', '\121',
'\172', '\164', '\040', '\164', '\141', '\040', '\061', '\012',
'\161', '\113', '\167', '\040', '\167', '\141', '\040', '\061',
'\012', '\163', '\143', '\112', '\040', '\163', '\164', '\040',
'\061', '\012', '\160', '\130', '\160', '\040', '\160', '\157',
'\040', '\061', '\012', '\126', '\161', '\151', '\040', '\164',
'\151', '\040', '\061', '\012', '\125', '\170', '\153', '\040',
'\153', '\141', '\040', '\061', '\012', '\153', '\112', '\166',
'\040', '\153', '\141', '\040', '\061', '\012', '\131', '\153',
'\144', '\040', '\153', '\141', '\040', '\061', '\012', '\166',
'\160', '\130', '\040', '\166', '\141', '\040', '\061', '\012',
'\151', '\102', '\166', '\040', '\164', '\151', '\040', '\061',
'\012', '\172', '\122', '\142', '\040', '\163', '\172', '\040',
'\061', '\012', '\171', '\124', '\155', '\040', '\155', '\151',
'\040', '\061', '\012', '\155', '\113', '\160', '\040', '\160',
'\162', '\040', '\061', '\012', '\126', '\172', '\161', '\040',
'\161', '\165', '\040', '\061', '\012', '\130', '\164', '\160',
'\040', '\164', '\151', '\040', '\061', '\012', '\155', '\166',
'\104', '\040', '\166', '\141', '\040', '\061', '\012', '\155',
'\104', '\161', '\040', '\155', '\145', '\040', '\061', '\012',
'\152', '\170', '\120', '\040', '\151', '\152', '\040', '\061',
'\012', '\102', '\170', '\166', '\040', '\166', '\141', '\040',
'\061', '\012', '\157', '\111', '\165', '\040', '\161', '\165',
'\040', '\061', '\012', '\122', '\166', '\143', '\040', '\166',
'\141', '\040', '\061', '\012', '\165', '\103', '\152', '\040',
'\161', '\165', '\040', '\061', '\012', '\157', '\101', '\157',
'\040', '\166', '\157', '\040', '\061', '\012', '\161', '\165',
'\102', '\040', '\164', '\165', '\040', '\061', '\012', '\142',
'\164', '\126', '\040', '\164', '\151', '\040', '\061', '\012',
'\114', '\155', '\143', '\040', '\155', '\145', '\040', '\061',
'\012', '\164', '\126', '\167', '\040', '\164', '\151', '\040',
'\061', '\012', '\131', '\170', '\166', '\040', '\166', '\141',
'\040', '\061', '\012', '\110', '\170', '\155', '\040', '\155',
'\145', '\040', '\061', '\012', '\144', '\126', '\150', '\040',
'\164', '\150', '\040', '\061', '\012', '\170', '\131', '\143',
'\040', '\143', '\150', '\040', '\061', '\012', '\165', '\120',
'\152', '\040', '\164', '\165', '\040', '\061', '\012', '\146',
'\124', '\146', '\040', '\146', '\157', '\040', '\061', '\012',
'\122', '\152', '\167', '\040', '\151', '\152', '\040', '\061',
'\012', '\170', '\144', '\101', '\040', '\144', '\151', '\040',
'\061', '\012', '\152', '\172', '\116', '\040', '\151', '\152',
'\040', '\061', '\012', '\155', '\170', '\114', '\040', '\155',
'\145', '\040', '\061', '\012', '\171', '\147', '\112', '\040',
'\156', '\147', '\040', '\061', '\012', '\126', '\166', '\147',
'\040', '\166', '\141', '\040', '\061', '\012', '\162', '\152',
'\113', '\040', '\151', '\152', '\040', '\061', '\012', '\171',
'\165', '\126', '\040', '\164', '\165', '\040', '\061', '\012',
'\163', '\127', '\153', '\040', '\153', '\165', '\040', '\061',
'\012', '\120', '\147', '\172', '\040', '\163', '\172', '\040',
'\061', '\012', '\152', '\110', '\155', '\040', '\155', '\145',
'\040', '\061', '\012', '\172', '\153', '\125', '\040', '\153',
'\165', '\040', '\061', '\012', '\147', '\166', '\107', '\040',
'\166', '\141', '\040', '\061', '\012', '\150', '\144', '\120',
'\040', '\164', '\150', '\040', '\061', '\012', '\155', '\126',
'\142', '\040', '\155', '\145', '\040', '\061', '\012', '\121',
'\147', '\144', '\040', '\144', '\151', '\040', '\061', '\012',
'\172', '\143', '\132', '\040', '\143', '\150', '\040', '\061',
'\012', '\172', '\161', '\152', '\040', '\151', '\152', '\040',
'\061', '\012', '\172', '\163', '\112', '\040', '\163', '\172',
'\040', '\061', '\012', '\144', '\146', '\116', '\040', '\144',
'\151', '\040', '\061', '\012', '\144', '\147', '\127', '\040',
'\144', '\151', '\040', '\061', '\012', '\167', '\116', '\162',
'\040', '\162', '\151', '\040', '\061', '\012', '\172', '\166',
'\103', '\040', '\166', '\141', '\040', '\061', '\012', '\161',
'\131', '\167', '\040', '\161', '\165', '\040', '\061', '\012',
'\165', '\110', '\171', '\040', '\164', '\165', '\040', '\061',
'\012', '\164', '\116', '\161', '\040', '\164', '\150', '\040',
'\061', '\012', '\154', '\170', '\112', '\040', '\154', '\151',
'\040', '\061', '\012', '\110', '\142', '\153', '\040', '\153',
'\165', '\040', '\061', '\012', '\170', '\163', '\107', '\040',
'\163', '\164', '\040', '\061', '\012', '\166', '\123', '\142',
'\040', '\166', '\141', '\040', '\061', '\012', '\170', '\106',
'\142', '\040', '\142', '\165', '\040', '\061', '\012', '\116',
'\164', '\147', '\040', '\164', '\150', '\040', '\061', '\012',
'\157', '\102', '\152', '\040', '\151', '\152', '\040', '\061',
'\012', '\161', '\153', '\166', '\040', '\161', '\165', '\040',
'\061', '\012', '\142', '\126', '\152', '\040', '\151', '\152',
'\040', '\061', '\012', '\172', '\152', '\124', '\040', '\151',
'\152', '\040', '\061', '\012', '\142', '\166', '\130', '\040',
'\166', '\141', '\040', '\061', '\012', '\157', '\132', '\146',
'\040', '\164', '\157', '\040', '\061', '\012', '\153', '\143',
'\125', '\040', '\153', '\157', '\040', '\061', '\012', '\146',
'\106', '\155', '\040', '\155', '\145', '\040', '\061', '\012',
'\130', '\142', '\152', '\040', '\151', '\152', '\040', '\061',
'\012', '\113', '\161', '\166', '\040', '\166', '\141', '\040',
'\061', '\012', '\122', '\167', '\152', '\040', '\151', '\152',
'\040', '\061', '\012', '\144', '\166', '\112', '\040', '\166',
'\141', '\040', '\061', '\012', '\172', '\156', '\112', '\040',
'\163', '\172', '\040', '\061', '\012', '\161', '\161', '\126',
'\040', '\161', '\165', '\040', '\061', '\012', '\160', '\170',
'\115', '\040', '\160', '\157', '\040', '\061', '\012', '\145',
'\102', '\152', '\040', '\151', '\152', '\040', '\061', '\012',
'\155', '\112', '\170', '\040', '\155', '\145', '\040', '\061',
'\012', '\170', '\156', '\115', '\040', '\156', '\147', '\040',
'\061', '\012', '\141', '\103', '\161', '\040', '\166', '\141',
'\040', '\061', '\012', '\160', '\110', '\152', '\040', '\151',
'\152', '\040', '\061', '\012', '\164', '\146', '\121', '\040',
'\164', '\150', '\040', '\061', '\012', '\167', '\161', '\156',
'\040', '\161', '\165', '\040', '\061', '\012', '\155', '\123',
'\163', '\040', '\151', '\163', '\040', '\061', '\012', '\163',
'\102', '\167', '\040', '\163', '\164', '\040', '\061', '\012',
'\106', '\150', '\156', '\040', '\164', '\150', '\040', '\061',
'\012', '\172', '\116', '\142', '\040', '\163', '\172', '\040',
'\061', '\012', '\115', '\166', '\142', '\040', '\166', '\141',
'\040', '\061', '\012', '\142', '\126', '\164', '\040', '\164',
'\150', '\040', '\061', '\012', '\161', '\110', '\164', '\040',
'\164', '\150', '\040', '\061', '\012', '\161', '\114', '\166',
'\040', '\161', '\165', '\040', '\061', '\012', '\153', '\147',
'\106', '\040', '\156', '\147', '\040', '\061', '\012', '\166',
'\170', '\127', '\040', '\166', '\141', '\040', '\061', '\012',
'\143', '\144', '\131', '\040', '\143', '\150', '\040', '\061',
'\012', '\130', '\162', '\172', '\040', '\163', '\172', '\040',
'\061', '\012', '\105', '\146', '\150', '\040', '\164', '\150',
'\040', '\061', '\012', '\154', '\161', '\111', '\040', '\161',
'\165', '\040', '\061', '\012', '\114', '\172', '\161', '\040',
'\161', '\165', '\040', '\061', '\012', '\172', '\150', '\130',
'\040', '\164', '\150', '\040', '\061', '\012', '\147', '\150',
'\132', '\040', '\164', '\150', '\040', '\061', '\012', '\154',
'\106', '\147', '\040', '\156', '\147', '\040', '\061', '\012',
'\166', '\126', '\143', '\040', '\166', '\141', '\040', '\061',
'\012', '\154', '\115', '\162', '\040', '\145', '\162', '\040',
'\061', '\012', '\124', '\161', '\152', '\040', '\161', '\165',
'\040', '\061', '\012', '\152', '\101', '\170', '\040', '\151',
'\152', '\040', '\061', '\012', '\151', '\115', '\164', '\040',
'\164', '\150', '\040', '\061', '\012', '\116', '\154', '\166',
'\040', '\166', '\141', '\040', '\061', '\012', '\172', '\142',
'\120', '\040', '\163', '\172', '\040', '\061', '\012', '\153',
'\126', '\170', '\040', '\153', '\141', '\040', '\061', '\012',
'\145', '\121', '\154', '\040', '\164', '\145', '\040', '\061',
'\012', '\163', '\127', '\142', '\040', '\163', '\164', '\040',
'\061', '\012', '\102', '\161', '\171', '\040', '\161', '\165',
'\040', '\061', '\012', '\144', '\130', '\153', '\040', '\153',
'\141', '\040', '\061', '\012', '\166', '\125', '\143', '\040',
'\166', '\141', '\040', '\061', '\012', '\166', '\117', '\142',
'\040', '\166', '\141', '\040', '\061', '\012', '\165', '\110',
'\146', '\040', '\161', '\165', '\040', '\061', '\012', '\161',
'\116', '\162', '\040', '\161', '\165', '\040', '\061', '\012',
'\165', '\106', '\172', '\040', '\161', '\165', '\040', '\061',
'\012', '\115', '\154', '\162', '\040', '\145', '\162', '\040',
'\061', '\012', '\153', '\155', '\132', '\040', '\153', '\141',
'\040', '\061', '\012', '\163', '\122', '\164', '\040', '\164',
'\150', '\040', '\061', '\012', '\127', '\161', '\166', '\040',
'\161', '\165', '\040', '\061', '\012', '\150', '\146', '\113',
'\040', '\164', '\150', '\040', '\061', '\012', '\166', '\170',
'\121', '\040', '\166', '\141', '\040', '\061', '\012', '\154',
'\103', '\161', '\040', '\161', '\165', '\040', '\061', '\012',
'\146', '\131', '\167', '\040', '\167', '\141', '\040', '\061',
'\012', '\164', '\146', '\123', '\040', '\164', '\150', '\040',
'\061', '\012', '\161', '\144', '\117', '\040', '\161', '\165',
'\040', '\061', '\012', '\144', '\121', '\144', '\040', '\144',
'\145', '\040', '\061', '\012', '\170', '\144', '\130', '\040',
'\144', '\145', '\040', '\061', '\012', '\155', '\116', '\170',
'\040', '\155', '\145', '\040', '\061', '\012', '\153', '\106',
'\172', '\040', '\163', '\172', '\040', '\061', '\012', '\167',
'\152', '\123', '\040', '\151', '\152', '\040', '\061', '\012',
'\171', '\120', '\160', '\040', '\160', '\162', '\040', '\061',
'\012', '\167', '\143', '\127', '\040', '\143', '\150', '\040',
'\061', '\012', '\116', '\152', '\172', '\040', '\163', '\172',
'\040', '\061', '\012', '\144', '\126', '\160', '\040', '\144',
'\145', '\040', '\061', '\012', '\144', '\161', '\104', '\040',
'\161', '\165', '\040', '\061', '\012', '\162', '\112', '\163',
'\040', '\163', '\172', '\040', '\061', '\012', '\170', '\160',
'\110', '\040', '\160', '\157', '\040', '\061', '\012', '\170',
'\161', '\122', '\040', '\161', '\165', '\040', '\061', '\012',
'\147', '\126', '\162', '\040', '\145', '\162', '\040', '\061',
'\012', '\102', '\164', '\161', '\040', '\164', '\150', '\040',
'\061', '\012', '\156', '\155', '\102', '\040', '\156', '\164',
'\040', '\061', '\012', '\172', '\143', '\115', '\040', '\163',
'\172', '\040', '\061', '\012', '\143', '\146', '\107', '\040',
'\143', '\150', '\040', '\061', '\012', '\155', '\146', '\117',
'\040', '\155', '\145', '\040', '\061', '\012', '\131', '\150',
'\143', '\040', '\164', '\150', '\040', '\061', '\012', '\142',
'\132', '\155', '\040', '\155', '\145', '\040', '\061', '\012',
'\155', '\172', '\102', '\040', '\163', '\172', '\040', '\061',
'\012', '\166', '\122', '\167', '\040', '\166', '\141', '\040',
'\061', '\012', '\171', '\104', '\150', '\040', '\164', '\150',
'\040', '\061', '\012', '\132', '\147', '\146', '\040', '\156',
'\147', '\040', '\061', '\012', '\153', '\161', '\124', '\040',
'\161', '\165', '\040', '\061', '\012', '\111', '\165', '\172',
'\040', '\161', '\165', '\040', '\061', '\012', '\162', '\142',
'\127', '\040', '\145', '\162', '\040', '\061', '\012', '\112',
'\155', '\161', '\040', '\161', '\165', '\040', '\061', '\012',
'\113', '\166', '\152', '\040', '\166', '\141', '\040', '\061',
'\012', '\172', '\143', '\104', '\040', '\143', '\150', '\040',
'\061', '\012', '\170', '\147', '\103', '\040', '\156', '\147',
'\040', '\061', '\012', '\152', '\103', '\170', '\040', '\151',
'\152', '\040', '\061', '\012', '\142', '\127', '\147', '\040',
'\156', '\147', '\040', '\061', '\012', '\171', '\167', '\127',
'\040', '\167', '\141', '\040', '\061', '\012', '\112', '\153',
'\143', '\040', '\143', '\150', '\040', '\061', '\012', '\170',
'\107', '\163', '\040', '\163', '\172', '\040', '\061', '\012',
'\166', '\142', '\110', '\040', '\166', '\141', '\040', '\061',
'\012', '\154', '\124', '\172', '\040', '\163', '\172', '\040',
'\061', '\012', '\145', '\103', '\142', '\040', '\145', '\162',
'\040', '\061', '\012', '\152', '\126', '\166', '\040', '\166',
'\141', '\040', '\061', '\012', '\152', '\104', '\161', '\040',
'\161', '\165', '\040', '\061', '\012', '\152', '\157', '\121',
'\040', '\160', '\157', '\040', '\061', '\012', '\161', '\164',
'\115', '\040', '\164', '\150', '\040', '\061', '\012', '\122',
'\161', '\153', '\040', '\161', '\165', '\040', '\061', '\012',
'\110', '\166', '\147', '\040', '\166', '\141', '\040', '\061',
'\012', '\165', '\101', '\172', '\040', '\161', '\165', '\040',
'\061', '\012', '\155', '\146', '\127', '\040', '\155', '\145',
'\040', '\061', '\012', '\164', '\147', '\123', '\040', '\164',
'\150', '\040', '\061', '\012', '\143', '\161', '\104', '\040',
'\161', '\165', '\040', '\061', '\012', '\163', '\146', '\131',
'\040', '\163', '\172', '\040', '\061', '\012', '\131', '\150',
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'\170', '\151', '\040', '\151', '\156', '\040', '\061', '\012',
'\125', '\147', '\160', '\040', '\156', '\147', '\040', '\061',
'\012', '\122', '\170', '\151', '\040', '\151', '\156', '\040',
'\061', '\012', '\113', '\167', '\155', '\040', '\155', '\145',
'\040', '\061', '\012', '\172', '\153', '\104', '\040', '\163',
'\172', '\040', '\061', '\012', '\122', '\161', '\154', '\040',
'\161', '\165', '\040', '\061', '\012', '\160', '\112', '\142',
'\040', '\160', '\162', '\040', '\061', '\012', '\146', '\143',
'\126', '\040', '\143', '\150', '\040', '\061', '\012', '\151',
'\126', '\144', '\040', '\151', '\156', '\040', '\061', '\012',
'\142', '\102', '\160', '\040', '\142', '\145', '\040', '\061',
'\012', '\117', '\152', '\167', '\040', '\151', '\152', '\040',
'\061', '\012', '\166', '\132', '\154', '\040', '\154', '\145',
'\040', '\061', '\012', '\111', '\171', '\152', '\040', '\151',
'\152', '\040', '\061', '\012', '\146', '\153', '\125', '\040',
'\153', '\141', '\040', '\061', '\012', '\113', '\143', '\161',
'\040', '\143', '\150', '\040', '\061', '\012', '\144', '\102',
'\161', '\040', '\161', '\165', '\040', '\061', '\012', '\115',
'\161', '\161', '\040', '\161', '\165', '\040', '\061', '\012',
'\151', '\115', '\147', '\040', '\156', '\147', '\040', '\061',
'\012', '\127', '\167', '\163', '\040', '\163', '\164', '\040',
'\061', '\012', '\164', '\161', '\130', '\040', '\164', '\150',
'\040', '\061', '\012', '\170', '\150', '\104', '\040', '\164',
'\150', '\040', '\061', '\012', '\162', '\116', '\154', '\040',
'\145', '\162', '\040', '\061', '\012', '\160', '\127', '\144',
'\040', '\144', '\145', '\040', '\061', '\012', '\152', '\162',
'\126', '\040', '\145', '\162', '\040', '\061', '\012', '\102',
'\155', '\152', '\040', '\151', '\152', '\040', '\061', '\012',
'\110', '\155', '\161', '\040', '\161', '\165', '\040', '\061',
'\012', '\166', '\154', '\110', '\040', '\154', '\145', '\040',
'\061', '\012', '\115', '\170', '\142', '\040', '\142', '\145',
'\040', '\061', '\012', '\171', '\171', '\123', '\040', '\156',
'\171', '\040', '\061', '\012', '\161', '\166', '\127', '\040',
'\161', '\165', '\040', '\061', '\012', '\146', '\166', '\130',
'\040', '\166', '\141', '\040', '\061', '\012', '\126', '\146',
'\145', '\040', '\145', '\162', '\040', '\061', '\012', '\103',
'\144', '\167', '\040', '\144', '\145', '\040', '\061', '\012',
'\113', '\147', '\145', '\040', '\156', '\147', '\040', '\061',
'\012', '\121', '\145', '\152', '\040', '\145', '\162', '\040',
'\061', '\012', '\162', '\166', '\132', '\040', '\145', '\162',
'\040', '\061', '\012', '\166', '\172', '\111', '\040', '\163',
'\172', '\040', '\061', '\012', '\144', '\104', '\156', '\040',
'\141', '\156', '\040', '\061', '\012', '\156', '\167', '\123',
'\040', '\141', '\156', '\040', '\061', '\012', '\121', '\143',
'\142', '\040', '\143', '\150', '\040', '\061', '\012', '\167',
'\153', '\126', '\040', '\153', '\141', '\040', '\061', '\012',
'\165', '\103', '\170', '\040', '\161', '\165', '\040', '\061',
'\012', '\111', '\147', '\153', '\040', '\156', '\147', '\040',
'\061', '\012', '\126', '\160', '\155', '\040', '\155', '\145',
'\040', '\061', '\012', '\150', '\102', '\155', '\040', '\164',
'\150', '\040', '\061', '\012', '\160', '\144', '\121', '\040',
'\144', '\145', '\040', '\061', '\012', '\146', '\147', '\121',
'\040', '\156', '\147', '\040', '\061', '\012', '\171', '\121',
'\155', '\040', '\155', '\145', '\040', '\061', '\012', '\147',
'\170', '\110', '\040', '\156', '\147', '\040', '\061', '\012',
'\160', '\161', '\113', '\040', '\161', '\165', '\040', '\061',
'\012', '\154', '\122', '\143', '\040', '\143', '\150', '\040',
'\061', '\012', '\130', '\144', '\166', '\040', '\144', '\145',
'\040', '\061', '\012', '\150', '\104', '\172', '\040', '\164',
'\150', '\040', '\061', '\012', '\144', '\106', '\167', '\040',
'\144', '\145', '\040', '\061', '\012', '\161', '\121', '\165',
'\040', '\165', '\156', '\040', '\061', '\012', '\170', '\142',
'\104', '\040', '\142', '\145', '\040', '\061', '\012', '\161',
'\155', '\105', '\040', '\161', '\165', '\040', '\061', '\012',
'\155', '\127', '\155', '\040', '\155', '\145', '\040', '\061',
'\012', '\152', '\102', '\142', '\040', '\151', '\152', '\040',
'\061', '\012', '\152', '\130', '\164', '\040', '\164', '\150',
'\040', '\061', '\012', '\146', '\170', '\125', '\040', '\146',
};
extern const int ksizeofUniversalAmbigsFile = sizeof(kUniversalAmbigsFile);
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: genericvector.h
// Description: Generic vector class
// Author: Daria Antonova
// Created: Mon Jun 23 11:26:43 PDT 2008
//
// (C) Copyright 2007, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
//
#ifndef TESSERACT_CCUTIL_GENERICVECTOR_H_
#define TESSERACT_CCUTIL_GENERICVECTOR_H_
#include <assert.h>
#include <stdio.h>
#include <stdlib.h>
#include "tesscallback.h"
#include "errcode.h"
#include "helpers.h"
#include "ndminx.h"
#include "serialis.h"
#include "strngs.h"
// Use PointerVector<T> below in preference to GenericVector<T*>, as that
// provides automatic deletion of pointers, [De]Serialize that works, and
// sort that works.
template <typename T>
class GenericVector {
public:
GenericVector() {
init(kDefaultVectorSize);
}
GenericVector(int size, T init_val) {
init(size);
init_to_size(size, init_val);
}
// Copy
GenericVector(const GenericVector& other) {
this->init(other.size());
this->operator+=(other);
}
GenericVector<T> &operator+=(const GenericVector& other);
GenericVector<T> &operator=(const GenericVector& other);
~GenericVector();
// Reserve some memory.
void reserve(int size);
// Double the size of the internal array.
void double_the_size();
// Resizes to size and sets all values to t.
void init_to_size(int size, T t);
// Resizes to size without any initialization.
void resize_no_init(int size) {
reserve(size);
size_used_ = size;
}
// Return the size used.
int size() const {
return size_used_;
}
int size_reserved() const {
return size_reserved_;
}
int length() const {
return size_used_;
}
// Return true if empty.
bool empty() const {
return size_used_ == 0;
}
// Return the object from an index.
T &get(int index) const;
T &back() const;
T &operator[](int index) const;
// Returns the last object and removes it.
T pop_back();
// Return the index of the T object.
// This method NEEDS a compare_callback to be passed to
// set_compare_callback.
int get_index(T object) const;
// Return true if T is in the array
bool contains(T object) const;
// Return true if the index is valid
T contains_index(int index) const;
// Push an element in the end of the array
int push_back(T object);
void operator+=(T t);
// Push an element in the end of the array if the same
// element is not already contained in the array.
int push_back_new(T object);
// Push an element in the front of the array
// Note: This function is O(n)
int push_front(T object);
// Set the value at the given index
void set(T t, int index);
// Insert t at the given index, push other elements to the right.
void insert(T t, int index);
// Removes an element at the given index and
// shifts the remaining elements to the left.
void remove(int index);
// Truncates the array to the given size by removing the end.
// If the current size is less, the array is not expanded.
void truncate(int size) {
if (size < size_used_)
size_used_ = size;
}
// Add a callback to be called to delete the elements when the array took
// their ownership.
void set_clear_callback(TessCallback1<T>* cb);
// Add a callback to be called to compare the elements when needed (contains,
// get_id, ...)
void set_compare_callback(TessResultCallback2<bool, T const &, T const &>* cb);
// Clear the array, calling the clear callback function if any.
// All the owned callbacks are also deleted.
// If you don't want the callbacks to be deleted, before calling clear, set
// the callback to NULL.
void clear();
// Delete objects pointed to by data_[i]
void delete_data_pointers();
// This method clears the current object, then, does a shallow copy of
// its argument, and finally invalidates its argument.
// Callbacks are moved to the current object;
void move(GenericVector<T>* from);
// Read/Write the array to a file. This does _NOT_ read/write the callbacks.
// The callback given must be permanent since they will be called more than
// once. The given callback will be deleted at the end.
// If the callbacks are NULL, then the data is simply read/written using
// fread (and swapping)/fwrite.
// Returns false on error or if the callback returns false.
// DEPRECATED. Use [De]Serialize[Classes] instead.
bool write(FILE* f, TessResultCallback2<bool, FILE*, T const &>* cb) const;
bool read(FILE* f, TessResultCallback3<bool, FILE*, T*, bool>* cb, bool swap);
// Writes a vector of simple types to the given file. Assumes that bitwise
// read/write of T will work. Returns false in case of error.
// TODO(rays) Change all callers to use TFile and remove deprecated methods.
bool Serialize(FILE* fp) const;
bool Serialize(tesseract::TFile* fp) const;
// Reads a vector of simple types from the given file. Assumes that bitwise
// read/write will work with ReverseN according to sizeof(T).
// Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, FILE* fp);
bool DeSerialize(bool swap, tesseract::TFile* fp);
// Writes a vector of classes to the given file. Assumes the existence of
// bool T::Serialize(FILE* fp) const that returns false in case of error.
// Returns false in case of error.
bool SerializeClasses(FILE* fp) const;
bool SerializeClasses(tesseract::TFile* fp) const;
// Reads a vector of classes from the given file. Assumes the existence of
// bool T::Deserialize(bool swap, FILE* fp) that returns false in case of
// error. Also needs T::T() and T::T(constT&), as init_to_size is used in
// this function. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerializeClasses(bool swap, FILE* fp);
bool DeSerializeClasses(bool swap, tesseract::TFile* fp);
// Allocates a new array of double the current_size, copies over the
// information from data to the new location, deletes data and returns
// the pointed to the new larger array.
// This function uses memcpy to copy the data, instead of invoking
// operator=() for each element like double_the_size() does.
static T *double_the_size_memcpy(int current_size, T *data) {
T *data_new = new T[current_size * 2];
memcpy(data_new, data, sizeof(T) * current_size);
delete[] data;
return data_new;
}
// Reverses the elements of the vector.
void reverse() {
for (int i = 0; i < size_used_ / 2; ++i)
Swap(&data_[i], &data_[size_used_ - 1 - i]);
}
// Sorts the members of this vector using the less than comparator (cmp_lt),
// which compares the values. Useful for GenericVectors to primitive types.
// Will not work so great for pointers (unless you just want to sort some
// pointers). You need to provide a specialization to sort_cmp to use
// your type.
void sort();
// Sort the array into the order defined by the qsort function comparator.
// The comparator function is as defined by qsort, ie. it receives pointers
// to two Ts and returns negative if the first element is to appear earlier
// in the result and positive if it is to appear later, with 0 for equal.
void sort(int (*comparator)(const void*, const void*)) {
qsort(data_, size_used_, sizeof(*data_), comparator);
}
// Searches the array (assuming sorted in ascending order, using sort()) for
// an element equal to target and returns true if it is present.
// Use binary_search to get the index of target, or its nearest candidate.
bool bool_binary_search(const T& target) const {
int index = binary_search(target);
if (index >= size_used_)
return false;
return data_[index] == target;
}
// Searches the array (assuming sorted in ascending order, using sort()) for
// an element equal to target and returns the index of the best candidate.
// The return value is conceptually the largest index i such that
// data_[i] <= target or 0 if target < the whole vector.
// NOTE that this function uses operator> so really the return value is
// the largest index i such that data_[i] > target is false.
int binary_search(const T& target) const {
int bottom = 0;
int top = size_used_;
do {
int middle = (bottom + top) / 2;
if (data_[middle] > target)
top = middle;
else
bottom = middle;
}
while (top - bottom > 1);
return bottom;
}
// Compact the vector by deleting elements using operator!= on basic types.
// The vector must be sorted.
void compact_sorted() {
if (size_used_ == 0)
return;
// First element is in no matter what, hence the i = 1.
int last_write = 0;
for (int i = 1; i < size_used_; ++i) {
// Finds next unique item and writes it.
if (data_[last_write] != data_[i])
data_[++last_write] = data_[i];
}
// last_write is the index of a valid data cell, so add 1.
size_used_ = last_write + 1;
}
// Compact the vector by deleting elements for which delete_cb returns
// true. delete_cb is a permanent callback and will be deleted.
void compact(TessResultCallback1<bool, int>* delete_cb) {
int new_size = 0;
int old_index = 0;
// Until the callback returns true, the elements stay the same.
while (old_index < size_used_ && !delete_cb->Run(old_index++))
++new_size;
// Now just copy anything else that gets false from delete_cb.
for (; old_index < size_used_; ++old_index) {
if (!delete_cb->Run(old_index)) {
data_[new_size++] = data_[old_index];
}
}
size_used_ = new_size;
delete delete_cb;
}
T dot_product(const GenericVector<T>& other) const {
T result = static_cast<T>(0);
for (int i = MIN(size_used_, other.size_used_) - 1; i >= 0; --i)
result += data_[i] * other.data_[i];
return result;
}
// Returns the index of what would be the target_index_th item in the array
// if the members were sorted, without actually sorting. Members are
// shuffled around, but it takes O(n) time.
// NOTE: uses operator< and operator== on the members.
int choose_nth_item(int target_index) {
// Make sure target_index is legal.
if (target_index < 0)
target_index = 0; // ensure legal
else if (target_index >= size_used_)
target_index = size_used_ - 1;
unsigned int seed = 1;
return choose_nth_item(target_index, 0, size_used_, &seed);
}
// Swaps the elements with the given indices.
void swap(int index1, int index2) {
if (index1 != index2) {
T tmp = data_[index1];
data_[index1] = data_[index2];
data_[index2] = tmp;
}
}
// Returns true if all elements of *this are within the given range.
// Only uses operator<
bool WithinBounds(const T& rangemin, const T& rangemax) const {
for (int i = 0; i < size_used_; ++i) {
if (data_[i] < rangemin || rangemax < data_[i])
return false;
}
return true;
}
protected:
// Internal recursive version of choose_nth_item.
int choose_nth_item(int target_index, int start, int end, unsigned int* seed);
// Init the object, allocating size memory.
void init(int size);
// We are assuming that the object generally placed in thie
// vector are small enough that for efficiency it makes sence
// to start with a larger initial size.
static const int kDefaultVectorSize = 4;
inT32 size_used_;
inT32 size_reserved_;
T* data_;
TessCallback1<T>* clear_cb_;
// Mutable because Run method is not const
mutable TessResultCallback2<bool, T const &, T const &>* compare_cb_;
};
namespace tesseract {
// Function to read a GenericVector<char> from a whole file.
// Returns false on failure.
typedef bool (*FileReader)(const STRING& filename, GenericVector<char>* data);
// Function to write a GenericVector<char> to a whole file.
// Returns false on failure.
typedef bool (*FileWriter)(const GenericVector<char>& data,
const STRING& filename);
// The default FileReader loads the whole file into the vector of char,
// returning false on error.
inline bool LoadDataFromFile(const STRING& filename,
GenericVector<char>* data) {
FILE* fp = fopen(filename.string(), "rb");
if (fp == NULL) return false;
fseek(fp, 0, SEEK_END);
size_t size = ftell(fp);
fseek(fp, 0, SEEK_SET);
// Pad with a 0, just in case we treat the result as a string.
data->init_to_size(size + 1, 0);
bool result = fread(&(*data)[0], 1, size, fp) == size;
fclose(fp);
return result;
}
// The default FileWriter writes the vector of char to the filename file,
// returning false on error.
inline bool SaveDataToFile(const GenericVector<char>& data,
const STRING& filename) {
FILE* fp = fopen(filename.string(), "wb");
if (fp == NULL) return false;
bool result =
static_cast<int>(fwrite(&data[0], 1, data.size(), fp)) == data.size();
fclose(fp);
return result;
}
template <typename T>
bool cmp_eq(T const & t1, T const & t2) {
return t1 == t2;
}
// Used by sort()
// return < 0 if t1 < t2
// return 0 if t1 == t2
// return > 0 if t1 > t2
template <typename T>
int sort_cmp(const void* t1, const void* t2) {
const T* a = static_cast<const T *> (t1);
const T* b = static_cast<const T *> (t2);
if (*a < *b) {
return -1;
} else if (*b < *a) {
return 1;
} else {
return 0;
}
}
// Used by PointerVector::sort()
// return < 0 if t1 < t2
// return 0 if t1 == t2
// return > 0 if t1 > t2
template <typename T>
int sort_ptr_cmp(const void* t1, const void* t2) {
const T* a = *reinterpret_cast<T * const *>(t1);
const T* b = *reinterpret_cast<T * const *>(t2);
if (*a < *b) {
return -1;
} else if (*b < *a) {
return 1;
} else {
return 0;
}
}
// Subclass for a vector of pointers. Use in preference to GenericVector<T*>
// as it provides automatic deletion and correct serialization, with the
// corollary that all copy operations are deep copies of the pointed-to objects.
template<typename T>
class PointerVector : public GenericVector<T*> {
public:
PointerVector() : GenericVector<T*>() { }
explicit PointerVector(int size) : GenericVector<T*>(size) { }
~PointerVector() {
// Clear must be called here, even though it is called again by the base,
// as the base will call the wrong clear.
clear();
}
// Copy must be deep, as the pointers will be automatically deleted on
// destruction.
PointerVector(const PointerVector& other) {
this->init(other.size());
this->operator+=(other);
}
PointerVector<T>& operator+=(const PointerVector& other) {
this->reserve(this->size_used_ + other.size_used_);
for (int i = 0; i < other.size(); ++i) {
this->push_back(new T(*other.data_[i]));
}
return *this;
}
PointerVector<T>& operator=(const PointerVector& other) {
this->truncate(0);
this->operator+=(other);
return *this;
}
// Removes an element at the given index and
// shifts the remaining elements to the left.
void remove(int index) {
delete GenericVector<T*>::data_[index];
GenericVector<T*>::remove(index);
}
// Truncates the array to the given size by removing the end.
// If the current size is less, the array is not expanded.
void truncate(int size) {
for (int i = size; i < GenericVector<T*>::size_used_; ++i)
delete GenericVector<T*>::data_[i];
GenericVector<T*>::truncate(size);
}
// Compact the vector by deleting elements for which delete_cb returns
// true. delete_cb is a permanent callback and will be deleted.
void compact(TessResultCallback1<bool, const T*>* delete_cb) {
int new_size = 0;
int old_index = 0;
// Until the callback returns true, the elements stay the same.
while (old_index < GenericVector<T*>::size_used_ &&
!delete_cb->Run(GenericVector<T*>::data_[old_index++]))
++new_size;
// Now just copy anything else that gets false from delete_cb.
for (; old_index < GenericVector<T*>::size_used_; ++old_index) {
if (!delete_cb->Run(GenericVector<T*>::data_[old_index])) {
GenericVector<T*>::data_[new_size++] =
GenericVector<T*>::data_[old_index];
} else {
delete GenericVector<T*>::data_[old_index];
}
}
GenericVector<T*>::size_used_ = new_size;
delete delete_cb;
}
// Clear the array, calling the clear callback function if any.
// All the owned callbacks are also deleted.
// If you don't want the callbacks to be deleted, before calling clear, set
// the callback to NULL.
void clear() {
GenericVector<T*>::delete_data_pointers();
GenericVector<T*>::clear();
}
// Writes a vector of (pointers to) classes to the given file. Assumes the
// existence of bool T::Serialize(FILE*) const that returns false in case of
// error. There is no Serialize for simple types, as you would have a
// normal GenericVector of those.
// Returns false in case of error.
bool Serialize(FILE* fp) const {
inT32 used = GenericVector<T*>::size_used_;
if (fwrite(&used, sizeof(used), 1, fp) != 1) return false;
for (int i = 0; i < used; ++i) {
inT8 non_null = GenericVector<T*>::data_[i] != NULL;
if (fwrite(&non_null, sizeof(non_null), 1, fp) != 1) return false;
if (non_null && !GenericVector<T*>::data_[i]->Serialize(fp)) return false;
}
return true;
}
bool Serialize(TFile* fp) const {
inT32 used = GenericVector<T*>::size_used_;
if (fp->FWrite(&used, sizeof(used), 1) != 1) return false;
for (int i = 0; i < used; ++i) {
inT8 non_null = GenericVector<T*>::data_[i] != NULL;
if (fp->FWrite(&non_null, sizeof(non_null), 1) != 1) return false;
if (non_null && !GenericVector<T*>::data_[i]->Serialize(fp)) return false;
}
return true;
}
// Reads a vector of (pointers to) classes to the given file. Assumes the
// existence of bool T::DeSerialize(bool, Tfile*) const that returns false in
// case of error. There is no Serialize for simple types, as you would have a
// normal GenericVector of those.
// If swap is true, assumes a big/little-endian swap is needed.
// Also needs T::T(), as new T is used in this function.
// Returns false in case of error.
bool DeSerialize(bool swap, FILE* fp) {
inT32 reserved;
if (fread(&reserved, sizeof(reserved), 1, fp) != 1) return false;
if (swap) Reverse32(&reserved);
GenericVector<T*>::reserve(reserved);
truncate(0);
for (int i = 0; i < reserved; ++i) {
inT8 non_null;
if (fread(&non_null, sizeof(non_null), 1, fp) != 1) return false;
T* item = NULL;
if (non_null) {
item = new T;
if (!item->DeSerialize(swap, fp)) {
delete item;
return false;
}
this->push_back(item);
} else {
// Null elements should keep their place in the vector.
this->push_back(NULL);
}
}
return true;
}
bool DeSerialize(bool swap, TFile* fp) {
inT32 reserved;
if (fp->FRead(&reserved, sizeof(reserved), 1) != 1) return false;
if (swap) Reverse32(&reserved);
GenericVector<T*>::reserve(reserved);
truncate(0);
for (int i = 0; i < reserved; ++i) {
inT8 non_null;
if (fp->FRead(&non_null, sizeof(non_null), 1) != 1) return false;
T* item = NULL;
if (non_null) {
item = new T;
if (!item->DeSerialize(swap, fp)) {
delete item;
return false;
}
this->push_back(item);
} else {
// Null elements should keep their place in the vector.
this->push_back(NULL);
}
}
return true;
}
// Sorts the items pointed to by the members of this vector using
// t::operator<().
void sort() {
sort(&sort_ptr_cmp<T>);
}
};
} // namespace tesseract
// A useful vector that uses operator== to do comparisons.
template <typename T>
class GenericVectorEqEq : public GenericVector<T> {
public:
GenericVectorEqEq() {
GenericVector<T>::set_compare_callback(
NewPermanentTessCallback(tesseract::cmp_eq<T>));
}
GenericVectorEqEq(int size) : GenericVector<T>(size) {
GenericVector<T>::set_compare_callback(
NewPermanentTessCallback(tesseract::cmp_eq<T>));
}
};
template <typename T>
void GenericVector<T>::init(int size) {
size_used_ = 0;
size_reserved_ = 0;
data_ = 0;
clear_cb_ = 0;
compare_cb_ = 0;
reserve(size);
}
template <typename T>
GenericVector<T>::~GenericVector() {
clear();
}
// Reserve some memory. If the internal array contains elements, they are
// copied.
template <typename T>
void GenericVector<T>::reserve(int size) {
if (size_reserved_ >= size || size <= 0)
return;
T* new_array = new T[size];
for (int i = 0; i < size_used_; ++i)
new_array[i] = data_[i];
if (data_ != NULL) delete[] data_;
data_ = new_array;
size_reserved_ = size;
}
template <typename T>
void GenericVector<T>::double_the_size() {
if (size_reserved_ == 0) {
reserve(kDefaultVectorSize);
}
else {
reserve(2 * size_reserved_);
}
}
// Resizes to size and sets all values to t.
template <typename T>
void GenericVector<T>::init_to_size(int size, T t) {
reserve(size);
size_used_ = size;
for (int i = 0; i < size; ++i)
data_[i] = t;
}
// Return the object from an index.
template <typename T>
T &GenericVector<T>::get(int index) const {
ASSERT_HOST(index >= 0 && index < size_used_);
return data_[index];
}
template <typename T>
T &GenericVector<T>::operator[](int index) const {
assert(index >= 0 && index < size_used_);
return data_[index];
}
template <typename T>
T &GenericVector<T>::back() const {
ASSERT_HOST(size_used_ > 0);
return data_[size_used_ - 1];
}
// Returns the last object and removes it.
template <typename T>
T GenericVector<T>::pop_back() {
ASSERT_HOST(size_used_ > 0);
return data_[--size_used_];
}
// Return the object from an index.
template <typename T>
void GenericVector<T>::set(T t, int index) {
ASSERT_HOST(index >= 0 && index < size_used_);
data_[index] = t;
}
// Shifts the rest of the elements to the right to make
// space for the new elements and inserts the given element
// at the specified index.
template <typename T>
void GenericVector<T>::insert(T t, int index) {
ASSERT_HOST(index >= 0 && index <= size_used_);
if (size_reserved_ == size_used_)
double_the_size();
for (int i = size_used_; i > index; --i) {
data_[i] = data_[i-1];
}
data_[index] = t;
size_used_++;
}
// Removes an element at the given index and
// shifts the remaining elements to the left.
template <typename T>
void GenericVector<T>::remove(int index) {
ASSERT_HOST(index >= 0 && index < size_used_);
for (int i = index; i < size_used_ - 1; ++i) {
data_[i] = data_[i+1];
}
size_used_--;
}
// Return true if the index is valindex
template <typename T>
T GenericVector<T>::contains_index(int index) const {
return index >= 0 && index < size_used_;
}
// Return the index of the T object.
template <typename T>
int GenericVector<T>::get_index(T object) const {
for (int i = 0; i < size_used_; ++i) {
ASSERT_HOST(compare_cb_ != NULL);
if (compare_cb_->Run(object, data_[i]))
return i;
}
return -1;
}
// Return true if T is in the array
template <typename T>
bool GenericVector<T>::contains(T object) const {
return get_index(object) != -1;
}
// Add an element in the array
template <typename T>
int GenericVector<T>::push_back(T object) {
int index = 0;
if (size_used_ == size_reserved_)
double_the_size();
index = size_used_++;
data_[index] = object;
return index;
}
template <typename T>
int GenericVector<T>::push_back_new(T object) {
int index = get_index(object);
if (index >= 0)
return index;
return push_back(object);
}
// Add an element in the array (front)
template <typename T>
int GenericVector<T>::push_front(T object) {
if (size_used_ == size_reserved_)
double_the_size();
for (int i = size_used_; i > 0; --i)
data_[i] = data_[i-1];
data_[0] = object;
++size_used_;
return 0;
}
template <typename T>
void GenericVector<T>::operator+=(T t) {
push_back(t);
}
template <typename T>
GenericVector<T> &GenericVector<T>::operator+=(const GenericVector& other) {
this->reserve(size_used_ + other.size_used_);
for (int i = 0; i < other.size(); ++i) {
this->operator+=(other.data_[i]);
}
return *this;
}
template <typename T>
GenericVector<T> &GenericVector<T>::operator=(const GenericVector& other) {
this->truncate(0);
this->operator+=(other);
return *this;
}
// Add a callback to be called to delete the elements when the array took
// their ownership.
template <typename T>
void GenericVector<T>::set_clear_callback(TessCallback1<T>* cb) {
clear_cb_ = cb;
}
// Add a callback to be called to delete the elements when the array took
// their ownership.
template <typename T>
void GenericVector<T>::set_compare_callback(
TessResultCallback2<bool, T const &, T const &>* cb) {
compare_cb_ = cb;
}
// Clear the array, calling the callback function if any.
template <typename T>
void GenericVector<T>::clear() {
if (size_reserved_ > 0) {
if (clear_cb_ != NULL)
for (int i = 0; i < size_used_; ++i)
clear_cb_->Run(data_[i]);
delete[] data_;
data_ = NULL;
size_used_ = 0;
size_reserved_ = 0;
}
if (clear_cb_ != NULL) {
delete clear_cb_;
clear_cb_ = NULL;
}
if (compare_cb_ != NULL) {
delete compare_cb_;
compare_cb_ = NULL;
}
}
template <typename T>
void GenericVector<T>::delete_data_pointers() {
for (int i = 0; i < size_used_; ++i)
if (data_[i]) {
delete data_[i];
}
}
template <typename T>
bool GenericVector<T>::write(
FILE* f, TessResultCallback2<bool, FILE*, T const &>* cb) const {
if (fwrite(&size_reserved_, sizeof(size_reserved_), 1, f) != 1) return false;
if (fwrite(&size_used_, sizeof(size_used_), 1, f) != 1) return false;
if (cb != NULL) {
for (int i = 0; i < size_used_; ++i) {
if (!cb->Run(f, data_[i])) {
delete cb;
return false;
}
}
delete cb;
} else {
if (fwrite(data_, sizeof(T), size_used_, f) != size_used_) return false;
}
return true;
}
template <typename T>
bool GenericVector<T>::read(FILE* f,
TessResultCallback3<bool, FILE*, T*, bool>* cb,
bool swap) {
inT32 reserved;
if (fread(&reserved, sizeof(reserved), 1, f) != 1) return false;
if (swap) Reverse32(&reserved);
reserve(reserved);
if (fread(&size_used_, sizeof(size_used_), 1, f) != 1) return false;
if (swap) Reverse32(&size_used_);
if (cb != NULL) {
for (int i = 0; i < size_used_; ++i) {
if (!cb->Run(f, data_ + i, swap)) {
delete cb;
return false;
}
}
delete cb;
} else {
if (fread(data_, sizeof(T), size_used_, f) != size_used_) return false;
if (swap) {
for (int i = 0; i < size_used_; ++i)
ReverseN(&data_[i], sizeof(T));
}
}
return true;
}
// Writes a vector of simple types to the given file. Assumes that bitwise
// read/write of T will work. Returns false in case of error.
template <typename T>
bool GenericVector<T>::Serialize(FILE* fp) const {
if (fwrite(&size_used_, sizeof(size_used_), 1, fp) != 1) return false;
if (fwrite(data_, sizeof(*data_), size_used_, fp) != size_used_) return false;
return true;
}
template <typename T>
bool GenericVector<T>::Serialize(tesseract::TFile* fp) const {
if (fp->FWrite(&size_used_, sizeof(size_used_), 1) != 1) return false;
if (fp->FWrite(data_, sizeof(*data_), size_used_) != size_used_) return false;
return true;
}
// Reads a vector of simple types from the given file. Assumes that bitwise
// read/write will work with ReverseN according to sizeof(T).
// Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
template <typename T>
bool GenericVector<T>::DeSerialize(bool swap, FILE* fp) {
inT32 reserved;
if (fread(&reserved, sizeof(reserved), 1, fp) != 1) return false;
if (swap) Reverse32(&reserved);
reserve(reserved);
size_used_ = reserved;
if (fread(data_, sizeof(T), size_used_, fp) != size_used_) return false;
if (swap) {
for (int i = 0; i < size_used_; ++i)
ReverseN(&data_[i], sizeof(data_[i]));
}
return true;
}
template <typename T>
bool GenericVector<T>::DeSerialize(bool swap, tesseract::TFile* fp) {
inT32 reserved;
if (fp->FRead(&reserved, sizeof(reserved), 1) != 1) return false;
if (swap) Reverse32(&reserved);
reserve(reserved);
size_used_ = reserved;
if (fp->FRead(data_, sizeof(T), size_used_) != size_used_) return false;
if (swap) {
for (int i = 0; i < size_used_; ++i)
ReverseN(&data_[i], sizeof(data_[i]));
}
return true;
}
// Writes a vector of classes to the given file. Assumes the existence of
// bool T::Serialize(FILE* fp) const that returns false in case of error.
// Returns false in case of error.
template <typename T>
bool GenericVector<T>::SerializeClasses(FILE* fp) const {
if (fwrite(&size_used_, sizeof(size_used_), 1, fp) != 1) return false;
for (int i = 0; i < size_used_; ++i) {
if (!data_[i].Serialize(fp)) return false;
}
return true;
}
template <typename T>
bool GenericVector<T>::SerializeClasses(tesseract::TFile* fp) const {
if (fp->FWrite(&size_used_, sizeof(size_used_), 1) != 1) return false;
for (int i = 0; i < size_used_; ++i) {
if (!data_[i].Serialize(fp)) return false;
}
return true;
}
// Reads a vector of classes from the given file. Assumes the existence of
// bool T::Deserialize(bool swap, FILE* fp) that returns false in case of
// error. Alse needs T::T() and T::T(constT&), as init_to_size is used in
// this function. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
template <typename T>
bool GenericVector<T>::DeSerializeClasses(bool swap, FILE* fp) {
uinT32 reserved;
if (fread(&reserved, sizeof(reserved), 1, fp) != 1) return false;
if (swap) Reverse32(&reserved);
T empty;
init_to_size(reserved, empty);
for (int i = 0; i < reserved; ++i) {
if (!data_[i].DeSerialize(swap, fp)) return false;
}
return true;
}
template <typename T>
bool GenericVector<T>::DeSerializeClasses(bool swap, tesseract::TFile* fp) {
uinT32 reserved;
if (fp->FRead(&reserved, sizeof(reserved), 1) != 1) return false;
if (swap) Reverse32(&reserved);
T empty;
init_to_size(reserved, empty);
for (int i = 0; i < reserved; ++i) {
if (!data_[i].DeSerialize(swap, fp)) return false;
}
return true;
}
// This method clear the current object, then, does a shallow copy of
// its argument, and finally invalidates its argument.
template <typename T>
void GenericVector<T>::move(GenericVector<T>* from) {
this->clear();
this->data_ = from->data_;
this->size_reserved_ = from->size_reserved_;
this->size_used_ = from->size_used_;
this->compare_cb_ = from->compare_cb_;
this->clear_cb_ = from->clear_cb_;
from->data_ = NULL;
from->clear_cb_ = NULL;
from->compare_cb_ = NULL;
from->size_used_ = 0;
from->size_reserved_ = 0;
}
template <typename T>
void GenericVector<T>::sort() {
sort(&tesseract::sort_cmp<T>);
}
// Internal recursive version of choose_nth_item.
// The algorithm used comes from "Algorithms" by Sedgewick:
// http://books.google.com/books/about/Algorithms.html?id=idUdqdDXqnAC
// The principle is to choose a random pivot, and move everything less than
// the pivot to its left, and everything greater than the pivot to the end
// of the array, then recurse on the part that contains the desired index, or
// just return the answer if it is in the equal section in the middle.
// The random pivot guarantees average linear time for the same reason that
// n times vector::push_back takes linear time on average.
// target_index, start and and end are all indices into the full array.
// Seed is a seed for rand_r for thread safety purposes. Its value is
// unimportant as the random numbers do not affect the result except
// between equal answers.
template <typename T>
int GenericVector<T>::choose_nth_item(int target_index, int start, int end,
unsigned int* seed) {
// Number of elements to process.
int num_elements = end - start;
// Trivial cases.
if (num_elements <= 1)
return start;
if (num_elements == 2) {
if (data_[start] < data_[start + 1]) {
return target_index > start ? start + 1 : start;
} else {
return target_index > start ? start : start + 1;
}
}
// Place the pivot at start.
#ifndef rand_r // _MSC_VER, ANDROID
srand(*seed);
#define rand_r(seed) rand()
#endif // _MSC_VER
int pivot = rand_r(seed) % num_elements + start;
swap(pivot, start);
// The invariant condition here is that items [start, next_lesser) are less
// than the pivot (which is at index next_lesser) and items
// [prev_greater, end) are greater than the pivot, with items
// [next_lesser, prev_greater) being equal to the pivot.
int next_lesser = start;
int prev_greater = end;
for (int next_sample = start + 1; next_sample < prev_greater;) {
if (data_[next_sample] < data_[next_lesser]) {
swap(next_lesser++, next_sample++);
} else if (data_[next_sample] == data_[next_lesser]) {
++next_sample;
} else {
swap(--prev_greater, next_sample);
}
}
// Now the invariant is set up, we recurse on just the section that contains
// the desired index.
if (target_index < next_lesser)
return choose_nth_item(target_index, start, next_lesser, seed);
else if (target_index < prev_greater)
return next_lesser; // In equal bracket.
else
return choose_nth_item(target_index, prev_greater, end, seed);
}
#endif // TESSERACT_CCUTIL_GENERICVECTOR_H_
| C++ |
/**********************************************************************
* File: clst.h (Formerly clist.h)
* Description: CONS cell list module include file.
* Author: Phil Cheatle
* Created: Mon Jan 28 08:33:13 GMT 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef CLST_H
#define CLST_H
#include <stdio.h>
#include "host.h"
#include "serialis.h"
#include "lsterr.h"
class CLIST_ITERATOR;
/**********************************************************************
* CLASS - CLIST_LINK
*
* Generic link class for singly linked CONS cell lists
*
* Note: No destructor - elements are assumed to be destroyed EITHER after
* they have been extracted from a list OR by the CLIST destructor which
* walks the list.
**********************************************************************/
class DLLSYM CLIST_LINK
{
friend class CLIST_ITERATOR;
friend class CLIST;
CLIST_LINK *next;
void *data;
public:
CLIST_LINK() { //constructor
data = next = NULL;
}
CLIST_LINK( //copy constructor
const CLIST_LINK &) { //dont copy link
data = next = NULL;
}
void operator= ( //dont copy links
const CLIST_LINK &) {
data = next = NULL;
}
};
/**********************************************************************
* CLASS - CLIST
*
* Generic list class for singly linked CONS cell lists
**********************************************************************/
class DLLSYM CLIST
{
friend class CLIST_ITERATOR;
CLIST_LINK *last; //End of list
//(Points to head)
CLIST_LINK *First() { // return first
return last != NULL ? last->next : NULL;
}
public:
CLIST() { //constructor
last = NULL;
}
~CLIST () { //destructor
shallow_clear();
}
void internal_deep_clear ( //destroy all links
void (*zapper) (void *)); //ptr to zapper functn
void shallow_clear(); //clear list but dont
//delete data elements
bool empty() const { //is list empty?
return !last;
}
bool singleton() const {
return last != NULL ? (last == last->next) : false;
}
void shallow_copy( //dangerous!!
CLIST *from_list) { //beware destructors!!
last = from_list->last;
}
void assign_to_sublist( //to this list
CLIST_ITERATOR *start_it, //from list start
CLIST_ITERATOR *end_it); //from list end
inT32 length() const; //# elements in list
void sort ( //sort elements
int comparator ( //comparison routine
const void *, const void *));
// Assuming list has been sorted already, insert new_data to
// keep the list sorted according to the same comparison function.
// Comparision function is the same as used by sort, i.e. uses double
// indirection. Time is O(1) to add to beginning or end.
// Time is linear to add pre-sorted items to an empty list.
// If unique, then don't add duplicate entries.
// Returns true if the element was added to the list.
bool add_sorted(int comparator(const void*, const void*),
bool unique, void* new_data);
// Assuming that the minuend and subtrahend are already sorted with
// the same comparison function, shallow clears this and then copies
// the set difference minuend - subtrahend to this, being the elements
// of minuend that do not compare equal to anything in subtrahend.
// If unique is true, any duplicates in minuend are also eliminated.
void set_subtract(int comparator(const void*, const void*), bool unique,
CLIST* minuend, CLIST* subtrahend);
};
/***********************************************************************
* CLASS - CLIST_ITERATOR
*
* Generic iterator class for singly linked lists with embedded links
**********************************************************************/
class DLLSYM CLIST_ITERATOR
{
friend void CLIST::assign_to_sublist(CLIST_ITERATOR *, CLIST_ITERATOR *);
CLIST *list; //List being iterated
CLIST_LINK *prev; //prev element
CLIST_LINK *current; //current element
CLIST_LINK *next; //next element
BOOL8 ex_current_was_last; //current extracted
//was end of list
BOOL8 ex_current_was_cycle_pt; //current extracted
//was cycle point
CLIST_LINK *cycle_pt; //point we are cycling
//the list to.
BOOL8 started_cycling; //Have we moved off
//the start?
CLIST_LINK *extract_sublist( //from this current...
CLIST_ITERATOR *other_it); //to other current
public:
CLIST_ITERATOR() { //constructor
list = NULL;
} //unassigned list
CLIST_ITERATOR( //constructor
CLIST *list_to_iterate);
void set_to_list( //change list
CLIST *list_to_iterate);
void add_after_then_move( //add after current &
void *new_data); //move to new
void add_after_stay_put( //add after current &
void *new_data); //stay at current
void add_before_then_move( //add before current &
void *new_data); //move to new
void add_before_stay_put( //add before current &
void *new_data); //stay at current
void add_list_after( //add a list &
CLIST *list_to_add); //stay at current
void add_list_before( //add a list &
CLIST *list_to_add); //move to it 1st item
void *data() { //get current data
#ifndef NDEBUG
if (!list)
NO_LIST.error ("CLIST_ITERATOR::data", ABORT, NULL);
if (!current)
NULL_DATA.error ("CLIST_ITERATOR::data", ABORT, NULL);
#endif
return current->data;
}
void *data_relative( //get data + or - ...
inT8 offset); //offset from current
void *forward(); //move to next element
void *extract(); //remove from list
void *move_to_first(); //go to start of list
void *move_to_last(); //go to end of list
void mark_cycle_pt(); //remember current
BOOL8 empty() { //is list empty?
#ifndef NDEBUG
if (!list)
NO_LIST.error ("CLIST_ITERATOR::empty", ABORT, NULL);
#endif
return list->empty ();
}
BOOL8 current_extracted() { //current extracted?
return !current;
}
BOOL8 at_first(); //Current is first?
BOOL8 at_last(); //Current is last?
BOOL8 cycled_list(); //Completed a cycle?
void add_to_end( //add at end &
void *new_data); //dont move
void exchange( //positions of 2 links
CLIST_ITERATOR *other_it); //other iterator
inT32 length(); //# elements in list
void sort ( //sort elements
int comparator ( //comparison routine
const void *, const void *));
};
/***********************************************************************
* CLIST_ITERATOR::set_to_list
*
* (Re-)initialise the iterator to point to the start of the list_to_iterate
* over.
**********************************************************************/
inline void CLIST_ITERATOR::set_to_list( //change list
CLIST *list_to_iterate) {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::set_to_list", ABORT, NULL);
if (!list_to_iterate)
BAD_PARAMETER.error ("CLIST_ITERATOR::set_to_list", ABORT,
"list_to_iterate is NULL");
#endif
list = list_to_iterate;
prev = list->last;
current = list->First ();
next = current != NULL ? current->next : NULL;
cycle_pt = NULL; //await explicit set
started_cycling = FALSE;
ex_current_was_last = FALSE;
ex_current_was_cycle_pt = FALSE;
}
/***********************************************************************
* CLIST_ITERATOR::CLIST_ITERATOR
*
* CONSTRUCTOR - set iterator to specified list;
**********************************************************************/
inline CLIST_ITERATOR::CLIST_ITERATOR(CLIST *list_to_iterate) {
set_to_list(list_to_iterate);
}
/***********************************************************************
* CLIST_ITERATOR::add_after_then_move
*
* Add a new element to the list after the current element and move the
* iterator to the new element.
**********************************************************************/
inline void CLIST_ITERATOR::add_after_then_move( // element to add
void *new_data) {
CLIST_LINK *new_element;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_after_then_move", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_after_then_move", ABORT, NULL);
if (!new_data)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_after_then_move", ABORT,
"new_data is NULL");
#endif
new_element = new CLIST_LINK;
new_element->data = new_data;
if (list->empty ()) {
new_element->next = new_element;
list->last = new_element;
prev = next = new_element;
}
else {
new_element->next = next;
if (current) { //not extracted
current->next = new_element;
prev = current;
if (current == list->last)
list->last = new_element;
}
else { //current extracted
prev->next = new_element;
if (ex_current_was_last)
list->last = new_element;
if (ex_current_was_cycle_pt)
cycle_pt = new_element;
}
}
current = new_element;
}
/***********************************************************************
* CLIST_ITERATOR::add_after_stay_put
*
* Add a new element to the list after the current element but do not move
* the iterator to the new element.
**********************************************************************/
inline void CLIST_ITERATOR::add_after_stay_put( // element to add
void *new_data) {
CLIST_LINK *new_element;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_after_stay_put", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_after_stay_put", ABORT, NULL);
if (!new_data)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_after_stay_put", ABORT,
"new_data is NULL");
#endif
new_element = new CLIST_LINK;
new_element->data = new_data;
if (list->empty ()) {
new_element->next = new_element;
list->last = new_element;
prev = next = new_element;
ex_current_was_last = FALSE;
current = NULL;
}
else {
new_element->next = next;
if (current) { //not extracted
current->next = new_element;
if (prev == current)
prev = new_element;
if (current == list->last)
list->last = new_element;
}
else { //current extracted
prev->next = new_element;
if (ex_current_was_last) {
list->last = new_element;
ex_current_was_last = FALSE;
}
}
next = new_element;
}
}
/***********************************************************************
* CLIST_ITERATOR::add_before_then_move
*
* Add a new element to the list before the current element and move the
* iterator to the new element.
**********************************************************************/
inline void CLIST_ITERATOR::add_before_then_move( // element to add
void *new_data) {
CLIST_LINK *new_element;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_before_then_move", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_before_then_move", ABORT, NULL);
if (!new_data)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_before_then_move", ABORT,
"new_data is NULL");
#endif
new_element = new CLIST_LINK;
new_element->data = new_data;
if (list->empty ()) {
new_element->next = new_element;
list->last = new_element;
prev = next = new_element;
}
else {
prev->next = new_element;
if (current) { //not extracted
new_element->next = current;
next = current;
}
else { //current extracted
new_element->next = next;
if (ex_current_was_last)
list->last = new_element;
if (ex_current_was_cycle_pt)
cycle_pt = new_element;
}
}
current = new_element;
}
/***********************************************************************
* CLIST_ITERATOR::add_before_stay_put
*
* Add a new element to the list before the current element but dont move the
* iterator to the new element.
**********************************************************************/
inline void CLIST_ITERATOR::add_before_stay_put( // element to add
void *new_data) {
CLIST_LINK *new_element;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_before_stay_put", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_before_stay_put", ABORT, NULL);
if (!new_data)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_before_stay_put", ABORT,
"new_data is NULL");
#endif
new_element = new CLIST_LINK;
new_element->data = new_data;
if (list->empty ()) {
new_element->next = new_element;
list->last = new_element;
prev = next = new_element;
ex_current_was_last = TRUE;
current = NULL;
}
else {
prev->next = new_element;
if (current) { //not extracted
new_element->next = current;
if (next == current)
next = new_element;
}
else { //current extracted
new_element->next = next;
if (ex_current_was_last)
list->last = new_element;
}
prev = new_element;
}
}
/***********************************************************************
* CLIST_ITERATOR::add_list_after
*
* Insert another list to this list after the current element but dont move the
* iterator.
**********************************************************************/
inline void CLIST_ITERATOR::add_list_after(CLIST *list_to_add) {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_list_after", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_list_after", ABORT, NULL);
if (!list_to_add)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_list_after", ABORT,
"list_to_add is NULL");
#endif
if (!list_to_add->empty ()) {
if (list->empty ()) {
list->last = list_to_add->last;
prev = list->last;
next = list->First ();
ex_current_was_last = TRUE;
current = NULL;
}
else {
if (current) { //not extracted
current->next = list_to_add->First ();
if (current == list->last)
list->last = list_to_add->last;
list_to_add->last->next = next;
next = current->next;
}
else { //current extracted
prev->next = list_to_add->First ();
if (ex_current_was_last) {
list->last = list_to_add->last;
ex_current_was_last = FALSE;
}
list_to_add->last->next = next;
next = prev->next;
}
}
list_to_add->last = NULL;
}
}
/***********************************************************************
* CLIST_ITERATOR::add_list_before
*
* Insert another list to this list before the current element. Move the
* iterator to the start of the inserted elements
* iterator.
**********************************************************************/
inline void CLIST_ITERATOR::add_list_before(CLIST *list_to_add) {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_list_before", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_list_before", ABORT, NULL);
if (!list_to_add)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_list_before", ABORT,
"list_to_add is NULL");
#endif
if (!list_to_add->empty ()) {
if (list->empty ()) {
list->last = list_to_add->last;
prev = list->last;
current = list->First ();
next = current->next;
ex_current_was_last = FALSE;
}
else {
prev->next = list_to_add->First ();
if (current) { //not extracted
list_to_add->last->next = current;
}
else { //current extracted
list_to_add->last->next = next;
if (ex_current_was_last)
list->last = list_to_add->last;
if (ex_current_was_cycle_pt)
cycle_pt = prev->next;
}
current = prev->next;
next = current->next;
}
list_to_add->last = NULL;
}
}
/***********************************************************************
* CLIST_ITERATOR::extract
*
* Do extraction by removing current from the list, deleting the cons cell
* and returning the data to the caller, but NOT updating the iterator. (So
* that any calling loop can do this.) The iterator's current points to
* NULL. If the data is to be deleted, this is the callers responsibility.
**********************************************************************/
inline void *CLIST_ITERATOR::extract() {
void *extracted_data;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::extract", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::extract", ABORT, NULL);
if (!current) //list empty or
//element extracted
NULL_CURRENT.error ("CLIST_ITERATOR::extract",
ABORT, NULL);
#endif
if (list->singleton()) {
// Special case where we do need to change the iterator.
prev = next = list->last = NULL;
} else {
prev->next = next; //remove from list
if (current == list->last) {
list->last = prev;
ex_current_was_last = TRUE;
} else {
ex_current_was_last = FALSE;
}
}
// Always set ex_current_was_cycle_pt so an add/forward will work in a loop.
ex_current_was_cycle_pt = (current == cycle_pt) ? TRUE : FALSE;
extracted_data = current->data;
delete(current); //destroy CONS cell
current = NULL;
return extracted_data;
}
/***********************************************************************
* CLIST_ITERATOR::move_to_first()
*
* Move current so that it is set to the start of the list.
* Return data just in case anyone wants it.
**********************************************************************/
inline void *CLIST_ITERATOR::move_to_first() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::move_to_first", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::move_to_first", ABORT, NULL);
#endif
current = list->First ();
prev = list->last;
next = current != NULL ? current->next : NULL;
return current != NULL ? current->data : NULL;
}
/***********************************************************************
* CLIST_ITERATOR::mark_cycle_pt()
*
* Remember the current location so that we can tell whether we've returned
* to this point later.
*
* If the current point is deleted either now, or in the future, the cycle
* point will be set to the next item which is set to current. This could be
* by a forward, add_after_then_move or add_after_then_move.
**********************************************************************/
inline void CLIST_ITERATOR::mark_cycle_pt() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::mark_cycle_pt", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::mark_cycle_pt", ABORT, NULL);
#endif
if (current)
cycle_pt = current;
else
ex_current_was_cycle_pt = TRUE;
started_cycling = FALSE;
}
/***********************************************************************
* CLIST_ITERATOR::at_first()
*
* Are we at the start of the list?
*
**********************************************************************/
inline BOOL8 CLIST_ITERATOR::at_first() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::at_first", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::at_first", ABORT, NULL);
#endif
//we're at a deleted
return ((list->empty ()) || (current == list->First ()) || ((current == NULL) &&
(prev == list->last) && //NON-last pt between
!ex_current_was_last)); //first and last
}
/***********************************************************************
* CLIST_ITERATOR::at_last()
*
* Are we at the end of the list?
*
**********************************************************************/
inline BOOL8 CLIST_ITERATOR::at_last() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::at_last", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::at_last", ABORT, NULL);
#endif
//we're at a deleted
return ((list->empty ()) || (current == list->last) || ((current == NULL) &&
(prev == list->last) && //last point between
ex_current_was_last)); //first and last
}
/***********************************************************************
* CLIST_ITERATOR::cycled_list()
*
* Have we returned to the cycle_pt since it was set?
*
**********************************************************************/
inline BOOL8 CLIST_ITERATOR::cycled_list() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::cycled_list", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::cycled_list", ABORT, NULL);
#endif
return ((list->empty ()) || ((current == cycle_pt) && started_cycling));
}
/***********************************************************************
* CLIST_ITERATOR::length()
*
* Return the length of the list
*
**********************************************************************/
inline inT32 CLIST_ITERATOR::length() {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::length", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::length", ABORT, NULL);
#endif
return list->length ();
}
/***********************************************************************
* CLIST_ITERATOR::sort()
*
* Sort the elements of the list, then reposition at the start.
*
**********************************************************************/
inline void
CLIST_ITERATOR::sort ( //sort elements
int comparator ( //comparison routine
const void *, const void *)) {
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::sort", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::sort", ABORT, NULL);
#endif
list->sort (comparator);
move_to_first();
}
/***********************************************************************
* CLIST_ITERATOR::add_to_end
*
* Add a new element to the end of the list without moving the iterator.
* This is provided because a single linked list cannot move to the last as
* the iterator couldn't set its prev pointer. Adding to the end is
* essential for implementing
queues.
**********************************************************************/
inline void CLIST_ITERATOR::add_to_end( // element to add
void *new_data) {
CLIST_LINK *new_element;
#ifndef NDEBUG
if (!this)
NULL_OBJECT.error ("CLIST_ITERATOR::add_to_end", ABORT, NULL);
if (!list)
NO_LIST.error ("CLIST_ITERATOR::add_to_end", ABORT, NULL);
if (!new_data)
BAD_PARAMETER.error ("CLIST_ITERATOR::add_to_end", ABORT,
"new_data is NULL");
#endif
if (this->at_last ()) {
this->add_after_stay_put (new_data);
}
else {
if (this->at_first ()) {
this->add_before_stay_put (new_data);
list->last = prev;
}
else { //Iteratr is elsewhere
new_element = new CLIST_LINK;
new_element->data = new_data;
new_element->next = list->last->next;
list->last->next = new_element;
list->last = new_element;
}
}
}
/***********************************************************************
QUOTE_IT MACRO DEFINITION
===========================
Replace <parm> with "<parm>". <parm> may be an arbitrary number of tokens
***********************************************************************/
#define QUOTE_IT( parm ) #parm
/***********************************************************************
CLISTIZE( CLASSNAME ) MACRO DEFINITION
======================================
CLASSNAME is assumed to be the name of a class to be used in a CONS list
NOTE: Because we dont use virtual functions in the list code, the list code
will NOT work correctly for classes derived from this.
The macro generates:
- An element deletion function: CLASSNAME##_c1_zapper
- An element copier function:
CLASSNAME##_c1_copier
- A CLIST subclass: CLASSNAME##_CLIST
- A CLIST_ITERATOR subclass:
CLASSNAME##_C_IT
NOTE: Generated names do NOT clash with those generated by ELISTIZE,
ELIST2ISE and CLIST2IZE
Two macros are provided: CLISTIZE and CLISTIZEH
The ...IZEH macros just define the class names for use in .h files
The ...IZE macros define the code use in .c files
***********************************************************************/
/***********************************************************************
CLISTIZEH( CLASSNAME ) MACRO
CLISTIZEH is a concatenation of 3 fragments CLISTIZEH_A, CLISTIZEH_B and
CLISTIZEH_C.
***********************************************************************/
#define CLISTIZEH_A( CLASSNAME ) \
\
extern DLLSYM void CLASSNAME##_c1_zapper( /*delete a link*/ \
void* link); /*link to delete*/ \
\
extern DLLSYM void* CLASSNAME##_c1_copier( /*deep copy a link*/ \
void* old_element); /*source link */
#define CLISTIZEH_B( CLASSNAME ) \
\
/*********************************************************************** \
* CLASS - CLASSNAME##_CLIST \
* \
* List class for class CLASSNAME \
* \
**********************************************************************/ \
\
class DLLSYM CLASSNAME##_CLIST : public CLIST \
{ \
public: \
CLASSNAME##_CLIST():CLIST() {} \
/* constructor */ \
\
CLASSNAME##_CLIST( /* dont construct */ \
const CLASSNAME##_CLIST&) /*by initial assign*/ \
{ DONT_CONSTRUCT_LIST_BY_COPY.error( QUOTE_IT( CLASSNAME##_CLIST ), \
ABORT, NULL ); } \
\
void deep_clear() /* delete elements */ \
{ CLIST::internal_deep_clear( &CLASSNAME##_c1_zapper ); } \
\
void operator=( /* prevent assign */ \
const CLASSNAME##_CLIST&) \
{ DONT_ASSIGN_LISTS.error( QUOTE_IT( CLASSNAME##_CLIST ), \
ABORT, NULL ); }
#define CLISTIZEH_C( CLASSNAME ) \
\
}; \
\
\
\
/*********************************************************************** \
* CLASS - CLASSNAME##_C_IT \
* \
* Iterator class for class CLASSNAME##_CLIST \
* \
* Note: We don't need to coerce pointers to member functions input \
* parameters as these are automatically converted to the type of the base \
* type. ("A ptr to a class may be converted to a pointer to a public base \
* class of that class") \
**********************************************************************/ \
\
class DLLSYM CLASSNAME##_C_IT : public CLIST_ITERATOR \
{ \
public: \
CLASSNAME##_C_IT():CLIST_ITERATOR(){} \
\
CLASSNAME##_C_IT( \
CLASSNAME##_CLIST* list):CLIST_ITERATOR(list){} \
\
CLASSNAME* data() \
{ return (CLASSNAME*) CLIST_ITERATOR::data(); } \
\
CLASSNAME* data_relative( \
inT8 offset) \
{ return (CLASSNAME*) CLIST_ITERATOR::data_relative( offset ); } \
\
CLASSNAME* forward() \
{ return (CLASSNAME*) CLIST_ITERATOR::forward(); } \
\
CLASSNAME* extract() \
{ return (CLASSNAME*) CLIST_ITERATOR::extract(); } \
\
CLASSNAME* move_to_first() \
{ return (CLASSNAME*) CLIST_ITERATOR::move_to_first(); } \
\
CLASSNAME* move_to_last() \
{ return (CLASSNAME*) CLIST_ITERATOR::move_to_last(); } \
};
#define CLISTIZEH( CLASSNAME ) \
\
CLISTIZEH_A( CLASSNAME ) \
\
CLISTIZEH_B( CLASSNAME ) \
\
CLISTIZEH_C( CLASSNAME )
/***********************************************************************
CLISTIZE( CLASSNAME ) MACRO
***********************************************************************/
#define CLISTIZE( CLASSNAME ) \
\
/*********************************************************************** \
* CLASSNAME##_c1_zapper \
* \
* A function which can delete a CLASSNAME element. This is passed to the \
* generic deep_clear list member function so that when a list is cleared the \
* elements on the list are properly destroyed from the base class, even \
* though we dont use a virtual destructor function. \
**********************************************************************/ \
\
DLLSYM void CLASSNAME##_c1_zapper( /*delete a link*/ \
void* link) /*link to delete*/ \
{ \
delete (CLASSNAME *) link; \
} \
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: indexmapbidi.h
// Description: Bi-directional mapping between a sparse and compact space.
// Author: rays@google.com (Ray Smith)
// Created: Tue Apr 06 11:33:59 PDT 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCUTIL_INDEXMAPBIDI_H_
#define TESSERACT_CCUTIL_INDEXMAPBIDI_H_
#include <stdio.h>
#include "genericvector.h"
namespace tesseract {
class IndexMapBiDi;
// Bidirectional one-to-one mapping between a sparse and a compact discrete
// space. Many entries in the sparse space are unmapped, but those that are
// mapped have a 1-1 mapping to (and from) the compact space, where all
// values are used. This is useful for forming subsets of larger collections,
// such as subsets of character sets, or subsets of binary feature spaces.
//
// This base class provides basic functionality with binary search for the
// SparseToCompact mapping to save memory.
// For a faster inverse mapping, or to allow a many-to-one mapping, use
// IndexMapBiDi below.
// NOTE: there are currently no methods to setup an IndexMap on its own!
// It must be initialized by copying from an IndexMapBiDi or by DeSerialize.
class IndexMap {
public:
virtual ~IndexMap() {}
// SparseToCompact takes a sparse index to an index in the compact space.
// Uses a binary search to find the result. For faster speed use
// IndexMapBiDi, but that takes more memory.
virtual int SparseToCompact(int sparse_index) const;
// CompactToSparse takes a compact index to the corresponding index in the
// sparse space.
int CompactToSparse(int compact_index) const {
return compact_map_[compact_index];
}
// The size of the sparse space.
virtual int SparseSize() const {
return sparse_size_;
}
// The size of the compact space.
int CompactSize() const {
return compact_map_.size();
}
// Copy from the input.
void CopyFrom(const IndexMap& src);
void CopyFrom(const IndexMapBiDi& src);
// Writes to the given file. Returns false in case of error.
bool Serialize(FILE* fp) const;
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, FILE* fp);
protected:
// The sparse space covers integers in the range [0, sparse_size_-1].
int sparse_size_;
// The compact space covers integers in the range [0, compact_map_.size()-1].
// Each element contains the corresponding sparse index.
GenericVector<inT32> compact_map_;
};
// Bidirectional many-to-one mapping between a sparse and a compact discrete
// space. As with IndexMap, many entries may be unmapped, but unlike IndexMap,
// of those that are, many may be mapped to the same compact index.
// If the map is many-to-one, it is not possible to directly obtain all the
// sparse indices that map to a single compact index.
// This map is time- rather than space-efficient. It stores the entire sparse
// space.
// IndexMapBiDi may be initialized in one of 3 ways:
// 1. Init(size, true);
// Setup();
// Sets a complete 1:1 mapping with no unmapped elements.
// 2. Init(size, false);
// for ... SetMap(index, true);
// Setup();
// Specifies precisely which sparse indices are mapped. The mapping is 1:1.
// 3. Either of the above, followed by:
// for ... Merge(index1, index2);
// CompleteMerges();
// Allows a many-to-one mapping by merging compact space indices.
class IndexMapBiDi : public IndexMap {
public:
virtual ~IndexMapBiDi() {}
// Top-level init function in a single call to initialize a map to select
// a single contiguous subrange [start, end) of the sparse space to be mapped
// 1 to 1 to the compact space, with all other elements of the sparse space
// left unmapped.
// No need to call Setup after this.
void InitAndSetupRange(int sparse_size, int start, int end);
// Initializes just the sparse_map_ to the given size with either all
// forward indices mapped (all_mapped = true) or none (all_mapped = false).
// Call Setup immediately after, or make calls to SetMap first to adjust the
// mapping and then call Setup before using the map.
void Init(int size, bool all_mapped);
// Sets a given index in the sparse_map_ to be mapped or not.
void SetMap(int sparse_index, bool mapped);
// Sets up the sparse_map_ and compact_map_ properly after Init and
// some calls to SetMap. Assumes an ordered 1-1 map from set indices
// in the sparse space to the compact space.
void Setup();
// Merges the two compact space indices. May be called many times, but
// the merges must be concluded by a call to CompleteMerges.
// Returns true if a merge was actually performed.
bool Merge(int compact_index1, int compact_index2);
// Returns true if the given compact index has been deleted.
bool IsCompactDeleted(int index) const {
return MasterCompactIndex(index) < 0;
}
// Completes one or more Merge operations by further compacting the
// compact space.
void CompleteMerges();
// SparseToCompact takes a sparse index to an index in the compact space.
virtual int SparseToCompact(int sparse_index) const {
return sparse_map_[sparse_index];
}
// The size of the sparse space.
virtual int SparseSize() const {
return sparse_map_.size();
}
// Copy from the input.
void CopyFrom(const IndexMapBiDi& src);
// Writes to the given file. Returns false in case of error.
bool Serialize(FILE* fp) const;
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool swap, FILE* fp);
// Bulk calls to SparseToCompact.
// Maps the given array of sparse indices to an array of compact indices.
// Assumes the input is sorted. The output indices are sorted and uniqued.
// Return value is the number of "missed" features, being features that
// don't map to the compact feature space.
int MapFeatures(const GenericVector<int>& sparse,
GenericVector<int>* compact) const;
private:
// Returns the master compact index for a given compact index.
// During a multiple merge operation, several compact indices may be
// combined, so we need to be able to find the master of all.
int MasterCompactIndex(int compact_index) const {
while (compact_index >= 0 &&
sparse_map_[compact_map_[compact_index]] != compact_index)
compact_index = sparse_map_[compact_map_[compact_index]];
return compact_index;
}
// Direct look-up of the compact index for each element in sparse space.
GenericVector<inT32> sparse_map_;
};
} // namespace tesseract.
#endif // TESSERACT_CCUTIL_INDEXMAPBIDI_H_
| C++ |
/**********************************************************************
* File: bits16.h (Formerly bits8.h)
* Description: Code for 8 bit field class.
* Author: Phil Cheatle
* Created: Thu Oct 17 10:10:05 BST 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef BITS16_H
#define BITS16_H
#include "host.h"
class DLLSYM BITS16
{
public:
uinT16 val;
BITS16() {
val = 0;
} // constructor
BITS16( // constructor
uinT16 init); // initial val
void turn_on_bit( // flip specified bit
uinT8 bit_num) { // bit to flip 0..7
val = val | 01 << bit_num;
};
void turn_off_bit( // flip specified bit
uinT8 bit_num) { // bit to flip 0..7
val = val & ~(01 << bit_num);
};
void set_bit( // flip specified bit
uinT8 bit_num, // bit to flip 0..7
BOOL8 value) { // value to flip to
if (value)
val = val | 01 << bit_num;
else
val = val & ~(01 << bit_num);
};
BOOL8 bit( // access bit
uinT8 bit_num) const { // bit to access
return (val >> bit_num) & 01;
};
};
#endif
| C++ |
/**********************************************************************
* File: unicodes.h
* Description: Unicode related machinery
* Author: David Eger
* Created: Wed Jun 15 16:37:50 PST 2011
*
* (C) Copyright 2011, Google, Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "unicodes.h"
#include "host.h" // for NULL
namespace tesseract {
const char *kUTF8LineSeparator = "\u2028"; // "\xe2\x80\xa8";
const char *kUTF8ParagraphSeparator = "\u2029"; // "\xe2\x80\xa9";
const char *kLRM = "\u200E"; // Left-to-Right Mark
const char *kRLM = "\u200F"; // Right-to-Left Mark
const char *kRLE = "\u202A"; // Right-to-Left Embedding
const char *kPDF = "\u202C"; // Pop Directional Formatting
const char *kHyphenLikeUTF8[] = {
"-", // ASCII hyphen-minus
"\u05BE", // word hyphen in hybrew
"\u2010", // hyphen
"\u2011", // non-breaking hyphen
"\u2012", // a hyphen the same width as digits
"\u2013", // en dash
"\u2014", // em dash
"\u2015", // horizontal bar
"\u2212", // arithmetic minus sign
"\uFE58", // small em dash
"\uFE63", // small hyphen-minus
"\uFF0D", // fullwidth hyphen-minus
NULL, // end of our list
};
const char *kApostropheLikeUTF8[] = {
"'", // ASCII apostrophe
"`", // ASCII backtick
"\u2018", // opening single quote
"\u2019", // closing single quote
"\u2032", // mathematical prime mark
NULL, // end of our list.
};
} // namespace
| C++ |
/**********************************************************************
* File: unicodes.h
* Description: Unicode related machinery
* Author: David Eger
* Created: Wed Jun 15 16:37:50 PST 2011
*
* (C) Copyright 2011, Google, Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef TESSERACT_CCUTIL_UNICODES_H__
#define TESSERACT_CCUTIL_UNICODES_H__
namespace tesseract {
extern const char *kUTF8LineSeparator;
extern const char *kUTF8ParagraphSeparator;
extern const char *kLRM; // Left-to-Right Mark
extern const char *kRLM; // Right-to-Left Mark
extern const char *kRLE; // Right-to-Left Embedding
extern const char *kPDF; // Pop Directional Formatting
// The following are confusable internal word punctuation symbols
// which we normalize to the first variant when matching in dawgs.
extern const char *kHyphenLikeUTF8[];
extern const char *kApostropheLikeUTF8[];
} // namespace
#endif // TESSERACT_CCUTIL_UNICODES_H__
| C++ |
/**********************************************************************
* File: mainblk.c (Formerly main.c)
* Description: Function to call from main() to setup.
* Author: Ray Smith
* Created: Tue Oct 22 11:09:40 BST 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "fileerr.h"
#ifdef __UNIX__
#include <unistd.h>
#include <signal.h>
#else
#include <io.h>
#endif
#include <stdlib.h>
#include "ccutil.h"
#define VARDIR "configs/" /**< variables files */
#define EXTERN
const ERRCODE NO_PATH =
"Warning:explicit path for executable will not be used for configs";
static const ERRCODE USAGE = "Usage";
namespace tesseract {
/**********************************************************************
* main_setup
*
* Main for mithras demo program. Read the arguments and set up globals.
**********************************************************************/
/**
* @brief CCUtil::main_setup - set location of tessdata and name of image
*
* @param argv0 - paths to the directory with language files and config files.
* An actual value of argv0 is used if not NULL, otherwise TESSDATA_PREFIX is
* used if not NULL, next try to use compiled in -DTESSDATA_PREFIX. If previous
* is not sucessul - use current directory.
* @param basename - name of image
*/
void CCUtil::main_setup(const char *argv0, const char *basename) {
imagebasename = basename; /**< name of image */
if (argv0 != NULL) {
datadir = argv0;
} else {
if (getenv("TESSDATA_PREFIX")) {
datadir = getenv("TESSDATA_PREFIX");
} else {
#ifdef TESSDATA_PREFIX
#define _STR(a) #a
#define _XSTR(a) _STR(a)
datadir = _XSTR(TESSDATA_PREFIX);
#undef _XSTR
#undef _STR
#endif
}
}
// datadir may still be empty:
if (datadir.length() == 0) {
datadir = "./";
} else {
// Remove tessdata from the end if present, as we will add it back!
int length = datadir.length();
if (length >= 8 && strcmp(&datadir[length - 8], "tessdata") == 0)
datadir.truncate_at(length - 8);
else if (length >= 9 && strcmp(&datadir[length - 9], "tessdata/") == 0)
datadir.truncate_at(length - 9);
}
// check for missing directory separator
const char *lastchar = datadir.string();
lastchar += datadir.length() - 1;
if ((strcmp(lastchar, "/") != 0) && (strcmp(lastchar, "\\") != 0))
datadir += "/";
datadir += m_data_sub_dir; /**< data directory */
}
} // namespace tesseract
| C++ |
// Copyright 2008 Google Inc. All Rights Reserved.
// Author: scharron@google.com (Samuel Charron)
#include "ccutil.h"
namespace tesseract {
CCUtil::CCUtil() :
params_(),
STRING_INIT_MEMBER(m_data_sub_dir,
"tessdata/", "Directory for data files", ¶ms_),
#ifdef _WIN32
STRING_INIT_MEMBER(tessedit_module_name, WINDLLNAME,
"Module colocated with tessdata dir", ¶ms_),
#endif
INT_INIT_MEMBER(ambigs_debug_level, 0, "Debug level for unichar ambiguities",
¶ms_),
BOOL_MEMBER(use_definite_ambigs_for_classifier, 0, "Use definite"
" ambiguities when running character classifier", ¶ms_),
BOOL_MEMBER(use_ambigs_for_adaption, 0, "Use ambigs for deciding"
" whether to adapt to a character", ¶ms_) {
}
CCUtil::~CCUtil() {
}
CCUtilMutex::CCUtilMutex() {
#ifdef _WIN32
mutex_ = CreateMutex(0, FALSE, 0);
#else
pthread_mutex_init(&mutex_, NULL);
#endif
}
void CCUtilMutex::Lock() {
#ifdef _WIN32
WaitForSingleObject(mutex_, INFINITE);
#else
pthread_mutex_lock(&mutex_);
#endif
}
void CCUtilMutex::Unlock() {
#ifdef _WIN32
ReleaseMutex(mutex_);
#else
pthread_mutex_unlock(&mutex_);
#endif
}
CCUtilMutex tprintfMutex; // should remain global
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: unicharmap.h
// Description: Unicode character/ligature to integer id class.
// Author: Thomas Kielbus
// Created: Wed Jun 28 17:05:01 PDT 2006
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCUTIL_UNICHARMAP_H__
#define TESSERACT_CCUTIL_UNICHARMAP_H__
#include "unichar.h"
// A UNICHARMAP stores unique unichars. Each of them is associated with one
// UNICHAR_ID.
class UNICHARMAP {
public:
// Create an empty UNICHARMAP
UNICHARMAP();
~UNICHARMAP();
// Insert the given unichar represention in the UNICHARMAP and associate it
// with the given id. The length of the representation MUST be non-zero.
void insert(const char* const unichar_repr, UNICHAR_ID id);
// Return the id associated with the given unichar representation,
// this representation MUST exist within the UNICHARMAP.
// The length of the representation MUST be non-zero.
UNICHAR_ID unichar_to_id(const char* const unichar_repr) const;
// Return the id associated with the given unichar representation,
// this representation MUST exist within the UNICHARMAP. The first
// length characters (maximum) from unichar_repr are used. The length
// MUST be non-zero.
UNICHAR_ID unichar_to_id(const char* const unichar_repr, int length) const;
// Return true if the given unichar representation is already present in the
// UNICHARMAP. The length of the representation MUST be non-zero.
bool contains(const char* const unichar_repr) const;
// Return true if the given unichar representation is already present in the
// UNICHARMAP. The first length characters (maximum) from unichar_repr are
// used. The length MUST be non-zero.
bool contains(const char* const unichar_repr, int length) const;
// Return the minimum number of characters that must be used from this string
// to obtain a match in the UNICHARMAP.
int minmatch(const char* const unichar_repr) const;
// Clear the UNICHARMAP. All previous data is lost.
void clear();
private:
// The UNICHARMAP is represented as a tree whose nodes are of type
// UNICHARMAP_NODE.
struct UNICHARMAP_NODE {
UNICHARMAP_NODE();
~UNICHARMAP_NODE();
UNICHARMAP_NODE* children;
UNICHAR_ID id;
};
UNICHARMAP_NODE* nodes;
};
#endif // TESSERACT_CCUTIL_UNICHARMAP_H__
| C++ |
// Copyright 2011 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: bitvector.cpp
// Description: Class replacement for BITVECTOR.
// Author: Ray Smith
// Created: Mon Jan 10 17:45:01 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "bitvector.h"
#include <string.h>
#include "helpers.h"
#include "ndminx.h"
namespace tesseract {
// Fast lookup table to get the first least significant set bit in a byte.
// For zero, the table has 255, but since it is a special case, most code
// that uses this table will check for zero before looking up lsb_index_.
const uinT8 BitVector::lsb_index_[256] = {
255, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
5, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
6, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
5, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
7, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
5, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
6, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
5, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0,
4, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 2, 0, 1, 0
};
// Fast lookup table to get the residual bits after zeroing the first (lowest)
// set bit in a byte.
const uinT8 BitVector::lsb_eroded_[256] = {
0, 0, 0, 0x2, 0, 0x4, 0x4, 0x6,
0, 0x8, 0x8, 0x0a, 0x08, 0x0c, 0x0c, 0x0e,
0, 0x10, 0x10, 0x12, 0x10, 0x14, 0x14, 0x16,
0x10, 0x18, 0x18, 0x1a, 0x18, 0x1c, 0x1c, 0x1e,
0, 0x20, 0x20, 0x22, 0x20, 0x24, 0x24, 0x26,
0x20, 0x28, 0x28, 0x2a, 0x28, 0x2c, 0x2c, 0x2e,
0x20, 0x30, 0x30, 0x32, 0x30, 0x34, 0x34, 0x36,
0x30, 0x38, 0x38, 0x3a, 0x38, 0x3c, 0x3c, 0x3e,
0, 0x40, 0x40, 0x42, 0x40, 0x44, 0x44, 0x46,
0x40, 0x48, 0x48, 0x4a, 0x48, 0x4c, 0x4c, 0x4e,
0x40, 0x50, 0x50, 0x52, 0x50, 0x54, 0x54, 0x56,
0x50, 0x58, 0x58, 0x5a, 0x58, 0x5c, 0x5c, 0x5e,
0x40, 0x60, 0x60, 0x62, 0x60, 0x64, 0x64, 0x66,
0x60, 0x68, 0x68, 0x6a, 0x68, 0x6c, 0x6c, 0x6e,
0x60, 0x70, 0x70, 0x72, 0x70, 0x74, 0x74, 0x76,
0x70, 0x78, 0x78, 0x7a, 0x78, 0x7c, 0x7c, 0x7e,
0, 0x80, 0x80, 0x82, 0x80, 0x84, 0x84, 0x86,
0x80, 0x88, 0x88, 0x8a, 0x88, 0x8c, 0x8c, 0x8e,
0x80, 0x90, 0x90, 0x92, 0x90, 0x94, 0x94, 0x96,
0x90, 0x98, 0x98, 0x9a, 0x98, 0x9c, 0x9c, 0x9e,
0x80, 0xa0, 0xa0, 0xa2, 0xa0, 0xa4, 0xa4, 0xa6,
0xa0, 0xa8, 0xa8, 0xaa, 0xa8, 0xac, 0xac, 0xae,
0xa0, 0xb0, 0xb0, 0xb2, 0xb0, 0xb4, 0xb4, 0xb6,
0xb0, 0xb8, 0xb8, 0xba, 0xb8, 0xbc, 0xbc, 0xbe,
0x80, 0xc0, 0xc0, 0xc2, 0xc0, 0xc4, 0xc4, 0xc6,
0xc0, 0xc8, 0xc8, 0xca, 0xc8, 0xcc, 0xcc, 0xce,
0xc0, 0xd0, 0xd0, 0xd2, 0xd0, 0xd4, 0xd4, 0xd6,
0xd0, 0xd8, 0xd8, 0xda, 0xd8, 0xdc, 0xdc, 0xde,
0xc0, 0xe0, 0xe0, 0xe2, 0xe0, 0xe4, 0xe4, 0xe6,
0xe0, 0xe8, 0xe8, 0xea, 0xe8, 0xec, 0xec, 0xee,
0xe0, 0xf0, 0xf0, 0xf2, 0xf0, 0xf4, 0xf4, 0xf6,
0xf0, 0xf8, 0xf8, 0xfa, 0xf8, 0xfc, 0xfc, 0xfe
};
// Fast lookup table to give the number of set bits in a byte.
const int BitVector::hamming_table_[256] = {
0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
1, 2, 2, 3, 2, 3, 3, 4, 2, 3, 3, 4, 3, 4, 4, 5,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
2, 3, 3, 4, 3, 4, 4, 5, 3, 4, 4, 5, 4, 5, 5, 6,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
3, 4, 4, 5, 4, 5, 5, 6, 4, 5, 5, 6, 5, 6, 6, 7,
4, 5, 5, 6, 5, 6, 6, 7, 5, 6, 6, 7, 6, 7, 7, 8
};
BitVector::BitVector() : bit_size_(0), array_(NULL) {}
BitVector::BitVector(int length) : bit_size_(length) {
array_ = new uinT32[WordLength()];
SetAllFalse();
}
BitVector::BitVector(const BitVector& src) : bit_size_(src.bit_size_) {
array_ = new uinT32[WordLength()];
memcpy(array_, src.array_, ByteLength());
}
BitVector& BitVector::operator=(const BitVector& src) {
Alloc(src.bit_size_);
memcpy(array_, src.array_, ByteLength());
return *this;
}
BitVector::~BitVector() {
delete [] array_;
}
// Initializes the array to length * false.
void BitVector::Init(int length) {
Alloc(length);
SetAllFalse();
}
// Writes to the given file. Returns false in case of error.
bool BitVector::Serialize(FILE* fp) const {
if (fwrite(&bit_size_, sizeof(bit_size_), 1, fp) != 1) return false;
int wordlen = WordLength();
if (static_cast<int>(fwrite(array_, sizeof(*array_), wordlen, fp)) != wordlen)
return false;
return true;
}
// Reads from the given file. Returns false in case of error.
// If swap is true, assumes a big/little-endian swap is needed.
bool BitVector::DeSerialize(bool swap, FILE* fp) {
uinT32 new_bit_size;
if (fread(&new_bit_size, sizeof(new_bit_size), 1, fp) != 1) return false;
if (swap) {
ReverseN(&new_bit_size, sizeof(new_bit_size));
}
Alloc(new_bit_size);
int wordlen = WordLength();
if (static_cast<int>(fread(array_, sizeof(*array_), wordlen, fp)) != wordlen)
return false;
if (swap) {
for (int i = 0; i < wordlen; ++i)
ReverseN(&array_[i], sizeof(array_[i]));
}
return true;
}
void BitVector::SetAllFalse() {
memset(array_, 0, ByteLength());
}
void BitVector::SetAllTrue() {
memset(array_, ~0, ByteLength());
}
// Returns the index of the next set bit after the given index.
// Useful for quickly iterating through the set bits in a sparse vector.
int BitVector::NextSetBit(int prev_bit) const {
// Move on to the next bit.
int next_bit = prev_bit + 1;
if (next_bit >= bit_size_) return -1;
// Check the remains of the word containing the next_bit first.
int next_word = WordIndex(next_bit);
int bit_index = next_word * kBitFactor;
int word_end = bit_index + kBitFactor;
uinT32 word = array_[next_word];
uinT8 byte = word & 0xff;
while (bit_index < word_end) {
if (bit_index + 8 > next_bit && byte != 0) {
while (bit_index + lsb_index_[byte] < next_bit && byte != 0)
byte = lsb_eroded_[byte];
if (byte != 0)
return bit_index + lsb_index_[byte];
}
word >>= 8;
bit_index += 8;
byte = word & 0xff;
}
// next_word didn't contain a 1, so find the next word with set bit.
++next_word;
int wordlen = WordLength();
while (next_word < wordlen && (word = array_[next_word]) == 0) {
++next_word;
bit_index += kBitFactor;
}
if (bit_index >= bit_size_) return -1;
// Find the first non-zero byte within the word.
while ((word & 0xff) == 0) {
word >>= 8;
bit_index += 8;
}
return bit_index + lsb_index_[word & 0xff];
}
// Returns the number of set bits in the vector.
int BitVector::NumSetBits() const {
int wordlen = WordLength();
int total_bits = 0;
for (int w = 0; w < wordlen; ++w) {
uinT32 word = array_[w];
for (int i = 0; i < 4; ++i) {
total_bits += hamming_table_[word & 0xff];
word >>= 8;
}
}
return total_bits;
}
// Logical in-place operations on whole bit vectors. Tries to do something
// sensible if they aren't the same size, but they should be really.
void BitVector::operator|=(const BitVector& other) {
int length = MIN(WordLength(), other.WordLength());
for (int w = 0; w < length; ++w)
array_[w] |= other.array_[w];
}
void BitVector::operator&=(const BitVector& other) {
int length = MIN(WordLength(), other.WordLength());
for (int w = 0; w < length; ++w)
array_[w] &= other.array_[w];
for (int w = WordLength() - 1; w >= length; --w)
array_[w] = 0;
}
void BitVector::operator^=(const BitVector& other) {
int length = MIN(WordLength(), other.WordLength());
for (int w = 0; w < length; ++w)
array_[w] ^= other.array_[w];
}
// Set subtraction *this = v1 - v2.
void BitVector::SetSubtract(const BitVector& v1, const BitVector& v2) {
Alloc(v1.size());
int length = MIN(v1.WordLength(), v2.WordLength());
for (int w = 0; w < length; ++w)
array_[w] = v1.array_[w] ^ (v1.array_[w] & v2.array_[w]);
for (int w = WordLength() - 1; w >= length; --w)
array_[w] = v1.array_[w];
}
// Allocates memory for a vector of the given length.
// Reallocates if the array is a different size, larger or smaller.
void BitVector::Alloc(int length) {
int initial_wordlength = WordLength();
bit_size_ = length;
int new_wordlength = WordLength();
if (new_wordlength != initial_wordlength) {
delete [] array_;
array_ = new uinT32[new_wordlength];
}
}
} // namespace tesseract.
| C++ |
/**********************************************************************
* File: bits16.h (Formerly bits8.h)
* Description: Code for 8 bit field class.
* Author: Phil Cheatle
* Created: Thu Oct 17 10:10:05 BST 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "bits16.h"
/**********************************************************************
* Constructor. Something to get it past the compiler as almost all inlined.
*
**********************************************************************/
BITS16::BITS16( // constructor
uinT16 init) { // initial val
val = init;
}
| C++ |
/**********************************************************************
* File: hashfn.h (Formerly hash.h)
* Description: Portability hacks for hash_map, hash_set and unique_ptr.
* Author: Ray Smith
* Created: Wed Jan 08 14:08:25 PST 2014
*
* (C) Copyright 2014, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef HASHFN_H
#define HASHFN_H
#ifdef USE_STD_NAMESPACE
#if (__cplusplus >= 201103L) || defined(_MSC_VER) // Visual Studio
#include <unordered_map>
#include <unordered_set>
#define hash_map std::unordered_map
#if (_MSC_VER >= 1500 && _MSC_VER < 1600) // Visual Studio 2008
using namespace std::tr1;
#else // _MSC_VER
using std::unordered_map;
using std::unordered_set;
#include <memory>
#define SmartPtr std::unique_ptr
#define HAVE_UNIQUE_PTR
#endif // _MSC_VER
#elif (defined(__GNUC__) && (((__GNUC__ == 3) && (__GNUC_MINOR__ > 0)) || \
__GNUC__ >= 4)) // gcc
// hash_set is deprecated in gcc
#include <ext/hash_map>
#include <ext/hash_set>
using __gnu_cxx::hash_map;
using __gnu_cxx::hash_set;
#define unordered_map hash_map
#define unordered_set hash_set
#else
#include <hash_map>
#include <hash_set>
#endif // gcc
#else // USE_STD_NAMESPACE
#include <hash_map>
#include <hash_set>
#define unordered_map hash_map
#define unordered_set hash_set
#endif // USE_STD_NAMESPACE
#ifndef HAVE_UNIQUE_PTR
// Trivial smart ptr. Expand to add features of std::unique_ptr as required.
template<class T> class SmartPtr {
public:
SmartPtr() : ptr_(NULL) {}
explicit SmartPtr(T* ptr) : ptr_(ptr) {}
~SmartPtr() {
delete ptr_;
}
T* get() const {
return ptr_;
}
void reset(T* ptr) {
if (ptr_ != NULL) delete ptr_;
ptr_ = ptr;
}
bool operator==(const T* ptr) const {
return ptr_ == ptr;
}
T* operator->() const {
return ptr_;
}
private:
T* ptr_;
};
#endif // HAVE_UNIQUE_PTR
#endif // HASHFN_H
| C++ |
///////////////////////////////////////////////////////////////////////
// File: unicharset.h
// Description: Unicode character/ligature set class.
// Author: Thomas Kielbus
// Created: Wed Jun 28 17:05:01 PDT 2006
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCUTIL_UNICHARSET_H__
#define TESSERACT_CCUTIL_UNICHARSET_H__
#include "errcode.h"
#include "genericvector.h"
#include "helpers.h"
#include "serialis.h"
#include "strngs.h"
#include "tesscallback.h"
#include "unichar.h"
#include "unicharmap.h"
// Enum holding special values of unichar_id. Every unicharset has these.
// Warning! Keep in sync with kSpecialUnicharCodes.
enum SpecialUnicharCodes {
UNICHAR_SPACE,
UNICHAR_JOINED,
UNICHAR_BROKEN,
SPECIAL_UNICHAR_CODES_COUNT
};
class CHAR_FRAGMENT {
public:
// Minimum number of characters used for fragment representation.
static const int kMinLen = 6;
// Maximum number of characters used for fragment representation.
static const int kMaxLen = 3 + UNICHAR_LEN + 2;
// Maximum number of fragments per character.
static const int kMaxChunks = 5;
// Setters and Getters.
inline void set_all(const char *unichar, int pos, int total, bool natural) {
set_unichar(unichar);
set_pos(pos);
set_total(total);
set_natural(natural);
}
inline void set_unichar(const char *uch) {
strncpy(this->unichar, uch, UNICHAR_LEN);
this->unichar[UNICHAR_LEN] = '\0';
}
inline void set_pos(int p) { this->pos = p; }
inline void set_total(int t) { this->total = t; }
inline const char* get_unichar() const { return this->unichar; }
inline int get_pos() const { return this->pos; }
inline int get_total() const { return this->total; }
// Returns the string that represents a fragment
// with the given unichar, pos and total.
static STRING to_string(const char *unichar, int pos, int total,
bool natural);
// Returns the string that represents this fragment.
STRING to_string() const {
return to_string(unichar, pos, total, natural);
}
// Checks whether a fragment has the same unichar,
// position and total as the given inputs.
inline bool equals(const char *other_unichar,
int other_pos, int other_total) const {
return (strcmp(this->unichar, other_unichar) == 0 &&
this->pos == other_pos && this->total == other_total);
}
inline bool equals(const CHAR_FRAGMENT *other) const {
return this->equals(other->get_unichar(),
other->get_pos(),
other->get_total());
}
// Checks whether a given fragment is a continuation of this fragment.
// Assumes that the given fragment pointer is not NULL.
inline bool is_continuation_of(const CHAR_FRAGMENT *fragment) const {
return (strcmp(this->unichar, fragment->get_unichar()) == 0 &&
this->total == fragment->get_total() &&
this->pos == fragment->get_pos() + 1);
}
// Returns true if this fragment is a beginning fragment.
inline bool is_beginning() const { return this->pos == 0; }
// Returns true if this fragment is an ending fragment.
inline bool is_ending() const { return this->pos == this->total-1; }
// Returns true if the fragment was a separate component to begin with,
// ie did not need chopping to be isolated, but may have been separated
// out from a multi-outline blob.
inline bool is_natural() const { return natural; }
void set_natural(bool value) { natural = value; }
// Parses the string to see whether it represents a character fragment
// (rather than a regular character). If so, allocates memory for a new
// CHAR_FRAGMENT instance and fills it in with the corresponding fragment
// information. Fragments are of the form:
// |m|1|2, meaning chunk 1 of 2 of character m, or
// |:|1n2, meaning chunk 1 of 2 of character :, and no chopping was needed
// to divide the parts, as they were already separate connected components.
//
// If parsing succeeded returns the pointer to the allocated CHAR_FRAGMENT
// instance, otherwise (if the string does not represent a fragment or it
// looks like it does, but parsing it as a fragment fails) returns NULL.
//
// Note: The caller is responsible for deallocating memory
// associated with the returned pointer.
static CHAR_FRAGMENT *parse_from_string(const char *str);
private:
char unichar[UNICHAR_LEN + 1];
// True if the fragment was a separate component to begin with,
// ie did not need chopping to be isolated, but may have been separated
// out from a multi-outline blob.
bool natural;
inT16 pos; // fragment position in the character
inT16 total; // total number of fragments in the character
};
// The UNICHARSET class is an utility class for Tesseract that holds the
// set of characters that are used by the engine. Each character is identified
// by a unique number, from 0 to (size - 1).
class UNICHARSET {
public:
// Custom list of characters and their ligature forms (UTF8)
// These map to unicode values in the private use area (PUC) and are supported
// by only few font families (eg. Wyld, Adobe Caslon Pro).
static const char* kCustomLigatures[][2];
// List of strings for the SpecialUnicharCodes. Keep in sync with the enum.
static const char* kSpecialUnicharCodes[SPECIAL_UNICHAR_CODES_COUNT];
// ICU 2.0 UCharDirection enum (from third_party/icu/include/unicode/uchar.h)
enum Direction {
U_LEFT_TO_RIGHT = 0,
U_RIGHT_TO_LEFT = 1,
U_EUROPEAN_NUMBER = 2,
U_EUROPEAN_NUMBER_SEPARATOR = 3,
U_EUROPEAN_NUMBER_TERMINATOR = 4,
U_ARABIC_NUMBER = 5,
U_COMMON_NUMBER_SEPARATOR = 6,
U_BLOCK_SEPARATOR = 7,
U_SEGMENT_SEPARATOR = 8,
U_WHITE_SPACE_NEUTRAL = 9,
U_OTHER_NEUTRAL = 10,
U_LEFT_TO_RIGHT_EMBEDDING = 11,
U_LEFT_TO_RIGHT_OVERRIDE = 12,
U_RIGHT_TO_LEFT_ARABIC = 13,
U_RIGHT_TO_LEFT_EMBEDDING = 14,
U_RIGHT_TO_LEFT_OVERRIDE = 15,
U_POP_DIRECTIONAL_FORMAT = 16,
U_DIR_NON_SPACING_MARK = 17,
U_BOUNDARY_NEUTRAL = 18,
U_CHAR_DIRECTION_COUNT
};
// Create an empty UNICHARSET
UNICHARSET();
~UNICHARSET();
// Return the UNICHAR_ID of a given unichar representation within the
// UNICHARSET.
const UNICHAR_ID unichar_to_id(const char* const unichar_repr) const;
// Return the UNICHAR_ID of a given unichar representation within the
// UNICHARSET. Only the first length characters from unichar_repr are used.
const UNICHAR_ID unichar_to_id(const char* const unichar_repr,
int length) const;
// Return the minimum number of bytes that matches a legal UNICHAR_ID,
// while leaving the rest of the string encodable. Returns 0 if the
// beginning of the string is not encodable.
// WARNING: this function now encodes the whole string for precision.
// Use encode_string in preference to repeatedly calling step.
int step(const char* str) const;
// As step except constraining the search to unichar-ids that are
// self-normalized. Unlike step, does not encode the whole string, therefore
// should be used on short strings (like those obtained from
// get_normed_unichar.)
int normed_step(const char* str) const;
// Return whether the given UTF-8 string is encodable with this UNICHARSET.
// If not encodable, write the first byte offset which cannot be converted
// into the second (return) argument.
bool encodable_string(const char *str, int *first_bad_position) const;
// Encodes the given UTF-8 string with this UNICHARSET.
// Any part of the string that cannot be encoded (because the utf8 can't
// be broken up into pieces that are in the unicharset) then:
// if give_up_on_failure, stops and returns a partial encoding,
// else continues and inserts an INVALID_UNICHAR_ID in the returned encoding.
// Returns true if the encoding succeeds completely, false if there is at
// least one failure.
// If lengths is not NULL, then it is filled with the corresponding
// byte length of each encoded UNICHAR_ID.
// If encoded_length is not NULL then on return it contains the length of
// str that was encoded. (if give_up_on_failure the location of the first
// failure, otherwise strlen(str).)
bool encode_string(const char* str, bool give_up_on_failure,
GenericVector<UNICHAR_ID>* encoding,
GenericVector<char>* lengths,
int* encoded_length) const;
// Return the unichar representation corresponding to the given UNICHAR_ID
// within the UNICHARSET.
const char* const id_to_unichar(UNICHAR_ID id) const;
// Return the UTF8 representation corresponding to the given UNICHAR_ID after
// resolving any private encodings internal to Tesseract. This method is
// preferrable to id_to_unichar for outputting text that will be visible to
// external applications.
const char* const id_to_unichar_ext(UNICHAR_ID id) const;
// Return a STRING that reformats the utf8 str into the str followed
// by its hex unicodes.
static STRING debug_utf8_str(const char* str);
// Return a STRING containing debug information on the unichar, including
// the id_to_unichar, its hex unicodes and the properties.
STRING debug_str(UNICHAR_ID id) const;
STRING debug_str(const char * unichar_repr) const {
return debug_str(unichar_to_id(unichar_repr));
}
// Add a unichar representation to the set.
void unichar_insert(const char* const unichar_repr);
// Return true if the given unichar id exists within the set.
// Relies on the fact that unichar ids are contiguous in the unicharset.
bool contains_unichar_id(UNICHAR_ID unichar_id) const {
return unichar_id != INVALID_UNICHAR_ID && unichar_id < size_used &&
unichar_id >= 0;
}
// Return true if the given unichar representation exists within the set.
bool contains_unichar(const char* const unichar_repr) const;
bool contains_unichar(const char* const unichar_repr, int length) const;
// Return true if the given unichar representation corresponds to the given
// UNICHAR_ID within the set.
bool eq(UNICHAR_ID unichar_id, const char* const unichar_repr) const;
// Delete CHAR_FRAGMENTs stored in properties of unichars array.
void delete_pointers_in_unichars() {
for (int i = 0; i < size_used; ++i) {
if (unichars[i].properties.fragment != NULL) {
delete unichars[i].properties.fragment;
unichars[i].properties.fragment = NULL;
}
}
}
// Clear the UNICHARSET (all the previous data is lost).
void clear() {
if (script_table != NULL) {
for (int i = 0; i < script_table_size_used; ++i)
delete[] script_table[i];
delete[] script_table;
script_table = NULL;
script_table_size_used = 0;
}
if (unichars != NULL) {
delete_pointers_in_unichars();
delete[] unichars;
unichars = NULL;
}
script_table_size_reserved = 0;
size_reserved = 0;
size_used = 0;
ids.clear();
top_bottom_set_ = false;
script_has_upper_lower_ = false;
script_has_xheight_ = false;
null_sid_ = 0;
common_sid_ = 0;
latin_sid_ = 0;
cyrillic_sid_ = 0;
greek_sid_ = 0;
han_sid_ = 0;
hiragana_sid_ = 0;
katakana_sid_ = 0;
}
// Return the size of the set (the number of different UNICHAR it holds).
int size() const {
return size_used;
}
// Reserve enough memory space for the given number of UNICHARS
void reserve(int unichars_number);
// Opens the file indicated by filename and saves unicharset to that file.
// Returns true if the operation is successful.
bool save_to_file(const char * const filename) const {
FILE* file = fopen(filename, "w+b");
if (file == NULL) return false;
bool result = save_to_file(file);
fclose(file);
return result;
}
// Saves the content of the UNICHARSET to the given file.
// Returns true if the operation is successful.
bool save_to_file(FILE *file) const {
STRING str;
if (!save_to_string(&str)) return false;
if (fwrite(&str[0], str.length(), 1, file) != 1) return false;
return true;
}
bool save_to_file(tesseract::TFile *file) const {
STRING str;
if (!save_to_string(&str)) return false;
if (file->FWrite(&str[0], str.length(), 1) != 1) return false;
return true;
}
// Saves the content of the UNICHARSET to the given STRING.
// Returns true if the operation is successful.
bool save_to_string(STRING *str) const;
// Load a unicharset from a unicharset file that has been loaded into
// the given memory buffer.
// Returns true if the operation is successful.
bool load_from_inmemory_file(const char* const memory, int mem_size,
bool skip_fragments);
// Returns true if the operation is successful.
bool load_from_inmemory_file(const char* const memory, int mem_size) {
return load_from_inmemory_file(memory, mem_size, false);
}
// Opens the file indicated by filename and loads the UNICHARSET
// from the given file. The previous data is lost.
// Returns true if the operation is successful.
bool load_from_file(const char* const filename, bool skip_fragments) {
FILE* file = fopen(filename, "rb");
if (file == NULL) return false;
bool result = load_from_file(file, skip_fragments);
fclose(file);
return result;
}
// returns true if the operation is successful.
bool load_from_file(const char* const filename) {
return load_from_file(filename, false);
}
// Loads the UNICHARSET from the given file. The previous data is lost.
// Returns true if the operation is successful.
bool load_from_file(FILE *file, bool skip_fragments);
bool load_from_file(FILE *file) { return load_from_file(file, false); }
bool load_from_file(tesseract::TFile *file, bool skip_fragments);
// Sets up internal data after loading the file, based on the char
// properties. Called from load_from_file, but also needs to be run
// during set_unicharset_properties.
void post_load_setup();
// Returns true if right_to_left scripts are significant in the unicharset,
// but without being so sensitive that "universal" unicharsets containing
// characters from many scripts, like orientation and script detection,
// look like they are right_to_left.
bool major_right_to_left() const;
// Set a whitelist and/or blacklist of characters to recognize.
// An empty or NULL whitelist enables everything (minus any blacklist).
// An empty or NULL blacklist disables nothing.
// An empty or NULL unblacklist has no effect.
// The blacklist overrides the whitelist.
// The unblacklist overrides the blacklist.
// Each list is a string of utf8 character strings. Boundaries between
// unicharset units are worked out automatically, and characters not in
// the unicharset are silently ignored.
void set_black_and_whitelist(const char* blacklist, const char* whitelist,
const char* unblacklist);
// Set the isalpha property of the given unichar to the given value.
void set_isalpha(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.isalpha = value;
}
// Set the islower property of the given unichar to the given value.
void set_islower(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.islower = value;
}
// Set the isupper property of the given unichar to the given value.
void set_isupper(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.isupper = value;
}
// Set the isdigit property of the given unichar to the given value.
void set_isdigit(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.isdigit = value;
}
// Set the ispunctuation property of the given unichar to the given value.
void set_ispunctuation(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.ispunctuation = value;
}
// Set the isngram property of the given unichar to the given value.
void set_isngram(UNICHAR_ID unichar_id, bool value) {
unichars[unichar_id].properties.isngram = value;
}
// Set the script name of the given unichar to the given value.
// Value is copied and thus can be a temporary;
void set_script(UNICHAR_ID unichar_id, const char* value) {
unichars[unichar_id].properties.script_id = add_script(value);
}
// Set other_case unichar id in the properties for the given unichar id.
void set_other_case(UNICHAR_ID unichar_id, UNICHAR_ID other_case) {
unichars[unichar_id].properties.other_case = other_case;
}
// Set the direction property of the given unichar to the given value.
void set_direction(UNICHAR_ID unichar_id, UNICHARSET::Direction value) {
unichars[unichar_id].properties.direction = value;
}
// Set mirror unichar id in the properties for the given unichar id.
void set_mirror(UNICHAR_ID unichar_id, UNICHAR_ID mirror) {
unichars[unichar_id].properties.mirror = mirror;
}
// Record normalized version of unichar with the given unichar_id.
void set_normed(UNICHAR_ID unichar_id, const char* normed) {
unichars[unichar_id].properties.normed = normed;
unichars[unichar_id].properties.normed_ids.truncate(0);
}
// Sets the normed_ids vector from the normed string. normed_ids is not
// stored in the file, and needs to be set when the UNICHARSET is loaded.
void set_normed_ids(UNICHAR_ID unichar_id);
// Return the isalpha property of the given unichar.
bool get_isalpha(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.isalpha;
}
// Return the islower property of the given unichar.
bool get_islower(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.islower;
}
// Return the isupper property of the given unichar.
bool get_isupper(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.isupper;
}
// Return the isdigit property of the given unichar.
bool get_isdigit(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.isdigit;
}
// Return the ispunctuation property of the given unichar.
bool get_ispunctuation(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.ispunctuation;
}
// Return the isngram property of the given unichar.
bool get_isngram(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return false;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.isngram;
}
// Returns whether the unichar id represents a unicode value in the private
// use area.
bool get_isprivate(UNICHAR_ID unichar_id) const;
// Returns true if the ids have useful min/max top/bottom values.
bool top_bottom_useful() const {
return top_bottom_set_;
}
// Sets all ranges to empty, so they can be expanded to set the values.
void set_ranges_empty();
// Sets all the properties for this unicharset given a src_unicharset with
// everything set. The unicharsets don't have to be the same, and graphemes
// are correctly accounted for.
void SetPropertiesFromOther(const UNICHARSET& src) {
PartialSetPropertiesFromOther(0, src);
}
// Sets properties from Other, starting only at the given index.
void PartialSetPropertiesFromOther(int start_index, const UNICHARSET& src);
// Expands the tops and bottoms and widths for this unicharset given a
// src_unicharset with ranges in it. The unicharsets don't have to be the
// same, and graphemes are correctly accounted for.
void ExpandRangesFromOther(const UNICHARSET& src);
// Makes this a copy of src. Clears this completely first, so the automattic
// ids will not be present in this if not in src.
void CopyFrom(const UNICHARSET& src);
// For each id in src, if it does not occur in this, add it, as in
// SetPropertiesFromOther, otherwise expand the ranges, as in
// ExpandRangesFromOther.
void AppendOtherUnicharset(const UNICHARSET& src);
// Returns true if the acceptable ranges of the tops of the characters do
// not overlap, making their x-height calculations distinct.
bool SizesDistinct(UNICHAR_ID id1, UNICHAR_ID id2) const;
// Returns the min and max bottom and top of the given unichar in
// baseline-normalized coordinates, ie, where the baseline is
// kBlnBaselineOffset and the meanline is kBlnBaselineOffset + kBlnXHeight
// (See normalis.h for the definitions).
void get_top_bottom(UNICHAR_ID unichar_id,
int* min_bottom, int* max_bottom,
int* min_top, int* max_top) const {
if (INVALID_UNICHAR_ID == unichar_id) {
*min_bottom = *min_top = 0;
*max_bottom = *max_top = 256; // kBlnCellHeight
return;
}
ASSERT_HOST(contains_unichar_id(unichar_id));
*min_bottom = unichars[unichar_id].properties.min_bottom;
*max_bottom = unichars[unichar_id].properties.max_bottom;
*min_top = unichars[unichar_id].properties.min_top;
*max_top = unichars[unichar_id].properties.max_top;
}
void set_top_bottom(UNICHAR_ID unichar_id,
int min_bottom, int max_bottom,
int min_top, int max_top) {
unichars[unichar_id].properties.min_bottom =
static_cast<uinT8>(ClipToRange(min_bottom, 0, MAX_UINT8));
unichars[unichar_id].properties.max_bottom =
static_cast<uinT8>(ClipToRange(max_bottom, 0, MAX_UINT8));
unichars[unichar_id].properties.min_top =
static_cast<uinT8>(ClipToRange(min_top, 0, MAX_UINT8));
unichars[unichar_id].properties.max_top =
static_cast<uinT8>(ClipToRange(max_top, 0, MAX_UINT8));
}
// Returns the width range of the given unichar in baseline-normalized
// coordinates, ie, where the baseline is kBlnBaselineOffset and the
// meanline is kBlnBaselineOffset + kBlnXHeight.
// (See normalis.h for the definitions).
void get_width_range(UNICHAR_ID unichar_id,
int* min_width, int* max_width) const {
if (INVALID_UNICHAR_ID == unichar_id) {
*min_width = 0;
*max_width = 256; // kBlnCellHeight;
return;
}
ASSERT_HOST(contains_unichar_id(unichar_id));
*min_width = unichars[unichar_id].properties.min_width;
*max_width = unichars[unichar_id].properties.max_width;
}
void set_width_range(UNICHAR_ID unichar_id, int min_width, int max_width) {
unichars[unichar_id].properties.min_width =
static_cast<inT16>(ClipToRange(min_width, 0, MAX_INT16));
unichars[unichar_id].properties.max_width =
static_cast<inT16>(ClipToRange(max_width, 0, MAX_INT16));
}
// Returns the range of the x-bearing of the given unichar in
// baseline-normalized coordinates, ie, where the baseline is
// kBlnBaselineOffset and the meanline is kBlnBaselineOffset + kBlnXHeight.
// (See normalis.h for the definitions).
void get_bearing_range(UNICHAR_ID unichar_id,
int* min_bearing, int* max_bearing) const {
if (INVALID_UNICHAR_ID == unichar_id) {
*min_bearing = *max_bearing = 0;
return;
}
ASSERT_HOST(contains_unichar_id(unichar_id));
*min_bearing = unichars[unichar_id].properties.min_bearing;
*max_bearing = unichars[unichar_id].properties.max_bearing;
}
void set_bearing_range(UNICHAR_ID unichar_id,
int min_bearing, int max_bearing) {
unichars[unichar_id].properties.min_bearing =
static_cast<inT16>(ClipToRange(min_bearing, 0, MAX_INT16));
unichars[unichar_id].properties.max_bearing =
static_cast<inT16>(ClipToRange(max_bearing, 0, MAX_INT16));
}
// Returns the range of the x-advance of the given unichar in
// baseline-normalized coordinates, ie, where the baseline is
// kBlnBaselineOffset and the meanline is kBlnBaselineOffset + kBlnXHeight.
// (See normalis.h for the definitions).
void get_advance_range(UNICHAR_ID unichar_id,
int* min_advance, int* max_advance) const {
if (INVALID_UNICHAR_ID == unichar_id) {
*min_advance = *max_advance = 0;
return;
}
ASSERT_HOST(contains_unichar_id(unichar_id));
*min_advance = unichars[unichar_id].properties.min_advance;
*max_advance = unichars[unichar_id].properties.max_advance;
}
void set_advance_range(UNICHAR_ID unichar_id,
int min_advance, int max_advance) {
unichars[unichar_id].properties.min_advance =
static_cast<inT16>(ClipToRange(min_advance, 0, MAX_INT16));
unichars[unichar_id].properties.max_advance =
static_cast<inT16>(ClipToRange(max_advance, 0, MAX_INT16));
}
// Return the script name of the given unichar.
// The returned pointer will always be the same for the same script, it's
// managed by unicharset and thus MUST NOT be deleted
int get_script(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return null_sid_;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.script_id;
}
// Return the character properties, eg. alpha/upper/lower/digit/punct,
// as a bit field of unsigned int.
unsigned int get_properties(UNICHAR_ID unichar_id) const;
// Return the character property as a single char. If a character has
// multiple attributes, the main property is defined by the following order:
// upper_case : 'A'
// lower_case : 'a'
// alpha : 'x'
// digit : '0'
// punctuation: 'p'
char get_chartype(UNICHAR_ID unichar_id) const;
// Get other_case unichar id in the properties for the given unichar id.
UNICHAR_ID get_other_case(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return INVALID_UNICHAR_ID;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.other_case;
}
// Returns the direction property of the given unichar.
Direction get_direction(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return UNICHARSET::U_OTHER_NEUTRAL;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.direction;
}
// Get mirror unichar id in the properties for the given unichar id.
UNICHAR_ID get_mirror(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return INVALID_UNICHAR_ID;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.mirror;
}
// Returns UNICHAR_ID of the corresponding lower-case unichar.
UNICHAR_ID to_lower(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return INVALID_UNICHAR_ID;
ASSERT_HOST(contains_unichar_id(unichar_id));
if (unichars[unichar_id].properties.islower) return unichar_id;
return unichars[unichar_id].properties.other_case;
}
// Returns UNICHAR_ID of the corresponding upper-case unichar.
UNICHAR_ID to_upper(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return INVALID_UNICHAR_ID;
ASSERT_HOST(contains_unichar_id(unichar_id));
if (unichars[unichar_id].properties.isupper) return unichar_id;
return unichars[unichar_id].properties.other_case;
}
// Returns true if this UNICHARSET has the special codes in
// SpecialUnicharCodes available. If false then there are normal unichars
// at these codes and they should not be used.
bool has_special_codes() const {
return get_fragment(UNICHAR_BROKEN) != NULL &&
strcmp(id_to_unichar(UNICHAR_BROKEN),
kSpecialUnicharCodes[UNICHAR_BROKEN]) == 0;
}
// Return a pointer to the CHAR_FRAGMENT class if the given
// unichar id represents a character fragment.
const CHAR_FRAGMENT *get_fragment(UNICHAR_ID unichar_id) const {
if (INVALID_UNICHAR_ID == unichar_id) return NULL;
ASSERT_HOST(contains_unichar_id(unichar_id));
return unichars[unichar_id].properties.fragment;
}
// Return the isalpha property of the given unichar representation.
bool get_isalpha(const char* const unichar_repr) const {
return get_isalpha(unichar_to_id(unichar_repr));
}
// Return the islower property of the given unichar representation.
bool get_islower(const char* const unichar_repr) const {
return get_islower(unichar_to_id(unichar_repr));
}
// Return the isupper property of the given unichar representation.
bool get_isupper(const char* const unichar_repr) const {
return get_isupper(unichar_to_id(unichar_repr));
}
// Return the isdigit property of the given unichar representation.
bool get_isdigit(const char* const unichar_repr) const {
return get_isdigit(unichar_to_id(unichar_repr));
}
// Return the ispunctuation property of the given unichar representation.
bool get_ispunctuation(const char* const unichar_repr) const {
return get_ispunctuation(unichar_to_id(unichar_repr));
}
// Return the character properties, eg. alpha/upper/lower/digit/punct,
// of the given unichar representation
unsigned int get_properties(const char* const unichar_repr) const {
return get_properties(unichar_to_id(unichar_repr));
}
char get_chartype(const char* const unichar_repr) const {
return get_chartype(unichar_to_id(unichar_repr));
}
// Return the script name of the given unichar representation.
// The returned pointer will always be the same for the same script, it's
// managed by unicharset and thus MUST NOT be deleted
int get_script(const char* const unichar_repr) const {
return get_script(unichar_to_id(unichar_repr));
}
// Return a pointer to the CHAR_FRAGMENT class struct if the given
// unichar representation represents a character fragment.
const CHAR_FRAGMENT *get_fragment(const char* const unichar_repr) const {
if (unichar_repr == NULL || unichar_repr[0] == '\0' ||
!ids.contains(unichar_repr)) {
return NULL;
}
return get_fragment(unichar_to_id(unichar_repr));
}
// Return the isalpha property of the given unichar representation.
// Only the first length characters from unichar_repr are used.
bool get_isalpha(const char* const unichar_repr,
int length) const {
return get_isalpha(unichar_to_id(unichar_repr, length));
}
// Return the islower property of the given unichar representation.
// Only the first length characters from unichar_repr are used.
bool get_islower(const char* const unichar_repr,
int length) const {
return get_islower(unichar_to_id(unichar_repr, length));
}
// Return the isupper property of the given unichar representation.
// Only the first length characters from unichar_repr are used.
bool get_isupper(const char* const unichar_repr,
int length) const {
return get_isupper(unichar_to_id(unichar_repr, length));
}
// Return the isdigit property of the given unichar representation.
// Only the first length characters from unichar_repr are used.
bool get_isdigit(const char* const unichar_repr,
int length) const {
return get_isdigit(unichar_to_id(unichar_repr, length));
}
// Return the ispunctuation property of the given unichar representation.
// Only the first length characters from unichar_repr are used.
bool get_ispunctuation(const char* const unichar_repr,
int length) const {
return get_ispunctuation(unichar_to_id(unichar_repr, length));
}
// Returns normalized version of unichar with the given unichar_id.
const char *get_normed_unichar(UNICHAR_ID unichar_id) const {
return unichars[unichar_id].properties.normed.string();
}
// Returns a vector of UNICHAR_IDs that represent the ids of the normalized
// version of the given id. There may be more than one UNICHAR_ID in the
// vector if unichar_id represents a ligature.
const GenericVector<UNICHAR_ID>& normed_ids(UNICHAR_ID unichar_id) const {
return unichars[unichar_id].properties.normed_ids;
}
// Return the script name of the given unichar representation.
// Only the first length characters from unichar_repr are used.
// The returned pointer will always be the same for the same script, it's
// managed by unicharset and thus MUST NOT be deleted
int get_script(const char* const unichar_repr,
int length) const {
return get_script(unichar_to_id(unichar_repr, length));
}
// Return the (current) number of scripts in the script table
int get_script_table_size() const {
return script_table_size_used;
}
// Return the script string from its id
const char* get_script_from_script_id(int id) const {
if (id >= script_table_size_used || id < 0)
return null_script;
return script_table[id];
}
// Returns the id from the name of the script, or 0 if script is not found.
// Note that this is an expensive operation since it involves iteratively
// comparing strings in the script table. To avoid dependency on STL, we
// won't use a hash. Instead, the calling function can use this to lookup
// and save the ID for relevant scripts for fast comparisons later.
int get_script_id_from_name(const char* script_name) const;
// Return true if the given script is the null script
bool is_null_script(const char* script) const {
return script == null_script;
}
// Uniquify the given script. For two scripts a and b, if strcmp(a, b) == 0,
// then the returned pointer will be the same.
// The script parameter is copied and thus can be a temporary.
int add_script(const char* script);
// Return the enabled property of the given unichar.
bool get_enabled(UNICHAR_ID unichar_id) const {
return unichars[unichar_id].properties.enabled;
}
int null_sid() const { return null_sid_; }
int common_sid() const { return common_sid_; }
int latin_sid() const { return latin_sid_; }
int cyrillic_sid() const { return cyrillic_sid_; }
int greek_sid() const { return greek_sid_; }
int han_sid() const { return han_sid_; }
int hiragana_sid() const { return hiragana_sid_; }
int katakana_sid() const { return katakana_sid_; }
int default_sid() const { return default_sid_; }
// Returns true if the unicharset has the concept of upper/lower case.
bool script_has_upper_lower() const {
return script_has_upper_lower_;
}
// Returns true if the unicharset has the concept of x-height.
// script_has_xheight can be true even if script_has_upper_lower is not,
// when the script has a sufficiently predominant top line with ascenders,
// such as Devanagari and Thai.
bool script_has_xheight() const {
return script_has_xheight_;
}
private:
struct UNICHAR_PROPERTIES {
UNICHAR_PROPERTIES();
// Initializes all properties to sensible default values.
void Init();
// Sets all ranges wide open. Initialization default in case there are
// no useful values available.
void SetRangesOpen();
// Sets all ranges to empty. Used before expanding with font-based data.
void SetRangesEmpty();
// Returns true if any of the top/bottom/width/bearing/advance ranges is
// emtpy.
bool AnyRangeEmpty() const;
// Expands the ranges with the ranges from the src properties.
void ExpandRangesFrom(const UNICHAR_PROPERTIES& src);
// Copies the properties from src into this.
void CopyFrom(const UNICHAR_PROPERTIES& src);
bool isalpha;
bool islower;
bool isupper;
bool isdigit;
bool ispunctuation;
bool isngram;
bool enabled;
// Possible limits of the top and bottom of the bounding box in
// baseline-normalized coordinates, ie, where the baseline is
// kBlnBaselineOffset and the meanline is kBlnBaselineOffset + kBlnXHeight
// (See normalis.h for the definitions).
uinT8 min_bottom;
uinT8 max_bottom;
uinT8 min_top;
uinT8 max_top;
// Limits on the widths of bounding box, also in baseline-normalized coords.
inT16 min_width;
inT16 max_width;
// Limits on the x-bearing and advance, also in baseline-normalized coords.
inT16 min_bearing;
inT16 max_bearing;
inT16 min_advance;
inT16 max_advance;
int script_id;
UNICHAR_ID other_case; // id of the corresponding upper/lower case unichar
Direction direction; // direction of this unichar
// Mirror property is useful for reverse DAWG lookup for words in
// right-to-left languages (e.g. "(word)" would be in
// '[open paren]' 'w' 'o' 'r' 'd' '[close paren]' in a UTF8 string.
// However, what we want in our DAWG is
// '[open paren]', 'd', 'r', 'o', 'w', '[close paren]' not
// '[close paren]', 'd', 'r', 'o', 'w', '[open paren]'.
UNICHAR_ID mirror;
// A string of unichar_ids that represent the corresponding normed string.
// For awkward characters like em-dash, this gives hyphen.
// For ligatures, this gives the string of normal unichars.
GenericVector<UNICHAR_ID> normed_ids;
STRING normed; // normalized version of this unichar
// Contains meta information about the fragment if a unichar represents
// a fragment of a character, otherwise should be set to NULL.
// It is assumed that character fragments are added to the unicharset
// after the corresponding 'base' characters.
CHAR_FRAGMENT *fragment;
};
struct UNICHAR_SLOT {
char representation[UNICHAR_LEN + 1];
UNICHAR_PROPERTIES properties;
};
// Internal recursive version of encode_string above.
// str is the start of the whole string.
// str_index is the current position in str.
// str_length is the length of str.
// encoding is a working encoding of str.
// lengths is a working set of lengths of each element of encoding.
// best_total_length is the longest length of str that has been successfully
// encoded so far.
// On return:
// best_encoding contains the encoding that used the longest part of str.
// best_lengths (may be null) contains the lengths of best_encoding.
void encode_string(const char* str, int str_index, int str_length,
GenericVector<UNICHAR_ID>* encoding,
GenericVector<char>* lengths,
int* best_total_length,
GenericVector<UNICHAR_ID>* best_encoding,
GenericVector<char>* best_lengths) const;
// Gets the properties for a grapheme string, combining properties for
// multiple characters in a meaningful way where possible.
// Returns false if no valid match was found in the unicharset.
// NOTE that script_id, mirror, and other_case refer to this unicharset on
// return and will need redirecting if the target unicharset is different.
bool GetStrProperties(const char* utf8_str,
UNICHAR_PROPERTIES* props) const;
// Load ourselves from a "file" where our only interface to the file is
// an implementation of fgets(). This is the parsing primitive accessed by
// the public routines load_from_file() and load_from_inmemory_file().
bool load_via_fgets(TessResultCallback2<char *, char *, int> *fgets_cb,
bool skip_fragments);
UNICHAR_SLOT* unichars;
UNICHARMAP ids;
int size_used;
int size_reserved;
char** script_table;
int script_table_size_used;
int script_table_size_reserved;
const char* null_script;
// True if the unichars have their tops/bottoms set.
bool top_bottom_set_;
// True if the unicharset has significant upper/lower case chars.
bool script_has_upper_lower_;
// True if the unicharset has a significant mean-line with significant
// ascenders above that.
bool script_has_xheight_;
// A few convenient script name-to-id mapping without using hash.
// These are initialized when unicharset file is loaded. Anything
// missing from this list can be looked up using get_script_id_from_name.
int null_sid_;
int common_sid_;
int latin_sid_;
int cyrillic_sid_;
int greek_sid_;
int han_sid_;
int hiragana_sid_;
int katakana_sid_;
// The most frequently occurring script in the charset.
int default_sid_;
};
#endif // TESSERACT_CCUTIL_UNICHARSET_H__
| C++ |
///////////////////////////////////////////////////////////////////////
// File: associate.h
// Description: Structs, classes, typedefs useful for the segmentation
// search. Functions for scoring segmentation paths according
// to their character widths, gap widths and seam cuts.
// Author: Daria Antonova
// Created: Mon Mar 8 11:26:43 PDT 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef ASSOCIATE_H
#define ASSOCIATE_H
#include "blobs.h"
#include "elst.h"
#include "ratngs.h"
#include "seam.h"
#include "split.h"
class WERD_RES;
namespace tesseract {
// Statisitcs about character widths, gaps and seams.
struct AssociateStats {
AssociateStats() { Clear(); }
void Clear() {
shape_cost = 0.0f;
bad_shape = false;
full_wh_ratio = 0.0f;
full_wh_ratio_total = 0.0f;
full_wh_ratio_var = 0.0f;
bad_fixed_pitch_right_gap = false;
bad_fixed_pitch_wh_ratio = false;
gap_sum = 0;
}
void Print() {
tprintf("AssociateStats: w(%g %d) s(%g %d)\n", shape_cost, bad_shape);
}
float shape_cost; // cost of blob shape
bool bad_shape; // true if the shape of the blob is unacceptable
float full_wh_ratio; // width-to-hight ratio + gap on the right
float full_wh_ratio_total; // sum of width-to-hight ratios
// on the path terminating at this blob
float full_wh_ratio_var; // variance of full_wh_ratios on the path
bool bad_fixed_pitch_right_gap; // true if there is no gap before
// the blob on the right
bool bad_fixed_pitch_wh_ratio; // true if the blobs has width-to-hight
// ratio > kMaxFixedPitchCharAspectRatio
int gap_sum; // sum of gaps within the blob
};
// Utility functions for scoring segmentation paths according to their
// character widths, gap widths, seam characteristics.
class AssociateUtils {
public:
static const float kMaxFixedPitchCharAspectRatio;
static const float kMinGap;
// Returns outline length of the given blob is computed as:
// rating_cert_scale * rating / certainty
// Since from Wordrec::SegSearch() in segsearch.cpp
// rating_cert_scale = -1.0 * getDict().certainty_scale / rating_scale
// And from Classify::ConvertMatchesToChoices() in adaptmatch.cpp
// Rating = Certainty = next.rating
// Rating *= rating_scale * Results->BlobLength
// Certainty *= -(getDict().certainty_scale)
static inline float ComputeOutlineLength(float rating_cert_scale,
const BLOB_CHOICE &b) {
return rating_cert_scale * b.rating() / b.certainty();
}
static inline float ComputeRating(float rating_cert_scale,
float cert, int width) {
return static_cast<float>(width) * cert / rating_cert_scale;
}
// Computes character widths, gaps and seams stats given the
// AssociateStats of the path so far, col, row of the blob that
// is being added to the path, and WERD_RES containing information
// about character widths, gaps and seams.
// Fills associate_cost with the combined shape, gap and seam cost
// of adding a unichar from (col, row) to the path (note that since
// this function could be used to compute the prioritization for
// pain points, (col, row) entry might not be classified yet; thus
// information in the (col, row) entry of the ratings matrix is not used).
//
// Note: the function assumes that word_res, stats and
// associate_cost pointers are not NULL.
static void ComputeStats(int col, int row,
const AssociateStats *parent_stats,
int parent_path_length,
bool fixed_pitch,
float max_char_wh_ratio,
WERD_RES *word_res,
bool debug,
AssociateStats *stats);
// Returns the width cost for fixed-pitch text.
static float FixedPitchWidthCost(float norm_width, float right_gap,
bool end_pos, float max_char_wh_ratio);
// Returns the gap cost for fixed-pitch text (penalizes vertically
// overlapping components).
static inline float FixedPitchGapCost(float norm_gap, bool end_pos) {
return (norm_gap < 0.05 && !end_pos) ? 5.0f : 0.0f;
}
};
} // namespace tesseract
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: params_model.h
// Description: Trained feature serialization for language parameter training.
// Author: David Eger
// Created: Mon Jun 11 11:26:42 PDT 2012
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_WORDREC_PARAMS_MODEL_H_
#define TESSERACT_WORDREC_PARAMS_MODEL_H_
#include "params_training_featdef.h"
#include "ratngs.h"
#include "strngs.h"
namespace tesseract {
// Represents the learned weights for a given language.
class ParamsModel {
public:
// Enum for expressing OCR pass.
enum PassEnum {
PTRAIN_PASS1,
PTRAIN_PASS2,
PTRAIN_NUM_PASSES
};
ParamsModel() : pass_(PTRAIN_PASS1) {}
ParamsModel(const char *lang, const GenericVector<float> &weights) :
lang_(lang), pass_(PTRAIN_PASS1) { weights_vec_[pass_] = weights; }
inline bool Initialized() {
return weights_vec_[pass_].size() == PTRAIN_NUM_FEATURE_TYPES;
}
// Prints out feature weights.
void Print();
// Clears weights for all passes.
void Clear() {
for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) weights_vec_[p].clear();
}
// Copies the weights of the given params model.
void Copy(const ParamsModel &other_model);
// Applies params model weights to the given features.
// Assumes that features is an array of size PTRAIN_NUM_FEATURE_TYPES.
float ComputeCost(const float features[]) const;
bool Equivalent(const ParamsModel &that) const;
// Returns true on success.
bool SaveToFile(const char *full_path) const;
// Returns true on success.
bool LoadFromFile(const char *lang, const char *full_path);
bool LoadFromFp(const char *lang, FILE *fp, inT64 end_offset);
const GenericVector<float>& weights() const {
return weights_vec_[pass_];
}
const GenericVector<float>& weights_for_pass(PassEnum pass) const {
return weights_vec_[pass];
}
void SetPass(PassEnum pass) { pass_ = pass; }
private:
bool ParseLine(char *line, char **key, float *val);
STRING lang_;
// Set to the current pass type and used to determine which set of weights
// should be used for ComputeCost() and other functions.
PassEnum pass_;
// Several sets of weights for various OCR passes (e.g. pass1 with adaption,
// pass2 without adaption, etc).
GenericVector<float> weights_vec_[PTRAIN_NUM_PASSES];
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_PARAMS_MODEL_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: language_model.h
// Description: Functions that utilize the knowledge about the properties,
// structure and statistics of the language to help segmentation
// search.
// Author: Daria Antonova
// Created: Mon Nov 11 11:26:43 PST 2009
//
// (C) Copyright 2009, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_WORDREC_LANGUAGE_MODEL_H_
#define TESSERACT_WORDREC_LANGUAGE_MODEL_H_
#include "associate.h"
#include "dawg.h"
#include "dict.h"
#include "fontinfo.h"
#include "intproto.h"
#include "lm_consistency.h"
#include "lm_pain_points.h"
#include "lm_state.h"
#include "matrix.h"
#include "params.h"
#include "pageres.h"
#include "params_model.h"
namespace tesseract {
// This class that contains the data structures and functions necessary
// to represent and use the knowledge about the language.
class LanguageModel {
public:
// Masks for keeping track of top choices that should not be pruned out.
static const LanguageModelFlagsType kSmallestRatingFlag = 0x1;
static const LanguageModelFlagsType kLowerCaseFlag = 0x2;
static const LanguageModelFlagsType kUpperCaseFlag = 0x4;
static const LanguageModelFlagsType kDigitFlag = 0x8;
static const LanguageModelFlagsType kXhtConsistentFlag = 0x10;
// Denominator for normalizing per-letter ngram cost when deriving
// penalty adjustments.
static const float kMaxAvgNgramCost;
LanguageModel(const UnicityTable<FontInfo> *fontinfo_table, Dict *dict);
~LanguageModel();
// Fills the given floats array with features extracted from path represented
// by the given ViterbiStateEntry. See ccstruct/params_training_featdef.h
// for feature information.
// Note: the function assumes that features points to an array of size
// PTRAIN_NUM_FEATURE_TYPES.
static void ExtractFeaturesFromPath(const ViterbiStateEntry &vse,
float features[]);
// Updates data structures that are used for the duration of the segmentation
// search on the current word;
void InitForWord(const WERD_CHOICE *prev_word,
bool fixed_pitch, float max_char_wh_ratio,
float rating_cert_scale);
// Updates language model state of the given BLOB_CHOICE_LIST (from
// the ratings matrix) a its parent. Updates pain_points if new
// problematic points are found in the segmentation graph.
//
// At most language_model_viterbi_list_size are kept in each
// LanguageModelState.viterbi_state_entries list.
// At most language_model_viterbi_list_max_num_prunable of those are prunable
// (non-dictionary) paths.
// The entries that represent dictionary word paths are kept at the front
// of the list.
// The list ordered by cost that is computed collectively by several
// language model components (currently dawg and ngram components).
bool UpdateState(
bool just_classified,
int curr_col, int curr_row,
BLOB_CHOICE_LIST *curr_list,
LanguageModelState *parent_node,
LMPainPoints *pain_points,
WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle);
// Returns true if an acceptable best choice was discovered.
inline bool AcceptableChoiceFound() { return acceptable_choice_found_; }
inline void SetAcceptableChoiceFound(bool val) {
acceptable_choice_found_ = val;
}
// Returns the reference to ParamsModel.
inline ParamsModel &getParamsModel() { return params_model_; }
protected:
inline float CertaintyScore(float cert) {
if (language_model_use_sigmoidal_certainty) {
// cert is assumed to be between 0 and -dict_->certainty_scale.
// If you enable language_model_use_sigmoidal_certainty, you
// need to adjust language_model_ngram_nonmatch_score as well.
cert = -cert / dict_->certainty_scale;
return 1.0f / (1.0f + exp(10.0f * cert));
} else {
return (-1.0f / cert);
}
}
inline float ComputeAdjustment(int num_problems, float penalty) {
if (num_problems == 0) return 0.0f;
if (num_problems == 1) return penalty;
return (penalty + (language_model_penalty_increment *
static_cast<float>(num_problems-1)));
}
// Computes the adjustment to the ratings sum based on the given
// consistency_info. The paths with invalid punctuation, inconsistent
// case and character type are penalized proportionally to the number
// of inconsistencies on the path.
inline float ComputeConsistencyAdjustment(
const LanguageModelDawgInfo *dawg_info,
const LMConsistencyInfo &consistency_info) {
if (dawg_info != NULL) {
return ComputeAdjustment(consistency_info.NumInconsistentCase(),
language_model_penalty_case) +
(consistency_info.inconsistent_script ?
language_model_penalty_script : 0.0f);
}
return (ComputeAdjustment(consistency_info.NumInconsistentPunc(),
language_model_penalty_punc) +
ComputeAdjustment(consistency_info.NumInconsistentCase(),
language_model_penalty_case) +
ComputeAdjustment(consistency_info.NumInconsistentChartype(),
language_model_penalty_chartype) +
ComputeAdjustment(consistency_info.NumInconsistentSpaces(),
language_model_penalty_spacing) +
(consistency_info.inconsistent_script ?
language_model_penalty_script : 0.0f) +
(consistency_info.inconsistent_font ?
language_model_penalty_font : 0.0f));
}
// Returns an adjusted ratings sum that includes inconsistency penalties,
// penalties for non-dictionary paths and paths with dips in ngram
// probability.
float ComputeAdjustedPathCost(ViterbiStateEntry *vse);
// Finds the first lower and upper case letter and first digit in curr_list.
// Uses the first character in the list in place of empty results.
// Returns true if both alpha and digits are found.
bool GetTopLowerUpperDigit(BLOB_CHOICE_LIST *curr_list,
BLOB_CHOICE **first_lower,
BLOB_CHOICE **first_upper,
BLOB_CHOICE **first_digit) const;
// Forces there to be at least one entry in the overall set of the
// viterbi_state_entries of each element of parent_node that has the
// top_choice_flag set for lower, upper and digit using the same rules as
// GetTopLowerUpperDigit, setting the flag on the first found suitable
// candidate, whether or not the flag is set on some other parent.
// Returns 1 if both alpha and digits are found among the parents, -1 if no
// parents are found at all (a legitimate case), and 0 otherwise.
int SetTopParentLowerUpperDigit(LanguageModelState *parent_node) const;
// Finds the next ViterbiStateEntry with which the given unichar_id can
// combine sensibly, taking into account any mixed alnum/mixed case
// situation, and whether this combination has been inspected before.
ViterbiStateEntry* GetNextParentVSE(
bool just_classified, bool mixed_alnum,
const BLOB_CHOICE* bc, LanguageModelFlagsType blob_choice_flags,
const UNICHARSET& unicharset, WERD_RES* word_res,
ViterbiStateEntry_IT* vse_it,
LanguageModelFlagsType* top_choice_flags) const;
// Helper function that computes the cost of the path composed of the
// path in the given parent ViterbiStateEntry and the given BLOB_CHOICE.
// If the new path looks good enough, adds a new ViterbiStateEntry to the
// list of viterbi entries in the given BLOB_CHOICE and returns true.
bool AddViterbiStateEntry(
LanguageModelFlagsType top_choice_flags, float denom, bool word_end,
int curr_col, int curr_row, BLOB_CHOICE *b,
LanguageModelState *curr_state, ViterbiStateEntry *parent_vse,
LMPainPoints *pain_points, WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle, BlamerBundle *blamer_bundle);
// Determines whether a potential entry is a true top choice and
// updates changed accordingly.
//
// Note: The function assumes that b, top_choice_flags and changed
// are not NULL.
void GenerateTopChoiceInfo(ViterbiStateEntry *new_vse,
const ViterbiStateEntry *parent_vse,
LanguageModelState *lms);
// Calls dict_->LetterIsOk() with DawgArgs initialized from parent_vse and
// unichar from b.unichar_id(). Constructs and returns LanguageModelDawgInfo
// with updated active dawgs, constraints and permuter.
//
// Note: the caller is responsible for deleting the returned pointer.
LanguageModelDawgInfo *GenerateDawgInfo(bool word_end,
int curr_col, int curr_row,
const BLOB_CHOICE &b,
const ViterbiStateEntry *parent_vse);
// Computes p(unichar | parent context) and records it in ngram_cost.
// If b.unichar_id() is an unlikely continuation of the parent context
// sets found_small_prob to true and returns NULL.
// Otherwise creates a new LanguageModelNgramInfo entry containing the
// updated context (that includes b.unichar_id() at the end) and returns it.
//
// Note: the caller is responsible for deleting the returned pointer.
LanguageModelNgramInfo *GenerateNgramInfo(
const char *unichar, float certainty, float denom,
int curr_col, int curr_row, float outline_length,
const ViterbiStateEntry *parent_vse);
// Computes -(log(prob(classifier)) + log(prob(ngram model)))
// for the given unichar in the given context. If there are multiple
// unichars at one position - takes the average of their probabilities.
// UNICHAR::utf8_step() is used to separate out individual UTF8 characters,
// since probability_in_context() can only handle one at a time (while
// unicharset might contain ngrams and glyphs composed from multiple UTF8
// characters).
float ComputeNgramCost(const char *unichar, float certainty, float denom,
const char *context, int *unichar_step_len,
bool *found_small_prob, float *ngram_prob);
// Computes the normalization factors for the classifier confidences
// (used by ComputeNgramCost()).
float ComputeDenom(BLOB_CHOICE_LIST *curr_list);
// Fills the given consistenty_info based on parent_vse.consistency_info
// and on the consistency of the given unichar_id with parent_vse.
void FillConsistencyInfo(
int curr_col, bool word_end, BLOB_CHOICE *b,
ViterbiStateEntry *parent_vse,
WERD_RES *word_res,
LMConsistencyInfo *consistency_info);
// Constructs WERD_CHOICE by recording unichar_ids of the BLOB_CHOICEs
// on the path represented by the given BLOB_CHOICE and language model
// state entries (lmse, dse). The path is re-constructed by following
// the parent pointers in the the lang model state entries). If the
// constructed WERD_CHOICE is better than the best/raw choice recorded
// in the best_choice_bundle, this function updates the corresponding
// fields and sets best_choice_bunldle->updated to true.
void UpdateBestChoice(ViterbiStateEntry *vse,
LMPainPoints *pain_points,
WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle);
// Constructs a WERD_CHOICE by tracing parent pointers starting with
// the given LanguageModelStateEntry. Returns the constructed word.
// Updates best_char_choices, certainties and state if they are not
// NULL (best_char_choices and certainties are assumed to have the
// length equal to lmse->length).
// The caller is responsible for freeing memory associated with the
// returned WERD_CHOICE.
WERD_CHOICE *ConstructWord(ViterbiStateEntry *vse,
WERD_RES *word_res,
DANGERR *fixpt,
BlamerBundle *blamer_bundle,
bool *truth_path);
// Wrapper around AssociateUtils::ComputeStats().
inline void ComputeAssociateStats(int col, int row,
float max_char_wh_ratio,
ViterbiStateEntry *parent_vse,
WERD_RES *word_res,
AssociateStats *associate_stats) {
AssociateUtils::ComputeStats(
col, row,
(parent_vse != NULL) ? &(parent_vse->associate_stats) : NULL,
(parent_vse != NULL) ? parent_vse->length : 0,
fixed_pitch_, max_char_wh_ratio,
word_res, language_model_debug_level > 2, associate_stats);
}
// Returns true if the path with such top_choice_flags and dawg_info
// could be pruned out (i.e. is neither a system/user/frequent dictionary
// nor a top choice path).
// In non-space delimited languages all paths can be "somewhat" dictionary
// words. In such languages we can not do dictionary-driven path pruning,
// so paths with non-empty dawg_info are considered prunable.
inline bool PrunablePath(const ViterbiStateEntry &vse) {
if (vse.top_choice_flags) return false;
if (vse.dawg_info != NULL &&
(vse.dawg_info->permuter == SYSTEM_DAWG_PERM ||
vse.dawg_info->permuter == USER_DAWG_PERM ||
vse.dawg_info->permuter == FREQ_DAWG_PERM)) return false;
return true;
}
// Returns true if the given ViterbiStateEntry represents an acceptable path.
inline bool AcceptablePath(const ViterbiStateEntry &vse) {
return (vse.dawg_info != NULL || vse.Consistent() ||
(vse.ngram_info != NULL && !vse.ngram_info->pruned));
}
public:
// Parameters.
INT_VAR_H(language_model_debug_level, 0, "Language model debug level");
BOOL_VAR_H(language_model_ngram_on, false,
"Turn on/off the use of character ngram model");
INT_VAR_H(language_model_ngram_order, 8,
"Maximum order of the character ngram model");
INT_VAR_H(language_model_viterbi_list_max_num_prunable, 10,
"Maximum number of prunable (those for which PrunablePath() is"
" true) entries in each viterbi list recorded in BLOB_CHOICEs");
INT_VAR_H(language_model_viterbi_list_max_size, 500,
"Maximum size of viterbi lists recorded in BLOB_CHOICEs");
double_VAR_H(language_model_ngram_small_prob, 0.000001,
"To avoid overly small denominators use this as the floor"
" of the probability returned by the ngram model");
double_VAR_H(language_model_ngram_nonmatch_score, -40.0,
"Average classifier score of a non-matching unichar");
BOOL_VAR_H(language_model_ngram_use_only_first_uft8_step, false,
"Use only the first UTF8 step of the given string"
" when computing log probabilities");
double_VAR_H(language_model_ngram_scale_factor, 0.03,
"Strength of the character ngram model relative to the"
" character classifier ");
double_VAR_H(language_model_ngram_rating_factor, 16.0,
"Factor to bring log-probs into the same range as ratings"
" when multiplied by outline length ");
BOOL_VAR_H(language_model_ngram_space_delimited_language, true,
"Words are delimited by space");
INT_VAR_H(language_model_min_compound_length, 3,
"Minimum length of compound words");
// Penalties used for adjusting path costs and final word rating.
double_VAR_H(language_model_penalty_non_freq_dict_word, 0.1,
"Penalty for words not in the frequent word dictionary");
double_VAR_H(language_model_penalty_non_dict_word, 0.15,
"Penalty for non-dictionary words");
double_VAR_H(language_model_penalty_punc, 0.2,
"Penalty for inconsistent punctuation");
double_VAR_H(language_model_penalty_case, 0.1,
"Penalty for inconsistent case");
double_VAR_H(language_model_penalty_script, 0.5,
"Penalty for inconsistent script");
double_VAR_H(language_model_penalty_chartype, 0.3,
"Penalty for inconsistent character type");
double_VAR_H(language_model_penalty_font, 0.00,
"Penalty for inconsistent font");
double_VAR_H(language_model_penalty_spacing, 0.05,
"Penalty for inconsistent spacing");
double_VAR_H(language_model_penalty_increment, 0.01, "Penalty increment");
INT_VAR_H(wordrec_display_segmentations, 0, "Display Segmentations");
BOOL_VAR_H(language_model_use_sigmoidal_certainty, false,
"Use sigmoidal score for certainty");
protected:
// Member Variables.
// Temporary DawgArgs struct that is re-used across different words to
// avoid dynamic memory re-allocation (should be cleared before each use).
DawgArgs *dawg_args_;
// Scaling for recovering blob outline length from rating and certainty.
float rating_cert_scale_;
// The following variables are set at construction time.
// Pointer to fontinfo table (not owned by LanguageModel).
const UnicityTable<FontInfo> *fontinfo_table_;
// Pointer to Dict class, that is used for querying the dictionaries
// (the pointer is not owned by LanguageModel).
Dict *dict_;
// TODO(daria): the following variables should become LanguageModel params
// when the old code in bestfirst.cpp and heuristic.cpp is deprecated.
//
// Set to true if we are dealing with fixed pitch text
// (set to assume_fixed_pitch_char_segment).
bool fixed_pitch_;
// Max char width-to-height ratio allowed
// (set to segsearch_max_char_wh_ratio).
float max_char_wh_ratio_;
// The following variables are initialized with InitForWord().
// String representation of the classification of the previous word
// (since this is only used by the character ngram model component,
// only the last language_model_ngram_order of the word are stored).
STRING prev_word_str_;
int prev_word_unichar_step_len_;
// Active dawg vector.
DawgPositionVector *very_beginning_active_dawgs_; // includes continuation
DawgPositionVector *beginning_active_dawgs_;
// Set to true if acceptable choice was discovered.
// Note: it would be nice to use this to terminate the search once an
// acceptable choices is found. However we do not do that and once an
// acceptable choice is found we finish looking for alternative choices
// in the current segmentation graph and then exit the search (no more
// classifications are done after an acceptable choice is found).
// This is needed in order to let the search find the words very close to
// the best choice in rating (e.g. what/What, Cat/cat, etc) and log these
// choices. This way the stopper will know that the best choice is not
// ambiguous (i.e. there are best choices in the best choice list that have
// ratings close to the very best one) and will be less likely to mis-adapt.
bool acceptable_choice_found_;
// Set to true if a choice representing correct segmentation was explored.
bool correct_segmentation_explored_;
// Params models containing weights for for computing ViterbiStateEntry costs.
ParamsModel params_model_;
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_LANGUAGE_MODEL_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: lm_consistency.h
// Description: Struct for recording consistency of the paths representing
// OCR hypotheses.
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
////////////////////////////////////////////////////////////////////////
#include "dawg.h"
#include "dict.h"
#include "host.h"
#include "ratngs.h"
#ifndef TESSERACT_WORDREC_CONSISTENCY_H_
#define TESSERACT_WORDREC_CONSISTENCY_H_
namespace tesseract {
static const char * const XHeightConsistencyEnumName[] = {
"XH_GOOD",
"XH_SUBNORMAL",
"XH_INCONSISTENT",
};
// Struct for keeping track of the consistency of the path.
struct LMConsistencyInfo {
enum ChartypeEnum { CT_NONE, CT_ALPHA, CT_DIGIT, CT_OTHER};
// How much do characters have to be shifted away from normal parameters
// before we say they're not normal?
static const int kShiftThresh = 1;
// How much shifting from subscript to superscript and back
// before we declare shenanigans?
static const int kMaxEntropy = 1;
// Script positions - order important for entropy calculation.
static const int kSUB = 0, kNORM = 1, kSUP = 2;
static const int kNumPos = 3;
explicit LMConsistencyInfo(const LMConsistencyInfo* parent_info) {
if (parent_info == NULL) {
// Initialize from scratch.
num_alphas = 0;
num_digits = 0;
num_punc = 0;
num_other = 0;
chartype = CT_NONE;
punc_ref = NO_EDGE;
invalid_punc = false;
num_non_first_upper = 0;
num_lower = 0;
script_id = 0;
inconsistent_script = false;
num_inconsistent_spaces = 0;
inconsistent_font = false;
// Initialize XHeight stats.
for (int i = 0; i < kNumPos; i++) {
xht_count[i] = 0;
xht_count_punc[i] = 0;
xht_lo[i] = 0;
xht_hi[i] = 256; // kBlnCellHeight
}
xht_sp = -1; // This invalid value indicates that there was no parent.
xpos_entropy = 0;
xht_decision = XH_GOOD;
} else {
// Copy parent info
*this = *parent_info;
}
}
inline int NumInconsistentPunc() const {
return invalid_punc ? num_punc : 0;
}
inline int NumInconsistentCase() const {
return (num_non_first_upper > num_lower) ? num_lower : num_non_first_upper;
}
inline int NumInconsistentChartype() const {
return (NumInconsistentPunc() + num_other +
((num_alphas > num_digits) ? num_digits : num_alphas));
}
inline bool Consistent() const {
return (NumInconsistentPunc() == 0 && NumInconsistentCase() == 0 &&
NumInconsistentChartype() == 0 && !inconsistent_script &&
!inconsistent_font && !InconsistentXHeight());
}
inline int NumInconsistentSpaces() const {
return num_inconsistent_spaces;
}
inline int InconsistentXHeight() const {
return xht_decision == XH_INCONSISTENT;
}
void ComputeXheightConsistency(const BLOB_CHOICE *b, bool is_punc);
float BodyMinXHeight() const {
if (InconsistentXHeight())
return 0.0f;
return xht_lo[kNORM];
}
float BodyMaxXHeight() const {
if (InconsistentXHeight())
return static_cast<float>(MAX_INT16);
return xht_hi[kNORM];
}
int num_alphas;
int num_digits;
int num_punc;
int num_other;
ChartypeEnum chartype;
EDGE_REF punc_ref;
bool invalid_punc;
int num_non_first_upper;
int num_lower;
int script_id;
bool inconsistent_script;
int num_inconsistent_spaces;
bool inconsistent_font;
// Metrics clumped by position.
float xht_lo[kNumPos];
float xht_hi[kNumPos];
inT16 xht_count[kNumPos];
inT16 xht_count_punc[kNumPos];
inT16 xht_sp;
inT16 xpos_entropy;
XHeightConsistencyEnum xht_decision;
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_CONSISTENCY_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: wordrec.cpp
// Description: wordrec class.
// Author: Samuel Charron
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "wordrec.h"
#include "language_model.h"
#include "params.h"
namespace tesseract {
Wordrec::Wordrec() :
// control parameters
BOOL_MEMBER(merge_fragments_in_matrix, TRUE,
"Merge the fragments in the ratings matrix and delete them"
" after merging", params()),
BOOL_MEMBER(wordrec_no_block, FALSE, "Don't output block information",
params()),
BOOL_MEMBER(wordrec_enable_assoc, TRUE, "Associator Enable",
params()),
BOOL_MEMBER(force_word_assoc, FALSE,
"force associator to run regardless of what enable_assoc is."
"This is used for CJK where component grouping is necessary.",
CCUtil::params()),
double_MEMBER(wordrec_worst_state, 1.0, "Worst segmentation state",
params()),
BOOL_MEMBER(fragments_guide_chopper, FALSE,
"Use information from fragments to guide chopping process",
params()),
INT_MEMBER(repair_unchopped_blobs, 1, "Fix blobs that aren't chopped",
params()),
double_MEMBER(tessedit_certainty_threshold, -2.25, "Good blob limit",
params()),
INT_MEMBER(chop_debug, 0, "Chop debug",
params()),
BOOL_MEMBER(chop_enable, 1, "Chop enable",
params()),
BOOL_MEMBER(chop_vertical_creep, 0, "Vertical creep",
params()),
INT_MEMBER(chop_split_length, 10000, "Split Length",
params()),
INT_MEMBER(chop_same_distance, 2, "Same distance",
params()),
INT_MEMBER(chop_min_outline_points, 6, "Min Number of Points on Outline",
params()),
INT_MEMBER(chop_seam_pile_size, 150, "Max number of seams in seam_pile",
params()),
BOOL_MEMBER(chop_new_seam_pile, 1, "Use new seam_pile", params()),
INT_MEMBER(chop_inside_angle, -50, "Min Inside Angle Bend",
params()),
INT_MEMBER(chop_min_outline_area, 2000, "Min Outline Area",
params()),
double_MEMBER(chop_split_dist_knob, 0.5, "Split length adjustment",
params()),
double_MEMBER(chop_overlap_knob, 0.9, "Split overlap adjustment",
params()),
double_MEMBER(chop_center_knob, 0.15, "Split center adjustment",
params()),
INT_MEMBER(chop_centered_maxwidth, 90, "Width of (smaller) chopped blobs "
"above which we don't care that a chop is not near the center.",
params()),
double_MEMBER(chop_sharpness_knob, 0.06, "Split sharpness adjustment",
params()),
double_MEMBER(chop_width_change_knob, 5.0, "Width change adjustment",
params()),
double_MEMBER(chop_ok_split, 100.0, "OK split limit",
params()),
double_MEMBER(chop_good_split, 50.0, "Good split limit",
params()),
INT_MEMBER(chop_x_y_weight, 3, "X / Y length weight",
params()),
INT_MEMBER(segment_adjust_debug, 0, "Segmentation adjustment debug",
params()),
BOOL_MEMBER(assume_fixed_pitch_char_segment, FALSE,
"include fixed-pitch heuristics in char segmentation",
params()),
INT_MEMBER(wordrec_debug_level, 0,
"Debug level for wordrec", params()),
INT_MEMBER(wordrec_max_join_chunks, 4,
"Max number of broken pieces to associate", params()),
BOOL_MEMBER(wordrec_skip_no_truth_words, false,
"Only run OCR for words that had truth recorded in BlamerBundle",
params()),
BOOL_MEMBER(wordrec_debug_blamer, false,
"Print blamer debug messages", params()),
BOOL_MEMBER(wordrec_run_blamer, false,
"Try to set the blame for errors", params()),
INT_MEMBER(segsearch_debug_level, 0,
"SegSearch debug level", params()),
INT_MEMBER(segsearch_max_pain_points, 2000,
"Maximum number of pain points stored in the queue",
params()),
INT_MEMBER(segsearch_max_futile_classifications, 20,
"Maximum number of pain point classifications per chunk that"
"did not result in finding a better word choice.",
params()),
double_MEMBER(segsearch_max_char_wh_ratio, 2.0,
"Maximum character width-to-height ratio", params()),
BOOL_MEMBER(save_alt_choices, true,
"Save alternative paths found during chopping"
" and segmentation search",
params()) {
prev_word_best_choice_ = NULL;
language_model_ = new LanguageModel(&get_fontinfo_table(),
&(getDict()));
fill_lattice_ = NULL;
}
Wordrec::~Wordrec() {
delete language_model_;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: lm_state.h
// Description: Structures and functionality for capturing the state of
// segmentation search guided by the language model.
//
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_WORDREC_LANGUAGE_MODEL_DEFS_H_
#define TESSERACT_WORDREC_LANGUAGE_MODEL_DEFS_H_
#include "associate.h"
#include "elst.h"
#include "dawg.h"
#include "lm_consistency.h"
#include "matrix.h"
#include "ratngs.h"
#include "stopper.h"
#include "strngs.h"
namespace tesseract {
// Used for expressing various language model flags.
typedef unsigned char LanguageModelFlagsType;
// The following structs are used for storing the state of the language model
// in the segmentation search graph. In this graph the nodes are BLOB_CHOICEs
// and the links are the relationships between the underlying blobs (see
// segsearch.h for a more detailed description).
// Each of the BLOB_CHOICEs contains LanguageModelState struct, which has
// a list of N best paths (list of ViterbiStateEntry) explored by the Viterbi
// search leading up to and including this BLOB_CHOICE.
// Each ViterbiStateEntry contains information from various components of the
// language model: dawgs in which the path is found, character ngram model
// probability of the path, script/chartype/font consistency info, state for
// language-specific heuristics (e.g. hyphenated and compound words, lower/upper
// case preferences, etc).
// Each ViterbiStateEntry also contains the parent pointer, so that the path
// that it represents (WERD_CHOICE) can be constructed by following these
// parent pointers.
// Struct for storing additional information used by Dawg language model
// component. It stores the set of active dawgs in which the sequence of
// letters on a path can be found.
struct LanguageModelDawgInfo {
LanguageModelDawgInfo(DawgPositionVector *a, PermuterType pt) : permuter(pt) {
active_dawgs = new DawgPositionVector(*a);
}
~LanguageModelDawgInfo() {
delete active_dawgs;
}
DawgPositionVector *active_dawgs;
PermuterType permuter;
};
// Struct for storing additional information used by Ngram language model
// component.
struct LanguageModelNgramInfo {
LanguageModelNgramInfo(const char *c, int l, bool p, float nc, float ncc)
: context(c), context_unichar_step_len(l), pruned(p), ngram_cost(nc),
ngram_and_classifier_cost(ncc) {}
STRING context; // context string
// Length of the context measured by advancing using UNICHAR::utf8_step()
// (should be at most the order of the character ngram model used).
int context_unichar_step_len;
// The paths with pruned set are pruned out from the perspective of the
// character ngram model. They are explored further because they represent
// a dictionary match or a top choice. Thus ngram_info is still computed
// for them in order to calculate the combined cost.
bool pruned;
// -ln(P_ngram_model(path))
float ngram_cost;
// -[ ln(P_classifier(path)) + scale_factor * ln(P_ngram_model(path)) ]
float ngram_and_classifier_cost;
};
// Struct for storing the information about a path in the segmentation graph
// explored by Viterbi search.
struct ViterbiStateEntry : public ELIST_LINK {
ViterbiStateEntry(ViterbiStateEntry *pe,
BLOB_CHOICE *b, float c, float ol,
const LMConsistencyInfo &ci,
const AssociateStats &as,
LanguageModelFlagsType tcf,
LanguageModelDawgInfo *d,
LanguageModelNgramInfo *n,
const char *debug_uch)
: cost(c), curr_b(b), parent_vse(pe), competing_vse(NULL),
ratings_sum(b->rating()),
min_certainty(b->certainty()), adapted(b->IsAdapted()), length(1),
outline_length(ol), consistency_info(ci), associate_stats(as),
top_choice_flags(tcf), dawg_info(d), ngram_info(n),
updated(true) {
debug_str = (debug_uch == NULL) ? NULL : new STRING();
if (pe != NULL) {
ratings_sum += pe->ratings_sum;
if (pe->min_certainty < min_certainty) {
min_certainty = pe->min_certainty;
}
adapted += pe->adapted;
length += pe->length;
outline_length += pe->outline_length;
if (debug_uch != NULL) *debug_str += *(pe->debug_str);
}
if (debug_str != NULL && debug_uch != NULL) *debug_str += debug_uch;
}
~ViterbiStateEntry() {
delete dawg_info;
delete ngram_info;
delete debug_str;
}
// Comparator function for sorting ViterbiStateEntry_LISTs in
// non-increasing order of costs.
static int Compare(const void *e1, const void *e2) {
const ViterbiStateEntry *ve1 =
*reinterpret_cast<const ViterbiStateEntry * const *>(e1);
const ViterbiStateEntry *ve2 =
*reinterpret_cast<const ViterbiStateEntry * const *>(e2);
return (ve1->cost < ve2->cost) ? -1 : 1;
}
inline bool Consistent() const {
if (dawg_info != NULL && consistency_info.NumInconsistentCase() == 0) {
return true;
}
return consistency_info.Consistent();
}
// Returns true if this VSE has an alphanumeric character as its classifier
// result.
bool HasAlnumChoice(const UNICHARSET& unicharset) {
if (curr_b == NULL) return false;
UNICHAR_ID unichar_id = curr_b->unichar_id();
if (unicharset.get_isalpha(unichar_id) ||
unicharset.get_isdigit(unichar_id))
return true;
return false;
}
void Print(const char *msg) const;
// The cost is an adjusted ratings sum, that is adjusted by all the language
// model components that use Viterbi search.
float cost;
// Pointers to BLOB_CHOICE and parent ViterbiStateEntry (not owned by this).
BLOB_CHOICE *curr_b;
ViterbiStateEntry *parent_vse;
// Pointer to a case-competing ViterbiStateEntry in the same list that
// represents a path ending in the same letter of the opposite case.
ViterbiStateEntry *competing_vse;
// Various information about the characters on the path represented
// by this ViterbiStateEntry.
float ratings_sum; // sum of ratings of character on the path
float min_certainty; // minimum certainty on the path
int adapted; // number of BLOB_CHOICES from adapted templates
int length; // number of characters on the path
float outline_length; // length of the outline so far
LMConsistencyInfo consistency_info; // path consistency info
AssociateStats associate_stats; // character widths/gaps/seams
// Flags for marking the entry as a top choice path with
// the smallest rating or lower/upper case letters).
LanguageModelFlagsType top_choice_flags;
// Extra information maintained by Dawg laguage model component
// (owned by ViterbiStateEntry).
LanguageModelDawgInfo *dawg_info;
// Extra information maintained by Ngram laguage model component
// (owned by ViterbiStateEntry).
LanguageModelNgramInfo *ngram_info;
bool updated; // set to true if the entry has just been created/updated
// UTF8 string representing the path corresponding to this vse.
// Populated only in when language_model_debug_level > 0.
STRING *debug_str;
};
ELISTIZEH(ViterbiStateEntry);
// Struct to store information maintained by various language model components.
struct LanguageModelState {
LanguageModelState() :
viterbi_state_entries_prunable_length(0),
viterbi_state_entries_prunable_max_cost(MAX_FLOAT32),
viterbi_state_entries_length(0) {}
~LanguageModelState() {}
// Clears the viterbi search state back to its initial conditions.
void Clear();
void Print(const char *msg);
// Storage for the Viterbi state.
ViterbiStateEntry_LIST viterbi_state_entries;
// Number and max cost of prunable paths in viterbi_state_entries.
int viterbi_state_entries_prunable_length;
float viterbi_state_entries_prunable_max_cost;
// Total number of entries in viterbi_state_entries.
int viterbi_state_entries_length;
};
// Bundle together all the things pertaining to the best choice/state.
struct BestChoiceBundle {
explicit BestChoiceBundle(int matrix_dimension)
: updated(false), best_vse(NULL) {
beam.reserve(matrix_dimension);
for (int i = 0; i < matrix_dimension; ++i)
beam.push_back(new LanguageModelState);
}
~BestChoiceBundle() {}
// Flag to indicate whether anything was changed.
bool updated;
// Places to try to fix the word suggested by ambiguity checking.
DANGERR fixpt;
// The beam. One LanguageModelState containing a list of ViterbiStateEntry per
// row in the ratings matrix containing all VSEs whose BLOB_CHOICE is
// somewhere in the corresponding row.
PointerVector<LanguageModelState> beam;
// Best ViterbiStateEntry and BLOB_CHOICE.
ViterbiStateEntry *best_vse;
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_LANGUAGE_MODEL_DEFS_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: pain_points.cpp
// Description: Functions that utilize the knowledge about the properties
// of the paths explored by the segmentation search in order
// to "pain points" - the locations in the ratings matrix
// which should be classified next.
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "lm_pain_points.h"
#include "associate.h"
#include "dict.h"
#include "genericheap.h"
#include "lm_state.h"
#include "matrix.h"
#include "pageres.h"
namespace tesseract {
const float LMPainPoints::kDefaultPainPointPriorityAdjustment = 2.0f;
const float LMPainPoints::kLooseMaxCharWhRatio = 2.5f;
LMPainPointsType LMPainPoints::Deque(MATRIX_COORD *pp, float *priority) {
for (int h = 0; h < LM_PPTYPE_NUM; ++h) {
if (pain_points_heaps_[h].empty()) continue;
*priority = pain_points_heaps_[h].PeekTop().key;
*pp = pain_points_heaps_[h].PeekTop().data;
pain_points_heaps_[h].Pop(NULL);
return static_cast<LMPainPointsType>(h);
}
return LM_PPTYPE_NUM;
}
void LMPainPoints::GenerateInitial(WERD_RES *word_res) {
MATRIX *ratings = word_res->ratings;
AssociateStats associate_stats;
for (int col = 0; col < ratings->dimension(); ++col) {
int row_end = MIN(ratings->dimension(), col + ratings->bandwidth() + 1);
for (int row = col + 1; row < row_end; ++row) {
MATRIX_COORD coord(col, row);
if (coord.Valid(*ratings) &&
ratings->get(col, row) != NOT_CLASSIFIED) continue;
// Add an initial pain point if needed.
if (ratings->Classified(col, row - 1, dict_->WildcardID()) ||
(col + 1 < ratings->dimension() &&
ratings->Classified(col + 1, row, dict_->WildcardID()))) {
GeneratePainPoint(col, row, LM_PPTYPE_SHAPE, 0.0,
true, max_char_wh_ratio_, word_res);
}
}
}
}
void LMPainPoints::GenerateFromPath(float rating_cert_scale,
ViterbiStateEntry *vse,
WERD_RES *word_res) {
ViterbiStateEntry *curr_vse = vse;
BLOB_CHOICE *curr_b = vse->curr_b;
// The following pain point generation and priority calculation approaches
// prioritize exploring paths with low average rating of the known part of
// the path, while not relying on the ratings of the pieces to be combined.
//
// A pain point to combine the neighbors is generated for each pair of
// neighboring blobs on the path (the path is represented by vse argument
// given to GenerateFromPath()). The priority of each pain point is set to
// the average rating (per outline length) of the path, not including the
// ratings of the blobs to be combined.
// The ratings of the blobs to be combined are not used to calculate the
// priority, since it is not possible to determine from their magnitude
// whether it will be beneficial to combine the blobs. The reason is that
// chopped junk blobs (/ | - ') can have very good (low) ratings, however
// combining them will be beneficial. Blobs with high ratings might be
// over-joined pieces of characters, but also could be blobs from an unseen
// font or chopped pieces of complex characters.
while (curr_vse->parent_vse != NULL) {
ViterbiStateEntry* parent_vse = curr_vse->parent_vse;
const MATRIX_COORD& curr_cell = curr_b->matrix_cell();
const MATRIX_COORD& parent_cell = parent_vse->curr_b->matrix_cell();
MATRIX_COORD pain_coord(parent_cell.col, curr_cell.row);
if (!pain_coord.Valid(*word_res->ratings) ||
!word_res->ratings->Classified(parent_cell.col, curr_cell.row,
dict_->WildcardID())) {
// rat_subtr contains ratings sum of the two adjacent blobs to be merged.
// rat_subtr will be subtracted from the ratings sum of the path, since
// the blobs will be joined into a new blob, whose rating is yet unknown.
float rat_subtr = curr_b->rating() + parent_vse->curr_b->rating();
// ol_subtr contains the outline length of the blobs that will be joined.
float ol_subtr =
AssociateUtils::ComputeOutlineLength(rating_cert_scale, *curr_b) +
AssociateUtils::ComputeOutlineLength(rating_cert_scale,
*(parent_vse->curr_b));
// ol_dif is the outline of the path without the two blobs to be joined.
float ol_dif = vse->outline_length - ol_subtr;
// priority is set to the average rating of the path per unit of outline,
// not counting the ratings of the pieces to be joined.
float priority = ol_dif > 0 ? (vse->ratings_sum-rat_subtr)/ol_dif : 0.0;
GeneratePainPoint(pain_coord.col, pain_coord.row, LM_PPTYPE_PATH,
priority, true, max_char_wh_ratio_, word_res);
} else if (debug_level_ > 3) {
tprintf("NO pain point (Classified) for col=%d row=%d type=%s\n",
pain_coord.col, pain_coord.row,
LMPainPointsTypeName[LM_PPTYPE_PATH]);
BLOB_CHOICE_IT b_it(word_res->ratings->get(pain_coord.col,
pain_coord.row));
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOB_CHOICE* choice = b_it.data();
choice->print_full();
}
}
curr_vse = parent_vse;
curr_b = curr_vse->curr_b;
}
}
void LMPainPoints::GenerateFromAmbigs(const DANGERR &fixpt,
ViterbiStateEntry *vse,
WERD_RES *word_res) {
// Begins and ends in DANGERR vector now record the blob indices as used
// by the ratings matrix.
for (int d = 0; d < fixpt.size(); ++d) {
const DANGERR_INFO &danger = fixpt[d];
// Only use dangerous ambiguities.
if (danger.dangerous) {
GeneratePainPoint(danger.begin, danger.end - 1,
LM_PPTYPE_AMBIG, vse->cost, true,
kLooseMaxCharWhRatio, word_res);
}
}
}
bool LMPainPoints::GeneratePainPoint(
int col, int row, LMPainPointsType pp_type, float special_priority,
bool ok_to_extend, float max_char_wh_ratio,
WERD_RES *word_res) {
MATRIX_COORD coord(col, row);
if (coord.Valid(*word_res->ratings) &&
word_res->ratings->Classified(col, row, dict_->WildcardID())) {
return false;
}
if (debug_level_ > 3) {
tprintf("Generating pain point for col=%d row=%d type=%s\n",
col, row, LMPainPointsTypeName[pp_type]);
}
// Compute associate stats.
AssociateStats associate_stats;
AssociateUtils::ComputeStats(col, row, NULL, 0, fixed_pitch_,
max_char_wh_ratio, word_res, debug_level_,
&associate_stats);
// For fixed-pitch fonts/languages: if the current combined blob overlaps
// the next blob on the right and it is ok to extend the blob, try extending
// the blob until there is no overlap with the next blob on the right or
// until the width-to-height ratio becomes too large.
if (ok_to_extend) {
while (associate_stats.bad_fixed_pitch_right_gap &&
row + 1 < word_res->ratings->dimension() &&
!associate_stats.bad_fixed_pitch_wh_ratio) {
AssociateUtils::ComputeStats(col, ++row, NULL, 0, fixed_pitch_,
max_char_wh_ratio, word_res, debug_level_,
&associate_stats);
}
}
if (associate_stats.bad_shape) {
if (debug_level_ > 3) {
tprintf("Discarded pain point with a bad shape\n");
}
return false;
}
// Insert the new pain point into pain_points_heap_.
if (pain_points_heaps_[pp_type].size() < max_heap_size_) {
// Compute pain point priority.
float priority;
if (pp_type == LM_PPTYPE_PATH) {
priority = special_priority;
} else {
priority = associate_stats.gap_sum;
}
MatrixCoordPair pain_point(priority, MATRIX_COORD(col, row));
pain_points_heaps_[pp_type].Push(&pain_point);
if (debug_level_) {
tprintf("Added pain point with priority %g\n", priority);
}
return true;
} else {
if (debug_level_) tprintf("Pain points heap is full\n");
return false;
}
}
// Adjusts the pain point coordinates to cope with expansion of the ratings
// matrix due to a split of the blob with the given index.
void LMPainPoints::RemapForSplit(int index) {
for (int i = 0; i < LM_PPTYPE_NUM; ++i) {
GenericVector<MatrixCoordPair>* heap = pain_points_heaps_[i].heap();
for (int j = 0; j < heap->size(); ++j)
(*heap)[j].data.MapForSplit(index);
}
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: wordrec.h
// Description: wordrec class.
// Author: Samuel Charron
//
// (C) Copyright 2006, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_WORDREC_WORDREC_H__
#define TESSERACT_WORDREC_WORDREC_H__
#include "associate.h"
#include "classify.h"
#include "dict.h"
#include "language_model.h"
#include "ratngs.h"
#include "matrix.h"
#include "gradechop.h"
#include "seam.h"
#include "findseam.h"
#include "callcpp.h"
class WERD_RES;
namespace tesseract {
// A class for storing which nodes are to be processed by the segmentation
// search. There is a single SegSearchPending for each column in the ratings
// matrix, and it indicates whether the segsearch should combine all
// BLOB_CHOICES in the column, or just the given row with the parents
// corresponding to *this SegSearchPending, and whether only updated parent
// ViterbiStateEntries should be combined, or all, with the BLOB_CHOICEs.
class SegSearchPending {
public:
SegSearchPending()
: classified_row_(-1),
revisit_whole_column_(false),
column_classified_(false) {}
// Marks the whole column as just classified. Used to start a search on
// a newly initialized ratings matrix.
void SetColumnClassified() {
column_classified_ = true;
}
// Marks the matrix entry at the given row as just classified.
// Used after classifying a new matrix cell.
// Additional to, not overriding a previous RevisitWholeColumn.
void SetBlobClassified(int row) {
classified_row_ = row;
}
// Marks the whole column as needing work, but not just classified.
// Used when the parent vse list is updated.
// Additional to, not overriding a previous SetBlobClassified.
void RevisitWholeColumn() {
revisit_whole_column_ = true;
}
// Clears *this to indicate no work to do.
void Clear() {
classified_row_ = -1;
revisit_whole_column_ = false;
column_classified_ = false;
}
// Returns true if there are updates to do in the column that *this
// represents.
bool WorkToDo() const {
return revisit_whole_column_ || column_classified_ || classified_row_ >= 0;
}
// Returns true if the given row was just classified.
bool IsRowJustClassified(int row) const {
return row == classified_row_ || column_classified_;
}
// Returns the single row to process if there is only one, otherwise -1.
int SingleRow() const {
return revisit_whole_column_ || column_classified_ ? -1 : classified_row_;
}
private:
// If non-negative, indicates the single row in the ratings matrix that has
// just been classified, and so should be combined with all the parents in the
// column that this SegSearchPending represents.
// Operates independently of revisit_whole_column.
int classified_row_;
// If revisit_whole_column is true, then all BLOB_CHOICEs in this column will
// be processed, but classified_row can indicate a row that is newly
// classified. Overridden if column_classified is true.
bool revisit_whole_column_;
// If column_classified is true, parent vses are processed with all rows
// regardless of whether they are just updated, overriding
// revisit_whole_column and classified_row.
bool column_classified_;
};
/* ccmain/tstruct.cpp *********************************************************/
class FRAGMENT:public ELIST_LINK
{
public:
FRAGMENT() { //constructor
}
FRAGMENT(EDGEPT *head_pt, //start
EDGEPT *tail_pt); //end
ICOORD head; //coords of start
ICOORD tail; //coords of end
EDGEPT *headpt; //start point
EDGEPT *tailpt; //end point
};
ELISTIZEH(FRAGMENT)
class Wordrec : public Classify {
public:
// config parameters *******************************************************
BOOL_VAR_H(merge_fragments_in_matrix, TRUE,
"Merge the fragments in the ratings matrix and delete them "
"after merging");
BOOL_VAR_H(wordrec_no_block, FALSE, "Don't output block information");
BOOL_VAR_H(wordrec_enable_assoc, TRUE, "Associator Enable");
BOOL_VAR_H(force_word_assoc, FALSE,
"force associator to run regardless of what enable_assoc is."
"This is used for CJK where component grouping is necessary.");
double_VAR_H(wordrec_worst_state, 1, "Worst segmentation state");
BOOL_VAR_H(fragments_guide_chopper, FALSE,
"Use information from fragments to guide chopping process");
INT_VAR_H(repair_unchopped_blobs, 1, "Fix blobs that aren't chopped");
double_VAR_H(tessedit_certainty_threshold, -2.25, "Good blob limit");
INT_VAR_H(chop_debug, 0, "Chop debug");
BOOL_VAR_H(chop_enable, 1, "Chop enable");
BOOL_VAR_H(chop_vertical_creep, 0, "Vertical creep");
INT_VAR_H(chop_split_length, 10000, "Split Length");
INT_VAR_H(chop_same_distance, 2, "Same distance");
INT_VAR_H(chop_min_outline_points, 6, "Min Number of Points on Outline");
INT_VAR_H(chop_seam_pile_size, 150, "Max number of seams in seam_pile");
BOOL_VAR_H(chop_new_seam_pile, 1, "Use new seam_pile");
INT_VAR_H(chop_inside_angle, -50, "Min Inside Angle Bend");
INT_VAR_H(chop_min_outline_area, 2000, "Min Outline Area");
double_VAR_H(chop_split_dist_knob, 0.5, "Split length adjustment");
double_VAR_H(chop_overlap_knob, 0.9, "Split overlap adjustment");
double_VAR_H(chop_center_knob, 0.15, "Split center adjustment");
INT_VAR_H(chop_centered_maxwidth, 90, "Width of (smaller) chopped blobs "
"above which we don't care that a chop is not near the center.");
double_VAR_H(chop_sharpness_knob, 0.06, "Split sharpness adjustment");
double_VAR_H(chop_width_change_knob, 5.0, "Width change adjustment");
double_VAR_H(chop_ok_split, 100.0, "OK split limit");
double_VAR_H(chop_good_split, 50.0, "Good split limit");
INT_VAR_H(chop_x_y_weight, 3, "X / Y length weight");
INT_VAR_H(segment_adjust_debug, 0, "Segmentation adjustment debug");
BOOL_VAR_H(assume_fixed_pitch_char_segment, FALSE,
"include fixed-pitch heuristics in char segmentation");
INT_VAR_H(wordrec_debug_level, 0, "Debug level for wordrec");
INT_VAR_H(wordrec_max_join_chunks, 4,
"Max number of broken pieces to associate");
BOOL_VAR_H(wordrec_skip_no_truth_words, false,
"Only run OCR for words that had truth recorded in BlamerBundle");
BOOL_VAR_H(wordrec_debug_blamer, false, "Print blamer debug messages");
BOOL_VAR_H(wordrec_run_blamer, false, "Try to set the blame for errors");
INT_VAR_H(segsearch_debug_level, 0, "SegSearch debug level");
INT_VAR_H(segsearch_max_pain_points, 2000,
"Maximum number of pain points stored in the queue");
INT_VAR_H(segsearch_max_futile_classifications, 10,
"Maximum number of pain point classifications per word.");
double_VAR_H(segsearch_max_char_wh_ratio, 2.0,
"Maximum character width-to-height ratio");
BOOL_VAR_H(save_alt_choices, true,
"Save alternative paths found during chopping "
"and segmentation search");
// methods from wordrec/*.cpp ***********************************************
Wordrec();
virtual ~Wordrec();
// Fills word->alt_choices with alternative paths found during
// chopping/segmentation search that are kept in best_choices.
void SaveAltChoices(const LIST &best_choices, WERD_RES *word);
// Fills character choice lattice in the given BlamerBundle
// using the given ratings matrix and best choice list.
void FillLattice(const MATRIX &ratings, const WERD_CHOICE_LIST &best_choices,
const UNICHARSET &unicharset, BlamerBundle *blamer_bundle);
// Calls fill_lattice_ member function
// (assumes that fill_lattice_ is not NULL).
void CallFillLattice(const MATRIX &ratings,
const WERD_CHOICE_LIST &best_choices,
const UNICHARSET &unicharset,
BlamerBundle *blamer_bundle) {
(this->*fill_lattice_)(ratings, best_choices, unicharset, blamer_bundle);
}
// tface.cpp
void program_editup(const char *textbase,
bool init_classifier,
bool init_permute);
void cc_recog(WERD_RES *word);
void program_editdown(inT32 elasped_time);
void set_pass1();
void set_pass2();
int end_recog();
BLOB_CHOICE_LIST *call_matcher(TBLOB* blob);
int dict_word(const WERD_CHOICE &word);
// wordclass.cpp
BLOB_CHOICE_LIST *classify_blob(TBLOB *blob,
const char *string,
C_COL color,
BlamerBundle *blamer_bundle);
// segsearch.cpp
// SegSearch works on the lower diagonal matrix of BLOB_CHOICE_LISTs.
// Each entry in the matrix represents the classification choice
// for a chunk, i.e. an entry in row 2, column 1 represents the list
// of ratings for the chunks 1 and 2 classified as a single blob.
// The entries on the diagonal of the matrix are classifier choice lists
// for a single chunk from the maximal segmentation.
//
// The ratings matrix given to SegSearch represents the segmentation
// graph / trellis for the current word. The nodes in the graph are the
// individual BLOB_CHOICEs in each of the BLOB_CHOICE_LISTs in the ratings
// matrix. The children of each node (nodes connected by outgoing links)
// are the entries in the column that is equal to node's row+1. The parents
// (nodes connected by the incoming links) are the entries in the row that
// is equal to the node's column-1. Here is an example ratings matrix:
//
// 0 1 2 3 4
// -------------------------
// 0| c,( |
// 1| d l,1 |
// 2| o |
// 3| c,( |
// 4| g,y l,1 |
// -------------------------
//
// In the example above node "o" has children (outgoing connection to nodes)
// "c","(","g","y" and parents (incoming connections from nodes) "l","1","d".
//
// The objective of the search is to find the least cost path, where the cost
// is determined by the language model components and the properties of the
// cut between the blobs on the path. SegSearch starts by populating the
// matrix with the all the entries that were classified by the chopper and
// finding the initial best path. Based on the classifier ratings, language
// model scores and the properties of each cut, a list of "pain points" is
// constructed - those are the points on the path where the choices do not
// look consistent with the neighboring choices, the cuts look particularly
// problematic, or the certainties of the blobs are low. The most troublesome
// "pain point" is picked from the list and the new entry in the ratings
// matrix corresponding to this "pain point" is filled in. Then the language
// model state is updated to reflect the new classification and the new
// "pain points" are added to the list and the next most troublesome
// "pain point" is determined. This continues until either the word choice
// composed from the best paths in the segmentation graph is "good enough"
// (e.g. above a certain certainty threshold, is an unambiguous dictionary
// word, etc) or there are no more "pain points" to explore.
//
// If associate_blobs is set to false no new classifications will be done
// to combine blobs. Segmentation search will run only one "iteration"
// on the classifications already recorded in chunks_record.ratings.
//
// Note: this function assumes that word_res, best_choice_bundle arguments
// are not NULL.
void SegSearch(WERD_RES* word_res,
BestChoiceBundle* best_choice_bundle,
BlamerBundle* blamer_bundle);
// Setup and run just the initial segsearch on an established matrix,
// without doing any additional chopping or joining.
void WordSearch(WERD_RES* word_res);
// Setup and run just the initial segsearch on an established matrix,
// without doing any additional chopping or joining.
// (Internal factored version that can be used as part of the main SegSearch.)
void InitialSegSearch(WERD_RES* word_res, LMPainPoints* pain_points,
GenericVector<SegSearchPending>* pending,
BestChoiceBundle* best_choice_bundle,
BlamerBundle* blamer_bundle);
// Runs SegSearch() function (above) without needing a best_choice_bundle
// or blamer_bundle. Used for testing.
void DoSegSearch(WERD_RES* word_res);
// chop.cpp
PRIORITY point_priority(EDGEPT *point);
void add_point_to_list(PointHeap* point_heap, EDGEPT *point);
int angle_change(EDGEPT *point1, EDGEPT *point2, EDGEPT *point3);
int is_little_chunk(EDGEPT *point1, EDGEPT *point2);
int is_small_area(EDGEPT *point1, EDGEPT *point2);
EDGEPT *pick_close_point(EDGEPT *critical_point,
EDGEPT *vertical_point,
int *best_dist);
void prioritize_points(TESSLINE *outline, PointHeap* points);
void new_min_point(EDGEPT *local_min, PointHeap* points);
void new_max_point(EDGEPT *local_max, PointHeap* points);
void vertical_projection_point(EDGEPT *split_point, EDGEPT *target_point,
EDGEPT** best_point,
EDGEPT_CLIST *new_points);
// chopper.cpp
SEAM *attempt_blob_chop(TWERD *word, TBLOB *blob, inT32 blob_number,
bool italic_blob, const GenericVector<SEAM*>& seams);
SEAM *chop_numbered_blob(TWERD *word, inT32 blob_number,
bool italic_blob, const GenericVector<SEAM*>& seams);
SEAM *chop_overlapping_blob(const GenericVector<TBOX>& boxes,
bool italic_blob,
WERD_RES *word_res, int *blob_number);
SEAM *improve_one_blob(const GenericVector<BLOB_CHOICE*> &blob_choices,
DANGERR *fixpt,
bool split_next_to_fragment,
bool italic_blob,
WERD_RES *word,
int *blob_number);
SEAM *chop_one_blob(const GenericVector<TBOX> &boxes,
const GenericVector<BLOB_CHOICE*> &blob_choices,
WERD_RES *word_res,
int *blob_number);
void chop_word_main(WERD_RES *word);
void improve_by_chopping(float rating_cert_scale,
WERD_RES *word,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle,
LMPainPoints *pain_points,
GenericVector<SegSearchPending>* pending);
int select_blob_to_split(const GenericVector<BLOB_CHOICE*> &blob_choices,
float rating_ceiling,
bool split_next_to_fragment);
int select_blob_to_split_from_fixpt(DANGERR *fixpt);
// findseam.cpp
void add_seam_to_queue(float new_priority, SEAM *new_seam, SeamQueue* seams);
void choose_best_seam(SeamQueue* seam_queue,
SPLIT *split,
PRIORITY priority,
SEAM **seam_result,
TBLOB *blob,
SeamPile* seam_pile);
void combine_seam(const SeamPile& seam_pile,
const SEAM* seam, SeamQueue* seam_queue);
inT16 constrained_split(SPLIT *split, TBLOB *blob);
SEAM *pick_good_seam(TBLOB *blob);
PRIORITY seam_priority(SEAM *seam, inT16 xmin, inT16 xmax);
void try_point_pairs (EDGEPT * points[MAX_NUM_POINTS],
inT16 num_points,
SeamQueue* seam_queue,
SeamPile* seam_pile,
SEAM ** seam, TBLOB * blob);
void try_vertical_splits(EDGEPT * points[MAX_NUM_POINTS],
inT16 num_points,
EDGEPT_CLIST *new_points,
SeamQueue* seam_queue,
SeamPile* seam_pile,
SEAM ** seam, TBLOB * blob);
// gradechop.cpp
PRIORITY full_split_priority(SPLIT *split, inT16 xmin, inT16 xmax);
PRIORITY grade_center_of_blob(register BOUNDS_RECT rect);
PRIORITY grade_overlap(register BOUNDS_RECT rect);
PRIORITY grade_split_length(register SPLIT *split);
PRIORITY grade_sharpness(register SPLIT *split);
PRIORITY grade_width_change(register BOUNDS_RECT rect);
void set_outline_bounds(register EDGEPT *point1,
register EDGEPT *point2,
BOUNDS_RECT rect);
// outlines.cpp
int crosses_outline(EDGEPT *p0, EDGEPT *p1, EDGEPT *outline);
int is_crossed(TPOINT a0, TPOINT a1, TPOINT b0, TPOINT b1);
int is_same_edgept(EDGEPT *p1, EDGEPT *p2);
bool near_point(EDGEPT *point, EDGEPT *line_pt_0, EDGEPT *line_pt_1,
EDGEPT **near_pt);
void reverse_outline(EDGEPT *outline);
// pieces.cpp
virtual BLOB_CHOICE_LIST *classify_piece(const GenericVector<SEAM*>& seams,
inT16 start,
inT16 end,
const char* description,
TWERD *word,
BlamerBundle *blamer_bundle);
// Try to merge fragments in the ratings matrix and put the result in
// the corresponding row and column
void merge_fragments(MATRIX *ratings,
inT16 num_blobs);
// Recursively go through the ratings matrix to find lists of fragments
// to be merged in the function merge_and_put_fragment_lists.
// current_frag is the postion of the piece we are looking for.
// current_row is the row in the rating matrix we are currently at.
// start is the row we started initially, so that we can know where
// to append the results to the matrix. num_frag_parts is the total
// number of pieces we are looking for and num_blobs is the size of the
// ratings matrix.
void get_fragment_lists(inT16 current_frag,
inT16 current_row,
inT16 start,
inT16 num_frag_parts,
inT16 num_blobs,
MATRIX *ratings,
BLOB_CHOICE_LIST *choice_lists);
// Merge the fragment lists in choice_lists and append it to the
// ratings matrix
void merge_and_put_fragment_lists(inT16 row,
inT16 column,
inT16 num_frag_parts,
BLOB_CHOICE_LIST *choice_lists,
MATRIX *ratings);
// Filter the fragment list so that the filtered_choices only contain
// fragments that are in the correct position. choices is the list
// that we are going to filter. fragment_pos is the position in the
// fragment that we are looking for and num_frag_parts is the the
// total number of pieces. The result will be appended to
// filtered_choices.
void fill_filtered_fragment_list(BLOB_CHOICE_LIST *choices,
int fragment_pos,
int num_frag_parts,
BLOB_CHOICE_LIST *filtered_choices);
// Member variables.
LanguageModel *language_model_;
PRIORITY pass2_ok_split;
// Stores the best choice for the previous word in the paragraph.
// This variable is modified by PAGE_RES_IT when iterating over
// words to OCR on the page.
WERD_CHOICE *prev_word_best_choice_;
// Sums of blame reasons computed by the blamer.
GenericVector<int> blame_reasons_;
// Function used to fill char choice lattices.
void (Wordrec::*fill_lattice_)(const MATRIX &ratings,
const WERD_CHOICE_LIST &best_choices,
const UNICHARSET &unicharset,
BlamerBundle *blamer_bundle);
protected:
inline bool SegSearchDone(int num_futile_classifications) {
return (language_model_->AcceptableChoiceFound() ||
num_futile_classifications >=
segsearch_max_futile_classifications);
}
// Updates the language model state recorded for the child entries specified
// in pending[starting_col]. Enqueues the children of the updated entries
// into pending and proceeds to update (and remove from pending) all the
// remaining entries in pending[col] (col >= starting_col). Upon termination
// of this function all the pending[col] lists will be empty.
//
// The arguments:
//
// starting_col: index of the column in chunks_record->ratings from
// which the update should be started
//
// pending: list of entries listing chunks_record->ratings entries
// that should be updated
//
// pain_points: priority heap listing the pain points generated by
// the language model
//
// temp_pain_points: temporary storage for tentative pain points generated
// by the language model after a single call to LanguageModel::UpdateState()
// (the argument is passed in rather than created before each
// LanguageModel::UpdateState() call to avoid dynamic memory re-allocation)
//
// best_choice_bundle: a collection of variables that should be updated
// if a new best choice is found
//
void UpdateSegSearchNodes(
float rating_cert_scale,
int starting_col,
GenericVector<SegSearchPending>* pending,
WERD_RES *word_res,
LMPainPoints *pain_points,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle);
// Process the given pain point: classify the corresponding blob, enqueue
// new pain points to join the newly classified blob with its neighbors.
void ProcessSegSearchPainPoint(float pain_point_priority,
const MATRIX_COORD &pain_point,
const char* pain_point_type,
GenericVector<SegSearchPending>* pending,
WERD_RES *word_res,
LMPainPoints *pain_points,
BlamerBundle *blamer_bundle);
// Resets enough of the results so that the Viterbi search is re-run.
// Needed when the n-gram model is enabled, as the multi-length comparison
// implementation will re-value existing paths to worse values.
void ResetNGramSearch(WERD_RES* word_res,
BestChoiceBundle* best_choice_bundle,
GenericVector<SegSearchPending>* pending);
// Add pain points for classifying blobs on the correct segmentation path
// (so that we can evaluate correct segmentation path and discover the reason
// for incorrect result).
void InitBlamerForSegSearch(WERD_RES *word_res,
LMPainPoints *pain_points,
BlamerBundle *blamer_bundle,
STRING *blamer_debug);
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_WORDREC_H__
| C++ |
///////////////////////////////////////////////////////////////////////
// File: associate.cpp
// Description: Functions for scoring segmentation paths according to
// their character widths, gap widths and seam cuts.
// Author: Daria Antonova
// Created: Mon Mar 8 11:26:43 PDT 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include <stdio.h>
#ifdef __UNIX__
#include <assert.h>
#endif
#include <math.h>
#include "associate.h"
#include "normalis.h"
#include "pageres.h"
namespace tesseract {
const float AssociateUtils::kMaxFixedPitchCharAspectRatio = 2.0f;
const float AssociateUtils::kMinGap = 0.03f;
void AssociateUtils::ComputeStats(int col, int row,
const AssociateStats *parent_stats,
int parent_path_length,
bool fixed_pitch,
float max_char_wh_ratio,
WERD_RES *word_res,
bool debug,
AssociateStats *stats) {
stats->Clear();
ASSERT_HOST(word_res != NULL);
if (word_res->blob_widths.empty()) {
return;
}
if (debug) {
tprintf("AssociateUtils::ComputeStats() for col=%d, row=%d%s\n",
col, row, fixed_pitch ? " (fixed pitch)" : "");
}
float normalizing_height = kBlnXHeight;
ROW* blob_row = word_res->blob_row;
// TODO(rays/daria) Can unicharset.script_has_xheight be useful here?
if (fixed_pitch && blob_row != NULL) {
// For fixed pitch language like CJK, we use the full text height
// as the normalizing factor so we are not dependent on xheight
// calculation.
if (blob_row->body_size() > 0.0f) {
normalizing_height = word_res->denorm.y_scale() * blob_row->body_size();
} else {
normalizing_height = word_res->denorm.y_scale() *
(blob_row->x_height() + blob_row->ascenders());
}
if (debug) {
tprintf("normalizing height = %g (scale %g xheight %g ascenders %g)\n",
normalizing_height, word_res->denorm.y_scale(),
blob_row->x_height(), blob_row->ascenders());
}
}
float wh_ratio = word_res->GetBlobsWidth(col, row) / normalizing_height;
if (wh_ratio > max_char_wh_ratio) stats->bad_shape = true;
// Compute the gap sum for this shape. If there are only negative or only
// positive gaps, record their sum in stats->gap_sum. However, if there is
// a mixture, record only the sum of the positive gaps.
// TODO(antonova): explain fragment.
int negative_gap_sum = 0;
for (int c = col; c < row; ++c) {
int gap = word_res->GetBlobsGap(c);
(gap > 0) ? stats->gap_sum += gap : negative_gap_sum += gap;
}
if (stats->gap_sum == 0) stats->gap_sum = negative_gap_sum;
if (debug) {
tprintf("wh_ratio=%g (max_char_wh_ratio=%g) gap_sum=%d %s\n",
wh_ratio, max_char_wh_ratio, stats->gap_sum,
stats->bad_shape ? "bad_shape" : "");
}
// Compute shape_cost (for fixed pitch mode).
if (fixed_pitch) {
bool end_row = (row == (word_res->ratings->dimension() - 1));
// Ensure that the blob has gaps on the left and the right sides
// (except for beginning and ending punctuation) and that there is
// no cutting through ink at the blob boundaries.
if (col > 0) {
float left_gap = word_res->GetBlobsGap(col - 1) / normalizing_height;
SEAM *left_seam = word_res->seam_array[col - 1];
if ((!end_row && left_gap < kMinGap) || left_seam->priority > 0.0f) {
stats->bad_shape = true;
}
if (debug) {
tprintf("left_gap %g, left_seam %g %s\n", left_gap, left_seam->priority,
stats->bad_shape ? "bad_shape" : "");
}
}
float right_gap = 0.0f;
if (!end_row) {
right_gap = word_res->GetBlobsGap(row) / normalizing_height;
SEAM *right_seam = word_res->seam_array[row];
if (right_gap < kMinGap || right_seam->priority > 0.0f) {
stats->bad_shape = true;
if (right_gap < kMinGap) stats->bad_fixed_pitch_right_gap = true;
}
if (debug) {
tprintf("right_gap %g right_seam %g %s\n",
right_gap, right_seam->priority,
stats->bad_shape ? "bad_shape" : "");
}
}
// Impose additional segmentation penalties if blob widths or gaps
// distribution don't fit a fixed-pitch model.
// Since we only know the widths and gaps of the path explored so far,
// the means and variances are computed for the path so far (not
// considering characters to the right of the last character on the path).
stats->full_wh_ratio = wh_ratio + right_gap;
if (parent_stats != NULL) {
stats->full_wh_ratio_total =
(parent_stats->full_wh_ratio_total + stats->full_wh_ratio);
float mean =
stats->full_wh_ratio_total / static_cast<float>(parent_path_length+1);
stats->full_wh_ratio_var =
parent_stats->full_wh_ratio_var + pow(mean-stats->full_wh_ratio, 2);
} else {
stats->full_wh_ratio_total = stats->full_wh_ratio;
}
if (debug) {
tprintf("full_wh_ratio %g full_wh_ratio_total %g full_wh_ratio_var %g\n",
stats->full_wh_ratio, stats->full_wh_ratio_total,
stats->full_wh_ratio_var);
}
stats->shape_cost =
FixedPitchWidthCost(wh_ratio, right_gap, end_row, max_char_wh_ratio);
// For some reason Tesseract prefers to treat the whole CJ words
// as one blob when the initial segmentation is particularly bad.
// This hack is to avoid favoring such states.
if (col == 0 && end_row && wh_ratio > max_char_wh_ratio) {
stats->shape_cost += 10;
}
stats->shape_cost += stats->full_wh_ratio_var;
if (debug) tprintf("shape_cost %g\n", stats->shape_cost);
}
}
float AssociateUtils::FixedPitchWidthCost(float norm_width,
float right_gap,
bool end_pos,
float max_char_wh_ratio) {
float cost = 0.0f;
if (norm_width > max_char_wh_ratio) cost += norm_width;
if (norm_width > kMaxFixedPitchCharAspectRatio)
cost += norm_width * norm_width; // extra penalty for merging CJK chars
// Penalize skinny blobs, except for punctuation in the last position.
if (norm_width+right_gap < 0.5f && !end_pos) {
cost += 1.0f - (norm_width + right_gap);
}
return cost;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: segsearch.h
// Description: Segmentation search functions.
// Author: Daria Antonova
// Created: Mon Jun 23 11:26:43 PDT 2008
//
// (C) Copyright 2009, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "wordrec.h"
#include "associate.h"
#include "language_model.h"
#include "matrix.h"
#include "params.h"
#include "lm_pain_points.h"
#include "ratngs.h"
namespace tesseract {
void Wordrec::DoSegSearch(WERD_RES* word_res) {
BestChoiceBundle best_choice_bundle(word_res->ratings->dimension());
// Run Segmentation Search.
SegSearch(word_res, &best_choice_bundle, NULL);
}
void Wordrec::SegSearch(WERD_RES* word_res,
BestChoiceBundle* best_choice_bundle,
BlamerBundle* blamer_bundle) {
LMPainPoints pain_points(segsearch_max_pain_points,
segsearch_max_char_wh_ratio,
assume_fixed_pitch_char_segment,
&getDict(), segsearch_debug_level);
// Compute scaling factor that will help us recover blob outline length
// from classifier rating and certainty for the blob.
float rating_cert_scale = -1.0 * getDict().certainty_scale / rating_scale;
GenericVector<SegSearchPending> pending;
InitialSegSearch(word_res, &pain_points, &pending, best_choice_bundle,
blamer_bundle);
if (!SegSearchDone(0)) { // find a better choice
if (chop_enable && word_res->chopped_word != NULL) {
improve_by_chopping(rating_cert_scale, word_res, best_choice_bundle,
blamer_bundle, &pain_points, &pending);
}
if (chop_debug)
print_seams("Final seam list:", word_res->seam_array);
if (blamer_bundle != NULL &&
!blamer_bundle->ChoiceIsCorrect(word_res->best_choice)) {
blamer_bundle->SetChopperBlame(word_res, wordrec_debug_blamer);
}
}
// Keep trying to find a better path by fixing the "pain points".
MATRIX_COORD pain_point;
float pain_point_priority;
int num_futile_classifications = 0;
STRING blamer_debug;
while (wordrec_enable_assoc &&
(!SegSearchDone(num_futile_classifications) ||
(blamer_bundle != NULL &&
blamer_bundle->GuidedSegsearchStillGoing()))) {
// Get the next valid "pain point".
bool found_nothing = true;
LMPainPointsType pp_type;
while ((pp_type = pain_points.Deque(&pain_point, &pain_point_priority)) !=
LM_PPTYPE_NUM) {
if (!pain_point.Valid(*word_res->ratings)) {
word_res->ratings->IncreaseBandSize(
pain_point.row - pain_point.col + 1);
}
if (pain_point.Valid(*word_res->ratings) &&
!word_res->ratings->Classified(pain_point.col, pain_point.row,
getDict().WildcardID())) {
found_nothing = false;
break;
}
}
if (found_nothing) {
if (segsearch_debug_level > 0) tprintf("Pain points queue is empty\n");
break;
}
ProcessSegSearchPainPoint(pain_point_priority, pain_point,
LMPainPoints::PainPointDescription(pp_type),
&pending, word_res, &pain_points, blamer_bundle);
UpdateSegSearchNodes(rating_cert_scale, pain_point.col, &pending,
word_res, &pain_points, best_choice_bundle,
blamer_bundle);
if (!best_choice_bundle->updated) ++num_futile_classifications;
if (segsearch_debug_level > 0) {
tprintf("num_futile_classifications %d\n", num_futile_classifications);
}
best_choice_bundle->updated = false; // reset updated
// See if it's time to terminate SegSearch or time for starting a guided
// search for the true path to find the blame for the incorrect best_choice.
if (SegSearchDone(num_futile_classifications) &&
blamer_bundle != NULL &&
blamer_bundle->GuidedSegsearchNeeded(word_res->best_choice)) {
InitBlamerForSegSearch(word_res, &pain_points, blamer_bundle,
&blamer_debug);
}
} // end while loop exploring alternative paths
if (blamer_bundle != NULL) {
blamer_bundle->FinishSegSearch(word_res->best_choice,
wordrec_debug_blamer, &blamer_debug);
}
if (segsearch_debug_level > 0) {
tprintf("Done with SegSearch (AcceptableChoiceFound: %d)\n",
language_model_->AcceptableChoiceFound());
}
}
// Setup and run just the initial segsearch on an established matrix,
// without doing any additional chopping or joining.
void Wordrec::WordSearch(WERD_RES* word_res) {
LMPainPoints pain_points(segsearch_max_pain_points,
segsearch_max_char_wh_ratio,
assume_fixed_pitch_char_segment,
&getDict(), segsearch_debug_level);
GenericVector<SegSearchPending> pending;
BestChoiceBundle best_choice_bundle(word_res->ratings->dimension());
// Run Segmentation Search.
InitialSegSearch(word_res, &pain_points, &pending, &best_choice_bundle, NULL);
if (segsearch_debug_level > 0) {
tprintf("Ending ratings matrix%s:\n",
wordrec_enable_assoc ? " (with assoc)" : "");
word_res->ratings->print(getDict().getUnicharset());
}
}
// Setup and run just the initial segsearch on an established matrix,
// without doing any additional chopping or joining.
// (Internal factored version that can be used as part of the main SegSearch.)
void Wordrec::InitialSegSearch(WERD_RES* word_res, LMPainPoints* pain_points,
GenericVector<SegSearchPending>* pending,
BestChoiceBundle* best_choice_bundle,
BlamerBundle* blamer_bundle) {
if (segsearch_debug_level > 0) {
tprintf("Starting SegSearch on ratings matrix%s:\n",
wordrec_enable_assoc ? " (with assoc)" : "");
word_res->ratings->print(getDict().getUnicharset());
}
pain_points->GenerateInitial(word_res);
// Compute scaling factor that will help us recover blob outline length
// from classifier rating and certainty for the blob.
float rating_cert_scale = -1.0 * getDict().certainty_scale / rating_scale;
language_model_->InitForWord(prev_word_best_choice_,
assume_fixed_pitch_char_segment,
segsearch_max_char_wh_ratio, rating_cert_scale);
// Initialize blamer-related information: map character boxes recorded in
// blamer_bundle->norm_truth_word to the corresponding i,j indices in the
// ratings matrix. We expect this step to succeed, since when running the
// chopper we checked that the correct chops are present.
if (blamer_bundle != NULL) {
blamer_bundle->SetupCorrectSegmentation(word_res->chopped_word,
wordrec_debug_blamer);
}
// pending[col] tells whether there is update work to do to combine
// best_choice_bundle->beam[col - 1] with some BLOB_CHOICEs in matrix[col, *].
// As the language model state is updated, pending entries are modified to
// minimize duplication of work. It is important that during the update the
// children are considered in the non-decreasing order of their column, since
// this guarantees that all the parents would be up to date before an update
// of a child is done.
pending->init_to_size(word_res->ratings->dimension(), SegSearchPending());
// Search the ratings matrix for the initial best path.
(*pending)[0].SetColumnClassified();
UpdateSegSearchNodes(rating_cert_scale, 0, pending, word_res,
pain_points, best_choice_bundle, blamer_bundle);
}
void Wordrec::UpdateSegSearchNodes(
float rating_cert_scale,
int starting_col,
GenericVector<SegSearchPending>* pending,
WERD_RES *word_res,
LMPainPoints *pain_points,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle) {
MATRIX *ratings = word_res->ratings;
ASSERT_HOST(ratings->dimension() == pending->size());
ASSERT_HOST(ratings->dimension() == best_choice_bundle->beam.size());
for (int col = starting_col; col < ratings->dimension(); ++col) {
if (!(*pending)[col].WorkToDo()) continue;
int first_row = col;
int last_row = MIN(ratings->dimension() - 1,
col + ratings->bandwidth() - 1);
if ((*pending)[col].SingleRow() >= 0) {
first_row = last_row = (*pending)[col].SingleRow();
}
if (segsearch_debug_level > 0) {
tprintf("\n\nUpdateSegSearchNodes: col=%d, rows=[%d,%d], alljust=%d\n",
col, first_row, last_row,
(*pending)[col].IsRowJustClassified(MAX_INT32));
}
// Iterate over the pending list for this column.
for (int row = first_row; row <= last_row; ++row) {
// Update language model state of this child+parent pair.
BLOB_CHOICE_LIST *current_node = ratings->get(col, row);
LanguageModelState *parent_node =
col == 0 ? NULL : best_choice_bundle->beam[col - 1];
if (current_node != NULL &&
language_model_->UpdateState((*pending)[col].IsRowJustClassified(row),
col, row, current_node, parent_node,
pain_points, word_res,
best_choice_bundle, blamer_bundle) &&
row + 1 < ratings->dimension()) {
// Since the language model state of this entry changed, process all
// the child column.
(*pending)[row + 1].RevisitWholeColumn();
if (segsearch_debug_level > 0) {
tprintf("Added child col=%d to pending\n", row + 1);
}
} // end if UpdateState.
} // end for row.
} // end for col.
if (best_choice_bundle->best_vse != NULL) {
ASSERT_HOST(word_res->StatesAllValid());
if (best_choice_bundle->best_vse->updated) {
pain_points->GenerateFromPath(rating_cert_scale,
best_choice_bundle->best_vse, word_res);
if (!best_choice_bundle->fixpt.empty()) {
pain_points->GenerateFromAmbigs(best_choice_bundle->fixpt,
best_choice_bundle->best_vse, word_res);
}
}
}
// The segsearch is completed. Reset all updated flags on all VSEs and reset
// all pendings.
for (int col = 0; col < pending->size(); ++col) {
(*pending)[col].Clear();
ViterbiStateEntry_IT
vse_it(&best_choice_bundle->beam[col]->viterbi_state_entries);
for (vse_it.mark_cycle_pt(); !vse_it.cycled_list(); vse_it.forward()) {
vse_it.data()->updated = false;
}
}
}
void Wordrec::ProcessSegSearchPainPoint(
float pain_point_priority,
const MATRIX_COORD &pain_point, const char* pain_point_type,
GenericVector<SegSearchPending>* pending, WERD_RES *word_res,
LMPainPoints *pain_points, BlamerBundle *blamer_bundle) {
if (segsearch_debug_level > 0) {
tprintf("Classifying pain point %s priority=%.4f, col=%d, row=%d\n",
pain_point_type, pain_point_priority,
pain_point.col, pain_point.row);
}
ASSERT_HOST(pain_points != NULL);
MATRIX *ratings = word_res->ratings;
// Classify blob [pain_point.col pain_point.row]
if (!pain_point.Valid(*ratings)) {
ratings->IncreaseBandSize(pain_point.row + 1 - pain_point.col);
}
ASSERT_HOST(pain_point.Valid(*ratings));
BLOB_CHOICE_LIST *classified = classify_piece(word_res->seam_array,
pain_point.col, pain_point.row,
pain_point_type,
word_res->chopped_word,
blamer_bundle);
BLOB_CHOICE_LIST *lst = ratings->get(pain_point.col, pain_point.row);
if (lst == NULL) {
ratings->put(pain_point.col, pain_point.row, classified);
} else {
// We can not delete old BLOB_CHOICEs, since they might contain
// ViterbiStateEntries that are parents of other "active" entries.
// Thus if the matrix cell already contains classifications we add
// the new ones to the beginning of the list.
BLOB_CHOICE_IT it(lst);
it.add_list_before(classified);
delete classified; // safe to delete, since empty after add_list_before()
classified = NULL;
}
if (segsearch_debug_level > 0) {
print_ratings_list("Updated ratings matrix with a new entry:",
ratings->get(pain_point.col, pain_point.row),
getDict().getUnicharset());
ratings->print(getDict().getUnicharset());
}
// Insert initial "pain points" to join the newly classified blob
// with its left and right neighbors.
if (classified != NULL && !classified->empty()) {
if (pain_point.col > 0) {
pain_points->GeneratePainPoint(
pain_point.col - 1, pain_point.row, LM_PPTYPE_SHAPE, 0.0,
true, segsearch_max_char_wh_ratio, word_res);
}
if (pain_point.row + 1 < ratings->dimension()) {
pain_points->GeneratePainPoint(
pain_point.col, pain_point.row + 1, LM_PPTYPE_SHAPE, 0.0,
true, segsearch_max_char_wh_ratio, word_res);
}
}
(*pending)[pain_point.col].SetBlobClassified(pain_point.row);
}
// Resets enough of the results so that the Viterbi search is re-run.
// Needed when the n-gram model is enabled, as the multi-length comparison
// implementation will re-value existing paths to worse values.
void Wordrec::ResetNGramSearch(WERD_RES* word_res,
BestChoiceBundle* best_choice_bundle,
GenericVector<SegSearchPending>* pending) {
// TODO(rays) More refactoring required here.
// Delete existing viterbi states.
for (int col = 0; col < best_choice_bundle->beam.size(); ++col) {
best_choice_bundle->beam[col]->Clear();
}
// Reset best_choice_bundle.
word_res->ClearWordChoices();
best_choice_bundle->best_vse = NULL;
// Clear out all existing pendings and add a new one for the first column.
(*pending)[0].SetColumnClassified();
for (int i = 1; i < pending->size(); ++i)
(*pending)[i].Clear();
}
void Wordrec::InitBlamerForSegSearch(WERD_RES *word_res,
LMPainPoints *pain_points,
BlamerBundle *blamer_bundle,
STRING *blamer_debug) {
pain_points->Clear(); // Clear pain points heap.
TessResultCallback2<bool, int, int>* pp_cb = NewPermanentTessCallback(
pain_points, &LMPainPoints::GenerateForBlamer,
static_cast<double>(segsearch_max_char_wh_ratio), word_res);
blamer_bundle->InitForSegSearch(word_res->best_choice, word_res->ratings,
getDict().WildcardID(), wordrec_debug_blamer,
blamer_debug, pp_cb);
delete pp_cb;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: language_model.cpp
// Description: Functions that utilize the knowledge about the properties,
// structure and statistics of the language to help recognition.
// Author: Daria Antonova
// Created: Mon Nov 11 11:26:43 PST 2009
//
// (C) Copyright 2009, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include <math.h>
#include "language_model.h"
#include "dawg.h"
#include "freelist.h"
#include "intproto.h"
#include "helpers.h"
#include "lm_state.h"
#include "lm_pain_points.h"
#include "matrix.h"
#include "params.h"
#include "params_training_featdef.h"
#if defined(_MSC_VER) || defined(ANDROID)
double log2(double n) {
return log(n) / log(2.0);
}
#endif // _MSC_VER
namespace tesseract {
const float LanguageModel::kMaxAvgNgramCost = 25.0f;
LanguageModel::LanguageModel(const UnicityTable<FontInfo> *fontinfo_table,
Dict *dict)
: INT_MEMBER(language_model_debug_level, 0, "Language model debug level",
dict->getCCUtil()->params()),
BOOL_INIT_MEMBER(language_model_ngram_on, false,
"Turn on/off the use of character ngram model",
dict->getCCUtil()->params()),
INT_MEMBER(language_model_ngram_order, 8,
"Maximum order of the character ngram model",
dict->getCCUtil()->params()),
INT_MEMBER(language_model_viterbi_list_max_num_prunable, 10,
"Maximum number of prunable (those for which"
" PrunablePath() is true) entries in each viterbi list"
" recorded in BLOB_CHOICEs",
dict->getCCUtil()->params()),
INT_MEMBER(language_model_viterbi_list_max_size, 500,
"Maximum size of viterbi lists recorded in BLOB_CHOICEs",
dict->getCCUtil()->params()),
double_MEMBER(language_model_ngram_small_prob, 0.000001,
"To avoid overly small denominators use this as the "
"floor of the probability returned by the ngram model.",
dict->getCCUtil()->params()),
double_MEMBER(language_model_ngram_nonmatch_score, -40.0,
"Average classifier score of a non-matching unichar.",
dict->getCCUtil()->params()),
BOOL_MEMBER(language_model_ngram_use_only_first_uft8_step, false,
"Use only the first UTF8 step of the given string"
" when computing log probabilities.",
dict->getCCUtil()->params()),
double_MEMBER(language_model_ngram_scale_factor, 0.03,
"Strength of the character ngram model relative to the"
" character classifier ",
dict->getCCUtil()->params()),
double_MEMBER(language_model_ngram_rating_factor, 16.0,
"Factor to bring log-probs into the same range as ratings"
" when multiplied by outline length ",
dict->getCCUtil()->params()),
BOOL_MEMBER(language_model_ngram_space_delimited_language, true,
"Words are delimited by space",
dict->getCCUtil()->params()),
INT_MEMBER(language_model_min_compound_length, 3,
"Minimum length of compound words",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_non_freq_dict_word, 0.1,
"Penalty for words not in the frequent word dictionary",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_non_dict_word, 0.15,
"Penalty for non-dictionary words",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_punc, 0.2,
"Penalty for inconsistent punctuation",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_case, 0.1,
"Penalty for inconsistent case",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_script, 0.5,
"Penalty for inconsistent script",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_chartype, 0.3,
"Penalty for inconsistent character type",
dict->getCCUtil()->params()),
// TODO(daria, rays): enable font consistency checking
// after improving font analysis.
double_MEMBER(language_model_penalty_font, 0.00,
"Penalty for inconsistent font",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_spacing, 0.05,
"Penalty for inconsistent spacing",
dict->getCCUtil()->params()),
double_MEMBER(language_model_penalty_increment, 0.01,
"Penalty increment",
dict->getCCUtil()->params()),
INT_MEMBER(wordrec_display_segmentations, 0, "Display Segmentations",
dict->getCCUtil()->params()),
BOOL_INIT_MEMBER(language_model_use_sigmoidal_certainty, false,
"Use sigmoidal score for certainty",
dict->getCCUtil()->params()),
fontinfo_table_(fontinfo_table), dict_(dict),
fixed_pitch_(false), max_char_wh_ratio_(0.0),
acceptable_choice_found_(false) {
ASSERT_HOST(dict_ != NULL);
dawg_args_ = new DawgArgs(NULL, new DawgPositionVector(), NO_PERM);
very_beginning_active_dawgs_ = new DawgPositionVector();
beginning_active_dawgs_ = new DawgPositionVector();
}
LanguageModel::~LanguageModel() {
delete very_beginning_active_dawgs_;
delete beginning_active_dawgs_;
delete dawg_args_->updated_dawgs;
delete dawg_args_;
}
void LanguageModel::InitForWord(const WERD_CHOICE *prev_word,
bool fixed_pitch, float max_char_wh_ratio,
float rating_cert_scale) {
fixed_pitch_ = fixed_pitch;
max_char_wh_ratio_ = max_char_wh_ratio;
rating_cert_scale_ = rating_cert_scale;
acceptable_choice_found_ = false;
correct_segmentation_explored_ = false;
// Initialize vectors with beginning DawgInfos.
very_beginning_active_dawgs_->clear();
dict_->init_active_dawgs(very_beginning_active_dawgs_, false);
beginning_active_dawgs_->clear();
dict_->default_dawgs(beginning_active_dawgs_, false);
// Fill prev_word_str_ with the last language_model_ngram_order
// unichars from prev_word.
if (language_model_ngram_on) {
if (prev_word != NULL && prev_word->unichar_string() != NULL) {
prev_word_str_ = prev_word->unichar_string();
if (language_model_ngram_space_delimited_language) prev_word_str_ += ' ';
} else {
prev_word_str_ = " ";
}
const char *str_ptr = prev_word_str_.string();
const char *str_end = str_ptr + prev_word_str_.length();
int step;
prev_word_unichar_step_len_ = 0;
while (str_ptr != str_end && (step = UNICHAR::utf8_step(str_ptr))) {
str_ptr += step;
++prev_word_unichar_step_len_;
}
ASSERT_HOST(str_ptr == str_end);
}
}
// Helper scans the collection of predecessors for competing siblings that
// have the same letter with the opposite case, setting competing_vse.
static void ScanParentsForCaseMix(const UNICHARSET& unicharset,
LanguageModelState* parent_node) {
if (parent_node == NULL) return;
ViterbiStateEntry_IT vit(&parent_node->viterbi_state_entries);
for (vit.mark_cycle_pt(); !vit.cycled_list(); vit.forward()) {
ViterbiStateEntry* vse = vit.data();
vse->competing_vse = NULL;
UNICHAR_ID unichar_id = vse->curr_b->unichar_id();
if (unicharset.get_isupper(unichar_id) ||
unicharset.get_islower(unichar_id)) {
UNICHAR_ID other_case = unicharset.get_other_case(unichar_id);
if (other_case == unichar_id) continue; // Not in unicharset.
// Find other case in same list. There could be multiple entries with
// the same unichar_id, but in theory, they should all point to the
// same BLOB_CHOICE, and that is what we will be using to decide
// which to keep.
ViterbiStateEntry_IT vit2(&parent_node->viterbi_state_entries);
for (vit2.mark_cycle_pt(); !vit2.cycled_list() &&
vit2.data()->curr_b->unichar_id() != other_case;
vit2.forward()) {}
if (!vit2.cycled_list()) {
vse->competing_vse = vit2.data();
}
}
}
}
// Helper returns true if the given choice has a better case variant before
// it in the choice_list that is not distinguishable by size.
static bool HasBetterCaseVariant(const UNICHARSET& unicharset,
const BLOB_CHOICE* choice,
BLOB_CHOICE_LIST* choices) {
UNICHAR_ID choice_id = choice->unichar_id();
UNICHAR_ID other_case = unicharset.get_other_case(choice_id);
if (other_case == choice_id || other_case == INVALID_UNICHAR_ID)
return false; // Not upper or lower or not in unicharset.
if (unicharset.SizesDistinct(choice_id, other_case))
return false; // Can be separated by size.
BLOB_CHOICE_IT bc_it(choices);
for (bc_it.mark_cycle_pt(); !bc_it.cycled_list(); bc_it.forward()) {
BLOB_CHOICE* better_choice = bc_it.data();
if (better_choice->unichar_id() == other_case)
return true; // Found an earlier instance of other_case.
else if (better_choice == choice)
return false; // Reached the original choice.
}
return false; // Should never happen, but just in case.
}
// UpdateState has the job of combining the ViterbiStateEntry lists on each
// of the choices on parent_list with each of the blob choices in curr_list,
// making a new ViterbiStateEntry for each sensible path.
// This could be a huge set of combinations, creating a lot of work only to
// be truncated by some beam limit, but only certain kinds of paths will
// continue at the next step:
// paths that are liked by the language model: either a DAWG or the n-gram
// model, where active.
// paths that represent some kind of top choice. The old permuter permuted
// the top raw classifier score, the top upper case word and the top lower-
// case word. UpdateState now concentrates its top-choice paths on top
// lower-case, top upper-case (or caseless alpha), and top digit sequence,
// with allowance for continuation of these paths through blobs where such
// a character does not appear in the choices list.
// GetNextParentVSE enforces some of these models to minimize the number of
// calls to AddViterbiStateEntry, even prior to looking at the language model.
// Thus an n-blob sequence of [l1I] will produce 3n calls to
// AddViterbiStateEntry instead of 3^n.
// Of course it isn't quite that simple as Title Case is handled by allowing
// lower case to continue an upper case initial, but it has to be detected
// in the combiner so it knows which upper case letters are initial alphas.
bool LanguageModel::UpdateState(
bool just_classified,
int curr_col, int curr_row,
BLOB_CHOICE_LIST *curr_list,
LanguageModelState *parent_node,
LMPainPoints *pain_points,
WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle) {
if (language_model_debug_level > 0) {
tprintf("\nUpdateState: col=%d row=%d %s",
curr_col, curr_row, just_classified ? "just_classified" : "");
if (language_model_debug_level > 5)
tprintf("(parent=%p)\n", parent_node);
else
tprintf("\n");
}
// Initialize helper variables.
bool word_end = (curr_row+1 >= word_res->ratings->dimension());
bool new_changed = false;
float denom = (language_model_ngram_on) ? ComputeDenom(curr_list) : 1.0f;
const UNICHARSET& unicharset = dict_->getUnicharset();
BLOB_CHOICE *first_lower = NULL;
BLOB_CHOICE *first_upper = NULL;
BLOB_CHOICE *first_digit = NULL;
bool has_alnum_mix = false;
if (parent_node != NULL) {
int result = SetTopParentLowerUpperDigit(parent_node);
if (result < 0) {
if (language_model_debug_level > 0)
tprintf("No parents found to process\n");
return false;
}
if (result > 0)
has_alnum_mix = true;
}
if (!GetTopLowerUpperDigit(curr_list, &first_lower, &first_upper,
&first_digit))
has_alnum_mix = false;;
ScanParentsForCaseMix(unicharset, parent_node);
if (language_model_debug_level > 3 && parent_node != NULL) {
parent_node->Print("Parent viterbi list");
}
LanguageModelState *curr_state = best_choice_bundle->beam[curr_row];
// Call AddViterbiStateEntry() for each parent+child ViterbiStateEntry.
ViterbiStateEntry_IT vit;
BLOB_CHOICE_IT c_it(curr_list);
for (c_it.mark_cycle_pt(); !c_it.cycled_list(); c_it.forward()) {
BLOB_CHOICE* choice = c_it.data();
// TODO(antonova): make sure commenting this out if ok for ngram
// model scoring (I think this was introduced to fix ngram model quirks).
// Skip NULL unichars unless it is the only choice.
//if (!curr_list->singleton() && c_it.data()->unichar_id() == 0) continue;
UNICHAR_ID unichar_id = choice->unichar_id();
if (unicharset.get_fragment(unichar_id)) {
continue; // Skip fragments.
}
// Set top choice flags.
LanguageModelFlagsType blob_choice_flags = kXhtConsistentFlag;
if (c_it.at_first() || !new_changed)
blob_choice_flags |= kSmallestRatingFlag;
if (first_lower == choice) blob_choice_flags |= kLowerCaseFlag;
if (first_upper == choice) blob_choice_flags |= kUpperCaseFlag;
if (first_digit == choice) blob_choice_flags |= kDigitFlag;
if (parent_node == NULL) {
// Process the beginning of a word.
// If there is a better case variant that is not distinguished by size,
// skip this blob choice, as we have no choice but to accept the result
// of the character classifier to distinguish between them, even if
// followed by an upper case.
// With words like iPoc, and other CamelBackWords, the lower-upper
// transition can only be achieved if the classifier has the correct case
// as the top choice, and leaving an initial I lower down the list
// increases the chances of choosing IPoc simply because it doesn't
// include such a transition. iPoc will beat iPOC and ipoc because
// the other words are baseline/x-height inconsistent.
if (HasBetterCaseVariant(unicharset, choice, curr_list))
continue;
// Upper counts as lower at the beginning of a word.
if (blob_choice_flags & kUpperCaseFlag)
blob_choice_flags |= kLowerCaseFlag;
new_changed |= AddViterbiStateEntry(
blob_choice_flags, denom, word_end, curr_col, curr_row,
choice, curr_state, NULL, pain_points,
word_res, best_choice_bundle, blamer_bundle);
} else {
// Get viterbi entries from each parent ViterbiStateEntry.
vit.set_to_list(&parent_node->viterbi_state_entries);
int vit_counter = 0;
vit.mark_cycle_pt();
ViterbiStateEntry* parent_vse = NULL;
LanguageModelFlagsType top_choice_flags;
while ((parent_vse = GetNextParentVSE(just_classified, has_alnum_mix,
c_it.data(), blob_choice_flags,
unicharset, word_res, &vit,
&top_choice_flags)) != NULL) {
// Skip pruned entries and do not look at prunable entries if already
// examined language_model_viterbi_list_max_num_prunable of those.
if (PrunablePath(*parent_vse) &&
(++vit_counter > language_model_viterbi_list_max_num_prunable ||
(language_model_ngram_on && parent_vse->ngram_info->pruned))) {
continue;
}
// If the parent has no alnum choice, (ie choice is the first in a
// string of alnum), and there is a better case variant that is not
// distinguished by size, skip this blob choice/parent, as with the
// initial blob treatment above.
if (!parent_vse->HasAlnumChoice(unicharset) &&
HasBetterCaseVariant(unicharset, choice, curr_list))
continue;
// Create a new ViterbiStateEntry if BLOB_CHOICE in c_it.data()
// looks good according to the Dawgs or character ngram model.
new_changed |= AddViterbiStateEntry(
top_choice_flags, denom, word_end, curr_col, curr_row,
c_it.data(), curr_state, parent_vse, pain_points,
word_res, best_choice_bundle, blamer_bundle);
}
}
}
return new_changed;
}
// Finds the first lower and upper case letter and first digit in curr_list.
// For non-upper/lower languages, alpha counts as upper.
// Uses the first character in the list in place of empty results.
// Returns true if both alpha and digits are found.
bool LanguageModel::GetTopLowerUpperDigit(BLOB_CHOICE_LIST *curr_list,
BLOB_CHOICE **first_lower,
BLOB_CHOICE **first_upper,
BLOB_CHOICE **first_digit) const {
BLOB_CHOICE_IT c_it(curr_list);
const UNICHARSET &unicharset = dict_->getUnicharset();
BLOB_CHOICE *first_unichar = NULL;
for (c_it.mark_cycle_pt(); !c_it.cycled_list(); c_it.forward()) {
UNICHAR_ID unichar_id = c_it.data()->unichar_id();
if (unicharset.get_fragment(unichar_id)) continue; // skip fragments
if (first_unichar == NULL) first_unichar = c_it.data();
if (*first_lower == NULL && unicharset.get_islower(unichar_id)) {
*first_lower = c_it.data();
}
if (*first_upper == NULL && unicharset.get_isalpha(unichar_id) &&
!unicharset.get_islower(unichar_id)) {
*first_upper = c_it.data();
}
if (*first_digit == NULL && unicharset.get_isdigit(unichar_id)) {
*first_digit = c_it.data();
}
}
ASSERT_HOST(first_unichar != NULL);
bool mixed = (*first_lower != NULL || *first_upper != NULL) &&
*first_digit != NULL;
if (*first_lower == NULL) *first_lower = first_unichar;
if (*first_upper == NULL) *first_upper = first_unichar;
if (*first_digit == NULL) *first_digit = first_unichar;
return mixed;
}
// Forces there to be at least one entry in the overall set of the
// viterbi_state_entries of each element of parent_node that has the
// top_choice_flag set for lower, upper and digit using the same rules as
// GetTopLowerUpperDigit, setting the flag on the first found suitable
// candidate, whether or not the flag is set on some other parent.
// Returns 1 if both alpha and digits are found among the parents, -1 if no
// parents are found at all (a legitimate case), and 0 otherwise.
int LanguageModel::SetTopParentLowerUpperDigit(
LanguageModelState *parent_node) const {
if (parent_node == NULL) return -1;
UNICHAR_ID top_id = INVALID_UNICHAR_ID;
ViterbiStateEntry* top_lower = NULL;
ViterbiStateEntry* top_upper = NULL;
ViterbiStateEntry* top_digit = NULL;
ViterbiStateEntry* top_choice = NULL;
float lower_rating = 0.0f;
float upper_rating = 0.0f;
float digit_rating = 0.0f;
float top_rating = 0.0f;
const UNICHARSET &unicharset = dict_->getUnicharset();
ViterbiStateEntry_IT vit(&parent_node->viterbi_state_entries);
for (vit.mark_cycle_pt(); !vit.cycled_list(); vit.forward()) {
ViterbiStateEntry* vse = vit.data();
// INVALID_UNICHAR_ID should be treated like a zero-width joiner, so scan
// back to the real character if needed.
ViterbiStateEntry* unichar_vse = vse;
UNICHAR_ID unichar_id = unichar_vse->curr_b->unichar_id();
float rating = unichar_vse->curr_b->rating();
while (unichar_id == INVALID_UNICHAR_ID &&
unichar_vse->parent_vse != NULL) {
unichar_vse = unichar_vse->parent_vse;
unichar_id = unichar_vse->curr_b->unichar_id();
rating = unichar_vse->curr_b->rating();
}
if (unichar_id != INVALID_UNICHAR_ID) {
if (unicharset.get_islower(unichar_id)) {
if (top_lower == NULL || lower_rating > rating) {
top_lower = vse;
lower_rating = rating;
}
} else if (unicharset.get_isalpha(unichar_id)) {
if (top_upper == NULL || upper_rating > rating) {
top_upper = vse;
upper_rating = rating;
}
} else if (unicharset.get_isdigit(unichar_id)) {
if (top_digit == NULL || digit_rating > rating) {
top_digit = vse;
digit_rating = rating;
}
}
}
if (top_choice == NULL || top_rating > rating) {
top_choice = vse;
top_rating = rating;
top_id = unichar_id;
}
}
if (top_choice == NULL) return -1;
bool mixed = (top_lower != NULL || top_upper != NULL) &&
top_digit != NULL;
if (top_lower == NULL) top_lower = top_choice;
top_lower->top_choice_flags |= kLowerCaseFlag;
if (top_upper == NULL) top_upper = top_choice;
top_upper->top_choice_flags |= kUpperCaseFlag;
if (top_digit == NULL) top_digit = top_choice;
top_digit->top_choice_flags |= kDigitFlag;
top_choice->top_choice_flags |= kSmallestRatingFlag;
if (top_id != INVALID_UNICHAR_ID && dict_->compound_marker(top_id) &&
(top_choice->top_choice_flags &
(kLowerCaseFlag | kUpperCaseFlag | kDigitFlag))) {
// If the compound marker top choice carries any of the top alnum flags,
// then give it all of them, allowing words like I-295 to be chosen.
top_choice->top_choice_flags |=
kLowerCaseFlag | kUpperCaseFlag | kDigitFlag;
}
return mixed ? 1 : 0;
}
// Finds the next ViterbiStateEntry with which the given unichar_id can
// combine sensibly, taking into account any mixed alnum/mixed case
// situation, and whether this combination has been inspected before.
ViterbiStateEntry* LanguageModel::GetNextParentVSE(
bool just_classified, bool mixed_alnum, const BLOB_CHOICE* bc,
LanguageModelFlagsType blob_choice_flags, const UNICHARSET& unicharset,
WERD_RES* word_res, ViterbiStateEntry_IT* vse_it,
LanguageModelFlagsType* top_choice_flags) const {
for (; !vse_it->cycled_list(); vse_it->forward()) {
ViterbiStateEntry* parent_vse = vse_it->data();
// Only consider the parent if it has been updated or
// if the current ratings cell has just been classified.
if (!just_classified && !parent_vse->updated) continue;
if (language_model_debug_level > 2)
parent_vse->Print("Considering");
// If the parent is non-alnum, then upper counts as lower.
*top_choice_flags = blob_choice_flags;
if ((blob_choice_flags & kUpperCaseFlag) &&
!parent_vse->HasAlnumChoice(unicharset)) {
*top_choice_flags |= kLowerCaseFlag;
}
*top_choice_flags &= parent_vse->top_choice_flags;
UNICHAR_ID unichar_id = bc->unichar_id();
const BLOB_CHOICE* parent_b = parent_vse->curr_b;
UNICHAR_ID parent_id = parent_b->unichar_id();
// Digits do not bind to alphas if there is a mix in both parent and current
// or if the alpha is not the top choice.
if (unicharset.get_isdigit(unichar_id) &&
unicharset.get_isalpha(parent_id) &&
(mixed_alnum || *top_choice_flags == 0))
continue; // Digits don't bind to alphas.
// Likewise alphas do not bind to digits if there is a mix in both or if
// the digit is not the top choice.
if (unicharset.get_isalpha(unichar_id) &&
unicharset.get_isdigit(parent_id) &&
(mixed_alnum || *top_choice_flags == 0))
continue; // Alphas don't bind to digits.
// If there is a case mix of the same alpha in the parent list, then
// competing_vse is non-null and will be used to determine whether
// or not to bind the current blob choice.
if (parent_vse->competing_vse != NULL) {
const BLOB_CHOICE* competing_b = parent_vse->competing_vse->curr_b;
UNICHAR_ID other_id = competing_b->unichar_id();
if (language_model_debug_level >= 5) {
tprintf("Parent %s has competition %s\n",
unicharset.id_to_unichar(parent_id),
unicharset.id_to_unichar(other_id));
}
if (unicharset.SizesDistinct(parent_id, other_id)) {
// If other_id matches bc wrt position and size, and parent_id, doesn't,
// don't bind to the current parent.
if (bc->PosAndSizeAgree(*competing_b, word_res->x_height,
language_model_debug_level >= 5) &&
!bc->PosAndSizeAgree(*parent_b, word_res->x_height,
language_model_debug_level >= 5))
continue; // Competing blobchoice has a better vertical match.
}
}
vse_it->forward();
return parent_vse; // This one is good!
}
return NULL; // Ran out of possibilities.
}
bool LanguageModel::AddViterbiStateEntry(
LanguageModelFlagsType top_choice_flags,
float denom,
bool word_end,
int curr_col, int curr_row,
BLOB_CHOICE *b,
LanguageModelState *curr_state,
ViterbiStateEntry *parent_vse,
LMPainPoints *pain_points,
WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle) {
ViterbiStateEntry_IT vit;
if (language_model_debug_level > 1) {
tprintf("AddViterbiStateEntry for unichar %s rating=%.4f"
" certainty=%.4f top_choice_flags=0x%x",
dict_->getUnicharset().id_to_unichar(b->unichar_id()),
b->rating(), b->certainty(), top_choice_flags);
if (language_model_debug_level > 5)
tprintf(" parent_vse=%p\n", parent_vse);
else
tprintf("\n");
}
// Check whether the list is full.
if (curr_state != NULL &&
curr_state->viterbi_state_entries_length >=
language_model_viterbi_list_max_size) {
if (language_model_debug_level > 1) {
tprintf("AddViterbiStateEntry: viterbi list is full!\n");
}
return false;
}
// Invoke Dawg language model component.
LanguageModelDawgInfo *dawg_info =
GenerateDawgInfo(word_end, curr_col, curr_row, *b, parent_vse);
float outline_length =
AssociateUtils::ComputeOutlineLength(rating_cert_scale_, *b);
// Invoke Ngram language model component.
LanguageModelNgramInfo *ngram_info = NULL;
if (language_model_ngram_on) {
ngram_info = GenerateNgramInfo(
dict_->getUnicharset().id_to_unichar(b->unichar_id()), b->certainty(),
denom, curr_col, curr_row, outline_length, parent_vse);
ASSERT_HOST(ngram_info != NULL);
}
bool liked_by_language_model = dawg_info != NULL ||
(ngram_info != NULL && !ngram_info->pruned);
// Quick escape if not liked by the language model, can't be consistent
// xheight, and not top choice.
if (!liked_by_language_model && top_choice_flags == 0) {
if (language_model_debug_level > 1) {
tprintf("Language model components very early pruned this entry\n");
}
delete ngram_info;
delete dawg_info;
return false;
}
// Check consistency of the path and set the relevant consistency_info.
LMConsistencyInfo consistency_info(
parent_vse != NULL ? &parent_vse->consistency_info : NULL);
// Start with just the x-height consistency, as it provides significant
// pruning opportunity.
consistency_info.ComputeXheightConsistency(
b, dict_->getUnicharset().get_ispunctuation(b->unichar_id()));
// Turn off xheight consistent flag if not consistent.
if (consistency_info.InconsistentXHeight()) {
top_choice_flags &= ~kXhtConsistentFlag;
}
// Quick escape if not liked by the language model, not consistent xheight,
// and not top choice.
if (!liked_by_language_model && top_choice_flags == 0) {
if (language_model_debug_level > 1) {
tprintf("Language model components early pruned this entry\n");
}
delete ngram_info;
delete dawg_info;
return false;
}
// Compute the rest of the consistency info.
FillConsistencyInfo(curr_col, word_end, b, parent_vse,
word_res, &consistency_info);
if (dawg_info != NULL && consistency_info.invalid_punc) {
consistency_info.invalid_punc = false; // do not penalize dict words
}
// Compute cost of associating the blobs that represent the current unichar.
AssociateStats associate_stats;
ComputeAssociateStats(curr_col, curr_row, max_char_wh_ratio_,
parent_vse, word_res, &associate_stats);
if (parent_vse != NULL) {
associate_stats.shape_cost += parent_vse->associate_stats.shape_cost;
associate_stats.bad_shape |= parent_vse->associate_stats.bad_shape;
}
// Create the new ViterbiStateEntry compute the adjusted cost of the path.
ViterbiStateEntry *new_vse = new ViterbiStateEntry(
parent_vse, b, 0.0, outline_length,
consistency_info, associate_stats, top_choice_flags, dawg_info,
ngram_info, (language_model_debug_level > 0) ?
dict_->getUnicharset().id_to_unichar(b->unichar_id()) : NULL);
new_vse->cost = ComputeAdjustedPathCost(new_vse);
if (language_model_debug_level >= 3)
tprintf("Adjusted cost = %g\n", new_vse->cost);
// Invoke Top Choice language model component to make the final adjustments
// to new_vse->top_choice_flags.
if (!curr_state->viterbi_state_entries.empty() && new_vse->top_choice_flags) {
GenerateTopChoiceInfo(new_vse, parent_vse, curr_state);
}
// If language model components did not like this unichar - return.
bool keep = new_vse->top_choice_flags || liked_by_language_model;
if (!(top_choice_flags & kSmallestRatingFlag) && // no non-top choice paths
consistency_info.inconsistent_script) { // with inconsistent script
keep = false;
}
if (!keep) {
if (language_model_debug_level > 1) {
tprintf("Language model components did not like this entry\n");
}
delete new_vse;
return false;
}
// Discard this entry if it represents a prunable path and
// language_model_viterbi_list_max_num_prunable such entries with a lower
// cost have already been recorded.
if (PrunablePath(*new_vse) &&
(curr_state->viterbi_state_entries_prunable_length >=
language_model_viterbi_list_max_num_prunable) &&
new_vse->cost >= curr_state->viterbi_state_entries_prunable_max_cost) {
if (language_model_debug_level > 1) {
tprintf("Discarded ViterbiEntry with high cost %g max cost %g\n",
new_vse->cost,
curr_state->viterbi_state_entries_prunable_max_cost);
}
delete new_vse;
return false;
}
// Update best choice if needed.
if (word_end) {
UpdateBestChoice(new_vse, pain_points, word_res,
best_choice_bundle, blamer_bundle);
// Discard the entry if UpdateBestChoice() found flaws in it.
if (new_vse->cost >= WERD_CHOICE::kBadRating &&
new_vse != best_choice_bundle->best_vse) {
if (language_model_debug_level > 1) {
tprintf("Discarded ViterbiEntry with high cost %g\n", new_vse->cost);
}
delete new_vse;
return false;
}
}
// Add the new ViterbiStateEntry and to curr_state->viterbi_state_entries.
curr_state->viterbi_state_entries.add_sorted(ViterbiStateEntry::Compare,
false, new_vse);
curr_state->viterbi_state_entries_length++;
if (PrunablePath(*new_vse)) {
curr_state->viterbi_state_entries_prunable_length++;
}
// Update lms->viterbi_state_entries_prunable_max_cost and clear
// top_choice_flags of entries with ratings_sum than new_vse->ratings_sum.
if ((curr_state->viterbi_state_entries_prunable_length >=
language_model_viterbi_list_max_num_prunable) ||
new_vse->top_choice_flags) {
ASSERT_HOST(!curr_state->viterbi_state_entries.empty());
int prunable_counter = language_model_viterbi_list_max_num_prunable;
vit.set_to_list(&(curr_state->viterbi_state_entries));
for (vit.mark_cycle_pt(); !vit.cycled_list(); vit.forward()) {
ViterbiStateEntry *curr_vse = vit.data();
// Clear the appropriate top choice flags of the entries in the
// list that have cost higher thank new_entry->cost
// (since they will not be top choices any more).
if (curr_vse->top_choice_flags && curr_vse != new_vse &&
curr_vse->cost > new_vse->cost) {
curr_vse->top_choice_flags &= ~(new_vse->top_choice_flags);
}
if (prunable_counter > 0 && PrunablePath(*curr_vse)) --prunable_counter;
// Update curr_state->viterbi_state_entries_prunable_max_cost.
if (prunable_counter == 0) {
curr_state->viterbi_state_entries_prunable_max_cost = vit.data()->cost;
if (language_model_debug_level > 1) {
tprintf("Set viterbi_state_entries_prunable_max_cost to %g\n",
curr_state->viterbi_state_entries_prunable_max_cost);
}
prunable_counter = -1; // stop counting
}
}
}
// Print the newly created ViterbiStateEntry.
if (language_model_debug_level > 2) {
new_vse->Print("New");
if (language_model_debug_level > 5)
curr_state->Print("Updated viterbi list");
}
return true;
}
void LanguageModel::GenerateTopChoiceInfo(ViterbiStateEntry *new_vse,
const ViterbiStateEntry *parent_vse,
LanguageModelState *lms) {
ViterbiStateEntry_IT vit(&(lms->viterbi_state_entries));
for (vit.mark_cycle_pt(); !vit.cycled_list() && new_vse->top_choice_flags &&
new_vse->cost >= vit.data()->cost; vit.forward()) {
// Clear the appropriate flags if the list already contains
// a top choice entry with a lower cost.
new_vse->top_choice_flags &= ~(vit.data()->top_choice_flags);
}
if (language_model_debug_level > 2) {
tprintf("GenerateTopChoiceInfo: top_choice_flags=0x%x\n",
new_vse->top_choice_flags);
}
}
LanguageModelDawgInfo *LanguageModel::GenerateDawgInfo(
bool word_end,
int curr_col, int curr_row,
const BLOB_CHOICE &b,
const ViterbiStateEntry *parent_vse) {
// Initialize active_dawgs from parent_vse if it is not NULL.
// Otherwise use very_beginning_active_dawgs_.
if (parent_vse == NULL) {
dawg_args_->active_dawgs = very_beginning_active_dawgs_;
dawg_args_->permuter = NO_PERM;
} else {
if (parent_vse->dawg_info == NULL) return NULL; // not a dict word path
dawg_args_->active_dawgs = parent_vse->dawg_info->active_dawgs;
dawg_args_->permuter = parent_vse->dawg_info->permuter;
}
// Deal with hyphenated words.
if (word_end && dict_->has_hyphen_end(b.unichar_id(), curr_col == 0)) {
if (language_model_debug_level > 0) tprintf("Hyphenated word found\n");
return new LanguageModelDawgInfo(dawg_args_->active_dawgs,
COMPOUND_PERM);
}
// Deal with compound words.
if (dict_->compound_marker(b.unichar_id()) &&
(parent_vse == NULL || parent_vse->dawg_info->permuter != NUMBER_PERM)) {
if (language_model_debug_level > 0) tprintf("Found compound marker\n");
// Do not allow compound operators at the beginning and end of the word.
// Do not allow more than one compound operator per word.
// Do not allow compounding of words with lengths shorter than
// language_model_min_compound_length
if (parent_vse == NULL || word_end ||
dawg_args_->permuter == COMPOUND_PERM ||
parent_vse->length < language_model_min_compound_length) return NULL;
int i;
// Check a that the path terminated before the current character is a word.
bool has_word_ending = false;
for (i = 0; i < parent_vse->dawg_info->active_dawgs->size(); ++i) {
const DawgPosition &pos = (*parent_vse->dawg_info->active_dawgs)[i];
const Dawg *pdawg = pos.dawg_index < 0
? NULL : dict_->GetDawg(pos.dawg_index);
if (pdawg == NULL || pos.back_to_punc) continue;;
if (pdawg->type() == DAWG_TYPE_WORD && pos.dawg_ref != NO_EDGE &&
pdawg->end_of_word(pos.dawg_ref)) {
has_word_ending = true;
break;
}
}
if (!has_word_ending) return NULL;
if (language_model_debug_level > 0) tprintf("Compound word found\n");
return new LanguageModelDawgInfo(beginning_active_dawgs_, COMPOUND_PERM);
} // done dealing with compound words
LanguageModelDawgInfo *dawg_info = NULL;
// Call LetterIsOkay().
// Use the normalized IDs so that all shapes of ' can be allowed in words
// like don't.
const GenericVector<UNICHAR_ID>& normed_ids =
dict_->getUnicharset().normed_ids(b.unichar_id());
DawgPositionVector tmp_active_dawgs;
for (int i = 0; i < normed_ids.size(); ++i) {
if (language_model_debug_level > 2)
tprintf("Test Letter OK for unichar %d, normed %d\n",
b.unichar_id(), normed_ids[i]);
dict_->LetterIsOkay(dawg_args_, normed_ids[i],
word_end && i == normed_ids.size() - 1);
if (dawg_args_->permuter == NO_PERM) {
break;
} else if (i < normed_ids.size() - 1) {
tmp_active_dawgs = *dawg_args_->updated_dawgs;
dawg_args_->active_dawgs = &tmp_active_dawgs;
}
if (language_model_debug_level > 2)
tprintf("Letter was OK for unichar %d, normed %d\n",
b.unichar_id(), normed_ids[i]);
}
dawg_args_->active_dawgs = NULL;
if (dawg_args_->permuter != NO_PERM) {
dawg_info = new LanguageModelDawgInfo(dawg_args_->updated_dawgs,
dawg_args_->permuter);
} else if (language_model_debug_level > 3) {
tprintf("Letter %s not OK!\n",
dict_->getUnicharset().id_to_unichar(b.unichar_id()));
}
return dawg_info;
}
LanguageModelNgramInfo *LanguageModel::GenerateNgramInfo(
const char *unichar, float certainty, float denom,
int curr_col, int curr_row, float outline_length,
const ViterbiStateEntry *parent_vse) {
// Initialize parent context.
const char *pcontext_ptr = "";
int pcontext_unichar_step_len = 0;
if (parent_vse == NULL) {
pcontext_ptr = prev_word_str_.string();
pcontext_unichar_step_len = prev_word_unichar_step_len_;
} else {
pcontext_ptr = parent_vse->ngram_info->context.string();
pcontext_unichar_step_len =
parent_vse->ngram_info->context_unichar_step_len;
}
// Compute p(unichar | parent context).
int unichar_step_len = 0;
bool pruned = false;
float ngram_cost;
float ngram_and_classifier_cost =
ComputeNgramCost(unichar, certainty, denom,
pcontext_ptr, &unichar_step_len,
&pruned, &ngram_cost);
// Normalize just the ngram_and_classifier_cost by outline_length.
// The ngram_cost is used by the params_model, so it needs to be left as-is,
// and the params model cost will be normalized by outline_length.
ngram_and_classifier_cost *=
outline_length / language_model_ngram_rating_factor;
// Add the ngram_cost of the parent.
if (parent_vse != NULL) {
ngram_and_classifier_cost +=
parent_vse->ngram_info->ngram_and_classifier_cost;
ngram_cost += parent_vse->ngram_info->ngram_cost;
}
// Shorten parent context string by unichar_step_len unichars.
int num_remove = (unichar_step_len + pcontext_unichar_step_len -
language_model_ngram_order);
if (num_remove > 0) pcontext_unichar_step_len -= num_remove;
while (num_remove > 0 && *pcontext_ptr != '\0') {
pcontext_ptr += UNICHAR::utf8_step(pcontext_ptr);
--num_remove;
}
// Decide whether to prune this ngram path and update changed accordingly.
if (parent_vse != NULL && parent_vse->ngram_info->pruned) pruned = true;
// Construct and return the new LanguageModelNgramInfo.
LanguageModelNgramInfo *ngram_info = new LanguageModelNgramInfo(
pcontext_ptr, pcontext_unichar_step_len, pruned, ngram_cost,
ngram_and_classifier_cost);
ngram_info->context += unichar;
ngram_info->context_unichar_step_len += unichar_step_len;
assert(ngram_info->context_unichar_step_len <= language_model_ngram_order);
return ngram_info;
}
float LanguageModel::ComputeNgramCost(const char *unichar,
float certainty,
float denom,
const char *context,
int *unichar_step_len,
bool *found_small_prob,
float *ngram_cost) {
const char *context_ptr = context;
char *modified_context = NULL;
char *modified_context_end = NULL;
const char *unichar_ptr = unichar;
const char *unichar_end = unichar_ptr + strlen(unichar_ptr);
float prob = 0.0f;
int step = 0;
while (unichar_ptr < unichar_end &&
(step = UNICHAR::utf8_step(unichar_ptr)) > 0) {
if (language_model_debug_level > 1) {
tprintf("prob(%s | %s)=%g\n", unichar_ptr, context_ptr,
dict_->ProbabilityInContext(context_ptr, -1, unichar_ptr, step));
}
prob += dict_->ProbabilityInContext(context_ptr, -1, unichar_ptr, step);
++(*unichar_step_len);
if (language_model_ngram_use_only_first_uft8_step) break;
unichar_ptr += step;
// If there are multiple UTF8 characters present in unichar, context is
// updated to include the previously examined characters from str,
// unless use_only_first_uft8_step is true.
if (unichar_ptr < unichar_end) {
if (modified_context == NULL) {
int context_len = strlen(context);
modified_context =
new char[context_len + strlen(unichar_ptr) + step + 1];
strncpy(modified_context, context, context_len);
modified_context_end = modified_context + context_len;
context_ptr = modified_context;
}
strncpy(modified_context_end, unichar_ptr - step, step);
modified_context_end += step;
*modified_context_end = '\0';
}
}
prob /= static_cast<float>(*unichar_step_len); // normalize
if (prob < language_model_ngram_small_prob) {
if (language_model_debug_level > 0) tprintf("Found small prob %g\n", prob);
*found_small_prob = true;
prob = language_model_ngram_small_prob;
}
*ngram_cost = -1.0*log2(prob);
float ngram_and_classifier_cost =
-1.0*log2(CertaintyScore(certainty)/denom) +
*ngram_cost * language_model_ngram_scale_factor;
if (language_model_debug_level > 1) {
tprintf("-log [ p(%s) * p(%s | %s) ] = -log2(%g*%g) = %g\n", unichar,
unichar, context_ptr, CertaintyScore(certainty)/denom, prob,
ngram_and_classifier_cost);
}
if (modified_context != NULL) delete[] modified_context;
return ngram_and_classifier_cost;
}
float LanguageModel::ComputeDenom(BLOB_CHOICE_LIST *curr_list) {
if (curr_list->empty()) return 1.0f;
float denom = 0.0f;
int len = 0;
BLOB_CHOICE_IT c_it(curr_list);
for (c_it.mark_cycle_pt(); !c_it.cycled_list(); c_it.forward()) {
ASSERT_HOST(c_it.data() != NULL);
++len;
denom += CertaintyScore(c_it.data()->certainty());
}
assert(len != 0);
// The ideal situation would be to have the classifier scores for
// classifying each position as each of the characters in the unicharset.
// Since we can not do this because of speed, we add a very crude estimate
// of what these scores for the "missing" classifications would sum up to.
denom += (dict_->getUnicharset().size() - len) *
CertaintyScore(language_model_ngram_nonmatch_score);
return denom;
}
void LanguageModel::FillConsistencyInfo(
int curr_col,
bool word_end,
BLOB_CHOICE *b,
ViterbiStateEntry *parent_vse,
WERD_RES *word_res,
LMConsistencyInfo *consistency_info) {
const UNICHARSET &unicharset = dict_->getUnicharset();
UNICHAR_ID unichar_id = b->unichar_id();
BLOB_CHOICE* parent_b = parent_vse != NULL ? parent_vse->curr_b : NULL;
// Check punctuation validity.
if (unicharset.get_ispunctuation(unichar_id)) consistency_info->num_punc++;
if (dict_->GetPuncDawg() != NULL && !consistency_info->invalid_punc) {
if (dict_->compound_marker(unichar_id) && parent_b != NULL &&
(unicharset.get_isalpha(parent_b->unichar_id()) ||
unicharset.get_isdigit(parent_b->unichar_id()))) {
// reset punc_ref for compound words
consistency_info->punc_ref = NO_EDGE;
} else {
bool is_apos = dict_->is_apostrophe(unichar_id);
bool prev_is_numalpha = (parent_b != NULL &&
(unicharset.get_isalpha(parent_b->unichar_id()) ||
unicharset.get_isdigit(parent_b->unichar_id())));
UNICHAR_ID pattern_unichar_id =
(unicharset.get_isalpha(unichar_id) ||
unicharset.get_isdigit(unichar_id) ||
(is_apos && prev_is_numalpha)) ?
Dawg::kPatternUnicharID : unichar_id;
if (consistency_info->punc_ref == NO_EDGE ||
pattern_unichar_id != Dawg::kPatternUnicharID ||
dict_->GetPuncDawg()->edge_letter(consistency_info->punc_ref) !=
Dawg::kPatternUnicharID) {
NODE_REF node = Dict::GetStartingNode(dict_->GetPuncDawg(),
consistency_info->punc_ref);
consistency_info->punc_ref =
(node != NO_EDGE) ? dict_->GetPuncDawg()->edge_char_of(
node, pattern_unichar_id, word_end) : NO_EDGE;
if (consistency_info->punc_ref == NO_EDGE) {
consistency_info->invalid_punc = true;
}
}
}
}
// Update case related counters.
if (parent_vse != NULL && !word_end && dict_->compound_marker(unichar_id)) {
// Reset counters if we are dealing with a compound word.
consistency_info->num_lower = 0;
consistency_info->num_non_first_upper = 0;
}
else if (unicharset.get_islower(unichar_id)) {
consistency_info->num_lower++;
} else if ((parent_b != NULL) && unicharset.get_isupper(unichar_id)) {
if (unicharset.get_isupper(parent_b->unichar_id()) ||
consistency_info->num_lower > 0 ||
consistency_info->num_non_first_upper > 0) {
consistency_info->num_non_first_upper++;
}
}
// Initialize consistency_info->script_id (use script of unichar_id
// if it is not Common, use script id recorded by the parent otherwise).
// Set inconsistent_script to true if the script of the current unichar
// is not consistent with that of the parent.
consistency_info->script_id = unicharset.get_script(unichar_id);
// Hiragana and Katakana can mix with Han.
if (dict_->getUnicharset().han_sid() != dict_->getUnicharset().null_sid()) {
if ((unicharset.hiragana_sid() != unicharset.null_sid() &&
consistency_info->script_id == unicharset.hiragana_sid()) ||
(unicharset.katakana_sid() != unicharset.null_sid() &&
consistency_info->script_id == unicharset.katakana_sid())) {
consistency_info->script_id = dict_->getUnicharset().han_sid();
}
}
if (parent_vse != NULL &&
(parent_vse->consistency_info.script_id !=
dict_->getUnicharset().common_sid())) {
int parent_script_id = parent_vse->consistency_info.script_id;
// If script_id is Common, use script id of the parent instead.
if (consistency_info->script_id == dict_->getUnicharset().common_sid()) {
consistency_info->script_id = parent_script_id;
}
if (consistency_info->script_id != parent_script_id) {
consistency_info->inconsistent_script = true;
}
}
// Update chartype related counters.
if (unicharset.get_isalpha(unichar_id)) {
consistency_info->num_alphas++;
} else if (unicharset.get_isdigit(unichar_id)) {
consistency_info->num_digits++;
} else if (!unicharset.get_ispunctuation(unichar_id)) {
consistency_info->num_other++;
}
// Check font and spacing consistency.
if (fontinfo_table_->size() > 0 && parent_b != NULL) {
int fontinfo_id = -1;
if (parent_b->fontinfo_id() == b->fontinfo_id() ||
parent_b->fontinfo_id2() == b->fontinfo_id()) {
fontinfo_id = b->fontinfo_id();
} else if (parent_b->fontinfo_id() == b->fontinfo_id2() ||
parent_b->fontinfo_id2() == b->fontinfo_id2()) {
fontinfo_id = b->fontinfo_id2();
}
if(language_model_debug_level > 1) {
tprintf("pfont %s pfont %s font %s font2 %s common %s(%d)\n",
(parent_b->fontinfo_id() >= 0) ?
fontinfo_table_->get(parent_b->fontinfo_id()).name : "" ,
(parent_b->fontinfo_id2() >= 0) ?
fontinfo_table_->get(parent_b->fontinfo_id2()).name : "",
(b->fontinfo_id() >= 0) ?
fontinfo_table_->get(b->fontinfo_id()).name : "",
(fontinfo_id >= 0) ? fontinfo_table_->get(fontinfo_id).name : "",
(fontinfo_id >= 0) ? fontinfo_table_->get(fontinfo_id).name : "",
fontinfo_id);
}
if (!word_res->blob_widths.empty()) { // if we have widths/gaps info
bool expected_gap_found = false;
float expected_gap;
int temp_gap;
if (fontinfo_id >= 0) { // found a common font
ASSERT_HOST(fontinfo_id < fontinfo_table_->size());
if (fontinfo_table_->get(fontinfo_id).get_spacing(
parent_b->unichar_id(), unichar_id, &temp_gap)) {
expected_gap = temp_gap;
expected_gap_found = true;
}
} else {
consistency_info->inconsistent_font = true;
// Get an average of the expected gaps in each font
int num_addends = 0;
expected_gap = 0;
int temp_fid;
for (int i = 0; i < 4; ++i) {
if (i == 0) {
temp_fid = parent_b->fontinfo_id();
} else if (i == 1) {
temp_fid = parent_b->fontinfo_id2();
} else if (i == 2) {
temp_fid = b->fontinfo_id();
} else {
temp_fid = b->fontinfo_id2();
}
ASSERT_HOST(temp_fid < 0 || fontinfo_table_->size());
if (temp_fid >= 0 && fontinfo_table_->get(temp_fid).get_spacing(
parent_b->unichar_id(), unichar_id, &temp_gap)) {
expected_gap += temp_gap;
num_addends++;
}
}
expected_gap_found = (num_addends > 0);
if (num_addends > 0) {
expected_gap /= static_cast<float>(num_addends);
}
}
if (expected_gap_found) {
float actual_gap =
static_cast<float>(word_res->GetBlobsGap(curr_col-1));
float gap_ratio = expected_gap / actual_gap;
// TODO(rays) The gaps seem to be way off most of the time, saved by
// the error here that the ratio was compared to 1/2, when it should
// have been 0.5f. Find the source of the gaps discrepancy and put
// the 0.5f here in place of 0.0f.
// Test on 2476595.sj, pages 0 to 6. (In French.)
if (gap_ratio < 0.0f || gap_ratio > 2.0f) {
consistency_info->num_inconsistent_spaces++;
}
if (language_model_debug_level > 1) {
tprintf("spacing for %s(%d) %s(%d) col %d: expected %g actual %g\n",
unicharset.id_to_unichar(parent_b->unichar_id()),
parent_b->unichar_id(), unicharset.id_to_unichar(unichar_id),
unichar_id, curr_col, expected_gap, actual_gap);
}
}
}
}
}
float LanguageModel::ComputeAdjustedPathCost(ViterbiStateEntry *vse) {
ASSERT_HOST(vse != NULL);
if (params_model_.Initialized()) {
float features[PTRAIN_NUM_FEATURE_TYPES];
ExtractFeaturesFromPath(*vse, features);
float cost = params_model_.ComputeCost(features);
if (language_model_debug_level > 3) {
tprintf("ComputeAdjustedPathCost %g ParamsModel features:\n", cost);
if (language_model_debug_level >= 5) {
for (int f = 0; f < PTRAIN_NUM_FEATURE_TYPES; ++f) {
tprintf("%s=%g\n", kParamsTrainingFeatureTypeName[f], features[f]);
}
}
}
return cost * vse->outline_length;
} else {
float adjustment = 1.0f;
if (vse->dawg_info == NULL || vse->dawg_info->permuter != FREQ_DAWG_PERM) {
adjustment += language_model_penalty_non_freq_dict_word;
}
if (vse->dawg_info == NULL) {
adjustment += language_model_penalty_non_dict_word;
if (vse->length > language_model_min_compound_length) {
adjustment += ((vse->length - language_model_min_compound_length) *
language_model_penalty_increment);
}
}
if (vse->associate_stats.shape_cost > 0) {
adjustment += vse->associate_stats.shape_cost /
static_cast<float>(vse->length);
}
if (language_model_ngram_on) {
ASSERT_HOST(vse->ngram_info != NULL);
return vse->ngram_info->ngram_and_classifier_cost * adjustment;
} else {
adjustment += ComputeConsistencyAdjustment(vse->dawg_info,
vse->consistency_info);
return vse->ratings_sum * adjustment;
}
}
}
void LanguageModel::UpdateBestChoice(
ViterbiStateEntry *vse,
LMPainPoints *pain_points,
WERD_RES *word_res,
BestChoiceBundle *best_choice_bundle,
BlamerBundle *blamer_bundle) {
bool truth_path;
WERD_CHOICE *word = ConstructWord(vse, word_res, &best_choice_bundle->fixpt,
blamer_bundle, &truth_path);
ASSERT_HOST(word != NULL);
if (dict_->stopper_debug_level >= 1) {
STRING word_str;
word->string_and_lengths(&word_str, NULL);
vse->Print(word_str.string());
}
if (language_model_debug_level > 0) {
word->print("UpdateBestChoice() constructed word");
}
// Record features from the current path if necessary.
ParamsTrainingHypothesis curr_hyp;
if (blamer_bundle != NULL) {
if (vse->dawg_info != NULL) vse->dawg_info->permuter =
static_cast<PermuterType>(word->permuter());
ExtractFeaturesFromPath(*vse, curr_hyp.features);
word->string_and_lengths(&(curr_hyp.str), NULL);
curr_hyp.cost = vse->cost; // record cost for error rate computations
if (language_model_debug_level > 0) {
tprintf("Raw features extracted from %s (cost=%g) [ ",
curr_hyp.str.string(), curr_hyp.cost);
for (int deb_i = 0; deb_i < PTRAIN_NUM_FEATURE_TYPES; ++deb_i) {
tprintf("%g ", curr_hyp.features[deb_i]);
}
tprintf("]\n");
}
// Record the current hypothesis in params_training_bundle.
blamer_bundle->AddHypothesis(curr_hyp);
if (truth_path)
blamer_bundle->UpdateBestRating(word->rating());
}
if (blamer_bundle != NULL && blamer_bundle->GuidedSegsearchStillGoing()) {
// The word was constructed solely for blamer_bundle->AddHypothesis, so
// we no longer need it.
delete word;
return;
}
if (word_res->chopped_word != NULL && !word_res->chopped_word->blobs.empty())
word->SetScriptPositions(false, word_res->chopped_word);
// Update and log new raw_choice if needed.
if (word_res->raw_choice == NULL ||
word->rating() < word_res->raw_choice->rating()) {
if (word_res->LogNewRawChoice(word) && language_model_debug_level > 0)
tprintf("Updated raw choice\n");
}
// Set the modified rating for best choice to vse->cost and log best choice.
word->set_rating(vse->cost);
// Call LogNewChoice() for best choice from Dict::adjust_word() since it
// computes adjust_factor that is used by the adaption code (e.g. by
// ClassifyAdaptableWord() to compute adaption acceptance thresholds).
// Note: the rating of the word is not adjusted.
dict_->adjust_word(word, vse->dawg_info == NULL,
vse->consistency_info.xht_decision, 0.0,
false, language_model_debug_level > 0);
// Hand ownership of the word over to the word_res.
if (!word_res->LogNewCookedChoice(dict_->tessedit_truncate_wordchoice_log,
dict_->stopper_debug_level >= 1, word)) {
// The word was so bad that it was deleted.
return;
}
if (word_res->best_choice == word) {
// Word was the new best.
if (dict_->AcceptableChoice(*word, vse->consistency_info.xht_decision) &&
AcceptablePath(*vse)) {
acceptable_choice_found_ = true;
}
// Update best_choice_bundle.
best_choice_bundle->updated = true;
best_choice_bundle->best_vse = vse;
if (language_model_debug_level > 0) {
tprintf("Updated best choice\n");
word->print_state("New state ");
}
// Update hyphen state if we are dealing with a dictionary word.
if (vse->dawg_info != NULL) {
if (dict_->has_hyphen_end(*word)) {
dict_->set_hyphen_word(*word, *(dawg_args_->active_dawgs));
} else {
dict_->reset_hyphen_vars(true);
}
}
if (blamer_bundle != NULL) {
blamer_bundle->set_best_choice_is_dict_and_top_choice(
vse->dawg_info != NULL && vse->top_choice_flags);
}
}
if (wordrec_display_segmentations && word_res->chopped_word != NULL) {
word->DisplaySegmentation(word_res->chopped_word);
}
}
void LanguageModel::ExtractFeaturesFromPath(
const ViterbiStateEntry &vse, float features[]) {
memset(features, 0, sizeof(float) * PTRAIN_NUM_FEATURE_TYPES);
// Record dictionary match info.
int len = vse.length <= kMaxSmallWordUnichars ? 0 :
vse.length <= kMaxMediumWordUnichars ? 1 : 2;
if (vse.dawg_info != NULL) {
int permuter = vse.dawg_info->permuter;
if (permuter == NUMBER_PERM || permuter == USER_PATTERN_PERM) {
if (vse.consistency_info.num_digits == vse.length) {
features[PTRAIN_DIGITS_SHORT+len] = 1.0;
} else {
features[PTRAIN_NUM_SHORT+len] = 1.0;
}
} else if (permuter == DOC_DAWG_PERM) {
features[PTRAIN_DOC_SHORT+len] = 1.0;
} else if (permuter == SYSTEM_DAWG_PERM || permuter == USER_DAWG_PERM ||
permuter == COMPOUND_PERM) {
features[PTRAIN_DICT_SHORT+len] = 1.0;
} else if (permuter == FREQ_DAWG_PERM) {
features[PTRAIN_FREQ_SHORT+len] = 1.0;
}
}
// Record shape cost feature (normalized by path length).
features[PTRAIN_SHAPE_COST_PER_CHAR] =
vse.associate_stats.shape_cost / static_cast<float>(vse.length);
// Record ngram cost. (normalized by the path length).
features[PTRAIN_NGRAM_COST_PER_CHAR] = 0.0;
if (vse.ngram_info != NULL) {
features[PTRAIN_NGRAM_COST_PER_CHAR] =
vse.ngram_info->ngram_cost / static_cast<float>(vse.length);
}
// Record consistency-related features.
// Disabled this feature for due to its poor performance.
// features[PTRAIN_NUM_BAD_PUNC] = vse.consistency_info.NumInconsistentPunc();
features[PTRAIN_NUM_BAD_CASE] = vse.consistency_info.NumInconsistentCase();
features[PTRAIN_XHEIGHT_CONSISTENCY] = vse.consistency_info.xht_decision;
features[PTRAIN_NUM_BAD_CHAR_TYPE] = vse.dawg_info == NULL ?
vse.consistency_info.NumInconsistentChartype() : 0.0;
features[PTRAIN_NUM_BAD_SPACING] =
vse.consistency_info.NumInconsistentSpaces();
// Disabled this feature for now due to its poor performance.
// features[PTRAIN_NUM_BAD_FONT] = vse.consistency_info.inconsistent_font;
// Classifier-related features.
features[PTRAIN_RATING_PER_CHAR] =
vse.ratings_sum / static_cast<float>(vse.outline_length);
}
WERD_CHOICE *LanguageModel::ConstructWord(
ViterbiStateEntry *vse,
WERD_RES *word_res,
DANGERR *fixpt,
BlamerBundle *blamer_bundle,
bool *truth_path) {
if (truth_path != NULL) {
*truth_path =
(blamer_bundle != NULL &&
vse->length == blamer_bundle->correct_segmentation_length());
}
BLOB_CHOICE *curr_b = vse->curr_b;
ViterbiStateEntry *curr_vse = vse;
int i;
bool compound = dict_->hyphenated(); // treat hyphenated words as compound
// Re-compute the variance of the width-to-height ratios (since we now
// can compute the mean over the whole word).
float full_wh_ratio_mean = 0.0f;
if (vse->associate_stats.full_wh_ratio_var != 0.0f) {
vse->associate_stats.shape_cost -= vse->associate_stats.full_wh_ratio_var;
full_wh_ratio_mean = (vse->associate_stats.full_wh_ratio_total /
static_cast<float>(vse->length));
vse->associate_stats.full_wh_ratio_var = 0.0f;
}
// Construct a WERD_CHOICE by tracing parent pointers.
WERD_CHOICE *word = new WERD_CHOICE(word_res->uch_set, vse->length);
word->set_length(vse->length);
int total_blobs = 0;
for (i = (vse->length-1); i >= 0; --i) {
if (blamer_bundle != NULL && truth_path != NULL && *truth_path &&
!blamer_bundle->MatrixPositionCorrect(i, curr_b->matrix_cell())) {
*truth_path = false;
}
// The number of blobs used for this choice is row - col + 1.
int num_blobs = curr_b->matrix_cell().row - curr_b->matrix_cell().col + 1;
total_blobs += num_blobs;
word->set_blob_choice(i, num_blobs, curr_b);
// Update the width-to-height ratio variance. Useful non-space delimited
// languages to ensure that the blobs are of uniform width.
// Skip leading and trailing punctuation when computing the variance.
if ((full_wh_ratio_mean != 0.0f &&
((curr_vse != vse && curr_vse->parent_vse != NULL) ||
!dict_->getUnicharset().get_ispunctuation(curr_b->unichar_id())))) {
vse->associate_stats.full_wh_ratio_var +=
pow(full_wh_ratio_mean - curr_vse->associate_stats.full_wh_ratio, 2);
if (language_model_debug_level > 2) {
tprintf("full_wh_ratio_var += (%g-%g)^2\n",
full_wh_ratio_mean, curr_vse->associate_stats.full_wh_ratio);
}
}
// Mark the word as compound if compound permuter was set for any of
// the unichars on the path (usually this will happen for unichars
// that are compounding operators, like "-" and "/").
if (!compound && curr_vse->dawg_info &&
curr_vse->dawg_info->permuter == COMPOUND_PERM) compound = true;
// Update curr_* pointers.
curr_vse = curr_vse->parent_vse;
if (curr_vse == NULL) break;
curr_b = curr_vse->curr_b;
}
ASSERT_HOST(i == 0); // check that we recorded all the unichar ids.
ASSERT_HOST(total_blobs == word_res->ratings->dimension());
// Re-adjust shape cost to include the updated width-to-height variance.
if (full_wh_ratio_mean != 0.0f) {
vse->associate_stats.shape_cost += vse->associate_stats.full_wh_ratio_var;
}
word->set_rating(vse->ratings_sum);
word->set_certainty(vse->min_certainty);
word->set_x_heights(vse->consistency_info.BodyMinXHeight(),
vse->consistency_info.BodyMaxXHeight());
if (vse->dawg_info != NULL) {
word->set_permuter(compound ? COMPOUND_PERM : vse->dawg_info->permuter);
} else if (language_model_ngram_on && !vse->ngram_info->pruned) {
word->set_permuter(NGRAM_PERM);
} else if (vse->top_choice_flags) {
word->set_permuter(TOP_CHOICE_PERM);
} else {
word->set_permuter(NO_PERM);
}
word->set_dangerous_ambig_found_(!dict_->NoDangerousAmbig(word, fixpt, true,
word_res->ratings));
return word;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: params_model.cpp
// Description: Trained language model parameters.
// Author: David Eger
// Created: Mon Jun 11 11:26:42 PDT 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "params_model.h"
#include <ctype.h>
#include <math.h>
#include <stdio.h>
#include "bitvector.h"
#include "tprintf.h"
namespace tesseract {
// Scale factor to apply to params model scores.
static const float kScoreScaleFactor = 100.0f;
// Minimum cost result to return.
static const float kMinFinalCost = 0.001f;
// Maximum cost result to return.
static const float kMaxFinalCost = 100.0f;
void ParamsModel::Print() {
for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
tprintf("ParamsModel for pass %d lang %s\n", p, lang_.string());
for (int i = 0; i < weights_vec_[p].size(); ++i) {
tprintf("%s = %g\n", kParamsTrainingFeatureTypeName[i],
weights_vec_[p][i]);
}
}
}
void ParamsModel::Copy(const ParamsModel &other_model) {
for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
weights_vec_[p] = other_model.weights_for_pass(
static_cast<PassEnum>(p));
}
}
// Given a (modifiable) line, parse out a key / value pair.
// Return true on success.
bool ParamsModel::ParseLine(char *line, char** key, float *val) {
if (line[0] == '#')
return false;
int end_of_key = 0;
while (line[end_of_key] && !isspace(line[end_of_key])) end_of_key++;
if (!line[end_of_key]) {
tprintf("ParamsModel::Incomplete line %s\n", line);
return false;
}
line[end_of_key++] = 0;
*key = line;
if (sscanf(line + end_of_key, " %f", val) != 1)
return false;
return true;
}
// Applies params model weights to the given features.
// Assumes that features is an array of size PTRAIN_NUM_FEATURE_TYPES.
// The cost is set to a number that can be multiplied by the outline length,
// as with the old ratings scheme. This enables words of different length
// and combinations of words to be compared meaningfully.
float ParamsModel::ComputeCost(const float features[]) const {
float unnorm_score = 0.0;
for (int f = 0; f < PTRAIN_NUM_FEATURE_TYPES; ++f) {
unnorm_score += weights_vec_[pass_][f] * features[f];
}
return ClipToRange(-unnorm_score / kScoreScaleFactor,
kMinFinalCost, kMaxFinalCost);
}
bool ParamsModel::Equivalent(const ParamsModel &that) const {
float epsilon = 0.0001;
for (int p = 0; p < PTRAIN_NUM_PASSES; ++p) {
if (weights_vec_[p].size() != that.weights_vec_[p].size()) return false;
for (int i = 0; i < weights_vec_[p].size(); i++) {
if (weights_vec_[p][i] != that.weights_vec_[p][i] &&
fabs(weights_vec_[p][i] - that.weights_vec_[p][i]) > epsilon)
return false;
}
}
return true;
}
bool ParamsModel::LoadFromFile(
const char *lang,
const char *full_path) {
FILE *fp = fopen(full_path, "rb");
if (!fp) {
tprintf("Error opening file %s\n", full_path);
return false;
}
bool result = LoadFromFp(lang, fp, -1);
fclose(fp);
return result;
}
bool ParamsModel::LoadFromFp(const char *lang, FILE *fp, inT64 end_offset) {
const int kMaxLineSize = 100;
char line[kMaxLineSize];
BitVector present;
present.Init(PTRAIN_NUM_FEATURE_TYPES);
lang_ = lang;
// Load weights for passes with adaption on.
GenericVector<float> &weights = weights_vec_[pass_];
weights.init_to_size(PTRAIN_NUM_FEATURE_TYPES, 0.0);
while ((end_offset < 0 || ftell(fp) < end_offset) &&
fgets(line, kMaxLineSize, fp)) {
char *key = NULL;
float value;
if (!ParseLine(line, &key, &value))
continue;
int idx = ParamsTrainingFeatureByName(key);
if (idx < 0) {
tprintf("ParamsModel::Unknown parameter %s\n", key);
continue;
}
if (!present[idx]) {
present.SetValue(idx, true);
}
weights[idx] = value;
}
bool complete = (present.NumSetBits() == PTRAIN_NUM_FEATURE_TYPES);
if (!complete) {
for (int i = 0; i < PTRAIN_NUM_FEATURE_TYPES; i++) {
if (!present[i]) {
tprintf("Missing field %s.\n", kParamsTrainingFeatureTypeName[i]);
}
}
lang_ = "";
weights.truncate(0);
}
return complete;
}
bool ParamsModel::SaveToFile(const char *full_path) const {
const GenericVector<float> &weights = weights_vec_[pass_];
if (weights.size() != PTRAIN_NUM_FEATURE_TYPES) {
tprintf("Refusing to save ParamsModel that has not been initialized.\n");
return false;
}
FILE *fp = fopen(full_path, "wb");
if (!fp) {
tprintf("Could not open %s for writing.\n", full_path);
return false;
}
bool all_good = true;
for (int i = 0; i < weights.size(); i++) {
if (fprintf(fp, "%s %f\n", kParamsTrainingFeatureTypeName[i], weights[i])
< 0) {
all_good = false;
}
}
fclose(fp);
return all_good;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: lm_state.cpp
// Description: Structures and functionality for capturing the state of
// segmentation search guided by the language model.
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "lm_state.h"
namespace tesseract {
ELISTIZE(ViterbiStateEntry);
void ViterbiStateEntry::Print(const char *msg) const {
tprintf("%s ViterbiStateEntry", msg);
if (updated) tprintf("(NEW)");
if (this->debug_str != NULL) {
tprintf(" str=%s", this->debug_str->string());
}
tprintf(" with ratings_sum=%.4f length=%d cost=%.6f",
this->ratings_sum, this->length, this->cost);
if (this->top_choice_flags) {
tprintf(" top_choice_flags=0x%x", this->top_choice_flags);
}
if (!this->Consistent()) {
tprintf(" inconsistent=(punc %d case %d chartype %d script %d font %d)",
this->consistency_info.NumInconsistentPunc(),
this->consistency_info.NumInconsistentCase(),
this->consistency_info.NumInconsistentChartype(),
this->consistency_info.inconsistent_script,
this->consistency_info.inconsistent_font);
}
if (this->dawg_info) tprintf(" permuter=%d", this->dawg_info->permuter);
if (this->ngram_info) {
tprintf(" ngram_cl_cost=%g context=%s ngram pruned=%d",
this->ngram_info->ngram_and_classifier_cost,
this->ngram_info->context.string(),
this->ngram_info->pruned);
}
if (this->associate_stats.shape_cost > 0.0f) {
tprintf(" shape_cost=%g", this->associate_stats.shape_cost);
}
tprintf(" %s",
XHeightConsistencyEnumName[this->consistency_info.xht_decision]);
tprintf("\n");
}
// Clears the viterbi search state back to its initial conditions.
void LanguageModelState::Clear() {
viterbi_state_entries.clear();
viterbi_state_entries_prunable_length = 0;
viterbi_state_entries_prunable_max_cost = MAX_FLOAT32;
viterbi_state_entries_length = 0;
}
void LanguageModelState::Print(const char *msg) {
tprintf("%s VSEs (max_cost=%g prn_len=%d tot_len=%d):\n",
msg, viterbi_state_entries_prunable_max_cost,
viterbi_state_entries_prunable_length, viterbi_state_entries_length);
ViterbiStateEntry_IT vit(&viterbi_state_entries);
for (vit.mark_cycle_pt(); !vit.cycled_list(); vit.forward()) {
vit.data()->Print("");
}
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: lm_pain_points.h
// Description: Functions that utilize the knowledge about the properties
// of the paths explored by the segmentation search in order
// to generate "pain points" - the locations in the ratings
// matrix which should be classified next.
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_WORDREC_PAIN_POINTS_H_
#define TESSERACT_WORDREC_PAIN_POINTS_H_
#include "associate.h"
#include "dict.h"
#include "genericheap.h"
#include "lm_state.h"
namespace tesseract {
// Heap of pain points used for determining where to chop/join.
typedef GenericHeap<MatrixCoordPair> PainPointHeap;
// Types of pain points (ordered in the decreasing level of importance).
enum LMPainPointsType {
LM_PPTYPE_BLAMER,
LM_PPTYPE_AMBIG,
LM_PPTYPE_PATH,
LM_PPTYPE_SHAPE,
LM_PPTYPE_NUM
};
static const char * const LMPainPointsTypeName[] = {
"LM_PPTYPE_BLAMER",
"LM_PPTYPE_AMBIGS",
"LM_PPTYPE_PATH",
"LM_PPTYPE_SHAPE",
};
class LMPainPoints {
public:
static const float kDefaultPainPointPriorityAdjustment;
// If there is a significant drop in character ngram probability or a
// dangerous ambiguity make the thresholds on what blob combinations
// can be classified looser.
static const float kLooseMaxCharWhRatio;
// Returns a description of the type of a pain point.
static const char* PainPointDescription(LMPainPointsType type) {
return LMPainPointsTypeName[type];
}
LMPainPoints(int max, float rat, bool fp, const Dict *d, int deb) :
max_heap_size_(max), max_char_wh_ratio_(rat), fixed_pitch_(fp),
dict_(d), debug_level_(deb) {}
~LMPainPoints() {}
// Returns true if the heap of pain points of pp_type is not empty().
inline bool HasPainPoints(LMPainPointsType pp_type) const {
return !pain_points_heaps_[pp_type].empty();
}
// Dequeues the next pain point from the pain points queue and copies
// its contents and priority to *pp and *priority.
// Returns LM_PPTYPE_NUM if pain points queue is empty, otherwise the type.
LMPainPointsType Deque(MATRIX_COORD *pp, float *priority);
// Clears pain points heap.
void Clear() {
for (int h = 0; h < LM_PPTYPE_NUM; ++h) pain_points_heaps_[h].clear();
}
// For each cell, generate a "pain point" if the cell is not classified
// and has a left or right neighbor that was classified.
void GenerateInitial(WERD_RES *word_res);
// Generate pain points from the given path.
void GenerateFromPath(float rating_cert_scale, ViterbiStateEntry *vse,
WERD_RES *word_res);
// Generate pain points from dangerous ambiguities in best choice.
void GenerateFromAmbigs(const DANGERR &fixpt, ViterbiStateEntry *vse,
WERD_RES *word_res);
// Generate a pain point for the blamer.
bool GenerateForBlamer(double max_char_wh_ratio, WERD_RES *word_res,
int col, int row) {
return GeneratePainPoint(col, row, LM_PPTYPE_BLAMER, 0.0, false,
max_char_wh_ratio, word_res);
}
// Adds a pain point to classify chunks_record->ratings(col, row).
// Returns true if a new pain point was added to an appropriate heap.
// Pain point priority is set to special_priority for pain points of
// LM_PPTYPE_AMBIG or LM_PPTYPE_PATH, for other pain points
// AssociateStats::gap_sum is used.
bool GeneratePainPoint(int col, int row, LMPainPointsType pp_type,
float special_priority, bool ok_to_extend,
float max_char_wh_ratio,
WERD_RES *word_res);
// Adjusts the pain point coordinates to cope with expansion of the ratings
// matrix due to a split of the blob with the given index.
void RemapForSplit(int index);
private:
// Priority queues containing pain points generated by the language model
// The priority is set by the language model components, adjustments like
// seam cost and width priority are factored into the priority.
PainPointHeap pain_points_heaps_[LM_PPTYPE_NUM];
// Maximum number of points to keep in the heap.
int max_heap_size_;
// Maximum character width/height ratio.
float max_char_wh_ratio_;
// Set to true if fixed pitch should be assumed.
bool fixed_pitch_;
// Cached pointer to dictionary.
const Dict *dict_;
// Debug level for print statements.
int debug_level_;
};
} // namespace tesseract
#endif // TESSERACT_WORDREC_PAIN_POINTS_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: lm_consistency.cpp
// Description: Struct for recording consistency of the paths representing
// OCR hypotheses.
// Author: Rika Antonova
// Created: Mon Jun 20 11:26:43 PST 2012
//
// (C) Copyright 2012, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
////////////////////////////////////////////////////////////////////////
#include "lm_consistency.h"
#include "associate.h"
#include "dict.h"
#include "ratngs.h"
namespace tesseract {
void LMConsistencyInfo::ComputeXheightConsistency(
const BLOB_CHOICE *b, bool is_punc) {
if (xht_decision == XH_INCONSISTENT)
return; // It isn't going to get any better.
// Compute xheight consistency.
bool parent_null = xht_sp < 0;
int parent_sp = xht_sp;
// Debug strings.
if (b->yshift() > LMConsistencyInfo::kShiftThresh) {
xht_sp = LMConsistencyInfo::kSUP;
} else if (b->yshift() < -LMConsistencyInfo::kShiftThresh) {
xht_sp = LMConsistencyInfo::kSUB;
} else {
xht_sp = LMConsistencyInfo::kNORM;
}
xht_count[xht_sp]++;
if (is_punc) xht_count_punc[xht_sp]++;
if (!parent_null) {
xpos_entropy += abs(parent_sp - xht_sp);
}
// TODO(eger): Figure out a better way to account for small caps.
// For the first character not y-shifted, we only care if it is too small.
// Too large is common in drop caps and small caps.
// inT16 small_xht = b->min_xheight();
// if (parent_vse == NULL && sp == LanguageModelConsistencyInfo::kNORM) {
// small_xht = 0;
// }
IntersectRange(b->min_xheight(), b->max_xheight(),
&(xht_lo[xht_sp]), &(xht_hi[xht_sp]));
// Compute xheight inconsistency kinds.
if (parent_null) {
if (xht_count[kNORM] == 1) {
xht_decision = XH_GOOD;
} else {
xht_decision = XH_SUBNORMAL;
}
return;
}
// When we intersect the ranges of xheights in pixels for all characters in
// each position (subscript, normal, superscript),
// How much range must be left? 0? [exactly one pixel height for xheight] 1?
// TODO(eger): Extend this code to take a prior for the rest of the line.
const int kMinIntersectedXHeightRange = 0;
for (int i = 0; i < kNumPos; i++) {
if (xht_lo[i] > xht_hi[i] - kMinIntersectedXHeightRange) {
xht_decision = XH_INCONSISTENT;
return;
}
}
// Reject as improbable anything where there's much punctuation in subscript
// or superscript regions.
if (xht_count_punc[kSUB] > xht_count[kSUB] * 0.4 ||
xht_count_punc[kSUP] > xht_count[kSUP] * 0.4) {
xht_decision = XH_INCONSISTENT;
return;
}
// Now check that the subscript and superscript aren't too small relative to
// the mainline.
double mainline_xht = static_cast<double>(xht_lo[kNORM]);
double kMinSizeRatio = 0.4;
if (mainline_xht > 0.0 &&
(static_cast<double>(xht_hi[kSUB]) / mainline_xht < kMinSizeRatio ||
static_cast<double>(xht_hi[kSUP]) / mainline_xht < kMinSizeRatio)) {
xht_decision = XH_INCONSISTENT;
return;
}
// TODO(eger): Check into inconsistency of super/subscript y offsets.
if (xpos_entropy > kMaxEntropy) {
xht_decision = XH_INCONSISTENT;
return;
}
if (xht_count[kSUB] == 0 && xht_count[kSUP] == 0) {
xht_decision = XH_GOOD;
return;
}
xht_decision = XH_SUBNORMAL;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: tface.c (Formerly tface.c)
* Description: C side of the Tess/tessedit C/C++ interface.
* Author: Ray Smith
* Created: Mon Apr 27 11:57:06 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "callcpp.h"
#include "chop.h"
#include "chopper.h"
#include "danerror.h"
#include "fxdefs.h"
#include "globals.h"
#include "gradechop.h"
#include "pageres.h"
#include "wordrec.h"
#include "featdefs.h"
#include "params_model.h"
#include <math.h>
#ifdef __UNIX__
#include <unistd.h>
#endif
namespace tesseract {
/**
* @name program_editup
*
* Initialize all the things in the program that need to be initialized.
* init_permute determines whether to initialize the permute functions
* and Dawg models.
*/
void Wordrec::program_editup(const char *textbase,
bool init_classifier,
bool init_dict) {
if (textbase != NULL) imagefile = textbase;
InitFeatureDefs(&feature_defs_);
SetupExtractors(&feature_defs_);
InitAdaptiveClassifier(init_classifier);
if (init_dict) getDict().Load(Dict::GlobalDawgCache());
pass2_ok_split = chop_ok_split;
}
/**
* @name end_recog
*
* Cleanup and exit the recog program.
*/
int Wordrec::end_recog() {
program_editdown (0);
return (0);
}
/**
* @name program_editdown
*
* This function holds any nessessary post processing for the Wise Owl
* program.
*/
void Wordrec::program_editdown(inT32 elasped_time) {
EndAdaptiveClassifier();
getDict().End();
}
/**
* @name set_pass1
*
* Get ready to do some pass 1 stuff.
*/
void Wordrec::set_pass1() {
chop_ok_split.set_value(70.0);
language_model_->getParamsModel().SetPass(ParamsModel::PTRAIN_PASS1);
SettupPass1();
}
/**
* @name set_pass2
*
* Get ready to do some pass 2 stuff.
*/
void Wordrec::set_pass2() {
chop_ok_split.set_value(pass2_ok_split);
language_model_->getParamsModel().SetPass(ParamsModel::PTRAIN_PASS2);
SettupPass2();
}
/**
* @name cc_recog
*
* Recognize a word.
*/
void Wordrec::cc_recog(WERD_RES *word) {
getDict().reset_hyphen_vars(word->word->flag(W_EOL));
chop_word_main(word);
word->DebugWordChoices(getDict().stopper_debug_level >= 1,
getDict().word_to_debug.string());
ASSERT_HOST(word->StatesAllValid());
}
/**
* @name dict_word()
*
* Test the dictionaries, returning NO_PERM (0) if not found, or one
* of the PermuterType values if found, according to the dictionary.
*/
int Wordrec::dict_word(const WERD_CHOICE &word) {
return getDict().valid_word(word);
}
/**
* @name call_matcher
*
* Called from Tess with a blob in tess form.
* The blob may need rotating to the correct orientation for classification.
*/
BLOB_CHOICE_LIST *Wordrec::call_matcher(TBLOB *tessblob) {
// Rotate the blob for classification if necessary.
TBLOB* rotated_blob = tessblob->ClassifyNormalizeIfNeeded();
if (rotated_blob == NULL) {
rotated_blob = tessblob;
}
BLOB_CHOICE_LIST *ratings = new BLOB_CHOICE_LIST(); // matcher result
AdaptiveClassifier(rotated_blob, ratings);
if (rotated_blob != tessblob) {
delete rotated_blob;
}
return ratings;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: drawfx.cpp (Formerly drawfx.c)
* Description: Draw things to do with feature extraction.
* Author: Ray Smith
* Created: Mon Jan 27 11:02:16 GMT 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "drawfx.h"
#include "normalis.h"
#include "werd.h"
#ifndef GRAPHICS_DISABLED
#define FXDEMOWIN "FXDemo"
#define FXDEMOXPOS 250
#define FXDEMOYPOS 0
#define FXDEMOXSIZE 600
#define FXDEMOYSIZE 256
#define BLN_MAX 512 //max coord for bln
#define WERDWIDTH (BLN_MAX*20)
#define DECENT_WERD_WIDTH (5*kBlnXHeight)
//title of window
#define DEBUG_WIN_NAME "FXDebug"
#define DEBUG_XPOS 0
#define DEBUG_YPOS 120
#define DEBUG_XSIZE 80
#define DEBUG_YSIZE 32
#define YMAX 3508
#define XMAX 2550
#define MAXEDGELENGTH 1024 //max steps inoutline
#define EXTERN
EXTERN STRING_VAR (fx_debugfile, DEBUG_WIN_NAME, "Name of debugfile");
EXTERN ScrollView* fx_win = NULL;
EXTERN FILE *fx_debug = NULL;
/**********************************************************************
* create_fx_win
*
* Create the fx window used to show the fit.
**********************************************************************/
void create_fx_win() { //make features win
fx_win = new ScrollView (FXDEMOWIN,
FXDEMOXPOS, FXDEMOYPOS, FXDEMOXSIZE, FXDEMOYSIZE,
WERDWIDTH*2, BLN_MAX*2, true);
}
/**********************************************************************
* clear_fx_win
*
* Clear the fx window and draw on the base/mean lines.
**********************************************************************/
void clear_fx_win() { //make features win
fx_win->Clear();
fx_win->Pen(64,64,64);
fx_win->Line(-WERDWIDTH, kBlnBaselineOffset, WERDWIDTH, kBlnBaselineOffset);
fx_win->Line(-WERDWIDTH, kBlnXHeight + kBlnBaselineOffset, WERDWIDTH,
kBlnXHeight + kBlnBaselineOffset);
}
#endif // GRAPHICS_DISABLED
/**********************************************************************
* create_fxdebug_win
*
* Create the fx window used to show the fit.
**********************************************************************/
void create_fxdebug_win() { //make gradients win
}
| C++ |
/**********************************************************************
* File: pgedit.cpp (Formerly pgeditor.c)
* Description: Page structure file editor
* Author: Phil Cheatle
* Created: Thu Oct 10 16:25:24 BST 1991
*
*(C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0(the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http:// www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "pgedit.h"
#include <ctype.h>
#include <math.h>
#include "blread.h"
#include "control.h"
#include "paramsd.h"
#include "pageres.h"
#include "tordmain.h"
#include "scrollview.h"
#include "svmnode.h"
#include "statistc.h"
#include "tesseractclass.h"
#include "werdit.h"
#ifndef GRAPHICS_DISABLED
#define ASC_HEIGHT (2 * kBlnBaselineOffset + kBlnXHeight)
#define X_HEIGHT (kBlnBaselineOffset + kBlnXHeight)
#define BL_HEIGHT kBlnBaselineOffset
#define DESC_HEIGHT 0
#define MAXSPACING 128 /*max expected spacing in pix */
const ERRCODE EMPTYBLOCKLIST = "No blocks to edit";
enum CMD_EVENTS
{
NULL_CMD_EVENT,
CHANGE_DISP_CMD_EVENT,
DUMP_WERD_CMD_EVENT,
SHOW_POINT_CMD_EVENT,
SHOW_BLN_WERD_CMD_EVENT,
DEBUG_WERD_CMD_EVENT,
BLAMER_CMD_EVENT,
BOUNDING_BOX_CMD_EVENT,
CORRECT_TEXT_CMD_EVENT,
POLYGONAL_CMD_EVENT,
BL_NORM_CMD_EVENT,
BITMAP_CMD_EVENT,
IMAGE_CMD_EVENT,
BLOCKS_CMD_EVENT,
BASELINES_CMD_EVENT,
UNIFORM_DISP_CMD_EVENT,
REFRESH_CMD_EVENT,
QUIT_CMD_EVENT,
RECOG_WERDS,
RECOG_PSEUDO,
SHOW_BLOB_FEATURES,
SHOW_SUBSCRIPT_CMD_EVENT,
SHOW_SUPERSCRIPT_CMD_EVENT,
SHOW_ITALIC_CMD_EVENT,
SHOW_BOLD_CMD_EVENT,
SHOW_UNDERLINE_CMD_EVENT,
SHOW_FIXEDPITCH_CMD_EVENT,
SHOW_SERIF_CMD_EVENT,
SHOW_SMALLCAPS_CMD_EVENT,
SHOW_DROPCAPS_CMD_EVENT,
};
enum ColorationMode {
CM_RAINBOW,
CM_SUBSCRIPT,
CM_SUPERSCRIPT,
CM_ITALIC,
CM_BOLD,
CM_UNDERLINE,
CM_FIXEDPITCH,
CM_SERIF,
CM_SMALLCAPS,
CM_DROPCAPS
};
/*
*
* Some global data
*
*/
ScrollView* image_win;
ParamsEditor* pe;
bool stillRunning = false;
#ifdef __UNIX__
FILE *debug_window = NULL; // opened on demand
#endif
ScrollView* bln_word_window = NULL; // baseline norm words
CMD_EVENTS mode = CHANGE_DISP_CMD_EVENT; // selected words op
bool recog_done = false; // recog_all_words was called
// These variables should remain global, since they are only used for the
// debug mode (in which only a single Tesseract thread/instance will be exist).
BITS16 word_display_mode;
static ColorationMode color_mode = CM_RAINBOW;
BOOL8 display_image = FALSE;
BOOL8 display_blocks = FALSE;
BOOL8 display_baselines = FALSE;
PAGE_RES *current_page_res = NULL;
STRING_VAR(editor_image_win_name, "EditorImage",
"Editor image window name");
INT_VAR(editor_image_xpos, 590, "Editor image X Pos");
INT_VAR(editor_image_ypos, 10, "Editor image Y Pos");
INT_VAR(editor_image_menuheight, 50, "Add to image height for menu bar");
INT_VAR(editor_image_word_bb_color, ScrollView::BLUE,
"Word bounding box colour");
INT_VAR(editor_image_blob_bb_color, ScrollView::YELLOW,
"Blob bounding box colour");
INT_VAR(editor_image_text_color, ScrollView::WHITE,
"Correct text colour");
STRING_VAR(editor_dbwin_name, "EditorDBWin",
"Editor debug window name");
INT_VAR(editor_dbwin_xpos, 50, "Editor debug window X Pos");
INT_VAR(editor_dbwin_ypos, 500, "Editor debug window Y Pos");
INT_VAR(editor_dbwin_height, 24, "Editor debug window height");
INT_VAR(editor_dbwin_width, 80, "Editor debug window width");
STRING_VAR(editor_word_name, "BlnWords", "BL normalized word window");
INT_VAR(editor_word_xpos, 60, "Word window X Pos");
INT_VAR(editor_word_ypos, 510, "Word window Y Pos");
INT_VAR(editor_word_height, 240, "Word window height");
INT_VAR(editor_word_width, 655, "Word window width");
STRING_VAR(editor_debug_config_file, "", "Config file to apply to single words");
class BlnEventHandler : public SVEventHandler {
public:
void Notify(const SVEvent* sv_event) {
if (sv_event->type == SVET_DESTROY)
bln_word_window = NULL;
else if (sv_event->type == SVET_CLICK)
show_point(current_page_res, sv_event->x, sv_event->y);
}
};
/**
* bln_word_window_handle()
*
* @return a WINDOW for the word window, creating it if necessary
*/
ScrollView* bln_word_window_handle() { // return handle
// not opened yet
if (bln_word_window == NULL) {
pgeditor_msg("Creating BLN word window...");
bln_word_window = new ScrollView(editor_word_name.string(),
editor_word_xpos, editor_word_ypos, editor_word_width,
editor_word_height, 4000, 4000, true);
BlnEventHandler* a = new BlnEventHandler();
bln_word_window->AddEventHandler(a);
pgeditor_msg("Creating BLN word window...Done");
}
return bln_word_window;
}
/**
* build_image_window()
*
* Destroy the existing image window if there is one. Work out how big the
* new window needs to be. Create it and re-display.
*/
void build_image_window(int width, int height) {
if (image_win != NULL) { delete image_win; }
image_win = new ScrollView(editor_image_win_name.string(),
editor_image_xpos, editor_image_ypos,
width + 1,
height + editor_image_menuheight + 1,
width,
height,
true);
}
/**
* display_bln_lines()
*
* Display normalized baseline, x-height, ascender limit and descender limit
*/
void display_bln_lines(ScrollView* window,
ScrollView::Color colour,
float scale_factor,
float y_offset,
float minx,
float maxx) {
window->Pen(colour);
window->Line(minx, y_offset + scale_factor * DESC_HEIGHT,
maxx, y_offset + scale_factor * DESC_HEIGHT);
window->Line(minx, y_offset + scale_factor * BL_HEIGHT,
maxx, y_offset + scale_factor * BL_HEIGHT);
window->Line(minx, y_offset + scale_factor * X_HEIGHT,
maxx, y_offset + scale_factor * X_HEIGHT);
window->Line(minx, y_offset + scale_factor * ASC_HEIGHT,
maxx, y_offset + scale_factor * ASC_HEIGHT);
}
/**
* notify()
*
* Event handler that processes incoming events, either forwarding
* them to process_cmd_win_event or process_image_event.
*
*/
void PGEventHandler::Notify(const SVEvent* event) {
char myval = '0';
if (event->type == SVET_POPUP) {
pe->Notify(event);
} // These are handled by ParamsEditor
else if (event->type == SVET_EXIT) { stillRunning = false; }
else if (event->type == SVET_MENU) {
if (strcmp(event->parameter, "true") == 0) { myval = 'T'; }
else if (strcmp(event->parameter, "false") == 0) { myval = 'F'; }
tess_->process_cmd_win_event(event->command_id, &myval);
}
else {
tess_->process_image_event(*event);
}
}
/**
* build_menu()
*
* Construct the menu tree used by the command window
*/
namespace tesseract {
SVMenuNode *Tesseract::build_menu_new() {
SVMenuNode* parent_menu;
SVMenuNode* root_menu_item = new SVMenuNode();
SVMenuNode* modes_menu_item = root_menu_item->AddChild("MODES");
modes_menu_item->AddChild("Change Display", CHANGE_DISP_CMD_EVENT);
modes_menu_item->AddChild("Dump Word", DUMP_WERD_CMD_EVENT);
modes_menu_item->AddChild("Show Point", SHOW_POINT_CMD_EVENT);
modes_menu_item->AddChild("Show BL Norm Word", SHOW_BLN_WERD_CMD_EVENT);
modes_menu_item->AddChild("Config Words", DEBUG_WERD_CMD_EVENT);
modes_menu_item->AddChild("Recog Words", RECOG_WERDS);
modes_menu_item->AddChild("Recog Blobs", RECOG_PSEUDO);
modes_menu_item->AddChild("Show Blob Features", SHOW_BLOB_FEATURES);
parent_menu = root_menu_item->AddChild("DISPLAY");
parent_menu->AddChild("Blamer", BLAMER_CMD_EVENT, FALSE);
parent_menu->AddChild("Bounding Boxes", BOUNDING_BOX_CMD_EVENT, FALSE);
parent_menu->AddChild("Correct Text", CORRECT_TEXT_CMD_EVENT, FALSE);
parent_menu->AddChild("Polygonal Approx", POLYGONAL_CMD_EVENT, FALSE);
parent_menu->AddChild("Baseline Normalized", BL_NORM_CMD_EVENT, FALSE);
parent_menu->AddChild("Edge Steps", BITMAP_CMD_EVENT, TRUE);
parent_menu->AddChild("Subscripts", SHOW_SUBSCRIPT_CMD_EVENT);
parent_menu->AddChild("Superscripts", SHOW_SUPERSCRIPT_CMD_EVENT);
parent_menu->AddChild("Italics", SHOW_ITALIC_CMD_EVENT);
parent_menu->AddChild("Bold", SHOW_BOLD_CMD_EVENT);
parent_menu->AddChild("Underline", SHOW_UNDERLINE_CMD_EVENT);
parent_menu->AddChild("FixedPitch", SHOW_FIXEDPITCH_CMD_EVENT);
parent_menu->AddChild("Serifs", SHOW_SERIF_CMD_EVENT);
parent_menu->AddChild("SmallCaps", SHOW_SMALLCAPS_CMD_EVENT);
parent_menu->AddChild("DropCaps", SHOW_DROPCAPS_CMD_EVENT);
parent_menu = root_menu_item->AddChild("OTHER");
parent_menu->AddChild("Quit", QUIT_CMD_EVENT);
parent_menu->AddChild("Show Image", IMAGE_CMD_EVENT, FALSE);
parent_menu->AddChild("ShowBlock Outlines", BLOCKS_CMD_EVENT, FALSE);
parent_menu->AddChild("Show Baselines", BASELINES_CMD_EVENT, FALSE);
parent_menu->AddChild("Uniform Display", UNIFORM_DISP_CMD_EVENT);
parent_menu->AddChild("Refresh Display", REFRESH_CMD_EVENT);
return root_menu_item;
}
/**
* do_re_display()
*
* Redisplay page
*/
void Tesseract::do_re_display(
BOOL8 (tesseract::Tesseract::*word_painter)(PAGE_RES_IT* pr_it)) {
int block_count = 1;
image_win->Clear();
if (display_image != 0) {
image_win->Image(pix_binary_, 0, 0);
}
PAGE_RES_IT pr_it(current_page_res);
for (WERD_RES* word = pr_it.word(); word != NULL; word = pr_it.forward()) {
(this->*word_painter)(&pr_it);
if (display_baselines && pr_it.row() != pr_it.prev_row())
pr_it.row()->row->plot_baseline(image_win, ScrollView::GREEN);
if (display_blocks && pr_it.block() != pr_it.prev_block())
pr_it.block()->block->plot(image_win, block_count++, ScrollView::RED);
}
image_win->Update();
}
/**
* pgeditor_main()
*
* Top level editor operation:
* Setup a new window and an according event handler
*
*/
void Tesseract::pgeditor_main(int width, int height, PAGE_RES *page_res) {
current_page_res = page_res;
if (current_page_res->block_res_list.empty())
return;
recog_done = false;
stillRunning = true;
build_image_window(width, height);
word_display_mode.turn_on_bit(DF_EDGE_STEP);
do_re_display(&tesseract::Tesseract::word_set_display);
#ifndef GRAPHICS_DISABLED
pe = new ParamsEditor(this, image_win);
#endif
PGEventHandler pgEventHandler(this);
image_win->AddEventHandler(&pgEventHandler);
image_win->AddMessageBox();
SVMenuNode* svMenuRoot = build_menu_new();
svMenuRoot->BuildMenu(image_win);
image_win->SetVisible(true);
image_win->AwaitEvent(SVET_DESTROY);
image_win->AddEventHandler(NULL);
}
} // namespace tesseract
/**
* pgeditor_msg()
*
* Display a message - in the command window if there is one, or to stdout
*/
void pgeditor_msg( // message display
const char *msg) {
image_win->AddMessage(msg);
}
/**
* pgeditor_show_point()
*
* Display the coordinates of a point in the command window
*/
void pgeditor_show_point( // display coords
SVEvent *event) {
image_win->AddMessage("Pointing at(%d, %d)", event->x, event->y);
}
/**
* process_cmd_win_event()
*
* Process a command returned from the command window
* (Just call the appropriate command handler)
*/
namespace tesseract {
BOOL8 Tesseract::process_cmd_win_event( // UI command semantics
inT32 cmd_event, // which menu item?
char *new_value // any prompt data
) {
char msg[160];
BOOL8 exit = FALSE;
color_mode = CM_RAINBOW;
// Run recognition on the full page if needed.
switch (cmd_event) {
case BLAMER_CMD_EVENT:
case SHOW_SUBSCRIPT_CMD_EVENT:
case SHOW_SUPERSCRIPT_CMD_EVENT:
case SHOW_ITALIC_CMD_EVENT:
case SHOW_BOLD_CMD_EVENT:
case SHOW_UNDERLINE_CMD_EVENT:
case SHOW_FIXEDPITCH_CMD_EVENT:
case SHOW_SERIF_CMD_EVENT:
case SHOW_SMALLCAPS_CMD_EVENT:
case SHOW_DROPCAPS_CMD_EVENT:
if (!recog_done) {
recog_all_words(current_page_res, NULL, NULL, NULL, 0);
recog_done = true;
}
break;
default:
break;
}
switch (cmd_event) {
case NULL_CMD_EVENT:
break;
case CHANGE_DISP_CMD_EVENT:
case DUMP_WERD_CMD_EVENT:
case SHOW_POINT_CMD_EVENT:
case SHOW_BLN_WERD_CMD_EVENT:
case RECOG_WERDS:
case RECOG_PSEUDO:
case SHOW_BLOB_FEATURES:
mode =(CMD_EVENTS) cmd_event;
break;
case DEBUG_WERD_CMD_EVENT:
mode = DEBUG_WERD_CMD_EVENT;
word_config_ = image_win->ShowInputDialog("Config File Name");
break;
case BOUNDING_BOX_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_BOX);
else
word_display_mode.turn_off_bit(DF_BOX);
mode = CHANGE_DISP_CMD_EVENT;
break;
case BLAMER_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_BLAMER);
else
word_display_mode.turn_off_bit(DF_BLAMER);
do_re_display(&tesseract::Tesseract::word_display);
mode = CHANGE_DISP_CMD_EVENT;
break;
case CORRECT_TEXT_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_TEXT);
else
word_display_mode.turn_off_bit(DF_TEXT);
mode = CHANGE_DISP_CMD_EVENT;
break;
case POLYGONAL_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_POLYGONAL);
else
word_display_mode.turn_off_bit(DF_POLYGONAL);
mode = CHANGE_DISP_CMD_EVENT;
break;
case BL_NORM_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_BN_POLYGONAL);
else
word_display_mode.turn_off_bit(DF_BN_POLYGONAL);
mode = CHANGE_DISP_CMD_EVENT;
break;
case BITMAP_CMD_EVENT:
if (new_value[0] == 'T')
word_display_mode.turn_on_bit(DF_EDGE_STEP);
else
word_display_mode.turn_off_bit(DF_EDGE_STEP);
mode = CHANGE_DISP_CMD_EVENT;
break;
case UNIFORM_DISP_CMD_EVENT:
do_re_display(&tesseract::Tesseract::word_set_display);
break;
case IMAGE_CMD_EVENT:
display_image =(new_value[0] == 'T');
do_re_display(&tesseract::Tesseract::word_display);
break;
case BLOCKS_CMD_EVENT:
display_blocks =(new_value[0] == 'T');
do_re_display(&tesseract::Tesseract::word_display);
break;
case BASELINES_CMD_EVENT:
display_baselines =(new_value[0] == 'T');
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_SUBSCRIPT_CMD_EVENT:
color_mode = CM_SUBSCRIPT;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_SUPERSCRIPT_CMD_EVENT:
color_mode = CM_SUPERSCRIPT;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_ITALIC_CMD_EVENT:
color_mode = CM_ITALIC;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_BOLD_CMD_EVENT:
color_mode = CM_BOLD;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_UNDERLINE_CMD_EVENT:
color_mode = CM_UNDERLINE;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_FIXEDPITCH_CMD_EVENT:
color_mode = CM_FIXEDPITCH;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_SERIF_CMD_EVENT:
color_mode = CM_SERIF;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_SMALLCAPS_CMD_EVENT:
color_mode = CM_SMALLCAPS;
do_re_display(&tesseract::Tesseract::word_display);
break;
case SHOW_DROPCAPS_CMD_EVENT:
color_mode = CM_DROPCAPS;
do_re_display(&tesseract::Tesseract::word_display);
break;
case REFRESH_CMD_EVENT:
do_re_display(&tesseract::Tesseract::word_display);
break;
case QUIT_CMD_EVENT:
exit = TRUE;
ScrollView::Exit();
break;
default:
sprintf(msg, "Unrecognised event " INT32FORMAT "(%s)",
cmd_event, new_value);
image_win->AddMessage(msg);
break;
}
return exit;
}
/**
* process_image_event()
*
* User has done something in the image window - mouse down or up. Work out
* what it is and do something with it.
* If DOWN - just remember where it was.
* If UP - for each word in the selected area do the operation defined by
* the current mode.
*/
void Tesseract::process_image_event( // action in image win
const SVEvent &event) {
// The following variable should remain static, since it is used by
// debug editor, which uses a single Tesseract instance.
static ICOORD down;
ICOORD up;
TBOX selection_box;
char msg[80];
switch(event.type) {
case SVET_SELECTION:
if (event.type == SVET_SELECTION) {
down.set_x(event.x + event.x_size);
down.set_y(event.y + event.y_size);
if (mode == SHOW_POINT_CMD_EVENT)
show_point(current_page_res, event.x, event.y);
}
up.set_x(event.x);
up.set_y(event.y);
selection_box = TBOX(down, up);
switch(mode) {
case CHANGE_DISP_CMD_EVENT:
process_selected_words(
current_page_res,
selection_box,
&tesseract::Tesseract::word_blank_and_set_display);
break;
case DUMP_WERD_CMD_EVENT:
process_selected_words(current_page_res,
selection_box,
&tesseract::Tesseract::word_dumper);
break;
case SHOW_BLN_WERD_CMD_EVENT:
process_selected_words(current_page_res,
selection_box,
&tesseract::Tesseract::word_bln_display);
break;
case DEBUG_WERD_CMD_EVENT:
debug_word(current_page_res, selection_box);
break;
case SHOW_POINT_CMD_EVENT:
break; // ignore up event
case RECOG_WERDS:
image_win->AddMessage("Recogging selected words");
this->process_selected_words(current_page_res,
selection_box,
&Tesseract::recog_interactive);
break;
case RECOG_PSEUDO:
image_win->AddMessage("Recogging selected blobs");
recog_pseudo_word(current_page_res, selection_box);
break;
case SHOW_BLOB_FEATURES:
blob_feature_display(current_page_res, selection_box);
break;
default:
sprintf(msg, "Mode %d not yet implemented", mode);
image_win->AddMessage(msg);
break;
}
default:
break;
}
}
/**
* debug_word
*
* Process the whole image, but load word_config_ for the selected word(s).
*/
void Tesseract::debug_word(PAGE_RES* page_res, const TBOX &selection_box) {
ResetAdaptiveClassifier();
recog_all_words(page_res, NULL, &selection_box, word_config_.string(), 0);
}
} // namespace tesseract
/**
* show_point()
*
* Show coords of point, blob bounding box, word bounding box and offset from
* row baseline
*/
void show_point(PAGE_RES* page_res, float x, float y) {
FCOORD pt(x, y);
PAGE_RES_IT pr_it(page_res);
char msg[160];
char *msg_ptr = msg;
msg_ptr += sprintf(msg_ptr, "Pt:(%0.3f, %0.3f) ", x, y);
for (WERD_RES* word = pr_it.word(); word != NULL; word = pr_it.forward()) {
if (pr_it.row() != pr_it.prev_row() &&
pr_it.row()->row->bounding_box().contains(pt)) {
msg_ptr += sprintf(msg_ptr, "BL(x)=%0.3f ",
pr_it.row()->row->base_line(x));
}
if (word->word->bounding_box().contains(pt)) {
TBOX box = word->word->bounding_box();
msg_ptr += sprintf(msg_ptr, "Wd(%d, %d)/(%d, %d) ",
box.left(), box.bottom(),
box.right(), box.top());
C_BLOB_IT cblob_it(word->word->cblob_list());
for (cblob_it.mark_cycle_pt();
!cblob_it.cycled_list();
cblob_it.forward()) {
C_BLOB* cblob = cblob_it.data();
box = cblob->bounding_box();
if (box.contains(pt)) {
msg_ptr += sprintf(msg_ptr,
"CBlb(%d, %d)/(%d, %d) ",
box.left(), box.bottom(),
box.right(), box.top());
}
}
}
}
image_win->AddMessage(msg);
}
/**********************************************************************
* WERD PROCESSOR FUNCTIONS
* ========================
*
* These routines are invoked by one or more of:
* process_all_words()
* process_selected_words()
* or
* process_all_words_it()
* process_selected_words_it()
* for each word to be processed
**********************************************************************/
/**
* word_blank_and_set_display() Word processor
*
* Blank display of word then redisplay word according to current display mode
* settings
*/
#endif // GRAPHICS_DISABLED
namespace tesseract {
#ifndef GRAPHICS_DISABLED
BOOL8 Tesseract:: word_blank_and_set_display(PAGE_RES_IT* pr_it) {
pr_it->word()->word->bounding_box().plot(image_win, ScrollView::BLACK,
ScrollView::BLACK);
return word_set_display(pr_it);
}
/**
* word_bln_display()
*
* Normalize word and display in word window
*/
BOOL8 Tesseract::word_bln_display(PAGE_RES_IT* pr_it) {
WERD_RES* word_res = pr_it->word();
if (word_res->chopped_word == NULL) {
// Setup word normalization parameters.
word_res->SetupForRecognition(unicharset, this, BestPix(),
tessedit_ocr_engine_mode, NULL,
classify_bln_numeric_mode,
textord_use_cjk_fp_model,
poly_allow_detailed_fx,
pr_it->row()->row, pr_it->block()->block);
}
bln_word_window_handle()->Clear();
display_bln_lines(bln_word_window_handle(), ScrollView::CYAN,
1.0, 0.0f, -1000.0f, 1000.0f);
C_BLOB_IT it(word_res->word->cblob_list());
ScrollView::Color color = WERD::NextColor(ScrollView::BLACK);
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward()) {
it.data()->plot_normed(word_res->denorm, color, ScrollView::BROWN,
bln_word_window_handle());
color = WERD::NextColor(color);
}
bln_word_window_handle()->Update();
return TRUE;
}
/**
* word_display() Word Processor
*
* Display a word according to its display modes
*/
BOOL8 Tesseract::word_display(PAGE_RES_IT* pr_it) {
WERD_RES* word_res = pr_it->word();
WERD* word = word_res->word;
TBOX word_bb; // word bounding box
int word_height; // ht of word BB
BOOL8 displayed_something = FALSE;
float shift; // from bot left
C_BLOB_IT c_it; // cblob iterator
if (color_mode != CM_RAINBOW && word_res->box_word != NULL) {
BoxWord* box_word = word_res->box_word;
WERD_CHOICE* best_choice = word_res->best_choice;
int length = box_word->length();
if (word_res->fontinfo == NULL) return false;
const FontInfo& font_info = *word_res->fontinfo;
for (int i = 0; i < length; ++i) {
ScrollView::Color color = ScrollView::GREEN;
switch (color_mode) {
case CM_SUBSCRIPT:
if (best_choice->BlobPosition(i) == SP_SUBSCRIPT)
color = ScrollView::RED;
break;
case CM_SUPERSCRIPT:
if (best_choice->BlobPosition(i) == SP_SUPERSCRIPT)
color = ScrollView::RED;
break;
case CM_ITALIC:
if (font_info.is_italic())
color = ScrollView::RED;
break;
case CM_BOLD:
if (font_info.is_bold())
color = ScrollView::RED;
break;
case CM_FIXEDPITCH:
if (font_info.is_fixed_pitch())
color = ScrollView::RED;
break;
case CM_SERIF:
if (font_info.is_serif())
color = ScrollView::RED;
break;
case CM_SMALLCAPS:
if (word_res->small_caps)
color = ScrollView::RED;
break;
case CM_DROPCAPS:
if (best_choice->BlobPosition(i) == SP_DROPCAP)
color = ScrollView::RED;
break;
// TODO(rays) underline is currently completely unsupported.
case CM_UNDERLINE:
default:
break;
}
image_win->Pen(color);
TBOX box = box_word->BlobBox(i);
image_win->Rectangle(box.left(), box.bottom(), box.right(), box.top());
}
return true;
}
/*
Note the double coercions of(COLOUR)((inT32)editor_image_word_bb_color)
etc. are to keep the compiler happy.
*/
// display bounding box
if (word->display_flag(DF_BOX)) {
word->bounding_box().plot(image_win,
(ScrollView::Color)((inT32)
editor_image_word_bb_color),
(ScrollView::Color)((inT32)
editor_image_word_bb_color));
ScrollView::Color c = (ScrollView::Color)
((inT32) editor_image_blob_bb_color);
image_win->Pen(c);
c_it.set_to_list(word->cblob_list());
for (c_it.mark_cycle_pt(); !c_it.cycled_list(); c_it.forward())
c_it.data()->bounding_box().plot(image_win);
displayed_something = TRUE;
}
// display edge steps
if (word->display_flag(DF_EDGE_STEP)) { // edgesteps available
word->plot(image_win); // rainbow colors
displayed_something = TRUE;
}
// display poly approx
if (word->display_flag(DF_POLYGONAL)) {
// need to convert
TWERD* tword = TWERD::PolygonalCopy(poly_allow_detailed_fx, word);
tword->plot(image_win);
delete tword;
displayed_something = TRUE;
}
// Display correct text and blamer information.
STRING text;
STRING blame;
if (word->display_flag(DF_TEXT) && word->text() != NULL) {
text = word->text();
}
if (word->display_flag(DF_BLAMER) &&
!(word_res->blamer_bundle != NULL &&
word_res->blamer_bundle->incorrect_result_reason() == IRR_CORRECT)) {
text = "";
const BlamerBundle *blamer_bundle = word_res->blamer_bundle;
if (blamer_bundle == NULL) {
text += "NULL";
} else {
text = blamer_bundle->TruthString();
}
text += " -> ";
STRING best_choice_str;
if (word_res->best_choice == NULL) {
best_choice_str = "NULL";
} else {
word_res->best_choice->string_and_lengths(&best_choice_str, NULL);
}
text += best_choice_str;
IncorrectResultReason reason = (blamer_bundle == NULL) ?
IRR_PAGE_LAYOUT : blamer_bundle->incorrect_result_reason();
ASSERT_HOST(reason < IRR_NUM_REASONS)
blame += " [";
blame += BlamerBundle::IncorrectReasonName(reason);
blame += "]";
}
if (text.length() > 0) {
word_bb = word->bounding_box();
image_win->Pen(ScrollView::RED);
word_height = word_bb.height();
int text_height = 0.50 * word_height;
if (text_height > 20) text_height = 20;
image_win->TextAttributes("Arial", text_height, false, false, false);
shift = (word_height < word_bb.width()) ? 0.25 * word_height : 0.0f;
image_win->Text(word_bb.left() + shift,
word_bb.bottom() + 0.25 * word_height, text.string());
if (blame.length() > 0) {
image_win->Text(word_bb.left() + shift,
word_bb.bottom() + 0.25 * word_height - text_height,
blame.string());
}
displayed_something = TRUE;
}
if (!displayed_something) // display BBox anyway
word->bounding_box().plot(image_win,
(ScrollView::Color)((inT32) editor_image_word_bb_color),
(ScrollView::Color)((inT32)
editor_image_word_bb_color));
return TRUE;
}
#endif // GRAPHICS_DISABLED
/**
* word_dumper()
*
* Dump members to the debug window
*/
BOOL8 Tesseract::word_dumper(PAGE_RES_IT* pr_it) {
if (pr_it->block()->block != NULL) {
tprintf("\nBlock data...\n");
pr_it->block()->block->print(NULL, FALSE);
}
tprintf("\nRow data...\n");
pr_it->row()->row->print(NULL);
tprintf("\nWord data...\n");
WERD_RES* word_res = pr_it->word();
word_res->word->print();
if (word_res->blamer_bundle != NULL && wordrec_debug_blamer &&
word_res->blamer_bundle->incorrect_result_reason() != IRR_CORRECT) {
tprintf("Current blamer debug: %s\n",
word_res->blamer_bundle->debug().string());
}
return TRUE;
}
#ifndef GRAPHICS_DISABLED
/**
* word_set_display() Word processor
*
* Display word according to current display mode settings
*/
BOOL8 Tesseract::word_set_display(PAGE_RES_IT* pr_it) {
WERD* word = pr_it->word()->word;
word->set_display_flag(DF_BOX, word_display_mode.bit(DF_BOX));
word->set_display_flag(DF_TEXT, word_display_mode.bit(DF_TEXT));
word->set_display_flag(DF_POLYGONAL, word_display_mode.bit(DF_POLYGONAL));
word->set_display_flag(DF_EDGE_STEP, word_display_mode.bit(DF_EDGE_STEP));
word->set_display_flag(DF_BN_POLYGONAL,
word_display_mode.bit(DF_BN_POLYGONAL));
word->set_display_flag(DF_BLAMER, word_display_mode.bit(DF_BLAMER));
return word_display(pr_it);
}
// page_res is non-const because the iterator doesn't know if you are going
// to change the items it points to! Really a const here though.
void Tesseract::blob_feature_display(PAGE_RES* page_res,
const TBOX& selection_box) {
PAGE_RES_IT* it = make_pseudo_word(page_res, selection_box);
if (it != NULL) {
WERD_RES* word_res = it->word();
word_res->x_height = it->row()->row->x_height();
word_res->SetupForRecognition(unicharset, this, BestPix(),
tessedit_ocr_engine_mode, NULL,
classify_bln_numeric_mode,
textord_use_cjk_fp_model,
poly_allow_detailed_fx,
it->row()->row, it->block()->block);
TWERD* bln_word = word_res->chopped_word;
TBLOB* bln_blob = bln_word->blobs[0];
INT_FX_RESULT_STRUCT fx_info;
GenericVector<INT_FEATURE_STRUCT> bl_features;
GenericVector<INT_FEATURE_STRUCT> cn_features;
Classify::ExtractFeatures(*bln_blob, classify_nonlinear_norm, &bl_features,
&cn_features, &fx_info, NULL);
// Display baseline features.
ScrollView* bl_win = CreateFeatureSpaceWindow("BL Features", 512, 0);
ClearFeatureSpaceWindow(baseline, bl_win);
for (int f = 0; f < bl_features.size(); ++f)
RenderIntFeature(bl_win, &bl_features[f], ScrollView::GREEN);
bl_win->Update();
// Display cn features.
ScrollView* cn_win = CreateFeatureSpaceWindow("CN Features", 512, 0);
ClearFeatureSpaceWindow(character, cn_win);
for (int f = 0; f < cn_features.size(); ++f)
RenderIntFeature(cn_win, &cn_features[f], ScrollView::GREEN);
cn_win->Update();
it->DeleteCurrentWord();
delete it;
}
}
#endif // GRAPHICS_DISABLED
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: par_control.cpp
// Description: Control code for parallel implementation.
// Author: Ray Smith
// Created: Mon Nov 04 13:23:15 PST 2013
//
// (C) Copyright 2013, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "tesseractclass.h"
namespace tesseract {
struct BlobData {
BlobData() : blob(NULL), choices(NULL) {}
BlobData(int index, Tesseract* tess, const WERD_RES& word)
: blob(word.chopped_word->blobs[index]),
tesseract(tess),
choices(&(*word.ratings)(index, index)) {}
TBLOB* blob;
Tesseract* tesseract;
BLOB_CHOICE_LIST** choices;
};
void Tesseract::PrerecAllWordsPar(const GenericVector<WordData>& words) {
// Prepare all the blobs.
GenericVector<BlobData> blobs;
for (int w = 0; w < words.size(); ++w) {
if (words[w].word->ratings != NULL &&
words[w].word->ratings->get(0, 0) == NULL) {
for (int s = 0; s < words[w].lang_words.size(); ++s) {
Tesseract* sub = s < sub_langs_.size() ? sub_langs_[s] : this;
const WERD_RES& word = *words[w].lang_words[s];
for (int b = 0; b < word.chopped_word->NumBlobs(); ++b) {
blobs.push_back(BlobData(b, sub, word));
}
}
}
}
// Pre-classify all the blobs.
if (tessedit_parallelize > 1) {
#pragma omp parallel for num_threads(10)
for (int b = 0; b < blobs.size(); ++b) {
*blobs[b].choices =
blobs[b].tesseract->classify_blob(blobs[b].blob, "par", White, NULL);
}
} else {
// TODO(AMD) parallelize this.
for (int b = 0; b < blobs.size(); ++b) {
*blobs[b].choices =
blobs[b].tesseract->classify_blob(blobs[b].blob, "par", White, NULL);
}
}
}
} // namespace tesseract.
| C++ |
///////////////////////////////////////////////////////////////////////
// File: resultiterator.h
// Description: Iterator for tesseract results that is capable of
// iterating in proper reading order over Bi Directional
// (e.g. mixed Hebrew and English) text.
// Author: David Eger
// Created: Fri May 27 13:58:06 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_RESULT_ITERATOR_H__
#define TESSERACT_CCMAIN_RESULT_ITERATOR_H__
#include "platform.h"
#include "ltrresultiterator.h"
template <typename T> class GenericVector;
template <typename T> class GenericVectorEqEq;
class BLOB_CHOICE_IT;
class WERD_RES;
class STRING;
namespace tesseract {
class Tesseract;
class TESS_API ResultIterator : public LTRResultIterator {
public:
static ResultIterator *StartOfParagraph(const LTRResultIterator &resit);
/**
* ResultIterator is copy constructible!
* The default copy constructor works just fine for us.
*/
virtual ~ResultIterator() {}
// ============= Moving around within the page ============.
/**
* Moves the iterator to point to the start of the page to begin
* an iteration.
*/
virtual void Begin();
/**
* Moves to the start of the next object at the given level in the
* page hierarchy in the appropriate reading order and returns false if
* the end of the page was reached.
* NOTE that RIL_SYMBOL will skip non-text blocks, but all other
* PageIteratorLevel level values will visit each non-text block once.
* Think of non text blocks as containing a single para, with a single line,
* with a single imaginary word.
* Calls to Next with different levels may be freely intermixed.
* This function iterates words in right-to-left scripts correctly, if
* the appropriate language has been loaded into Tesseract.
*/
virtual bool Next(PageIteratorLevel level);
/**
* IsAtBeginningOf() returns whether we're at the logical beginning of the
* given level. (as opposed to ResultIterator's left-to-right top-to-bottom
* order). Otherwise, this acts the same as PageIterator::IsAtBeginningOf().
* For a full description, see pageiterator.h
*/
virtual bool IsAtBeginningOf(PageIteratorLevel level) const;
/**
* Implement PageIterator's IsAtFinalElement correctly in a BiDi context.
* For instance, IsAtFinalElement(RIL_PARA, RIL_WORD) returns whether we
* point at the last word in a paragraph. See PageIterator for full comment.
*/
virtual bool IsAtFinalElement(PageIteratorLevel level,
PageIteratorLevel element) const;
// ============= Accessing data ==============.
/**
* Returns the null terminated UTF-8 encoded text string for the current
* object at the given level. Use delete [] to free after use.
*/
virtual char* GetUTF8Text(PageIteratorLevel level) const;
/**
* Return whether the current paragraph's dominant reading direction
* is left-to-right (as opposed to right-to-left).
*/
bool ParagraphIsLtr() const;
// ============= Exposed only for testing =============.
/**
* Yields the reading order as a sequence of indices and (optional)
* meta-marks for a set of words (given left-to-right).
* The meta marks are passed as negative values:
* kMinorRunStart Start of minor direction text.
* kMinorRunEnd End of minor direction text.
* kComplexWord The next indexed word contains both left-to-right and
* right-to-left characters and was treated as neutral.
*
* For example, suppose we have five words in a text line,
* indexed [0,1,2,3,4] from the leftmost side of the text line.
* The following are all believable reading_orders:
*
* Left-to-Right (in ltr paragraph):
* { 0, 1, 2, 3, 4 }
* Left-to-Right (in rtl paragraph):
* { kMinorRunStart, 0, 1, 2, 3, 4, kMinorRunEnd }
* Right-to-Left (in rtl paragraph):
* { 4, 3, 2, 1, 0 }
* Left-to-Right except for an RTL phrase in words 2, 3 in an ltr paragraph:
* { 0, 1, kMinorRunStart, 3, 2, kMinorRunEnd, 4 }
*/
static void CalculateTextlineOrder(
bool paragraph_is_ltr,
const GenericVector<StrongScriptDirection> &word_dirs,
GenericVectorEqEq<int> *reading_order);
static const int kMinorRunStart;
static const int kMinorRunEnd;
static const int kComplexWord;
protected:
/**
* We presume the data associated with the given iterator will outlive us.
* NB: This is private because it does something that is non-obvious:
* it resets to the beginning of the paragraph instead of staying wherever
* resit might have pointed.
*/
TESS_LOCAL explicit ResultIterator(const LTRResultIterator &resit);
private:
/**
* Calculates the current paragraph's dominant writing direction.
* Typically, members should use current_paragraph_ltr_ instead.
*/
bool CurrentParagraphIsLtr() const;
/**
* Returns word indices as measured from resit->RestartRow() = index 0
* for the reading order of words within a textline given an iterator
* into the middle of the text line.
* In addition to non-negative word indices, the following negative values
* may be inserted:
* kMinorRunStart Start of minor direction text.
* kMinorRunEnd End of minor direction text.
* kComplexWord The previous word contains both left-to-right and
* right-to-left characters and was treated as neutral.
*/
void CalculateTextlineOrder(bool paragraph_is_ltr,
const LTRResultIterator &resit,
GenericVectorEqEq<int> *indices) const;
/** Same as above, but the caller's ssd gets filled in if ssd != NULL. */
void CalculateTextlineOrder(bool paragraph_is_ltr,
const LTRResultIterator &resit,
GenericVector<StrongScriptDirection> *ssd,
GenericVectorEqEq<int> *indices) const;
/**
* What is the index of the current word in a strict left-to-right reading
* of the row?
*/
int LTRWordIndex() const;
/**
* Given an iterator pointing at a word, returns the logical reading order
* of blob indices for the word.
*/
void CalculateBlobOrder(GenericVector<int> *blob_indices) const;
/** Precondition: current_paragraph_is_ltr_ is set. */
void MoveToLogicalStartOfTextline();
/**
* Precondition: current_paragraph_is_ltr_ and in_minor_direction_
* are set.
*/
void MoveToLogicalStartOfWord();
/** Are we pointing at the final (reading order) symbol of the word? */
bool IsAtFinalSymbolOfWord() const;
/** Are we pointing at the first (reading order) symbol of the word? */
bool IsAtFirstSymbolOfWord() const;
/**
* Append any extra marks that should be appended to this word when printed.
* Mostly, these are Unicode BiDi control characters.
*/
void AppendSuffixMarks(STRING *text) const;
/** Appends the current word in reading order to the given buffer.*/
void AppendUTF8WordText(STRING *text) const;
/**
* Appends the text of the current text line, *assuming this iterator is
* positioned at the beginning of the text line* This function
* updates the iterator to point to the first position past the text line.
* Each textline is terminated in a single newline character.
* If the textline ends a paragraph, it gets a second terminal newline.
*/
void IterateAndAppendUTF8TextlineText(STRING *text);
/**
* Appends the text of the current paragraph in reading order
* to the given buffer.
* Each textline is terminated in a single newline character, and the
* paragraph gets an extra newline at the end.
*/
void AppendUTF8ParagraphText(STRING *text) const;
/** Returns whether the bidi_debug flag is set to at least min_level. */
bool BidiDebug(int min_level) const;
bool current_paragraph_is_ltr_;
/**
* Is the currently pointed-at character at the beginning of
* a minor-direction run?
*/
bool at_beginning_of_minor_run_;
/** Is the currently pointed-at character in a minor-direction sequence? */
bool in_minor_direction_;
/**
* Should detected inter-word spaces be preserved, or "compressed" to a single
* space character (default behavior).
*/
bool preserve_interword_spaces_;
};
} // namespace tesseract.
#endif // TESSERACT_CCMAIN_RESULT_ITERATOR_H__
| C++ |
/**********************************************************************
* File: werdit.cpp (Formerly wordit.c)
* Description: An iterator for passing over all the words in a document.
* Author: Ray Smith
* Created: Mon Apr 27 08:51:22 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "werdit.h"
/**********************************************************************
* make_pseudo_word
*
* Make all the blobs inside a selection into a single word.
* The returned PAGE_RES_IT* it points to the new word. After use, call
* it->DeleteCurrentWord() to delete the fake word, and then
* delete it to get rid of the iterator itself.
**********************************************************************/
PAGE_RES_IT* make_pseudo_word(PAGE_RES* page_res, const TBOX& selection_box) {
PAGE_RES_IT pr_it(page_res);
C_BLOB_LIST new_blobs; // list of gathered blobs
C_BLOB_IT new_blob_it = &new_blobs; // iterator
for (WERD_RES* word_res = pr_it.word(); word_res != NULL;
word_res = pr_it.forward()) {
WERD* word = word_res->word;
if (word->bounding_box().overlap(selection_box)) {
C_BLOB_IT blob_it(word->cblob_list());
for (blob_it.mark_cycle_pt();
!blob_it.cycled_list(); blob_it.forward()) {
C_BLOB* blob = blob_it.data();
if (blob->bounding_box().overlap(selection_box)) {
new_blob_it.add_after_then_move(C_BLOB::deep_copy(blob));
}
}
if (!new_blobs.empty()) {
WERD* pseudo_word = new WERD(&new_blobs, 1, NULL);
word_res = pr_it.InsertSimpleCloneWord(*word_res, pseudo_word);
PAGE_RES_IT* it = new PAGE_RES_IT(page_res);
while (it->word() != word_res && it->word() != NULL) it->forward();
ASSERT_HOST(it->word() == word_res);
return it;
}
}
}
return NULL;
}
| C++ |
/**********************************************************************
* File: tessbox.cpp (Formerly tessbox.c)
* Description: Black boxed Tess for developing a resaljet.
* Author: Ray Smith
* Created: Thu Apr 23 11:03:36 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
#include "mfoutline.h"
#include "tessbox.h"
#include "tesseractclass.h"
#define EXTERN
/**
* @name tess_segment_pass_n
*
* Segment a word using the pass_n conditions of the tess segmenter.
* @param pass_n pass number
* @param word word to do
*/
namespace tesseract {
void Tesseract::tess_segment_pass_n(int pass_n, WERD_RES *word) {
int saved_enable_assoc = 0;
int saved_chop_enable = 0;
if (word->word->flag(W_DONT_CHOP)) {
saved_enable_assoc = wordrec_enable_assoc;
saved_chop_enable = chop_enable;
wordrec_enable_assoc.set_value(0);
chop_enable.set_value(0);
}
if (pass_n == 1)
set_pass1();
else
set_pass2();
recog_word(word);
if (word->best_choice == NULL)
word->SetupFake(*word->uch_set);
if (word->word->flag(W_DONT_CHOP)) {
wordrec_enable_assoc.set_value(saved_enable_assoc);
chop_enable.set_value(saved_chop_enable);
}
}
/**
* @name tess_acceptable_word
*
* @return true if the word is regarded as "good enough".
* @param word_choice after context
* @param raw_choice before context
*/
bool Tesseract::tess_acceptable_word(WERD_RES* word) {
return getDict().AcceptableResult(word);
}
/**
* @name tess_add_doc_word
*
* Add the given word to the document dictionary
*/
void Tesseract::tess_add_doc_word(WERD_CHOICE *word_choice) {
getDict().add_document_word(*word_choice);
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: paramsd.cpp
// Description: Tesseract parameter editor
// Author: Joern Wanke
// Created: Wed Jul 18 10:05:01 PDT 2007
//
// (C) Copyright 2007, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
//
// Tesseract parameter editor is used to edit all the parameters used
// within tesseract from the ui.
#ifndef GRAPHICS_DISABLED
#ifndef VARABLED_H
#define VARABLED_H
#include "elst.h"
#include "scrollview.h"
#include "params.h"
#include "tesseractclass.h"
class SVMenuNode;
// A list of all possible parameter types used.
enum ParamType {
VT_INTEGER,
VT_BOOLEAN,
VT_STRING,
VT_DOUBLE
};
// A rather hackish helper structure which can take any kind of parameter input
// (defined by ParamType) and do a couple of common operations on them, like
// comparisond or getting its value. It is used in the context of the
// ParamsEditor as a bridge from the internal tesseract parameters to the
// ones displayed by the ScrollView server.
class ParamContent : public ELIST_LINK {
public:
// Compare two VC objects by their name.
static int Compare(const void* v1, const void* v2);
// Gets a VC object identified by its ID.
static ParamContent* GetParamContentById(int id);
// Constructors for the various ParamTypes.
ParamContent() {
}
explicit ParamContent(tesseract::StringParam* it);
explicit ParamContent(tesseract::IntParam* it);
explicit ParamContent(tesseract::BoolParam* it);
explicit ParamContent(tesseract::DoubleParam* it);
// Getters and Setters.
void SetValue(const char* val);
STRING GetValue() const;
const char* GetName() const;
const char* GetDescription() const;
int GetId() { return my_id_; }
bool HasChanged() { return changed_; }
private:
// The unique ID of this VC object.
int my_id_;
// Whether the parameter was changed_ and thus needs to be rewritten.
bool changed_;
// The actual ParamType of this VC object.
ParamType param_type_;
tesseract::StringParam* sIt;
tesseract::IntParam* iIt;
tesseract::BoolParam* bIt;
tesseract::DoubleParam* dIt;
};
ELISTIZEH(ParamContent)
// The parameters editor enables the user to edit all the parameters used within
// tesseract. It can be invoked on its own, but is supposed to be invoked by
// the program editor.
class ParamsEditor : public SVEventHandler {
public:
// Integrate the parameters editor as popupmenu into the existing scrollview
// window (usually the pg editor). If sv == null, create a new empty
// empty window and attach the parameter editor to that window (ugly).
explicit ParamsEditor(tesseract::Tesseract*, ScrollView* sv = NULL);
// Event listener. Waits for SVET_POPUP events and processes them.
void Notify(const SVEvent* sve);
private:
// Gets the up to the first 3 prefixes from s (split by _).
// For example, tesseract_foo_bar will be split into tesseract,foo and bar.
void GetPrefixes(const char* s, STRING* level_one,
STRING* level_two, STRING* level_three);
// Gets the first n words (split by _) and puts them in t.
// For example, tesseract_foo_bar with N=2 will yield tesseract_foo_.
void GetFirstWords(const char *s, // source string
int n, // number of words
char *t); // target string
// Find all editable parameters used within tesseract and create a
// SVMenuNode tree from it.
SVMenuNode *BuildListOfAllLeaves(tesseract::Tesseract *tess);
// Write all (changed_) parameters to a config file.
void WriteParams(char* filename, bool changes_only);
ScrollView* sv_window_;
};
#endif
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: equationdetect.cpp
// Description: Helper classes to detect equations.
// Author: Zongyi (Joe) Liu (joeliu@google.com)
// Created: Fri Aug 31 11:13:01 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#include <mathfix.h>
#endif
#ifdef __MINGW32__
#include <limits.h>
#endif
#include <float.h>
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "equationdetect.h"
#include "bbgrid.h"
#include "classify.h"
#include "colpartition.h"
#include "colpartitiongrid.h"
#include "colpartitionset.h"
#include "helpers.h"
#include "ratngs.h"
#include "tesseractclass.h"
// Config variables.
BOOL_VAR(equationdetect_save_bi_image, false, "Save input bi image");
BOOL_VAR(equationdetect_save_spt_image, false, "Save special character image");
BOOL_VAR(equationdetect_save_seed_image, false, "Save the seed image");
BOOL_VAR(equationdetect_save_merged_image, false, "Save the merged image");
namespace tesseract {
///////////////////////////////////////////////////////////////////////////
// Utility ColParition sort functions.
///////////////////////////////////////////////////////////////////////////
static int SortCPByTopReverse(const void* p1, const void* p2) {
const ColPartition* cp1 = *reinterpret_cast<ColPartition* const*>(p1);
const ColPartition* cp2 = *reinterpret_cast<ColPartition* const*>(p2);
ASSERT_HOST(cp1 != NULL && cp2 != NULL);
const TBOX &box1(cp1->bounding_box()), &box2(cp2->bounding_box());
return box2.top() - box1.top();
}
static int SortCPByBottom(const void* p1, const void* p2) {
const ColPartition* cp1 = *reinterpret_cast<ColPartition* const*>(p1);
const ColPartition* cp2 = *reinterpret_cast<ColPartition* const*>(p2);
ASSERT_HOST(cp1 != NULL && cp2 != NULL);
const TBOX &box1(cp1->bounding_box()), &box2(cp2->bounding_box());
return box1.bottom() - box2.bottom();
}
static int SortCPByHeight(const void* p1, const void* p2) {
const ColPartition* cp1 = *reinterpret_cast<ColPartition* const*>(p1);
const ColPartition* cp2 = *reinterpret_cast<ColPartition* const*>(p2);
ASSERT_HOST(cp1 != NULL && cp2 != NULL);
const TBOX &box1(cp1->bounding_box()), &box2(cp2->bounding_box());
return box1.height() - box2.height();
}
// TODO(joeliu): we may want to parameterize these constants.
const float kMathDigitDensityTh1 = 0.25;
const float kMathDigitDensityTh2 = 0.1;
const float kMathItalicDensityTh = 0.5;
const float kUnclearDensityTh = 0.25;
const int kSeedBlobsCountTh = 10;
const int kLeftIndentAlignmentCountTh = 1;
// Returns true if PolyBlockType is of text type or equation type.
inline bool IsTextOrEquationType(PolyBlockType type) {
return PTIsTextType(type) || type == PT_EQUATION;
}
inline bool IsLeftIndented(const EquationDetect::IndentType type) {
return type == EquationDetect::LEFT_INDENT ||
type == EquationDetect::BOTH_INDENT;
}
inline bool IsRightIndented(const EquationDetect::IndentType type) {
return type == EquationDetect::RIGHT_INDENT ||
type == EquationDetect::BOTH_INDENT;
}
EquationDetect::EquationDetect(const char* equ_datapath,
const char* equ_name) {
const char* default_name = "equ";
if (equ_name == NULL) {
equ_name = default_name;
}
equ_tesseract_ = lang_tesseract_ = NULL;
resolution_ = 0;
page_count_ = 0;
// Construct equ_tesseract_.
equ_tesseract_ = new Tesseract();
if (equ_tesseract_->init_tesseract(equ_datapath, equ_name,
OEM_TESSERACT_ONLY)) {
tprintf("Warning: equation region detection requested,"
" but %s failed to load from %s\n", equ_name, equ_datapath);
delete equ_tesseract_;
equ_tesseract_ = NULL;
}
cps_super_bbox_ = NULL;
}
EquationDetect::~EquationDetect() {
if (equ_tesseract_) {
delete (equ_tesseract_);
}
if (cps_super_bbox_) {
delete(cps_super_bbox_);
}
}
void EquationDetect::SetLangTesseract(Tesseract* lang_tesseract) {
lang_tesseract_ = lang_tesseract;
}
void EquationDetect::SetResolution(const int resolution) {
resolution_ = resolution;
}
int EquationDetect::LabelSpecialText(TO_BLOCK* to_block) {
if (to_block == NULL) {
tprintf("Warning: input to_block is NULL!\n");
return -1;
}
GenericVector<BLOBNBOX_LIST*> blob_lists;
blob_lists.push_back(&(to_block->blobs));
blob_lists.push_back(&(to_block->large_blobs));
for (int i = 0; i < blob_lists.size(); ++i) {
BLOBNBOX_IT bbox_it(blob_lists[i]);
for (bbox_it.mark_cycle_pt (); !bbox_it.cycled_list();
bbox_it.forward()) {
bbox_it.data()->set_special_text_type(BSTT_NONE);
}
}
return 0;
}
void EquationDetect::IdentifySpecialText(
BLOBNBOX *blobnbox, const int height_th) {
ASSERT_HOST(blobnbox != NULL);
if (blobnbox->bounding_box().height() < height_th && height_th > 0) {
// For small blob, we simply set to BSTT_NONE.
blobnbox->set_special_text_type(BSTT_NONE);
return;
}
BLOB_CHOICE_LIST ratings_equ, ratings_lang;
C_BLOB* blob = blobnbox->cblob();
// TODO(joeliu/rays) Fix this. We may have to normalize separately for
// each classifier here, as they may require different PolygonalCopy.
TBLOB* tblob = TBLOB::PolygonalCopy(false, blob);
const TBOX& box = tblob->bounding_box();
// Normalize the blob. Set the origin to the place we want to be the
// bottom-middle, and scaling is to make the height the x-height.
float scaling = static_cast<float>(kBlnXHeight) / box.height();
float x_orig = (box.left() + box.right()) / 2.0f, y_orig = box.bottom();
TBLOB* normed_blob = new TBLOB(*tblob);
normed_blob->Normalize(NULL, NULL, NULL, x_orig, y_orig, scaling, scaling,
0.0f, static_cast<float>(kBlnBaselineOffset),
false, NULL);
equ_tesseract_->AdaptiveClassifier(normed_blob, &ratings_equ);
lang_tesseract_->AdaptiveClassifier(normed_blob, &ratings_lang);
delete normed_blob;
delete tblob;
// Get the best choice from ratings_lang and rating_equ. As the choice in the
// list has already been sorted by the certainty, we simply use the first
// choice.
BLOB_CHOICE *lang_choice = NULL, *equ_choice = NULL;
if (ratings_lang.length() > 0) {
BLOB_CHOICE_IT choice_it(&ratings_lang);
lang_choice = choice_it.data();
}
if (ratings_equ.length() > 0) {
BLOB_CHOICE_IT choice_it(&ratings_equ);
equ_choice = choice_it.data();
}
float lang_score = lang_choice ? lang_choice->certainty() : -FLT_MAX;
float equ_score = equ_choice ? equ_choice->certainty() : -FLT_MAX;
const float kConfScoreTh = -5.0f, kConfDiffTh = 1.8;
// The scores here are negative, so the max/min == fabs(min/max).
// float ratio = fmax(lang_score, equ_score) / fmin(lang_score, equ_score);
float diff = fabs(lang_score - equ_score);
BlobSpecialTextType type = BSTT_NONE;
// Classification.
if (fmax(lang_score, equ_score) < kConfScoreTh) {
// If both score are very small, then mark it as unclear.
type = BSTT_UNCLEAR;
} else if (diff > kConfDiffTh && equ_score > lang_score) {
// If equ_score is significantly higher, then we classify this character as
// math symbol.
type = BSTT_MATH;
} else if (lang_choice) {
// For other cases: lang_score is similar or significantly higher.
type = EstimateTypeForUnichar(
lang_tesseract_->unicharset, lang_choice->unichar_id());
}
if (type == BSTT_NONE && lang_tesseract_->get_fontinfo_table().get(
lang_choice->fontinfo_id()).is_italic()) {
// For text symbol, we still check if it is italic.
blobnbox->set_special_text_type(BSTT_ITALIC);
} else {
blobnbox->set_special_text_type(type);
}
}
BlobSpecialTextType EquationDetect::EstimateTypeForUnichar(
const UNICHARSET& unicharset, const UNICHAR_ID id) const {
STRING s = unicharset.id_to_unichar(id);
if (unicharset.get_isalpha(id)) {
return BSTT_NONE;
}
if (unicharset.get_ispunctuation(id)) {
// Exclude some special texts that are likely to be confused as math symbol.
static GenericVector<UNICHAR_ID> ids_to_exclude;
if (ids_to_exclude.empty()) {
static const STRING kCharsToEx[] = {"'", "`", "\"", "\\", ",", ".",
"〈", "〉", "《", "》", "」", "「", ""};
int i = 0;
while (kCharsToEx[i] != "") {
ids_to_exclude.push_back(
unicharset.unichar_to_id(kCharsToEx[i++].string()));
}
ids_to_exclude.sort();
}
return ids_to_exclude.bool_binary_search(id) ? BSTT_NONE : BSTT_MATH;
}
// Check if it is digit. In addition to the isdigit attribute, we also check
// if this character belongs to those likely to be confused with a digit.
static const STRING kDigitsChars = "|";
if (unicharset.get_isdigit(id) ||
(s.length() == 1 && kDigitsChars.contains(s[0]))) {
return BSTT_DIGIT;
} else {
return BSTT_MATH;
}
}
void EquationDetect::IdentifySpecialText() {
// Set configuration for Tesseract::AdaptiveClassifier.
equ_tesseract_->tess_cn_matching.set_value(true); // turn it on
equ_tesseract_->tess_bn_matching.set_value(false);
// Set the multiplier to zero for lang_tesseract_ to improve the accuracy.
int classify_class_pruner = lang_tesseract_->classify_class_pruner_multiplier;
int classify_integer_matcher =
lang_tesseract_->classify_integer_matcher_multiplier;
lang_tesseract_->classify_class_pruner_multiplier.set_value(0);
lang_tesseract_->classify_integer_matcher_multiplier.set_value(0);
ColPartitionGridSearch gsearch(part_grid_);
ColPartition *part = NULL;
gsearch.StartFullSearch();
while ((part = gsearch.NextFullSearch()) != NULL) {
if (!IsTextOrEquationType(part->type())) {
continue;
}
IdentifyBlobsToSkip(part);
BLOBNBOX_C_IT bbox_it(part->boxes());
// Compute the height threshold.
GenericVector<int> blob_heights;
for (bbox_it.mark_cycle_pt (); !bbox_it.cycled_list();
bbox_it.forward()) {
if (bbox_it.data()->special_text_type() != BSTT_SKIP) {
blob_heights.push_back(bbox_it.data()->bounding_box().height());
}
}
blob_heights.sort();
int height_th = blob_heights[blob_heights.size() / 2] / 3 * 2;
for (bbox_it.mark_cycle_pt (); !bbox_it.cycled_list();
bbox_it.forward()) {
if (bbox_it.data()->special_text_type() != BSTT_SKIP) {
IdentifySpecialText(bbox_it.data(), height_th);
}
}
}
// Set the multiplier values back.
lang_tesseract_->classify_class_pruner_multiplier.set_value(
classify_class_pruner);
lang_tesseract_->classify_integer_matcher_multiplier.set_value(
classify_integer_matcher);
if (equationdetect_save_spt_image) { // For debug.
STRING outfile;
GetOutputTiffName("_spt", &outfile);
PaintSpecialTexts(outfile);
}
}
void EquationDetect::IdentifyBlobsToSkip(ColPartition* part) {
ASSERT_HOST(part);
BLOBNBOX_C_IT blob_it(part->boxes());
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
// At this moment, no blob should have been joined.
ASSERT_HOST(!blob_it.data()->joined_to_prev());
}
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
BLOBNBOX* blob = blob_it.data();
if (blob->joined_to_prev() || blob->special_text_type() == BSTT_SKIP) {
continue;
}
TBOX blob_box = blob->bounding_box();
// Search if any blob can be merged into blob. If found, then we mark all
// these blobs as BSTT_SKIP.
BLOBNBOX_C_IT blob_it2 = blob_it;
bool found = false;
while (!blob_it2.at_last()) {
BLOBNBOX* nextblob = blob_it2.forward();
const TBOX& nextblob_box = nextblob->bounding_box();
if (nextblob_box.left() >= blob_box.right()) {
break;
}
const float kWidthR = 0.4, kHeightR = 0.3;
bool xoverlap = blob_box.major_x_overlap(nextblob_box),
yoverlap = blob_box.y_overlap(nextblob_box);
float widthR = static_cast<float>(
MIN(nextblob_box.width(), blob_box.width())) /
MAX(nextblob_box.width(), blob_box.width());
float heightR = static_cast<float>(
MIN(nextblob_box.height(), blob_box.height())) /
MAX(nextblob_box.height(), blob_box.height());
if (xoverlap && yoverlap && widthR > kWidthR && heightR > kHeightR) {
// Found one, set nextblob type and recompute blob_box.
found = true;
nextblob->set_special_text_type(BSTT_SKIP);
blob_box += nextblob_box;
}
}
if (found) {
blob->set_special_text_type(BSTT_SKIP);
}
}
}
int EquationDetect::FindEquationParts(
ColPartitionGrid* part_grid, ColPartitionSet** best_columns) {
if (!equ_tesseract_ || !lang_tesseract_) {
tprintf("Warning: equ_tesseract_/lang_tesseract_ is NULL!\n");
return -1;
}
if (!part_grid || !best_columns) {
tprintf("part_grid/best_columns is NULL!!\n");
return -1;
}
cp_seeds_.clear();
part_grid_ = part_grid;
best_columns_ = best_columns;
resolution_ = lang_tesseract_->source_resolution();
STRING outfile;
page_count_++;
if (equationdetect_save_bi_image) {
GetOutputTiffName("_bi", &outfile);
pixWrite(outfile.string(), lang_tesseract_->pix_binary(), IFF_TIFF_G4);
}
// Pass 0: Compute special text type for blobs.
IdentifySpecialText();
// Pass 1: Merge parts by overlap.
MergePartsByLocation();
// Pass 2: compute the math blob density and find the seed partition.
IdentifySeedParts();
// We still need separate seed into block seed and inline seed partition.
IdentifyInlineParts();
if (equationdetect_save_seed_image) {
GetOutputTiffName("_seed", &outfile);
PaintColParts(outfile);
}
// Pass 3: expand block equation seeds.
while (!cp_seeds_.empty()) {
GenericVector<ColPartition*> seeds_expanded;
for (int i = 0; i < cp_seeds_.size(); ++i) {
if (ExpandSeed(cp_seeds_[i])) {
// If this seed is expanded, then we add it into seeds_expanded. Note
// this seed has been removed from part_grid_ if it is expanded.
seeds_expanded.push_back(cp_seeds_[i]);
}
}
// Add seeds_expanded back into part_grid_ and reset cp_seeds_.
for (int i = 0; i < seeds_expanded.size(); ++i) {
InsertPartAfterAbsorb(seeds_expanded[i]);
}
cp_seeds_ = seeds_expanded;
}
// Pass 4: find math block satellite text partitions and merge them.
ProcessMathBlockSatelliteParts();
if (equationdetect_save_merged_image) { // For debug.
GetOutputTiffName("_merged", &outfile);
PaintColParts(outfile);
}
return 0;
}
void EquationDetect::MergePartsByLocation() {
while (true) {
ColPartition* part = NULL;
// partitions that have been updated.
GenericVector<ColPartition*> parts_updated;
ColPartitionGridSearch gsearch(part_grid_);
gsearch.StartFullSearch();
while ((part = gsearch.NextFullSearch()) != NULL) {
if (!IsTextOrEquationType(part->type())) {
continue;
}
GenericVector<ColPartition*> parts_to_merge;
SearchByOverlap(part, &parts_to_merge);
if (parts_to_merge.empty()) {
continue;
}
// Merge parts_to_merge with part, and remove them from part_grid_.
part_grid_->RemoveBBox(part);
for (int i = 0; i < parts_to_merge.size(); ++i) {
ASSERT_HOST(parts_to_merge[i] != NULL && parts_to_merge[i] != part);
part->Absorb(parts_to_merge[i], NULL);
}
gsearch.RepositionIterator();
parts_updated.push_back(part);
}
if (parts_updated.empty()) { // Exit the loop
break;
}
// Re-insert parts_updated into part_grid_.
for (int i = 0; i < parts_updated.size(); ++i) {
InsertPartAfterAbsorb(parts_updated[i]);
}
}
}
void EquationDetect::SearchByOverlap(
ColPartition* seed,
GenericVector<ColPartition*>* parts_overlap) {
ASSERT_HOST(seed != NULL && parts_overlap != NULL);
if (!IsTextOrEquationType(seed->type())) {
return;
}
ColPartitionGridSearch search(part_grid_);
const TBOX& seed_box(seed->bounding_box());
const int kRadNeighborCells = 30;
search.StartRadSearch((seed_box.left() + seed_box.right()) / 2,
(seed_box.top() + seed_box.bottom()) / 2,
kRadNeighborCells);
search.SetUniqueMode(true);
// Search iteratively.
ColPartition *part;
GenericVector<ColPartition*> parts;
const float kLargeOverlapTh = 0.95;
const float kEquXOverlap = 0.4, kEquYOverlap = 0.5;
while ((part = search.NextRadSearch()) != NULL) {
if (part == seed || !IsTextOrEquationType(part->type())) {
continue;
}
const TBOX& part_box(part->bounding_box());
bool merge = false;
float x_overlap_fraction = part_box.x_overlap_fraction(seed_box),
y_overlap_fraction = part_box.y_overlap_fraction(seed_box);
// If part is large overlapped with seed, then set merge to true.
if (x_overlap_fraction >= kLargeOverlapTh &&
y_overlap_fraction >= kLargeOverlapTh) {
merge = true;
} else if (seed->type() == PT_EQUATION &&
IsTextOrEquationType(part->type())) {
if ((x_overlap_fraction > kEquXOverlap && y_overlap_fraction > 0.0) ||
(x_overlap_fraction > 0.0 && y_overlap_fraction > kEquYOverlap)) {
merge = true;
}
}
if (merge) { // Remove the part from search and put it into parts.
search.RemoveBBox();
parts_overlap->push_back(part);
}
}
}
void EquationDetect::InsertPartAfterAbsorb(ColPartition* part) {
ASSERT_HOST(part);
// Before insert part back into part_grid_, we will need re-compute some
// of its attributes such as first_column_, last_column_. However, we still
// want to preserve its type.
BlobTextFlowType flow_type = part->flow();
PolyBlockType part_type = part->type();
BlobRegionType blob_type = part->blob_type();
// Call SetPartitionType to re-compute the attributes of part.
const TBOX& part_box(part->bounding_box());
int grid_x, grid_y;
part_grid_->GridCoords(
part_box.left(), part_box.bottom(), &grid_x, &grid_y);
part->SetPartitionType(resolution_, best_columns_[grid_y]);
// Reset the types back.
part->set_type(part_type);
part->set_blob_type(blob_type);
part->set_flow(flow_type);
part->SetBlobTypes();
// Insert into part_grid_.
part_grid_->InsertBBox(true, true, part);
}
void EquationDetect::IdentifySeedParts() {
ColPartitionGridSearch gsearch(part_grid_);
ColPartition *part = NULL;
gsearch.StartFullSearch();
GenericVector<ColPartition*> seeds1, seeds2;
// The left coordinates of indented text partitions.
GenericVector<int> indented_texts_left;
// The foreground density of text partitions.
GenericVector<float> texts_foreground_density;
while ((part = gsearch.NextFullSearch()) != NULL) {
if (!IsTextOrEquationType(part->type())) {
continue;
}
part->ComputeSpecialBlobsDensity();
bool blobs_check = CheckSeedBlobsCount(part);
const int kTextBlobsTh = 20;
if (CheckSeedDensity(kMathDigitDensityTh1, kMathDigitDensityTh2, part) &&
blobs_check) {
// Passed high density threshold test, save into seeds1.
seeds1.push_back(part);
} else {
IndentType indent = IsIndented(part);
if (IsLeftIndented(indent) && blobs_check &&
CheckSeedDensity(kMathDigitDensityTh2, kMathDigitDensityTh2, part)) {
// Passed low density threshold test and is indented, save into seeds2.
seeds2.push_back(part);
} else if (!IsRightIndented(indent) &&
part->boxes_count() > kTextBlobsTh) {
// This is likely to be a text part, save the features.
const TBOX&box = part->bounding_box();
if (IsLeftIndented(indent)) {
indented_texts_left.push_back(box.left());
}
texts_foreground_density.push_back(ComputeForegroundDensity(box));
}
}
}
// Sort the features collected from text regions.
indented_texts_left.sort();
texts_foreground_density.sort();
float foreground_density_th = 0.15; // Default value.
if (!texts_foreground_density.empty()) {
// Use the median of the texts_foreground_density.
foreground_density_th = 0.8 * texts_foreground_density[
texts_foreground_density.size() / 2];
}
for (int i = 0; i < seeds1.size(); ++i) {
const TBOX& box = seeds1[i]->bounding_box();
if (CheckSeedFgDensity(foreground_density_th, seeds1[i]) &&
!(IsLeftIndented(IsIndented(seeds1[i])) &&
CountAlignment(indented_texts_left, box.left()) >=
kLeftIndentAlignmentCountTh)) {
// Mark as PT_EQUATION type.
seeds1[i]->set_type(PT_EQUATION);
cp_seeds_.push_back(seeds1[i]);
} else { // Mark as PT_INLINE_EQUATION type.
seeds1[i]->set_type(PT_INLINE_EQUATION);
}
}
for (int i = 0; i < seeds2.size(); ++i) {
if (CheckForSeed2(indented_texts_left, foreground_density_th, seeds2[i])) {
seeds2[i]->set_type(PT_EQUATION);
cp_seeds_.push_back(seeds2[i]);
}
}
}
float EquationDetect::ComputeForegroundDensity(const TBOX& tbox) {
#if LIBLEPT_MINOR_VERSION < 69 && LIBLEPT_MAJOR_VERSION <= 1
// This will disable the detector because no seed will be identified.
return 1.0f;
#else
Pix *pix_bi = lang_tesseract_->pix_binary();
int pix_height = pixGetHeight(pix_bi);
Box* box = boxCreate(tbox.left(), pix_height - tbox.top(),
tbox.width(), tbox.height());
Pix *pix_sub = pixClipRectangle(pix_bi, box, NULL);
l_float32 fract;
pixForegroundFraction(pix_sub, &fract);
pixDestroy(&pix_sub);
boxDestroy(&box);
return fract;
#endif
}
bool EquationDetect::CheckSeedFgDensity(const float density_th,
ColPartition* part) {
ASSERT_HOST(part);
// Split part horizontall, and check for each sub part.
GenericVector<TBOX> sub_boxes;
SplitCPHorLite(part, &sub_boxes);
float parts_passed = 0.0;
for (int i = 0; i < sub_boxes.size(); ++i) {
float density = ComputeForegroundDensity(sub_boxes[i]);
if (density < density_th) {
parts_passed++;
}
}
// If most sub parts passed, then we return true.
const float kSeedPartRatioTh = 0.3;
bool retval = (parts_passed / sub_boxes.size() >= kSeedPartRatioTh);
return retval;
}
void EquationDetect::SplitCPHor(ColPartition* part,
GenericVector<ColPartition*>* parts_splitted) {
ASSERT_HOST(part && parts_splitted);
if (part->median_width() == 0 || part->boxes_count() == 0) {
return;
}
// Make a copy of part, and reset parts_splitted.
ColPartition* right_part = part->CopyButDontOwnBlobs();
parts_splitted->delete_data_pointers();
parts_splitted->clear();
const double kThreshold = part->median_width() * 3.0;
bool found_split = true;
while (found_split) {
found_split = false;
BLOBNBOX_C_IT box_it(right_part->boxes());
// Blobs are sorted left side first. If blobs overlap,
// the previous blob may have a "more right" right side.
// Account for this by always keeping the largest "right"
// so far.
int previous_right = MIN_INT32;
// Look for the next split in the partition.
for (box_it.mark_cycle_pt(); !box_it.cycled_list(); box_it.forward()) {
const TBOX& box = box_it.data()->bounding_box();
if (previous_right != MIN_INT32 &&
box.left() - previous_right > kThreshold) {
// We have a split position. Split the partition in two pieces.
// Insert the left piece in the grid and keep processing the right.
int mid_x = (box.left() + previous_right) / 2;
ColPartition* left_part = right_part;
right_part = left_part->SplitAt(mid_x);
parts_splitted->push_back(left_part);
left_part->ComputeSpecialBlobsDensity();
found_split = true;
break;
}
// The right side of the previous blobs.
previous_right = MAX(previous_right, box.right());
}
}
// Add the last piece.
right_part->ComputeSpecialBlobsDensity();
parts_splitted->push_back(right_part);
}
void EquationDetect::SplitCPHorLite(ColPartition* part,
GenericVector<TBOX>* splitted_boxes) {
ASSERT_HOST(part && splitted_boxes);
splitted_boxes->clear();
if (part->median_width() == 0) {
return;
}
const double kThreshold = part->median_width() * 3.0;
// Blobs are sorted left side first. If blobs overlap,
// the previous blob may have a "more right" right side.
// Account for this by always keeping the largest "right"
// so far.
TBOX union_box;
int previous_right = MIN_INT32;
BLOBNBOX_C_IT box_it(part->boxes());
for (box_it.mark_cycle_pt(); !box_it.cycled_list(); box_it.forward()) {
const TBOX& box = box_it.data()->bounding_box();
if (previous_right != MIN_INT32 &&
box.left() - previous_right > kThreshold) {
// We have a split position.
splitted_boxes->push_back(union_box);
previous_right = MIN_INT32;
}
if (previous_right == MIN_INT32) {
union_box = box;
} else {
union_box += box;
}
// The right side of the previous blobs.
previous_right = MAX(previous_right, box.right());
}
// Add the last piece.
if (previous_right != MIN_INT32) {
splitted_boxes->push_back(union_box);
}
}
bool EquationDetect::CheckForSeed2(
const GenericVector<int>& indented_texts_left,
const float foreground_density_th,
ColPartition* part) {
ASSERT_HOST(part);
const TBOX& box = part->bounding_box();
// Check if it is aligned with any indented_texts_left.
if (!indented_texts_left.empty() &&
CountAlignment(indented_texts_left, box.left()) >=
kLeftIndentAlignmentCountTh) {
return false;
}
// Check the foreground density.
if (ComputeForegroundDensity(box) > foreground_density_th) {
return false;
}
return true;
}
int EquationDetect::CountAlignment(
const GenericVector<int>& sorted_vec, const int val) const {
if (sorted_vec.empty()) {
return 0;
}
const int kDistTh = static_cast<int>(roundf(0.03 * resolution_));
int pos = sorted_vec.binary_search(val), count = 0;
// Search left side.
int index = pos;
while (index >= 0 && abs(val - sorted_vec[index--]) < kDistTh) {
count++;
}
// Search right side.
index = pos + 1;
while (index < sorted_vec.size() && sorted_vec[index++] - val < kDistTh) {
count++;
}
return count;
}
void EquationDetect::IdentifyInlineParts() {
ComputeCPsSuperBBox();
IdentifyInlinePartsHorizontal();
int textparts_linespacing = EstimateTextPartLineSpacing();
IdentifyInlinePartsVertical(true, textparts_linespacing);
IdentifyInlinePartsVertical(false, textparts_linespacing);
}
void EquationDetect::ComputeCPsSuperBBox() {
ColPartitionGridSearch gsearch(part_grid_);
ColPartition *part = NULL;
gsearch.StartFullSearch();
if (cps_super_bbox_) {
delete cps_super_bbox_;
}
cps_super_bbox_ = new TBOX();
while ((part = gsearch.NextFullSearch()) != NULL) {
(*cps_super_bbox_) += part->bounding_box();
}
}
void EquationDetect::IdentifyInlinePartsHorizontal() {
ASSERT_HOST(cps_super_bbox_);
GenericVector<ColPartition*> new_seeds;
const int kMarginDiffTh = IntCastRounded(
0.5 * lang_tesseract_->source_resolution());
const int kGapTh = static_cast<int>(roundf(
1.0 * lang_tesseract_->source_resolution()));
ColPartitionGridSearch search(part_grid_);
search.SetUniqueMode(true);
// The center x coordinate of the cp_super_bbox_.
int cps_cx = cps_super_bbox_->left() + cps_super_bbox_->width() / 2;
for (int i = 0; i < cp_seeds_.size(); ++i) {
ColPartition* part = cp_seeds_[i];
const TBOX& part_box(part->bounding_box());
int left_margin = part_box.left() - cps_super_bbox_->left(),
right_margin = cps_super_bbox_->right() - part_box.right();
bool right_to_left;
if (left_margin + kMarginDiffTh < right_margin &&
left_margin < kMarginDiffTh) {
// part is left aligned, so we search if it has any right neighbor.
search.StartSideSearch(
part_box.right(), part_box.top(), part_box.bottom());
right_to_left = false;
} else if (left_margin > cps_cx) {
// part locates on the right half on image, so search if it has any left
// neighbor.
search.StartSideSearch(
part_box.left(), part_box.top(), part_box.bottom());
right_to_left = true;
} else { // part is not an inline equation.
new_seeds.push_back(part);
continue;
}
ColPartition* neighbor = NULL;
bool side_neighbor_found = false;
while ((neighbor = search.NextSideSearch(right_to_left)) != NULL) {
const TBOX& neighbor_box(neighbor->bounding_box());
if (!IsTextOrEquationType(neighbor->type()) ||
part_box.x_gap(neighbor_box) > kGapTh ||
!part_box.major_y_overlap(neighbor_box) ||
part_box.major_x_overlap(neighbor_box)) {
continue;
}
// We have found one. Set the side_neighbor_found flag.
side_neighbor_found = true;
break;
}
if (!side_neighbor_found) { // Mark part as PT_INLINE_EQUATION.
part->set_type(PT_INLINE_EQUATION);
} else {
// Check the geometric feature of neighbor.
const TBOX& neighbor_box(neighbor->bounding_box());
if (neighbor_box.width() > part_box.width() &&
neighbor->type() != PT_EQUATION) { // Mark as PT_INLINE_EQUATION.
part->set_type(PT_INLINE_EQUATION);
} else { // part is not an inline equation type.
new_seeds.push_back(part);
}
}
}
// Reset the cp_seeds_ using the new_seeds.
cp_seeds_ = new_seeds;
}
int EquationDetect::EstimateTextPartLineSpacing() {
ColPartitionGridSearch gsearch(part_grid_);
// Get the y gap between text partitions;
ColPartition *current = NULL, *prev = NULL;
gsearch.StartFullSearch();
GenericVector<int> ygaps;
while ((current = gsearch.NextFullSearch()) != NULL) {
if (!PTIsTextType(current->type())) {
continue;
}
if (prev != NULL) {
const TBOX ¤t_box = current->bounding_box();
const TBOX &prev_box = prev->bounding_box();
// prev and current should be x major overlap and non y overlap.
if (current_box.major_x_overlap(prev_box) &&
!current_box.y_overlap(prev_box)) {
int gap = current_box.y_gap(prev_box);
if (gap < MIN(current_box.height(), prev_box.height())) {
// The gap should be smaller than the height of the bounding boxes.
ygaps.push_back(gap);
}
}
}
prev = current;
}
if (ygaps.size() < 8) { // We do not have enough data.
return -1;
}
// Compute the line spacing from ygaps: use the mean of the first half.
ygaps.sort();
int spacing = 0, count;
for (count = 0; count < ygaps.size() / 2; count++) {
spacing += ygaps[count];
}
return spacing / count;
}
void EquationDetect::IdentifyInlinePartsVertical(
const bool top_to_bottom, const int textparts_linespacing) {
if (cp_seeds_.empty()) {
return;
}
// Sort cp_seeds_.
if (top_to_bottom) { // From top to bottom.
cp_seeds_.sort(&SortCPByTopReverse);
} else { // From bottom to top.
cp_seeds_.sort(&SortCPByBottom);
}
GenericVector<ColPartition*> new_seeds;
for (int i = 0; i < cp_seeds_.size(); ++i) {
ColPartition* part = cp_seeds_[i];
// If we sort cp_seeds_ from top to bottom, then for each cp_seeds_, we look
// for its top neighbors, so that if two/more inline regions are connected
// to each other, then we will identify the top one, and then use it to
// identify the bottom one.
if (IsInline(!top_to_bottom, textparts_linespacing, part)) {
part->set_type(PT_INLINE_EQUATION);
} else {
new_seeds.push_back(part);
}
}
cp_seeds_ = new_seeds;
}
bool EquationDetect::IsInline(const bool search_bottom,
const int textparts_linespacing,
ColPartition* part) {
ASSERT_HOST(part != NULL);
// Look for its nearest vertical neighbor that hardly overlaps in y but
// largely overlaps in x.
ColPartitionGridSearch search(part_grid_);
ColPartition *neighbor = NULL;
const TBOX& part_box(part->bounding_box());
const float kYGapRatioTh = 1.0;
if (search_bottom) {
search.StartVerticalSearch(part_box.left(), part_box.right(),
part_box.bottom());
} else {
search.StartVerticalSearch(part_box.left(), part_box.right(),
part_box.top());
}
search.SetUniqueMode(true);
while ((neighbor = search.NextVerticalSearch(search_bottom)) != NULL) {
const TBOX& neighbor_box(neighbor->bounding_box());
if (part_box.y_gap(neighbor_box) > kYGapRatioTh *
MIN(part_box.height(), neighbor_box.height())) {
// Finished searching.
break;
}
if (!PTIsTextType(neighbor->type())) {
continue;
}
// Check if neighbor and part is inline similar.
const float kHeightRatioTh = 0.5;
const int kYGapTh = textparts_linespacing > 0 ?
textparts_linespacing + static_cast<int>(roundf(0.02 * resolution_)):
static_cast<int>(roundf(0.05 * resolution_)); // Default value.
if (part_box.x_overlap(neighbor_box) && // Location feature.
part_box.y_gap(neighbor_box) <= kYGapTh && // Line spacing.
// Geo feature.
static_cast<float>(MIN(part_box.height(), neighbor_box.height())) /
MAX(part_box.height(), neighbor_box.height()) > kHeightRatioTh) {
return true;
}
}
return false;
}
bool EquationDetect::CheckSeedBlobsCount(ColPartition* part) {
if (!part) {
return false;
}
const int kSeedMathBlobsCount = 2;
const int kSeedMathDigitBlobsCount = 5;
int blobs = part->boxes_count(),
math_blobs = part->SpecialBlobsCount(BSTT_MATH),
digit_blobs = part->SpecialBlobsCount(BSTT_DIGIT);
if (blobs < kSeedBlobsCountTh || math_blobs <= kSeedMathBlobsCount ||
math_blobs + digit_blobs <= kSeedMathDigitBlobsCount) {
return false;
}
return true;
}
bool EquationDetect::CheckSeedDensity(
const float math_density_high,
const float math_density_low,
const ColPartition* part) const {
ASSERT_HOST(part);
float math_digit_density = part->SpecialBlobsDensity(BSTT_MATH)
+ part->SpecialBlobsDensity(BSTT_DIGIT);
float italic_density = part->SpecialBlobsDensity(BSTT_ITALIC);
if (math_digit_density > math_density_high) {
return true;
}
if (math_digit_density + italic_density > kMathItalicDensityTh &&
math_digit_density > math_density_low) {
return true;
}
return false;
}
EquationDetect::IndentType EquationDetect::IsIndented(ColPartition* part) {
ASSERT_HOST(part);
ColPartitionGridSearch search(part_grid_);
ColPartition *neighbor = NULL;
const TBOX& part_box(part->bounding_box());
const int kXGapTh = static_cast<int>(roundf(0.5 * resolution_));
const int kRadiusTh = static_cast<int>(roundf(3.0 * resolution_));
const int kYGapTh = static_cast<int>(roundf(0.5 * resolution_));
// Here we use a simple approximation algorithm: from the center of part, We
// perform the radius search, and check if we can find a neighboring parition
// that locates on the top/bottom left of part.
search.StartRadSearch((part_box.left() + part_box.right()) / 2,
(part_box.top() + part_box.bottom()) / 2, kRadiusTh);
search.SetUniqueMode(true);
bool left_indented = false, right_indented = false;
while ((neighbor = search.NextRadSearch()) != NULL &&
(!left_indented || !right_indented)) {
if (neighbor == part) {
continue;
}
const TBOX& neighbor_box(neighbor->bounding_box());
if (part_box.major_y_overlap(neighbor_box) &&
part_box.x_gap(neighbor_box) < kXGapTh) {
// When this happens, it is likely part is a fragment of an
// over-segmented colpartition. So we return false.
return NO_INDENT;
}
if (!IsTextOrEquationType(neighbor->type())) {
continue;
}
// The neighbor should be above/below part, and overlap in x direction.
if (!part_box.x_overlap(neighbor_box) || part_box.y_overlap(neighbor_box)) {
continue;
}
if (part_box.y_gap(neighbor_box) < kYGapTh) {
int left_gap = part_box.left() - neighbor_box.left();
int right_gap = neighbor_box.right() - part_box.right();
if (left_gap > kXGapTh) {
left_indented = true;
}
if (right_gap > kXGapTh) {
right_indented = true;
}
}
}
if (left_indented && right_indented) {
return BOTH_INDENT;
}
if (left_indented) {
return LEFT_INDENT;
}
if (right_indented) {
return RIGHT_INDENT;
}
return NO_INDENT;
}
bool EquationDetect::ExpandSeed(ColPartition* seed) {
if (seed == NULL || // This seed has been absorbed by other seeds.
seed->IsVerticalType()) { // We skip vertical type right now.
return false;
}
// Expand in four directions.
GenericVector<ColPartition*> parts_to_merge;
ExpandSeedHorizontal(true, seed, &parts_to_merge);
ExpandSeedHorizontal(false, seed, &parts_to_merge);
ExpandSeedVertical(true, seed, &parts_to_merge);
ExpandSeedVertical(false, seed, &parts_to_merge);
SearchByOverlap(seed, &parts_to_merge);
if (parts_to_merge.empty()) { // We don't find any partition to merge.
return false;
}
// Merge all partitions in parts_to_merge with seed. We first remove seed
// from part_grid_ as its bounding box is going to expand. Then we add it
// back after it aborbs all parts_to_merge parititions.
part_grid_->RemoveBBox(seed);
for (int i = 0; i < parts_to_merge.size(); ++i) {
ColPartition* part = parts_to_merge[i];
if (part->type() == PT_EQUATION) {
// If part is in cp_seeds_, then we mark it as NULL so that we won't
// process it again.
for (int j = 0; j < cp_seeds_.size(); ++j) {
if (part == cp_seeds_[j]) {
cp_seeds_[j] = NULL;
break;
}
}
}
// part has already been removed from part_grid_ in function
// ExpandSeedHorizontal/ExpandSeedVertical.
seed->Absorb(part, NULL);
}
return true;
}
void EquationDetect::ExpandSeedHorizontal(
const bool search_left,
ColPartition* seed,
GenericVector<ColPartition*>* parts_to_merge) {
ASSERT_HOST(seed != NULL && parts_to_merge != NULL);
const float kYOverlapTh = 0.6;
const int kXGapTh = static_cast<int>(roundf(0.2 * resolution_));
ColPartitionGridSearch search(part_grid_);
const TBOX& seed_box(seed->bounding_box());
int x = search_left ? seed_box.left() : seed_box.right();
search.StartSideSearch(x, seed_box.bottom(), seed_box.top());
search.SetUniqueMode(true);
// Search iteratively.
ColPartition *part = NULL;
while ((part = search.NextSideSearch(search_left)) != NULL) {
if (part == seed) {
continue;
}
const TBOX& part_box(part->bounding_box());
if (part_box.x_gap(seed_box) > kXGapTh) { // Out of scope.
break;
}
// Check part location.
if ((part_box.left() >= seed_box.left() && search_left) ||
(part_box.right() <= seed_box.right() && !search_left)) {
continue;
}
if (part->type() != PT_EQUATION) { // Non-equation type.
// Skip PT_LINLINE_EQUATION and non text type.
if (part->type() == PT_INLINE_EQUATION ||
(!IsTextOrEquationType(part->type()) &&
part->blob_type() != BRT_HLINE)) {
continue;
}
// For other types, it should be the near small neighbor of seed.
if (!IsNearSmallNeighbor(seed_box, part_box) ||
!CheckSeedNeighborDensity(part)) {
continue;
}
} else { // Equation type, check the y overlap.
if (part_box.y_overlap_fraction(seed_box) < kYOverlapTh &&
seed_box.y_overlap_fraction(part_box) < kYOverlapTh) {
continue;
}
}
// Passed the check, delete it from search and add into parts_to_merge.
search.RemoveBBox();
parts_to_merge->push_back(part);
}
}
void EquationDetect::ExpandSeedVertical(
const bool search_bottom,
ColPartition* seed,
GenericVector<ColPartition*>* parts_to_merge) {
ASSERT_HOST(seed != NULL && parts_to_merge != NULL &&
cps_super_bbox_ != NULL);
const float kXOverlapTh = 0.4;
const int kYGapTh = static_cast<int>(roundf(0.2 * resolution_));
ColPartitionGridSearch search(part_grid_);
const TBOX& seed_box(seed->bounding_box());
int y = search_bottom ? seed_box.bottom() : seed_box.top();
search.StartVerticalSearch(
cps_super_bbox_->left(), cps_super_bbox_->right(), y);
search.SetUniqueMode(true);
// Search iteratively.
ColPartition *part = NULL;
GenericVector<ColPartition*> parts;
int skipped_min_top = INT_MAX, skipped_max_bottom = -1;
while ((part = search.NextVerticalSearch(search_bottom)) != NULL) {
if (part == seed) {
continue;
}
const TBOX& part_box(part->bounding_box());
if (part_box.y_gap(seed_box) > kYGapTh) { // Out of scope.
break;
}
// Check part location.
if ((part_box.bottom() >= seed_box.bottom() && search_bottom) ||
(part_box.top() <= seed_box.top() && !search_bottom)) {
continue;
}
bool skip_part = false;
if (part->type() != PT_EQUATION) { // Non-equation type.
// Skip PT_LINLINE_EQUATION and non text type.
if (part->type() == PT_INLINE_EQUATION ||
(!IsTextOrEquationType(part->type()) &&
part->blob_type() != BRT_HLINE)) {
skip_part = true;
} else if (!IsNearSmallNeighbor(seed_box, part_box) ||
!CheckSeedNeighborDensity(part)) {
// For other types, it should be the near small neighbor of seed.
skip_part = true;
}
} else { // Equation type, check the x overlap.
if (part_box.x_overlap_fraction(seed_box) < kXOverlapTh &&
seed_box.x_overlap_fraction(part_box) < kXOverlapTh) {
skip_part = true;
}
}
if (skip_part) {
if (part->type() != PT_EQUATION) {
if (skipped_min_top > part_box.top()) {
skipped_min_top = part_box.top();
}
if (skipped_max_bottom < part_box.bottom()) {
skipped_max_bottom = part_box.bottom();
}
}
} else {
parts.push_back(part);
}
}
// For every part in parts, we need verify it is not above skipped_min_top
// when search top, or not below skipped_max_bottom when search bottom. I.e.,
// we will skip a part if it looks like:
// search bottom | search top
// seed: ****************** | part: **********
// skipped: xxx | skipped: xxx
// part: ********** | seed: ***********
for (int i = 0; i < parts.size(); i++) {
const TBOX& part_box(parts[i]->bounding_box());
if ((search_bottom && part_box.top() <= skipped_max_bottom) ||
(!search_bottom && part_box.bottom() >= skipped_min_top)) {
continue;
}
// Add parts[i] into parts_to_merge, and delete it from part_grid_.
parts_to_merge->push_back(parts[i]);
part_grid_->RemoveBBox(parts[i]);
}
}
bool EquationDetect::IsNearSmallNeighbor(const TBOX& seed_box,
const TBOX& part_box) const {
const int kXGapTh = static_cast<int>(roundf(0.25 * resolution_));
const int kYGapTh = static_cast<int>(roundf(0.05 * resolution_));
// Check geometric feature.
if (part_box.height() > seed_box.height() ||
part_box.width() > seed_box.width()) {
return false;
}
// Check overlap and distance.
if ((!part_box.major_x_overlap(seed_box) ||
part_box.y_gap(seed_box) > kYGapTh) &&
(!part_box.major_y_overlap(seed_box) ||
part_box.x_gap(seed_box) > kXGapTh)) {
return false;
}
return true;
}
bool EquationDetect::CheckSeedNeighborDensity(const ColPartition* part) const {
ASSERT_HOST(part);
if (part->boxes_count() < kSeedBlobsCountTh) {
// Too few blobs, skip the check.
return true;
}
// We check the math blobs density and the unclear blobs density.
if (part->SpecialBlobsDensity(BSTT_MATH) +
part->SpecialBlobsDensity(BSTT_DIGIT) > kMathDigitDensityTh1 ||
part->SpecialBlobsDensity(BSTT_UNCLEAR) > kUnclearDensityTh) {
return true;
}
return false;
}
void EquationDetect::ProcessMathBlockSatelliteParts() {
// Iterate over part_grid_, and find all parts that are text type but not
// equation type.
ColPartition *part = NULL;
GenericVector<ColPartition*> text_parts;
ColPartitionGridSearch gsearch(part_grid_);
gsearch.StartFullSearch();
while ((part = gsearch.NextFullSearch()) != NULL) {
if (part->type() == PT_FLOWING_TEXT || part->type() == PT_HEADING_TEXT) {
text_parts.push_back(part);
}
}
if (text_parts.empty()) {
return;
}
// Compute the medium height of the text_parts.
text_parts.sort(&SortCPByHeight);
const TBOX& text_box = text_parts[text_parts.size() / 2]->bounding_box();
int med_height = text_box.height();
if (text_parts.size() % 2 == 0 && text_parts.size() > 1) {
const TBOX& text_box =
text_parts[text_parts.size() / 2 - 1]->bounding_box();
med_height = static_cast<int>(roundf(
0.5 * (text_box.height() + med_height)));
}
// Iterate every text_parts and check if it is a math block satellite.
for (int i = 0; i < text_parts.size(); ++i) {
const TBOX& text_box(text_parts[i]->bounding_box());
if (text_box.height() > med_height) {
continue;
}
GenericVector<ColPartition*> math_blocks;
if (!IsMathBlockSatellite(text_parts[i], &math_blocks)) {
continue;
}
// Found. merge text_parts[i] with math_blocks.
part_grid_->RemoveBBox(text_parts[i]);
text_parts[i]->set_type(PT_EQUATION);
for (int j = 0; j < math_blocks.size(); ++j) {
part_grid_->RemoveBBox(math_blocks[j]);
text_parts[i]->Absorb(math_blocks[j], NULL);
}
InsertPartAfterAbsorb(text_parts[i]);
}
}
bool EquationDetect::IsMathBlockSatellite(
ColPartition* part, GenericVector<ColPartition*>* math_blocks) {
ASSERT_HOST(part != NULL && math_blocks != NULL);
math_blocks->clear();
const TBOX& part_box(part->bounding_box());
// Find the top/bottom nearest neighbor of part.
ColPartition *neighbors[2];
int y_gaps[2] = {INT_MAX, INT_MAX};
// The horizontal boundary of the neighbors.
int neighbors_left = INT_MAX, neighbors_right = 0;
for (int i = 0; i < 2; ++i) {
neighbors[i] = SearchNNVertical(i != 0, part);
if (neighbors[i]) {
const TBOX& neighbor_box = neighbors[i]->bounding_box();
y_gaps[i] = neighbor_box.y_gap(part_box);
if (neighbor_box.left() < neighbors_left) {
neighbors_left = neighbor_box.left();
}
if (neighbor_box.right() > neighbors_right) {
neighbors_right = neighbor_box.right();
}
}
}
if (neighbors[0] == neighbors[1]) {
// This happens when part is inside neighbor.
neighbors[1] = NULL;
y_gaps[1] = INT_MAX;
}
// Check if part is within [neighbors_left, neighbors_right].
if (part_box.left() < neighbors_left || part_box.right() > neighbors_right) {
return false;
}
// Get the index of the near one in neighbors.
int index = y_gaps[0] < y_gaps[1] ? 0 : 1;
// Check the near one.
if (IsNearMathNeighbor(y_gaps[index], neighbors[index])) {
math_blocks->push_back(neighbors[index]);
} else {
// If the near one failed the check, then we skip checking the far one.
return false;
}
// Check the far one.
index = 1 - index;
if (IsNearMathNeighbor(y_gaps[index], neighbors[index])) {
math_blocks->push_back(neighbors[index]);
}
return true;
}
ColPartition* EquationDetect::SearchNNVertical(
const bool search_bottom, const ColPartition* part) {
ASSERT_HOST(part);
ColPartition *nearest_neighbor = NULL, *neighbor = NULL;
const int kYGapTh = static_cast<int>(roundf(resolution_ * 0.5));
ColPartitionGridSearch search(part_grid_);
search.SetUniqueMode(true);
const TBOX& part_box(part->bounding_box());
int y = search_bottom ? part_box.bottom() : part_box.top();
search.StartVerticalSearch(part_box.left(), part_box.right(), y);
int min_y_gap = INT_MAX;
while ((neighbor = search.NextVerticalSearch(search_bottom)) != NULL) {
if (neighbor == part || !IsTextOrEquationType(neighbor->type())) {
continue;
}
const TBOX& neighbor_box(neighbor->bounding_box());
int y_gap = neighbor_box.y_gap(part_box);
if (y_gap > kYGapTh) { // Out of scope.
break;
}
if (!neighbor_box.major_x_overlap(part_box) ||
(search_bottom && neighbor_box.bottom() > part_box.bottom()) ||
(!search_bottom && neighbor_box.top() < part_box.top())) {
continue;
}
if (y_gap < min_y_gap) {
min_y_gap = y_gap;
nearest_neighbor = neighbor;
}
}
return nearest_neighbor;
}
bool EquationDetect::IsNearMathNeighbor(
const int y_gap, const ColPartition *neighbor) const {
if (!neighbor) {
return false;
}
const int kYGapTh = static_cast<int>(roundf(resolution_ * 0.1));
return neighbor->type() == PT_EQUATION && y_gap <= kYGapTh;
}
void EquationDetect::GetOutputTiffName(const char* name,
STRING* image_name) const {
ASSERT_HOST(image_name && name);
char page[50];
snprintf(page, sizeof(page), "%04d", page_count_);
*image_name = STRING(lang_tesseract_->imagebasename) + page + name + ".tif";
}
void EquationDetect::PaintSpecialTexts(const STRING& outfile) const {
Pix *pix = NULL, *pixBi = lang_tesseract_->pix_binary();
pix = pixConvertTo32(pixBi);
ColPartitionGridSearch gsearch(part_grid_);
ColPartition* part = NULL;
gsearch.StartFullSearch();
while ((part = gsearch.NextFullSearch()) != NULL) {
BLOBNBOX_C_IT blob_it(part->boxes());
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list(); blob_it.forward()) {
RenderSpecialText(pix, blob_it.data());
}
}
pixWrite(outfile.string(), pix, IFF_TIFF_LZW);
pixDestroy(&pix);
}
void EquationDetect::PaintColParts(const STRING& outfile) const {
Pix *pix = pixConvertTo32(lang_tesseract_->BestPix());
ColPartitionGridSearch gsearch(part_grid_);
gsearch.StartFullSearch();
ColPartition* part = NULL;
while ((part = gsearch.NextFullSearch()) != NULL) {
const TBOX& tbox = part->bounding_box();
Box *box = boxCreate(tbox.left(), pixGetHeight(pix) - tbox.top(),
tbox.width(), tbox.height());
if (part->type() == PT_EQUATION) {
pixRenderBoxArb(pix, box, 5, 255, 0, 0);
} else if (part->type() == PT_INLINE_EQUATION) {
pixRenderBoxArb(pix, box, 5, 0, 255, 0);
} else {
pixRenderBoxArb(pix, box, 5, 0, 0, 255);
}
boxDestroy(&box);
}
pixWrite(outfile.string(), pix, IFF_TIFF_LZW);
pixDestroy(&pix);
}
void EquationDetect::PrintSpecialBlobsDensity(const ColPartition* part) const {
ASSERT_HOST(part);
TBOX box(part->bounding_box());
int h = pixGetHeight(lang_tesseract_->BestPix());
tprintf("Printing special blobs density values for ColParition (t=%d,b=%d) ",
h - box.top(), h - box.bottom());
box.print();
tprintf("blobs count = %d, density = ", part->boxes_count());
for (int i = 0; i < BSTT_COUNT; ++i) {
BlobSpecialTextType type = static_cast<BlobSpecialTextType>(i);
tprintf("%d:%f ", i, part->SpecialBlobsDensity(type));
}
tprintf("\n");
}
}; // namespace tesseract
| C++ |
/**********************************************************************
* File: cube_reco_context.h
* Description: Declaration of the Cube Recognition Context Class
* Author: Ahmad Abdulkader
* Created: 2007
*
* (C) Copyright 2008, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
// The CubeRecoContext class abstracts the Cube OCR Engine. Typically a process
// (or a thread) would create one CubeRecoContext object per language.
// The CubeRecoContext object also provides methods to get and set the
// different attribues of the Cube OCR Engine.
#ifndef CUBE_RECO_CONTEXT_H
#define CUBE_RECO_CONTEXT_H
#include <string>
#include "neural_net.h"
#include "lang_model.h"
#include "classifier_base.h"
#include "feature_base.h"
#include "char_set.h"
#include "word_size_model.h"
#include "char_bigrams.h"
#include "word_unigrams.h"
namespace tesseract {
class Tesseract;
class TessdataManager;
class CubeRecoContext {
public:
// Reading order enum type
enum ReadOrder {
L2R,
R2L
};
// Instantiate using a Tesseract object
CubeRecoContext(Tesseract *tess_obj);
~CubeRecoContext();
// accessor functions
inline const string & Lang() const { return lang_; }
inline CharSet *CharacterSet() const { return char_set_; }
const UNICHARSET *TessUnicharset() const { return tess_unicharset_; }
inline CharClassifier *Classifier() const { return char_classifier_; }
inline WordSizeModel *SizeModel() const { return word_size_model_; }
inline CharBigrams *Bigrams() const { return char_bigrams_; }
inline WordUnigrams *WordUnigramsObj() const { return word_unigrams_; }
inline TuningParams *Params() const { return params_; }
inline LangModel *LangMod() const { return lang_mod_; }
// the reading order of the language
inline ReadOrder ReadingOrder() const {
return ((lang_ == "ara") ? R2L : L2R);
}
// does the language support case
inline bool HasCase() const {
return (lang_ != "ara" && lang_ != "hin");
}
inline bool Cursive() const {
return (lang_ == "ara");
}
inline bool HasItalics() const {
return (lang_ != "ara" && lang_ != "hin");
}
inline bool Contextual() const {
return (lang_ == "ara");
}
// RecoContext runtime flags accessor functions
inline bool SizeNormalization() const { return size_normalization_; }
inline bool NoisyInput() const { return noisy_input_; }
inline bool OOD() const { return lang_mod_->OOD(); }
inline bool Numeric() const { return lang_mod_->Numeric(); }
inline bool WordList() const { return lang_mod_->WordList(); }
inline bool Punc() const { return lang_mod_->Punc(); }
inline bool CaseSensitive() const {
return char_classifier_->CaseSensitive();
}
inline void SetSizeNormalization(bool size_normalization) {
size_normalization_ = size_normalization;
}
inline void SetNoisyInput(bool noisy_input) {
noisy_input_ = noisy_input;
}
inline void SetOOD(bool ood_enabled) {
lang_mod_->SetOOD(ood_enabled);
}
inline void SetNumeric(bool numeric_enabled) {
lang_mod_->SetNumeric(numeric_enabled);
}
inline void SetWordList(bool word_list_enabled) {
lang_mod_->SetWordList(word_list_enabled);
}
inline void SetPunc(bool punc_enabled) {
lang_mod_->SetPunc(punc_enabled);
}
inline void SetCaseSensitive(bool case_sensitive) {
char_classifier_->SetCaseSensitive(case_sensitive);
}
inline tesseract::Tesseract *TesseractObject() const {
return tess_obj_;
}
// Returns the path of the data files
bool GetDataFilePath(string *path) const;
// Creates a CubeRecoContext object using a tesseract object. Data
// files are loaded via the tessdata_manager, and the tesseract
// unicharset is provided in order to map Cube's unicharset to
// Tesseract's in the case where the two unicharsets differ.
static CubeRecoContext *Create(Tesseract *tess_obj,
TessdataManager *tessdata_manager,
UNICHARSET *tess_unicharset);
private:
bool loaded_;
string lang_;
CharSet *char_set_;
UNICHARSET *tess_unicharset_;
WordSizeModel *word_size_model_;
CharClassifier *char_classifier_;
CharBigrams *char_bigrams_;
WordUnigrams *word_unigrams_;
TuningParams *params_;
LangModel *lang_mod_;
Tesseract *tess_obj_; // CubeRecoContext does not own this pointer
bool size_normalization_;
bool noisy_input_;
// Loads and initialized all the necessary components of a
// CubeRecoContext. See .cpp for more details.
bool Load(TessdataManager *tessdata_manager,
UNICHARSET *tess_unicharset);
};
}
#endif // CUBE_RECO_CONTEXT_H
| C++ |
///////////////////////////////////////////////////////////////////////
// File: tesseractclass.cpp
// Description: The Tesseract class. It holds/owns everything needed
// to run Tesseract on a single language, and also a set of
// sub-Tesseracts to run sub-languages. For thread safety, *every*
// variable that was previously global or static (except for
// constant data, and some visual debugging flags) has been moved
// in here, directly, or indirectly.
// This makes it safe to run multiple Tesseracts in different
// threads in parallel, and keeps the different language
// instances separate.
// Some global functions remain, but they are isolated re-entrant
// functions that operate on their arguments. Functions that work
// on variable data have been moved to an appropriate class based
// mostly on the directory hierarchy. For more information see
// slide 6 of "2ArchitectureAndDataStructures" in
// https://drive.google.com/file/d/0B7l10Bj_LprhbUlIUFlCdGtDYkE/edit?usp=sharing
// Some global data and related functions still exist in the
// training-related code, but they don't interfere with normal
// recognition operation.
// Author: Ray Smith
// Created: Fri Mar 07 08:17:01 PST 2008
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "tesseractclass.h"
#include "allheaders.h"
#include "cube_reco_context.h"
#include "edgblob.h"
#include "equationdetect.h"
#include "globals.h"
#include "tesseract_cube_combiner.h"
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
namespace tesseract {
Tesseract::Tesseract()
: BOOL_MEMBER(tessedit_resegment_from_boxes, false,
"Take segmentation and labeling from box file",
this->params()),
BOOL_MEMBER(tessedit_resegment_from_line_boxes, false,
"Conversion of word/line box file to char box file",
this->params()),
BOOL_MEMBER(tessedit_train_from_boxes, false,
"Generate training data from boxed chars", this->params()),
BOOL_MEMBER(tessedit_make_boxes_from_boxes, false,
"Generate more boxes from boxed chars", this->params()),
BOOL_MEMBER(tessedit_dump_pageseg_images, false,
"Dump intermediate images made during page segmentation",
this->params()),
// The default for pageseg_mode is the old behaviour, so as not to
// upset anything that relies on that.
INT_MEMBER(tessedit_pageseg_mode, PSM_SINGLE_BLOCK,
"Page seg mode: 0=osd only, 1=auto+osd, 2=auto, 3=col, 4=block,"
" 5=line, 6=word, 7=char"
" (Values from PageSegMode enum in publictypes.h)",
this->params()),
INT_INIT_MEMBER(tessedit_ocr_engine_mode, tesseract::OEM_TESSERACT_ONLY,
"Which OCR engine(s) to run (Tesseract, Cube, both)."
" Defaults to loading and running only Tesseract"
" (no Cube,no combiner)."
" Values from OcrEngineMode enum in tesseractclass.h)",
this->params()),
STRING_MEMBER(tessedit_char_blacklist, "",
"Blacklist of chars not to recognize", this->params()),
STRING_MEMBER(tessedit_char_whitelist, "",
"Whitelist of chars to recognize", this->params()),
STRING_MEMBER(tessedit_char_unblacklist, "",
"List of chars to override tessedit_char_blacklist",
this->params()),
BOOL_MEMBER(tessedit_ambigs_training, false,
"Perform training for ambiguities", this->params()),
INT_MEMBER(pageseg_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing page-segmentation.", this->params()),
INT_MEMBER(ocr_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing ocr.", this->params()),
STRING_MEMBER(tessedit_write_params_to_file, "",
"Write all parameters to the given file.", this->params()),
BOOL_MEMBER(tessedit_adaption_debug, false, "Generate and print debug"
" information for adaption", this->params()),
INT_MEMBER(bidi_debug, 0, "Debug level for BiDi", this->params()),
INT_MEMBER(applybox_debug, 1, "Debug level", this->params()),
INT_MEMBER(applybox_page, 0,
"Page number to apply boxes from", this->params()),
STRING_MEMBER(applybox_exposure_pattern, ".exp", "Exposure value follows"
" this pattern in the image filename. The name of the image"
" files are expected to be in the form"
" [lang].[fontname].exp[num].tif", this->params()),
BOOL_MEMBER(applybox_learn_chars_and_char_frags_mode, false,
"Learn both character fragments (as is done in the"
" special low exposure mode) as well as unfragmented"
" characters.", this->params()),
BOOL_MEMBER(applybox_learn_ngrams_mode, false, "Each bounding box"
" is assumed to contain ngrams. Only learn the ngrams"
" whose outlines overlap horizontally.", this->params()),
BOOL_MEMBER(tessedit_display_outwords, false,
"Draw output words", this->params()),
BOOL_MEMBER(tessedit_dump_choices, false,
"Dump char choices", this->params()),
BOOL_MEMBER(tessedit_timing_debug, false, "Print timing stats",
this->params()),
BOOL_MEMBER(tessedit_fix_fuzzy_spaces, true,
"Try to improve fuzzy spaces", this->params()),
BOOL_MEMBER(tessedit_unrej_any_wd, false,
"Dont bother with word plausibility", this->params()),
BOOL_MEMBER(tessedit_fix_hyphens, true,
"Crunch double hyphens?", this->params()),
BOOL_MEMBER(tessedit_redo_xheight, true,
"Check/Correct x-height", this->params()),
BOOL_MEMBER(tessedit_enable_doc_dict, true,
"Add words to the document dictionary", this->params()),
BOOL_MEMBER(tessedit_debug_fonts, false,
"Output font info per char", this->params()),
BOOL_MEMBER(tessedit_debug_block_rejection, false,
"Block and Row stats", this->params()),
BOOL_MEMBER(tessedit_enable_bigram_correction, true,
"Enable correction based on the word bigram dictionary.",
this->params()),
BOOL_MEMBER(tessedit_enable_dict_correction, false,
"Enable single word correction based on the dictionary.",
this->params()),
INT_MEMBER(tessedit_bigram_debug, 0,
"Amount of debug output for bigram correction.",
this->params()),
INT_MEMBER(debug_x_ht_level, 0, "Reestimate debug", this->params()),
BOOL_MEMBER(debug_acceptable_wds, false,
"Dump word pass/fail chk", this->params()),
STRING_MEMBER(chs_leading_punct, "('`\"",
"Leading punctuation", this->params()),
STRING_MEMBER(chs_trailing_punct1, ").,;:?!",
"1st Trailing punctuation", this->params()),
STRING_MEMBER(chs_trailing_punct2, ")'`\"",
"2nd Trailing punctuation", this->params()),
double_MEMBER(quality_rej_pc, 0.08,
"good_quality_doc lte rejection limit", this->params()),
double_MEMBER(quality_blob_pc, 0.0,
"good_quality_doc gte good blobs limit", this->params()),
double_MEMBER(quality_outline_pc, 1.0,
"good_quality_doc lte outline error limit", this->params()),
double_MEMBER(quality_char_pc, 0.95,
"good_quality_doc gte good char limit", this->params()),
INT_MEMBER(quality_min_initial_alphas_reqd, 2,
"alphas in a good word", this->params()),
INT_MEMBER(tessedit_tess_adaption_mode, 0x27,
"Adaptation decision algorithm for tess", this->params()),
BOOL_MEMBER(tessedit_minimal_rej_pass1, false,
"Do minimal rejection on pass 1 output", this->params()),
BOOL_MEMBER(tessedit_test_adaption, false,
"Test adaption criteria", this->params()),
BOOL_MEMBER(tessedit_matcher_log, false,
"Log matcher activity", this->params()),
INT_MEMBER(tessedit_test_adaption_mode, 3,
"Adaptation decision algorithm for tess", this->params()),
BOOL_MEMBER(test_pt, false, "Test for point", this->params()),
double_MEMBER(test_pt_x, 99999.99, "xcoord", this->params()),
double_MEMBER(test_pt_y, 99999.99, "ycoord", this->params()),
INT_MEMBER(paragraph_debug_level, 0, "Print paragraph debug info.",
this->params()),
BOOL_MEMBER(paragraph_text_based, true,
"Run paragraph detection on the post-text-recognition "
"(more accurate)", this->params()),
INT_MEMBER(cube_debug_level, 0, "Print cube debug info.", this->params()),
STRING_MEMBER(outlines_odd, "%| ", "Non standard number of outlines",
this->params()),
STRING_MEMBER(outlines_2, "ij!?%\":;",
"Non standard number of outlines", this->params()),
BOOL_MEMBER(docqual_excuse_outline_errs, false,
"Allow outline errs in unrejection?", this->params()),
BOOL_MEMBER(tessedit_good_quality_unrej, true,
"Reduce rejection on good docs", this->params()),
BOOL_MEMBER(tessedit_use_reject_spaces, true,
"Reject spaces?", this->params()),
double_MEMBER(tessedit_reject_doc_percent, 65.00,
"%rej allowed before rej whole doc", this->params()),
double_MEMBER(tessedit_reject_block_percent, 45.00,
"%rej allowed before rej whole block", this->params()),
double_MEMBER(tessedit_reject_row_percent, 40.00,
"%rej allowed before rej whole row", this->params()),
double_MEMBER(tessedit_whole_wd_rej_row_percent, 70.00,
"Number of row rejects in whole word rejects"
"which prevents whole row rejection", this->params()),
BOOL_MEMBER(tessedit_preserve_blk_rej_perfect_wds, true,
"Only rej partially rejected words in block rejection",
this->params()),
BOOL_MEMBER(tessedit_preserve_row_rej_perfect_wds, true,
"Only rej partially rejected words in row rejection",
this->params()),
BOOL_MEMBER(tessedit_dont_blkrej_good_wds, false,
"Use word segmentation quality metric", this->params()),
BOOL_MEMBER(tessedit_dont_rowrej_good_wds, false,
"Use word segmentation quality metric", this->params()),
INT_MEMBER(tessedit_preserve_min_wd_len, 2,
"Only preserve wds longer than this", this->params()),
BOOL_MEMBER(tessedit_row_rej_good_docs, true,
"Apply row rejection to good docs", this->params()),
double_MEMBER(tessedit_good_doc_still_rowrej_wd, 1.1,
"rej good doc wd if more than this fraction rejected",
this->params()),
BOOL_MEMBER(tessedit_reject_bad_qual_wds, true,
"Reject all bad quality wds", this->params()),
BOOL_MEMBER(tessedit_debug_doc_rejection, false,
"Page stats", this->params()),
BOOL_MEMBER(tessedit_debug_quality_metrics, false,
"Output data to debug file", this->params()),
BOOL_MEMBER(bland_unrej, false,
"unrej potential with no chekcs", this->params()),
double_MEMBER(quality_rowrej_pc, 1.1,
"good_quality_doc gte good char limit", this->params()),
BOOL_MEMBER(unlv_tilde_crunching, true,
"Mark v.bad words for tilde crunch", this->params()),
BOOL_MEMBER(hocr_font_info, false,
"Add font info to hocr output", this->params()),
BOOL_MEMBER(crunch_early_merge_tess_fails, true,
"Before word crunch?", this->params()),
BOOL_MEMBER(crunch_early_convert_bad_unlv_chs, false,
"Take out ~^ early?", this->params()),
double_MEMBER(crunch_terrible_rating, 80.0,
"crunch rating lt this", this->params()),
BOOL_MEMBER(crunch_terrible_garbage, true, "As it says", this->params()),
double_MEMBER(crunch_poor_garbage_cert, -9.0,
"crunch garbage cert lt this", this->params()),
double_MEMBER(crunch_poor_garbage_rate, 60,
"crunch garbage rating lt this", this->params()),
double_MEMBER(crunch_pot_poor_rate, 40,
"POTENTIAL crunch rating lt this", this->params()),
double_MEMBER(crunch_pot_poor_cert, -8.0,
"POTENTIAL crunch cert lt this", this->params()),
BOOL_MEMBER(crunch_pot_garbage, true,
"POTENTIAL crunch garbage", this->params()),
double_MEMBER(crunch_del_rating, 60,
"POTENTIAL crunch rating lt this", this->params()),
double_MEMBER(crunch_del_cert, -10.0,
"POTENTIAL crunch cert lt this", this->params()),
double_MEMBER(crunch_del_min_ht, 0.7,
"Del if word ht lt xht x this", this->params()),
double_MEMBER(crunch_del_max_ht, 3.0,
"Del if word ht gt xht x this", this->params()),
double_MEMBER(crunch_del_min_width, 3.0,
"Del if word width lt xht x this", this->params()),
double_MEMBER(crunch_del_high_word, 1.5,
"Del if word gt xht x this above bl", this->params()),
double_MEMBER(crunch_del_low_word, 0.5,
"Del if word gt xht x this below bl", this->params()),
double_MEMBER(crunch_small_outlines_size, 0.6,
"Small if lt xht x this", this->params()),
INT_MEMBER(crunch_rating_max, 10,
"For adj length in rating per ch", this->params()),
INT_MEMBER(crunch_pot_indicators, 1,
"How many potential indicators needed", this->params()),
BOOL_MEMBER(crunch_leave_ok_strings, true,
"Dont touch sensible strings", this->params()),
BOOL_MEMBER(crunch_accept_ok, true,
"Use acceptability in okstring", this->params()),
BOOL_MEMBER(crunch_leave_accept_strings, false,
"Dont pot crunch sensible strings", this->params()),
BOOL_MEMBER(crunch_include_numerals, false,
"Fiddle alpha figures", this->params()),
INT_MEMBER(crunch_leave_lc_strings, 4,
"Dont crunch words with long lower case strings",
this->params()),
INT_MEMBER(crunch_leave_uc_strings, 4,
"Dont crunch words with long lower case strings",
this->params()),
INT_MEMBER(crunch_long_repetitions, 3,
"Crunch words with long repetitions", this->params()),
INT_MEMBER(crunch_debug, 0, "As it says", this->params()),
INT_MEMBER(fixsp_non_noise_limit, 1,
"How many non-noise blbs either side?", this->params()),
double_MEMBER(fixsp_small_outlines_size, 0.28,
"Small if lt xht x this", this->params()),
BOOL_MEMBER(tessedit_prefer_joined_punct, false,
"Reward punctation joins", this->params()),
INT_MEMBER(fixsp_done_mode, 1,
"What constitues done for spacing", this->params()),
INT_MEMBER(debug_fix_space_level, 0,
"Contextual fixspace debug", this->params()),
STRING_MEMBER(numeric_punctuation, ".,",
"Punct. chs expected WITHIN numbers", this->params()),
INT_MEMBER(x_ht_acceptance_tolerance, 8,
"Max allowed deviation of blob top outside of font data",
this->params()),
INT_MEMBER(x_ht_min_change, 8,
"Min change in xht before actually trying it", this->params()),
INT_MEMBER(superscript_debug, 0, "Debug level for sub & superscript fixer",
this->params()),
double_MEMBER(superscript_worse_certainty, 2.0, "How many times worse "
"certainty does a superscript position glyph need to be for "
"us to try classifying it as a char with a different "
"baseline?", this->params()),
double_MEMBER(superscript_bettered_certainty, 0.97, "What reduction in "
"badness do we think sufficient to choose a superscript "
"over what we'd thought. For example, a value of 0.6 means "
"we want to reduce badness of certainty by at least 40%",
this->params()),
double_MEMBER(superscript_scaledown_ratio, 0.4,
"A superscript scaled down more than this is unbelievably "
"small. For example, 0.3 means we expect the font size to "
"be no smaller than 30% of the text line font size.",
this->params()),
double_MEMBER(subscript_max_y_top, 0.5,
"Maximum top of a character measured as a multiple of "
"x-height above the baseline for us to reconsider whether "
"it's a subscript.", this->params()),
double_MEMBER(superscript_min_y_bottom, 0.3,
"Minimum bottom of a character measured as a multiple of "
"x-height above the baseline for us to reconsider whether "
"it's a superscript.", this->params()),
BOOL_MEMBER(tessedit_write_block_separators, false,
"Write block separators in output", this->params()),
BOOL_MEMBER(tessedit_write_rep_codes, false,
"Write repetition char code", this->params()),
BOOL_MEMBER(tessedit_write_unlv, false,
"Write .unlv output file", this->params()),
BOOL_MEMBER(tessedit_create_txt, true,
"Write .txt output file", this->params()),
BOOL_MEMBER(tessedit_create_hocr, false,
"Write .html hOCR output file", this->params()),
BOOL_MEMBER(tessedit_create_pdf, false,
"Write .pdf output file", this->params()),
STRING_MEMBER(unrecognised_char, "|",
"Output char for unidentified blobs", this->params()),
INT_MEMBER(suspect_level, 99, "Suspect marker level", this->params()),
INT_MEMBER(suspect_space_level, 100,
"Min suspect level for rejecting spaces", this->params()),
INT_MEMBER(suspect_short_words, 2,
"Dont Suspect dict wds longer than this", this->params()),
BOOL_MEMBER(suspect_constrain_1Il, false,
"UNLV keep 1Il chars rejected", this->params()),
double_MEMBER(suspect_rating_per_ch, 999.9,
"Dont touch bad rating limit", this->params()),
double_MEMBER(suspect_accept_rating, -999.9,
"Accept good rating limit", this->params()),
BOOL_MEMBER(tessedit_minimal_rejection, false,
"Only reject tess failures", this->params()),
BOOL_MEMBER(tessedit_zero_rejection, false,
"Dont reject ANYTHING", this->params()),
BOOL_MEMBER(tessedit_word_for_word, false,
"Make output have exactly one word per WERD", this->params()),
BOOL_MEMBER(tessedit_zero_kelvin_rejection, false,
"Dont reject ANYTHING AT ALL", this->params()),
BOOL_MEMBER(tessedit_consistent_reps, true,
"Force all rep chars the same", this->params()),
INT_MEMBER(tessedit_reject_mode, 0, "Rejection algorithm", this->params()),
BOOL_MEMBER(tessedit_rejection_debug, false,
"Adaption debug", this->params()),
BOOL_MEMBER(tessedit_flip_0O, true,
"Contextual 0O O0 flips", this->params()),
double_MEMBER(tessedit_lower_flip_hyphen, 1.5,
"Aspect ratio dot/hyphen test", this->params()),
double_MEMBER(tessedit_upper_flip_hyphen, 1.8,
"Aspect ratio dot/hyphen test", this->params()),
BOOL_MEMBER(rej_trust_doc_dawg, false,
"Use DOC dawg in 11l conf. detector", this->params()),
BOOL_MEMBER(rej_1Il_use_dict_word, false,
"Use dictword test", this->params()),
BOOL_MEMBER(rej_1Il_trust_permuter_type, true,
"Dont double check", this->params()),
BOOL_MEMBER(rej_use_tess_accepted, true,
"Individual rejection control", this->params()),
BOOL_MEMBER(rej_use_tess_blanks, true,
"Individual rejection control", this->params()),
BOOL_MEMBER(rej_use_good_perm, true,
"Individual rejection control", this->params()),
BOOL_MEMBER(rej_use_sensible_wd, false,
"Extend permuter check", this->params()),
BOOL_MEMBER(rej_alphas_in_number_perm, false,
"Extend permuter check", this->params()),
double_MEMBER(rej_whole_of_mostly_reject_word_fract, 0.85,
"if >this fract", this->params()),
INT_MEMBER(tessedit_image_border, 2,
"Rej blbs near image edge limit", this->params()),
STRING_MEMBER(ok_repeated_ch_non_alphanum_wds, "-?*\075",
"Allow NN to unrej", this->params()),
STRING_MEMBER(conflict_set_I_l_1, "Il1[]",
"Il1 conflict set", this->params()),
INT_MEMBER(min_sane_x_ht_pixels, 8,
"Reject any x-ht lt or eq than this", this->params()),
BOOL_MEMBER(tessedit_create_boxfile, false,
"Output text with boxes", this->params()),
INT_MEMBER(tessedit_page_number, -1, "-1 -> All pages"
" , else specifc page to process", this->params()),
BOOL_MEMBER(tessedit_write_images, false,
"Capture the image from the IPE", this->params()),
BOOL_MEMBER(interactive_display_mode, false, "Run interactively?",
this->params()),
STRING_MEMBER(file_type, ".tif", "Filename extension", this->params()),
BOOL_MEMBER(tessedit_override_permuter, true,
"According to dict_word", this->params()),
INT_MEMBER(tessdata_manager_debug_level, 0, "Debug level for"
" TessdataManager functions.", this->params()),
STRING_MEMBER(tessedit_load_sublangs, "",
"List of languages to load with this one", this->params()),
BOOL_MEMBER(tessedit_use_primary_params_model, false,
"In multilingual mode use params model of the"
" primary language", this->params()),
double_MEMBER(min_orientation_margin, 7.0,
"Min acceptable orientation margin", this->params()),
BOOL_MEMBER(textord_tabfind_show_vlines, false, "Debug line finding",
this->params()),
BOOL_MEMBER(textord_use_cjk_fp_model, FALSE, "Use CJK fixed pitch model",
this->params()),
BOOL_MEMBER(poly_allow_detailed_fx, false,
"Allow feature extractors to see the original outline",
this->params()),
BOOL_INIT_MEMBER(tessedit_init_config_only, false,
"Only initialize with the config file. Useful if the "
"instance is not going to be used for OCR but say only "
"for layout analysis.", this->params()),
BOOL_MEMBER(textord_equation_detect, false, "Turn on equation detector",
this->params()),
BOOL_MEMBER(textord_tabfind_vertical_text, true,
"Enable vertical detection", this->params()),
BOOL_MEMBER(textord_tabfind_force_vertical_text, false,
"Force using vertical text page mode", this->params()),
double_MEMBER(textord_tabfind_vertical_text_ratio, 0.5,
"Fraction of textlines deemed vertical to use vertical page "
"mode", this->params()),
double_MEMBER(textord_tabfind_aligned_gap_fraction, 0.75,
"Fraction of height used as a minimum gap for aligned blobs.",
this->params()),
INT_MEMBER(tessedit_parallelize, 0, "Run in parallel where possible",
this->params()),
BOOL_MEMBER(preserve_interword_spaces, false,
"Preserve multiple interword spaces", this->params()),
BOOL_MEMBER(include_page_breaks, FALSE,
"Include page separator string in output text after each "
"image/page.", this->params()),
STRING_MEMBER(page_separator, "\f",
"Page separator (default is form feed control character)",
this->params()),
// The following parameters were deprecated and removed from their original
// locations. The parameters are temporarily kept here to give Tesseract
// users a chance to updated their [lang].traineddata and config files
// without introducing failures during Tesseract initialization.
// TODO(ocr-team): remove these parameters from the code once we are
// reasonably sure that Tesseract users have updated their data files.
//
// BEGIN DEPRECATED PARAMETERS
BOOL_MEMBER(textord_tabfind_vertical_horizontal_mix, true,
"find horizontal lines such as headers in vertical page mode",
this->params()),
INT_MEMBER(tessedit_ok_mode, 5,
"Acceptance decision algorithm", this->params()),
BOOL_INIT_MEMBER(load_fixed_length_dawgs, true, "Load fixed length dawgs"
" (e.g. for non-space delimited languages)",
this->params()),
INT_MEMBER(segment_debug, 0, "Debug the whole segmentation process",
this->params()),
BOOL_MEMBER(permute_debug, 0, "Debug char permutation process",
this->params()),
double_MEMBER(bestrate_pruning_factor, 2.0, "Multiplying factor of"
" current best rate to prune other hypotheses",
this->params()),
BOOL_MEMBER(permute_script_word, 0,
"Turn on word script consistency permuter",
this->params()),
BOOL_MEMBER(segment_segcost_rating, 0,
"incorporate segmentation cost in word rating?",
this->params()),
double_MEMBER(segment_reward_script, 0.95,
"Score multipler for script consistency within a word. "
"Being a 'reward' factor, it should be <= 1. "
"Smaller value implies bigger reward.",
this->params()),
BOOL_MEMBER(permute_fixed_length_dawg, 0,
"Turn on fixed-length phrasebook search permuter",
this->params()),
BOOL_MEMBER(permute_chartype_word, 0,
"Turn on character type (property) consistency permuter",
this->params()),
double_MEMBER(segment_reward_chartype, 0.97,
"Score multipler for char type consistency within a word. ",
this->params()),
double_MEMBER(segment_reward_ngram_best_choice, 0.99,
"Score multipler for ngram permuter's best choice"
" (only used in the Han script path).",
this->params()),
BOOL_MEMBER(ngram_permuter_activated, false,
"Activate character-level n-gram-based permuter",
this->params()),
BOOL_MEMBER(permute_only_top, false, "Run only the top choice permuter",
this->params()),
INT_MEMBER(language_model_fixed_length_choices_depth, 3,
"Depth of blob choice lists to explore"
" when fixed length dawgs are on",
this->params()),
BOOL_MEMBER(use_new_state_cost, FALSE,
"use new state cost heuristics for segmentation state"
" evaluation", this->params()),
double_MEMBER(heuristic_segcost_rating_base, 1.25,
"base factor for adding segmentation cost into word rating."
"It's a multiplying factor, the larger the value above 1, "
"the bigger the effect of segmentation cost.",
this->params()),
double_MEMBER(heuristic_weight_rating, 1.0,
"weight associated with char rating in combined cost of"
"state", this->params()),
double_MEMBER(heuristic_weight_width, 1000.0,
"weight associated with width evidence in combined cost of"
" state", this->params()),
double_MEMBER(heuristic_weight_seamcut, 0.0,
"weight associated with seam cut in combined cost of state",
this->params()),
double_MEMBER(heuristic_max_char_wh_ratio, 2.0,
"max char width-to-height ratio allowed in segmentation",
this->params()),
BOOL_MEMBER(enable_new_segsearch, true,
"Enable new segmentation search path.", this->params()),
double_MEMBER(segsearch_max_fixed_pitch_char_wh_ratio, 2.0,
"Maximum character width-to-height ratio for"
" fixed-pitch fonts",
this->params()),
// END DEPRECATED PARAMETERS
backup_config_file_(NULL),
pix_binary_(NULL),
cube_binary_(NULL),
pix_grey_(NULL),
pix_thresholds_(NULL),
source_resolution_(0),
textord_(this),
right_to_left_(false),
scaled_color_(NULL),
scaled_factor_(-1),
deskew_(1.0f, 0.0f),
reskew_(1.0f, 0.0f),
most_recently_used_(this),
font_table_size_(0),
cube_cntxt_(NULL),
tess_cube_combiner_(NULL),
equ_detect_(NULL) {
}
Tesseract::~Tesseract() {
Clear();
end_tesseract();
sub_langs_.delete_data_pointers();
// Delete cube objects.
if (cube_cntxt_ != NULL) {
delete cube_cntxt_;
cube_cntxt_ = NULL;
}
if (tess_cube_combiner_ != NULL) {
delete tess_cube_combiner_;
tess_cube_combiner_ = NULL;
}
}
void Tesseract::Clear() {
pixDestroy(&pix_binary_);
pixDestroy(&cube_binary_);
pixDestroy(&pix_grey_);
pixDestroy(&pix_thresholds_);
pixDestroy(&scaled_color_);
deskew_ = FCOORD(1.0f, 0.0f);
reskew_ = FCOORD(1.0f, 0.0f);
splitter_.Clear();
scaled_factor_ = -1;
for (int i = 0; i < sub_langs_.size(); ++i)
sub_langs_[i]->Clear();
}
void Tesseract::SetEquationDetect(EquationDetect* detector) {
equ_detect_ = detector;
equ_detect_->SetLangTesseract(this);
}
// Clear all memory of adaption for this and all subclassifiers.
void Tesseract::ResetAdaptiveClassifier() {
ResetAdaptiveClassifierInternal();
for (int i = 0; i < sub_langs_.size(); ++i) {
sub_langs_[i]->ResetAdaptiveClassifierInternal();
}
}
// Clear the document dictionary for this and all subclassifiers.
void Tesseract::ResetDocumentDictionary() {
getDict().ResetDocumentDictionary();
for (int i = 0; i < sub_langs_.size(); ++i) {
sub_langs_[i]->getDict().ResetDocumentDictionary();
}
}
void Tesseract::SetBlackAndWhitelist() {
// Set the white and blacklists (if any)
unicharset.set_black_and_whitelist(tessedit_char_blacklist.string(),
tessedit_char_whitelist.string(),
tessedit_char_unblacklist.string());
// Black and white lists should apply to all loaded classifiers.
for (int i = 0; i < sub_langs_.size(); ++i) {
sub_langs_[i]->unicharset.set_black_and_whitelist(
tessedit_char_blacklist.string(), tessedit_char_whitelist.string(),
tessedit_char_unblacklist.string());
}
}
// Perform steps to prepare underlying binary image/other data structures for
// page segmentation.
void Tesseract::PrepareForPageseg() {
textord_.set_use_cjk_fp_model(textord_use_cjk_fp_model);
pixDestroy(&cube_binary_);
cube_binary_ = pixClone(pix_binary());
// Find the max splitter strategy over all langs.
ShiroRekhaSplitter::SplitStrategy max_pageseg_strategy =
static_cast<ShiroRekhaSplitter::SplitStrategy>(
static_cast<inT32>(pageseg_devanagari_split_strategy));
for (int i = 0; i < sub_langs_.size(); ++i) {
ShiroRekhaSplitter::SplitStrategy pageseg_strategy =
static_cast<ShiroRekhaSplitter::SplitStrategy>(
static_cast<inT32>(sub_langs_[i]->pageseg_devanagari_split_strategy));
if (pageseg_strategy > max_pageseg_strategy)
max_pageseg_strategy = pageseg_strategy;
// Clone the cube image to all the sub langs too.
pixDestroy(&sub_langs_[i]->cube_binary_);
sub_langs_[i]->cube_binary_ = pixClone(pix_binary());
pixDestroy(&sub_langs_[i]->pix_binary_);
sub_langs_[i]->pix_binary_ = pixClone(pix_binary());
}
// Perform shiro-rekha (top-line) splitting and replace the current image by
// the newly splitted image.
splitter_.set_orig_pix(pix_binary());
splitter_.set_pageseg_split_strategy(max_pageseg_strategy);
if (splitter_.Split(true)) {
ASSERT_HOST(splitter_.splitted_image());
pixDestroy(&pix_binary_);
pix_binary_ = pixClone(splitter_.splitted_image());
}
}
// Perform steps to prepare underlying binary image/other data structures for
// OCR. The current segmentation is required by this method.
// Note that this method resets pix_binary_ to the original binarized image,
// which may be different from the image actually used for OCR depending on the
// value of devanagari_ocr_split_strategy.
void Tesseract::PrepareForTessOCR(BLOCK_LIST* block_list,
Tesseract* osd_tess, OSResults* osr) {
// Find the max splitter strategy over all langs.
ShiroRekhaSplitter::SplitStrategy max_ocr_strategy =
static_cast<ShiroRekhaSplitter::SplitStrategy>(
static_cast<inT32>(ocr_devanagari_split_strategy));
for (int i = 0; i < sub_langs_.size(); ++i) {
ShiroRekhaSplitter::SplitStrategy ocr_strategy =
static_cast<ShiroRekhaSplitter::SplitStrategy>(
static_cast<inT32>(sub_langs_[i]->ocr_devanagari_split_strategy));
if (ocr_strategy > max_ocr_strategy)
max_ocr_strategy = ocr_strategy;
}
// Utilize the segmentation information available.
splitter_.set_segmentation_block_list(block_list);
splitter_.set_ocr_split_strategy(max_ocr_strategy);
// Run the splitter for OCR
bool split_for_ocr = splitter_.Split(false);
// Restore pix_binary to the binarized original pix for future reference.
ASSERT_HOST(splitter_.orig_pix());
pixDestroy(&pix_binary_);
pix_binary_ = pixClone(splitter_.orig_pix());
// If the pageseg and ocr strategies are different, refresh the block list
// (from the last SegmentImage call) with blobs from the real image to be used
// for OCR.
if (splitter_.HasDifferentSplitStrategies()) {
BLOCK block("", TRUE, 0, 0, 0, 0, pixGetWidth(pix_binary_),
pixGetHeight(pix_binary_));
Pix* pix_for_ocr = split_for_ocr ? splitter_.splitted_image() :
splitter_.orig_pix();
extract_edges(pix_for_ocr, &block);
splitter_.RefreshSegmentationWithNewBlobs(block.blob_list());
}
// The splitter isn't needed any more after this, so save memory by clearing.
splitter_.Clear();
}
} // namespace tesseract
| C++ |
/******************************************************************
* File: cube_control.cpp
* Description: Tesseract class methods for invoking cube convolutional
* neural network word recognizer.
* Author: Raquel Romano
* Created: September 2009
*
**********************************************************************/
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "allheaders.h"
#include "cube_object.h"
#include "cube_reco_context.h"
#include "tesseractclass.h"
#include "tesseract_cube_combiner.h"
namespace tesseract {
/**********************************************************************
* convert_prob_to_tess_certainty
*
* Normalize a probability in the range [0.0, 1.0] to a tesseract
* certainty in the range [-20.0, 0.0]
**********************************************************************/
static float convert_prob_to_tess_certainty(float prob) {
return (prob - 1.0) * 20.0;
}
/**********************************************************************
* char_box_to_tbox
*
* Create a TBOX from a character bounding box. If nonzero, the
* x_offset accounts for any additional padding of the word box that
* should be taken into account.
*
**********************************************************************/
TBOX char_box_to_tbox(Box* char_box, TBOX word_box, int x_offset) {
l_int32 left;
l_int32 top;
l_int32 width;
l_int32 height;
l_int32 right;
l_int32 bottom;
boxGetGeometry(char_box, &left, &top, &width, &height);
left += word_box.left() - x_offset;
right = left + width;
top = word_box.bottom() + word_box.height() - top;
bottom = top - height;
return TBOX(left, bottom, right, top);
}
/**********************************************************************
* extract_cube_state
*
* Extract CharSamp objects and character bounding boxes from the
* CubeObject's state. The caller should free both structres.
*
**********************************************************************/
bool Tesseract::extract_cube_state(CubeObject* cube_obj,
int* num_chars,
Boxa** char_boxes,
CharSamp*** char_samples) {
if (!cube_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (extract_cube_state): Invalid cube object "
"passed to extract_cube_state\n");
}
return false;
}
// Note that the CubeObject accessors return either the deslanted or
// regular objects search object or beam search object, whichever
// was used in the last call to Recognize()
CubeSearchObject* cube_search_obj = cube_obj->SrchObj();
if (!cube_search_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Extract_cube_state): Could not retrieve "
"cube's search object in extract_cube_state.\n");
}
return false;
}
BeamSearch *beam_search_obj = cube_obj->BeamObj();
if (!beam_search_obj) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Extract_cube_state): Could not retrieve "
"cube's beam search object in extract_cube_state.\n");
}
return false;
}
// Get the character samples and bounding boxes by backtracking
// through the beam search path
int best_node_index = beam_search_obj->BestPresortedNodeIndex();
*char_samples = beam_search_obj->BackTrack(
cube_search_obj, best_node_index, num_chars, NULL, char_boxes);
if (!*char_samples)
return false;
return true;
}
/**********************************************************************
* create_cube_box_word
*
* Fill the given BoxWord with boxes from character bounding
* boxes. The char_boxes have local coordinates w.r.t. the
* word bounding box, i.e., the left-most character bbox of each word
* has (0,0) left-top coord, but the BoxWord must be defined in page
* coordinates.
**********************************************************************/
bool Tesseract::create_cube_box_word(Boxa *char_boxes,
int num_chars,
TBOX word_box,
BoxWord* box_word) {
if (!box_word) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (create_cube_box_word): Invalid box_word.\n");
}
return false;
}
// Find the x-coordinate of left-most char_box, which could be
// nonzero if the word image was padded before recognition took place.
int x_offset = -1;
for (int i = 0; i < num_chars; ++i) {
Box* char_box = boxaGetBox(char_boxes, i, L_CLONE);
if (x_offset < 0 || char_box->x < x_offset) {
x_offset = char_box->x;
}
boxDestroy(&char_box);
}
for (int i = 0; i < num_chars; ++i) {
Box* char_box = boxaGetBox(char_boxes, i, L_CLONE);
TBOX tbox = char_box_to_tbox(char_box, word_box, x_offset);
boxDestroy(&char_box);
box_word->InsertBox(i, tbox);
}
return true;
}
/**********************************************************************
* init_cube_objects
*
* Instantiates Tesseract object's CubeRecoContext and TesseractCubeCombiner.
* Returns false if cube context could not be created or if load_combiner is
* true, but the combiner could not be loaded.
**********************************************************************/
bool Tesseract::init_cube_objects(bool load_combiner,
TessdataManager *tessdata_manager) {
ASSERT_HOST(cube_cntxt_ == NULL);
ASSERT_HOST(tess_cube_combiner_ == NULL);
// Create the cube context object
cube_cntxt_ = CubeRecoContext::Create(this, tessdata_manager, &unicharset);
if (cube_cntxt_ == NULL) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::init_cube_objects()): Failed to "
"instantiate CubeRecoContext\n");
}
return false;
}
// Create the combiner object and load the combiner net for target languages.
if (load_combiner) {
tess_cube_combiner_ = new tesseract::TesseractCubeCombiner(cube_cntxt_);
if (!tess_cube_combiner_ || !tess_cube_combiner_->LoadCombinerNet()) {
delete cube_cntxt_;
cube_cntxt_ = NULL;
if (tess_cube_combiner_ != NULL) {
delete tess_cube_combiner_;
tess_cube_combiner_ = NULL;
}
if (cube_debug_level > 0)
tprintf("Cube ERROR (Failed to instantiate TesseractCubeCombiner\n");
return false;
}
}
return true;
}
/**********************************************************************
* run_cube_combiner
*
* Iterates through tesseract's results and calls cube on each word,
* combining the results with the existing tesseract result.
**********************************************************************/
void Tesseract::run_cube_combiner(PAGE_RES *page_res) {
if (page_res == NULL || tess_cube_combiner_ == NULL)
return;
PAGE_RES_IT page_res_it(page_res);
// Iterate through the word results and call cube on each word.
for (page_res_it.restart_page(); page_res_it.word () != NULL;
page_res_it.forward()) {
BLOCK* block = page_res_it.block()->block;
if (block->poly_block() != NULL && !block->poly_block()->IsText())
continue; // Don't deal with non-text blocks.
WERD_RES* word = page_res_it.word();
// Skip cube entirely if tesseract's certainty is greater than threshold.
int combiner_run_thresh = convert_prob_to_tess_certainty(
cube_cntxt_->Params()->CombinerRunThresh());
if (word->best_choice->certainty() >= combiner_run_thresh) {
continue;
}
// Use the same language as Tesseract used for the word.
Tesseract* lang_tess = word->tesseract;
// Setup a trial WERD_RES in which to classify with cube.
WERD_RES cube_word;
cube_word.InitForRetryRecognition(*word);
cube_word.SetupForRecognition(lang_tess->unicharset, this, BestPix(),
OEM_CUBE_ONLY,
NULL, false, false, false,
page_res_it.row()->row,
page_res_it.block()->block);
CubeObject *cube_obj = lang_tess->cube_recognize_word(
page_res_it.block()->block, &cube_word);
if (cube_obj != NULL)
lang_tess->cube_combine_word(cube_obj, &cube_word, word);
delete cube_obj;
}
}
/**********************************************************************
* cube_word_pass1
*
* Recognizes a single word using (only) cube. Compatible with
* Tesseract's classify_word_pass1/classify_word_pass2.
**********************************************************************/
void Tesseract::cube_word_pass1(BLOCK* block, ROW *row, WERD_RES *word) {
CubeObject *cube_obj = cube_recognize_word(block, word);
delete cube_obj;
}
/**********************************************************************
* cube_recognize_word
*
* Cube recognizer to recognize a single word as with classify_word_pass1
* but also returns the cube object in case the combiner is needed.
**********************************************************************/
CubeObject* Tesseract::cube_recognize_word(BLOCK* block, WERD_RES* word) {
if (!cube_binary_ || !cube_cntxt_) {
if (cube_debug_level > 0 && !cube_binary_)
tprintf("Tesseract::run_cube(): NULL binary image.\n");
word->SetupFake(unicharset);
return NULL;
}
TBOX word_box = word->word->bounding_box();
if (block != NULL && (block->re_rotation().x() != 1.0f ||
block->re_rotation().y() != 0.0f)) {
// TODO(rays) We have to rotate the bounding box to get the true coords.
// This will be achieved in the future via DENORM.
// In the mean time, cube can't process this word.
if (cube_debug_level > 0) {
tprintf("Cube can't process rotated word at:");
word_box.print();
}
word->SetupFake(unicharset);
return NULL;
}
CubeObject* cube_obj = new tesseract::CubeObject(
cube_cntxt_, cube_binary_, word_box.left(),
pixGetHeight(cube_binary_) - word_box.top(),
word_box.width(), word_box.height());
if (!cube_recognize(cube_obj, block, word)) {
delete cube_obj;
return NULL;
}
return cube_obj;
}
/**********************************************************************
* cube_combine_word
*
* Combines the cube and tesseract results for a single word, leaving the
* result in tess_word.
**********************************************************************/
void Tesseract::cube_combine_word(CubeObject* cube_obj, WERD_RES* cube_word,
WERD_RES* tess_word) {
float combiner_prob = tess_cube_combiner_->CombineResults(tess_word,
cube_obj);
// If combiner probability is greater than tess/cube combiner
// classifier threshold, i.e. tesseract wins, then just return the
// tesseract result unchanged, as the combiner knows nothing about how
// correct the answer is. If cube and tesseract agree, then improve the
// scores before returning.
WERD_CHOICE* tess_best = tess_word->best_choice;
WERD_CHOICE* cube_best = cube_word->best_choice;
if (cube_debug_level || classify_debug_level) {
tprintf("Combiner prob = %g vs threshold %g\n",
combiner_prob, cube_cntxt_->Params()->CombinerClassifierThresh());
}
if (combiner_prob >=
cube_cntxt_->Params()->CombinerClassifierThresh()) {
if (tess_best->unichar_string() == cube_best->unichar_string()) {
// Cube and tess agree, so improve the scores.
tess_best->set_rating(tess_best->rating() / 2);
tess_best->set_certainty(tess_best->certainty() / 2);
}
return;
}
// Cube wins.
// It is better for the language combiner to have all tesseract scores,
// so put them in the cube result.
cube_best->set_rating(tess_best->rating());
cube_best->set_certainty(tess_best->certainty());
if (cube_debug_level || classify_debug_level) {
tprintf("Cube INFO: tesseract result replaced by cube: %s -> %s\n",
tess_best->unichar_string().string(),
cube_best->unichar_string().string());
}
tess_word->ConsumeWordResults(cube_word);
}
/**********************************************************************
* cube_recognize
*
* Call cube on the current word, and write the result to word.
* Sets up a fake result and returns false if something goes wrong.
**********************************************************************/
bool Tesseract::cube_recognize(CubeObject *cube_obj, BLOCK* block,
WERD_RES *word) {
// Run cube
WordAltList *cube_alt_list = cube_obj->RecognizeWord();
if (!cube_alt_list || cube_alt_list->AltCount() <= 0) {
if (cube_debug_level > 0) {
tprintf("Cube returned nothing for word at:");
word->word->bounding_box().print();
}
word->SetupFake(unicharset);
return false;
}
// Get cube's best result and its probability, mapped to tesseract's
// certainty range
char_32 *cube_best_32 = cube_alt_list->Alt(0);
double cube_prob = CubeUtils::Cost2Prob(cube_alt_list->AltCost(0));
float cube_certainty = convert_prob_to_tess_certainty(cube_prob);
string cube_best_str;
CubeUtils::UTF32ToUTF8(cube_best_32, &cube_best_str);
// Retrieve Cube's character bounding boxes and CharSamples,
// corresponding to the most recent call to RecognizeWord().
Boxa *char_boxes = NULL;
CharSamp **char_samples = NULL;;
int num_chars;
if (!extract_cube_state(cube_obj, &num_chars, &char_boxes, &char_samples)
&& cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::cube_recognize): Cannot extract "
"cube state.\n");
word->SetupFake(unicharset);
return false;
}
// Convert cube's character bounding boxes to a BoxWord.
BoxWord cube_box_word;
TBOX tess_word_box = word->word->bounding_box();
if (word->denorm.block() != NULL)
tess_word_box.rotate(word->denorm.block()->re_rotation());
bool box_word_success = create_cube_box_word(char_boxes, num_chars,
tess_word_box,
&cube_box_word);
boxaDestroy(&char_boxes);
if (!box_word_success) {
if (cube_debug_level > 0) {
tprintf("Cube WARNING (Tesseract::cube_recognize): Could not "
"create cube BoxWord\n");
}
word->SetupFake(unicharset);
return false;
}
// Fill tesseract result's fields with cube results
fill_werd_res(cube_box_word, cube_best_str.c_str(), word);
// Create cube's best choice.
BLOB_CHOICE** choices = new BLOB_CHOICE*[num_chars];
for (int i = 0; i < num_chars; ++i) {
UNICHAR_ID uch_id =
cube_cntxt_->CharacterSet()->UnicharID(char_samples[i]->StrLabel());
choices[i] = new BLOB_CHOICE(uch_id, -cube_certainty, cube_certainty,
-1, -1, 0, 0, 0, 0, BCC_STATIC_CLASSIFIER);
}
word->FakeClassifyWord(num_chars, choices);
// within a word, cube recognizes the word in reading order.
word->best_choice->set_unichars_in_script_order(true);
delete [] choices;
delete [] char_samples;
// Some sanity checks
ASSERT_HOST(word->best_choice->length() == word->reject_map.length());
if (cube_debug_level || classify_debug_level) {
tprintf("Cube result: %s r=%g, c=%g\n",
word->best_choice->unichar_string().string(),
word->best_choice->rating(),
word->best_choice->certainty());
}
return true;
}
/**********************************************************************
* fill_werd_res
*
* Fill Tesseract's word result fields with cube's.
*
**********************************************************************/
void Tesseract::fill_werd_res(const BoxWord& cube_box_word,
const char* cube_best_str,
WERD_RES* tess_werd_res) {
delete tess_werd_res->box_word;
tess_werd_res->box_word = new BoxWord(cube_box_word);
tess_werd_res->box_word->ClipToOriginalWord(tess_werd_res->denorm.block(),
tess_werd_res->word);
// Fill text and remaining fields
tess_werd_res->word->set_text(cube_best_str);
tess_werd_res->tess_failed = FALSE;
tess_werd_res->tess_accepted = tess_acceptable_word(tess_werd_res);
// There is no output word, so we can' call AdaptableWord, but then I don't
// think we need to. Fudge the result with accepted.
tess_werd_res->tess_would_adapt = tess_werd_res->tess_accepted;
// Set word to done, i.e., ignore all of tesseract's tests for rejection
tess_werd_res->done = tess_werd_res->tess_accepted;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: pgedit.h
// Description: Page structure file editor
// Author: Joern Wanke
// Created: Wed Jul 18 10:05:01 PDT 2007
//
// (C) Copyright 2007, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef PGEDIT_H
#define PGEDIT_H
#include "ocrblock.h"
#include "ocrrow.h"
#include "werd.h"
#include "rect.h"
#include "params.h"
#include "tesseractclass.h"
class ScrollView;
class SVMenuNode;
struct SVEvent;
// A small event handler class to process incoming events to
// this window.
class PGEventHandler : public SVEventHandler {
public:
PGEventHandler(tesseract::Tesseract* tess) : tess_(tess) {
}
void Notify(const SVEvent* sve);
private:
tesseract::Tesseract* tess_;
};
extern BLOCK_LIST *current_block_list;
extern STRING_VAR_H (editor_image_win_name, "EditorImage",
"Editor image window name");
extern INT_VAR_H (editor_image_xpos, 590, "Editor image X Pos");
extern INT_VAR_H (editor_image_ypos, 10, "Editor image Y Pos");
extern INT_VAR_H (editor_image_height, 680, "Editor image height");
extern INT_VAR_H (editor_image_width, 655, "Editor image width");
extern INT_VAR_H (editor_image_word_bb_color, BLUE,
"Word bounding box colour");
extern INT_VAR_H (editor_image_blob_bb_color, YELLOW,
"Blob bounding box colour");
extern INT_VAR_H (editor_image_text_color, WHITE, "Correct text colour");
extern STRING_VAR_H (editor_dbwin_name, "EditorDBWin",
"Editor debug window name");
extern INT_VAR_H (editor_dbwin_xpos, 50, "Editor debug window X Pos");
extern INT_VAR_H (editor_dbwin_ypos, 500, "Editor debug window Y Pos");
extern INT_VAR_H (editor_dbwin_height, 24, "Editor debug window height");
extern INT_VAR_H (editor_dbwin_width, 80, "Editor debug window width");
extern STRING_VAR_H (editor_word_name, "BlnWords",
"BL normalised word window");
extern INT_VAR_H (editor_word_xpos, 60, "Word window X Pos");
extern INT_VAR_H (editor_word_ypos, 510, "Word window Y Pos");
extern INT_VAR_H (editor_word_height, 240, "Word window height");
extern INT_VAR_H (editor_word_width, 655, "Word window width");
extern double_VAR_H (editor_smd_scale_factor, 1.0, "Scaling for smd image");
ScrollView* bln_word_window_handle(); //return handle
void build_image_window(int width, int height);
void display_bln_lines(ScrollView window,
ScrollView::Color colour,
float scale_factor,
float y_offset,
float minx,
float maxx);
//function to call
void pgeditor_msg( //message display
const char *msg);
void pgeditor_show_point( //display coords
SVEvent *event);
//put bln word in box
void show_point(PAGE_RES* page_res, float x, float y);
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: thresholder.cpp
// Description: Base API for thresolding images in tesseract.
// Author: Ray Smith
// Created: Mon May 12 11:28:15 PDT 2008
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "allheaders.h"
#include "thresholder.h"
#include <string.h>
#include "otsuthr.h"
#include "openclwrapper.h"
namespace tesseract {
ImageThresholder::ImageThresholder()
: pix_(NULL),
image_width_(0), image_height_(0),
pix_channels_(0), pix_wpl_(0),
scale_(1), yres_(300), estimated_res_(300) {
SetRectangle(0, 0, 0, 0);
}
ImageThresholder::~ImageThresholder() {
Clear();
}
// Destroy the Pix if there is one, freeing memory.
void ImageThresholder::Clear() {
pixDestroy(&pix_);
}
// Return true if no image has been set.
bool ImageThresholder::IsEmpty() const {
return pix_ == NULL;
}
// SetImage makes a copy of all the image data, so it may be deleted
// immediately after this call.
// Greyscale of 8 and color of 24 or 32 bits per pixel may be given.
// Palette color images will not work properly and must be converted to
// 24 bit.
// Binary images of 1 bit per pixel may also be given but they must be
// byte packed with the MSB of the first byte being the first pixel, and a
// one pixel is WHITE. For binary images set bytes_per_pixel=0.
void ImageThresholder::SetImage(const unsigned char* imagedata,
int width, int height,
int bytes_per_pixel, int bytes_per_line) {
int bpp = bytes_per_pixel * 8;
if (bpp == 0) bpp = 1;
Pix* pix = pixCreate(width, height, bpp == 24 ? 32 : bpp);
l_uint32* data = pixGetData(pix);
int wpl = pixGetWpl(pix);
switch (bpp) {
case 1:
for (int y = 0; y < height; ++y, data += wpl, imagedata += bytes_per_line) {
for (int x = 0; x < width; ++x) {
if (imagedata[x / 8] & (0x80 >> (x % 8)))
CLEAR_DATA_BIT(data, x);
else
SET_DATA_BIT(data, x);
}
}
break;
case 8:
// Greyscale just copies the bytes in the right order.
for (int y = 0; y < height; ++y, data += wpl, imagedata += bytes_per_line) {
for (int x = 0; x < width; ++x)
SET_DATA_BYTE(data, x, imagedata[x]);
}
break;
case 24:
// Put the colors in the correct places in the line buffer.
for (int y = 0; y < height; ++y, imagedata += bytes_per_line) {
for (int x = 0; x < width; ++x, ++data) {
SET_DATA_BYTE(data, COLOR_RED, imagedata[3 * x]);
SET_DATA_BYTE(data, COLOR_GREEN, imagedata[3 * x + 1]);
SET_DATA_BYTE(data, COLOR_BLUE, imagedata[3 * x + 2]);
}
}
break;
case 32:
// Maintain byte order consistency across different endianness.
for (int y = 0; y < height; ++y, imagedata += bytes_per_line, data += wpl) {
for (int x = 0; x < width; ++x) {
data[x] = (imagedata[x * 4] << 24) | (imagedata[x * 4 + 1] << 16) |
(imagedata[x * 4 + 2] << 8) | imagedata[x * 4 + 3];
}
}
break;
default:
tprintf("Cannot convert RAW image to Pix with bpp = %d\n", bpp);
}
pixSetYRes(pix, 300);
SetImage(pix);
pixDestroy(&pix);
}
// Store the coordinates of the rectangle to process for later use.
// Doesn't actually do any thresholding.
void ImageThresholder::SetRectangle(int left, int top, int width, int height) {
rect_left_ = left;
rect_top_ = top;
rect_width_ = width;
rect_height_ = height;
}
// Get enough parameters to be able to rebuild bounding boxes in the
// original image (not just within the rectangle).
// Left and top are enough with top-down coordinates, but
// the height of the rectangle and the image are needed for bottom-up.
void ImageThresholder::GetImageSizes(int* left, int* top,
int* width, int* height,
int* imagewidth, int* imageheight) {
*left = rect_left_;
*top = rect_top_;
*width = rect_width_;
*height = rect_height_;
*imagewidth = image_width_;
*imageheight = image_height_;
}
// Pix vs raw, which to use? Pix is the preferred input for efficiency,
// since raw buffers are copied.
// SetImage for Pix clones its input, so the source pix may be pixDestroyed
// immediately after, but may not go away until after the Thresholder has
// finished with it.
void ImageThresholder::SetImage(const Pix* pix) {
if (pix_ != NULL)
pixDestroy(&pix_);
Pix* src = const_cast<Pix*>(pix);
int depth;
pixGetDimensions(src, &image_width_, &image_height_, &depth);
// Convert the image as necessary so it is one of binary, plain RGB, or
// 8 bit with no colormap.
if (depth > 1 && depth < 8) {
pix_ = pixConvertTo8(src, false);
} else if (pixGetColormap(src)) {
pix_ = pixRemoveColormap(src, REMOVE_CMAP_BASED_ON_SRC);
} else {
pix_ = pixClone(src);
}
depth = pixGetDepth(pix_);
pix_channels_ = depth / 8;
pix_wpl_ = pixGetWpl(pix_);
scale_ = 1;
estimated_res_ = yres_ = pixGetYRes(src);
Init();
}
// Threshold the source image as efficiently as possible to the output Pix.
// Creates a Pix and sets pix to point to the resulting pointer.
// Caller must use pixDestroy to free the created Pix.
void ImageThresholder::ThresholdToPix(PageSegMode pageseg_mode, Pix** pix) {
if (pix_channels_ == 0) {
// We have a binary image, so it just has to be cloned.
*pix = GetPixRect();
} else {
OtsuThresholdRectToPix(pix_, pix);
}
}
// Gets a pix that contains an 8 bit threshold value at each pixel. The
// returned pix may be an integer reduction of the binary image such that
// the scale factor may be inferred from the ratio of the sizes, even down
// to the extreme of a 1x1 pixel thresholds image.
// Ideally the 8 bit threshold should be the exact threshold used to generate
// the binary image in ThresholdToPix, but this is not a hard constraint.
// Returns NULL if the input is binary. PixDestroy after use.
Pix* ImageThresholder::GetPixRectThresholds() {
if (IsBinary()) return NULL;
Pix* pix_grey = GetPixRectGrey();
int width = pixGetWidth(pix_grey);
int height = pixGetHeight(pix_grey);
int* thresholds;
int* hi_values;
OtsuThreshold(pix_grey, 0, 0, width, height, &thresholds, &hi_values);
pixDestroy(&pix_grey);
Pix* pix_thresholds = pixCreate(width, height, 8);
int threshold = thresholds[0] > 0 ? thresholds[0] : 128;
pixSetAllArbitrary(pix_thresholds, threshold);
delete [] thresholds;
delete [] hi_values;
return pix_thresholds;
}
// Common initialization shared between SetImage methods.
void ImageThresholder::Init() {
SetRectangle(0, 0, image_width_, image_height_);
}
// Get a clone/copy of the source image rectangle.
// The returned Pix must be pixDestroyed.
// This function will be used in the future by the page layout analysis, and
// the layout analysis that uses it will only be available with Leptonica,
// so there is no raw equivalent.
Pix* ImageThresholder::GetPixRect() {
if (IsFullImage()) {
// Just clone the whole thing.
return pixClone(pix_);
} else {
// Crop to the given rectangle.
Box* box = boxCreate(rect_left_, rect_top_, rect_width_, rect_height_);
Pix* cropped = pixClipRectangle(pix_, box, NULL);
boxDestroy(&box);
return cropped;
}
}
// Get a clone/copy of the source image rectangle, reduced to greyscale,
// and at the same resolution as the output binary.
// The returned Pix must be pixDestroyed.
// Provided to the classifier to extract features from the greyscale image.
Pix* ImageThresholder::GetPixRectGrey() {
Pix* pix = GetPixRect(); // May have to be reduced to grey.
int depth = pixGetDepth(pix);
if (depth != 8) {
Pix* result = depth < 8 ? pixConvertTo8(pix, false)
: pixConvertRGBToLuminance(pix);
pixDestroy(&pix);
return result;
}
return pix;
}
// Otsu thresholds the rectangle, taking the rectangle from *this.
void ImageThresholder::OtsuThresholdRectToPix(Pix* src_pix,
Pix** out_pix) const {
PERF_COUNT_START("OtsuThresholdRectToPix")
int* thresholds;
int* hi_values;
int num_channels = OtsuThreshold(src_pix, rect_left_, rect_top_, rect_width_,
rect_height_, &thresholds, &hi_values);
// only use opencl if compiled w/ OpenCL and selected device is opencl
#ifdef USE_OPENCL
OpenclDevice od;
if ((num_channels == 4 || num_channels == 1) &&
od.selectedDeviceIsOpenCL() && rect_top_ == 0 && rect_left_ == 0 ) {
od.ThresholdRectToPixOCL((const unsigned char*)pixGetData(src_pix),
num_channels, pixGetWpl(src_pix) * 4,
thresholds, hi_values, out_pix /*pix_OCL*/,
rect_height_, rect_width_, rect_top_, rect_left_);
} else {
#endif
ThresholdRectToPix(src_pix, num_channels, thresholds, hi_values, out_pix);
#ifdef USE_OPENCL
}
#endif
delete [] thresholds;
delete [] hi_values;
PERF_COUNT_END
}
/// Threshold the rectangle, taking everything except the src_pix
/// from the class, using thresholds/hi_values to the output pix.
/// NOTE that num_channels is the size of the thresholds and hi_values
// arrays and also the bytes per pixel in src_pix.
void ImageThresholder::ThresholdRectToPix(Pix* src_pix,
int num_channels,
const int* thresholds,
const int* hi_values,
Pix** pix) const {
PERF_COUNT_START("ThresholdRectToPix")
*pix = pixCreate(rect_width_, rect_height_, 1);
uinT32* pixdata = pixGetData(*pix);
int wpl = pixGetWpl(*pix);
int src_wpl = pixGetWpl(src_pix);
uinT32* srcdata = pixGetData(src_pix);
for (int y = 0; y < rect_height_; ++y) {
const uinT32* linedata = srcdata + (y + rect_top_) * src_wpl;
uinT32* pixline = pixdata + y * wpl;
for (int x = 0; x < rect_width_; ++x) {
bool white_result = true;
for (int ch = 0; ch < num_channels; ++ch) {
int pixel = GET_DATA_BYTE(const_cast<void*>(
reinterpret_cast<const void *>(linedata)),
(x + rect_left_) * num_channels + ch);
if (hi_values[ch] >= 0 &&
(pixel > thresholds[ch]) == (hi_values[ch] == 0)) {
white_result = false;
break;
}
}
if (white_result)
CLEAR_DATA_BIT(pixline, x);
else
SET_DATA_BIT(pixline, x);
}
}
PERF_COUNT_END
}
} // namespace tesseract.
| C++ |
/**********************************************************************
* File: fixxht.cpp (Formerly fixxht.c)
* Description: Improve x_ht and look out for case inconsistencies
* Author: Phil Cheatle
* Created: Thu Aug 5 14:11:08 BST 1993
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <string.h>
#include <ctype.h>
#include "params.h"
#include "float2int.h"
#include "tesseractclass.h"
namespace tesseract {
// Fixxht overview.
// Premise: Initial estimate of x-height is adequate most of the time, but
// occasionally it is incorrect. Most notable causes of failure are:
// 1. Small caps, where the top of the caps is the same as the body text
// xheight. For small caps words the xheight needs to be reduced to correctly
// recognize the caps in the small caps word.
// 2. All xheight lines, such as summer. Here the initial estimate will have
// guessed that the blob tops are caps and will have placed the xheight too low.
// 3. Noise/logos beside words, or changes in font size on a line. Such
// things can blow the statistics and cause an incorrect estimate.
//
// Algorithm.
// Compare the vertical position (top only) of alphnumerics in a word with
// the range of positions in training data (in the unicharset).
// See CountMisfitTops. If any characters disagree sufficiently with the
// initial xheight estimate, then recalculate the xheight, re-run OCR on
// the word, and if the number of vertical misfits goes down, along with
// either the word rating or certainty, then keep the new xheight.
// The new xheight is calculated as follows:ComputeCompatibleXHeight
// For each alphanumeric character that has a vertically misplaced top
// (a misfit), yet its bottom is within the acceptable range (ie it is not
// likely a sub-or super-script) calculate the range of acceptable xheight
// positions from its range of tops, and give each value in the range a
// number of votes equal to the distance of its top from its acceptance range.
// The x-height position with the median of the votes becomes the new
// x-height. This assumes that most characters will be correctly recognized
// even if the x-height is incorrect. This is not a terrible assumption, but
// it is not great. An improvement would be to use a classifier that does
// not care about vertical position or scaling at all.
// If the max-min top of a unicharset char is bigger than kMaxCharTopRange
// then the char top cannot be used to judge misfits or suggest a new top.
const int kMaxCharTopRange = 48;
// Returns the number of misfit blob tops in this word.
int Tesseract::CountMisfitTops(WERD_RES *word_res) {
int bad_blobs = 0;
int num_blobs = word_res->rebuild_word->NumBlobs();
for (int blob_id = 0; blob_id < num_blobs; ++blob_id) {
TBLOB* blob = word_res->rebuild_word->blobs[blob_id];
UNICHAR_ID class_id = word_res->best_choice->unichar_id(blob_id);
if (unicharset.get_isalpha(class_id) || unicharset.get_isdigit(class_id)) {
int top = blob->bounding_box().top();
if (top >= INT_FEAT_RANGE)
top = INT_FEAT_RANGE - 1;
int min_bottom, max_bottom, min_top, max_top;
unicharset.get_top_bottom(class_id, &min_bottom, &max_bottom,
&min_top, &max_top);
if (max_top - min_top > kMaxCharTopRange)
continue;
bool bad = top < min_top - x_ht_acceptance_tolerance ||
top > max_top + x_ht_acceptance_tolerance;
if (bad)
++bad_blobs;
if (debug_x_ht_level >= 1) {
tprintf("Class %s is %s with top %d vs limits of %d->%d, +/-%d\n",
unicharset.id_to_unichar(class_id),
bad ? "Misfit" : "OK", top, min_top, max_top,
static_cast<int>(x_ht_acceptance_tolerance));
}
}
}
return bad_blobs;
}
// Returns a new x-height maximally compatible with the result in word_res.
// See comment above for overall algorithm.
float Tesseract::ComputeCompatibleXheight(WERD_RES *word_res) {
STATS top_stats(0, MAX_UINT8);
int num_blobs = word_res->rebuild_word->NumBlobs();
for (int blob_id = 0; blob_id < num_blobs; ++blob_id) {
TBLOB* blob = word_res->rebuild_word->blobs[blob_id];
UNICHAR_ID class_id = word_res->best_choice->unichar_id(blob_id);
if (unicharset.get_isalpha(class_id) || unicharset.get_isdigit(class_id)) {
int top = blob->bounding_box().top();
// Clip the top to the limit of normalized feature space.
if (top >= INT_FEAT_RANGE)
top = INT_FEAT_RANGE - 1;
int bottom = blob->bounding_box().bottom();
int min_bottom, max_bottom, min_top, max_top;
unicharset.get_top_bottom(class_id, &min_bottom, &max_bottom,
&min_top, &max_top);
// Chars with a wild top range would mess up the result so ignore them.
if (max_top - min_top > kMaxCharTopRange)
continue;
int misfit_dist = MAX((min_top - x_ht_acceptance_tolerance) - top,
top - (max_top + x_ht_acceptance_tolerance));
int height = top - kBlnBaselineOffset;
if (debug_x_ht_level >= 20) {
tprintf("Class %s: height=%d, bottom=%d,%d top=%d,%d, actual=%d,%d : ",
unicharset.id_to_unichar(class_id),
height, min_bottom, max_bottom, min_top, max_top,
bottom, top);
}
// Use only chars that fit in the expected bottom range, and where
// the range of tops is sensibly near the xheight.
if (min_bottom <= bottom + x_ht_acceptance_tolerance &&
bottom - x_ht_acceptance_tolerance <= max_bottom &&
min_top > kBlnBaselineOffset &&
max_top - kBlnBaselineOffset >= kBlnXHeight &&
misfit_dist > 0) {
// Compute the x-height position using proportionality between the
// actual height and expected height.
int min_xht = DivRounded(height * kBlnXHeight,
max_top - kBlnBaselineOffset);
int max_xht = DivRounded(height * kBlnXHeight,
min_top - kBlnBaselineOffset);
if (debug_x_ht_level >= 20) {
tprintf(" xht range min=%d, max=%d\n",
min_xht, max_xht);
}
// The range of expected heights gets a vote equal to the distance
// of the actual top from the expected top.
for (int y = min_xht; y <= max_xht; ++y)
top_stats.add(y, misfit_dist);
} else if (debug_x_ht_level >= 20) {
tprintf(" already OK\n");
}
}
}
if (top_stats.get_total() == 0)
return 0.0f;
// The new xheight is just the median vote, which is then scaled out
// of BLN space back to pixel space to get the x-height in pixel space.
float new_xht = top_stats.median();
if (debug_x_ht_level >= 20) {
tprintf("Median xht=%f\n", new_xht);
tprintf("Mode20:A: New x-height = %f (norm), %f (orig)\n",
new_xht, new_xht / word_res->denorm.y_scale());
}
// The xheight must change by at least x_ht_min_change to be used.
if (fabs(new_xht - kBlnXHeight) >= x_ht_min_change)
return new_xht / word_res->denorm.y_scale();
else
return 0.0f;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: osdetect.h
// Description: Orientation and script detection.
// Author: Samuel Charron
// Ranjith Unnikrishnan
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_OSDETECT_H__
#define TESSERACT_CCMAIN_OSDETECT_H__
#include "strngs.h"
#include "unicharset.h"
class TO_BLOCK_LIST;
class BLOBNBOX;
class BLOB_CHOICE_LIST;
class BLOBNBOX_CLIST;
namespace tesseract {
class Tesseract;
}
// Max number of scripts in ICU + "NULL" + Japanese and Korean + Fraktur
const int kMaxNumberOfScripts = 116 + 1 + 2 + 1;
struct OSBestResult {
OSBestResult() : orientation_id(0), script_id(0), sconfidence(0.0),
oconfidence(0.0) {}
int orientation_id;
int script_id;
float sconfidence;
float oconfidence;
};
struct OSResults {
OSResults() : unicharset(NULL) {
for (int i = 0; i < 4; ++i) {
for (int j = 0; j < kMaxNumberOfScripts; ++j)
scripts_na[i][j] = 0;
orientations[i] = 0;
}
}
void update_best_orientation();
// Set the estimate of the orientation to the given id.
void set_best_orientation(int orientation_id);
// Update/Compute the best estimate of the script assuming the given
// orientation id.
void update_best_script(int orientation_id);
// Return the index of the script with the highest score for this orientation.
TESS_API int get_best_script(int orientation_id) const;
// Accumulate scores with given OSResults instance and update the best script.
void accumulate(const OSResults& osr);
// Print statistics.
void print_scores(void) const;
void print_scores(int orientation_id) const;
// Array holding scores for each orientation id [0,3].
// Orientation ids [0..3] map to [0, 270, 180, 90] degree orientations of the
// page respectively, where the values refer to the amount of clockwise
// rotation to be applied to the page for the text to be upright and readable.
float orientations[4];
// Script confidence scores for each of 4 possible orientations.
float scripts_na[4][kMaxNumberOfScripts];
UNICHARSET* unicharset;
OSBestResult best_result;
};
class OrientationDetector {
public:
OrientationDetector(const GenericVector<int>* allowed_scripts,
OSResults* results);
bool detect_blob(BLOB_CHOICE_LIST* scores);
int get_orientation();
private:
OSResults* osr_;
tesseract::Tesseract* tess_;
const GenericVector<int>* allowed_scripts_;
};
class ScriptDetector {
public:
ScriptDetector(const GenericVector<int>* allowed_scripts,
OSResults* osr, tesseract::Tesseract* tess);
void detect_blob(BLOB_CHOICE_LIST* scores);
bool must_stop(int orientation);
private:
OSResults* osr_;
static const char* korean_script_;
static const char* japanese_script_;
static const char* fraktur_script_;
int korean_id_;
int japanese_id_;
int katakana_id_;
int hiragana_id_;
int han_id_;
int hangul_id_;
int latin_id_;
int fraktur_id_;
tesseract::Tesseract* tess_;
const GenericVector<int>* allowed_scripts_;
};
int orientation_and_script_detection(STRING& filename,
OSResults*,
tesseract::Tesseract*);
int os_detect(TO_BLOCK_LIST* port_blocks,
OSResults* osr,
tesseract::Tesseract* tess);
int os_detect_blobs(const GenericVector<int>* allowed_scripts,
BLOBNBOX_CLIST* blob_list,
OSResults* osr,
tesseract::Tesseract* tess);
bool os_detect_blob(BLOBNBOX* bbox, OrientationDetector* o,
ScriptDetector* s, OSResults*,
tesseract::Tesseract* tess);
// Helper method to convert an orientation index to its value in degrees.
// The value represents the amount of clockwise rotation in degrees that must be
// applied for the text to be upright (readable).
TESS_API const int OrientationIdToValue(const int& id);
#endif // TESSERACT_CCMAIN_OSDETECT_H__
| C++ |
/**********************************************************************
* File: tfacepp.cpp (Formerly tface++.c)
* Description: C++ side of the C/C++ Tess/Editor interface.
* Author: Ray Smith
* Created: Thu Apr 23 15:39:23 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#pragma warning(disable:4305) // int/float warnings
#pragma warning(disable:4800) // int/bool warnings
#endif
#include <math.h>
#include "blamer.h"
#include "errcode.h"
#include "ratngs.h"
#include "reject.h"
#include "tesseractclass.h"
#include "werd.h"
#define MAX_UNDIVIDED_LENGTH 24
/**********************************************************************
* recog_word
*
* Convert the word to tess form and pass it to the tess segmenter.
* Convert the output back to editor form.
**********************************************************************/
namespace tesseract {
void Tesseract::recog_word(WERD_RES *word) {
if (wordrec_skip_no_truth_words && (word->blamer_bundle == NULL ||
word->blamer_bundle->incorrect_result_reason() == IRR_NO_TRUTH)) {
if (classify_debug_level) tprintf("No truth for word - skipping\n");
word->tess_failed = true;
return;
}
ASSERT_HOST(!word->chopped_word->blobs.empty());
recog_word_recursive(word);
word->SetupBoxWord();
if (word->best_choice->length() != word->box_word->length()) {
tprintf("recog_word ASSERT FAIL String:\"%s\"; "
"Strlen=%d; #Blobs=%d\n",
word->best_choice->debug_string().string(),
word->best_choice->length(), word->box_word->length());
}
ASSERT_HOST(word->best_choice->length() == word->box_word->length());
// Check that the ratings matrix size matches the sum of all the
// segmentation states.
if (!word->StatesAllValid()) {
tprintf("Not all words have valid states relative to ratings matrix!!");
word->DebugWordChoices(true, NULL);
ASSERT_HOST(word->StatesAllValid());
}
if (tessedit_override_permuter) {
/* Override the permuter type if a straight dictionary check disagrees. */
uinT8 perm_type = word->best_choice->permuter();
if ((perm_type != SYSTEM_DAWG_PERM) &&
(perm_type != FREQ_DAWG_PERM) && (perm_type != USER_DAWG_PERM)) {
uinT8 real_dict_perm_type = dict_word(*word->best_choice);
if (((real_dict_perm_type == SYSTEM_DAWG_PERM) ||
(real_dict_perm_type == FREQ_DAWG_PERM) ||
(real_dict_perm_type == USER_DAWG_PERM)) &&
(alpha_count(word->best_choice->unichar_string().string(),
word->best_choice->unichar_lengths().string()) > 0)) {
word->best_choice->set_permuter(real_dict_perm_type); // use dict perm
}
}
if (tessedit_rejection_debug &&
perm_type != word->best_choice->permuter()) {
tprintf("Permuter Type Flipped from %d to %d\n",
perm_type, word->best_choice->permuter());
}
}
// Factored out from control.cpp
ASSERT_HOST((word->best_choice == NULL) == (word->raw_choice == NULL));
if (word->best_choice == NULL || word->best_choice->length() == 0 ||
static_cast<int>(strspn(word->best_choice->unichar_string().string(),
" ")) == word->best_choice->length()) {
word->tess_failed = true;
word->reject_map.initialise(word->box_word->length());
word->reject_map.rej_word_tess_failure();
} else {
word->tess_failed = false;
}
}
/**********************************************************************
* recog_word_recursive
*
* Convert the word to tess form and pass it to the tess segmenter.
* Convert the output back to editor form.
**********************************************************************/
void Tesseract::recog_word_recursive(WERD_RES *word) {
int word_length = word->chopped_word->NumBlobs(); // no of blobs
if (word_length > MAX_UNDIVIDED_LENGTH) {
return split_and_recog_word(word);
}
cc_recog(word);
word_length = word->rebuild_word->NumBlobs(); // No of blobs in output.
// Do sanity checks and minor fixes on best_choice.
if (word->best_choice->length() > word_length) {
word->best_choice->make_bad(); // should never happen
tprintf("recog_word: Discarded long string \"%s\""
" (%d characters vs %d blobs)\n",
word->best_choice->unichar_string().string(),
word->best_choice->length(), word_length);
tprintf("Word is at:");
word->word->bounding_box().print();
}
if (word->best_choice->length() < word_length) {
UNICHAR_ID space_id = unicharset.unichar_to_id(" ");
while (word->best_choice->length() < word_length) {
word->best_choice->append_unichar_id(space_id, 1, 0.0,
word->best_choice->certainty());
}
}
}
/**********************************************************************
* split_and_recog_word
*
* Split the word into 2 smaller pieces at the largest gap.
* Recognize the pieces and stick the results back together.
**********************************************************************/
void Tesseract::split_and_recog_word(WERD_RES *word) {
// Find the biggest blob gap in the chopped_word.
int bestgap = -MAX_INT32;
int split_index = 0;
for (int b = 1; b < word->chopped_word->NumBlobs(); ++b) {
TBOX prev_box = word->chopped_word->blobs[b - 1]->bounding_box();
TBOX blob_box = word->chopped_word->blobs[b]->bounding_box();
int gap = blob_box.left() - prev_box.right();
if (gap > bestgap) {
bestgap = gap;
split_index = b;
}
}
ASSERT_HOST(split_index > 0);
WERD_RES *word2 = NULL;
BlamerBundle *orig_bb = NULL;
split_word(word, split_index, &word2, &orig_bb);
// Recognize the first part of the word.
recog_word_recursive(word);
// Recognize the second part of the word.
recog_word_recursive(word2);
join_words(word, word2, orig_bb);
}
/**********************************************************************
* split_word
*
* Split a given WERD_RES in place into two smaller words for recognition.
* split_pt is the index of the first blob to go in the second word.
* The underlying word is left alone, only the TWERD (and subsequent data)
* are split up. orig_blamer_bundle is set to the original blamer bundle,
* and will now be owned by the caller. New blamer bundles are forged for the
* two pieces.
**********************************************************************/
void Tesseract::split_word(WERD_RES *word,
int split_pt,
WERD_RES **right_piece,
BlamerBundle **orig_blamer_bundle) const {
ASSERT_HOST(split_pt >0 && split_pt < word->chopped_word->NumBlobs());
// Save a copy of the blamer bundle so we can try to reconstruct it below.
BlamerBundle *orig_bb =
word->blamer_bundle ? new BlamerBundle(*word->blamer_bundle) : NULL;
WERD_RES *word2 = new WERD_RES(*word);
// blow away the copied chopped_word, as we want to work with
// the blobs from the input chopped_word so seam_arrays can be merged.
TWERD *chopped = word->chopped_word;
TWERD *chopped2 = new TWERD;
chopped2->blobs.reserve(chopped->NumBlobs() - split_pt);
for (int i = split_pt; i < chopped->NumBlobs(); ++i) {
chopped2->blobs.push_back(chopped->blobs[i]);
}
chopped->blobs.truncate(split_pt);
word->chopped_word = NULL;
delete word2->chopped_word;
word2->chopped_word = NULL;
const UNICHARSET &unicharset = *word->uch_set;
word->ClearResults();
word2->ClearResults();
word->chopped_word = chopped;
word2->chopped_word = chopped2;
word->SetupBasicsFromChoppedWord(unicharset);
word2->SetupBasicsFromChoppedWord(unicharset);
// Try to adjust the blamer bundle.
if (orig_bb != NULL) {
// TODO(rays) Looks like a leak to me.
// orig_bb should take, rather than copy.
word->blamer_bundle = new BlamerBundle();
word2->blamer_bundle = new BlamerBundle();
orig_bb->SplitBundle(chopped->blobs.back()->bounding_box().right(),
word2->chopped_word->blobs[0]->bounding_box().left(),
wordrec_debug_blamer,
word->blamer_bundle, word2->blamer_bundle);
}
*right_piece = word2;
*orig_blamer_bundle = orig_bb;
}
/**********************************************************************
* join_words
*
* The opposite of split_word():
* join word2 (including any recognized data / seam array / etc)
* onto the right of word and then delete word2.
* Also, if orig_bb is provided, stitch it back into word.
**********************************************************************/
void Tesseract::join_words(WERD_RES *word,
WERD_RES *word2,
BlamerBundle *orig_bb) const {
TBOX prev_box = word->chopped_word->blobs.back()->bounding_box();
TBOX blob_box = word2->chopped_word->blobs[0]->bounding_box();
// Tack the word2 outputs onto the end of the word outputs.
word->chopped_word->blobs += word2->chopped_word->blobs;
word->rebuild_word->blobs += word2->rebuild_word->blobs;
word2->chopped_word->blobs.clear();
word2->rebuild_word->blobs.clear();
TPOINT split_pt;
split_pt.x = (prev_box.right() + blob_box.left()) / 2;
split_pt.y = (prev_box.top() + prev_box.bottom() +
blob_box.top() + blob_box.bottom()) / 4;
// Move the word2 seams onto the end of the word1 seam_array.
// Since the seam list is one element short, an empty seam marking the
// end of the last blob in the first word is needed first.
word->seam_array.push_back(new SEAM(0.0f, split_pt, NULL, NULL, NULL));
word->seam_array += word2->seam_array;
word2->seam_array.truncate(0);
// Fix widths and gaps.
word->blob_widths += word2->blob_widths;
word->blob_gaps += word2->blob_gaps;
// Fix the ratings matrix.
int rat1 = word->ratings->dimension();
int rat2 = word2->ratings->dimension();
word->ratings->AttachOnCorner(word2->ratings);
ASSERT_HOST(word->ratings->dimension() == rat1 + rat2);
word->best_state += word2->best_state;
// Append the word choices.
*word->raw_choice += *word2->raw_choice;
// How many alt choices from each should we try to get?
const int kAltsPerPiece = 2;
// When do we start throwing away extra alt choices?
const int kTooManyAltChoices = 100;
// Construct the cartesian product of the best_choices of word(1) and word2.
WERD_CHOICE_LIST joined_choices;
WERD_CHOICE_IT jc_it(&joined_choices);
WERD_CHOICE_IT bc1_it(&word->best_choices);
WERD_CHOICE_IT bc2_it(&word2->best_choices);
int num_word1_choices = word->best_choices.length();
int total_joined_choices = num_word1_choices;
// Nota Bene: For the main loop here, we operate only on the 2nd and greater
// word2 choices, and put them in the joined_choices list. The 1st word2
// choice gets added to the original word1 choices in-place after we have
// finished with them.
int bc2_index = 1;
for (bc2_it.forward(); !bc2_it.at_first(); bc2_it.forward(), ++bc2_index) {
if (total_joined_choices >= kTooManyAltChoices &&
bc2_index > kAltsPerPiece)
break;
int bc1_index = 0;
for (bc1_it.move_to_first(); bc1_index < num_word1_choices;
++bc1_index, bc1_it.forward()) {
if (total_joined_choices >= kTooManyAltChoices &&
bc1_index > kAltsPerPiece)
break;
WERD_CHOICE *wc = new WERD_CHOICE(*bc1_it.data());
*wc += *bc2_it.data();
jc_it.add_after_then_move(wc);
++total_joined_choices;
}
}
// Now that we've filled in as many alternates as we want, paste the best
// choice for word2 onto the original word alt_choices.
bc1_it.move_to_first();
bc2_it.move_to_first();
for (bc1_it.mark_cycle_pt(); !bc1_it.cycled_list(); bc1_it.forward()) {
*bc1_it.data() += *bc2_it.data();
}
bc1_it.move_to_last();
bc1_it.add_list_after(&joined_choices);
// Restore the pointer to original blamer bundle and combine blamer
// information recorded in the splits.
if (orig_bb != NULL) {
orig_bb->JoinBlames(*word->blamer_bundle, *word2->blamer_bundle,
wordrec_debug_blamer);
delete word->blamer_bundle;
word->blamer_bundle = orig_bb;
}
word->SetupBoxWord();
word->reject_map.initialise(word->box_word->length());
delete word2;
}
} // namespace tesseract
| C++ |
/******************************************************************
* File: superscript.cpp
* Description: Correction pass to fix superscripts and subscripts.
* Author: David Eger
* Created: Mon Mar 12 14:05:00 PDT 2012
*
* (C) Copyright 2012, Google, Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "normalis.h"
#include "tesseractclass.h"
static int LeadingUnicharsToChopped(WERD_RES *word, int num_unichars) {
int num_chopped = 0;
for (int i = 0; i < num_unichars; i++)
num_chopped += word->best_state[i];
return num_chopped;
}
static int TrailingUnicharsToChopped(WERD_RES *word, int num_unichars) {
int num_chopped = 0;
for (int i = 0; i < num_unichars; i++)
num_chopped += word->best_state[word->best_state.size() - 1 - i];
return num_chopped;
}
namespace tesseract {
/**
* Given a recognized blob, see if a contiguous collection of sub-pieces
* (chopped blobs) starting at its left might qualify as being a subscript
* or superscript letter based only on y position. Also do this for the
* right side.
*/
void YOutlierPieces(WERD_RES *word, int rebuilt_blob_index,
int super_y_bottom, int sub_y_top,
ScriptPos *leading_pos, int *num_leading_outliers,
ScriptPos *trailing_pos, int *num_trailing_outliers) {
ScriptPos sp_unused1, sp_unused2;
int unused1, unused2;
if (!leading_pos) leading_pos = &sp_unused1;
if (!num_leading_outliers) num_leading_outliers = &unused1;
if (!trailing_pos) trailing_pos = &sp_unused2;
if (!num_trailing_outliers) num_trailing_outliers = &unused2;
*num_leading_outliers = *num_trailing_outliers = 0;
*leading_pos = *trailing_pos = SP_NORMAL;
int chopped_start = LeadingUnicharsToChopped(word, rebuilt_blob_index);
int num_chopped_pieces = word->best_state[rebuilt_blob_index];
ScriptPos last_pos = SP_NORMAL;
int trailing_outliers = 0;
for (int i = 0; i < num_chopped_pieces; i++) {
TBOX box = word->chopped_word->blobs[chopped_start + i]->bounding_box();
ScriptPos pos = SP_NORMAL;
if (box.bottom() >= super_y_bottom) {
pos = SP_SUPERSCRIPT;
} else if (box.top() <= sub_y_top) {
pos = SP_SUBSCRIPT;
}
if (pos == SP_NORMAL) {
if (trailing_outliers == i) {
*num_leading_outliers = trailing_outliers;
*leading_pos = last_pos;
}
trailing_outliers = 0;
} else {
if (pos == last_pos) {
trailing_outliers++;
} else {
trailing_outliers = 1;
}
}
last_pos = pos;
}
*num_trailing_outliers = trailing_outliers;
*trailing_pos = last_pos;
}
/**
* Attempt to split off any high (or low) bits at the ends of the word with poor
* certainty and recognize them separately. If the certainty gets much better
* and other sanity checks pass, acccept.
*
* This superscript fix is meant to be called in the second pass of recognition
* when we have tried once and already have a preliminary answer for word.
*
* @return Whether we modified the given word.
*/
bool Tesseract::SubAndSuperscriptFix(WERD_RES *word) {
if (word->tess_failed || word->word->flag(W_REP_CHAR) ||
!word->best_choice) {
return false;
}
int num_leading, num_trailing;
ScriptPos sp_leading, sp_trailing;
float leading_certainty, trailing_certainty;
float avg_certainty, unlikely_threshold;
// Calculate the number of whole suspicious characters at the edges.
GetSubAndSuperscriptCandidates(
word, &num_leading, &sp_leading, &leading_certainty,
&num_trailing, &sp_trailing, &trailing_certainty,
&avg_certainty, &unlikely_threshold);
const char *leading_pos = sp_leading == SP_SUBSCRIPT ? "sub" : "super";
const char *trailing_pos = sp_trailing == SP_SUBSCRIPT ? "sub" : "super";
int num_blobs = word->best_choice->length();
// Calculate the remainder (partial characters) at the edges.
// This accounts for us having classified the best version of
// a word as [speaker?'] when it was instead [speaker.^{21}]
// (that is we accidentally thought the 2 was attached to the period).
int num_remainder_leading = 0, num_remainder_trailing = 0;
if (num_leading + num_trailing < num_blobs && unlikely_threshold < 0.0) {
int super_y_bottom =
kBlnBaselineOffset + kBlnXHeight * superscript_min_y_bottom;
int sub_y_top =
kBlnBaselineOffset + kBlnXHeight * subscript_max_y_top;
int last_word_char = num_blobs - 1 - num_trailing;
float last_char_certainty = word->best_choice->certainty(last_word_char);
if (word->best_choice->unichar_id(last_word_char) != 0 &&
last_char_certainty <= unlikely_threshold) {
ScriptPos rpos;
YOutlierPieces(word, last_word_char, super_y_bottom, sub_y_top,
NULL, NULL, &rpos, &num_remainder_trailing);
if (num_trailing > 0 && rpos != sp_trailing) num_remainder_trailing = 0;
if (num_remainder_trailing > 0 &&
last_char_certainty < trailing_certainty) {
trailing_certainty = last_char_certainty;
}
}
bool another_blob_available = (num_remainder_trailing == 0) ||
num_leading + num_trailing + 1 < num_blobs;
int first_char_certainty = word->best_choice->certainty(num_leading);
if (another_blob_available &&
word->best_choice->unichar_id(num_leading) != 0 &&
first_char_certainty <= unlikely_threshold) {
ScriptPos lpos;
YOutlierPieces(word, num_leading, super_y_bottom, sub_y_top,
&lpos, &num_remainder_leading, NULL, NULL);
if (num_leading > 0 && lpos != sp_leading) num_remainder_leading = 0;
if (num_remainder_leading > 0 &&
first_char_certainty < leading_certainty) {
leading_certainty = first_char_certainty;
}
}
}
// If nothing to do, bail now.
if (num_leading + num_trailing +
num_remainder_leading + num_remainder_trailing == 0) {
return false;
}
if (superscript_debug >= 1) {
tprintf("Candidate for superscript detection: %s (",
word->best_choice->unichar_string().string());
if (num_leading || num_remainder_leading) {
tprintf("%d.%d %s-leading ", num_leading, num_remainder_leading,
leading_pos);
}
if (num_trailing || num_remainder_trailing) {
tprintf("%d.%d %s-trailing ", num_trailing, num_remainder_trailing,
trailing_pos);
}
tprintf(")\n");
}
if (superscript_debug >= 3) {
word->best_choice->print();
}
if (superscript_debug >= 2) {
tprintf(" Certainties -- Average: %.2f Unlikely thresh: %.2f ",
avg_certainty, unlikely_threshold);
if (num_leading)
tprintf("Orig. leading (min): %.2f ", leading_certainty);
if (num_trailing)
tprintf("Orig. trailing (min): %.2f ", trailing_certainty);
tprintf("\n");
}
// We've now calculated the number of rebuilt blobs we want to carve off.
// However, split_word() works from TBLOBs in chopped_word, so we need to
// convert to those.
int num_chopped_leading =
LeadingUnicharsToChopped(word, num_leading) + num_remainder_leading;
int num_chopped_trailing =
TrailingUnicharsToChopped(word, num_trailing) + num_remainder_trailing;
int retry_leading = 0;
int retry_trailing = 0;
bool is_good = false;
WERD_RES *revised = TrySuperscriptSplits(
num_chopped_leading, leading_certainty, sp_leading,
num_chopped_trailing, trailing_certainty, sp_trailing,
word, &is_good, &retry_leading, &retry_trailing);
if (is_good) {
word->ConsumeWordResults(revised);
} else if (retry_leading || retry_trailing) {
int retry_chopped_leading =
LeadingUnicharsToChopped(revised, retry_leading);
int retry_chopped_trailing =
TrailingUnicharsToChopped(revised, retry_trailing);
WERD_RES *revised2 = TrySuperscriptSplits(
retry_chopped_leading, leading_certainty, sp_leading,
retry_chopped_trailing, trailing_certainty, sp_trailing,
revised, &is_good, &retry_leading, &retry_trailing);
if (is_good) {
word->ConsumeWordResults(revised2);
}
delete revised2;
}
delete revised;
return is_good;
}
/**
* Determine how many characters (rebuilt blobs) on each end of a given word
* might plausibly be superscripts so SubAndSuperscriptFix can try to
* re-recognize them. Even if we find no whole blobs at either end,
* we will set *unlikely_threshold to a certainty that might be used to
* select "bad enough" outlier characters. If *unlikely_threshold is set to 0,
* though, there's really no hope.
*
* @param[in] word The word to examine.
* @param[out] num_rebuilt_leading the number of rebuilt blobs at the start
* of the word which are all up or down and
* seem badly classified.
* @param[out] leading_pos "super" or "sub" (for debugging)
* @param[out] leading_certainty the worst certainty in the leading blobs.
* @param[out] num_rebuilt_trailing the number of rebuilt blobs at the end
* of the word which are all up or down and
* seem badly classified.
* @param[out] trailing_pos "super" or "sub" (for debugging)
* @param[out] trailing_certainty the worst certainty in the trailing blobs.
* @param[out] avg_certainty the average certainty of "normal" blobs in
* the word.
* @param[out] unlikely_threshold the threshold (on certainty) we used to
* select "bad enough" outlier characters.
*/
void Tesseract::GetSubAndSuperscriptCandidates(const WERD_RES *word,
int *num_rebuilt_leading,
ScriptPos *leading_pos,
float *leading_certainty,
int *num_rebuilt_trailing,
ScriptPos *trailing_pos,
float *trailing_certainty,
float *avg_certainty,
float *unlikely_threshold) {
*avg_certainty = *unlikely_threshold = 0.0f;
*num_rebuilt_leading = *num_rebuilt_trailing = 0;
*leading_certainty = *trailing_certainty = 0.0f;
int super_y_bottom =
kBlnBaselineOffset + kBlnXHeight * superscript_min_y_bottom;
int sub_y_top =
kBlnBaselineOffset + kBlnXHeight * subscript_max_y_top;
// Step one: Get an average certainty for "normally placed" characters.
// Counts here are of blobs in the rebuild_word / unichars in best_choice.
*leading_pos = *trailing_pos = SP_NORMAL;
int leading_outliers = 0;
int trailing_outliers = 0;
int num_normal = 0;
float normal_certainty_total = 0.0f;
float worst_normal_certainty = 0.0f;
ScriptPos last_pos = SP_NORMAL;
int num_blobs = word->rebuild_word->NumBlobs();
for (int b = 0; b < num_blobs; ++b) {
TBOX box = word->rebuild_word->blobs[b]->bounding_box();
ScriptPos pos = SP_NORMAL;
if (box.bottom() >= super_y_bottom) {
pos = SP_SUPERSCRIPT;
} else if (box.top() <= sub_y_top) {
pos = SP_SUBSCRIPT;
}
if (pos == SP_NORMAL) {
if (word->best_choice->unichar_id(b) != 0) {
float char_certainty = word->best_choice->certainty(b);
if (char_certainty < worst_normal_certainty) {
worst_normal_certainty = char_certainty;
}
num_normal++;
normal_certainty_total += char_certainty;
}
if (trailing_outliers == b) {
leading_outliers = trailing_outliers;
*leading_pos = last_pos;
}
trailing_outliers = 0;
} else {
if (last_pos == pos) {
trailing_outliers++;
} else {
trailing_outliers = 1;
}
}
last_pos = pos;
}
*trailing_pos = last_pos;
if (num_normal >= 3) { // throw out the worst as an outlier.
num_normal--;
normal_certainty_total -= worst_normal_certainty;
}
if (num_normal > 0) {
*avg_certainty = normal_certainty_total / num_normal;
*unlikely_threshold = superscript_worse_certainty * (*avg_certainty);
}
if (num_normal == 0 ||
(leading_outliers == 0 && trailing_outliers == 0)) {
return;
}
// Step two: Try to split off bits of the word that are both outliers
// and have much lower certainty than average
// Calculate num_leading and leading_certainty.
for (*leading_certainty = 0.0f, *num_rebuilt_leading = 0;
*num_rebuilt_leading < leading_outliers;
(*num_rebuilt_leading)++) {
float char_certainty = word->best_choice->certainty(*num_rebuilt_leading);
if (char_certainty > *unlikely_threshold) {
break;
}
if (char_certainty < *leading_certainty) {
*leading_certainty = char_certainty;
}
}
// Calculate num_trailing and trailing_certainty.
for (*trailing_certainty = 0.0f, *num_rebuilt_trailing = 0;
*num_rebuilt_trailing < trailing_outliers;
(*num_rebuilt_trailing)++) {
int blob_idx = num_blobs - 1 - *num_rebuilt_trailing;
float char_certainty = word->best_choice->certainty(blob_idx);
if (char_certainty > *unlikely_threshold) {
break;
}
if (char_certainty < *trailing_certainty) {
*trailing_certainty = char_certainty;
}
}
}
/**
* Try splitting off the given number of (chopped) blobs from the front and
* back of the given word and recognizing the pieces.
*
* @param[in] num_chopped_leading how many chopped blobs from the left
* end of the word to chop off and try recognizing as a
* superscript (or subscript)
* @param[in] leading_certainty the (minimum) certainty had by the
* characters in the original leading section.
* @param[in] leading_pos "super" or "sub" (for debugging)
* @param[in] num_chopped_trailing how many chopped blobs from the right
* end of the word to chop off and try recognizing as a
* superscript (or subscript)
* @param[in] trailing_certainty the (minimum) certainty had by the
* characters in the original trailing section.
* @param[in] trailing_pos "super" or "sub" (for debugging)
* @param[in] word the word to try to chop up.
* @param[out] is_good do we believe our result?
* @param[out] retry_rebuild_leading, retry_rebuild_trailing
* If non-zero, and !is_good, then the caller may have luck trying
* to split the returned word with this number of (rebuilt) leading
* and trailing blobs / unichars.
* @return A word which is the result of re-recognizing as asked.
*/
WERD_RES *Tesseract::TrySuperscriptSplits(
int num_chopped_leading, float leading_certainty, ScriptPos leading_pos,
int num_chopped_trailing, float trailing_certainty,
ScriptPos trailing_pos,
WERD_RES *word,
bool *is_good,
int *retry_rebuild_leading, int *retry_rebuild_trailing) {
int num_chopped = word->chopped_word->NumBlobs();
*retry_rebuild_leading = *retry_rebuild_trailing = 0;
// Chop apart the word into up to three pieces.
BlamerBundle *bb0 = NULL;
BlamerBundle *bb1 = NULL;
WERD_RES *prefix = NULL;
WERD_RES *core = NULL;
WERD_RES *suffix = NULL;
if (num_chopped_leading > 0) {
prefix = new WERD_RES(*word);
split_word(prefix, num_chopped_leading, &core, &bb0);
} else {
core = new WERD_RES(*word);
}
if (num_chopped_trailing > 0) {
int split_pt = num_chopped - num_chopped_trailing - num_chopped_leading;
split_word(core, split_pt, &suffix, &bb1);
}
// Recognize the pieces in turn.
int saved_cp_multiplier = classify_class_pruner_multiplier;
int saved_im_multiplier = classify_integer_matcher_multiplier;
if (prefix) {
// Turn off Tesseract's y-position penalties for the leading superscript.
classify_class_pruner_multiplier.set_value(0);
classify_integer_matcher_multiplier.set_value(0);
// Adjust our expectations about the baseline for this prefix.
if (superscript_debug >= 3) {
tprintf(" recognizing first %d chopped blobs\n", num_chopped_leading);
}
recog_word_recursive(prefix);
if (superscript_debug >= 2) {
tprintf(" The leading bits look like %s %s\n",
ScriptPosToString(leading_pos),
prefix->best_choice->unichar_string().string());
}
// Restore the normal y-position penalties.
classify_class_pruner_multiplier.set_value(saved_cp_multiplier);
classify_integer_matcher_multiplier.set_value(saved_im_multiplier);
}
if (superscript_debug >= 3) {
tprintf(" recognizing middle %d chopped blobs\n",
num_chopped - num_chopped_leading - num_chopped_trailing);
}
if (suffix) {
// Turn off Tesseract's y-position penalties for the trailing superscript.
classify_class_pruner_multiplier.set_value(0);
classify_integer_matcher_multiplier.set_value(0);
if (superscript_debug >= 3) {
tprintf(" recognizing last %d chopped blobs\n", num_chopped_trailing);
}
recog_word_recursive(suffix);
if (superscript_debug >= 2) {
tprintf(" The trailing bits look like %s %s\n",
ScriptPosToString(trailing_pos),
suffix->best_choice->unichar_string().string());
}
// Restore the normal y-position penalties.
classify_class_pruner_multiplier.set_value(saved_cp_multiplier);
classify_integer_matcher_multiplier.set_value(saved_im_multiplier);
}
// Evaluate whether we think the results are believably better
// than what we already had.
bool good_prefix = !prefix || BelievableSuperscript(
superscript_debug >= 1, *prefix,
superscript_bettered_certainty * leading_certainty,
retry_rebuild_leading, NULL);
bool good_suffix = !suffix || BelievableSuperscript(
superscript_debug >= 1, *suffix,
superscript_bettered_certainty * trailing_certainty,
NULL, retry_rebuild_trailing);
*is_good = good_prefix && good_suffix;
if (!*is_good && !*retry_rebuild_leading && !*retry_rebuild_trailing) {
// None of it is any good. Quit now.
delete core;
delete prefix;
delete suffix;
return NULL;
}
recog_word_recursive(core);
// Now paste the results together into core.
if (suffix) {
suffix->SetAllScriptPositions(trailing_pos);
join_words(core, suffix, bb1);
}
if (prefix) {
prefix->SetAllScriptPositions(leading_pos);
join_words(prefix, core, bb0);
core = prefix;
prefix = NULL;
}
if (superscript_debug >= 1) {
tprintf("%s superscript fix: %s\n", *is_good ? "ACCEPT" : "REJECT",
core->best_choice->unichar_string().string());
}
return core;
}
/**
* Return whether this is believable superscript or subscript text.
*
* We insist that:
* + there are no punctuation marks.
* + there are no italics.
* + no normal-sized character is smaller than superscript_scaledown_ratio
* of what it ought to be, and
* + each character is at least as certain as certainty_threshold.
*
* @param[in] debug If true, spew debug output
* @param[in] word The word whose best_choice we're evaluating
* @param[in] certainty_threshold If any of the characters have less
* certainty than this, reject.
* @param[out] left_ok How many left-side characters were ok?
* @param[out] right_ok How many right-side characters were ok?
* @return Whether the complete best choice is believable as a superscript.
*/
bool Tesseract::BelievableSuperscript(bool debug,
const WERD_RES &word,
float certainty_threshold,
int *left_ok,
int *right_ok) const {
int initial_ok_run_count = 0;
int ok_run_count = 0;
float worst_certainty = 0.0f;
const WERD_CHOICE &wc = *word.best_choice;
const UnicityTable<FontInfo>& fontinfo_table = get_fontinfo_table();
for (int i = 0; i < wc.length(); i++) {
TBLOB *blob = word.rebuild_word->blobs[i];
UNICHAR_ID unichar_id = wc.unichar_id(i);
float char_certainty = wc.certainty(i);
bool bad_certainty = char_certainty < certainty_threshold;
bool is_punc = wc.unicharset()->get_ispunctuation(unichar_id);
bool is_italic = word.fontinfo && word.fontinfo->is_italic();
BLOB_CHOICE *choice = word.GetBlobChoice(i);
if (choice && fontinfo_table.size() > 0) {
// Get better information from the specific choice, if available.
int font_id1 = choice->fontinfo_id();
bool font1_is_italic = font_id1 >= 0
? fontinfo_table.get(font_id1).is_italic() : false;
int font_id2 = choice->fontinfo_id2();
is_italic = font1_is_italic &&
(font_id2 < 0 || fontinfo_table.get(font_id2).is_italic());
}
float height_fraction = 1.0f;
float char_height = blob->bounding_box().height();
float normal_height = char_height;
if (wc.unicharset()->top_bottom_useful()) {
int min_bot, max_bot, min_top, max_top;
wc.unicharset()->get_top_bottom(unichar_id,
&min_bot, &max_bot,
&min_top, &max_top);
float hi_height = max_top - max_bot;
float lo_height = min_top - min_bot;
normal_height = (hi_height + lo_height) / 2;
if (normal_height >= kBlnXHeight) {
// Only ding characters that we have decent information for because
// they're supposed to be normal sized, not tiny specks or dashes.
height_fraction = char_height / normal_height;
}
}
bool bad_height = height_fraction < superscript_scaledown_ratio;
if (debug) {
if (is_italic) {
tprintf(" Rejecting: superscript is italic.\n");
}
if (is_punc) {
tprintf(" Rejecting: punctuation present.\n");
}
const char *char_str = wc.unicharset()->id_to_unichar(unichar_id);
if (bad_certainty) {
tprintf(" Rejecting: don't believe character %s with certainty %.2f "
"which is less than threshold %.2f\n", char_str,
char_certainty, certainty_threshold);
}
if (bad_height) {
tprintf(" Rejecting: character %s seems too small @ %.2f versus "
"expected %.2f\n", char_str, char_height, normal_height);
}
}
if (bad_certainty || bad_height || is_punc || is_italic) {
if (ok_run_count == i) {
initial_ok_run_count = ok_run_count;
}
ok_run_count = 0;
} else {
ok_run_count++;
}
if (char_certainty < worst_certainty) {
worst_certainty = char_certainty;
}
}
bool all_ok = ok_run_count == wc.length();
if (all_ok && debug) {
tprintf(" Accept: worst revised certainty is %.2f\n", worst_certainty);
}
if (!all_ok) {
if (left_ok) *left_ok = initial_ok_run_count;
if (right_ok) *right_ok = ok_run_count;
}
return all_ok;
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: ltrresultiterator.cpp
// Description: Iterator for tesseract results in strict left-to-right
// order that avoids using tesseract internal data structures.
// Author: Ray Smith
// Created: Fri Feb 26 14:32:09 PST 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "ltrresultiterator.h"
#include "allheaders.h"
#include "pageres.h"
#include "strngs.h"
#include "tesseractclass.h"
namespace tesseract {
LTRResultIterator::LTRResultIterator(PAGE_RES* page_res, Tesseract* tesseract,
int scale, int scaled_yres,
int rect_left, int rect_top,
int rect_width, int rect_height)
: PageIterator(page_res, tesseract, scale, scaled_yres,
rect_left, rect_top, rect_width, rect_height),
line_separator_("\n"),
paragraph_separator_("\n") {
}
LTRResultIterator::~LTRResultIterator() {
}
// Returns the null terminated UTF-8 encoded text string for the current
// object at the given level. Use delete [] to free after use.
char* LTRResultIterator::GetUTF8Text(PageIteratorLevel level) const {
if (it_->word() == NULL) return NULL; // Already at the end!
STRING text;
PAGE_RES_IT res_it(*it_);
WERD_CHOICE* best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
if (level == RIL_SYMBOL) {
text = res_it.word()->BestUTF8(blob_index_, false);
} else if (level == RIL_WORD) {
text = best_choice->unichar_string();
} else {
bool eol = false; // end of line?
bool eop = false; // end of paragraph?
do { // for each paragraph in a block
do { // for each text line in a paragraph
do { // for each word in a text line
best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
text += best_choice->unichar_string();
text += " ";
res_it.forward();
eol = res_it.row() != res_it.prev_row();
} while (!eol);
text.truncate_at(text.length() - 1);
text += line_separator_;
eop = res_it.block() != res_it.prev_block() ||
res_it.row()->row->para() != res_it.prev_row()->row->para();
} while (level != RIL_TEXTLINE && !eop);
if (eop) text += paragraph_separator_;
} while (level == RIL_BLOCK && res_it.block() == res_it.prev_block());
}
int length = text.length() + 1;
char* result = new char[length];
strncpy(result, text.string(), length);
return result;
}
// Set the string inserted at the end of each text line. "\n" by default.
void LTRResultIterator::SetLineSeparator(const char *new_line) {
line_separator_ = new_line;
}
// Set the string inserted at the end of each paragraph. "\n" by default.
void LTRResultIterator::SetParagraphSeparator(const char *new_para) {
paragraph_separator_ = new_para;
}
// Returns the mean confidence of the current object at the given level.
// The number should be interpreted as a percent probability. (0.0f-100.0f)
float LTRResultIterator::Confidence(PageIteratorLevel level) const {
if (it_->word() == NULL) return 0.0f; // Already at the end!
float mean_certainty = 0.0f;
int certainty_count = 0;
PAGE_RES_IT res_it(*it_);
WERD_CHOICE* best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
switch (level) {
case RIL_BLOCK:
do {
best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
mean_certainty += best_choice->certainty();
++certainty_count;
res_it.forward();
} while (res_it.block() == res_it.prev_block());
break;
case RIL_PARA:
do {
best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
mean_certainty += best_choice->certainty();
++certainty_count;
res_it.forward();
} while (res_it.block() == res_it.prev_block() &&
res_it.row()->row->para() == res_it.prev_row()->row->para());
break;
case RIL_TEXTLINE:
do {
best_choice = res_it.word()->best_choice;
ASSERT_HOST(best_choice != NULL);
mean_certainty += best_choice->certainty();
++certainty_count;
res_it.forward();
} while (res_it.row() == res_it.prev_row());
break;
case RIL_WORD:
mean_certainty += best_choice->certainty();
++certainty_count;
break;
case RIL_SYMBOL:
mean_certainty += best_choice->certainty(blob_index_);
++certainty_count;
}
if (certainty_count > 0) {
mean_certainty /= certainty_count;
float confidence = 100 + 5 * mean_certainty;
if (confidence < 0.0f) confidence = 0.0f;
if (confidence > 100.0f) confidence = 100.0f;
return confidence;
}
return 0.0f;
}
// Returns the font attributes of the current word. If iterating at a higher
// level object than words, eg textlines, then this will return the
// attributes of the first word in that textline.
// The actual return value is a string representing a font name. It points
// to an internal table and SHOULD NOT BE DELETED. Lifespan is the same as
// the iterator itself, ie rendered invalid by various members of
// TessBaseAPI, including Init, SetImage, End or deleting the TessBaseAPI.
// Pointsize is returned in printers points (1/72 inch.)
const char* LTRResultIterator::WordFontAttributes(bool* is_bold,
bool* is_italic,
bool* is_underlined,
bool* is_monospace,
bool* is_serif,
bool* is_smallcaps,
int* pointsize,
int* font_id) const {
if (it_->word() == NULL) return NULL; // Already at the end!
if (it_->word()->fontinfo == NULL) {
*font_id = -1;
return NULL; // No font information.
}
const FontInfo& font_info = *it_->word()->fontinfo;
*font_id = font_info.universal_id;
*is_bold = font_info.is_bold();
*is_italic = font_info.is_italic();
*is_underlined = false; // TODO(rays) fix this!
*is_monospace = font_info.is_fixed_pitch();
*is_serif = font_info.is_serif();
*is_smallcaps = it_->word()->small_caps;
float row_height = it_->row()->row->x_height() +
it_->row()->row->ascenders() - it_->row()->row->descenders();
// Convert from pixels to printers points.
*pointsize = scaled_yres_ > 0
? static_cast<int>(row_height * kPointsPerInch / scaled_yres_ + 0.5)
: 0;
return font_info.name;
}
// Returns the name of the language used to recognize this word.
const char* LTRResultIterator::WordRecognitionLanguage() const {
if (it_->word() == NULL || it_->word()->tesseract == NULL) return NULL;
return it_->word()->tesseract->lang.string();
}
// Return the overall directionality of this word.
StrongScriptDirection LTRResultIterator::WordDirection() const {
if (it_->word() == NULL) return DIR_NEUTRAL;
bool has_rtl = it_->word()->AnyRtlCharsInWord();
bool has_ltr = it_->word()->AnyLtrCharsInWord();
if (has_rtl && !has_ltr)
return DIR_RIGHT_TO_LEFT;
if (has_ltr && !has_rtl)
return DIR_LEFT_TO_RIGHT;
if (!has_ltr && !has_rtl)
return DIR_NEUTRAL;
return DIR_MIX;
}
// Returns true if the current word was found in a dictionary.
bool LTRResultIterator::WordIsFromDictionary() const {
if (it_->word() == NULL) return false; // Already at the end!
int permuter = it_->word()->best_choice->permuter();
return permuter == SYSTEM_DAWG_PERM || permuter == FREQ_DAWG_PERM ||
permuter == USER_DAWG_PERM;
}
// Returns true if the current word is numeric.
bool LTRResultIterator::WordIsNumeric() const {
if (it_->word() == NULL) return false; // Already at the end!
int permuter = it_->word()->best_choice->permuter();
return permuter == NUMBER_PERM;
}
// Returns true if the word contains blamer information.
bool LTRResultIterator::HasBlamerInfo() const {
return it_->word() != NULL && it_->word()->blamer_bundle != NULL &&
it_->word()->blamer_bundle->HasDebugInfo();
}
// Returns the pointer to ParamsTrainingBundle stored in the BlamerBundle
// of the current word.
const void *LTRResultIterator::GetParamsTrainingBundle() const {
return (it_->word() != NULL && it_->word()->blamer_bundle != NULL) ?
&(it_->word()->blamer_bundle->params_training_bundle()) : NULL;
}
// Returns the pointer to the string with blamer information for this word.
// Assumes that the word's blamer_bundle is not NULL.
const char *LTRResultIterator::GetBlamerDebug() const {
return it_->word()->blamer_bundle->debug().string();
}
// Returns the pointer to the string with misadaption information for this word.
// Assumes that the word's blamer_bundle is not NULL.
const char *LTRResultIterator::GetBlamerMisadaptionDebug() const {
return it_->word()->blamer_bundle->misadaption_debug().string();
}
// Returns true if a truth string was recorded for the current word.
bool LTRResultIterator::HasTruthString() const {
if (it_->word() == NULL) return false; // Already at the end!
if (it_->word()->blamer_bundle == NULL ||
it_->word()->blamer_bundle->NoTruth()) {
return false; // no truth information for this word
}
return true;
}
// Returns true if the given string is equivalent to the truth string for
// the current word.
bool LTRResultIterator::EquivalentToTruth(const char *str) const {
if (!HasTruthString()) return false;
ASSERT_HOST(it_->word()->uch_set != NULL);
WERD_CHOICE str_wd(str, *(it_->word()->uch_set));
return it_->word()->blamer_bundle->ChoiceIsCorrect(&str_wd);
}
// Returns the null terminated UTF-8 encoded truth string for the current word.
// Use delete [] to free after use.
char* LTRResultIterator::WordTruthUTF8Text() const {
if (!HasTruthString()) return NULL;
STRING truth_text = it_->word()->blamer_bundle->TruthString();
int length = truth_text.length() + 1;
char* result = new char[length];
strncpy(result, truth_text.string(), length);
return result;
}
// Returns the null terminated UTF-8 encoded normalized OCR string for the
// current word. Use delete [] to free after use.
char* LTRResultIterator::WordNormedUTF8Text() const {
if (it_->word() == NULL) return NULL; // Already at the end!
STRING ocr_text;
WERD_CHOICE* best_choice = it_->word()->best_choice;
const UNICHARSET *unicharset = it_->word()->uch_set;
ASSERT_HOST(best_choice != NULL);
for (int i = 0; i < best_choice->length(); ++i) {
ocr_text += unicharset->get_normed_unichar(best_choice->unichar_id(i));
}
int length = ocr_text.length() + 1;
char* result = new char[length];
strncpy(result, ocr_text.string(), length);
return result;
}
// Returns a pointer to serialized choice lattice.
// Fills lattice_size with the number of bytes in lattice data.
const char *LTRResultIterator::WordLattice(int *lattice_size) const {
if (it_->word() == NULL) return NULL; // Already at the end!
if (it_->word()->blamer_bundle == NULL) return NULL;
*lattice_size = it_->word()->blamer_bundle->lattice_size();
return it_->word()->blamer_bundle->lattice_data();
}
// Returns true if the current symbol is a superscript.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool LTRResultIterator::SymbolIsSuperscript() const {
if (cblob_it_ == NULL && it_->word() != NULL)
return it_->word()->best_choice->BlobPosition(blob_index_) ==
SP_SUPERSCRIPT;
return false;
}
// Returns true if the current symbol is a subscript.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool LTRResultIterator::SymbolIsSubscript() const {
if (cblob_it_ == NULL && it_->word() != NULL)
return it_->word()->best_choice->BlobPosition(blob_index_) == SP_SUBSCRIPT;
return false;
}
// Returns true if the current symbol is a dropcap.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool LTRResultIterator::SymbolIsDropcap() const {
if (cblob_it_ == NULL && it_->word() != NULL)
return it_->word()->best_choice->BlobPosition(blob_index_) == SP_DROPCAP;
return false;
}
ChoiceIterator::ChoiceIterator(const LTRResultIterator& result_it) {
ASSERT_HOST(result_it.it_->word() != NULL);
word_res_ = result_it.it_->word();
BLOB_CHOICE_LIST* choices = NULL;
if (word_res_->ratings != NULL)
choices = word_res_->GetBlobChoices(result_it.blob_index_);
if (choices != NULL && !choices->empty()) {
choice_it_ = new BLOB_CHOICE_IT(choices);
choice_it_->mark_cycle_pt();
} else {
choice_it_ = NULL;
}
}
ChoiceIterator::~ChoiceIterator() {
delete choice_it_;
}
// Moves to the next choice for the symbol and returns false if there
// are none left.
bool ChoiceIterator::Next() {
if (choice_it_ == NULL)
return false;
choice_it_->forward();
return !choice_it_->cycled_list();
}
// Returns the null terminated UTF-8 encoded text string for the current
// choice. Do NOT use delete [] to free after use.
const char* ChoiceIterator::GetUTF8Text() const {
if (choice_it_ == NULL)
return NULL;
UNICHAR_ID id = choice_it_->data()->unichar_id();
return word_res_->uch_set->id_to_unichar_ext(id);
}
// Returns the confidence of the current choice.
// The number should be interpreted as a percent probability. (0.0f-100.0f)
float ChoiceIterator::Confidence() const {
if (choice_it_ == NULL)
return 0.0f;
float confidence = 100 + 5 * choice_it_->data()->certainty();
if (confidence < 0.0f) confidence = 0.0f;
if (confidence > 100.0f) confidence = 100.0f;
return confidence;
}
} // namespace tesseract.
| C++ |
/******************************************************************
* File: fixspace.cpp (Formerly fixspace.c)
* Description: Implements a pass over the page res, exploring the alternative
* spacing possibilities, trying to use context to improve the
* word spacing
* Author: Phil Cheatle
* Created: Thu Oct 21 11:38:43 BST 1993
*
* (C) Copyright 1993, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <ctype.h>
#include "reject.h"
#include "statistc.h"
#include "control.h"
#include "fixspace.h"
#include "genblob.h"
#include "tessvars.h"
#include "tessbox.h"
#include "globals.h"
#include "tesseractclass.h"
#define PERFECT_WERDS 999
#define MAXSPACING 128 /*max expected spacing in pix */
namespace tesseract {
/**
* @name fix_fuzzy_spaces()
* Walk over the page finding sequences of words joined by fuzzy spaces. Extract
* them as a sublist, process the sublist to find the optimal arrangement of
* spaces then replace the sublist in the ROW_RES.
*
* @param monitor progress monitor
* @param word_count count of words in doc
* @param[out] page_res
*/
void Tesseract::fix_fuzzy_spaces(ETEXT_DESC *monitor,
inT32 word_count,
PAGE_RES *page_res) {
BLOCK_RES_IT block_res_it;
ROW_RES_IT row_res_it;
WERD_RES_IT word_res_it_from;
WERD_RES_IT word_res_it_to;
WERD_RES *word_res;
WERD_RES_LIST fuzzy_space_words;
inT16 new_length;
BOOL8 prevent_null_wd_fixsp; // DONT process blobless wds
inT32 word_index; // current word
block_res_it.set_to_list(&page_res->block_res_list);
word_index = 0;
for (block_res_it.mark_cycle_pt(); !block_res_it.cycled_list();
block_res_it.forward()) {
row_res_it.set_to_list(&block_res_it.data()->row_res_list);
for (row_res_it.mark_cycle_pt(); !row_res_it.cycled_list();
row_res_it.forward()) {
word_res_it_from.set_to_list(&row_res_it.data()->word_res_list);
while (!word_res_it_from.at_last()) {
word_res = word_res_it_from.data();
while (!word_res_it_from.at_last() &&
!(word_res->combination ||
word_res_it_from.data_relative(1)->word->flag(W_FUZZY_NON) ||
word_res_it_from.data_relative(1)->word->flag(W_FUZZY_SP))) {
fix_sp_fp_word(word_res_it_from, row_res_it.data()->row,
block_res_it.data()->block);
word_res = word_res_it_from.forward();
word_index++;
if (monitor != NULL) {
monitor->ocr_alive = TRUE;
monitor->progress = 90 + 5 * word_index / word_count;
if (monitor->deadline_exceeded() ||
(monitor->cancel != NULL &&
(*monitor->cancel)(monitor->cancel_this, stats_.dict_words)))
return;
}
}
if (!word_res_it_from.at_last()) {
word_res_it_to = word_res_it_from;
prevent_null_wd_fixsp =
word_res->word->cblob_list()->empty();
if (check_debug_pt(word_res, 60))
debug_fix_space_level.set_value(10);
word_res_it_to.forward();
word_index++;
if (monitor != NULL) {
monitor->ocr_alive = TRUE;
monitor->progress = 90 + 5 * word_index / word_count;
if (monitor->deadline_exceeded() ||
(monitor->cancel != NULL &&
(*monitor->cancel)(monitor->cancel_this, stats_.dict_words)))
return;
}
while (!word_res_it_to.at_last () &&
(word_res_it_to.data_relative(1)->word->flag(W_FUZZY_NON) ||
word_res_it_to.data_relative(1)->word->flag(W_FUZZY_SP))) {
if (check_debug_pt(word_res, 60))
debug_fix_space_level.set_value(10);
if (word_res->word->cblob_list()->empty())
prevent_null_wd_fixsp = TRUE;
word_res = word_res_it_to.forward();
}
if (check_debug_pt(word_res, 60))
debug_fix_space_level.set_value(10);
if (word_res->word->cblob_list()->empty())
prevent_null_wd_fixsp = TRUE;
if (prevent_null_wd_fixsp) {
word_res_it_from = word_res_it_to;
} else {
fuzzy_space_words.assign_to_sublist(&word_res_it_from,
&word_res_it_to);
fix_fuzzy_space_list(fuzzy_space_words,
row_res_it.data()->row,
block_res_it.data()->block);
new_length = fuzzy_space_words.length();
word_res_it_from.add_list_before(&fuzzy_space_words);
for (;
!word_res_it_from.at_last() && new_length > 0;
new_length--) {
word_res_it_from.forward();
}
}
if (test_pt)
debug_fix_space_level.set_value(0);
}
fix_sp_fp_word(word_res_it_from, row_res_it.data()->row,
block_res_it.data()->block);
// Last word in row
}
}
}
}
void Tesseract::fix_fuzzy_space_list(WERD_RES_LIST &best_perm,
ROW *row,
BLOCK* block) {
inT16 best_score;
WERD_RES_LIST current_perm;
inT16 current_score;
BOOL8 improved = FALSE;
best_score = eval_word_spacing(best_perm); // default score
dump_words(best_perm, best_score, 1, improved);
if (best_score != PERFECT_WERDS)
initialise_search(best_perm, current_perm);
while ((best_score != PERFECT_WERDS) && !current_perm.empty()) {
match_current_words(current_perm, row, block);
current_score = eval_word_spacing(current_perm);
dump_words(current_perm, current_score, 2, improved);
if (current_score > best_score) {
best_perm.clear();
best_perm.deep_copy(¤t_perm, &WERD_RES::deep_copy);
best_score = current_score;
improved = TRUE;
}
if (current_score < PERFECT_WERDS)
transform_to_next_perm(current_perm);
}
dump_words(best_perm, best_score, 3, improved);
}
} // namespace tesseract
void initialise_search(WERD_RES_LIST &src_list, WERD_RES_LIST &new_list) {
WERD_RES_IT src_it(&src_list);
WERD_RES_IT new_it(&new_list);
WERD_RES *src_wd;
WERD_RES *new_wd;
for (src_it.mark_cycle_pt(); !src_it.cycled_list(); src_it.forward()) {
src_wd = src_it.data();
if (!src_wd->combination) {
new_wd = WERD_RES::deep_copy(src_wd);
new_wd->combination = FALSE;
new_wd->part_of_combo = FALSE;
new_it.add_after_then_move(new_wd);
}
}
}
namespace tesseract {
void Tesseract::match_current_words(WERD_RES_LIST &words, ROW *row,
BLOCK* block) {
WERD_RES_IT word_it(&words);
WERD_RES *word;
// Since we are not using PAGE_RES to iterate over words, we need to update
// prev_word_best_choice_ before calling classify_word_pass2().
prev_word_best_choice_ = NULL;
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
word = word_it.data();
if ((!word->part_of_combo) && (word->box_word == NULL)) {
WordData word_data(block, row, word);
SetupWordPassN(2, &word_data);
classify_word_and_language(&Tesseract::classify_word_pass2, NULL,
&word_data);
}
prev_word_best_choice_ = word->best_choice;
}
}
/**
* @name eval_word_spacing()
* The basic measure is the number of characters in contextually confirmed
* words. (I.e the word is done)
* If all words are contextually confirmed the evaluation is deemed perfect.
*
* Some fiddles are done to handle "1"s as these are VERY frequent causes of
* fuzzy spaces. The problem with the basic measure is that "561 63" would score
* the same as "56163", though given our knowledge that the space is fuzzy, and
* that there is a "1" next to the fuzzy space, we need to ensure that "56163"
* is prefered.
*
* The solution is to NOT COUNT the score of any word which has a digit at one
* end and a "1Il" as the character the other side of the space.
*
* Conversly, any character next to a "1" within a word is counted as a positive
* score. Thus "561 63" would score 4 (3 chars in a numeric word plus 1 side of
* the "1" joined). "56163" would score 7 - all chars in a numeric word + 2
* sides of a "1" joined.
*
* The joined 1 rule is applied to any word REGARDLESS of contextual
* confirmation. Thus "PS7a71 3/7a" scores 1 (neither word is contexutally
* confirmed. The only score is from the joined 1. "PS7a713/7a" scores 2.
*
*/
inT16 Tesseract::eval_word_spacing(WERD_RES_LIST &word_res_list) {
WERD_RES_IT word_res_it(&word_res_list);
inT16 total_score = 0;
inT16 word_count = 0;
inT16 done_word_count = 0;
inT16 word_len;
inT16 i;
inT16 offset;
WERD_RES *word; // current word
inT16 prev_word_score = 0;
BOOL8 prev_word_done = FALSE;
BOOL8 prev_char_1 = FALSE; // prev ch a "1/I/l"?
BOOL8 prev_char_digit = FALSE; // prev ch 2..9 or 0
BOOL8 current_char_1 = FALSE;
BOOL8 current_word_ok_so_far;
STRING punct_chars = "!\"`',.:;";
BOOL8 prev_char_punct = FALSE;
BOOL8 current_char_punct = FALSE;
BOOL8 word_done = FALSE;
do {
word = word_res_it.data();
word_done = fixspace_thinks_word_done(word);
word_count++;
if (word->tess_failed) {
total_score += prev_word_score;
if (prev_word_done)
done_word_count++;
prev_word_score = 0;
prev_char_1 = FALSE;
prev_char_digit = FALSE;
prev_word_done = FALSE;
} else {
/*
Can we add the prev word score and potentially count this word?
Yes IF it didnt end in a 1 when the first char of this word is a digit
AND it didnt end in a digit when the first char of this word is a 1
*/
word_len = word->reject_map.length();
current_word_ok_so_far = FALSE;
if (!((prev_char_1 && digit_or_numeric_punct(word, 0)) ||
(prev_char_digit && (
(word_done &&
word->best_choice->unichar_lengths().string()[0] == 1 &&
word->best_choice->unichar_string()[0] == '1') ||
(!word_done && STRING(conflict_set_I_l_1).contains(
word->best_choice->unichar_string()[0])))))) {
total_score += prev_word_score;
if (prev_word_done)
done_word_count++;
current_word_ok_so_far = word_done;
}
if (current_word_ok_so_far) {
prev_word_done = TRUE;
prev_word_score = word_len;
} else {
prev_word_done = FALSE;
prev_word_score = 0;
}
/* Add 1 to total score for every joined 1 regardless of context and
rejtn */
for (i = 0, prev_char_1 = FALSE; i < word_len; i++) {
current_char_1 = word->best_choice->unichar_string()[i] == '1';
if (prev_char_1 || (current_char_1 && (i > 0)))
total_score++;
prev_char_1 = current_char_1;
}
/* Add 1 to total score for every joined punctuation regardless of context
and rejtn */
if (tessedit_prefer_joined_punct) {
for (i = 0, offset = 0, prev_char_punct = FALSE; i < word_len;
offset += word->best_choice->unichar_lengths()[i++]) {
current_char_punct =
punct_chars.contains(word->best_choice->unichar_string()[offset]);
if (prev_char_punct || (current_char_punct && i > 0))
total_score++;
prev_char_punct = current_char_punct;
}
}
prev_char_digit = digit_or_numeric_punct(word, word_len - 1);
for (i = 0, offset = 0; i < word_len - 1;
offset += word->best_choice->unichar_lengths()[i++]);
prev_char_1 =
((word_done && (word->best_choice->unichar_string()[offset] == '1'))
|| (!word_done && STRING(conflict_set_I_l_1).contains(
word->best_choice->unichar_string()[offset])));
}
/* Find next word */
do {
word_res_it.forward();
} while (word_res_it.data()->part_of_combo);
} while (!word_res_it.at_first());
total_score += prev_word_score;
if (prev_word_done)
done_word_count++;
if (done_word_count == word_count)
return PERFECT_WERDS;
else
return total_score;
}
BOOL8 Tesseract::digit_or_numeric_punct(WERD_RES *word, int char_position) {
int i;
int offset;
for (i = 0, offset = 0; i < char_position;
offset += word->best_choice->unichar_lengths()[i++]);
return (
word->uch_set->get_isdigit(
word->best_choice->unichar_string().string() + offset,
word->best_choice->unichar_lengths()[i]) ||
(word->best_choice->permuter() == NUMBER_PERM &&
STRING(numeric_punctuation).contains(
word->best_choice->unichar_string().string()[offset])));
}
} // namespace tesseract
/**
* @name transform_to_next_perm()
* Examines the current word list to find the smallest word gap size. Then walks
* the word list closing any gaps of this size by either inserted new
* combination words, or extending existing ones.
*
* The routine COULD be limited to stop it building words longer than N blobs.
*
* If there are no more gaps then it DELETES the entire list and returns the
* empty list to cause termination.
*/
void transform_to_next_perm(WERD_RES_LIST &words) {
WERD_RES_IT word_it(&words);
WERD_RES_IT prev_word_it(&words);
WERD_RES *word;
WERD_RES *prev_word;
WERD_RES *combo;
WERD *copy_word;
inT16 prev_right = -MAX_INT16;
TBOX box;
inT16 gap;
inT16 min_gap = MAX_INT16;
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
word = word_it.data();
if (!word->part_of_combo) {
box = word->word->bounding_box();
if (prev_right > -MAX_INT16) {
gap = box.left() - prev_right;
if (gap < min_gap)
min_gap = gap;
}
prev_right = box.right();
}
}
if (min_gap < MAX_INT16) {
prev_right = -MAX_INT16; // back to start
word_it.set_to_list(&words);
// Note: we can't use cycle_pt due to inserted combos at start of list.
for (; (prev_right == -MAX_INT16) || !word_it.at_first();
word_it.forward()) {
word = word_it.data();
if (!word->part_of_combo) {
box = word->word->bounding_box();
if (prev_right > -MAX_INT16) {
gap = box.left() - prev_right;
if (gap <= min_gap) {
prev_word = prev_word_it.data();
if (prev_word->combination) {
combo = prev_word;
} else {
/* Make a new combination and insert before
* the first word being joined. */
copy_word = new WERD;
*copy_word = *(prev_word->word);
// deep copy
combo = new WERD_RES(copy_word);
combo->combination = TRUE;
combo->x_height = prev_word->x_height;
prev_word->part_of_combo = TRUE;
prev_word_it.add_before_then_move(combo);
}
combo->word->set_flag(W_EOL, word->word->flag(W_EOL));
if (word->combination) {
combo->word->join_on(word->word);
// Move blobs to combo
// old combo no longer needed
delete word_it.extract();
} else {
// Copy current wd to combo
combo->copy_on(word);
word->part_of_combo = TRUE;
}
combo->done = FALSE;
combo->ClearResults();
} else {
prev_word_it = word_it; // catch up
}
}
prev_right = box.right();
}
}
} else {
words.clear(); // signal termination
}
}
namespace tesseract {
void Tesseract::dump_words(WERD_RES_LIST &perm, inT16 score,
inT16 mode, BOOL8 improved) {
WERD_RES_IT word_res_it(&perm);
if (debug_fix_space_level > 0) {
if (mode == 1) {
stats_.dump_words_str = "";
for (word_res_it.mark_cycle_pt(); !word_res_it.cycled_list();
word_res_it.forward()) {
if (!word_res_it.data()->part_of_combo) {
stats_.dump_words_str +=
word_res_it.data()->best_choice->unichar_string();
stats_.dump_words_str += ' ';
}
}
}
if (debug_fix_space_level > 1) {
switch (mode) {
case 1:
tprintf("EXTRACTED (%d): \"", score);
break;
case 2:
tprintf("TESTED (%d): \"", score);
break;
case 3:
tprintf("RETURNED (%d): \"", score);
break;
}
for (word_res_it.mark_cycle_pt(); !word_res_it.cycled_list();
word_res_it.forward()) {
if (!word_res_it.data()->part_of_combo) {
tprintf("%s/%1d ",
word_res_it.data()->best_choice->unichar_string().string(),
(int)word_res_it.data()->best_choice->permuter());
}
}
tprintf("\"\n");
} else if (improved) {
tprintf("FIX SPACING \"%s\" => \"", stats_.dump_words_str.string());
for (word_res_it.mark_cycle_pt(); !word_res_it.cycled_list();
word_res_it.forward()) {
if (!word_res_it.data()->part_of_combo) {
tprintf("%s/%1d ",
word_res_it.data()->best_choice->unichar_string().string(),
(int)word_res_it.data()->best_choice->permuter());
}
}
tprintf("\"\n");
}
}
}
BOOL8 Tesseract::fixspace_thinks_word_done(WERD_RES *word) {
if (word->done)
return TRUE;
/*
Use all the standard pass 2 conditions for mode 5 in set_done() in
reject.c BUT DONT REJECT IF THE WERD IS AMBIGUOUS - FOR SPACING WE DONT
CARE WHETHER WE HAVE of/at on/an etc.
*/
if (fixsp_done_mode > 0 &&
(word->tess_accepted ||
(fixsp_done_mode == 2 && word->reject_map.reject_count() == 0) ||
fixsp_done_mode == 3) &&
(strchr(word->best_choice->unichar_string().string(), ' ') == NULL) &&
((word->best_choice->permuter() == SYSTEM_DAWG_PERM) ||
(word->best_choice->permuter() == FREQ_DAWG_PERM) ||
(word->best_choice->permuter() == USER_DAWG_PERM) ||
(word->best_choice->permuter() == NUMBER_PERM))) {
return TRUE;
} else {
return FALSE;
}
}
/**
* @name fix_sp_fp_word()
* Test the current word to see if it can be split by deleting noise blobs. If
* so, do the business.
* Return with the iterator pointing to the same place if the word is unchanged,
* or the last of the replacement words.
*/
void Tesseract::fix_sp_fp_word(WERD_RES_IT &word_res_it, ROW *row,
BLOCK* block) {
WERD_RES *word_res;
WERD_RES_LIST sub_word_list;
WERD_RES_IT sub_word_list_it(&sub_word_list);
inT16 blob_index;
inT16 new_length;
float junk;
word_res = word_res_it.data();
if (word_res->word->flag(W_REP_CHAR) ||
word_res->combination ||
word_res->part_of_combo ||
!word_res->word->flag(W_DONT_CHOP))
return;
blob_index = worst_noise_blob(word_res, &junk);
if (blob_index < 0)
return;
if (debug_fix_space_level > 1) {
tprintf("FP fixspace working on \"%s\"\n",
word_res->best_choice->unichar_string().string());
}
word_res->word->rej_cblob_list()->sort(c_blob_comparator);
sub_word_list_it.add_after_stay_put(word_res_it.extract());
fix_noisy_space_list(sub_word_list, row, block);
new_length = sub_word_list.length();
word_res_it.add_list_before(&sub_word_list);
for (; !word_res_it.at_last() && new_length > 1; new_length--) {
word_res_it.forward();
}
}
void Tesseract::fix_noisy_space_list(WERD_RES_LIST &best_perm, ROW *row,
BLOCK* block) {
inT16 best_score;
WERD_RES_IT best_perm_it(&best_perm);
WERD_RES_LIST current_perm;
WERD_RES_IT current_perm_it(¤t_perm);
WERD_RES *old_word_res;
inT16 current_score;
BOOL8 improved = FALSE;
best_score = fp_eval_word_spacing(best_perm); // default score
dump_words(best_perm, best_score, 1, improved);
old_word_res = best_perm_it.data();
// Even deep_copy doesn't copy the underlying WERD unless its combination
// flag is true!.
old_word_res->combination = TRUE; // Kludge to force deep copy
current_perm_it.add_to_end(WERD_RES::deep_copy(old_word_res));
old_word_res->combination = FALSE; // Undo kludge
break_noisiest_blob_word(current_perm);
while (best_score != PERFECT_WERDS && !current_perm.empty()) {
match_current_words(current_perm, row, block);
current_score = fp_eval_word_spacing(current_perm);
dump_words(current_perm, current_score, 2, improved);
if (current_score > best_score) {
best_perm.clear();
best_perm.deep_copy(¤t_perm, &WERD_RES::deep_copy);
best_score = current_score;
improved = TRUE;
}
if (current_score < PERFECT_WERDS) {
break_noisiest_blob_word(current_perm);
}
}
dump_words(best_perm, best_score, 3, improved);
}
/**
* break_noisiest_blob_word()
* Find the word with the blob which looks like the worst noise.
* Break the word into two, deleting the noise blob.
*/
void Tesseract::break_noisiest_blob_word(WERD_RES_LIST &words) {
WERD_RES_IT word_it(&words);
WERD_RES_IT worst_word_it;
float worst_noise_score = 9999;
int worst_blob_index = -1; // Noisiest blob of noisiest wd
int blob_index; // of wds noisiest blob
float noise_score; // of wds noisiest blob
WERD_RES *word_res;
C_BLOB_IT blob_it;
C_BLOB_IT rej_cblob_it;
C_BLOB_LIST new_blob_list;
C_BLOB_IT new_blob_it;
C_BLOB_IT new_rej_cblob_it;
WERD *new_word;
inT16 start_of_noise_blob;
inT16 i;
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
blob_index = worst_noise_blob(word_it.data(), &noise_score);
if (blob_index > -1 && worst_noise_score > noise_score) {
worst_noise_score = noise_score;
worst_blob_index = blob_index;
worst_word_it = word_it;
}
}
if (worst_blob_index < 0) {
words.clear(); // signal termination
return;
}
/* Now split the worst_word_it */
word_res = worst_word_it.data();
/* Move blobs before noise blob to a new bloblist */
new_blob_it.set_to_list(&new_blob_list);
blob_it.set_to_list(word_res->word->cblob_list());
for (i = 0; i < worst_blob_index; i++, blob_it.forward()) {
new_blob_it.add_after_then_move(blob_it.extract());
}
start_of_noise_blob = blob_it.data()->bounding_box().left();
delete blob_it.extract(); // throw out noise blob
new_word = new WERD(&new_blob_list, word_res->word);
new_word->set_flag(W_EOL, FALSE);
word_res->word->set_flag(W_BOL, FALSE);
word_res->word->set_blanks(1); // After break
new_rej_cblob_it.set_to_list(new_word->rej_cblob_list());
rej_cblob_it.set_to_list(word_res->word->rej_cblob_list());
for (;
(!rej_cblob_it.empty() &&
(rej_cblob_it.data()->bounding_box().left() < start_of_noise_blob));
rej_cblob_it.forward()) {
new_rej_cblob_it.add_after_then_move(rej_cblob_it.extract());
}
WERD_RES* new_word_res = new WERD_RES(new_word);
new_word_res->combination = TRUE;
worst_word_it.add_before_then_move(new_word_res);
word_res->ClearResults();
}
inT16 Tesseract::worst_noise_blob(WERD_RES *word_res,
float *worst_noise_score) {
float noise_score[512];
int i;
int min_noise_blob; // 1st contender
int max_noise_blob; // last contender
int non_noise_count;
int worst_noise_blob; // Worst blob
float small_limit = kBlnXHeight * fixsp_small_outlines_size;
float non_noise_limit = kBlnXHeight * 0.8;
if (word_res->rebuild_word == NULL)
return -1; // Can't handle cube words.
// Normalised.
int blob_count = word_res->box_word->length();
ASSERT_HOST(blob_count <= 512);
if (blob_count < 5)
return -1; // too short to split
/* Get the noise scores for all blobs */
#ifndef SECURE_NAMES
if (debug_fix_space_level > 5)
tprintf("FP fixspace Noise metrics for \"%s\": ",
word_res->best_choice->unichar_string().string());
#endif
for (i = 0; i < blob_count && i < word_res->rebuild_word->NumBlobs(); i++) {
TBLOB* blob = word_res->rebuild_word->blobs[i];
if (word_res->reject_map[i].accepted())
noise_score[i] = non_noise_limit;
else
noise_score[i] = blob_noise_score(blob);
if (debug_fix_space_level > 5)
tprintf("%1.1f ", noise_score[i]);
}
if (debug_fix_space_level > 5)
tprintf("\n");
/* Now find the worst one which is far enough away from the end of the word */
non_noise_count = 0;
for (i = 0; i < blob_count && non_noise_count < fixsp_non_noise_limit; i++) {
if (noise_score[i] >= non_noise_limit) {
non_noise_count++;
}
}
if (non_noise_count < fixsp_non_noise_limit)
return -1;
min_noise_blob = i;
non_noise_count = 0;
for (i = blob_count - 1; i >= 0 && non_noise_count < fixsp_non_noise_limit;
i--) {
if (noise_score[i] >= non_noise_limit) {
non_noise_count++;
}
}
if (non_noise_count < fixsp_non_noise_limit)
return -1;
max_noise_blob = i;
if (min_noise_blob > max_noise_blob)
return -1;
*worst_noise_score = small_limit;
worst_noise_blob = -1;
for (i = min_noise_blob; i <= max_noise_blob; i++) {
if (noise_score[i] < *worst_noise_score) {
worst_noise_blob = i;
*worst_noise_score = noise_score[i];
}
}
return worst_noise_blob;
}
float Tesseract::blob_noise_score(TBLOB *blob) {
TBOX box; // BB of outline
inT16 outline_count = 0;
inT16 max_dimension;
inT16 largest_outline_dimension = 0;
for (TESSLINE* ol = blob->outlines; ol != NULL; ol= ol->next) {
outline_count++;
box = ol->bounding_box();
if (box.height() > box.width()) {
max_dimension = box.height();
} else {
max_dimension = box.width();
}
if (largest_outline_dimension < max_dimension)
largest_outline_dimension = max_dimension;
}
if (outline_count > 5) {
// penalise LOTS of blobs
largest_outline_dimension *= 2;
}
box = blob->bounding_box();
if (box.bottom() > kBlnBaselineOffset * 4 ||
box.top() < kBlnBaselineOffset / 2) {
// Lax blob is if high or low
largest_outline_dimension /= 2;
}
return largest_outline_dimension;
}
} // namespace tesseract
void fixspace_dbg(WERD_RES *word) {
TBOX box = word->word->bounding_box();
BOOL8 show_map_detail = FALSE;
inT16 i;
box.print();
tprintf(" \"%s\" ", word->best_choice->unichar_string().string());
tprintf("Blob count: %d (word); %d/%d (rebuild word)\n",
word->word->cblob_list()->length(),
word->rebuild_word->NumBlobs(),
word->box_word->length());
word->reject_map.print(debug_fp);
tprintf("\n");
if (show_map_detail) {
tprintf("\"%s\"\n", word->best_choice->unichar_string().string());
for (i = 0; word->best_choice->unichar_string()[i] != '\0'; i++) {
tprintf("**** \"%c\" ****\n", word->best_choice->unichar_string()[i]);
word->reject_map[i].full_print(debug_fp);
}
}
tprintf("Tess Accepted: %s\n", word->tess_accepted ? "TRUE" : "FALSE");
tprintf("Done flag: %s\n\n", word->done ? "TRUE" : "FALSE");
}
/**
* fp_eval_word_spacing()
* Evaluation function for fixed pitch word lists.
*
* Basically, count the number of "nice" characters - those which are in tess
* acceptable words or in dict words and are not rejected.
* Penalise any potential noise chars
*/
namespace tesseract {
inT16 Tesseract::fp_eval_word_spacing(WERD_RES_LIST &word_res_list) {
WERD_RES_IT word_it(&word_res_list);
WERD_RES *word;
inT16 word_length;
inT16 score = 0;
inT16 i;
float small_limit = kBlnXHeight * fixsp_small_outlines_size;
for (word_it.mark_cycle_pt(); !word_it.cycled_list(); word_it.forward()) {
word = word_it.data();
if (word->rebuild_word == NULL)
continue; // Can't handle cube words.
word_length = word->reject_map.length();
if (word->done ||
word->tess_accepted ||
word->best_choice->permuter() == SYSTEM_DAWG_PERM ||
word->best_choice->permuter() == FREQ_DAWG_PERM ||
word->best_choice->permuter() == USER_DAWG_PERM ||
safe_dict_word(word) > 0) {
int num_blobs = word->rebuild_word->NumBlobs();
UNICHAR_ID space = word->uch_set->unichar_to_id(" ");
for (i = 0; i < word->best_choice->length() && i < num_blobs; ++i) {
TBLOB* blob = word->rebuild_word->blobs[i];
if (word->best_choice->unichar_id(i) == space ||
blob_noise_score(blob) < small_limit) {
score -= 1; // penalise possibly erroneous non-space
} else if (word->reject_map[i].accepted()) {
score++;
}
}
}
}
if (score < 0)
score = 0;
return score;
}
} // namespace tesseract
| C++ |
/******************************************************************
* File: control.cpp (Formerly control.c)
* Description: Module-independent matcher controller.
* Author: Ray Smith
* Created: Thu Apr 23 11:09:58 BST 1992
* ReHacked: Tue Sep 22 08:42:49 BST 1992 Phil Cheatle
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <string.h>
#include <math.h>
#ifdef __UNIX__
#include <assert.h>
#include <unistd.h>
#include <errno.h>
#endif
#include <ctype.h>
#include "ocrclass.h"
#include "werdit.h"
#include "drawfx.h"
#include "tessbox.h"
#include "tessvars.h"
#include "pgedit.h"
#include "reject.h"
#include "fixspace.h"
#include "docqual.h"
#include "control.h"
#include "output.h"
#include "callcpp.h"
#include "globals.h"
#include "sorthelper.h"
#include "tesseractclass.h"
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#define MIN_FONT_ROW_COUNT 8
#define MAX_XHEIGHT_DIFF 3
const char* const kBackUpConfigFile = "tempconfigdata.config";
// Multiple of x-height to make a repeated word have spaces in it.
const double kRepcharGapThreshold = 0.5;
// Min believable x-height for any text when refitting as a fraction of
// original x-height
const double kMinRefitXHeightFraction = 0.5;
/**
* recog_pseudo_word
*
* Make a word from the selected blobs and run Tess on them.
*
* @param page_res recognise blobs
* @param selection_box within this box
*/
namespace tesseract {
void Tesseract::recog_pseudo_word(PAGE_RES* page_res,
TBOX &selection_box) {
PAGE_RES_IT* it = make_pseudo_word(page_res, selection_box);
if (it != NULL) {
recog_interactive(it);
it->DeleteCurrentWord();
delete it;
}
}
/**
* recog_interactive
*
* Recognize a single word in interactive mode.
*
* @param block block
* @param row row of word
* @param word_res word to recognise
*/
BOOL8 Tesseract::recog_interactive(PAGE_RES_IT* pr_it) {
inT16 char_qual;
inT16 good_char_qual;
WordData word_data(*pr_it);
SetupWordPassN(2, &word_data);
classify_word_and_language(&Tesseract::classify_word_pass2, pr_it,
&word_data);
if (tessedit_debug_quality_metrics) {
WERD_RES* word_res = pr_it->word();
word_char_quality(word_res, pr_it->row()->row, &char_qual, &good_char_qual);
tprintf("\n%d chars; word_blob_quality: %d; outline_errs: %d; "
"char_quality: %d; good_char_quality: %d\n",
word_res->reject_map.length(),
word_blob_quality(word_res, pr_it->row()->row),
word_outline_errs(word_res), char_qual, good_char_qual);
}
return TRUE;
}
// Helper function to check for a target word and handle it appropriately.
// Inspired by Jetsoft's requirement to process only single words on pass2
// and beyond.
// If word_config is not null:
// If the word_box and target_word_box overlap, read the word_config file
// else reset to previous config data.
// return true.
// else
// If the word_box and target_word_box overlap or pass <= 1, return true.
// Note that this function uses a fixed temporary file for storing the previous
// configs, so it is neither thread-safe, nor process-safe, but the assumption
// is that it will only be used for one debug window at a time.
//
// Since this function is used for debugging (and not to change OCR results)
// set only debug params from the word config file.
bool Tesseract::ProcessTargetWord(const TBOX& word_box,
const TBOX& target_word_box,
const char* word_config,
int pass) {
if (word_config != NULL) {
if (word_box.major_overlap(target_word_box)) {
if (backup_config_file_ == NULL) {
backup_config_file_ = kBackUpConfigFile;
FILE* config_fp = fopen(backup_config_file_, "wb");
ParamUtils::PrintParams(config_fp, params());
fclose(config_fp);
ParamUtils::ReadParamsFile(word_config,
SET_PARAM_CONSTRAINT_DEBUG_ONLY,
params());
}
} else {
if (backup_config_file_ != NULL) {
ParamUtils::ReadParamsFile(backup_config_file_,
SET_PARAM_CONSTRAINT_DEBUG_ONLY,
params());
backup_config_file_ = NULL;
}
}
} else if (pass > 1 && !word_box.major_overlap(target_word_box)) {
return false;
}
return true;
}
// If tesseract is to be run, sets the words up ready for it.
void Tesseract::SetupAllWordsPassN(int pass_n,
const TBOX* target_word_box,
const char* word_config,
PAGE_RES* page_res,
GenericVector<WordData>* words) {
// Prepare all the words.
PAGE_RES_IT page_res_it(page_res);
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
if (target_word_box == NULL ||
ProcessTargetWord(page_res_it.word()->word->bounding_box(),
*target_word_box, word_config, 1)) {
words->push_back(WordData(page_res_it));
}
}
// Setup all the words for recognition with polygonal approximation.
for (int w = 0; w < words->size(); ++w) {
SetupWordPassN(pass_n, &(*words)[w]);
if (w > 0) (*words)[w].prev_word = &(*words)[w - 1];
}
}
// Sets up the single word ready for whichever engine is to be run.
void Tesseract::SetupWordPassN(int pass_n, WordData* word) {
if (pass_n == 1 || !word->word->done) {
if (pass_n == 1) {
word->word->SetupForRecognition(unicharset, this, BestPix(),
tessedit_ocr_engine_mode, NULL,
classify_bln_numeric_mode,
textord_use_cjk_fp_model,
poly_allow_detailed_fx,
word->row, word->block);
} else if (pass_n == 2) {
// TODO(rays) Should we do this on pass1 too?
word->word->caps_height = 0.0;
if (word->word->x_height == 0.0f)
word->word->x_height = word->row->x_height();
}
for (int s = 0; s <= sub_langs_.size(); ++s) {
// The sub_langs_.size() entry is for the master language.
Tesseract* lang_t = s < sub_langs_.size() ? sub_langs_[s] : this;
WERD_RES* word_res = new WERD_RES;
word_res->InitForRetryRecognition(*word->word);
word->lang_words.push_back(word_res);
// Cube doesn't get setup for pass2.
if (pass_n == 1 || lang_t->tessedit_ocr_engine_mode != OEM_CUBE_ONLY) {
word_res->SetupForRecognition(
lang_t->unicharset, lang_t, BestPix(),
lang_t->tessedit_ocr_engine_mode, NULL,
lang_t->classify_bln_numeric_mode,
lang_t->textord_use_cjk_fp_model,
lang_t->poly_allow_detailed_fx, word->row, word->block);
}
}
}
}
// Runs word recognition on all the words.
bool Tesseract::RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor,
PAGE_RES_IT* pr_it,
GenericVector<WordData>* words) {
// TODO(rays) Before this loop can be parallelized (it would yield a massive
// speed-up) all remaining member globals need to be converted to local/heap
// (eg set_pass1 and set_pass2) and an intermediate adaption pass needs to be
// added. The results will be significantly different with adaption on, and
// deterioration will need investigation.
pr_it->restart_page();
for (int w = 0; w < words->size(); ++w) {
WordData* word = &(*words)[w];
if (w > 0) word->prev_word = &(*words)[w - 1];
if (monitor != NULL) {
monitor->ocr_alive = TRUE;
if (pass_n == 1)
monitor->progress = 30 + 50 * w / words->size();
else
monitor->progress = 80 + 10 * w / words->size();
if (monitor->deadline_exceeded() ||
(monitor->cancel != NULL && (*monitor->cancel)(monitor->cancel_this,
words->size()))) {
// Timeout. Fake out the rest of the words.
for (; w < words->size(); ++w) {
(*words)[w].word->SetupFake(unicharset);
}
return false;
}
}
if (word->word->tess_failed) {
int s;
for (s = 0; s < word->lang_words.size() &&
word->lang_words[s]->tess_failed; ++s) {}
// If all are failed, skip it. Image words are skipped by this test.
if (s > word->lang_words.size()) continue;
}
// Sync pr_it with the wth WordData.
while (pr_it->word() != NULL && pr_it->word() != word->word)
pr_it->forward();
ASSERT_HOST(pr_it->word() != NULL);
WordRecognizer recognizer = pass_n == 1 ? &Tesseract::classify_word_pass1
: &Tesseract::classify_word_pass2;
classify_word_and_language(recognizer, pr_it, word);
if (tessedit_dump_choices) {
tprintf("Pass%d: %s [%s]\n", pass_n,
word->word->best_choice->unichar_string().string(),
word->word->best_choice->debug_string().string());
}
pr_it->forward();
}
return true;
}
/**
* recog_all_words()
*
* Walk the page_res, recognizing all the words.
* If monitor is not null, it is used as a progress monitor/timeout/cancel.
* If dopasses is 0, all recognition passes are run,
* 1 just pass 1, 2 passes2 and higher.
* If target_word_box is not null, special things are done to words that
* overlap the target_word_box:
* if word_config is not null, the word config file is read for just the
* target word(s), otherwise, on pass 2 and beyond ONLY the target words
* are processed (Jetsoft modification.)
* Returns false if we cancelled prematurely.
*
* @param page_res page structure
* @param monitor progress monitor
* @param word_config word_config file
* @param target_word_box specifies just to extract a rectangle
* @param dopasses 0 - all, 1 just pass 1, 2 passes 2 and higher
*/
bool Tesseract::recog_all_words(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config,
int dopasses) {
PAGE_RES_IT page_res_it(page_res);
if (tessedit_minimal_rej_pass1) {
tessedit_test_adaption.set_value (TRUE);
tessedit_minimal_rejection.set_value (TRUE);
}
if (dopasses==0 || dopasses==1) {
page_res_it.restart_page();
// ****************** Pass 1 *******************
// Clear adaptive classifier at the beginning of the page if it is full.
// This is done only at the beginning of the page to ensure that the
// classifier is not reset at an arbitrary point while processing the page,
// which would cripple Passes 2+ if the reset happens towards the end of
// Pass 1 on a page with very difficult text.
// TODO(daria): preemptively clear the classifier if it is almost full.
if (AdaptiveClassifierIsFull()) ResetAdaptiveClassifierInternal();
// Now check the sub-langs as well.
for (int i = 0; i < sub_langs_.size(); ++i) {
if (sub_langs_[i]->AdaptiveClassifierIsFull())
sub_langs_[i]->ResetAdaptiveClassifierInternal();
}
// Set up all words ready for recognition, so that if parallelism is on
// all the input and output classes are ready to run the classifier.
GenericVector<WordData> words;
SetupAllWordsPassN(1, target_word_box, word_config, page_res, &words);
if (tessedit_parallelize) {
PrerecAllWordsPar(words);
}
stats_.word_count = words.size();
stats_.dict_words = 0;
stats_.doc_blob_quality = 0;
stats_.doc_outline_errs = 0;
stats_.doc_char_quality = 0;
stats_.good_char_count = 0;
stats_.doc_good_char_quality = 0;
most_recently_used_ = this;
// Run pass 1 word recognition.
if (!RecogAllWordsPassN(1, monitor, &page_res_it, &words)) return false;
// Pass 1 post-processing.
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
if (page_res_it.word()->word->flag(W_REP_CHAR)) {
fix_rep_char(&page_res_it);
continue;
}
// Count dict words.
if (page_res_it.word()->best_choice->permuter() == USER_DAWG_PERM)
++(stats_.dict_words);
// Update misadaption log (we only need to do it on pass 1, since
// adaption only happens on this pass).
if (page_res_it.word()->blamer_bundle != NULL &&
page_res_it.word()->blamer_bundle->misadaption_debug().length() > 0) {
page_res->misadaption_log.push_back(
page_res_it.word()->blamer_bundle->misadaption_debug());
}
}
}
if (dopasses == 1) return true;
// ****************** Pass 2 *******************
if (tessedit_tess_adaption_mode != 0x0 && !tessedit_test_adaption &&
AnyTessLang()) {
page_res_it.restart_page();
GenericVector<WordData> words;
SetupAllWordsPassN(2, target_word_box, word_config, page_res, &words);
if (tessedit_parallelize) {
PrerecAllWordsPar(words);
}
most_recently_used_ = this;
// Run pass 2 word recognition.
if (!RecogAllWordsPassN(2, monitor, &page_res_it, &words)) return false;
}
// The next passes can only be run if tesseract has been used, as cube
// doesn't set all the necessary outputs in WERD_RES.
if (AnyTessLang()) {
// ****************** Pass 3 *******************
// Fix fuzzy spaces.
set_global_loc_code(LOC_FUZZY_SPACE);
if (!tessedit_test_adaption && tessedit_fix_fuzzy_spaces
&& !tessedit_word_for_word && !right_to_left())
fix_fuzzy_spaces(monitor, stats_.word_count, page_res);
// ****************** Pass 4 *******************
if (tessedit_enable_dict_correction) dictionary_correction_pass(page_res);
if (tessedit_enable_bigram_correction) bigram_correction_pass(page_res);
// ****************** Pass 5,6 *******************
rejection_passes(page_res, monitor, target_word_box, word_config);
// ****************** Pass 7 *******************
// Cube combiner.
// If cube is loaded and its combiner is present, run it.
if (tessedit_ocr_engine_mode == OEM_TESSERACT_CUBE_COMBINED) {
run_cube_combiner(page_res);
}
// ****************** Pass 8 *******************
font_recognition_pass(page_res);
// ****************** Pass 9 *******************
// Check the correctness of the final results.
blamer_pass(page_res);
script_pos_pass(page_res);
}
// Write results pass.
set_global_loc_code(LOC_WRITE_RESULTS);
// This is now redundant, but retained commented so show how to obtain
// bounding boxes and style information.
// changed by jetsoft
// needed for dll to output memory structure
if ((dopasses == 0 || dopasses == 2) && (monitor || tessedit_write_unlv))
output_pass(page_res_it, target_word_box);
// end jetsoft
PageSegMode pageseg_mode = static_cast<PageSegMode>(
static_cast<int>(tessedit_pageseg_mode));
textord_.CleanupSingleRowResult(pageseg_mode, page_res);
// Remove empty words, as these mess up the result iterators.
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
WERD_RES* word = page_res_it.word();
if (word->best_choice == NULL || word->best_choice->length() == 0)
page_res_it.DeleteCurrentWord();
}
if (monitor != NULL) {
monitor->progress = 100;
}
return true;
}
void Tesseract::bigram_correction_pass(PAGE_RES *page_res) {
PAGE_RES_IT word_it(page_res);
WERD_RES *w_prev = NULL;
WERD_RES *w = word_it.word();
while (1) {
w_prev = w;
while (word_it.forward() != NULL &&
(!word_it.word() || word_it.word()->part_of_combo)) {
// advance word_it, skipping over parts of combos
}
if (!word_it.word()) break;
w = word_it.word();
if (!w || !w_prev || w->uch_set != w_prev->uch_set) {
continue;
}
if (w_prev->word->flag(W_REP_CHAR) || w->word->flag(W_REP_CHAR)) {
if (tessedit_bigram_debug) {
tprintf("Skipping because one of the words is W_REP_CHAR\n");
}
continue;
}
// Two words sharing the same language model, excellent!
GenericVector<WERD_CHOICE *> overrides_word1;
GenericVector<WERD_CHOICE *> overrides_word2;
STRING orig_w1_str = w_prev->best_choice->unichar_string();
STRING orig_w2_str = w->best_choice->unichar_string();
WERD_CHOICE prev_best(w->uch_set);
{
int w1start, w1end;
w_prev->best_choice->GetNonSuperscriptSpan(&w1start, &w1end);
prev_best = w_prev->best_choice->shallow_copy(w1start, w1end);
}
WERD_CHOICE this_best(w->uch_set);
{
int w2start, w2end;
w->best_choice->GetNonSuperscriptSpan(&w2start, &w2end);
this_best = w->best_choice->shallow_copy(w2start, w2end);
}
if (w->tesseract->getDict().valid_bigram(prev_best, this_best)) {
if (tessedit_bigram_debug) {
tprintf("Top choice \"%s %s\" verified by bigram model.\n",
orig_w1_str.string(), orig_w2_str.string());
}
continue;
}
if (tessedit_bigram_debug > 2) {
tprintf("Examining alt choices for \"%s %s\".\n",
orig_w1_str.string(), orig_w2_str.string());
}
if (tessedit_bigram_debug > 1) {
if (!w_prev->best_choices.singleton()) {
w_prev->PrintBestChoices();
}
if (!w->best_choices.singleton()) {
w->PrintBestChoices();
}
}
float best_rating = 0.0;
int best_idx = 0;
WERD_CHOICE_IT prev_it(&w_prev->best_choices);
for (prev_it.mark_cycle_pt(); !prev_it.cycled_list(); prev_it.forward()) {
WERD_CHOICE *p1 = prev_it.data();
WERD_CHOICE strip1(w->uch_set);
{
int p1start, p1end;
p1->GetNonSuperscriptSpan(&p1start, &p1end);
strip1 = p1->shallow_copy(p1start, p1end);
}
WERD_CHOICE_IT w_it(&w->best_choices);
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD_CHOICE *p2 = w_it.data();
WERD_CHOICE strip2(w->uch_set);
{
int p2start, p2end;
p2->GetNonSuperscriptSpan(&p2start, &p2end);
strip2 = p2->shallow_copy(p2start, p2end);
}
if (w->tesseract->getDict().valid_bigram(strip1, strip2)) {
overrides_word1.push_back(p1);
overrides_word2.push_back(p2);
if (overrides_word1.size() == 1 ||
p1->rating() + p2->rating() < best_rating) {
best_rating = p1->rating() + p2->rating();
best_idx = overrides_word1.size() - 1;
}
}
}
}
if (overrides_word1.size() >= 1) {
// Excellent, we have some bigram matches.
if (EqualIgnoringCaseAndTerminalPunct(*w_prev->best_choice,
*overrides_word1[best_idx]) &&
EqualIgnoringCaseAndTerminalPunct(*w->best_choice,
*overrides_word2[best_idx])) {
if (tessedit_bigram_debug > 1) {
tprintf("Top choice \"%s %s\" verified (sans case) by bigram "
"model.\n", orig_w1_str.string(), orig_w2_str.string());
}
continue;
}
STRING new_w1_str = overrides_word1[best_idx]->unichar_string();
STRING new_w2_str = overrides_word2[best_idx]->unichar_string();
if (new_w1_str != orig_w1_str) {
w_prev->ReplaceBestChoice(overrides_word1[best_idx]);
}
if (new_w2_str != orig_w2_str) {
w->ReplaceBestChoice(overrides_word2[best_idx]);
}
if (tessedit_bigram_debug > 0) {
STRING choices_description;
int num_bigram_choices
= overrides_word1.size() * overrides_word2.size();
if (num_bigram_choices == 1) {
choices_description = "This was the unique bigram choice.";
} else {
if (tessedit_bigram_debug > 1) {
STRING bigrams_list;
const int kMaxChoicesToPrint = 20;
for (int i = 0; i < overrides_word1.size() &&
i < kMaxChoicesToPrint; i++) {
if (i > 0) { bigrams_list += ", "; }
WERD_CHOICE *p1 = overrides_word1[i];
WERD_CHOICE *p2 = overrides_word2[i];
bigrams_list += p1->unichar_string() + " " + p2->unichar_string();
if (i == kMaxChoicesToPrint) {
bigrams_list += " ...";
}
}
choices_description = "There were many choices: {";
choices_description += bigrams_list;
choices_description += "}";
} else {
choices_description.add_str_int("There were ", num_bigram_choices);
choices_description += " compatible bigrams.";
}
}
tprintf("Replaced \"%s %s\" with \"%s %s\" with bigram model. %s\n",
orig_w1_str.string(), orig_w2_str.string(),
new_w1_str.string(), new_w2_str.string(),
choices_description.string());
}
}
}
}
void Tesseract::rejection_passes(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config) {
PAGE_RES_IT page_res_it(page_res);
// ****************** Pass 5 *******************
// Gather statistics on rejects.
int word_index = 0;
while (!tessedit_test_adaption && page_res_it.word() != NULL) {
set_global_loc_code(LOC_MM_ADAPT);
WERD_RES* word = page_res_it.word();
word_index++;
if (monitor != NULL) {
monitor->ocr_alive = TRUE;
monitor->progress = 95 + 5 * word_index / stats_.word_count;
}
if (word->rebuild_word == NULL) {
// Word was not processed by tesseract.
page_res_it.forward();
continue;
}
check_debug_pt(word, 70);
// changed by jetsoft
// specific to its needs to extract one word when need
if (target_word_box &&
!ProcessTargetWord(word->word->bounding_box(),
*target_word_box, word_config, 4)) {
page_res_it.forward();
continue;
}
// end jetsoft
page_res_it.rej_stat_word();
int chars_in_word = word->reject_map.length();
int rejects_in_word = word->reject_map.reject_count();
int blob_quality = word_blob_quality(word, page_res_it.row()->row);
stats_.doc_blob_quality += blob_quality;
int outline_errs = word_outline_errs(word);
stats_.doc_outline_errs += outline_errs;
inT16 all_char_quality;
inT16 accepted_all_char_quality;
word_char_quality(word, page_res_it.row()->row,
&all_char_quality, &accepted_all_char_quality);
stats_.doc_char_quality += all_char_quality;
uinT8 permuter_type = word->best_choice->permuter();
if ((permuter_type == SYSTEM_DAWG_PERM) ||
(permuter_type == FREQ_DAWG_PERM) ||
(permuter_type == USER_DAWG_PERM)) {
stats_.good_char_count += chars_in_word - rejects_in_word;
stats_.doc_good_char_quality += accepted_all_char_quality;
}
check_debug_pt(word, 80);
if (tessedit_reject_bad_qual_wds &&
(blob_quality == 0) && (outline_errs >= chars_in_word))
word->reject_map.rej_word_bad_quality();
check_debug_pt(word, 90);
page_res_it.forward();
}
if (tessedit_debug_quality_metrics) {
tprintf
("QUALITY: num_chs= %d num_rejs= %d %5.3f blob_qual= %d %5.3f"
" outline_errs= %d %5.3f char_qual= %d %5.3f good_ch_qual= %d %5.3f\n",
page_res->char_count, page_res->rej_count,
page_res->rej_count / static_cast<float>(page_res->char_count),
stats_.doc_blob_quality,
stats_.doc_blob_quality / static_cast<float>(page_res->char_count),
stats_.doc_outline_errs,
stats_.doc_outline_errs / static_cast<float>(page_res->char_count),
stats_.doc_char_quality,
stats_.doc_char_quality / static_cast<float>(page_res->char_count),
stats_.doc_good_char_quality,
(stats_.good_char_count > 0) ?
(stats_.doc_good_char_quality /
static_cast<float>(stats_.good_char_count)) : 0.0);
}
BOOL8 good_quality_doc =
((page_res->rej_count / static_cast<float>(page_res->char_count)) <=
quality_rej_pc) &&
(stats_.doc_blob_quality / static_cast<float>(page_res->char_count) >=
quality_blob_pc) &&
(stats_.doc_outline_errs / static_cast<float>(page_res->char_count) <=
quality_outline_pc) &&
(stats_.doc_char_quality / static_cast<float>(page_res->char_count) >=
quality_char_pc);
// ****************** Pass 6 *******************
// Do whole document or whole block rejection pass
if (!tessedit_test_adaption) {
set_global_loc_code(LOC_DOC_BLK_REJ);
quality_based_rejection(page_res_it, good_quality_doc);
}
}
void Tesseract::blamer_pass(PAGE_RES* page_res) {
if (!wordrec_run_blamer) return;
PAGE_RES_IT page_res_it(page_res);
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
WERD_RES *word = page_res_it.word();
BlamerBundle::LastChanceBlame(wordrec_debug_blamer, word);
page_res->blame_reasons[word->blamer_bundle->incorrect_result_reason()]++;
}
tprintf("Blame reasons:\n");
for (int bl = 0; bl < IRR_NUM_REASONS; ++bl) {
tprintf("%s %d\n", BlamerBundle::IncorrectReasonName(
static_cast<IncorrectResultReason>(bl)),
page_res->blame_reasons[bl]);
}
if (page_res->misadaption_log.length() > 0) {
tprintf("Misadaption log:\n");
for (int i = 0; i < page_res->misadaption_log.length(); ++i) {
tprintf("%s\n", page_res->misadaption_log[i].string());
}
}
}
// Sets script positions and detects smallcaps on all output words.
void Tesseract::script_pos_pass(PAGE_RES* page_res) {
PAGE_RES_IT page_res_it(page_res);
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
WERD_RES* word = page_res_it.word();
if (word->word->flag(W_REP_CHAR)) {
page_res_it.forward();
continue;
}
float x_height = page_res_it.block()->block->x_height();
float word_x_height = word->x_height;
if (word_x_height < word->best_choice->min_x_height() ||
word_x_height > word->best_choice->max_x_height()) {
word_x_height = (word->best_choice->min_x_height() +
word->best_choice->max_x_height()) / 2.0f;
}
// Test for small caps. Word capheight must be close to block xheight,
// and word must contain no lower case letters, and at least one upper case.
double small_cap_xheight = x_height * kXHeightCapRatio;
double small_cap_delta = (x_height - small_cap_xheight) / 2.0;
if (word->uch_set->script_has_xheight() &&
small_cap_xheight - small_cap_delta <= word_x_height &&
word_x_height <= small_cap_xheight + small_cap_delta) {
// Scan for upper/lower.
int num_upper = 0;
int num_lower = 0;
for (int i = 0; i < word->best_choice->length(); ++i) {
if (word->uch_set->get_isupper(word->best_choice->unichar_id(i)))
++num_upper;
else if (word->uch_set->get_islower(word->best_choice->unichar_id(i)))
++num_lower;
}
if (num_upper > 0 && num_lower == 0)
word->small_caps = true;
}
word->SetScriptPositions();
}
}
// Factored helper considers the indexed word and updates all the pointed
// values.
static void EvaluateWord(const PointerVector<WERD_RES>& words, int index,
float* rating, float* certainty, bool* bad,
bool* valid_permuter, int* right, int* next_left) {
*right = -MAX_INT32;
*next_left = MAX_INT32;
if (index < words.size()) {
WERD_CHOICE* choice = words[index]->best_choice;
if (choice == NULL) {
*bad = true;
} else {
*rating += choice->rating();
*certainty = MIN(*certainty, choice->certainty());
if (!Dict::valid_word_permuter(choice->permuter(), false))
*valid_permuter = false;
}
*right = words[index]->word->bounding_box().right();
if (index + 1 < words.size())
*next_left = words[index + 1]->word->bounding_box().left();
} else {
*valid_permuter = false;
*bad = true;
}
}
// Helper chooses the best combination of words, transferring good ones from
// new_words to best_words. To win, a new word must have (better rating and
// certainty) or (better permuter status and rating within rating ratio and
// certainty within certainty margin) than current best.
// All the new_words are consumed (moved to best_words or deleted.)
// The return value is the number of new_words used minus the number of
// best_words that remain in the output.
static int SelectBestWords(double rating_ratio,
double certainty_margin,
bool debug,
PointerVector<WERD_RES>* new_words,
PointerVector<WERD_RES>* best_words) {
// Process the smallest groups of words that have an overlapping word
// boundary at the end.
GenericVector<WERD_RES*> out_words;
// Index into each word vector (best, new).
int b = 0, n = 0;
int num_best = 0, num_new = 0;
while (b < best_words->size() || n < new_words->size()) {
// Start of the current run in each.
int start_b = b, start_n = n;
// Rating of the current run in each.
float b_rating = 0.0f, n_rating = 0.0f;
// Certainty of the current run in each.
float b_certainty = 0.0f, n_certainty = 0.0f;
// True if any word is missing its best choice.
bool b_bad = false, n_bad = false;
// True if all words have a valid permuter.
bool b_valid_permuter = true, n_valid_permuter = true;
while (b < best_words->size() || n < new_words->size()) {
int b_right = -MAX_INT32;
int next_b_left = MAX_INT32;
EvaluateWord(*best_words, b, &b_rating, &b_certainty, &b_bad,
&b_valid_permuter, &b_right, &next_b_left);
int n_right = -MAX_INT32;
int next_n_left = MAX_INT32;
EvaluateWord(*new_words, n, &n_rating, &n_certainty, &n_bad,
&n_valid_permuter, &n_right, &next_n_left);
if (MAX(b_right, n_right) < MIN(next_b_left, next_n_left)) {
// The word breaks overlap. [start_b,b] and [start_n, n] match.
break;
}
// Keep searching for the matching word break.
if ((b_right < n_right && b < best_words->size()) ||
n == new_words->size())
++b;
else
++n;
}
bool new_better = false;
if (!n_bad && (b_bad || (n_certainty > b_certainty &&
n_rating < b_rating) ||
(!b_valid_permuter && n_valid_permuter &&
n_rating < b_rating * rating_ratio &&
n_certainty > b_certainty - certainty_margin))) {
// New is better.
for (int i = start_n; i <= n; ++i) {
out_words.push_back((*new_words)[i]);
(*new_words)[i] = NULL;
++num_new;
}
new_better = true;
} else if (!b_bad) {
// Current best is better.
for (int i = start_b; i <= b; ++i) {
out_words.push_back((*best_words)[i]);
(*best_words)[i] = NULL;
++num_best;
}
}
int end_b = b < best_words->size() ? b + 1 : b;
int end_n = n < new_words->size() ? n + 1 : n;
if (debug) {
tprintf("%d new words %s than %d old words: r: %g v %g c: %g v %g"
" valid dict: %d v %d\n",
end_n - start_n, new_better ? "better" : "worse",
end_b - start_b, n_rating, b_rating,
n_certainty, b_certainty, n_valid_permuter, b_valid_permuter);
}
// Move on to the next group.
b = end_b;
n = end_n;
}
// Transfer from out_words to best_words.
best_words->clear();
for (int i = 0; i < out_words.size(); ++i)
best_words->push_back(out_words[i]);
return num_new - num_best;
}
// Helper to recognize the word using the given (language-specific) tesseract.
// Returns positive if this recognizer found more new best words than the
// number kept from best_words.
int Tesseract::RetryWithLanguage(const WordData& word_data,
WordRecognizer recognizer,
WERD_RES** in_word,
PointerVector<WERD_RES>* best_words) {
bool debug = classify_debug_level || cube_debug_level;
if (debug) {
tprintf("Trying word using lang %s, oem %d\n",
lang.string(), static_cast<int>(tessedit_ocr_engine_mode));
}
// Run the recognizer on the word.
PointerVector<WERD_RES> new_words;
(this->*recognizer)(word_data, in_word, &new_words);
if (new_words.empty()) {
// Transfer input word to new_words, as the classifier must have put
// the result back in the input.
new_words.push_back(*in_word);
*in_word = NULL;
}
if (debug) {
for (int i = 0; i < new_words.size(); ++i)
new_words[i]->DebugTopChoice("Lang result");
}
// Initial version is a bit of a hack based on better certainty and rating
// (to reduce false positives from cube) or a dictionary vs non-dictionary
// word.
return SelectBestWords(classify_max_rating_ratio,
classify_max_certainty_margin,
debug, &new_words, best_words);
}
// Helper returns true if all the words are acceptable.
static bool WordsAcceptable(const PointerVector<WERD_RES>& words) {
for (int w = 0; w < words.size(); ++w) {
if (words[w]->tess_failed || !words[w]->tess_accepted) return false;
}
return true;
}
// Generic function for classifying a word. Can be used either for pass1 or
// pass2 according to the function passed to recognizer.
// word_data holds the word to be recognized, and its block and row, and
// pr_it points to the word as well, in case we are running LSTM and it wants
// to output multiple words.
// Recognizes in the current language, and if successful that is all.
// If recognition was not successful, tries all available languages until
// it gets a successful result or runs out of languages. Keeps the best result.
void Tesseract::classify_word_and_language(WordRecognizer recognizer,
PAGE_RES_IT* pr_it,
WordData* word_data) {
// Best result so far.
PointerVector<WERD_RES> best_words;
// Points to the best result. May be word or in lang_words.
WERD_RES* word = word_data->word;
clock_t start_t = clock();
if (classify_debug_level || cube_debug_level) {
tprintf("%s word with lang %s at:",
word->done ? "Already done" : "Processing",
most_recently_used_->lang.string());
word->word->bounding_box().print();
}
if (word->done) {
// If done on pass1, leave it as-is.
if (!word->tess_failed)
most_recently_used_ = word->tesseract;
return;
}
int sub = sub_langs_.size();
if (most_recently_used_ != this) {
// Get the index of the most_recently_used_.
for (sub = 0; sub < sub_langs_.size() &&
most_recently_used_ != sub_langs_[sub]; ++sub) {}
}
most_recently_used_->RetryWithLanguage(
*word_data, recognizer, &word_data->lang_words[sub], &best_words);
Tesseract* best_lang_tess = most_recently_used_;
if (!WordsAcceptable(best_words)) {
// Try all the other languages to see if they are any better.
if (most_recently_used_ != this &&
this->RetryWithLanguage(*word_data, recognizer,
&word_data->lang_words[sub_langs_.size()],
&best_words) > 0) {
best_lang_tess = this;
}
for (int i = 0; !WordsAcceptable(best_words) && i < sub_langs_.size();
++i) {
if (most_recently_used_ != sub_langs_[i] &&
sub_langs_[i]->RetryWithLanguage(*word_data, recognizer,
&word_data->lang_words[i],
&best_words) > 0) {
best_lang_tess = sub_langs_[i];
}
}
}
most_recently_used_ = best_lang_tess;
if (!best_words.empty()) {
if (best_words.size() == 1 && !best_words[0]->combination) {
// Move the best single result to the main word.
word_data->word->ConsumeWordResults(best_words[0]);
} else {
// Words came from LSTM, and must be moved to the PAGE_RES properly.
word_data->word = best_words.back();
pr_it->ReplaceCurrentWord(&best_words);
}
ASSERT_HOST(word_data->word->box_word != NULL);
} else {
tprintf("no best words!!\n");
}
clock_t ocr_t = clock();
if (tessedit_timing_debug) {
tprintf("%s (ocr took %.2f sec)\n",
word->best_choice->unichar_string().string(),
static_cast<double>(ocr_t-start_t)/CLOCKS_PER_SEC);
}
}
/**
* classify_word_pass1
*
* Baseline normalize the word and pass it to Tess.
*/
void Tesseract::classify_word_pass1(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words) {
ROW* row = word_data.row;
BLOCK* block = word_data.block;
prev_word_best_choice_ = word_data.prev_word != NULL
? word_data.prev_word->word->best_choice : NULL;
// If we only intend to run cube - run it and return.
if (tessedit_ocr_engine_mode == OEM_CUBE_ONLY) {
cube_word_pass1(block, row, *in_word);
return;
}
WERD_RES* word = *in_word;
match_word_pass_n(1, word, row, block);
if (!word->tess_failed && !word->word->flag(W_REP_CHAR)) {
word->tess_would_adapt = AdaptableWord(word);
bool adapt_ok = word_adaptable(word, tessedit_tess_adaption_mode);
if (adapt_ok) {
// Send word to adaptive classifier for training.
word->BestChoiceToCorrectText();
LearnWord(NULL, word);
// Mark misadaptions if running blamer.
if (word->blamer_bundle != NULL) {
word->blamer_bundle->SetMisAdaptionDebug(word->best_choice,
wordrec_debug_blamer);
}
}
if (tessedit_enable_doc_dict && !word->IsAmbiguous())
tess_add_doc_word(word->best_choice);
}
}
// Helper to report the result of the xheight fix.
void Tesseract::ReportXhtFixResult(bool accept_new_word, float new_x_ht,
WERD_RES* word, WERD_RES* new_word) {
tprintf("New XHT Match:%s = %s ",
word->best_choice->unichar_string().string(),
word->best_choice->debug_string().string());
word->reject_map.print(debug_fp);
tprintf(" -> %s = %s ",
new_word->best_choice->unichar_string().string(),
new_word->best_choice->debug_string().string());
new_word->reject_map.print(debug_fp);
tprintf(" %s->%s %s %s\n",
word->guessed_x_ht ? "GUESS" : "CERT",
new_word->guessed_x_ht ? "GUESS" : "CERT",
new_x_ht > 0.1 ? "STILL DOUBT" : "OK",
accept_new_word ? "ACCEPTED" : "");
}
// Run the x-height fix-up, based on min/max top/bottom information in
// unicharset.
// Returns true if the word was changed.
// See the comment in fixxht.cpp for a description of the overall process.
bool Tesseract::TrainedXheightFix(WERD_RES *word, BLOCK* block, ROW *row) {
bool accept_new_x_ht = false;
int original_misfits = CountMisfitTops(word);
if (original_misfits == 0)
return false;
float new_x_ht = ComputeCompatibleXheight(word);
if (new_x_ht >= kMinRefitXHeightFraction * word->x_height) {
WERD_RES new_x_ht_word(word->word);
if (word->blamer_bundle != NULL) {
new_x_ht_word.blamer_bundle = new BlamerBundle();
new_x_ht_word.blamer_bundle->CopyTruth(*(word->blamer_bundle));
}
new_x_ht_word.x_height = new_x_ht;
new_x_ht_word.caps_height = 0.0;
new_x_ht_word.SetupForRecognition(
unicharset, this, BestPix(), tessedit_ocr_engine_mode, NULL,
classify_bln_numeric_mode, textord_use_cjk_fp_model,
poly_allow_detailed_fx, row, block);
match_word_pass_n(2, &new_x_ht_word, row, block);
if (!new_x_ht_word.tess_failed) {
int new_misfits = CountMisfitTops(&new_x_ht_word);
if (debug_x_ht_level >= 1) {
tprintf("Old misfits=%d with x-height %f, new=%d with x-height %f\n",
original_misfits, word->x_height,
new_misfits, new_x_ht);
tprintf("Old rating= %f, certainty=%f, new=%f, %f\n",
word->best_choice->rating(), word->best_choice->certainty(),
new_x_ht_word.best_choice->rating(),
new_x_ht_word.best_choice->certainty());
}
// The misfits must improve and either the rating or certainty.
accept_new_x_ht = new_misfits < original_misfits &&
(new_x_ht_word.best_choice->certainty() >
word->best_choice->certainty() ||
new_x_ht_word.best_choice->rating() <
word->best_choice->rating());
if (debug_x_ht_level >= 1) {
ReportXhtFixResult(accept_new_x_ht, new_x_ht, word, &new_x_ht_word);
}
}
if (accept_new_x_ht) {
word->ConsumeWordResults(&new_x_ht_word);
return true;
}
}
return false;
}
/**
* classify_word_pass2
*
* Control what to do with the word in pass 2
*/
void Tesseract::classify_word_pass2(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words) {
// Return if we do not want to run Tesseract.
if (tessedit_ocr_engine_mode != OEM_TESSERACT_ONLY &&
tessedit_ocr_engine_mode != OEM_TESSERACT_CUBE_COMBINED &&
word_data.word->best_choice != NULL)
return;
if (tessedit_ocr_engine_mode == OEM_CUBE_ONLY) {
return;
}
ROW* row = word_data.row;
BLOCK* block = word_data.block;
WERD_RES* word = *in_word;
prev_word_best_choice_ = word_data.prev_word != NULL
? word_data.prev_word->word->best_choice : NULL;
set_global_subloc_code(SUBLOC_NORM);
check_debug_pt(word, 30);
if (!word->done) {
word->caps_height = 0.0;
if (word->x_height == 0.0f)
word->x_height = row->x_height();
match_word_pass_n(2, word, row, block);
check_debug_pt(word, 40);
}
SubAndSuperscriptFix(word);
if (!word->tess_failed && !word->word->flag(W_REP_CHAR)) {
if (unicharset.top_bottom_useful() && unicharset.script_has_xheight() &&
block->classify_rotation().y() == 0.0f) {
// Use the tops and bottoms since they are available.
TrainedXheightFix(word, block, row);
}
set_global_subloc_code(SUBLOC_NORM);
}
#ifndef GRAPHICS_DISABLED
if (tessedit_display_outwords) {
if (fx_win == NULL)
create_fx_win();
clear_fx_win();
word->rebuild_word->plot(fx_win);
TBOX wbox = word->rebuild_word->bounding_box();
fx_win->ZoomToRectangle(wbox.left(), wbox.top(),
wbox.right(), wbox.bottom());
ScrollView::Update();
}
#endif
set_global_subloc_code(SUBLOC_NORM);
check_debug_pt(word, 50);
}
/**
* match_word_pass2
*
* Baseline normalize the word and pass it to Tess.
*/
void Tesseract::match_word_pass_n(int pass_n, WERD_RES *word,
ROW *row, BLOCK* block) {
if (word->tess_failed) return;
tess_segment_pass_n(pass_n, word);
if (!word->tess_failed) {
if (!word->word->flag (W_REP_CHAR)) {
word->fix_quotes();
if (tessedit_fix_hyphens)
word->fix_hyphens();
/* Dont trust fix_quotes! - though I think I've fixed the bug */
if (word->best_choice->length() != word->box_word->length()) {
tprintf("POST FIX_QUOTES FAIL String:\"%s\"; Strlen=%d;"
" #Blobs=%d\n",
word->best_choice->debug_string().string(),
word->best_choice->length(),
word->box_word->length());
}
word->tess_accepted = tess_acceptable_word(word);
// Also sets word->done flag
make_reject_map(word, row, pass_n);
}
}
set_word_fonts(word);
ASSERT_HOST(word->raw_choice != NULL);
}
// Helper to return the best rated BLOB_CHOICE in the whole word that matches
// the given char_id, or NULL if none can be found.
static BLOB_CHOICE* FindBestMatchingChoice(UNICHAR_ID char_id,
WERD_RES* word_res) {
// Find the corresponding best BLOB_CHOICE from any position in the word_res.
BLOB_CHOICE* best_choice = NULL;
for (int i = 0; i < word_res->best_choice->length(); ++i) {
BLOB_CHOICE* choice = FindMatchingChoice(char_id,
word_res->GetBlobChoices(i));
if (choice != NULL) {
if (best_choice == NULL || choice->rating() < best_choice->rating())
best_choice = choice;
}
}
return best_choice;
}
// Helper to insert blob_choice in each location in the leader word if there is
// no matching BLOB_CHOICE there already, and correct any incorrect results
// in the best_choice.
static void CorrectRepcharChoices(BLOB_CHOICE* blob_choice,
WERD_RES* word_res) {
WERD_CHOICE* word = word_res->best_choice;
for (int i = 0; i < word_res->best_choice->length(); ++i) {
BLOB_CHOICE* choice = FindMatchingChoice(blob_choice->unichar_id(),
word_res->GetBlobChoices(i));
if (choice == NULL) {
BLOB_CHOICE_IT choice_it(word_res->GetBlobChoices(i));
choice_it.add_before_stay_put(new BLOB_CHOICE(*blob_choice));
}
}
// Correct any incorrect results in word.
for (int i = 0; i < word->length(); ++i) {
if (word->unichar_id(i) != blob_choice->unichar_id())
word->set_unichar_id(blob_choice->unichar_id(), i);
}
}
/**
* fix_rep_char()
* The word is a repeated char. (Leader.) Find the repeated char character.
* Create the appropriate single-word or multi-word sequence according to
* the size of spaces in between blobs, and correct the classifications
* where some of the characters disagree with the majority.
*/
void Tesseract::fix_rep_char(PAGE_RES_IT* page_res_it) {
WERD_RES *word_res = page_res_it->word();
const WERD_CHOICE &word = *(word_res->best_choice);
// Find the frequency of each unique character in the word.
SortHelper<UNICHAR_ID> rep_ch(word.length());
for (int i = 0; i < word.length(); ++i) {
rep_ch.Add(word.unichar_id(i), 1);
}
// Find the most frequent result.
UNICHAR_ID maxch_id = INVALID_UNICHAR_ID; // most common char
int max_count = rep_ch.MaxCount(&maxch_id);
// Find the best exemplar of a classifier result for maxch_id.
BLOB_CHOICE* best_choice = FindBestMatchingChoice(maxch_id, word_res);
if (best_choice == NULL) {
tprintf("Failed to find a choice for %s, occurring %d times\n",
word_res->uch_set->debug_str(maxch_id).string(), max_count);
return;
}
word_res->done = TRUE;
// Measure the mean space.
int gap_count = 0;
WERD* werd = word_res->word;
C_BLOB_IT blob_it(werd->cblob_list());
C_BLOB* prev_blob = blob_it.data();
for (blob_it.forward(); !blob_it.at_first(); blob_it.forward()) {
C_BLOB* blob = blob_it.data();
int gap = blob->bounding_box().left();
gap -= prev_blob->bounding_box().right();
++gap_count;
prev_blob = blob;
}
// Just correct existing classification.
CorrectRepcharChoices(best_choice, word_res);
word_res->reject_map.initialise(word.length());
}
ACCEPTABLE_WERD_TYPE Tesseract::acceptable_word_string(
const UNICHARSET& char_set, const char *s, const char *lengths) {
int i = 0;
int offset = 0;
int leading_punct_count;
int upper_count = 0;
int hyphen_pos = -1;
ACCEPTABLE_WERD_TYPE word_type = AC_UNACCEPTABLE;
if (strlen (lengths) > 20)
return word_type;
/* Single Leading punctuation char*/
if (s[offset] != '\0' && STRING(chs_leading_punct).contains(s[offset]))
offset += lengths[i++];
leading_punct_count = i;
/* Initial cap */
while (s[offset] != '\0' && char_set.get_isupper(s + offset, lengths[i])) {
offset += lengths[i++];
upper_count++;
}
if (upper_count > 1) {
word_type = AC_UPPER_CASE;
} else {
/* Lower case word, possibly with an initial cap */
while (s[offset] != '\0' && char_set.get_islower(s + offset, lengths[i])) {
offset += lengths[i++];
}
if (i - leading_punct_count < quality_min_initial_alphas_reqd)
goto not_a_word;
/*
Allow a single hyphen in a lower case word
- dont trust upper case - I've seen several cases of "H" -> "I-I"
*/
if (lengths[i] == 1 && s[offset] == '-') {
hyphen_pos = i;
offset += lengths[i++];
if (s[offset] != '\0') {
while ((s[offset] != '\0') &&
char_set.get_islower(s + offset, lengths[i])) {
offset += lengths[i++];
}
if (i < hyphen_pos + 3)
goto not_a_word;
}
} else {
/* Allow "'s" in NON hyphenated lower case words */
if (lengths[i] == 1 && (s[offset] == '\'') &&
lengths[i + 1] == 1 && (s[offset + lengths[i]] == 's')) {
offset += lengths[i++];
offset += lengths[i++];
}
}
if (upper_count > 0)
word_type = AC_INITIAL_CAP;
else
word_type = AC_LOWER_CASE;
}
/* Up to two different, constrained trailing punctuation chars */
if (lengths[i] == 1 && s[offset] != '\0' &&
STRING(chs_trailing_punct1).contains(s[offset]))
offset += lengths[i++];
if (lengths[i] == 1 && s[offset] != '\0' && i > 0 &&
s[offset - lengths[i - 1]] != s[offset] &&
STRING(chs_trailing_punct2).contains (s[offset]))
offset += lengths[i++];
if (s[offset] != '\0')
word_type = AC_UNACCEPTABLE;
not_a_word:
if (word_type == AC_UNACCEPTABLE) {
/* Look for abbreviation string */
i = 0;
offset = 0;
if (s[0] != '\0' && char_set.get_isupper(s, lengths[0])) {
word_type = AC_UC_ABBREV;
while (s[offset] != '\0' &&
char_set.get_isupper(s + offset, lengths[i]) &&
lengths[i + 1] == 1 && s[offset + lengths[i]] == '.') {
offset += lengths[i++];
offset += lengths[i++];
}
}
else if (s[0] != '\0' && char_set.get_islower(s, lengths[0])) {
word_type = AC_LC_ABBREV;
while (s[offset] != '\0' &&
char_set.get_islower(s + offset, lengths[i]) &&
lengths[i + 1] == 1 && s[offset + lengths[i]] == '.') {
offset += lengths[i++];
offset += lengths[i++];
}
}
if (s[offset] != '\0')
word_type = AC_UNACCEPTABLE;
}
return word_type;
}
BOOL8 Tesseract::check_debug_pt(WERD_RES *word, int location) {
BOOL8 show_map_detail = FALSE;
inT16 i;
if (!test_pt)
return FALSE;
tessedit_rejection_debug.set_value (FALSE);
debug_x_ht_level.set_value (0);
if (word->word->bounding_box ().contains (FCOORD (test_pt_x, test_pt_y))) {
if (location < 0)
return TRUE; // For breakpoint use
tessedit_rejection_debug.set_value (TRUE);
debug_x_ht_level.set_value (20);
tprintf ("\n\nTESTWD::");
switch (location) {
case 0:
tprintf ("classify_word_pass1 start\n");
word->word->print();
break;
case 10:
tprintf ("make_reject_map: initial map");
break;
case 20:
tprintf ("make_reject_map: after NN");
break;
case 30:
tprintf ("classify_word_pass2 - START");
break;
case 40:
tprintf ("classify_word_pass2 - Pre Xht");
break;
case 50:
tprintf ("classify_word_pass2 - END");
show_map_detail = TRUE;
break;
case 60:
tprintf ("fixspace");
break;
case 70:
tprintf ("MM pass START");
break;
case 80:
tprintf ("MM pass END");
break;
case 90:
tprintf ("After Poor quality rejection");
break;
case 100:
tprintf ("unrej_good_quality_words - START");
break;
case 110:
tprintf ("unrej_good_quality_words - END");
break;
case 120:
tprintf ("Write results pass");
show_map_detail = TRUE;
break;
}
if (word->best_choice != NULL) {
tprintf(" \"%s\" ", word->best_choice->unichar_string().string());
word->reject_map.print(debug_fp);
tprintf("\n");
if (show_map_detail) {
tprintf("\"%s\"\n", word->best_choice->unichar_string().string());
for (i = 0; word->best_choice->unichar_string()[i] != '\0'; i++) {
tprintf("**** \"%c\" ****\n", word->best_choice->unichar_string()[i]);
word->reject_map[i].full_print(debug_fp);
}
}
} else {
tprintf("null best choice\n");
}
tprintf ("Tess Accepted: %s\n", word->tess_accepted ? "TRUE" : "FALSE");
tprintf ("Done flag: %s\n\n", word->done ? "TRUE" : "FALSE");
return TRUE;
} else {
return FALSE;
}
}
/**
* find_modal_font
*
* Find the modal font and remove from the stats.
*/
static void find_modal_font( //good chars in word
STATS *fonts, //font stats
inT16 *font_out, //output font
inT8 *font_count //output count
) {
inT16 font; //font index
inT32 count; //pile couat
if (fonts->get_total () > 0) {
font = (inT16) fonts->mode ();
*font_out = font;
count = fonts->pile_count (font);
*font_count = count < MAX_INT8 ? count : MAX_INT8;
fonts->add (font, -*font_count);
}
else {
*font_out = -1;
*font_count = 0;
}
}
/**
* set_word_fonts
*
* Get the fonts for the word.
*/
void Tesseract::set_word_fonts(WERD_RES *word) {
// Don't try to set the word fonts for a cube word, as the configs
// will be meaningless.
if (word->chopped_word == NULL) return;
ASSERT_HOST(word->best_choice != NULL);
inT32 index; // char id index
// character iterator
BLOB_CHOICE_IT choice_it; // choice iterator
int fontinfo_size = get_fontinfo_table().size();
int fontset_size = get_fontset_table().size();
if (fontinfo_size == 0 || fontset_size == 0) return;
STATS fonts(0, fontinfo_size); // font counters
word->italic = 0;
word->bold = 0;
if (!word->best_choice_fontinfo_ids.empty()) {
word->best_choice_fontinfo_ids.clear();
}
// Compute the modal font for the word
for (index = 0; index < word->best_choice->length(); ++index) {
UNICHAR_ID word_ch_id = word->best_choice->unichar_id(index);
choice_it.set_to_list(word->GetBlobChoices(index));
if (tessedit_debug_fonts) {
tprintf("Examining fonts in %s\n",
word->best_choice->debug_string().string());
}
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
choice_it.forward()) {
UNICHAR_ID blob_ch_id = choice_it.data()->unichar_id();
if (blob_ch_id == word_ch_id) {
if (tessedit_debug_fonts) {
tprintf("%s font %s (%d) font2 %s (%d)\n",
word->uch_set->id_to_unichar(blob_ch_id),
choice_it.data()->fontinfo_id() < 0 ? "unknown" :
fontinfo_table_.get(choice_it.data()->fontinfo_id()).name,
choice_it.data()->fontinfo_id(),
choice_it.data()->fontinfo_id2() < 0 ? "unknown" :
fontinfo_table_.get(choice_it.data()->fontinfo_id2()).name,
choice_it.data()->fontinfo_id2());
}
// 1st choice font gets 2 pts, 2nd choice 1 pt.
if (choice_it.data()->fontinfo_id() >= 0) {
fonts.add(choice_it.data()->fontinfo_id(), 2);
}
if (choice_it.data()->fontinfo_id2() >= 0) {
fonts.add(choice_it.data()->fontinfo_id2(), 1);
}
break;
}
}
}
inT16 font_id1, font_id2;
find_modal_font(&fonts, &font_id1, &word->fontinfo_id_count);
find_modal_font(&fonts, &font_id2, &word->fontinfo_id2_count);
word->fontinfo = font_id1 >= 0 ? &fontinfo_table_.get(font_id1) : NULL;
word->fontinfo2 = font_id2 >= 0 ? &fontinfo_table_.get(font_id2) : NULL;
// All the blobs get the word's best choice font.
for (int i = 0; i < word->best_choice->length(); ++i) {
word->best_choice_fontinfo_ids.push_back(font_id1);
}
if (word->fontinfo_id_count > 0) {
FontInfo fi = fontinfo_table_.get(font_id1);
if (tessedit_debug_fonts) {
if (word->fontinfo_id2_count > 0) {
tprintf("Word modal font=%s, score=%d, 2nd choice %s/%d\n",
fi.name, word->fontinfo_id_count,
fontinfo_table_.get(font_id2).name,
word->fontinfo_id2_count);
} else {
tprintf("Word modal font=%s, score=%d. No 2nd choice\n",
fi.name, word->fontinfo_id_count);
}
}
// 1st choices got 2 pts, so we need to halve the score for the mode.
word->italic = (fi.is_italic() ? 1 : -1) * (word->fontinfo_id_count + 1) / 2;
word->bold = (fi.is_bold() ? 1 : -1) * (word->fontinfo_id_count + 1) / 2;
}
}
/**
* font_recognition_pass
*
* Smooth the fonts for the document.
*/
void Tesseract::font_recognition_pass(PAGE_RES* page_res) {
PAGE_RES_IT page_res_it(page_res);
WERD_RES *word; // current word
STATS doc_fonts(0, font_table_size_); // font counters
// Gather font id statistics.
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
word = page_res_it.word();
if (word->fontinfo != NULL) {
doc_fonts.add(word->fontinfo->universal_id, word->fontinfo_id_count);
}
if (word->fontinfo2 != NULL) {
doc_fonts.add(word->fontinfo2->universal_id, word->fontinfo_id2_count);
}
}
inT16 doc_font; // modal font
inT8 doc_font_count; // modal font
find_modal_font(&doc_fonts, &doc_font, &doc_font_count);
if (doc_font_count == 0)
return;
// Get the modal font pointer.
const FontInfo* modal_font = NULL;
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
word = page_res_it.word();
if (word->fontinfo != NULL && word->fontinfo->universal_id == doc_font) {
modal_font = word->fontinfo;
break;
}
if (word->fontinfo2 != NULL && word->fontinfo2->universal_id == doc_font) {
modal_font = word->fontinfo2;
break;
}
}
ASSERT_HOST(modal_font != NULL);
// Assign modal font to weak words.
for (page_res_it.restart_page(); page_res_it.word() != NULL;
page_res_it.forward()) {
word = page_res_it.word();
int length = word->best_choice->length();
// 1st choices got 2 pts, so we need to halve the score for the mode.
int count = (word->fontinfo_id_count + 1) / 2;
if (!(count == length || (length > 3 && count >= length * 3 / 4))) {
word->fontinfo = modal_font;
// Counts only get 1 as it came from the doc.
word->fontinfo_id_count = 1;
word->italic = modal_font->is_italic() ? 1 : -1;
word->bold = modal_font->is_bold() ? 1 : -1;
}
}
}
// If a word has multiple alternates check if the best choice is in the
// dictionary. If not, replace it with an alternate that exists in the
// dictionary.
void Tesseract::dictionary_correction_pass(PAGE_RES *page_res) {
PAGE_RES_IT word_it(page_res);
for (WERD_RES* word = word_it.word(); word != NULL;
word = word_it.forward()) {
if (word->best_choices.singleton())
continue; // There are no alternates.
WERD_CHOICE* best = word->best_choice;
if (word->tesseract->getDict().valid_word(*best) != 0)
continue; // The best choice is in the dictionary.
WERD_CHOICE_IT choice_it(&word->best_choices);
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
choice_it.forward()) {
WERD_CHOICE* alternate = choice_it.data();
if (word->tesseract->getDict().valid_word(*alternate)) {
// The alternate choice is in the dictionary.
if (tessedit_bigram_debug) {
tprintf("Dictionary correction replaces best choice '%s' with '%s'\n",
best->unichar_string().string(),
alternate->unichar_string().string());
}
// Replace the 'best' choice with a better choice.
word->ReplaceBestChoice(alternate);
break;
}
}
}
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: thresholder.h
// Description: Base API for thresolding images in tesseract.
// Author: Ray Smith
// Created: Mon May 12 11:00:15 PDT 2008
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_THRESHOLDER_H__
#define TESSERACT_CCMAIN_THRESHOLDER_H__
#include "platform.h"
#include "publictypes.h"
struct Pix;
namespace tesseract {
/// Base class for all tesseract image thresholding classes.
/// Specific classes can add new thresholding methods by
/// overriding ThresholdToPix.
/// Each instance deals with a single image, but the design is intended to
/// be useful for multiple calls to SetRectangle and ThresholdTo* if
/// desired.
class TESS_API ImageThresholder {
public:
ImageThresholder();
virtual ~ImageThresholder();
/// Destroy the Pix if there is one, freeing memory.
virtual void Clear();
/// Return true if no image has been set.
bool IsEmpty() const;
/// SetImage makes a copy of all the image data, so it may be deleted
/// immediately after this call.
/// Greyscale of 8 and color of 24 or 32 bits per pixel may be given.
/// Palette color images will not work properly and must be converted to
/// 24 bit.
/// Binary images of 1 bit per pixel may also be given but they must be
/// byte packed with the MSB of the first byte being the first pixel, and a
/// one pixel is WHITE. For binary images set bytes_per_pixel=0.
void SetImage(const unsigned char* imagedata, int width, int height,
int bytes_per_pixel, int bytes_per_line);
/// Store the coordinates of the rectangle to process for later use.
/// Doesn't actually do any thresholding.
void SetRectangle(int left, int top, int width, int height);
/// Get enough parameters to be able to rebuild bounding boxes in the
/// original image (not just within the rectangle).
/// Left and top are enough with top-down coordinates, but
/// the height of the rectangle and the image are needed for bottom-up.
virtual void GetImageSizes(int* left, int* top, int* width, int* height,
int* imagewidth, int* imageheight);
/// Return true if the source image is color.
bool IsColor() const {
return pix_channels_ >= 3;
}
/// Returns true if the source image is binary.
bool IsBinary() const {
return pix_channels_ == 0;
}
int GetScaleFactor() const {
return scale_;
}
// Set the resolution of the source image in pixels per inch.
// This should be called right after SetImage(), and will let us return
// appropriate font sizes for the text.
void SetSourceYResolution(int ppi) {
yres_ = ppi;
estimated_res_ = ppi;
}
int GetSourceYResolution() const {
return yres_;
}
int GetScaledYResolution() const {
return scale_ * yres_;
}
// Set the resolution of the source image in pixels per inch, as estimated
// by the thresholder from the text size found during thresholding.
// This value will be used to set internal size thresholds during recognition
// and will not influence the output "point size." The default value is
// the same as the source resolution. (yres_)
void SetEstimatedResolution(int ppi) {
estimated_res_ = ppi;
}
// Returns the estimated resolution, including any active scaling.
// This value will be used to set internal size thresholds during recognition.
int GetScaledEstimatedResolution() const {
return scale_ * estimated_res_;
}
/// Pix vs raw, which to use? Pix is the preferred input for efficiency,
/// since raw buffers are copied.
/// SetImage for Pix clones its input, so the source pix may be pixDestroyed
/// immediately after, but may not go away until after the Thresholder has
/// finished with it.
void SetImage(const Pix* pix);
/// Threshold the source image as efficiently as possible to the output Pix.
/// Creates a Pix and sets pix to point to the resulting pointer.
/// Caller must use pixDestroy to free the created Pix.
virtual void ThresholdToPix(PageSegMode pageseg_mode, Pix** pix);
// Gets a pix that contains an 8 bit threshold value at each pixel. The
// returned pix may be an integer reduction of the binary image such that
// the scale factor may be inferred from the ratio of the sizes, even down
// to the extreme of a 1x1 pixel thresholds image.
// Ideally the 8 bit threshold should be the exact threshold used to generate
// the binary image in ThresholdToPix, but this is not a hard constraint.
// Returns NULL if the input is binary. PixDestroy after use.
virtual Pix* GetPixRectThresholds();
/// Get a clone/copy of the source image rectangle.
/// The returned Pix must be pixDestroyed.
/// This function will be used in the future by the page layout analysis, and
/// the layout analysis that uses it will only be available with Leptonica,
/// so there is no raw equivalent.
Pix* GetPixRect();
// Get a clone/copy of the source image rectangle, reduced to greyscale,
// and at the same resolution as the output binary.
// The returned Pix must be pixDestroyed.
// Provided to the classifier to extract features from the greyscale image.
virtual Pix* GetPixRectGrey();
protected:
// ----------------------------------------------------------------------
// Utility functions that may be useful components for other thresholders.
/// Common initialization shared between SetImage methods.
virtual void Init();
/// Return true if we are processing the full image.
bool IsFullImage() const {
return rect_left_ == 0 && rect_top_ == 0 &&
rect_width_ == image_width_ && rect_height_ == image_height_;
}
// Otsu thresholds the rectangle, taking the rectangle from *this.
void OtsuThresholdRectToPix(Pix* src_pix, Pix** out_pix) const;
/// Threshold the rectangle, taking everything except the src_pix
/// from the class, using thresholds/hi_values to the output pix.
/// NOTE that num_channels is the size of the thresholds and hi_values
// arrays and also the bytes per pixel in src_pix.
void ThresholdRectToPix(Pix* src_pix, int num_channels,
const int* thresholds, const int* hi_values,
Pix** pix) const;
protected:
/// Clone or other copy of the source Pix.
/// The pix will always be PixDestroy()ed on destruction of the class.
Pix* pix_;
int image_width_; //< Width of source pix_.
int image_height_; //< Height of source pix_.
int pix_channels_; //< Number of 8-bit channels in pix_.
int pix_wpl_; //< Words per line of pix_.
// Limits of image rectangle to be processed.
int scale_; //< Scale factor from original image.
int yres_; //< y pixels/inch in source image.
int estimated_res_; //< Resolution estimate from text size.
int rect_left_;
int rect_top_;
int rect_width_;
int rect_height_;
};
} // namespace tesseract.
#endif // TESSERACT_CCMAIN_THRESHOLDER_H__
| C++ |
/**********************************************************************
* File: paragraphs.h
* Description: Paragraph Detection data structures.
* Author: David Eger
* Created: 25 February 2011
*
* (C) Copyright 2011, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef TESSERACT_CCMAIN_PARAGRAPHS_H_
#define TESSERACT_CCMAIN_PARAGRAPHS_H_
#include "rect.h"
#include "ocrpara.h"
#include "genericvector.h"
#include "strngs.h"
class WERD;
class UNICHARSET;
namespace tesseract {
class MutableIterator;
// This structure captures all information needed about a text line for the
// purposes of paragraph detection. It is meant to be exceedingly light-weight
// so that we can easily test paragraph detection independent of the rest of
// Tesseract.
class RowInfo {
public:
// Constant data derived from Tesseract output.
STRING text; // the full UTF-8 text of the line.
bool ltr; // whether the majority of the text is left-to-right
// TODO(eger) make this more fine-grained.
bool has_leaders; // does the line contain leader dots (.....)?
bool has_drop_cap; // does the line have a drop cap?
int pix_ldistance; // distance to the left pblock boundary in pixels
int pix_rdistance; // distance to the right pblock boundary in pixels
float pix_xheight; // guessed xheight for the line
int average_interword_space; // average space between words in pixels.
int num_words;
TBOX lword_box; // in normalized (horiz text rows) space
TBOX rword_box; // in normalized (horiz text rows) space
STRING lword_text; // the UTF-8 text of the leftmost werd
STRING rword_text; // the UTF-8 text of the rightmost werd
// The text of a paragraph typically starts with the start of an idea and
// ends with the end of an idea. Here we define paragraph as something that
// may have a first line indent and a body indent which may be different.
// Typical words that start an idea are:
// 1. Words in western scripts that start with
// a capital letter, for example "The"
// 2. Bulleted or numbered list items, for
// example "2."
// Typical words which end an idea are words ending in punctuation marks. In
// this vocabulary, each list item is represented as a paragraph.
bool lword_indicates_list_item;
bool lword_likely_starts_idea;
bool lword_likely_ends_idea;
bool rword_indicates_list_item;
bool rword_likely_starts_idea;
bool rword_likely_ends_idea;
};
// Main entry point for Paragraph Detection Algorithm.
//
// Given a set of equally spaced textlines (described by row_infos),
// Split them into paragraphs. See http://goto/paragraphstalk
//
// Output:
// row_owners - one pointer for each row, to the paragraph it belongs to.
// paragraphs - this is the actual list of PARA objects.
// models - the list of paragraph models referenced by the PARA objects.
// caller is responsible for deleting the models.
void DetectParagraphs(int debug_level,
GenericVector<RowInfo> *row_infos,
GenericVector<PARA *> *row_owners,
PARA_LIST *paragraphs,
GenericVector<ParagraphModel *> *models);
// Given a MutableIterator to the start of a block, run DetectParagraphs on
// that block and commit the results to the underlying ROW and BLOCK structs,
// saving the ParagraphModels in models. Caller owns the models.
// We use unicharset during the function to answer questions such as "is the
// first letter of this word upper case?"
void DetectParagraphs(int debug_level,
bool after_text_recognition,
const MutableIterator *block_start,
GenericVector<ParagraphModel *> *models);
} // namespace
#endif // TESSERACT_CCMAIN_PARAGRAPHS_H_
| C++ |
/**********************************************************************
* File: tessedit.cpp (Formerly tessedit.c)
* Description: Main program for merge of tess and editor.
* Author: Ray Smith
* Created: Tue Jan 07 15:21:46 GMT 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "stderr.h"
#include "basedir.h"
#include "tessvars.h"
#include "control.h"
#include "reject.h"
#include "pageres.h"
#include "nwmain.h"
#include "pgedit.h"
#include "tprintf.h"
#include "tessedit.h"
#include "stopper.h"
#include "intmatcher.h"
#include "chop.h"
#include "efio.h"
#include "danerror.h"
#include "globals.h"
#include "tesseractclass.h"
#include "params.h"
#define VARDIR "configs/" /*variables files */
//config under api
#define API_CONFIG "configs/api_config"
ETEXT_DESC *global_monitor = NULL; // progress monitor
namespace tesseract {
// Read a "config" file containing a set of variable, value pairs.
// Searches the standard places: tessdata/configs, tessdata/tessconfigs
// and also accepts a relative or absolute path name.
void Tesseract::read_config_file(const char *filename,
SetParamConstraint constraint) {
STRING path = datadir;
path += "configs/";
path += filename;
FILE* fp;
if ((fp = fopen(path.string(), "rb")) != NULL) {
fclose(fp);
} else {
path = datadir;
path += "tessconfigs/";
path += filename;
if ((fp = fopen(path.string(), "rb")) != NULL) {
fclose(fp);
} else {
path = filename;
}
}
ParamUtils::ReadParamsFile(path.string(), constraint, this->params());
}
// Returns false if a unicharset file for the specified language was not found
// or was invalid.
// This function initializes TessdataManager. After TessdataManager is
// no longer needed, TessdataManager::End() should be called.
//
// This function sets tessedit_oem_mode to the given OcrEngineMode oem, unless
// it is OEM_DEFAULT, in which case the value of the variable will be obtained
// from the language-specific config file (stored in [lang].traineddata), from
// the config files specified on the command line or left as the default
// OEM_TESSERACT_ONLY if none of the configs specify this variable.
bool Tesseract::init_tesseract_lang_data(
const char *arg0, const char *textbase, const char *language,
OcrEngineMode oem, char **configs, int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_non_debug_params) {
// Set the basename, compute the data directory.
main_setup(arg0, textbase);
// Set the language data path prefix
lang = language != NULL ? language : "eng";
language_data_path_prefix = datadir;
language_data_path_prefix += lang;
language_data_path_prefix += ".";
// Initialize TessdataManager.
STRING tessdata_path = language_data_path_prefix + kTrainedDataSuffix;
if (!tessdata_manager.Init(tessdata_path.string(),
tessdata_manager_debug_level)) {
return false;
}
// If a language specific config file (lang.config) exists, load it in.
if (tessdata_manager.SeekToStart(TESSDATA_LANG_CONFIG)) {
ParamUtils::ReadParamsFromFp(
tessdata_manager.GetDataFilePtr(),
tessdata_manager.GetEndOffset(TESSDATA_LANG_CONFIG),
SET_PARAM_CONSTRAINT_NONE, this->params());
if (tessdata_manager_debug_level) {
tprintf("Loaded language config file\n");
}
}
SetParamConstraint set_params_constraint = set_only_non_debug_params ?
SET_PARAM_CONSTRAINT_NON_DEBUG_ONLY : SET_PARAM_CONSTRAINT_NONE;
// Load tesseract variables from config files. This is done after loading
// language-specific variables from [lang].traineddata file, so that custom
// config files can override values in [lang].traineddata file.
for (int i = 0; i < configs_size; ++i) {
read_config_file(configs[i], set_params_constraint);
}
// Set params specified in vars_vec (done after setting params from config
// files, so that params in vars_vec can override those from files).
if (vars_vec != NULL && vars_values != NULL) {
for (int i = 0; i < vars_vec->size(); ++i) {
if (!ParamUtils::SetParam((*vars_vec)[i].string(),
(*vars_values)[i].string(),
set_params_constraint, this->params())) {
tprintf("Error setting param %s\n", (*vars_vec)[i].string());
exit(1);
}
}
}
if (((STRING &)tessedit_write_params_to_file).length() > 0) {
FILE *params_file = fopen(tessedit_write_params_to_file.string(), "wb");
if (params_file != NULL) {
ParamUtils::PrintParams(params_file, this->params());
fclose(params_file);
if (tessdata_manager_debug_level > 0) {
tprintf("Wrote parameters to %s\n",
tessedit_write_params_to_file.string());
}
} else {
tprintf("Failed to open %s for writing params.\n",
tessedit_write_params_to_file.string());
}
}
// Determine which ocr engine(s) should be loaded and used for recognition.
if (oem != OEM_DEFAULT) tessedit_ocr_engine_mode.set_value(oem);
if (tessdata_manager_debug_level) {
tprintf("Loading Tesseract/Cube with tessedit_ocr_engine_mode %d\n",
static_cast<int>(tessedit_ocr_engine_mode));
}
// If we are only loading the config file (and so not planning on doing any
// recognition) then there's nothing else do here.
if (tessedit_init_config_only) {
if (tessdata_manager_debug_level) {
tprintf("Returning after loading config file\n");
}
return true;
}
// Load the unicharset
if (!tessdata_manager.SeekToStart(TESSDATA_UNICHARSET) ||
!unicharset.load_from_file(tessdata_manager.GetDataFilePtr())) {
return false;
}
if (unicharset.size() > MAX_NUM_CLASSES) {
tprintf("Error: Size of unicharset is greater than MAX_NUM_CLASSES\n");
return false;
}
if (tessdata_manager_debug_level) tprintf("Loaded unicharset\n");
right_to_left_ = unicharset.major_right_to_left();
// Setup initial unichar ambigs table and read universal ambigs.
UNICHARSET encoder_unicharset;
encoder_unicharset.CopyFrom(unicharset);
unichar_ambigs.InitUnicharAmbigs(unicharset, use_ambigs_for_adaption);
unichar_ambigs.LoadUniversal(encoder_unicharset, &unicharset);
if (!tessedit_ambigs_training &&
tessdata_manager.SeekToStart(TESSDATA_AMBIGS)) {
TFile ambigs_file;
ambigs_file.Open(tessdata_manager.GetDataFilePtr(),
tessdata_manager.GetEndOffset(TESSDATA_AMBIGS) + 1);
unichar_ambigs.LoadUnicharAmbigs(
encoder_unicharset,
&ambigs_file,
ambigs_debug_level, use_ambigs_for_adaption, &unicharset);
if (tessdata_manager_debug_level) tprintf("Loaded ambigs\n");
}
// Load Cube objects if necessary.
if (tessedit_ocr_engine_mode == OEM_CUBE_ONLY) {
ASSERT_HOST(init_cube_objects(false, &tessdata_manager));
if (tessdata_manager_debug_level)
tprintf("Loaded Cube w/out combiner\n");
} else if (tessedit_ocr_engine_mode == OEM_TESSERACT_CUBE_COMBINED) {
ASSERT_HOST(init_cube_objects(true, &tessdata_manager));
if (tessdata_manager_debug_level)
tprintf("Loaded Cube with combiner\n");
}
// Init ParamsModel.
// Load pass1 and pass2 weights (for now these two sets are the same, but in
// the future separate sets of weights can be generated).
for (int p = ParamsModel::PTRAIN_PASS1;
p < ParamsModel::PTRAIN_NUM_PASSES; ++p) {
language_model_->getParamsModel().SetPass(
static_cast<ParamsModel::PassEnum>(p));
if (tessdata_manager.SeekToStart(TESSDATA_PARAMS_MODEL)) {
if (!language_model_->getParamsModel().LoadFromFp(
lang.string(), tessdata_manager.GetDataFilePtr(),
tessdata_manager.GetEndOffset(TESSDATA_PARAMS_MODEL))) {
return false;
}
}
}
if (tessdata_manager_debug_level) language_model_->getParamsModel().Print();
return true;
}
// Helper returns true if the given string is in the vector of strings.
static bool IsStrInList(const STRING& str,
const GenericVector<STRING>& str_list) {
for (int i = 0; i < str_list.size(); ++i) {
if (str_list[i] == str)
return true;
}
return false;
}
// Parse a string of the form [~]<lang>[+[~]<lang>]*.
// Langs with no prefix get appended to to_load, provided they
// are not in there already.
// Langs with ~ prefix get appended to not_to_load, provided they are not in
// there already.
void Tesseract::ParseLanguageString(const char* lang_str,
GenericVector<STRING>* to_load,
GenericVector<STRING>* not_to_load) {
STRING remains(lang_str);
while (remains.length() > 0) {
// Find the start of the lang code and which vector to add to.
const char* start = remains.string();
while (*start == '+')
++start;
GenericVector<STRING>* target = to_load;
if (*start == '~') {
target = not_to_load;
++start;
}
// Find the index of the end of the lang code in string start.
int end = strlen(start);
const char* plus = strchr(start, '+');
if (plus != NULL && plus - start < end)
end = plus - start;
STRING lang_code(start);
lang_code.truncate_at(end);
STRING next(start + end);
remains = next;
// Check whether lang_code is already in the target vector and add.
if (!IsStrInList(lang_code, *target)) {
if (tessdata_manager_debug_level)
tprintf("Adding language '%s' to list\n", lang_code.string());
target->push_back(lang_code);
}
}
}
// Initialize for potentially a set of languages defined by the language
// string and recursively any additional languages required by any language
// traineddata file (via tessedit_load_sublangs in its config) that is loaded.
// See init_tesseract_internal for args.
int Tesseract::init_tesseract(
const char *arg0, const char *textbase, const char *language,
OcrEngineMode oem, char **configs, int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_non_debug_params) {
GenericVector<STRING> langs_to_load;
GenericVector<STRING> langs_not_to_load;
ParseLanguageString(language, &langs_to_load, &langs_not_to_load);
sub_langs_.delete_data_pointers();
sub_langs_.clear();
// Find the first loadable lang and load into this.
// Add any languages that this language requires
bool loaded_primary = false;
// Load the rest into sub_langs_.
for (int lang_index = 0; lang_index < langs_to_load.size(); ++lang_index) {
if (!IsStrInList(langs_to_load[lang_index], langs_not_to_load)) {
const char *lang_str = langs_to_load[lang_index].string();
Tesseract *tess_to_init;
if (!loaded_primary) {
tess_to_init = this;
} else {
tess_to_init = new Tesseract;
}
int result = tess_to_init->init_tesseract_internal(
arg0, textbase, lang_str, oem, configs, configs_size,
vars_vec, vars_values, set_only_non_debug_params);
if (!loaded_primary) {
if (result < 0) {
tprintf("Failed loading language '%s'\n", lang_str);
} else {
if (tessdata_manager_debug_level)
tprintf("Loaded language '%s' as main language\n", lang_str);
ParseLanguageString(tess_to_init->tessedit_load_sublangs.string(),
&langs_to_load, &langs_not_to_load);
loaded_primary = true;
}
} else {
if (result < 0) {
tprintf("Failed loading language '%s'\n", lang_str);
delete tess_to_init;
} else {
if (tessdata_manager_debug_level)
tprintf("Loaded language '%s' as secondary language\n", lang_str);
sub_langs_.push_back(tess_to_init);
// Add any languages that this language requires
ParseLanguageString(tess_to_init->tessedit_load_sublangs.string(),
&langs_to_load, &langs_not_to_load);
}
}
}
}
if (!loaded_primary) {
tprintf("Tesseract couldn't load any languages!\n");
return -1; // Couldn't load any language!
}
if (!sub_langs_.empty()) {
// In multilingual mode word ratings have to be directly comparable,
// so use the same language model weights for all languages:
// use the primary language's params model if
// tessedit_use_primary_params_model is set,
// otherwise use default language model weights.
if (tessedit_use_primary_params_model) {
for (int s = 0; s < sub_langs_.size(); ++s) {
sub_langs_[s]->language_model_->getParamsModel().Copy(
this->language_model_->getParamsModel());
}
tprintf("Using params model of the primary language\n");
if (tessdata_manager_debug_level) {
this->language_model_->getParamsModel().Print();
}
} else {
this->language_model_->getParamsModel().Clear();
for (int s = 0; s < sub_langs_.size(); ++s) {
sub_langs_[s]->language_model_->getParamsModel().Clear();
}
if (tessdata_manager_debug_level)
tprintf("Using default language params\n");
}
}
SetupUniversalFontIds();
return 0;
}
// Common initialization for a single language.
// arg0 is the datapath for the tessdata directory, which could be the
// path of the tessdata directory with no trailing /, or (if tessdata
// lives in the same directory as the executable, the path of the executable,
// hence the name arg0.
// textbase is an optional output file basename (used only for training)
// language is the language code to load.
// oem controls which engine(s) will operate on the image
// configs (argv) is an array of config filenames to load variables from.
// May be NULL.
// configs_size (argc) is the number of elements in configs.
// vars_vec is an optional vector of variables to set.
// vars_values is an optional corresponding vector of values for the variables
// in vars_vec.
// If set_only_init_params is true, then only the initialization variables
// will be set.
int Tesseract::init_tesseract_internal(
const char *arg0, const char *textbase, const char *language,
OcrEngineMode oem, char **configs, int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_non_debug_params) {
if (!init_tesseract_lang_data(arg0, textbase, language, oem, configs,
configs_size, vars_vec, vars_values,
set_only_non_debug_params)) {
return -1;
}
if (tessedit_init_config_only) {
tessdata_manager.End();
return 0;
}
// If only Cube will be used, skip loading Tesseract classifier's
// pre-trained templates.
bool init_tesseract_classifier =
(tessedit_ocr_engine_mode == OEM_TESSERACT_ONLY ||
tessedit_ocr_engine_mode == OEM_TESSERACT_CUBE_COMBINED);
// If only Cube will be used and if it has its own Unicharset,
// skip initializing permuter and loading Tesseract Dawgs.
bool init_dict =
!(tessedit_ocr_engine_mode == OEM_CUBE_ONLY &&
tessdata_manager.SeekToStart(TESSDATA_CUBE_UNICHARSET));
program_editup(textbase, init_tesseract_classifier, init_dict);
tessdata_manager.End();
return 0; //Normal exit
}
// Helper builds the all_fonts table by adding new fonts from new_fonts.
static void CollectFonts(const UnicityTable<FontInfo>& new_fonts,
UnicityTable<FontInfo>* all_fonts) {
for (int i = 0; i < new_fonts.size(); ++i) {
// UnicityTable uniques as we go.
all_fonts->push_back(new_fonts.get(i));
}
}
// Helper assigns an id to lang_fonts using the index in all_fonts table.
static void AssignIds(const UnicityTable<FontInfo>& all_fonts,
UnicityTable<FontInfo>* lang_fonts) {
for (int i = 0; i < lang_fonts->size(); ++i) {
int index = all_fonts.get_id(lang_fonts->get(i));
lang_fonts->get_mutable(i)->universal_id = index;
}
}
// Set the universal_id member of each font to be unique among all
// instances of the same font loaded.
void Tesseract::SetupUniversalFontIds() {
// Note that we can get away with bitwise copying FontInfo in
// all_fonts, as it is a temporary structure and we avoid setting the
// delete callback.
UnicityTable<FontInfo> all_fonts;
all_fonts.set_compare_callback(NewPermanentTessCallback(CompareFontInfo));
// Create the universal ID table.
CollectFonts(get_fontinfo_table(), &all_fonts);
for (int i = 0; i < sub_langs_.size(); ++i) {
CollectFonts(sub_langs_[i]->get_fontinfo_table(), &all_fonts);
}
// Assign ids from the table to each font table.
AssignIds(all_fonts, &get_fontinfo_table());
for (int i = 0; i < sub_langs_.size(); ++i) {
AssignIds(all_fonts, &sub_langs_[i]->get_fontinfo_table());
}
font_table_size_ = all_fonts.size();
}
// init the LM component
int Tesseract::init_tesseract_lm(const char *arg0,
const char *textbase,
const char *language) {
if (!init_tesseract_lang_data(arg0, textbase, language, OEM_TESSERACT_ONLY,
NULL, 0, NULL, NULL, false))
return -1;
getDict().Load(Dict::GlobalDawgCache());
tessdata_manager.End();
return 0;
}
void Tesseract::end_tesseract() {
end_recog();
}
/* Define command type identifiers */
enum CMD_EVENTS
{
ACTION_1_CMD_EVENT,
RECOG_WERDS,
RECOG_PSEUDO,
ACTION_2_CMD_EVENT
};
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: recogtraining.cpp
// Description: Functions for ambiguity and parameter training.
// Author: Daria Antonova
// Created: Mon Aug 13 11:26:43 PDT 2009
//
// (C) Copyright 2009, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "tesseractclass.h"
#include "boxread.h"
#include "control.h"
#include "cutil.h"
#include "host.h"
#include "ratngs.h"
#include "reject.h"
#include "stopper.h"
namespace tesseract {
const inT16 kMaxBoxEdgeDiff = 2;
// Sets flags necessary for recognition in the training mode.
// Opens and returns the pointer to the output file.
FILE *Tesseract::init_recog_training(const STRING &fname) {
if (tessedit_ambigs_training) {
tessedit_tess_adaption_mode.set_value(0); // turn off adaption
tessedit_enable_doc_dict.set_value(0); // turn off document dictionary
// Explore all segmentations.
getDict().stopper_no_acceptable_choices.set_value(1);
}
STRING output_fname = fname;
const char *lastdot = strrchr(output_fname.string(), '.');
if (lastdot != NULL) output_fname[lastdot - output_fname.string()] = '\0';
output_fname += ".txt";
FILE *output_file = open_file(output_fname.string(), "a+");
return output_file;
}
// Copies the bounding box from page_res_it->word() to the given TBOX.
bool read_t(PAGE_RES_IT *page_res_it, TBOX *tbox) {
while (page_res_it->block() != NULL && page_res_it->word() == NULL)
page_res_it->forward();
if (page_res_it->word() != NULL) {
*tbox = page_res_it->word()->word->bounding_box();
// If tbox->left() is negative, the training image has vertical text and
// all the coordinates of bounding boxes of page_res are rotated by 90
// degrees in a counterclockwise direction. We need to rotate the TBOX back
// in order to compare with the TBOXes of box files.
if (tbox->left() < 0) {
tbox->rotate(FCOORD(0.0, -1.0));
}
return true;
} else {
return false;
}
}
// This function takes tif/box pair of files and runs recognition on the image,
// while making sure that the word bounds that tesseract identified roughly
// match to those specified by the input box file. For each word (ngram in a
// single bounding box from the input box file) it outputs the ocred result,
// the correct label, rating and certainty.
void Tesseract::recog_training_segmented(const STRING &fname,
PAGE_RES *page_res,
volatile ETEXT_DESC *monitor,
FILE *output_file) {
STRING box_fname = fname;
const char *lastdot = strrchr(box_fname.string(), '.');
if (lastdot != NULL) box_fname[lastdot - box_fname.string()] = '\0';
box_fname += ".box";
// read_next_box() will close box_file
FILE *box_file = open_file(box_fname.string(), "r");
PAGE_RES_IT page_res_it;
page_res_it.page_res = page_res;
page_res_it.restart_page();
STRING label;
// Process all the words on this page.
TBOX tbox; // tesseract-identified box
TBOX bbox; // box from the box file
bool keep_going;
int line_number = 0;
int examined_words = 0;
do {
keep_going = read_t(&page_res_it, &tbox);
keep_going &= ReadNextBox(applybox_page, &line_number, box_file, &label,
&bbox);
// Align bottom left points of the TBOXes.
while (keep_going &&
!NearlyEqual<int>(tbox.bottom(), bbox.bottom(), kMaxBoxEdgeDiff)) {
if (bbox.bottom() < tbox.bottom()) {
page_res_it.forward();
keep_going = read_t(&page_res_it, &tbox);
} else {
keep_going = ReadNextBox(applybox_page, &line_number, box_file, &label,
&bbox);
}
}
while (keep_going &&
!NearlyEqual<int>(tbox.left(), bbox.left(), kMaxBoxEdgeDiff)) {
if (bbox.left() > tbox.left()) {
page_res_it.forward();
keep_going = read_t(&page_res_it, &tbox);
} else {
keep_going = ReadNextBox(applybox_page, &line_number, box_file, &label,
&bbox);
}
}
// OCR the word if top right points of the TBOXes are similar.
if (keep_going &&
NearlyEqual<int>(tbox.right(), bbox.right(), kMaxBoxEdgeDiff) &&
NearlyEqual<int>(tbox.top(), bbox.top(), kMaxBoxEdgeDiff)) {
ambigs_classify_and_output(label.string(), &page_res_it, output_file);
examined_words++;
}
page_res_it.forward();
} while (keep_going);
fclose(box_file);
// Set up scripts on all of the words that did not get sent to
// ambigs_classify_and_output. They all should have, but if all the
// werd_res's don't get uch_sets, tesseract will crash when you try
// to iterate over them. :-(
int total_words = 0;
for (page_res_it.restart_page(); page_res_it.block() != NULL;
page_res_it.forward()) {
if (page_res_it.word()) {
if (page_res_it.word()->uch_set == NULL)
page_res_it.word()->SetupFake(unicharset);
total_words++;
}
}
if (examined_words < 0.85 * total_words) {
tprintf("TODO(antonova): clean up recog_training_segmented; "
" It examined only a small fraction of the ambigs image.\n");
}
tprintf("recog_training_segmented: examined %d / %d words.\n",
examined_words, total_words);
}
// Helper prints the given set of blob choices.
static void PrintPath(int length, const BLOB_CHOICE** blob_choices,
const UNICHARSET& unicharset,
const char *label, FILE *output_file) {
float rating = 0.0f;
float certainty = 0.0f;
for (int i = 0; i < length; ++i) {
const BLOB_CHOICE* blob_choice = blob_choices[i];
fprintf(output_file, "%s",
unicharset.id_to_unichar(blob_choice->unichar_id()));
rating += blob_choice->rating();
if (certainty > blob_choice->certainty())
certainty = blob_choice->certainty();
}
fprintf(output_file, "\t%s\t%.4f\t%.4f\n",
label, rating, certainty);
}
// Helper recursively prints all paths through the ratings matrix, starting
// at column col.
static void PrintMatrixPaths(int col, int dim,
const MATRIX& ratings,
int length, const BLOB_CHOICE** blob_choices,
const UNICHARSET& unicharset,
const char *label, FILE *output_file) {
for (int row = col; row < dim && row - col < ratings.bandwidth(); ++row) {
if (ratings.get(col, row) != NOT_CLASSIFIED) {
BLOB_CHOICE_IT bc_it(ratings.get(col, row));
for (bc_it.mark_cycle_pt(); !bc_it.cycled_list(); bc_it.forward()) {
blob_choices[length] = bc_it.data();
if (row + 1 < dim) {
PrintMatrixPaths(row + 1, dim, ratings, length + 1, blob_choices,
unicharset, label, output_file);
} else {
PrintPath(length + 1, blob_choices, unicharset, label, output_file);
}
}
}
}
}
// Runs classify_word_pass1() on the current word. Outputs Tesseract's
// raw choice as a result of the classification. For words labeled with a
// single unichar also outputs all alternatives from blob_choices of the
// best choice.
void Tesseract::ambigs_classify_and_output(const char *label,
PAGE_RES_IT* pr_it,
FILE *output_file) {
// Classify word.
fflush(stdout);
WordData word_data(*pr_it);
SetupWordPassN(1, &word_data);
classify_word_and_language(&Tesseract::classify_word_pass1,
pr_it, &word_data);
WERD_RES* werd_res = word_data.word;
WERD_CHOICE *best_choice = werd_res->best_choice;
ASSERT_HOST(best_choice != NULL);
// Compute the number of unichars in the label.
GenericVector<UNICHAR_ID> encoding;
if (!unicharset.encode_string(label, true, &encoding, NULL, NULL)) {
tprintf("Not outputting illegal unichar %s\n", label);
return;
}
// Dump all paths through the ratings matrix (which is normally small).
int dim = werd_res->ratings->dimension();
const BLOB_CHOICE** blob_choices = new const BLOB_CHOICE*[dim];
PrintMatrixPaths(0, dim, *werd_res->ratings, 0, blob_choices,
unicharset, label, output_file);
delete [] blob_choices;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: pagewalk.cpp (Formerly walkers.c)
* Description: Block list processors
* Author: Phil Cheatle
* Created: Thu Oct 10 16:25:24 BST 1991
*
* (C) Copyright 1991, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include "pageres.h"
#include "tesseractclass.h"
/**
* process_selected_words()
*
* Walk the current block list applying the specified word processor function
* to each word that overlaps the selection_box.
*/
namespace tesseract {
void Tesseract::process_selected_words(
PAGE_RES* page_res, // blocks to check
TBOX & selection_box,
BOOL8(tesseract::Tesseract::*word_processor)(PAGE_RES_IT* pr_it)) {
for (PAGE_RES_IT page_res_it(page_res); page_res_it.word() != NULL;
page_res_it.forward()) {
WERD* word = page_res_it.word()->word;
if (word->bounding_box().overlap(selection_box)) {
if (!(this->*word_processor)(&page_res_it))
return;
}
}
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: tesseractclass.h
// Description: The Tesseract class. It holds/owns everything needed
// to run Tesseract on a single language, and also a set of
// sub-Tesseracts to run sub-languages. For thread safety, *every*
// global variable goes in here, directly, or indirectly.
// This makes it safe to run multiple Tesseracts in different
// threads in parallel, and keeps the different language
// instances separate.
// Author: Ray Smith
// Created: Fri Mar 07 08:17:01 PST 2008
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_TESSERACTCLASS_H__
#define TESSERACT_CCMAIN_TESSERACTCLASS_H__
#include "allheaders.h"
#include "control.h"
#include "docqual.h"
#include "devanagari_processing.h"
#include "genericvector.h"
#include "params.h"
#include "ocrclass.h"
#include "textord.h"
#include "wordrec.h"
class BLOB_CHOICE_LIST_CLIST;
class BLOCK_LIST;
class CharSamp;
struct OSResults;
class PAGE_RES;
class PAGE_RES_IT;
struct Pix;
class ROW;
class SVMenuNode;
class TBOX;
class TO_BLOCK_LIST;
class WERD;
class WERD_CHOICE;
class WERD_RES;
// Top-level class for all tesseract global instance data.
// This class either holds or points to all data used by an instance
// of Tesseract, including the memory allocator. When this is
// complete, Tesseract will be thread-safe. UNTIL THEN, IT IS NOT!
//
// NOTE to developers: Do not create cyclic dependencies through this class!
// The directory dependency tree must remain a tree! The keep this clean,
// lower-level code (eg in ccutil, the bottom level) must never need to
// know about the content of a higher-level directory.
// The following scheme will grant the easiest access to lower-level
// global members without creating a cyclic dependency:
//
// Class Hierarchy (^ = inheritance):
//
// CCUtil (ccutil/ccutil.h)
// ^ Members include: UNICHARSET
// CUtil (cutil/cutil_class.h)
// ^ Members include: TBLOB*, TEXTBLOCK*
// CCStruct (ccstruct/ccstruct.h)
// ^ Members include: Image
// Classify (classify/classify.h)
// ^ Members include: Dict
// WordRec (wordrec/wordrec.h)
// ^ Members include: WERD*, DENORM*
// Tesseract (ccmain/tesseractclass.h)
// Members include: Pix*, CubeRecoContext*,
// TesseractCubeCombiner*
//
// Other important classes:
//
// TessBaseAPI (api/baseapi.h)
// Members include: BLOCK_LIST*, PAGE_RES*,
// Tesseract*, ImageThresholder*
// Dict (dict/dict.h)
// Members include: Image* (private)
//
// NOTE: that each level contains members that correspond to global
// data that is defined (and used) at that level, not necessarily where
// the type is defined so for instance:
// BOOL_VAR_H(textord_show_blobs, false, "Display unsorted blobs");
// goes inside the Textord class, not the cc_util class.
namespace tesseract {
class ColumnFinder;
class CubeLineObject;
class CubeObject;
class CubeRecoContext;
class EquationDetect;
class Tesseract;
class TesseractCubeCombiner;
// A collection of various variables for statistics and debugging.
struct TesseractStats {
TesseractStats()
: adaption_word_number(0),
doc_blob_quality(0),
doc_outline_errs(0),
doc_char_quality(0),
good_char_count(0),
doc_good_char_quality(0),
word_count(0),
dict_words(0),
tilde_crunch_written(false),
last_char_was_newline(true),
last_char_was_tilde(false),
write_results_empty_block(true) {}
inT32 adaption_word_number;
inT16 doc_blob_quality;
inT16 doc_outline_errs;
inT16 doc_char_quality;
inT16 good_char_count;
inT16 doc_good_char_quality;
inT32 word_count; // count of word in the document
inT32 dict_words; // number of dicitionary words in the document
STRING dump_words_str; // accumulator used by dump_words()
// Flags used by write_results()
bool tilde_crunch_written;
bool last_char_was_newline;
bool last_char_was_tilde;
bool write_results_empty_block;
};
// Struct to hold all the pointers to relevant data for processing a word.
struct WordData {
WordData() : word(NULL), row(NULL), block(NULL), prev_word(NULL) {}
explicit WordData(const PAGE_RES_IT& page_res_it)
: word(page_res_it.word()), row(page_res_it.row()->row),
block(page_res_it.block()->block), prev_word(NULL) {}
WordData(BLOCK* block_in, ROW* row_in, WERD_RES* word_res)
: word(word_res), row(row_in), block(block_in), prev_word(NULL) {}
WERD_RES* word;
ROW* row;
BLOCK* block;
WordData* prev_word;
PointerVector<WERD_RES> lang_words;
};
// Definition of a Tesseract WordRecognizer. The WordData provides the context
// of row/block, in_word holds an initialized, possibly pre-classified word,
// that the recognizer may or may not consume (but if so it sets *in_word=NULL)
// and produces one or more output words in out_words, which may be the
// consumed in_word, or may be generated independently.
// This api allows both a conventional tesseract classifier to work, or a
// line-level classifier that generates multiple words from a merged input.
typedef void (Tesseract::*WordRecognizer)(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
class Tesseract : public Wordrec {
public:
Tesseract();
~Tesseract();
// Clear as much used memory as possible without resetting the adaptive
// classifier or losing any other classifier data.
void Clear();
// Clear all memory of adaption for this and all subclassifiers.
void ResetAdaptiveClassifier();
// Clear the document dictionary for this and all subclassifiers.
void ResetDocumentDictionary();
// Set the equation detector.
void SetEquationDetect(EquationDetect* detector);
// Simple accessors.
const FCOORD& reskew() const {
return reskew_;
}
// Destroy any existing pix and return a pointer to the pointer.
Pix** mutable_pix_binary() {
Clear();
return &pix_binary_;
}
Pix* pix_binary() const {
return pix_binary_;
}
Pix* pix_grey() const {
return pix_grey_;
}
void set_pix_grey(Pix* grey_pix) {
pixDestroy(&pix_grey_);
pix_grey_ = grey_pix;
}
// Returns a pointer to a Pix representing the best available image of the
// page. The image will be 8-bit grey if the input was grey or color. Note
// that in grey 0 is black and 255 is white. If the input was binary, then
// the returned Pix will be binary. Note that here black is 1 and white is 0.
// To tell the difference pixGetDepth() will return 8 or 1.
// In either case, the return value is a borrowed Pix, and should not be
// deleted or pixDestroyed.
Pix* BestPix() const {
return pix_grey_ != NULL ? pix_grey_ : pix_binary_;
}
void set_pix_thresholds(Pix* thresholds) {
pixDestroy(&pix_thresholds_);
pix_thresholds_ = thresholds;
}
int source_resolution() const {
return source_resolution_;
}
void set_source_resolution(int ppi) {
source_resolution_ = ppi;
}
int ImageWidth() const {
return pixGetWidth(pix_binary_);
}
int ImageHeight() const {
return pixGetHeight(pix_binary_);
}
Pix* scaled_color() const {
return scaled_color_;
}
int scaled_factor() const {
return scaled_factor_;
}
void SetScaledColor(int factor, Pix* color) {
scaled_factor_ = factor;
scaled_color_ = color;
}
const Textord& textord() const {
return textord_;
}
Textord* mutable_textord() {
return &textord_;
}
bool right_to_left() const {
return right_to_left_;
}
int num_sub_langs() const {
return sub_langs_.size();
}
Tesseract* get_sub_lang(int index) const {
return sub_langs_[index];
}
// Returns true if any language uses Tesseract (as opposed to cube).
bool AnyTessLang() const {
if (tessedit_ocr_engine_mode != OEM_CUBE_ONLY) return true;
for (int i = 0; i < sub_langs_.size(); ++i) {
if (sub_langs_[i]->tessedit_ocr_engine_mode != OEM_CUBE_ONLY)
return true;
}
return false;
}
void SetBlackAndWhitelist();
// Perform steps to prepare underlying binary image/other data structures for
// page segmentation. Uses the strategy specified in the global variable
// pageseg_devanagari_split_strategy for perform splitting while preparing for
// page segmentation.
void PrepareForPageseg();
// Perform steps to prepare underlying binary image/other data structures for
// Tesseract OCR. The current segmentation is required by this method.
// Uses the strategy specified in the global variable
// ocr_devanagari_split_strategy for performing splitting while preparing for
// Tesseract ocr.
void PrepareForTessOCR(BLOCK_LIST* block_list,
Tesseract* osd_tess, OSResults* osr);
int SegmentPage(const STRING* input_file, BLOCK_LIST* blocks,
Tesseract* osd_tess, OSResults* osr);
void SetupWordScripts(BLOCK_LIST* blocks);
int AutoPageSeg(PageSegMode pageseg_mode,
BLOCK_LIST* blocks, TO_BLOCK_LIST* to_blocks,
Tesseract* osd_tess, OSResults* osr);
ColumnFinder* SetupPageSegAndDetectOrientation(
bool single_column, bool osd, bool only_osd,
BLOCK_LIST* blocks, Tesseract* osd_tess, OSResults* osr,
TO_BLOCK_LIST* to_blocks, Pix** photo_mask_pix, Pix** music_mask_pix);
// par_control.cpp
void PrerecAllWordsPar(const GenericVector<WordData>& words);
//// control.h /////////////////////////////////////////////////////////
bool ProcessTargetWord(const TBOX& word_box, const TBOX& target_word_box,
const char* word_config, int pass);
// Sets up the words ready for whichever engine is to be run
void SetupAllWordsPassN(int pass_n,
const TBOX* target_word_box,
const char* word_config,
PAGE_RES* page_res,
GenericVector<WordData>* words);
// Sets up the single word ready for whichever engine is to be run.
void SetupWordPassN(int pass_n, WordData* word);
// Runs word recognition on all the words.
bool RecogAllWordsPassN(int pass_n, ETEXT_DESC* monitor,
PAGE_RES_IT* pr_it,
GenericVector<WordData>* words);
bool recog_all_words(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config,
int dopasses);
void rejection_passes(PAGE_RES* page_res,
ETEXT_DESC* monitor,
const TBOX* target_word_box,
const char* word_config);
void bigram_correction_pass(PAGE_RES *page_res);
void blamer_pass(PAGE_RES* page_res);
// Sets script positions and detects smallcaps on all output words.
void script_pos_pass(PAGE_RES* page_res);
// Helper to recognize the word using the given (language-specific) tesseract.
// Returns positive if this recognizer found more new best words than the
// number kept from best_words.
int RetryWithLanguage(const WordData& word_data,
WordRecognizer recognizer,
WERD_RES** in_word,
PointerVector<WERD_RES>* best_words);
void classify_word_and_language(WordRecognizer recognizer,
PAGE_RES_IT* pr_it,
WordData* word_data);
void classify_word_pass1(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
void recog_pseudo_word(PAGE_RES* page_res, // blocks to check
TBOX &selection_box);
void fix_rep_char(PAGE_RES_IT* page_res_it);
ACCEPTABLE_WERD_TYPE acceptable_word_string(const UNICHARSET& char_set,
const char *s,
const char *lengths);
void match_word_pass_n(int pass_n, WERD_RES *word, ROW *row, BLOCK* block);
void classify_word_pass2(const WordData& word_data,
WERD_RES** in_word,
PointerVector<WERD_RES>* out_words);
void ReportXhtFixResult(bool accept_new_word, float new_x_ht,
WERD_RES* word, WERD_RES* new_word);
bool RunOldFixXht(WERD_RES *word, BLOCK* block, ROW *row);
bool TrainedXheightFix(WERD_RES *word, BLOCK* block, ROW *row);
BOOL8 recog_interactive(PAGE_RES_IT* pr_it);
// Set fonts of this word.
void set_word_fonts(WERD_RES *word);
void font_recognition_pass(PAGE_RES* page_res);
void dictionary_correction_pass(PAGE_RES* page_res);
BOOL8 check_debug_pt(WERD_RES *word, int location);
//// superscript.cpp ////////////////////////////////////////////////////
bool SubAndSuperscriptFix(WERD_RES *word_res);
void GetSubAndSuperscriptCandidates(const WERD_RES *word,
int *num_rebuilt_leading,
ScriptPos *leading_pos,
float *leading_certainty,
int *num_rebuilt_trailing,
ScriptPos *trailing_pos,
float *trailing_certainty,
float *avg_certainty,
float *unlikely_threshold);
WERD_RES *TrySuperscriptSplits(int num_chopped_leading,
float leading_certainty,
ScriptPos leading_pos,
int num_chopped_trailing,
float trailing_certainty,
ScriptPos trailing_pos,
WERD_RES *word,
bool *is_good,
int *retry_leading,
int *retry_trailing);
bool BelievableSuperscript(bool debug,
const WERD_RES &word,
float certainty_threshold,
int *left_ok,
int *right_ok) const;
//// cube_control.cpp ///////////////////////////////////////////////////
bool init_cube_objects(bool load_combiner,
TessdataManager *tessdata_manager);
// Iterates through tesseract's results and calls cube on each word,
// combining the results with the existing tesseract result.
void run_cube_combiner(PAGE_RES *page_res);
// Recognizes a single word using (only) cube. Compatible with
// Tesseract's classify_word_pass1/classify_word_pass2.
void cube_word_pass1(BLOCK* block, ROW *row, WERD_RES *word);
// Cube recognizer to recognize a single word as with classify_word_pass1
// but also returns the cube object in case the combiner is needed.
CubeObject* cube_recognize_word(BLOCK* block, WERD_RES* word);
// Combines the cube and tesseract results for a single word, leaving the
// result in tess_word.
void cube_combine_word(CubeObject* cube_obj, WERD_RES* cube_word,
WERD_RES* tess_word);
// Call cube on the current word, and write the result to word.
// Sets up a fake result and returns false if something goes wrong.
bool cube_recognize(CubeObject *cube_obj, BLOCK* block, WERD_RES *word);
void fill_werd_res(const BoxWord& cube_box_word,
const char* cube_best_str,
WERD_RES* tess_werd_res);
bool extract_cube_state(CubeObject* cube_obj, int* num_chars,
Boxa** char_boxes, CharSamp*** char_samples);
bool create_cube_box_word(Boxa *char_boxes, int num_chars,
TBOX word_box, BoxWord* box_word);
//// output.h //////////////////////////////////////////////////////////
void output_pass(PAGE_RES_IT &page_res_it, const TBOX *target_word_box);
void write_results(PAGE_RES_IT &page_res_it, // full info
char newline_type, // type of newline
BOOL8 force_eol // override tilde crunch?
);
void set_unlv_suspects(WERD_RES *word);
UNICHAR_ID get_rep_char(WERD_RES *word); // what char is repeated?
BOOL8 acceptable_number_string(const char *s,
const char *lengths);
inT16 count_alphanums(const WERD_CHOICE &word);
inT16 count_alphas(const WERD_CHOICE &word);
//// tessedit.h ////////////////////////////////////////////////////////
void read_config_file(const char *filename, SetParamConstraint constraint);
// Initialize for potentially a set of languages defined by the language
// string and recursively any additional languages required by any language
// traineddata file (via tessedit_load_sublangs in its config) that is loaded.
// See init_tesseract_internal for args.
int init_tesseract(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
int init_tesseract(const char *datapath,
const char *language,
OcrEngineMode oem) {
return init_tesseract(datapath, NULL, language, oem,
NULL, 0, NULL, NULL, false);
}
// Common initialization for a single language.
// arg0 is the datapath for the tessdata directory, which could be the
// path of the tessdata directory with no trailing /, or (if tessdata
// lives in the same directory as the executable, the path of the executable,
// hence the name arg0.
// textbase is an optional output file basename (used only for training)
// language is the language code to load.
// oem controls which engine(s) will operate on the image
// configs (argv) is an array of config filenames to load variables from.
// May be NULL.
// configs_size (argc) is the number of elements in configs.
// vars_vec is an optional vector of variables to set.
// vars_values is an optional corresponding vector of values for the variables
// in vars_vec.
// If set_only_init_params is true, then only the initialization variables
// will be set.
int init_tesseract_internal(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
// Set the universal_id member of each font to be unique among all
// instances of the same font loaded.
void SetupUniversalFontIds();
int init_tesseract_lm(const char *arg0,
const char *textbase,
const char *language);
void recognize_page(STRING& image_name);
void end_tesseract();
bool init_tesseract_lang_data(const char *arg0,
const char *textbase,
const char *language,
OcrEngineMode oem,
char **configs,
int configs_size,
const GenericVector<STRING> *vars_vec,
const GenericVector<STRING> *vars_values,
bool set_only_init_params);
void ParseLanguageString(const char* lang_str,
GenericVector<STRING>* to_load,
GenericVector<STRING>* not_to_load);
//// pgedit.h //////////////////////////////////////////////////////////
SVMenuNode *build_menu_new();
#ifndef GRAPHICS_DISABLED
void pgeditor_main(int width, int height, PAGE_RES* page_res);
#endif // GRAPHICS_DISABLED
void process_image_event( // action in image win
const SVEvent &event);
BOOL8 process_cmd_win_event( // UI command semantics
inT32 cmd_event, // which menu item?
char *new_value // any prompt data
);
void debug_word(PAGE_RES* page_res, const TBOX &selection_box);
void do_re_display(
BOOL8 (tesseract::Tesseract::*word_painter)(PAGE_RES_IT* pr_it));
BOOL8 word_display(PAGE_RES_IT* pr_it);
BOOL8 word_bln_display(PAGE_RES_IT* pr_it);
BOOL8 word_blank_and_set_display(PAGE_RES_IT* pr_its);
BOOL8 word_set_display(PAGE_RES_IT* pr_it);
// #ifndef GRAPHICS_DISABLED
BOOL8 word_dumper(PAGE_RES_IT* pr_it);
// #endif // GRAPHICS_DISABLED
void blob_feature_display(PAGE_RES* page_res, const TBOX& selection_box);
//// reject.h //////////////////////////////////////////////////////////
// make rej map for word
void make_reject_map(WERD_RES *word, ROW *row, inT16 pass);
BOOL8 one_ell_conflict(WERD_RES *word_res, BOOL8 update_map);
inT16 first_alphanum_index(const char *word,
const char *word_lengths);
inT16 first_alphanum_offset(const char *word,
const char *word_lengths);
inT16 alpha_count(const char *word,
const char *word_lengths);
BOOL8 word_contains_non_1_digit(const char *word,
const char *word_lengths);
void dont_allow_1Il(WERD_RES *word);
inT16 count_alphanums( //how many alphanums
WERD_RES *word);
void flip_0O(WERD_RES *word);
BOOL8 non_0_digit(const UNICHARSET& ch_set, UNICHAR_ID unichar_id);
BOOL8 non_O_upper(const UNICHARSET& ch_set, UNICHAR_ID unichar_id);
BOOL8 repeated_nonalphanum_wd(WERD_RES *word, ROW *row);
void nn_match_word( //Match a word
WERD_RES *word,
ROW *row);
void nn_recover_rejects(WERD_RES *word, ROW *row);
void set_done( //set done flag
WERD_RES *word,
inT16 pass);
inT16 safe_dict_word(const WERD_RES *werd_res); // is best_choice in dict?
void flip_hyphens(WERD_RES *word);
void reject_I_1_L(WERD_RES *word);
void reject_edge_blobs(WERD_RES *word);
void reject_mostly_rejects(WERD_RES *word);
//// adaptions.h ///////////////////////////////////////////////////////
BOOL8 word_adaptable( //should we adapt?
WERD_RES *word,
uinT16 mode);
//// tfacepp.cpp ///////////////////////////////////////////////////////
void recog_word_recursive(WERD_RES* word);
void recog_word(WERD_RES *word);
void split_and_recog_word(WERD_RES* word);
void split_word(WERD_RES *word,
int split_pt,
WERD_RES **right_piece,
BlamerBundle **orig_blamer_bundle) const;
void join_words(WERD_RES *word,
WERD_RES *word2,
BlamerBundle *orig_bb) const;
//// fixspace.cpp ///////////////////////////////////////////////////////
BOOL8 digit_or_numeric_punct(WERD_RES *word, int char_position);
inT16 eval_word_spacing(WERD_RES_LIST &word_res_list);
void match_current_words(WERD_RES_LIST &words, ROW *row, BLOCK* block);
inT16 fp_eval_word_spacing(WERD_RES_LIST &word_res_list);
void fix_noisy_space_list(WERD_RES_LIST &best_perm, ROW *row, BLOCK* block);
void fix_fuzzy_space_list(WERD_RES_LIST &best_perm, ROW *row, BLOCK* block);
void fix_sp_fp_word(WERD_RES_IT &word_res_it, ROW *row, BLOCK* block);
void fix_fuzzy_spaces( //find fuzzy words
ETEXT_DESC *monitor, //progress monitor
inT32 word_count, //count of words in doc
PAGE_RES *page_res);
void dump_words(WERD_RES_LIST &perm, inT16 score,
inT16 mode, BOOL8 improved);
BOOL8 fixspace_thinks_word_done(WERD_RES *word);
inT16 worst_noise_blob(WERD_RES *word_res, float *worst_noise_score);
float blob_noise_score(TBLOB *blob);
void break_noisiest_blob_word(WERD_RES_LIST &words);
//// docqual.cpp ////////////////////////////////////////////////////////
GARBAGE_LEVEL garbage_word(WERD_RES *word, BOOL8 ok_dict_word);
BOOL8 potential_word_crunch(WERD_RES *word,
GARBAGE_LEVEL garbage_level,
BOOL8 ok_dict_word);
void tilde_crunch(PAGE_RES_IT &page_res_it);
void unrej_good_quality_words( //unreject potential
PAGE_RES_IT &page_res_it);
void doc_and_block_rejection( //reject big chunks
PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc);
void quality_based_rejection(PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc);
void convert_bad_unlv_chs(WERD_RES *word_res);
void tilde_delete(PAGE_RES_IT &page_res_it);
inT16 word_blob_quality(WERD_RES *word, ROW *row);
void word_char_quality(WERD_RES *word, ROW *row, inT16 *match_count,
inT16 *accepted_match_count);
void unrej_good_chs(WERD_RES *word, ROW *row);
inT16 count_outline_errs(char c, inT16 outline_count);
inT16 word_outline_errs(WERD_RES *word);
BOOL8 terrible_word_crunch(WERD_RES *word, GARBAGE_LEVEL garbage_level);
CRUNCH_MODE word_deletable(WERD_RES *word, inT16 &delete_mode);
inT16 failure_count(WERD_RES *word);
BOOL8 noise_outlines(TWERD *word);
//// pagewalk.cpp ///////////////////////////////////////////////////////
void
process_selected_words (
PAGE_RES* page_res, // blocks to check
//function to call
TBOX & selection_box,
BOOL8 (tesseract::Tesseract::*word_processor)(PAGE_RES_IT* pr_it));
//// tessbox.cpp ///////////////////////////////////////////////////////
void tess_add_doc_word( //test acceptability
WERD_CHOICE *word_choice //after context
);
void tess_segment_pass_n(int pass_n, WERD_RES *word);
bool tess_acceptable_word(WERD_RES *word);
//// applybox.cpp //////////////////////////////////////////////////////
// Applies the box file based on the image name fname, and resegments
// the words in the block_list (page), with:
// blob-mode: one blob per line in the box file, words as input.
// word/line-mode: one blob per space-delimited unit after the #, and one word
// per line in the box file. (See comment above for box file format.)
// If find_segmentation is true, (word/line mode) then the classifier is used
// to re-segment words/lines to match the space-delimited truth string for
// each box. In this case, the input box may be for a word or even a whole
// text line, and the output words will contain multiple blobs corresponding
// to the space-delimited input string.
// With find_segmentation false, no classifier is needed, but the chopper
// can still be used to correctly segment touching characters with the help
// of the input boxes.
// In the returned PAGE_RES, the WERD_RES are setup as they would be returned
// from normal classification, ie. with a word, chopped_word, rebuild_word,
// seam_array, denorm, box_word, and best_state, but NO best_choice or
// raw_choice, as they would require a UNICHARSET, which we aim to avoid.
// Instead, the correct_text member of WERD_RES is set, and this may be later
// converted to a best_choice using CorrectClassifyWords. CorrectClassifyWords
// is not required before calling ApplyBoxTraining.
PAGE_RES* ApplyBoxes(const STRING& fname, bool find_segmentation,
BLOCK_LIST *block_list);
// Any row xheight that is significantly different from the median is set
// to the median.
void PreenXHeights(BLOCK_LIST *block_list);
// Builds a PAGE_RES from the block_list in the way required for ApplyBoxes:
// All fuzzy spaces are removed, and all the words are maximally chopped.
PAGE_RES* SetupApplyBoxes(const GenericVector<TBOX>& boxes,
BLOCK_LIST *block_list);
// Tests the chopper by exhaustively running chop_one_blob.
// The word_res will contain filled chopped_word, seam_array, denorm,
// box_word and best_state for the maximally chopped word.
void MaximallyChopWord(const GenericVector<TBOX>& boxes,
BLOCK* block, ROW* row, WERD_RES* word_res);
// Gather consecutive blobs that match the given box into the best_state
// and corresponding correct_text.
// Fights over which box owns which blobs are settled by pre-chopping and
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an appropriate blob for a box.
// This means that occasionally, blobs may be incorrectly segmented if the
// chopper fails to find a suitable chop point.
bool ResegmentCharBox(PAGE_RES* page_res, const TBOX *prev_box,
const TBOX& box, const TBOX& next_box,
const char* correct_text);
// Consume all source blobs that strongly overlap the given box,
// putting them into a new word, with the correct_text label.
// Fights over which box owns which blobs are settled by
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an overlapping blob for a box.
bool ResegmentWordBox(BLOCK_LIST *block_list,
const TBOX& box, const TBOX& next_box,
const char* correct_text);
// Resegments the words by running the classifier in an attempt to find the
// correct segmentation that produces the required string.
void ReSegmentByClassification(PAGE_RES* page_res);
// Converts the space-delimited string of utf8 text to a vector of UNICHAR_ID.
// Returns false if an invalid UNICHAR_ID is encountered.
bool ConvertStringToUnichars(const char* utf8,
GenericVector<UNICHAR_ID>* class_ids);
// Resegments the word to achieve the target_text from the classifier.
// Returns false if the re-segmentation fails.
// Uses brute-force combination of upto kMaxGroupSize adjacent blobs, and
// applies a full search on the classifier results to find the best classified
// segmentation. As a compromise to obtain better recall, 1-1 ambigiguity
// substitutions ARE used.
bool FindSegmentation(const GenericVector<UNICHAR_ID>& target_text,
WERD_RES* word_res);
// Recursive helper to find a match to the target_text (from text_index
// position) in the choices (from choices_pos position).
// Choices is an array of GenericVectors, of length choices_length, with each
// element representing a starting position in the word, and the
// GenericVector holding classification results for a sequence of consecutive
// blobs, with index 0 being a single blob, index 1 being 2 blobs etc.
void SearchForText(const GenericVector<BLOB_CHOICE_LIST*>* choices,
int choices_pos, int choices_length,
const GenericVector<UNICHAR_ID>& target_text,
int text_index,
float rating, GenericVector<int>* segmentation,
float* best_rating, GenericVector<int>* best_segmentation);
// Counts up the labelled words and the blobs within.
// Deletes all unused or emptied words, counting the unused ones.
// Resets W_BOL and W_EOL flags correctly.
// Builds the rebuild_word and rebuilds the box_word.
void TidyUp(PAGE_RES* page_res);
// Logs a bad box by line in the box file and box coords.
void ReportFailedBox(int boxfile_lineno, TBOX box, const char *box_ch,
const char *err_msg);
// Creates a fake best_choice entry in each WERD_RES with the correct text.
void CorrectClassifyWords(PAGE_RES* page_res);
// Call LearnWord to extract features for labelled blobs within each word.
// Features are written to the given filename.
void ApplyBoxTraining(const STRING& filename, PAGE_RES* page_res);
//// fixxht.cpp ///////////////////////////////////////////////////////
// Returns the number of misfit blob tops in this word.
int CountMisfitTops(WERD_RES *word_res);
// Returns a new x-height in pixels (original image coords) that is
// maximally compatible with the result in word_res.
// Returns 0.0f if no x-height is found that is better than the current
// estimate.
float ComputeCompatibleXheight(WERD_RES *word_res);
//// Data members ///////////////////////////////////////////////////////
// TODO(ocr-team): Find and remove obsolete parameters.
BOOL_VAR_H(tessedit_resegment_from_boxes, false,
"Take segmentation and labeling from box file");
BOOL_VAR_H(tessedit_resegment_from_line_boxes, false,
"Conversion of word/line box file to char box file");
BOOL_VAR_H(tessedit_train_from_boxes, false,
"Generate training data from boxed chars");
BOOL_VAR_H(tessedit_make_boxes_from_boxes, false,
"Generate more boxes from boxed chars");
BOOL_VAR_H(tessedit_dump_pageseg_images, false,
"Dump intermediate images made during page segmentation");
INT_VAR_H(tessedit_pageseg_mode, PSM_SINGLE_BLOCK,
"Page seg mode: 0=osd only, 1=auto+osd, 2=auto, 3=col, 4=block,"
" 5=line, 6=word, 7=char"
" (Values from PageSegMode enum in publictypes.h)");
INT_VAR_H(tessedit_ocr_engine_mode, tesseract::OEM_TESSERACT_ONLY,
"Which OCR engine(s) to run (Tesseract, Cube, both). Defaults"
" to loading and running only Tesseract (no Cube, no combiner)."
" (Values from OcrEngineMode enum in tesseractclass.h)");
STRING_VAR_H(tessedit_char_blacklist, "",
"Blacklist of chars not to recognize");
STRING_VAR_H(tessedit_char_whitelist, "",
"Whitelist of chars to recognize");
STRING_VAR_H(tessedit_char_unblacklist, "",
"List of chars to override tessedit_char_blacklist");
BOOL_VAR_H(tessedit_ambigs_training, false,
"Perform training for ambiguities");
INT_VAR_H(pageseg_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing page-segmentation.");
INT_VAR_H(ocr_devanagari_split_strategy,
tesseract::ShiroRekhaSplitter::NO_SPLIT,
"Whether to use the top-line splitting process for Devanagari "
"documents while performing ocr.");
STRING_VAR_H(tessedit_write_params_to_file, "",
"Write all parameters to the given file.");
BOOL_VAR_H(tessedit_adaption_debug, false,
"Generate and print debug information for adaption");
INT_VAR_H(bidi_debug, 0, "Debug level for BiDi");
INT_VAR_H(applybox_debug, 1, "Debug level");
INT_VAR_H(applybox_page, 0, "Page number to apply boxes from");
STRING_VAR_H(applybox_exposure_pattern, ".exp",
"Exposure value follows this pattern in the image"
" filename. The name of the image files are expected"
" to be in the form [lang].[fontname].exp[num].tif");
BOOL_VAR_H(applybox_learn_chars_and_char_frags_mode, false,
"Learn both character fragments (as is done in the"
" special low exposure mode) as well as unfragmented"
" characters.");
BOOL_VAR_H(applybox_learn_ngrams_mode, false,
"Each bounding box is assumed to contain ngrams. Only"
" learn the ngrams whose outlines overlap horizontally.");
BOOL_VAR_H(tessedit_display_outwords, false, "Draw output words");
BOOL_VAR_H(tessedit_dump_choices, false, "Dump char choices");
BOOL_VAR_H(tessedit_timing_debug, false, "Print timing stats");
BOOL_VAR_H(tessedit_fix_fuzzy_spaces, true,
"Try to improve fuzzy spaces");
BOOL_VAR_H(tessedit_unrej_any_wd, false,
"Dont bother with word plausibility");
BOOL_VAR_H(tessedit_fix_hyphens, true, "Crunch double hyphens?");
BOOL_VAR_H(tessedit_redo_xheight, true, "Check/Correct x-height");
BOOL_VAR_H(tessedit_enable_doc_dict, true,
"Add words to the document dictionary");
BOOL_VAR_H(tessedit_debug_fonts, false, "Output font info per char");
BOOL_VAR_H(tessedit_debug_block_rejection, false, "Block and Row stats");
BOOL_VAR_H(tessedit_enable_bigram_correction, true,
"Enable correction based on the word bigram dictionary.");
BOOL_VAR_H(tessedit_enable_dict_correction, false,
"Enable single word correction based on the dictionary.");
INT_VAR_H(tessedit_bigram_debug, 0, "Amount of debug output for bigram "
"correction.");
INT_VAR_H(debug_x_ht_level, 0, "Reestimate debug");
BOOL_VAR_H(debug_acceptable_wds, false, "Dump word pass/fail chk");
STRING_VAR_H(chs_leading_punct, "('`\"", "Leading punctuation");
STRING_VAR_H(chs_trailing_punct1, ").,;:?!", "1st Trailing punctuation");
STRING_VAR_H(chs_trailing_punct2, ")'`\"", "2nd Trailing punctuation");
double_VAR_H(quality_rej_pc, 0.08, "good_quality_doc lte rejection limit");
double_VAR_H(quality_blob_pc, 0.0, "good_quality_doc gte good blobs limit");
double_VAR_H(quality_outline_pc, 1.0,
"good_quality_doc lte outline error limit");
double_VAR_H(quality_char_pc, 0.95, "good_quality_doc gte good char limit");
INT_VAR_H(quality_min_initial_alphas_reqd, 2, "alphas in a good word");
INT_VAR_H(tessedit_tess_adaption_mode, 0x27,
"Adaptation decision algorithm for tess");
BOOL_VAR_H(tessedit_minimal_rej_pass1, false,
"Do minimal rejection on pass 1 output");
BOOL_VAR_H(tessedit_test_adaption, false, "Test adaption criteria");
BOOL_VAR_H(tessedit_matcher_log, false, "Log matcher activity");
INT_VAR_H(tessedit_test_adaption_mode, 3,
"Adaptation decision algorithm for tess");
BOOL_VAR_H(test_pt, false, "Test for point");
double_VAR_H(test_pt_x, 99999.99, "xcoord");
double_VAR_H(test_pt_y, 99999.99, "ycoord");
INT_VAR_H(paragraph_debug_level, 0, "Print paragraph debug info.");
BOOL_VAR_H(paragraph_text_based, true,
"Run paragraph detection on the post-text-recognition "
"(more accurate)");
INT_VAR_H(cube_debug_level, 1, "Print cube debug info.");
STRING_VAR_H(outlines_odd, "%| ", "Non standard number of outlines");
STRING_VAR_H(outlines_2, "ij!?%\":;", "Non standard number of outlines");
BOOL_VAR_H(docqual_excuse_outline_errs, false,
"Allow outline errs in unrejection?");
BOOL_VAR_H(tessedit_good_quality_unrej, true,
"Reduce rejection on good docs");
BOOL_VAR_H(tessedit_use_reject_spaces, true, "Reject spaces?");
double_VAR_H(tessedit_reject_doc_percent, 65.00,
"%rej allowed before rej whole doc");
double_VAR_H(tessedit_reject_block_percent, 45.00,
"%rej allowed before rej whole block");
double_VAR_H(tessedit_reject_row_percent, 40.00,
"%rej allowed before rej whole row");
double_VAR_H(tessedit_whole_wd_rej_row_percent, 70.00,
"Number of row rejects in whole word rejects"
"which prevents whole row rejection");
BOOL_VAR_H(tessedit_preserve_blk_rej_perfect_wds, true,
"Only rej partially rejected words in block rejection");
BOOL_VAR_H(tessedit_preserve_row_rej_perfect_wds, true,
"Only rej partially rejected words in row rejection");
BOOL_VAR_H(tessedit_dont_blkrej_good_wds, false,
"Use word segmentation quality metric");
BOOL_VAR_H(tessedit_dont_rowrej_good_wds, false,
"Use word segmentation quality metric");
INT_VAR_H(tessedit_preserve_min_wd_len, 2,
"Only preserve wds longer than this");
BOOL_VAR_H(tessedit_row_rej_good_docs, true,
"Apply row rejection to good docs");
double_VAR_H(tessedit_good_doc_still_rowrej_wd, 1.1,
"rej good doc wd if more than this fraction rejected");
BOOL_VAR_H(tessedit_reject_bad_qual_wds, true,
"Reject all bad quality wds");
BOOL_VAR_H(tessedit_debug_doc_rejection, false, "Page stats");
BOOL_VAR_H(tessedit_debug_quality_metrics, false,
"Output data to debug file");
BOOL_VAR_H(bland_unrej, false, "unrej potential with no chekcs");
double_VAR_H(quality_rowrej_pc, 1.1,
"good_quality_doc gte good char limit");
BOOL_VAR_H(unlv_tilde_crunching, true,
"Mark v.bad words for tilde crunch");
BOOL_VAR_H(hocr_font_info, false,
"Add font info to hocr output");
BOOL_VAR_H(crunch_early_merge_tess_fails, true, "Before word crunch?");
BOOL_VAR_H(crunch_early_convert_bad_unlv_chs, false, "Take out ~^ early?");
double_VAR_H(crunch_terrible_rating, 80.0, "crunch rating lt this");
BOOL_VAR_H(crunch_terrible_garbage, true, "As it says");
double_VAR_H(crunch_poor_garbage_cert, -9.0,
"crunch garbage cert lt this");
double_VAR_H(crunch_poor_garbage_rate, 60, "crunch garbage rating lt this");
double_VAR_H(crunch_pot_poor_rate, 40, "POTENTIAL crunch rating lt this");
double_VAR_H(crunch_pot_poor_cert, -8.0, "POTENTIAL crunch cert lt this");
BOOL_VAR_H(crunch_pot_garbage, true, "POTENTIAL crunch garbage");
double_VAR_H(crunch_del_rating, 60, "POTENTIAL crunch rating lt this");
double_VAR_H(crunch_del_cert, -10.0, "POTENTIAL crunch cert lt this");
double_VAR_H(crunch_del_min_ht, 0.7, "Del if word ht lt xht x this");
double_VAR_H(crunch_del_max_ht, 3.0, "Del if word ht gt xht x this");
double_VAR_H(crunch_del_min_width, 3.0, "Del if word width lt xht x this");
double_VAR_H(crunch_del_high_word, 1.5,
"Del if word gt xht x this above bl");
double_VAR_H(crunch_del_low_word, 0.5, "Del if word gt xht x this below bl");
double_VAR_H(crunch_small_outlines_size, 0.6, "Small if lt xht x this");
INT_VAR_H(crunch_rating_max, 10, "For adj length in rating per ch");
INT_VAR_H(crunch_pot_indicators, 1, "How many potential indicators needed");
BOOL_VAR_H(crunch_leave_ok_strings, true, "Dont touch sensible strings");
BOOL_VAR_H(crunch_accept_ok, true, "Use acceptability in okstring");
BOOL_VAR_H(crunch_leave_accept_strings, false,
"Dont pot crunch sensible strings");
BOOL_VAR_H(crunch_include_numerals, false, "Fiddle alpha figures");
INT_VAR_H(crunch_leave_lc_strings, 4,
"Dont crunch words with long lower case strings");
INT_VAR_H(crunch_leave_uc_strings, 4,
"Dont crunch words with long lower case strings");
INT_VAR_H(crunch_long_repetitions, 3, "Crunch words with long repetitions");
INT_VAR_H(crunch_debug, 0, "As it says");
INT_VAR_H(fixsp_non_noise_limit, 1,
"How many non-noise blbs either side?");
double_VAR_H(fixsp_small_outlines_size, 0.28, "Small if lt xht x this");
BOOL_VAR_H(tessedit_prefer_joined_punct, false, "Reward punctation joins");
INT_VAR_H(fixsp_done_mode, 1, "What constitues done for spacing");
INT_VAR_H(debug_fix_space_level, 0, "Contextual fixspace debug");
STRING_VAR_H(numeric_punctuation, ".,",
"Punct. chs expected WITHIN numbers");
INT_VAR_H(x_ht_acceptance_tolerance, 8,
"Max allowed deviation of blob top outside of font data");
INT_VAR_H(x_ht_min_change, 8, "Min change in xht before actually trying it");
INT_VAR_H(superscript_debug, 0, "Debug level for sub & superscript fixer");
double_VAR_H(superscript_worse_certainty, 2.0, "How many times worse "
"certainty does a superscript position glyph need to be for us "
"to try classifying it as a char with a different baseline?");
double_VAR_H(superscript_bettered_certainty, 0.97, "What reduction in "
"badness do we think sufficient to choose a superscript over "
"what we'd thought. For example, a value of 0.6 means we want "
"to reduce badness of certainty by 40%");
double_VAR_H(superscript_scaledown_ratio, 0.4,
"A superscript scaled down more than this is unbelievably "
"small. For example, 0.3 means we expect the font size to "
"be no smaller than 30% of the text line font size.");
double_VAR_H(subscript_max_y_top, 0.5,
"Maximum top of a character measured as a multiple of x-height "
"above the baseline for us to reconsider whether it's a "
"subscript.");
double_VAR_H(superscript_min_y_bottom, 0.3,
"Minimum bottom of a character measured as a multiple of "
"x-height above the baseline for us to reconsider whether it's "
"a superscript.");
BOOL_VAR_H(tessedit_write_block_separators, false,
"Write block separators in output");
BOOL_VAR_H(tessedit_write_rep_codes, false,
"Write repetition char code");
BOOL_VAR_H(tessedit_write_unlv, false, "Write .unlv output file");
BOOL_VAR_H(tessedit_create_txt, true, "Write .txt output file");
BOOL_VAR_H(tessedit_create_hocr, false, "Write .html hOCR output file");
BOOL_VAR_H(tessedit_create_pdf, false, "Write .pdf output file");
STRING_VAR_H(unrecognised_char, "|",
"Output char for unidentified blobs");
INT_VAR_H(suspect_level, 99, "Suspect marker level");
INT_VAR_H(suspect_space_level, 100,
"Min suspect level for rejecting spaces");
INT_VAR_H(suspect_short_words, 2,
"Dont Suspect dict wds longer than this");
BOOL_VAR_H(suspect_constrain_1Il, false, "UNLV keep 1Il chars rejected");
double_VAR_H(suspect_rating_per_ch, 999.9, "Dont touch bad rating limit");
double_VAR_H(suspect_accept_rating, -999.9, "Accept good rating limit");
BOOL_VAR_H(tessedit_minimal_rejection, false, "Only reject tess failures");
BOOL_VAR_H(tessedit_zero_rejection, false, "Dont reject ANYTHING");
BOOL_VAR_H(tessedit_word_for_word, false,
"Make output have exactly one word per WERD");
BOOL_VAR_H(tessedit_zero_kelvin_rejection, false,
"Dont reject ANYTHING AT ALL");
BOOL_VAR_H(tessedit_consistent_reps, true, "Force all rep chars the same");
INT_VAR_H(tessedit_reject_mode, 0, "Rejection algorithm");
BOOL_VAR_H(tessedit_rejection_debug, false, "Adaption debug");
BOOL_VAR_H(tessedit_flip_0O, true, "Contextual 0O O0 flips");
double_VAR_H(tessedit_lower_flip_hyphen, 1.5,
"Aspect ratio dot/hyphen test");
double_VAR_H(tessedit_upper_flip_hyphen, 1.8,
"Aspect ratio dot/hyphen test");
BOOL_VAR_H(rej_trust_doc_dawg, false, "Use DOC dawg in 11l conf. detector");
BOOL_VAR_H(rej_1Il_use_dict_word, false, "Use dictword test");
BOOL_VAR_H(rej_1Il_trust_permuter_type, true, "Dont double check");
BOOL_VAR_H(rej_use_tess_accepted, true, "Individual rejection control");
BOOL_VAR_H(rej_use_tess_blanks, true, "Individual rejection control");
BOOL_VAR_H(rej_use_good_perm, true, "Individual rejection control");
BOOL_VAR_H(rej_use_sensible_wd, false, "Extend permuter check");
BOOL_VAR_H(rej_alphas_in_number_perm, false, "Extend permuter check");
double_VAR_H(rej_whole_of_mostly_reject_word_fract, 0.85, "if >this fract");
INT_VAR_H(tessedit_image_border, 2, "Rej blbs near image edge limit");
STRING_VAR_H(ok_repeated_ch_non_alphanum_wds, "-?*\075",
"Allow NN to unrej");
STRING_VAR_H(conflict_set_I_l_1, "Il1[]", "Il1 conflict set");
INT_VAR_H(min_sane_x_ht_pixels, 8, "Reject any x-ht lt or eq than this");
BOOL_VAR_H(tessedit_create_boxfile, false, "Output text with boxes");
INT_VAR_H(tessedit_page_number, -1,
"-1 -> All pages, else specifc page to process");
BOOL_VAR_H(tessedit_write_images, false, "Capture the image from the IPE");
BOOL_VAR_H(interactive_display_mode, false, "Run interactively?");
STRING_VAR_H(file_type, ".tif", "Filename extension");
BOOL_VAR_H(tessedit_override_permuter, true, "According to dict_word");
INT_VAR_H(tessdata_manager_debug_level, 0,
"Debug level for TessdataManager functions.");
STRING_VAR_H(tessedit_load_sublangs, "",
"List of languages to load with this one");
BOOL_VAR_H(tessedit_use_primary_params_model, false,
"In multilingual mode use params model of the primary language");
// Min acceptable orientation margin (difference in scores between top and 2nd
// choice in OSResults::orientations) to believe the page orientation.
double_VAR_H(min_orientation_margin, 7.0,
"Min acceptable orientation margin");
BOOL_VAR_H(textord_tabfind_show_vlines, false, "Debug line finding");
BOOL_VAR_H(textord_use_cjk_fp_model, FALSE, "Use CJK fixed pitch model");
BOOL_VAR_H(poly_allow_detailed_fx, false,
"Allow feature extractors to see the original outline");
BOOL_VAR_H(tessedit_init_config_only, false,
"Only initialize with the config file. Useful if the instance is "
"not going to be used for OCR but say only for layout analysis.");
BOOL_VAR_H(textord_equation_detect, false, "Turn on equation detector");
BOOL_VAR_H(textord_tabfind_vertical_text, true, "Enable vertical detection");
BOOL_VAR_H(textord_tabfind_force_vertical_text, false,
"Force using vertical text page mode");
double_VAR_H(textord_tabfind_vertical_text_ratio, 0.5,
"Fraction of textlines deemed vertical to use vertical page "
"mode");
double_VAR_H(textord_tabfind_aligned_gap_fraction, 0.75,
"Fraction of height used as a minimum gap for aligned blobs.");
INT_VAR_H(tessedit_parallelize, 0, "Run in parallel where possible");
BOOL_VAR_H(preserve_interword_spaces, false,
"Preserve multiple interword spaces");
BOOL_VAR_H(include_page_breaks, false,
"Include page separator string in output text after each "
"image/page.");
STRING_VAR_H(page_separator, "\f",
"Page separator (default is form feed control character)");
// The following parameters were deprecated and removed from their original
// locations. The parameters are temporarily kept here to give Tesseract
// users a chance to updated their [lang].traineddata and config files
// without introducing failures during Tesseract initialization.
// TODO(ocr-team): remove these parameters from the code once we are
// reasonably sure that Tesseract users have updated their data files.
//
// BEGIN DEPRECATED PARAMETERS
BOOL_VAR_H(textord_tabfind_vertical_horizontal_mix, true,
"find horizontal lines such as headers in vertical page mode");
INT_VAR_H(tessedit_ok_mode, 5, "Acceptance decision algorithm");
BOOL_VAR_H(load_fixed_length_dawgs, true, "Load fixed length"
" dawgs (e.g. for non-space delimited languages)");
INT_VAR_H(segment_debug, 0, "Debug the whole segmentation process");
BOOL_VAR_H(permute_debug, 0, "char permutation debug");
double_VAR_H(bestrate_pruning_factor, 2.0, "Multiplying factor of"
" current best rate to prune other hypotheses");
BOOL_VAR_H(permute_script_word, 0,
"Turn on word script consistency permuter");
BOOL_VAR_H(segment_segcost_rating, 0,
"incorporate segmentation cost in word rating?");
double_VAR_H(segment_reward_script, 0.95,
"Score multipler for script consistency within a word. "
"Being a 'reward' factor, it should be <= 1. "
"Smaller value implies bigger reward.");
BOOL_VAR_H(permute_fixed_length_dawg, 0,
"Turn on fixed-length phrasebook search permuter");
BOOL_VAR_H(permute_chartype_word, 0,
"Turn on character type (property) consistency permuter");
double_VAR_H(segment_reward_chartype, 0.97,
"Score multipler for char type consistency within a word. ");
double_VAR_H(segment_reward_ngram_best_choice, 0.99,
"Score multipler for ngram permuter's best choice"
" (only used in the Han script path).");
BOOL_VAR_H(ngram_permuter_activated, false,
"Activate character-level n-gram-based permuter");
BOOL_VAR_H(permute_only_top, false, "Run only the top choice permuter");
INT_VAR_H(language_model_fixed_length_choices_depth, 3,
"Depth of blob choice lists to explore"
" when fixed length dawgs are on");
BOOL_VAR_H(use_new_state_cost, FALSE,
"use new state cost heuristics for segmentation state evaluation");
double_VAR_H(heuristic_segcost_rating_base, 1.25,
"base factor for adding segmentation cost into word rating."
"It's a multiplying factor, the larger the value above 1, "
"the bigger the effect of segmentation cost.");
double_VAR_H(heuristic_weight_rating, 1,
"weight associated with char rating in combined cost of state");
double_VAR_H(heuristic_weight_width, 1000.0,
"weight associated with width evidence in combined cost of"
" state");
double_VAR_H(heuristic_weight_seamcut, 0,
"weight associated with seam cut in combined cost of state");
double_VAR_H(heuristic_max_char_wh_ratio, 2.0,
"max char width-to-height ratio allowed in segmentation");
BOOL_VAR_H(enable_new_segsearch, false,
"Enable new segmentation search path.");
double_VAR_H(segsearch_max_fixed_pitch_char_wh_ratio, 2.0,
"Maximum character width-to-height ratio for"
"fixed pitch fonts");
// END DEPRECATED PARAMETERS
//// ambigsrecog.cpp /////////////////////////////////////////////////////////
FILE *init_recog_training(const STRING &fname);
void recog_training_segmented(const STRING &fname,
PAGE_RES *page_res,
volatile ETEXT_DESC *monitor,
FILE *output_file);
void ambigs_classify_and_output(const char *label,
PAGE_RES_IT* pr_it,
FILE *output_file);
inline CubeRecoContext *GetCubeRecoContext() { return cube_cntxt_; }
private:
// The filename of a backup config file. If not null, then we currently
// have a temporary debug config file loaded, and backup_config_file_
// will be loaded, and set to null when debug is complete.
const char* backup_config_file_;
// The filename of a config file to read when processing a debug word.
STRING word_config_;
// Image used for input to layout analysis and tesseract recognition.
// May be modified by the ShiroRekhaSplitter to eliminate the top-line.
Pix* pix_binary_;
// Unmodified image used for input to cube. Always valid.
Pix* cube_binary_;
// Grey-level input image if the input was not binary, otherwise NULL.
Pix* pix_grey_;
// Thresholds that were used to generate the thresholded image from grey.
Pix* pix_thresholds_;
// Input image resolution after any scaling. The resolution is not well
// transmitted by operations on Pix, so we keep an independent record here.
int source_resolution_;
// The shiro-rekha splitter object which is used to split top-lines in
// Devanagari words to provide a better word and grapheme segmentation.
ShiroRekhaSplitter splitter_;
// Page segmentation/layout
Textord textord_;
// True if the primary language uses right_to_left reading order.
bool right_to_left_;
Pix* scaled_color_;
int scaled_factor_;
FCOORD deskew_;
FCOORD reskew_;
TesseractStats stats_;
// Sub-languages to be tried in addition to this.
GenericVector<Tesseract*> sub_langs_;
// Most recently used Tesseract out of this and sub_langs_. The default
// language for the next word.
Tesseract* most_recently_used_;
// The size of the font table, ie max possible font id + 1.
int font_table_size_;
// Cube objects.
CubeRecoContext* cube_cntxt_;
TesseractCubeCombiner *tess_cube_combiner_;
// Equation detector. Note: this pointer is NOT owned by the class.
EquationDetect* equ_detect_;
};
} // namespace tesseract
#endif // TESSERACT_CCMAIN_TESSERACTCLASS_H__
| C++ |
/**********************************************************************
* File: reject.cpp (Formerly reject.c)
* Description: Rejection functions used in tessedit
* Author: Phil Cheatle
* Created: Wed Sep 23 16:50:21 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#pragma warning(disable:4305) // int/float warnings
#endif
#include "tessvars.h"
#ifdef __UNIX__
#include <assert.h>
#include <errno.h>
#endif
#include "scanutils.h"
#include <ctype.h>
#include <string.h>
#include "genericvector.h"
#include "reject.h"
#include "control.h"
#include "docqual.h"
#include "globaloc.h" // For err_exit.
#include "globals.h"
#include "helpers.h"
#include "tesseractclass.h"
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
CLISTIZEH (STRING) CLISTIZE (STRING)
/*************************************************************************
* set_done()
*
* Set the done flag based on the word acceptability criteria
*************************************************************************/
namespace tesseract {
void Tesseract::set_done(WERD_RES *word, inT16 pass) {
word->done = word->tess_accepted &&
(strchr(word->best_choice->unichar_string().string(), ' ') == NULL);
bool word_is_ambig = word->best_choice->dangerous_ambig_found();
bool word_from_dict = word->best_choice->permuter() == SYSTEM_DAWG_PERM ||
word->best_choice->permuter() == FREQ_DAWG_PERM ||
word->best_choice->permuter() == USER_DAWG_PERM;
if (word->done && (pass == 1) && (!word_from_dict || word_is_ambig) &&
one_ell_conflict(word, FALSE)) {
if (tessedit_rejection_debug) tprintf("one_ell_conflict detected\n");
word->done = FALSE;
}
if (word->done && ((!word_from_dict &&
word->best_choice->permuter() != NUMBER_PERM) || word_is_ambig)) {
if (tessedit_rejection_debug) tprintf("non-dict or ambig word detected\n");
word->done = FALSE;
}
if (tessedit_rejection_debug) {
tprintf("set_done(): done=%d\n", word->done);
word->best_choice->print("");
}
}
/*************************************************************************
* make_reject_map()
*
* Sets the done flag to indicate whether the resylt is acceptable.
*
* Sets a reject map for the word.
*************************************************************************/
void Tesseract::make_reject_map(WERD_RES *word, ROW *row, inT16 pass) {
int i;
int offset;
flip_0O(word);
check_debug_pt(word, -1); // For trap only
set_done(word, pass); // Set acceptance
word->reject_map.initialise(word->best_choice->unichar_lengths().length());
reject_blanks(word);
/*
0: Rays original heuristic - the baseline
*/
if (tessedit_reject_mode == 0) {
if (!word->done)
reject_poor_matches(word);
} else if (tessedit_reject_mode == 5) {
/*
5: Reject I/1/l from words where there is no strong contextual confirmation;
the whole of any unacceptable words (incl PERM rej of dubious 1/I/ls);
and the whole of any words which are very small
*/
if (kBlnXHeight / word->denorm.y_scale() <= min_sane_x_ht_pixels) {
word->reject_map.rej_word_small_xht();
} else {
one_ell_conflict(word, TRUE);
/*
Originally the code here just used the done flag. Now I have duplicated
and unpacked the conditions for setting the done flag so that each
mechanism can be turned on or off independently. This works WITHOUT
affecting the done flag setting.
*/
if (rej_use_tess_accepted && !word->tess_accepted)
word->reject_map.rej_word_not_tess_accepted ();
if (rej_use_tess_blanks &&
(strchr (word->best_choice->unichar_string().string (), ' ') != NULL))
word->reject_map.rej_word_contains_blanks ();
WERD_CHOICE* best_choice = word->best_choice;
if (rej_use_good_perm) {
if ((best_choice->permuter() == SYSTEM_DAWG_PERM ||
best_choice->permuter() == FREQ_DAWG_PERM ||
best_choice->permuter() == USER_DAWG_PERM) &&
(!rej_use_sensible_wd ||
acceptable_word_string(*word->uch_set,
best_choice->unichar_string().string(),
best_choice->unichar_lengths().string()) !=
AC_UNACCEPTABLE)) {
// PASSED TEST
} else if (best_choice->permuter() == NUMBER_PERM) {
if (rej_alphas_in_number_perm) {
for (i = 0, offset = 0;
best_choice->unichar_string()[offset] != '\0';
offset += best_choice->unichar_lengths()[i++]) {
if (word->reject_map[i].accepted() &&
word->uch_set->get_isalpha(
best_choice->unichar_string().string() + offset,
best_choice->unichar_lengths()[i]))
word->reject_map[i].setrej_bad_permuter();
// rej alpha
}
}
} else {
word->reject_map.rej_word_bad_permuter();
}
}
/* Ambig word rejection was here once !!*/
}
} else {
tprintf("BAD tessedit_reject_mode\n");
err_exit();
}
if (tessedit_image_border > -1)
reject_edge_blobs(word);
check_debug_pt (word, 10);
if (tessedit_rejection_debug) {
tprintf("Permuter Type = %d\n", word->best_choice->permuter ());
tprintf("Certainty: %f Rating: %f\n",
word->best_choice->certainty (), word->best_choice->rating ());
tprintf("Dict word: %d\n", dict_word(*(word->best_choice)));
}
flip_hyphens(word);
check_debug_pt(word, 20);
}
} // namespace tesseract
void reject_blanks(WERD_RES *word) {
inT16 i;
inT16 offset;
for (i = 0, offset = 0; word->best_choice->unichar_string()[offset] != '\0';
offset += word->best_choice->unichar_lengths()[i], i += 1) {
if (word->best_choice->unichar_string()[offset] == ' ')
//rej unrecognised blobs
word->reject_map[i].setrej_tess_failure ();
}
}
namespace tesseract {
void Tesseract::reject_I_1_L(WERD_RES *word) {
inT16 i;
inT16 offset;
for (i = 0, offset = 0; word->best_choice->unichar_string()[offset] != '\0';
offset += word->best_choice->unichar_lengths()[i], i += 1) {
if (STRING (conflict_set_I_l_1).
contains (word->best_choice->unichar_string()[offset])) {
//rej 1Il conflict
word->reject_map[i].setrej_1Il_conflict ();
}
}
}
} // namespace tesseract
void reject_poor_matches(WERD_RES *word) {
float threshold = compute_reject_threshold(word->best_choice);
for (int i = 0; i < word->best_choice->length(); ++i) {
if (word->best_choice->unichar_id(i) == UNICHAR_SPACE)
word->reject_map[i].setrej_tess_failure();
else if (word->best_choice->certainty(i) < threshold)
word->reject_map[i].setrej_poor_match();
}
}
/**********************************************************************
* compute_reject_threshold
*
* Set a rejection threshold for this word.
* Initially this is a trivial function which looks for the largest
* gap in the certainty value.
**********************************************************************/
float compute_reject_threshold(WERD_CHOICE* word) {
float threshold; // rejection threshold
float bestgap = 0.0f; // biggest gap
float gapstart; // bottom of gap
// super iterator
BLOB_CHOICE_IT choice_it; // real iterator
int blob_count = word->length();
GenericVector<float> ratings;
ratings.init_to_size(blob_count, 0.0f);
for (int i = 0; i < blob_count; ++i) {
ratings[i] = word->certainty(i);
}
ratings.sort();
gapstart = ratings[0] - 1; // all reject if none better
if (blob_count >= 3) {
for (int index = 0; index < blob_count - 1; index++) {
if (ratings[index + 1] - ratings[index] > bestgap) {
bestgap = ratings[index + 1] - ratings[index];
// find biggest
gapstart = ratings[index];
}
}
}
threshold = gapstart + bestgap / 2;
return threshold;
}
/*************************************************************************
* reject_edge_blobs()
*
* If the word is perilously close to the edge of the image, reject those blobs
* in the word which are too close to the edge as they could be clipped.
*************************************************************************/
namespace tesseract {
void Tesseract::reject_edge_blobs(WERD_RES *word) {
TBOX word_box = word->word->bounding_box();
// Use the box_word as it is already denormed back to image coordinates.
int blobcount = word->box_word->length();
if (word_box.left() < tessedit_image_border ||
word_box.bottom() < tessedit_image_border ||
word_box.right() + tessedit_image_border > ImageWidth() - 1 ||
word_box.top() + tessedit_image_border > ImageHeight() - 1) {
ASSERT_HOST(word->reject_map.length() == blobcount);
for (int blobindex = 0; blobindex < blobcount; blobindex++) {
TBOX blob_box = word->box_word->BlobBox(blobindex);
if (blob_box.left() < tessedit_image_border ||
blob_box.bottom() < tessedit_image_border ||
blob_box.right() + tessedit_image_border > ImageWidth() - 1 ||
blob_box.top() + tessedit_image_border > ImageHeight() - 1) {
word->reject_map[blobindex].setrej_edge_char();
// Close to edge
}
}
}
}
/**********************************************************************
* one_ell_conflict()
*
* Identify words where there is a potential I/l/1 error.
* - A bundle of contextual heuristics!
**********************************************************************/
BOOL8 Tesseract::one_ell_conflict(WERD_RES *word_res, BOOL8 update_map) {
const char *word;
const char *lengths;
inT16 word_len; //its length
inT16 first_alphanum_index_;
inT16 first_alphanum_offset_;
inT16 i;
inT16 offset;
BOOL8 non_conflict_set_char; //non conf set a/n?
BOOL8 conflict = FALSE;
BOOL8 allow_1s;
ACCEPTABLE_WERD_TYPE word_type;
BOOL8 dict_perm_type;
BOOL8 dict_word_ok;
int dict_word_type;
word = word_res->best_choice->unichar_string().string ();
lengths = word_res->best_choice->unichar_lengths().string();
word_len = strlen (lengths);
/*
If there are no occurrences of the conflict set characters then the word
is OK.
*/
if (strpbrk (word, conflict_set_I_l_1.string ()) == NULL)
return FALSE;
/*
There is a conflict if there are NO other (confirmed) alphanumerics apart
from those in the conflict set.
*/
for (i = 0, offset = 0, non_conflict_set_char = FALSE;
(i < word_len) && !non_conflict_set_char; offset += lengths[i++])
non_conflict_set_char =
(word_res->uch_set->get_isalpha(word + offset, lengths[i]) ||
word_res->uch_set->get_isdigit(word + offset, lengths[i])) &&
!STRING (conflict_set_I_l_1).contains (word[offset]);
if (!non_conflict_set_char) {
if (update_map)
reject_I_1_L(word_res);
return TRUE;
}
/*
If the word is accepted by a dawg permuter, and the first alpha character
is "I" or "l", check to see if the alternative is also a dawg word. If it
is, then there is a potential error otherwise the word is ok.
*/
dict_perm_type = (word_res->best_choice->permuter () == SYSTEM_DAWG_PERM) ||
(word_res->best_choice->permuter () == USER_DAWG_PERM) ||
(rej_trust_doc_dawg &&
(word_res->best_choice->permuter () == DOC_DAWG_PERM)) ||
(word_res->best_choice->permuter () == FREQ_DAWG_PERM);
dict_word_type = dict_word(*(word_res->best_choice));
dict_word_ok = (dict_word_type > 0) &&
(rej_trust_doc_dawg || (dict_word_type != DOC_DAWG_PERM));
if ((rej_1Il_use_dict_word && dict_word_ok) ||
(rej_1Il_trust_permuter_type && dict_perm_type) ||
(dict_perm_type && dict_word_ok)) {
first_alphanum_index_ = first_alphanum_index (word, lengths);
first_alphanum_offset_ = first_alphanum_offset (word, lengths);
if (lengths[first_alphanum_index_] == 1 &&
word[first_alphanum_offset_] == 'I') {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'l';
if (safe_dict_word(word_res) > 0) {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'I';
if (update_map)
word_res->reject_map[first_alphanum_index_].
setrej_1Il_conflict();
return TRUE;
}
else {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'I';
return FALSE;
}
}
if (lengths[first_alphanum_index_] == 1 &&
word[first_alphanum_offset_] == 'l') {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'I';
if (safe_dict_word(word_res) > 0) {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'l';
if (update_map)
word_res->reject_map[first_alphanum_index_].
setrej_1Il_conflict();
return TRUE;
}
else {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'l';
return FALSE;
}
}
return FALSE;
}
/*
NEW 1Il code. The old code relied on permuter types too much. In fact,
tess will use TOP_CHOICE permute for good things like "palette".
In this code the string is examined independently to see if it looks like
a well formed word.
*/
/*
REGARDLESS OF PERMUTER, see if flipping a leading I/l generates a
dictionary word.
*/
first_alphanum_index_ = first_alphanum_index (word, lengths);
first_alphanum_offset_ = first_alphanum_offset (word, lengths);
if (lengths[first_alphanum_index_] == 1 &&
word[first_alphanum_offset_] == 'l') {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'I';
if (safe_dict_word(word_res) > 0)
return FALSE;
else
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'l';
}
else if (lengths[first_alphanum_index_] == 1 &&
word[first_alphanum_offset_] == 'I') {
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'l';
if (safe_dict_word(word_res) > 0)
return FALSE;
else
word_res->best_choice->unichar_string()[first_alphanum_offset_] = 'I';
}
/*
For strings containing digits:
If there are no alphas OR the numeric permuter liked the word,
reject any non 1 conflict chs
Else reject all conflict chs
*/
if (word_contains_non_1_digit (word, lengths)) {
allow_1s = (alpha_count (word, lengths) == 0) ||
(word_res->best_choice->permuter () == NUMBER_PERM);
inT16 offset;
conflict = FALSE;
for (i = 0, offset = 0; word[offset] != '\0';
offset += word_res->best_choice->unichar_lengths()[i++]) {
if ((!allow_1s || (word[offset] != '1')) &&
STRING (conflict_set_I_l_1).contains (word[offset])) {
if (update_map)
word_res->reject_map[i].setrej_1Il_conflict ();
conflict = TRUE;
}
}
return conflict;
}
/*
For anything else. See if it conforms to an acceptable word type. If so,
treat accordingly.
*/
word_type = acceptable_word_string(*word_res->uch_set, word, lengths);
if ((word_type == AC_LOWER_CASE) || (word_type == AC_INITIAL_CAP)) {
first_alphanum_index_ = first_alphanum_index (word, lengths);
first_alphanum_offset_ = first_alphanum_offset (word, lengths);
if (STRING (conflict_set_I_l_1).contains (word[first_alphanum_offset_])) {
if (update_map)
word_res->reject_map[first_alphanum_index_].
setrej_1Il_conflict ();
return TRUE;
}
else
return FALSE;
}
else if (word_type == AC_UPPER_CASE) {
return FALSE;
}
else {
if (update_map)
reject_I_1_L(word_res);
return TRUE;
}
}
inT16 Tesseract::first_alphanum_index(const char *word,
const char *word_lengths) {
inT16 i;
inT16 offset;
for (i = 0, offset = 0; word[offset] != '\0'; offset += word_lengths[i++]) {
if (unicharset.get_isalpha(word + offset, word_lengths[i]) ||
unicharset.get_isdigit(word + offset, word_lengths[i]))
return i;
}
return -1;
}
inT16 Tesseract::first_alphanum_offset(const char *word,
const char *word_lengths) {
inT16 i;
inT16 offset;
for (i = 0, offset = 0; word[offset] != '\0'; offset += word_lengths[i++]) {
if (unicharset.get_isalpha(word + offset, word_lengths[i]) ||
unicharset.get_isdigit(word + offset, word_lengths[i]))
return offset;
}
return -1;
}
inT16 Tesseract::alpha_count(const char *word,
const char *word_lengths) {
inT16 i;
inT16 offset;
inT16 count = 0;
for (i = 0, offset = 0; word[offset] != '\0'; offset += word_lengths[i++]) {
if (unicharset.get_isalpha (word + offset, word_lengths[i]))
count++;
}
return count;
}
BOOL8 Tesseract::word_contains_non_1_digit(const char *word,
const char *word_lengths) {
inT16 i;
inT16 offset;
for (i = 0, offset = 0; word[offset] != '\0'; offset += word_lengths[i++]) {
if (unicharset.get_isdigit (word + offset, word_lengths[i]) &&
(word_lengths[i] != 1 || word[offset] != '1'))
return TRUE;
}
return FALSE;
}
/*************************************************************************
* dont_allow_1Il()
* Dont unreject LONE accepted 1Il conflict set chars
*************************************************************************/
void Tesseract::dont_allow_1Il(WERD_RES *word) {
int i = 0;
int offset;
int word_len = word->reject_map.length();
const char *s = word->best_choice->unichar_string().string();
const char *lengths = word->best_choice->unichar_lengths().string();
BOOL8 accepted_1Il = FALSE;
for (i = 0, offset = 0; i < word_len;
offset += word->best_choice->unichar_lengths()[i++]) {
if (word->reject_map[i].accepted()) {
if (STRING(conflict_set_I_l_1).contains(s[offset])) {
accepted_1Il = TRUE;
} else {
if (word->uch_set->get_isalpha(s + offset, lengths[i]) ||
word->uch_set->get_isdigit(s + offset, lengths[i]))
return; // >=1 non 1Il ch accepted
}
}
}
if (!accepted_1Il)
return; //Nothing to worry about
for (i = 0, offset = 0; i < word_len;
offset += word->best_choice->unichar_lengths()[i++]) {
if (STRING(conflict_set_I_l_1).contains(s[offset]) &&
word->reject_map[i].accepted())
word->reject_map[i].setrej_postNN_1Il();
}
}
inT16 Tesseract::count_alphanums(WERD_RES *word_res) {
int count = 0;
const WERD_CHOICE *best_choice = word_res->best_choice;
for (int i = 0; i < word_res->reject_map.length(); ++i) {
if ((word_res->reject_map[i].accepted()) &&
(word_res->uch_set->get_isalpha(best_choice->unichar_id(i)) ||
word_res->uch_set->get_isdigit(best_choice->unichar_id(i)))) {
count++;
}
}
return count;
}
// reject all if most rejected.
void Tesseract::reject_mostly_rejects(WERD_RES *word) {
/* Reject the whole of the word if the fraction of rejects exceeds a limit */
if ((float) word->reject_map.reject_count() / word->reject_map.length() >=
rej_whole_of_mostly_reject_word_fract)
word->reject_map.rej_word_mostly_rej();
}
BOOL8 Tesseract::repeated_nonalphanum_wd(WERD_RES *word, ROW *row) {
inT16 char_quality;
inT16 accepted_char_quality;
if (word->best_choice->unichar_lengths().length() <= 1)
return FALSE;
if (!STRING(ok_repeated_ch_non_alphanum_wds).
contains(word->best_choice->unichar_string()[0]))
return FALSE;
UNICHAR_ID uch_id = word->best_choice->unichar_id(0);
for (int i = 1; i < word->best_choice->length(); ++i) {
if (word->best_choice->unichar_id(i) != uch_id) return FALSE;
}
word_char_quality(word, row, &char_quality, &accepted_char_quality);
if ((word->best_choice->unichar_lengths().length () == char_quality) &&
(char_quality == accepted_char_quality))
return TRUE;
else
return FALSE;
}
inT16 Tesseract::safe_dict_word(const WERD_RES *werd_res) {
const WERD_CHOICE &word = *werd_res->best_choice;
int dict_word_type = werd_res->tesseract->dict_word(word);
return dict_word_type == DOC_DAWG_PERM ? 0 : dict_word_type;
}
// Note: After running this function word_res->ratings
// might not contain the right BLOB_CHOICE corresponding to each character
// in word_res->best_choice.
void Tesseract::flip_hyphens(WERD_RES *word_res) {
WERD_CHOICE *best_choice = word_res->best_choice;
int i;
int prev_right = -9999;
int next_left;
TBOX out_box;
float aspect_ratio;
if (tessedit_lower_flip_hyphen <= 1)
return;
int num_blobs = word_res->rebuild_word->NumBlobs();
UNICHAR_ID unichar_dash = word_res->uch_set->unichar_to_id("-");
for (i = 0; i < best_choice->length() && i < num_blobs; ++i) {
TBLOB* blob = word_res->rebuild_word->blobs[i];
out_box = blob->bounding_box();
if (i + 1 == num_blobs)
next_left = 9999;
else
next_left = word_res->rebuild_word->blobs[i + 1]->bounding_box().left();
// Dont touch small or touching blobs - it is too dangerous.
if ((out_box.width() > 8 * word_res->denorm.x_scale()) &&
(out_box.left() > prev_right) && (out_box.right() < next_left)) {
aspect_ratio = out_box.width() / (float) out_box.height();
if (word_res->uch_set->eq(best_choice->unichar_id(i), ".")) {
if (aspect_ratio >= tessedit_upper_flip_hyphen &&
word_res->uch_set->contains_unichar_id(unichar_dash) &&
word_res->uch_set->get_enabled(unichar_dash)) {
/* Certain HYPHEN */
best_choice->set_unichar_id(unichar_dash, i);
if (word_res->reject_map[i].rejected())
word_res->reject_map[i].setrej_hyphen_accept();
}
if ((aspect_ratio > tessedit_lower_flip_hyphen) &&
word_res->reject_map[i].accepted())
//Suspected HYPHEN
word_res->reject_map[i].setrej_hyphen ();
}
else if (best_choice->unichar_id(i) == unichar_dash) {
if ((aspect_ratio >= tessedit_upper_flip_hyphen) &&
(word_res->reject_map[i].rejected()))
word_res->reject_map[i].setrej_hyphen_accept();
//Certain HYPHEN
if ((aspect_ratio <= tessedit_lower_flip_hyphen) &&
(word_res->reject_map[i].accepted()))
//Suspected HYPHEN
word_res->reject_map[i].setrej_hyphen();
}
}
prev_right = out_box.right();
}
}
// Note: After running this function word_res->ratings
// might not contain the right BLOB_CHOICE corresponding to each character
// in word_res->best_choice.
void Tesseract::flip_0O(WERD_RES *word_res) {
WERD_CHOICE *best_choice = word_res->best_choice;
int i;
TBOX out_box;
if (!tessedit_flip_0O)
return;
int num_blobs = word_res->rebuild_word->NumBlobs();
for (i = 0; i < best_choice->length() && i < num_blobs; ++i) {
TBLOB* blob = word_res->rebuild_word->blobs[i];
if (word_res->uch_set->get_isupper(best_choice->unichar_id(i)) ||
word_res->uch_set->get_isdigit(best_choice->unichar_id(i))) {
out_box = blob->bounding_box();
if ((out_box.top() < kBlnBaselineOffset + kBlnXHeight) ||
(out_box.bottom() > kBlnBaselineOffset + kBlnXHeight / 4))
return; //Beware words with sub/superscripts
}
}
UNICHAR_ID unichar_0 = word_res->uch_set->unichar_to_id("0");
UNICHAR_ID unichar_O = word_res->uch_set->unichar_to_id("O");
if (unichar_0 == INVALID_UNICHAR_ID ||
!word_res->uch_set->get_enabled(unichar_0) ||
unichar_O == INVALID_UNICHAR_ID ||
!word_res->uch_set->get_enabled(unichar_O)) {
return; // 0 or O are not present/enabled in unicharset
}
for (i = 1; i < best_choice->length(); ++i) {
if (best_choice->unichar_id(i) == unichar_0 ||
best_choice->unichar_id(i) == unichar_O) {
/* A0A */
if ((i+1) < best_choice->length() &&
non_O_upper(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
non_O_upper(*word_res->uch_set, best_choice->unichar_id(i+1))) {
best_choice->set_unichar_id(unichar_O, i);
}
/* A00A */
if (non_O_upper(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(i+1) < best_choice->length() &&
(best_choice->unichar_id(i+1) == unichar_0 ||
best_choice->unichar_id(i+1) == unichar_O) &&
(i+2) < best_choice->length() &&
non_O_upper(*word_res->uch_set, best_choice->unichar_id(i+2))) {
best_choice->set_unichar_id(unichar_O, i);
i++;
}
/* AA0<non digit or end of word> */
if ((i > 1) &&
non_O_upper(*word_res->uch_set, best_choice->unichar_id(i-2)) &&
non_O_upper(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(((i+1) < best_choice->length() &&
!word_res->uch_set->get_isdigit(best_choice->unichar_id(i+1)) &&
!word_res->uch_set->eq(best_choice->unichar_id(i+1), "l") &&
!word_res->uch_set->eq(best_choice->unichar_id(i+1), "I")) ||
(i == best_choice->length() - 1))) {
best_choice->set_unichar_id(unichar_O, i);
}
/* 9O9 */
if (non_0_digit(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(i+1) < best_choice->length() &&
non_0_digit(*word_res->uch_set, best_choice->unichar_id(i+1))) {
best_choice->set_unichar_id(unichar_0, i);
}
/* 9OOO */
if (non_0_digit(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(i+2) < best_choice->length() &&
(best_choice->unichar_id(i+1) == unichar_0 ||
best_choice->unichar_id(i+1) == unichar_O) &&
(best_choice->unichar_id(i+2) == unichar_0 ||
best_choice->unichar_id(i+2) == unichar_O)) {
best_choice->set_unichar_id(unichar_0, i);
best_choice->set_unichar_id(unichar_0, i+1);
best_choice->set_unichar_id(unichar_0, i+2);
i += 2;
}
/* 9OO<non upper> */
if (non_0_digit(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(i+2) < best_choice->length() &&
(best_choice->unichar_id(i+1) == unichar_0 ||
best_choice->unichar_id(i+1) == unichar_O) &&
!word_res->uch_set->get_isupper(best_choice->unichar_id(i+2))) {
best_choice->set_unichar_id(unichar_0, i);
best_choice->set_unichar_id(unichar_0, i+1);
i++;
}
/* 9O<non upper> */
if (non_0_digit(*word_res->uch_set, best_choice->unichar_id(i-1)) &&
(i+1) < best_choice->length() &&
!word_res->uch_set->get_isupper(best_choice->unichar_id(i+1))) {
best_choice->set_unichar_id(unichar_0, i);
}
/* 9[.,]OOO.. */
if ((i > 1) &&
(word_res->uch_set->eq(best_choice->unichar_id(i-1), ".") ||
word_res->uch_set->eq(best_choice->unichar_id(i-1), ",")) &&
(word_res->uch_set->get_isdigit(best_choice->unichar_id(i-2)) ||
best_choice->unichar_id(i-2) == unichar_O)) {
if (best_choice->unichar_id(i-2) == unichar_O) {
best_choice->set_unichar_id(unichar_0, i-2);
}
while (i < best_choice->length() &&
(best_choice->unichar_id(i) == unichar_O ||
best_choice->unichar_id(i) == unichar_0)) {
best_choice->set_unichar_id(unichar_0, i);
i++;
}
i--;
}
}
}
}
BOOL8 Tesseract::non_O_upper(const UNICHARSET& ch_set, UNICHAR_ID unichar_id) {
return ch_set.get_isupper(unichar_id) && !ch_set.eq(unichar_id, "O");
}
BOOL8 Tesseract::non_0_digit(const UNICHARSET& ch_set, UNICHAR_ID unichar_id) {
return ch_set.get_isdigit(unichar_id) && !ch_set.eq(unichar_id, "0");
}
} // namespace tesseract
| C++ |
///////////////////////////////////////////////////////////////////////
// File: equationdetect.h
// Description: The equation detection class that inherits equationdetectbase.
// Author: Zongyi (Joe) Liu (joeliu@google.com)
// Created: Fri Aug 31 11:13:01 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_EQUATIONDETECT_H__
#define TESSERACT_CCMAIN_EQUATIONDETECT_H__
#include "blobbox.h"
#include "equationdetectbase.h"
#include "genericvector.h"
#include "unichar.h"
class BLOBNBOX;
class BLOB_CHOICE;
class BLOB_CHOICE_LIST;
class TO_BLOCK_LIST;
class TBOX;
class UNICHARSET;
namespace tesseract {
class Tesseract;
class ColPartition;
class ColPartitionGrid;
class ColPartitionSet;
class EquationDetect : public EquationDetectBase {
public:
EquationDetect(const char* equ_datapath,
const char* equ_language);
~EquationDetect();
enum IndentType {
NO_INDENT,
LEFT_INDENT,
RIGHT_INDENT,
BOTH_INDENT,
INDENT_TYPE_COUNT
};
// Reset the lang_tesseract_ pointer. This function should be called before we
// do any detector work.
void SetLangTesseract(Tesseract* lang_tesseract);
// Iterate over the blobs inside to_block, and set the blobs that we want to
// process to BSTT_NONE. (By default, they should be BSTT_SKIP). The function
// returns 0 upon success.
int LabelSpecialText(TO_BLOCK* to_block);
// Find possible equation partitions from part_grid. Should be called
// after the special_text_type of blobs are set.
// It returns 0 upon success.
int FindEquationParts(ColPartitionGrid* part_grid,
ColPartitionSet** best_columns);
// Reset the resolution of the processing image. TEST only function.
void SetResolution(const int resolution);
protected:
// Identify the special text type for one blob, and update its field. When
// height_th is set (> 0), we will label the blob as BSTT_NONE if its height
// is less than height_th.
void IdentifySpecialText(BLOBNBOX *blob, const int height_th);
// Estimate the type for one unichar.
BlobSpecialTextType EstimateTypeForUnichar(
const UNICHARSET& unicharset, const UNICHAR_ID id) const;
// Compute special text type for each blobs in part_grid_.
void IdentifySpecialText();
// Identify blobs that we want to skip during special blob type
// classification.
void IdentifyBlobsToSkip(ColPartition* part);
// The ColPartitions in part_grid_ maybe over-segmented, particularly in the
// block equation regions. So we like to identify these partitions and merge
// them before we do the searching.
void MergePartsByLocation();
// Staring from the seed center, we do radius search. And for partitions that
// have large overlaps with seed, we remove them from part_grid_ and add into
// parts_overlap. Note: this function may update the part_grid_, so if the
// caller is also running ColPartitionGridSearch, use the RepositionIterator
// to continue.
void SearchByOverlap(ColPartition* seed,
GenericVector<ColPartition*>* parts_overlap);
// Insert part back into part_grid_, after it absorbs some other parts.
void InsertPartAfterAbsorb(ColPartition* part);
// Identify the colparitions in part_grid_, label them as PT_EQUATION, and
// save them into cp_seeds_.
void IdentifySeedParts();
// Check the blobs count for a seed region candidate.
bool CheckSeedBlobsCount(ColPartition* part);
// Compute the foreground pixel density for a tbox area.
float ComputeForegroundDensity(const TBOX& tbox);
// Check if part from seed2 label: with low math density and left indented. We
// are using two checks:
// 1. If its left is aligned with any coordinates in indented_texts_left,
// which we assume have been sorted.
// 2. If its foreground density is over foreground_density_th.
bool CheckForSeed2(
const GenericVector<int>& indented_texts_left,
const float foreground_density_th,
ColPartition* part);
// Count the number of values in sorted_vec that is close to val, used to
// check if a partition is aligned with text partitions.
int CountAlignment(
const GenericVector<int>& sorted_vec, const int val) const;
// Check for a seed candidate using the foreground pixel density. And we
// return true if the density is below a certain threshold, because characters
// in equation regions usually are apart with more white spaces.
bool CheckSeedFgDensity(const float density_th, ColPartition* part);
// A light version of SplitCPHor: instead of really doing the part split, we
// simply compute the union bounding box of each splitted part.
void SplitCPHorLite(ColPartition* part, GenericVector<TBOX>* splitted_boxes);
// Split the part (horizontally), and save the splitted result into
// parts_splitted. Note that it is caller's responsibility to release the
// memory owns by parts_splitted. On the other hand, the part is unchanged
// during this process and still owns the blobs, so do NOT call DeleteBoxes
// when freeing the colpartitions in parts_splitted.
void SplitCPHor(ColPartition* part,
GenericVector<ColPartition*>* parts_splitted);
// Check the density for a seed candidate (part) using its math density and
// italic density, returns true if the check passed.
bool CheckSeedDensity(const float math_density_high,
const float math_density_low,
const ColPartition* part) const;
// Check if part is indented.
IndentType IsIndented(ColPartition* part);
// Identify inline partitions from cp_seeds_, and re-label them.
void IdentifyInlineParts();
// Comute the super bounding box for all colpartitions inside part_grid_.
void ComputeCPsSuperBBox();
// Identify inline partitions from cp_seeds_ using the horizontal search.
void IdentifyInlinePartsHorizontal();
// Estimate the line spacing between two text partitions. Returns -1 if not
// enough data.
int EstimateTextPartLineSpacing();
// Identify inline partitions from cp_seeds_ using vertical search.
void IdentifyInlinePartsVertical(const bool top_to_bottom,
const int textPartsLineSpacing);
// Check if part is an inline equation zone. This should be called after we
// identified the seed regions.
bool IsInline(const bool search_bottom,
const int textPartsLineSpacing,
ColPartition* part);
// For a given seed partition, we search the part_grid_ and see if there is
// any partition can be merged with it. It returns true if the seed has been
// expanded.
bool ExpandSeed(ColPartition* seed);
// Starting from the seed position, we search the part_grid_
// horizontally/vertically, find all parititions that can be
// merged with seed, remove them from part_grid_, and put them into
// parts_to_merge.
void ExpandSeedHorizontal(const bool search_left,
ColPartition* seed,
GenericVector<ColPartition*>* parts_to_merge);
void ExpandSeedVertical(const bool search_bottom,
ColPartition* seed,
GenericVector<ColPartition*>* parts_to_merge);
// Check if a part_box is the small neighbor of seed_box.
bool IsNearSmallNeighbor(const TBOX& seed_box,
const TBOX& part_box) const;
// Perform the density check for part, which we assume is nearing a seed
// partition. It returns true if the check passed.
bool CheckSeedNeighborDensity(const ColPartition* part) const;
// After identify the math blocks, we do one more scanning on all text
// partitions, and check if any of them is the satellite of:
// math blocks: here a p is the satellite of q if:
// 1. q is the nearest vertical neighbor of p, and
// 2. y_gap(p, q) is less than a threshold, and
// 3. x_overlap(p, q) is over a threshold.
// Note that p can be the satellites of two blocks: its top neighbor and
// bottom neighbor.
void ProcessMathBlockSatelliteParts();
// Check if part is the satellite of one/two math blocks. If it is, we return
// true, and save the blocks into math_blocks.
bool IsMathBlockSatellite(
ColPartition* part, GenericVector<ColPartition*>* math_blocks);
// Search the nearest neighbor of part in one vertical direction as defined in
// search_bottom. It returns the neighbor found that major x overlap with it,
// or NULL when not found.
ColPartition* SearchNNVertical(const bool search_bottom,
const ColPartition* part);
// Check if the neighbor with vertical distance of y_gap is a near and math
// block partition.
bool IsNearMathNeighbor(const int y_gap, const ColPartition *neighbor) const;
// Generate the tiff file name for output/debug file.
void GetOutputTiffName(const char* name, STRING* image_name) const;
// Debugger function that renders ColPartitions on the input image, where:
// parts labeled as PT_EQUATION will be painted in red, PT_INLINE_EQUATION
// will be painted in green, and other parts will be painted in blue.
void PaintColParts(const STRING& outfile) const;
// Debugger function that renders the blobs in part_grid_ over the input
// image.
void PaintSpecialTexts(const STRING& outfile) const;
// Debugger function that print the math blobs density values for a
// ColPartition object.
void PrintSpecialBlobsDensity(const ColPartition* part) const;
// The tesseract engine intialized from equation training data.
Tesseract* equ_tesseract_;
// The tesseract engine used for OCR. This pointer is passed in by the caller,
// so do NOT destroy it in this class.
Tesseract* lang_tesseract_;
// The ColPartitionGrid that we are processing. This pointer is passed in from
// the caller, so do NOT destroy it in the class.
ColPartitionGrid* part_grid_;
// A simple array of pointers to the best assigned column division at
// each grid y coordinate. This pointer is passed in from the caller, so do
// NOT destroy it in the class.
ColPartitionSet** best_columns_;
// The super bounding box of all cps in the part_grid_.
TBOX* cps_super_bbox_;
// The seed ColPartition for equation region.
GenericVector<ColPartition*> cp_seeds_;
// The resolution (dpi) of the processing image.
int resolution_;
// The number of pages we have processed.
int page_count_;
};
} // namespace tesseract
#endif // TESSERACT_CCMAIN_EQUATIONDETECT_H_
| C++ |
// Copyright 2011 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: cubeclassifier.h
// Description: Cube implementation of a ShapeClassifier.
// Author: Ray Smith
// Created: Wed Nov 23 10:36:32 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef THIRD_PARTY_TESSERACT_CCMAIN_CUBECLASSIFIER_H_
#define THIRD_PARTY_TESSERACT_CCMAIN_CUBECLASSIFIER_H_
#include "shapeclassifier.h"
namespace tesseract {
class Classify;
class CubeRecoContext;
class ShapeTable;
class TessClassifier;
class Tesseract;
class TrainingSample;
struct UnicharRating;
// Cube implementation of a ShapeClassifier.
class CubeClassifier : public ShapeClassifier {
public:
explicit CubeClassifier(Tesseract* tesseract);
virtual ~CubeClassifier();
// Classifies the given [training] sample, writing to results.
// See ShapeClassifier for a full description.
virtual int UnicharClassifySample(const TrainingSample& sample, Pix* page_pix,
int debug, UNICHAR_ID keep_this,
GenericVector<UnicharRating>* results);
// Provides access to the ShapeTable that this classifier works with.
virtual const ShapeTable* GetShapeTable() const;
private:
// Cube objects.
CubeRecoContext* cube_cntxt_;
const ShapeTable& shape_table_;
};
// Combination of Tesseract class pruner with scoring by cube.
class CubeTessClassifier : public ShapeClassifier {
public:
explicit CubeTessClassifier(Tesseract* tesseract);
virtual ~CubeTessClassifier();
// Classifies the given [training] sample, writing to results.
// See ShapeClassifier for a full description.
virtual int UnicharClassifySample(const TrainingSample& sample, Pix* page_pix,
int debug, UNICHAR_ID keep_this,
GenericVector<UnicharRating>* results);
// Provides access to the ShapeTable that this classifier works with.
virtual const ShapeTable* GetShapeTable() const;
private:
// Cube objects.
CubeRecoContext* cube_cntxt_;
const ShapeTable& shape_table_;
TessClassifier* pruner_;
};
} // namespace tesseract
#endif /* THIRD_PARTY_TESSERACT_CCMAIN_CUBECLASSIFIER_H_ */
| C++ |
// Copyright 2011 Google Inc. All Rights Reserved.
// Author: rays@google.com (Ray Smith)
///////////////////////////////////////////////////////////////////////
// File: cubeclassifier.cpp
// Description: Cube implementation of a ShapeClassifier.
// Author: Ray Smith
// Created: Wed Nov 23 10:39:45 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "cubeclassifier.h"
#include "char_altlist.h"
#include "char_set.h"
#include "cube_object.h"
#include "cube_reco_context.h"
#include "tessclassifier.h"
#include "tesseractclass.h"
#include "trainingsample.h"
#include "unicharset.h"
namespace tesseract {
CubeClassifier::CubeClassifier(tesseract::Tesseract* tesseract)
: cube_cntxt_(tesseract->GetCubeRecoContext()),
shape_table_(*tesseract->shape_table()) {
}
CubeClassifier::~CubeClassifier() {
}
// Classifies the given [training] sample, writing to results.
// See ShapeClassifier for a full description.
int CubeClassifier::UnicharClassifySample(
const TrainingSample& sample, Pix* page_pix, int debug,
UNICHAR_ID keep_this, GenericVector<UnicharRating>* results) {
results->clear();
if (page_pix == NULL) return 0;
ASSERT_HOST(cube_cntxt_ != NULL);
const TBOX& char_box = sample.bounding_box();
CubeObject* cube_obj = new tesseract::CubeObject(
cube_cntxt_, page_pix, char_box.left(),
pixGetHeight(page_pix) - char_box.top(),
char_box.width(), char_box.height());
CharAltList* alt_list = cube_obj->RecognizeChar();
if (alt_list != NULL) {
alt_list->Sort();
CharSet* char_set = cube_cntxt_->CharacterSet();
for (int i = 0; i < alt_list->AltCount(); ++i) {
// Convert cube representation to a shape_id.
int alt_id = alt_list->Alt(i);
int unichar_id = char_set->UnicharID(char_set->ClassString(alt_id));
if (unichar_id >= 0)
results->push_back(UnicharRating(unichar_id, alt_list->AltProb(i)));
}
delete alt_list;
}
delete cube_obj;
return results->size();
}
// Provides access to the ShapeTable that this classifier works with.
const ShapeTable* CubeClassifier::GetShapeTable() const {
return &shape_table_;
}
CubeTessClassifier::CubeTessClassifier(tesseract::Tesseract* tesseract)
: cube_cntxt_(tesseract->GetCubeRecoContext()),
shape_table_(*tesseract->shape_table()),
pruner_(new TessClassifier(true, tesseract)) {
}
CubeTessClassifier::~CubeTessClassifier() {
delete pruner_;
}
// Classifies the given [training] sample, writing to results.
// See ShapeClassifier for a full description.
int CubeTessClassifier::UnicharClassifySample(
const TrainingSample& sample, Pix* page_pix, int debug,
UNICHAR_ID keep_this, GenericVector<UnicharRating>* results) {
int num_results = pruner_->UnicharClassifySample(sample, page_pix, debug,
keep_this, results);
if (page_pix == NULL) return num_results;
ASSERT_HOST(cube_cntxt_ != NULL);
const TBOX& char_box = sample.bounding_box();
CubeObject* cube_obj = new tesseract::CubeObject(
cube_cntxt_, page_pix, char_box.left(),
pixGetHeight(page_pix) - char_box.top(),
char_box.width(), char_box.height());
CharAltList* alt_list = cube_obj->RecognizeChar();
CharSet* char_set = cube_cntxt_->CharacterSet();
if (alt_list != NULL) {
for (int r = 0; r < num_results; ++r) {
// Get the best cube probability of the unichar in the result.
double best_prob = 0.0;
for (int i = 0; i < alt_list->AltCount(); ++i) {
int alt_id = alt_list->Alt(i);
int unichar_id = char_set->UnicharID(char_set->ClassString(alt_id));
if (unichar_id == (*results)[r].unichar_id &&
alt_list->AltProb(i) > best_prob) {
best_prob = alt_list->AltProb(i);
}
}
(*results)[r].rating = best_prob;
}
delete alt_list;
// Re-sort by rating.
results->sort(&UnicharRating::SortDescendingRating);
}
delete cube_obj;
return results->size();
}
// Provides access to the ShapeTable that this classifier works with.
const ShapeTable* CubeTessClassifier::GetShapeTable() const {
return &shape_table_;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: paragraphs.h
* Description: Paragraph Detection internal data structures.
* Author: David Eger
* Created: 11 March 2011
*
* (C) Copyright 2011, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifndef TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_
#define TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_
#include "paragraphs.h"
#ifdef _MSC_VER
#include <string>
#else
#include "strings.h"
#endif
// NO CODE OUTSIDE OF paragraphs.cpp AND TESTS SHOULD NEED TO ACCESS
// DATA STRUCTURES OR FUNCTIONS IN THIS FILE.
class WERD_CHOICE;
namespace tesseract {
// Return whether the given word is likely to be a list item start word.
bool AsciiLikelyListItem(const STRING &word);
// Return the first Unicode Codepoint from werd[pos].
int UnicodeFor(const UNICHARSET *u, const WERD_CHOICE *werd, int pos);
// Set right word attributes given either a unicharset and werd or a utf8
// string.
void RightWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd,
const STRING &utf8,
bool *is_list, bool *starts_idea, bool *ends_idea);
// Set left word attributes given either a unicharset and werd or a utf8 string.
void LeftWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd,
const STRING &utf8,
bool *is_list, bool *starts_idea, bool *ends_idea);
enum LineType {
LT_START = 'S', // First line of a paragraph.
LT_BODY = 'C', // Continuation line of a paragraph.
LT_UNKNOWN = 'U', // No clues.
LT_MULTIPLE = 'M', // Matches for both LT_START and LT_BODY.
};
// The first paragraph in a page of body text is often un-indented.
// This is a typographic convention which is common to indicate either that:
// (1) The paragraph is the continuation of a previous paragraph, or
// (2) The paragraph is the first paragraph in a chapter.
//
// I refer to such paragraphs as "crown"s, and the output of the paragraph
// detection algorithm attempts to give them the same paragraph model as
// the rest of the body text.
//
// Nonetheless, while building hypotheses, it is useful to mark the lines
// of crown paragraphs temporarily as crowns, either aligned left or right.
extern const ParagraphModel *kCrownLeft;
extern const ParagraphModel *kCrownRight;
inline bool StrongModel(const ParagraphModel *model) {
return model != NULL && model != kCrownLeft && model != kCrownRight;
}
struct LineHypothesis {
LineHypothesis() : ty(LT_UNKNOWN), model(NULL) {}
LineHypothesis(LineType line_type, const ParagraphModel *m)
: ty(line_type), model(m) {}
LineHypothesis(const LineHypothesis &other)
: ty(other.ty), model(other.model) {}
bool operator==(const LineHypothesis &other) const {
return ty == other.ty && model == other.model;
}
LineType ty;
const ParagraphModel *model;
};
class ParagraphTheory; // Forward Declaration
typedef GenericVectorEqEq<const ParagraphModel *> SetOfModels;
// Row Scratch Registers are data generated by the paragraph detection
// algorithm based on a RowInfo input.
class RowScratchRegisters {
public:
// We presume row will outlive us.
void Init(const RowInfo &row);
LineType GetLineType() const;
LineType GetLineType(const ParagraphModel *model) const;
// Mark this as a start line type, sans model. This is useful for the
// initial marking of probable body lines or paragraph start lines.
void SetStartLine();
// Mark this as a body line type, sans model. This is useful for the
// initial marking of probably body lines or paragraph start lines.
void SetBodyLine();
// Record that this row fits as a paragraph start line in the given model,
void AddStartLine(const ParagraphModel *model);
// Record that this row fits as a paragraph body line in the given model,
void AddBodyLine(const ParagraphModel *model);
// Clear all hypotheses about this line.
void SetUnknown() { hypotheses_.truncate(0); }
// Append all hypotheses of strong models that match this row as a start.
void StartHypotheses(SetOfModels *models) const;
// Append all hypotheses of strong models matching this row.
void StrongHypotheses(SetOfModels *models) const;
// Append all hypotheses for this row.
void NonNullHypotheses(SetOfModels *models) const;
// Discard any hypotheses whose model is not in the given list.
void DiscardNonMatchingHypotheses(const SetOfModels &models);
// If we have only one hypothesis and that is that this line is a paragraph
// start line of a certain model, return that model. Else return NULL.
const ParagraphModel *UniqueStartHypothesis() const;
// If we have only one hypothesis and that is that this line is a paragraph
// body line of a certain model, return that model. Else return NULL.
const ParagraphModel *UniqueBodyHypothesis() const;
// Return the indentation for the side opposite of the aligned side.
int OffsideIndent(tesseract::ParagraphJustification just) const {
switch (just) {
case tesseract::JUSTIFICATION_RIGHT: return lindent_;
case tesseract::JUSTIFICATION_LEFT: return rindent_;
default: return lindent_ > rindent_ ? lindent_ : rindent_;
}
}
// Return the indentation for the side the text is aligned to.
int AlignsideIndent(tesseract::ParagraphJustification just) const {
switch (just) {
case tesseract::JUSTIFICATION_RIGHT: return rindent_;
case tesseract::JUSTIFICATION_LEFT: return lindent_;
default: return lindent_ > rindent_ ? lindent_ : rindent_;
}
}
// Append header fields to a vector of row headings.
static void AppendDebugHeaderFields(GenericVector<STRING> *header);
// Append data for this row to a vector of debug strings.
void AppendDebugInfo(const ParagraphTheory &theory,
GenericVector<STRING> *dbg) const;
const RowInfo *ri_;
// These four constants form a horizontal box model for the white space
// on the edges of each line. At each point in the algorithm, the following
// shall hold:
// ri_->pix_ldistance = lmargin_ + lindent_
// ri_->pix_rdistance = rindent_ + rmargin_
int lmargin_;
int lindent_;
int rindent_;
int rmargin_;
private:
// Hypotheses of either LT_START or LT_BODY
GenericVectorEqEq<LineHypothesis> hypotheses_;
};
// A collection of convenience functions for wrapping the set of
// Paragraph Models we believe correctly model the paragraphs in the image.
class ParagraphTheory {
public:
// We presume models will outlive us, and that models will take ownership
// of any ParagraphModel *'s we add.
explicit ParagraphTheory(GenericVector<ParagraphModel *> *models)
: models_(models) {}
GenericVector<ParagraphModel *> &models() { return *models_; }
const GenericVector<ParagraphModel *> &models() const { return *models_; }
// Return an existing model if one that is Comparable() can be found.
// Else, allocate a new copy of model to save and return a pointer to it.
const ParagraphModel *AddModel(const ParagraphModel &model);
// Discard any models we've made that are not in the list of used models.
void DiscardUnusedModels(const SetOfModels &used_models);
// Return the set of all non-centered models.
void NonCenteredModels(SetOfModels *models);
// If any of the non-centered paragraph models we know about fit
// rows[start, end), return it. Else NULL.
const ParagraphModel *Fits(const GenericVector<RowScratchRegisters> *rows,
int start, int end) const;
int IndexOf(const ParagraphModel *model) const;
private:
GenericVector<ParagraphModel *> *models_;
GenericVectorEqEq<ParagraphModel *> models_we_added_;
};
bool ValidFirstLine(const GenericVector<RowScratchRegisters> *rows,
int row, const ParagraphModel *model);
bool ValidBodyLine(const GenericVector<RowScratchRegisters> *rows,
int row, const ParagraphModel *model);
bool CrownCompatible(const GenericVector<RowScratchRegisters> *rows,
int a, int b, const ParagraphModel *model);
// A class for smearing Paragraph Model hypotheses to surrounding rows.
// The idea here is that StrongEvidenceClassify first marks only exceedingly
// obvious start and body rows and constructs models of them. Thereafter,
// we may have left over unmarked lines (mostly end-of-paragraph lines) which
// were too short to have much confidence about, but which fit the models we've
// constructed perfectly and which we ought to mark. This class is used to
// "smear" our models over the text.
class ParagraphModelSmearer {
public:
ParagraphModelSmearer(GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
ParagraphTheory *theory);
// Smear forward paragraph models from existing row markings to subsequent
// text lines if they fit, and mark any thereafter still unmodeled rows
// with any model in the theory that fits them.
void Smear();
private:
// Record in open_models_ for rows [start_row, end_row) the list of models
// currently open at each row.
// A model is still open in a row if some previous row has said model as a
// start hypothesis, and all rows since (including this row) would fit as
// either a body or start line in that model.
void CalculateOpenModels(int row_start, int row_end);
SetOfModels &OpenModels(int row) {
return open_models_[row - row_start_ + 1];
}
ParagraphTheory *theory_;
GenericVector<RowScratchRegisters> *rows_;
int row_start_;
int row_end_;
// open_models_ corresponds to rows[start_row_ - 1, end_row_]
//
// open_models_: Contains models which there was an active (open) paragraph
// as of the previous line and for which the left and right
// indents admit the possibility that this text line continues
// to fit the same model.
// TODO(eger): Think about whether we can get rid of "Open" models and just
// use the current hypotheses on RowScratchRegisters.
GenericVector<SetOfModels> open_models_;
};
// Clear all hypotheses about lines [start, end) and reset the margins to the
// percentile (0..100) value of the left and right row edges for this run of
// rows.
void RecomputeMarginsAndClearHypotheses(
GenericVector<RowScratchRegisters> *rows, int start, int end,
int percentile);
// Return the median inter-word space in rows[row_start, row_end).
int InterwordSpace(const GenericVector<RowScratchRegisters> &rows,
int row_start, int row_end);
// Return whether the first word on the after line can fit in the space at
// the end of the before line (knowing which way the text is aligned and read).
bool FirstWordWouldHaveFit(const RowScratchRegisters &before,
const RowScratchRegisters &after,
tesseract::ParagraphJustification justification);
// Return whether the first word on the after line can fit in the space at
// the end of the before line (not knowing the text alignment).
bool FirstWordWouldHaveFit(const RowScratchRegisters &before,
const RowScratchRegisters &after);
// Do rows[start, end) form a single instance of the given paragraph model?
bool RowsFitModel(const GenericVector<RowScratchRegisters> *rows,
int start, int end, const ParagraphModel *model);
// Do the text and geometry of two rows support a paragraph break between them?
bool LikelyParagraphStart(const RowScratchRegisters &before,
const RowScratchRegisters &after,
tesseract::ParagraphJustification j);
// Given a set of row_owners pointing to PARAs or NULL (no paragraph known),
// normalize each row_owner to point to an actual PARA, and output the
// paragraphs in order onto paragraphs.
void CanonicalizeDetectionResults(
GenericVector<PARA *> *row_owners,
PARA_LIST *paragraphs);
} // namespace
#endif // TESSERACT_CCMAIN_PARAGRAPHS_INTERNAL_H_
| C++ |
///////////////////////////////////////////////////////////////////////
// File: mutableiterator.h
// Description: Iterator for tesseract results providing access to
// both high-level API and Tesseract internal data structures.
// Author: David Eger
// Created: Thu Feb 24 19:01:06 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_MUTABLEITERATOR_H__
#define TESSERACT_CCMAIN_MUTABLEITERATOR_H__
#include "resultiterator.h"
class BLOB_CHOICE_IT;
namespace tesseract {
class Tesseract;
// Class to iterate over tesseract results, providing access to all levels
// of the page hierarchy, without including any tesseract headers or having
// to handle any tesseract structures.
// WARNING! This class points to data held within the TessBaseAPI class, and
// therefore can only be used while the TessBaseAPI class still exists and
// has not been subjected to a call of Init, SetImage, Recognize, Clear, End
// DetectOS, or anything else that changes the internal PAGE_RES.
// See apitypes.h for the definition of PageIteratorLevel.
// See also base class PageIterator, which contains the bulk of the interface.
// ResultIterator adds text-specific methods for access to OCR output.
// MutableIterator adds access to internal data structures.
class MutableIterator : public ResultIterator {
public:
// See argument descriptions in ResultIterator()
MutableIterator(PAGE_RES* page_res, Tesseract* tesseract,
int scale, int scaled_yres,
int rect_left, int rect_top,
int rect_width, int rect_height)
: ResultIterator(
LTRResultIterator(page_res, tesseract, scale, scaled_yres, rect_left,
rect_top, rect_width, rect_height)) {}
virtual ~MutableIterator() {}
// See PageIterator and ResultIterator for most calls.
// Return access to Tesseract internals.
const PAGE_RES_IT *PageResIt() const { return it_; }
};
} // namespace tesseract.
#endif // TESSERACT_CCMAIN_MUTABLEITERATOR_H__
| C++ |
/**********************************************************************
* File: cube_reco_context.cpp
* Description: Implementation of the Cube Recognition Context Class
* Author: Ahmad Abdulkader
* Created: 2007
*
* (C) Copyright 2008, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <string>
#include <limits.h>
#include "cube_reco_context.h"
#include "classifier_factory.h"
#include "cube_tuning_params.h"
#include "dict.h"
#include "feature_bmp.h"
#include "tessdatamanager.h"
#include "tesseractclass.h"
#include "tess_lang_model.h"
namespace tesseract {
// Instantiate a CubeRecoContext object using a Tesseract object.
// CubeRecoContext will not take ownership of tess_obj, but will
// record the pointer to it and will make use of various Tesseract
// components (language model, flags, etc). Thus the caller should
// keep tess_obj alive so long as the instantiated CubeRecoContext is used.
CubeRecoContext::CubeRecoContext(Tesseract *tess_obj) {
tess_obj_ = tess_obj;
lang_ = "";
loaded_ = false;
lang_mod_ = NULL;
params_ = NULL;
char_classifier_ = NULL;
char_set_ = NULL;
word_size_model_ = NULL;
char_bigrams_ = NULL;
word_unigrams_ = NULL;
noisy_input_ = false;
size_normalization_ = false;
}
CubeRecoContext::~CubeRecoContext() {
if (char_classifier_ != NULL) {
delete char_classifier_;
char_classifier_ = NULL;
}
if (word_size_model_ != NULL) {
delete word_size_model_;
word_size_model_ = NULL;
}
if (char_set_ != NULL) {
delete char_set_;
char_set_ = NULL;
}
if (char_bigrams_ != NULL) {
delete char_bigrams_;
char_bigrams_ = NULL;
}
if (word_unigrams_ != NULL) {
delete word_unigrams_;
word_unigrams_ = NULL;
}
if (lang_mod_ != NULL) {
delete lang_mod_;
lang_mod_ = NULL;
}
if (params_ != NULL) {
delete params_;
params_ = NULL;
}
}
// Returns the path of the data files by looking up the TESSDATA_PREFIX
// environment variable and appending a "tessdata" directory to it
bool CubeRecoContext::GetDataFilePath(string *path) const {
*path = tess_obj_->datadir.string();
return true;
}
// The object initialization function that loads all the necessary
// components of a RecoContext. TessdataManager is used to load the
// data from [lang].traineddata file. If TESSDATA_CUBE_UNICHARSET
// component is present, Cube will be instantiated with the unicharset
// specified in this component and the corresponding dictionary
// (TESSDATA_CUBE_SYSTEM_DAWG), and will map Cube's unicharset to
// Tesseract's. Otherwise, TessdataManager will assume that Cube will
// be using Tesseract's unicharset and dawgs, and will load the
// unicharset from the TESSDATA_UNICHARSET component and will load the
// dawgs from TESSDATA_*_DAWG components.
bool CubeRecoContext::Load(TessdataManager *tessdata_manager,
UNICHARSET *tess_unicharset) {
ASSERT_HOST(tess_obj_ != NULL);
tess_unicharset_ = tess_unicharset;
string data_file_path;
// Get the data file path.
if (GetDataFilePath(&data_file_path) == false) {
fprintf(stderr, "Unable to get data file path\n");
return false;
}
// Get the language from the Tesseract object.
lang_ = tess_obj_->lang.string();
// Create the char set.
if ((char_set_ =
CharSet::Create(tessdata_manager, tess_unicharset)) == NULL) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Load): unable to load "
"CharSet\n");
return false;
}
// Create the language model.
string lm_file_name = data_file_path + lang_ + ".cube.lm";
string lm_params;
if (!CubeUtils::ReadFileToString(lm_file_name, &lm_params)) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Load): unable to read cube "
"language model params from %s\n", lm_file_name.c_str());
return false;
}
lang_mod_ = new TessLangModel(lm_params, data_file_path,
tess_obj_->getDict().load_system_dawg,
tessdata_manager, this);
if (lang_mod_ == NULL) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Load): unable to create "
"TessLangModel\n");
return false;
}
// Create the optional char bigrams object.
char_bigrams_ = CharBigrams::Create(data_file_path, lang_);
// Create the optional word unigrams object.
word_unigrams_ = WordUnigrams::Create(data_file_path, lang_);
// Create the optional size model.
word_size_model_ = WordSizeModel::Create(data_file_path, lang_,
char_set_, Contextual());
// Load tuning params.
params_ = CubeTuningParams::Create(data_file_path, lang_);
if (params_ == NULL) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Load): unable to read "
"CubeTuningParams from %s\n", data_file_path.c_str());
return false;
}
// Create the char classifier.
char_classifier_ = CharClassifierFactory::Create(data_file_path, lang_,
lang_mod_, char_set_,
params_);
if (char_classifier_ == NULL) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Load): unable to load "
"CharClassifierFactory object from %s\n", data_file_path.c_str());
return false;
}
loaded_ = true;
return true;
}
// Creates a CubeRecoContext object using a tesseract object
CubeRecoContext * CubeRecoContext::Create(Tesseract *tess_obj,
TessdataManager *tessdata_manager,
UNICHARSET *tess_unicharset) {
// create the object
CubeRecoContext *cntxt = new CubeRecoContext(tess_obj);
if (cntxt == NULL) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Create): unable to create "
"CubeRecoContext object\n");
return NULL;
}
// load the necessary components
if (cntxt->Load(tessdata_manager, tess_unicharset) == false) {
fprintf(stderr, "Cube ERROR (CubeRecoContext::Create): unable to init "
"CubeRecoContext object\n");
delete cntxt;
return NULL;
}
// success
return cntxt;
}
} // tesseract}
| C++ |
/**********************************************************************
* File: applybox.cpp (Formerly applybox.c)
* Description: Re segment rows according to box file data
* Author: Phil Cheatle
* Created: Wed Nov 24 09:11:23 GMT 1993
*
* (C) Copyright 1993, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
#include <ctype.h>
#include <string.h>
#ifdef __UNIX__
#include <assert.h>
#include <errno.h>
#endif
#include "allheaders.h"
#include "boxread.h"
#include "chopper.h"
#include "pageres.h"
#include "unichar.h"
#include "unicharset.h"
#include "tesseractclass.h"
#include "genericvector.h"
// Max number of blobs to classify together in FindSegmentation.
const int kMaxGroupSize = 4;
// Max fraction of median allowed as deviation in xheight before switching
// to median.
const double kMaxXHeightDeviationFraction = 0.125;
/*************************************************************************
* The box file is assumed to contain box definitions, one per line, of the
* following format for blob-level boxes:
* <UTF8 str> <left> <bottom> <right> <top> <page id>
* and for word/line-level boxes:
* WordStr <left> <bottom> <right> <top> <page id> #<space-delimited word str>
* NOTES:
* The boxes use tesseract coordinates, i.e. 0,0 is at BOTTOM-LEFT.
*
* <page id> is 0-based, and the page number is used for multipage input (tiff).
*
* In the blob-level form, each line represents a recognizable unit, which may
* be several UTF-8 bytes, but there is a bounding box around each recognizable
* unit, and no classifier is needed to train in this mode (bootstrapping.)
*
* In the word/line-level form, the line begins with the literal "WordStr", and
* the bounding box bounds either a whole line or a whole word. The recognizable
* units in the word/line are listed after the # at the end of the line and
* are space delimited, ignoring any original spaces on the line.
* Eg.
* word -> #w o r d
* multi word line -> #m u l t i w o r d l i n e
* The recognizable units must be space-delimited in order to allow multiple
* unicodes to be used for a single recognizable unit, eg Hindi.
* In this mode, the classifier must have been pre-trained with the desired
* character set, or it will not be able to find the character segmentations.
*************************************************************************/
namespace tesseract {
static void clear_any_old_text(BLOCK_LIST *block_list) {
BLOCK_IT block_it(block_list);
for (block_it.mark_cycle_pt();
!block_it.cycled_list(); block_it.forward()) {
ROW_IT row_it(block_it.data()->row_list());
for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
WERD_IT word_it(row_it.data()->word_list());
for (word_it.mark_cycle_pt();
!word_it.cycled_list(); word_it.forward()) {
word_it.data()->set_text("");
}
}
}
}
// Applies the box file based on the image name fname, and resegments
// the words in the block_list (page), with:
// blob-mode: one blob per line in the box file, words as input.
// word/line-mode: one blob per space-delimited unit after the #, and one word
// per line in the box file. (See comment above for box file format.)
// If find_segmentation is true, (word/line mode) then the classifier is used
// to re-segment words/lines to match the space-delimited truth string for
// each box. In this case, the input box may be for a word or even a whole
// text line, and the output words will contain multiple blobs corresponding
// to the space-delimited input string.
// With find_segmentation false, no classifier is needed, but the chopper
// can still be used to correctly segment touching characters with the help
// of the input boxes.
// In the returned PAGE_RES, the WERD_RES are setup as they would be returned
// from normal classification, ie. with a word, chopped_word, rebuild_word,
// seam_array, denorm, box_word, and best_state, but NO best_choice or
// raw_choice, as they would require a UNICHARSET, which we aim to avoid.
// Instead, the correct_text member of WERD_RES is set, and this may be later
// converted to a best_choice using CorrectClassifyWords. CorrectClassifyWords
// is not required before calling ApplyBoxTraining.
PAGE_RES* Tesseract::ApplyBoxes(const STRING& fname,
bool find_segmentation,
BLOCK_LIST *block_list) {
GenericVector<TBOX> boxes;
GenericVector<STRING> texts, full_texts;
if (!ReadAllBoxes(applybox_page, true, fname, &boxes, &texts, &full_texts,
NULL)) {
return NULL; // Can't do it.
}
int box_count = boxes.size();
int box_failures = 0;
// Add an empty everything to the end.
boxes.push_back(TBOX());
texts.push_back(STRING());
full_texts.push_back(STRING());
// In word mode, we use the boxes to make a word for each box, but
// in blob mode we use the existing words and maximally chop them first.
PAGE_RES* page_res = find_segmentation ?
NULL : SetupApplyBoxes(boxes, block_list);
clear_any_old_text(block_list);
for (int i = 0; i < boxes.size() - 1; i++) {
bool foundit = false;
if (page_res != NULL) {
if (i == 0) {
foundit = ResegmentCharBox(page_res, NULL, boxes[i], boxes[i + 1],
full_texts[i].string());
} else {
foundit = ResegmentCharBox(page_res, &boxes[i-1], boxes[i],
boxes[i + 1], full_texts[i].string());
}
} else {
foundit = ResegmentWordBox(block_list, boxes[i], boxes[i + 1],
texts[i].string());
}
if (!foundit) {
box_failures++;
ReportFailedBox(i, boxes[i], texts[i].string(),
"FAILURE! Couldn't find a matching blob");
}
}
if (page_res == NULL) {
// In word/line mode, we now maximally chop all the words and resegment
// them with the classifier.
page_res = SetupApplyBoxes(boxes, block_list);
ReSegmentByClassification(page_res);
}
if (applybox_debug > 0) {
tprintf("APPLY_BOXES:\n");
tprintf(" Boxes read from boxfile: %6d\n", box_count);
if (box_failures > 0)
tprintf(" Boxes failed resegmentation: %6d\n", box_failures);
}
TidyUp(page_res);
return page_res;
}
// Helper computes median xheight in the image.
static double MedianXHeight(BLOCK_LIST *block_list) {
BLOCK_IT block_it(block_list);
STATS xheights(0, block_it.data()->bounding_box().height());
for (block_it.mark_cycle_pt();
!block_it.cycled_list(); block_it.forward()) {
ROW_IT row_it(block_it.data()->row_list());
for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
xheights.add(IntCastRounded(row_it.data()->x_height()), 1);
}
}
return xheights.median();
}
// Any row xheight that is significantly different from the median is set
// to the median.
void Tesseract::PreenXHeights(BLOCK_LIST *block_list) {
double median_xheight = MedianXHeight(block_list);
double max_deviation = kMaxXHeightDeviationFraction * median_xheight;
// Strip all fuzzy space markers to simplify the PAGE_RES.
BLOCK_IT b_it(block_list);
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOCK* block = b_it.data();
ROW_IT r_it(block->row_list());
for (r_it.mark_cycle_pt(); !r_it.cycled_list(); r_it.forward ()) {
ROW* row = r_it.data();
float diff = fabs(row->x_height() - median_xheight);
if (diff > max_deviation) {
if (applybox_debug) {
tprintf("row xheight=%g, but median xheight = %g\n",
row->x_height(), median_xheight);
}
row->set_x_height(static_cast<float>(median_xheight));
}
}
}
}
// Builds a PAGE_RES from the block_list in the way required for ApplyBoxes:
// All fuzzy spaces are removed, and all the words are maximally chopped.
PAGE_RES* Tesseract::SetupApplyBoxes(const GenericVector<TBOX>& boxes,
BLOCK_LIST *block_list) {
PreenXHeights(block_list);
// Strip all fuzzy space markers to simplify the PAGE_RES.
BLOCK_IT b_it(block_list);
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOCK* block = b_it.data();
ROW_IT r_it(block->row_list());
for (r_it.mark_cycle_pt(); !r_it.cycled_list(); r_it.forward ()) {
ROW* row = r_it.data();
WERD_IT w_it(row->word_list());
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD* word = w_it.data();
if (word->cblob_list()->empty()) {
delete w_it.extract();
} else {
word->set_flag(W_FUZZY_SP, false);
word->set_flag(W_FUZZY_NON, false);
}
}
}
}
PAGE_RES* page_res = new PAGE_RES(false, block_list, NULL);
PAGE_RES_IT pr_it(page_res);
WERD_RES* word_res;
while ((word_res = pr_it.word()) != NULL) {
MaximallyChopWord(boxes, pr_it.block()->block,
pr_it.row()->row, word_res);
pr_it.forward();
}
return page_res;
}
// Tests the chopper by exhaustively running chop_one_blob.
// The word_res will contain filled chopped_word, seam_array, denorm,
// box_word and best_state for the maximally chopped word.
void Tesseract::MaximallyChopWord(const GenericVector<TBOX>& boxes,
BLOCK* block, ROW* row,
WERD_RES* word_res) {
if (!word_res->SetupForRecognition(unicharset, this, BestPix(),
tessedit_ocr_engine_mode, NULL,
classify_bln_numeric_mode,
textord_use_cjk_fp_model,
poly_allow_detailed_fx,
row, block)) {
word_res->CloneChoppedToRebuild();
return;
}
if (chop_debug) {
tprintf("Maximally chopping word at:");
word_res->word->bounding_box().print();
}
GenericVector<BLOB_CHOICE*> blob_choices;
ASSERT_HOST(!word_res->chopped_word->blobs.empty());
float rating = static_cast<float>(MAX_INT8);
for (int i = 0; i < word_res->chopped_word->NumBlobs(); ++i) {
// The rating and certainty are not quite arbitrary. Since
// select_blob_to_chop uses the worst certainty to choose, they all have
// to be different, so starting with MAX_INT8, subtract 1/8 for each blob
// in here, and then divide by e each time they are chopped, which
// should guarantee a set of unequal values for the whole tree of blobs
// produced, however much chopping is required. The chops are thus only
// limited by the ability of the chopper to find suitable chop points,
// and not by the value of the certainties.
BLOB_CHOICE* choice =
new BLOB_CHOICE(0, rating, -rating, -1, -1, 0, 0, 0, 0, BCC_FAKE);
blob_choices.push_back(choice);
rating -= 0.125f;
}
const double e = exp(1.0); // The base of natural logs.
int blob_number;
int right_chop_index = 0;
if (!assume_fixed_pitch_char_segment) {
// We only chop if the language is not fixed pitch like CJK.
SEAM* seam = NULL;
while ((seam = chop_one_blob(boxes, blob_choices, word_res,
&blob_number)) != NULL) {
word_res->InsertSeam(blob_number, seam);
BLOB_CHOICE* left_choice = blob_choices[blob_number];
rating = left_choice->rating() / e;
left_choice->set_rating(rating);
left_choice->set_certainty(-rating);
// combine confidence w/ serial #
BLOB_CHOICE* right_choice = new BLOB_CHOICE(++right_chop_index,
rating - 0.125f, -rating,
-1, -1, 0, 0, 0, 0, BCC_FAKE);
blob_choices.insert(right_choice, blob_number + 1);
}
}
word_res->CloneChoppedToRebuild();
word_res->FakeClassifyWord(blob_choices.size(), &blob_choices[0]);
}
// Helper to compute the dispute resolution metric.
// Disputed blob resolution. The aim is to give the blob to the most
// appropriate boxfile box. Most of the time it is obvious, but if
// two boxfile boxes overlap significantly it is not. If a small boxfile
// box takes most of the blob, and a large boxfile box does too, then
// we want the small boxfile box to get it, but if the small box
// is much smaller than the blob, we don't want it to get it.
// Details of the disputed blob resolution:
// Given a box with area A, and a blob with area B, with overlap area C,
// then the miss metric is (A-C)(B-C)/(AB) and the box with minimum
// miss metric gets the blob.
static double BoxMissMetric(const TBOX& box1, const TBOX& box2) {
int overlap_area = box1.intersection(box2).area();
double miss_metric = box1.area()- overlap_area;
miss_metric /= box1.area();
miss_metric *= box2.area() - overlap_area;
miss_metric /= box2.area();
return miss_metric;
}
// Gather consecutive blobs that match the given box into the best_state
// and corresponding correct_text.
// Fights over which box owns which blobs are settled by pre-chopping and
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an appropriate blob for a box.
// This means that occasionally, blobs may be incorrectly segmented if the
// chopper fails to find a suitable chop point.
bool Tesseract::ResegmentCharBox(PAGE_RES* page_res, const TBOX *prev_box,
const TBOX& box, const TBOX& next_box,
const char* correct_text) {
if (applybox_debug > 1) {
tprintf("\nAPPLY_BOX: in ResegmentCharBox() for %s\n", correct_text);
}
PAGE_RES_IT page_res_it(page_res);
WERD_RES* word_res;
for (word_res = page_res_it.word(); word_res != NULL;
word_res = page_res_it.forward()) {
if (!word_res->box_word->bounding_box().major_overlap(box))
continue;
if (applybox_debug > 1) {
tprintf("Checking word box:");
word_res->box_word->bounding_box().print();
}
int word_len = word_res->box_word->length();
for (int i = 0; i < word_len; ++i) {
TBOX char_box = TBOX();
int blob_count = 0;
for (blob_count = 0; i + blob_count < word_len; ++blob_count) {
TBOX blob_box = word_res->box_word->BlobBox(i + blob_count);
if (!blob_box.major_overlap(box))
break;
if (word_res->correct_text[i + blob_count].length() > 0)
break; // Blob is claimed already.
double current_box_miss_metric = BoxMissMetric(blob_box, box);
double next_box_miss_metric = BoxMissMetric(blob_box, next_box);
if (applybox_debug > 2) {
tprintf("Checking blob:");
blob_box.print();
tprintf("Current miss metric = %g, next = %g\n",
current_box_miss_metric, next_box_miss_metric);
}
if (current_box_miss_metric > next_box_miss_metric)
break; // Blob is a better match for next box.
char_box += blob_box;
}
if (blob_count > 0) {
if (applybox_debug > 1) {
tprintf("Index [%d, %d) seem good.\n", i, i + blob_count);
}
if (!char_box.almost_equal(box, 3) &&
(box.x_gap(next_box) < -3 ||
(prev_box != NULL && prev_box->x_gap(box) < -3))) {
return false;
}
// We refine just the box_word, best_state and correct_text here.
// The rebuild_word is made in TidyUp.
// blob_count blobs are put together to match the box. Merge the
// box_word boxes, save the blob_count in the state and the text.
word_res->box_word->MergeBoxes(i, i + blob_count);
word_res->best_state[i] = blob_count;
word_res->correct_text[i] = correct_text;
if (applybox_debug > 2) {
tprintf("%d Blobs match: blob box:", blob_count);
word_res->box_word->BlobBox(i).print();
tprintf("Matches box:");
box.print();
tprintf("With next box:");
next_box.print();
}
// Eliminated best_state and correct_text entries for the consumed
// blobs.
for (int j = 1; j < blob_count; ++j) {
word_res->best_state.remove(i + 1);
word_res->correct_text.remove(i + 1);
}
// Assume that no box spans multiple source words, so we are done with
// this box.
if (applybox_debug > 1) {
tprintf("Best state = ");
for (int j = 0; j < word_res->best_state.size(); ++j) {
tprintf("%d ", word_res->best_state[j]);
}
tprintf("\n");
tprintf("Correct text = [[ ");
for (int j = 0; j < word_res->correct_text.size(); ++j) {
tprintf("%s ", word_res->correct_text[j].string());
}
tprintf("]]\n");
}
return true;
}
}
}
if (applybox_debug > 0) {
tprintf("FAIL!\n");
}
return false; // Failure.
}
// Consume all source blobs that strongly overlap the given box,
// putting them into a new word, with the correct_text label.
// Fights over which box owns which blobs are settled by
// applying the blobs to box or next_box with the least non-overlap.
// Returns false if the box was in error, which can only be caused by
// failing to find an overlapping blob for a box.
bool Tesseract::ResegmentWordBox(BLOCK_LIST *block_list,
const TBOX& box, const TBOX& next_box,
const char* correct_text) {
if (applybox_debug > 1) {
tprintf("\nAPPLY_BOX: in ResegmentWordBox() for %s\n", correct_text);
}
WERD* new_word = NULL;
BLOCK_IT b_it(block_list);
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
BLOCK* block = b_it.data();
if (!box.major_overlap(block->bounding_box()))
continue;
ROW_IT r_it(block->row_list());
for (r_it.mark_cycle_pt(); !r_it.cycled_list(); r_it.forward()) {
ROW* row = r_it.data();
if (!box.major_overlap(row->bounding_box()))
continue;
WERD_IT w_it(row->word_list());
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
WERD* word = w_it.data();
if (applybox_debug > 2) {
tprintf("Checking word:");
word->bounding_box().print();
}
if (word->text() != NULL && word->text()[0] != '\0')
continue; // Ignore words that are already done.
if (!box.major_overlap(word->bounding_box()))
continue;
C_BLOB_IT blob_it(word->cblob_list());
for (blob_it.mark_cycle_pt(); !blob_it.cycled_list();
blob_it.forward()) {
C_BLOB* blob = blob_it.data();
TBOX blob_box = blob->bounding_box();
if (!blob_box.major_overlap(box))
continue;
double current_box_miss_metric = BoxMissMetric(blob_box, box);
double next_box_miss_metric = BoxMissMetric(blob_box, next_box);
if (applybox_debug > 2) {
tprintf("Checking blob:");
blob_box.print();
tprintf("Current miss metric = %g, next = %g\n",
current_box_miss_metric, next_box_miss_metric);
}
if (current_box_miss_metric > next_box_miss_metric)
continue; // Blob is a better match for next box.
if (applybox_debug > 2) {
tprintf("Blob match: blob:");
blob_box.print();
tprintf("Matches box:");
box.print();
tprintf("With next box:");
next_box.print();
}
if (new_word == NULL) {
// Make a new word with a single blob.
new_word = word->shallow_copy();
new_word->set_text(correct_text);
w_it.add_to_end(new_word);
}
C_BLOB_IT new_blob_it(new_word->cblob_list());
new_blob_it.add_to_end(blob_it.extract());
}
}
}
}
if (new_word == NULL && applybox_debug > 0) tprintf("FAIL!\n");
return new_word != NULL;
}
// Resegments the words by running the classifier in an attempt to find the
// correct segmentation that produces the required string.
void Tesseract::ReSegmentByClassification(PAGE_RES* page_res) {
PAGE_RES_IT pr_it(page_res);
WERD_RES* word_res;
for (; (word_res = pr_it.word()) != NULL; pr_it.forward()) {
WERD* word = word_res->word;
if (word->text() == NULL || word->text()[0] == '\0')
continue; // Ignore words that have no text.
// Convert the correct text to a vector of UNICHAR_ID
GenericVector<UNICHAR_ID> target_text;
if (!ConvertStringToUnichars(word->text(), &target_text)) {
tprintf("APPLY_BOX: FAILURE: can't find class_id for '%s'\n",
word->text());
pr_it.DeleteCurrentWord();
continue;
}
if (!FindSegmentation(target_text, word_res)) {
tprintf("APPLY_BOX: FAILURE: can't find segmentation for '%s'\n",
word->text());
pr_it.DeleteCurrentWord();
continue;
}
}
}
// Converts the space-delimited string of utf8 text to a vector of UNICHAR_ID.
// Returns false if an invalid UNICHAR_ID is encountered.
bool Tesseract::ConvertStringToUnichars(const char* utf8,
GenericVector<UNICHAR_ID>* class_ids) {
for (int step = 0; *utf8 != '\0'; utf8 += step) {
const char* next_space = strchr(utf8, ' ');
if (next_space == NULL)
next_space = utf8 + strlen(utf8);
step = next_space - utf8;
UNICHAR_ID class_id = unicharset.unichar_to_id(utf8, step);
if (class_id == INVALID_UNICHAR_ID) {
return false;
}
while (utf8[step] == ' ')
++step;
class_ids->push_back(class_id);
}
return true;
}
// Resegments the word to achieve the target_text from the classifier.
// Returns false if the re-segmentation fails.
// Uses brute-force combination of up to kMaxGroupSize adjacent blobs, and
// applies a full search on the classifier results to find the best classified
// segmentation. As a compromise to obtain better recall, 1-1 ambiguity
// substitutions ARE used.
bool Tesseract::FindSegmentation(const GenericVector<UNICHAR_ID>& target_text,
WERD_RES* word_res) {
// Classify all required combinations of blobs and save results in choices.
int word_length = word_res->box_word->length();
GenericVector<BLOB_CHOICE_LIST*>* choices =
new GenericVector<BLOB_CHOICE_LIST*>[word_length];
for (int i = 0; i < word_length; ++i) {
for (int j = 1; j <= kMaxGroupSize && i + j <= word_length; ++j) {
BLOB_CHOICE_LIST* match_result = classify_piece(
word_res->seam_array, i, i + j - 1, "Applybox",
word_res->chopped_word, word_res->blamer_bundle);
if (applybox_debug > 2) {
tprintf("%d+%d:", i, j);
print_ratings_list("Segment:", match_result, unicharset);
}
choices[i].push_back(match_result);
}
}
// Search the segmentation graph for the target text. Must be an exact
// match. Using wildcards makes it difficult to find the correct
// segmentation even when it is there.
word_res->best_state.clear();
GenericVector<int> search_segmentation;
float best_rating = 0.0f;
SearchForText(choices, 0, word_length, target_text, 0, 0.0f,
&search_segmentation, &best_rating, &word_res->best_state);
for (int i = 0; i < word_length; ++i)
choices[i].delete_data_pointers();
delete [] choices;
if (word_res->best_state.empty()) {
// Build the original segmentation and if it is the same length as the
// truth, assume it will do.
int blob_count = 1;
for (int s = 0; s < word_res->seam_array.size(); ++s) {
SEAM* seam = word_res->seam_array[s];
if (seam->split1 == NULL) {
word_res->best_state.push_back(blob_count);
blob_count = 1;
} else {
++blob_count;
}
}
word_res->best_state.push_back(blob_count);
if (word_res->best_state.size() != target_text.size()) {
word_res->best_state.clear(); // No good. Original segmentation bad size.
return false;
}
}
word_res->correct_text.clear();
for (int i = 0; i < target_text.size(); ++i) {
word_res->correct_text.push_back(
STRING(unicharset.id_to_unichar(target_text[i])));
}
return true;
}
// Recursive helper to find a match to the target_text (from text_index
// position) in the choices (from choices_pos position).
// Choices is an array of GenericVectors, of length choices_length, with each
// element representing a starting position in the word, and the
// GenericVector holding classification results for a sequence of consecutive
// blobs, with index 0 being a single blob, index 1 being 2 blobs etc.
void Tesseract::SearchForText(const GenericVector<BLOB_CHOICE_LIST*>* choices,
int choices_pos, int choices_length,
const GenericVector<UNICHAR_ID>& target_text,
int text_index,
float rating, GenericVector<int>* segmentation,
float* best_rating,
GenericVector<int>* best_segmentation) {
const UnicharAmbigsVector& table = getDict().getUnicharAmbigs().dang_ambigs();
for (int length = 1; length <= choices[choices_pos].size(); ++length) {
// Rating of matching choice or worst choice if no match.
float choice_rating = 0.0f;
// Find the corresponding best BLOB_CHOICE.
BLOB_CHOICE_IT choice_it(choices[choices_pos][length - 1]);
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
choice_it.forward()) {
BLOB_CHOICE* choice = choice_it.data();
choice_rating = choice->rating();
UNICHAR_ID class_id = choice->unichar_id();
if (class_id == target_text[text_index]) {
break;
}
// Search ambigs table.
if (class_id < table.size() && table[class_id] != NULL) {
AmbigSpec_IT spec_it(table[class_id]);
for (spec_it.mark_cycle_pt(); !spec_it.cycled_list();
spec_it.forward()) {
const AmbigSpec *ambig_spec = spec_it.data();
// We'll only do 1-1.
if (ambig_spec->wrong_ngram[1] == INVALID_UNICHAR_ID &&
ambig_spec->correct_ngram_id == target_text[text_index])
break;
}
if (!spec_it.cycled_list())
break; // Found an ambig.
}
}
if (choice_it.cycled_list())
continue; // No match.
segmentation->push_back(length);
if (choices_pos + length == choices_length &&
text_index + 1 == target_text.size()) {
// This is a complete match. If the rating is good record a new best.
if (applybox_debug > 2) {
tprintf("Complete match, rating = %g, best=%g, seglength=%d, best=%d\n",
rating + choice_rating, *best_rating, segmentation->size(),
best_segmentation->size());
}
if (best_segmentation->empty() || rating + choice_rating < *best_rating) {
*best_segmentation = *segmentation;
*best_rating = rating + choice_rating;
}
} else if (choices_pos + length < choices_length &&
text_index + 1 < target_text.size()) {
if (applybox_debug > 3) {
tprintf("Match found for %d=%s:%s, at %d+%d, recursing...\n",
target_text[text_index],
unicharset.id_to_unichar(target_text[text_index]),
choice_it.data()->unichar_id() == target_text[text_index]
? "Match" : "Ambig",
choices_pos, length);
}
SearchForText(choices, choices_pos + length, choices_length, target_text,
text_index + 1, rating + choice_rating, segmentation,
best_rating, best_segmentation);
if (applybox_debug > 3) {
tprintf("End recursion for %d=%s\n", target_text[text_index],
unicharset.id_to_unichar(target_text[text_index]));
}
}
segmentation->truncate(segmentation->size() - 1);
}
}
// Counts up the labelled words and the blobs within.
// Deletes all unused or emptied words, counting the unused ones.
// Resets W_BOL and W_EOL flags correctly.
// Builds the rebuild_word and rebuilds the box_word and the best_choice.
void Tesseract::TidyUp(PAGE_RES* page_res) {
int ok_blob_count = 0;
int bad_blob_count = 0;
int ok_word_count = 0;
int unlabelled_words = 0;
PAGE_RES_IT pr_it(page_res);
WERD_RES* word_res;
for (; (word_res = pr_it.word()) != NULL; pr_it.forward()) {
int ok_in_word = 0;
int blob_count = word_res->correct_text.size();
WERD_CHOICE* word_choice = new WERD_CHOICE(word_res->uch_set, blob_count);
word_choice->set_permuter(TOP_CHOICE_PERM);
for (int c = 0; c < blob_count; ++c) {
if (word_res->correct_text[c].length() > 0) {
++ok_in_word;
}
// Since we only need a fake word_res->best_choice, the actual
// unichar_ids do not matter. Which is fortunate, since TidyUp()
// can be called while training Tesseract, at the stage where
// unicharset is not meaningful yet.
word_choice->append_unichar_id_space_allocated(
INVALID_UNICHAR_ID, word_res->best_state[c], 1.0f, -1.0f);
}
if (ok_in_word > 0) {
ok_blob_count += ok_in_word;
bad_blob_count += word_res->correct_text.size() - ok_in_word;
word_res->LogNewRawChoice(word_choice);
word_res->LogNewCookedChoice(1, false, word_choice);
} else {
++unlabelled_words;
if (applybox_debug > 0) {
tprintf("APPLY_BOXES: Unlabelled word at :");
word_res->word->bounding_box().print();
}
pr_it.DeleteCurrentWord();
delete word_choice;
}
}
pr_it.restart_page();
for (; (word_res = pr_it.word()) != NULL; pr_it.forward()) {
// Denormalize back to a BoxWord.
word_res->RebuildBestState();
word_res->SetupBoxWord();
word_res->word->set_flag(W_BOL, pr_it.prev_row() != pr_it.row());
word_res->word->set_flag(W_EOL, pr_it.next_row() != pr_it.row());
}
if (applybox_debug > 0) {
tprintf(" Found %d good blobs.\n", ok_blob_count);
if (bad_blob_count > 0) {
tprintf(" Leaving %d unlabelled blobs in %d words.\n",
bad_blob_count, ok_word_count);
}
if (unlabelled_words > 0)
tprintf(" %d remaining unlabelled words deleted.\n", unlabelled_words);
}
}
// Logs a bad box by line in the box file and box coords.
void Tesseract::ReportFailedBox(int boxfile_lineno, TBOX box,
const char *box_ch, const char *err_msg) {
tprintf("APPLY_BOXES: boxfile line %d/%s ((%d,%d),(%d,%d)): %s\n",
boxfile_lineno + 1, box_ch,
box.left(), box.bottom(), box.right(), box.top(), err_msg);
}
// Creates a fake best_choice entry in each WERD_RES with the correct text.
void Tesseract::CorrectClassifyWords(PAGE_RES* page_res) {
PAGE_RES_IT pr_it(page_res);
for (WERD_RES *word_res = pr_it.word(); word_res != NULL;
word_res = pr_it.forward()) {
WERD_CHOICE* choice = new WERD_CHOICE(word_res->uch_set,
word_res->correct_text.size());
for (int i = 0; i < word_res->correct_text.size(); ++i) {
// The part before the first space is the real ground truth, and the
// rest is the bounding box location and page number.
GenericVector<STRING> tokens;
word_res->correct_text[i].split(' ', &tokens);
UNICHAR_ID char_id = unicharset.unichar_to_id(tokens[0].string());
choice->append_unichar_id_space_allocated(char_id,
word_res->best_state[i],
0.0f, 0.0f);
}
word_res->ClearWordChoices();
word_res->LogNewRawChoice(choice);
word_res->LogNewCookedChoice(1, false, choice);
}
}
// Calls LearnWord to extract features for labelled blobs within each word.
// Features are written to the given filename.
void Tesseract::ApplyBoxTraining(const STRING& filename, PAGE_RES* page_res) {
PAGE_RES_IT pr_it(page_res);
int word_count = 0;
for (WERD_RES *word_res = pr_it.word(); word_res != NULL;
word_res = pr_it.forward()) {
LearnWord(filename.string(), word_res);
++word_count;
}
tprintf("Generated training data for %d words\n", word_count);
}
} // namespace tesseract
| C++ |
/******************************************************************
* File: output.cpp (Formerly output.c)
* Description: Output pass
* Author: Phil Cheatle
* Created: Thu Aug 4 10:56:08 BST 1994
*
* (C) Copyright 1994, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
#include <string.h>
#include <ctype.h>
#ifdef __UNIX__
#include <assert.h>
#include <unistd.h>
#include <errno.h>
#endif
#include "helpers.h"
#include "tessvars.h"
#include "control.h"
#include "reject.h"
#include "docqual.h"
#include "output.h"
#include "globals.h"
#include "tesseractclass.h"
#define EPAPER_EXT ".ep"
#define PAGE_YSIZE 3508
#define CTRL_INSET '\024' //dc4=text inset
#define CTRL_FONT '\016' //so=font change
#define CTRL_DEFAULT '\017' //si=default font
#define CTRL_SHIFT '\022' //dc2=x shift
#define CTRL_TAB '\011' //tab
#define CTRL_NEWLINE '\012' //newline
#define CTRL_HARDLINE '\015' //cr
/**********************************************************************
* pixels_to_pts
*
* Convert an integer number of pixels to the nearest integer
* number of points.
**********************************************************************/
inT32 pixels_to_pts( //convert coords
inT32 pixels,
inT32 pix_res //resolution
) {
float pts; //converted value
pts = pixels * 72.0 / pix_res;
return (inT32) (pts + 0.5); //round it
}
namespace tesseract {
void Tesseract::output_pass( //Tess output pass //send to api
PAGE_RES_IT &page_res_it,
const TBOX *target_word_box) {
BLOCK_RES *block_of_last_word;
BOOL8 force_eol; //During output
BLOCK *nextblock; //block of next word
WERD *nextword; //next word
page_res_it.restart_page ();
block_of_last_word = NULL;
while (page_res_it.word () != NULL) {
check_debug_pt (page_res_it.word (), 120);
if (target_word_box)
{
TBOX current_word_box=page_res_it.word ()->word->bounding_box();
FCOORD center_pt((current_word_box.right()+current_word_box.left())/2,(current_word_box.bottom()+current_word_box.top())/2);
if (!target_word_box->contains(center_pt))
{
page_res_it.forward ();
continue;
}
}
if (tessedit_write_block_separators &&
block_of_last_word != page_res_it.block ()) {
block_of_last_word = page_res_it.block ();
}
force_eol = (tessedit_write_block_separators &&
(page_res_it.block () != page_res_it.next_block ())) ||
(page_res_it.next_word () == NULL);
if (page_res_it.next_word () != NULL)
nextword = page_res_it.next_word ()->word;
else
nextword = NULL;
if (page_res_it.next_block () != NULL)
nextblock = page_res_it.next_block ()->block;
else
nextblock = NULL;
//regardless of tilde crunching
write_results(page_res_it,
determine_newline_type(page_res_it.word()->word,
page_res_it.block()->block,
nextword, nextblock), force_eol);
page_res_it.forward();
}
}
/*************************************************************************
* write_results()
*
* All recognition and rejection has now been done. Generate the following:
* .txt file - giving the final best choices with NO highlighting
* .raw file - giving the tesseract top choice output for each word
* .map file - showing how the .txt file has been rejected in the .ep file
* epchoice list - a list of one element per word, containing the text for the
* epaper. Reject strings are inserted.
* inset list - a list of bounding boxes of reject insets - indexed by the
* reject strings in the epchoice text.
*************************************************************************/
void Tesseract::write_results(PAGE_RES_IT &page_res_it,
char newline_type, // type of newline
BOOL8 force_eol) { // override tilde crunch?
WERD_RES *word = page_res_it.word();
const UNICHARSET &uchset = *word->uch_set;
int i;
BOOL8 need_reject = FALSE;
UNICHAR_ID space = uchset.unichar_to_id(" ");
if ((word->unlv_crunch_mode != CR_NONE ||
word->best_choice->length() == 0) &&
!tessedit_zero_kelvin_rejection && !tessedit_word_for_word) {
if ((word->unlv_crunch_mode != CR_DELETE) &&
(!stats_.tilde_crunch_written ||
((word->unlv_crunch_mode == CR_KEEP_SPACE) &&
(word->word->space () > 0) &&
!word->word->flag (W_FUZZY_NON) &&
!word->word->flag (W_FUZZY_SP)))) {
if (!word->word->flag (W_BOL) &&
(word->word->space () > 0) &&
!word->word->flag (W_FUZZY_NON) &&
!word->word->flag (W_FUZZY_SP)) {
stats_.last_char_was_tilde = false;
}
need_reject = TRUE;
}
if ((need_reject && !stats_.last_char_was_tilde) ||
(force_eol && stats_.write_results_empty_block)) {
/* Write a reject char - mark as rejected unless zero_rejection mode */
stats_.last_char_was_tilde = TRUE;
stats_.tilde_crunch_written = true;
stats_.last_char_was_newline = false;
stats_.write_results_empty_block = false;
}
if ((word->word->flag (W_EOL) && !stats_.last_char_was_newline) || force_eol) {
stats_.tilde_crunch_written = false;
stats_.last_char_was_newline = true;
stats_.last_char_was_tilde = false;
}
if (force_eol)
stats_.write_results_empty_block = true;
return;
}
/* NORMAL PROCESSING of non tilde crunched words */
stats_.tilde_crunch_written = false;
if (newline_type)
stats_.last_char_was_newline = true;
else
stats_.last_char_was_newline = false;
stats_.write_results_empty_block = force_eol; // about to write a real word
if (unlv_tilde_crunching &&
stats_.last_char_was_tilde &&
(word->word->space() == 0) &&
!(word->word->flag(W_REP_CHAR) && tessedit_write_rep_codes) &&
(word->best_choice->unichar_id(0) == space)) {
/* Prevent adjacent tilde across words - we know that adjacent tildes within
words have been removed */
word->MergeAdjacentBlobs(0);
}
if (newline_type ||
(word->word->flag (W_REP_CHAR) && tessedit_write_rep_codes))
stats_.last_char_was_tilde = false;
else {
if (word->reject_map.length () > 0) {
if (word->best_choice->unichar_id(word->reject_map.length() - 1) == space)
stats_.last_char_was_tilde = true;
else
stats_.last_char_was_tilde = false;
}
else if (word->word->space () > 0)
stats_.last_char_was_tilde = false;
/* else it is unchanged as there are no output chars */
}
ASSERT_HOST (word->best_choice->length() == word->reject_map.length());
set_unlv_suspects(word);
check_debug_pt (word, 120);
if (tessedit_rejection_debug) {
tprintf ("Dict word: \"%s\": %d\n",
word->best_choice->debug_string().string(),
dict_word(*(word->best_choice)));
}
if (!word->word->flag(W_REP_CHAR) || !tessedit_write_rep_codes) {
if (tessedit_zero_rejection) {
/* OVERRIDE ALL REJECTION MECHANISMS - ONLY REJECT TESS FAILURES */
for (i = 0; i < word->best_choice->length(); ++i) {
if (word->reject_map[i].rejected())
word->reject_map[i].setrej_minimal_rej_accept();
}
}
if (tessedit_minimal_rejection) {
/* OVERRIDE ALL REJECTION MECHANISMS - ONLY REJECT TESS FAILURES */
for (i = 0; i < word->best_choice->length(); ++i) {
if ((word->best_choice->unichar_id(i) != space) &&
word->reject_map[i].rejected())
word->reject_map[i].setrej_minimal_rej_accept();
}
}
}
}
} // namespace tesseract
/**********************************************************************
* determine_newline_type
*
* Find whether we have a wrapping or hard newline.
* Return FALSE if not at end of line.
**********************************************************************/
char determine_newline_type( //test line ends
WERD *word, //word to do
BLOCK *block, //current block
WERD *next_word, //next word
BLOCK *next_block //block of next word
) {
inT16 end_gap; //to right edge
inT16 width; //of next word
TBOX word_box; //bounding
TBOX next_box; //next word
TBOX block_box; //block bounding
if (!word->flag (W_EOL))
return FALSE; //not end of line
if (next_word == NULL || next_block == NULL || block != next_block)
return CTRL_NEWLINE;
if (next_word->space () > 0)
return CTRL_HARDLINE; //it is tabbed
word_box = word->bounding_box ();
next_box = next_word->bounding_box ();
block_box = block->bounding_box ();
//gap to eol
end_gap = block_box.right () - word_box.right ();
end_gap -= (inT32) block->space ();
width = next_box.right () - next_box.left ();
// tprintf("end_gap=%d-%d=%d, width=%d-%d=%d, nl=%d\n",
// block_box.right(),word_box.right(),end_gap,
// next_box.right(),next_box.left(),width,
// end_gap>width ? CTRL_HARDLINE : CTRL_NEWLINE);
return end_gap > width ? CTRL_HARDLINE : CTRL_NEWLINE;
}
/*************************************************************************
* get_rep_char()
* Return the first accepted character from the repetition string. This is the
* character which is repeated - as determined earlier by fix_rep_char()
*************************************************************************/
namespace tesseract {
UNICHAR_ID Tesseract::get_rep_char(WERD_RES *word) { // what char is repeated?
int i;
for (i = 0; ((i < word->reject_map.length()) &&
(word->reject_map[i].rejected())); ++i);
if (i < word->reject_map.length()) {
return word->best_choice->unichar_id(i);
} else {
return word->uch_set->unichar_to_id(unrecognised_char.string());
}
}
/*************************************************************************
* SUSPECT LEVELS
*
* 0 - dont reject ANYTHING
* 1,2 - partial rejection
* 3 - BEST
*
* NOTE: to reject JUST tess failures in the .map file set suspect_level 3 and
* tessedit_minimal_rejection.
*************************************************************************/
void Tesseract::set_unlv_suspects(WERD_RES *word_res) {
int len = word_res->reject_map.length();
const WERD_CHOICE &word = *(word_res->best_choice);
const UNICHARSET &uchset = *word.unicharset();
int i;
float rating_per_ch;
if (suspect_level == 0) {
for (i = 0; i < len; i++) {
if (word_res->reject_map[i].rejected())
word_res->reject_map[i].setrej_minimal_rej_accept();
}
return;
}
if (suspect_level >= 3)
return; //Use defaults
/* NOW FOR LEVELS 1 and 2 Find some stuff to unreject*/
if (safe_dict_word(word_res) &&
(count_alphas(word) > suspect_short_words)) {
/* Unreject alphas in dictionary words */
for (i = 0; i < len; ++i) {
if (word_res->reject_map[i].rejected() &&
uchset.get_isalpha(word.unichar_id(i)))
word_res->reject_map[i].setrej_minimal_rej_accept();
}
}
rating_per_ch = word.rating() / word_res->reject_map.length();
if (rating_per_ch >= suspect_rating_per_ch)
return; //Dont touch bad ratings
if ((word_res->tess_accepted) || (rating_per_ch < suspect_accept_rating)) {
/* Unreject any Tess Acceptable word - but NOT tess reject chs*/
for (i = 0; i < len; ++i) {
if (word_res->reject_map[i].rejected() &&
(!uchset.eq(word.unichar_id(i), " ")))
word_res->reject_map[i].setrej_minimal_rej_accept();
}
}
for (i = 0; i < len; i++) {
if (word_res->reject_map[i].rejected()) {
if (word_res->reject_map[i].flag(R_DOC_REJ))
word_res->reject_map[i].setrej_minimal_rej_accept();
if (word_res->reject_map[i].flag(R_BLOCK_REJ))
word_res->reject_map[i].setrej_minimal_rej_accept();
if (word_res->reject_map[i].flag(R_ROW_REJ))
word_res->reject_map[i].setrej_minimal_rej_accept();
}
}
if (suspect_level == 2)
return;
if (!suspect_constrain_1Il ||
(word_res->reject_map.length() <= suspect_short_words)) {
for (i = 0; i < len; i++) {
if (word_res->reject_map[i].rejected()) {
if ((word_res->reject_map[i].flag(R_1IL_CONFLICT) ||
word_res->reject_map[i].flag(R_POSTNN_1IL)))
word_res->reject_map[i].setrej_minimal_rej_accept();
if (!suspect_constrain_1Il &&
word_res->reject_map[i].flag(R_MM_REJECT))
word_res->reject_map[i].setrej_minimal_rej_accept();
}
}
}
if (acceptable_word_string(*word_res->uch_set,
word.unichar_string().string(),
word.unichar_lengths().string()) !=
AC_UNACCEPTABLE ||
acceptable_number_string(word.unichar_string().string(),
word.unichar_lengths().string())) {
if (word_res->reject_map.length() > suspect_short_words) {
for (i = 0; i < len; i++) {
if (word_res->reject_map[i].rejected() &&
(!word_res->reject_map[i].perm_rejected() ||
word_res->reject_map[i].flag (R_1IL_CONFLICT) ||
word_res->reject_map[i].flag (R_POSTNN_1IL) ||
word_res->reject_map[i].flag (R_MM_REJECT))) {
word_res->reject_map[i].setrej_minimal_rej_accept();
}
}
}
}
}
inT16 Tesseract::count_alphas(const WERD_CHOICE &word) {
int count = 0;
for (int i = 0; i < word.length(); ++i) {
if (word.unicharset()->get_isalpha(word.unichar_id(i)))
count++;
}
return count;
}
inT16 Tesseract::count_alphanums(const WERD_CHOICE &word) {
int count = 0;
for (int i = 0; i < word.length(); ++i) {
if (word.unicharset()->get_isalpha(word.unichar_id(i)) ||
word.unicharset()->get_isdigit(word.unichar_id(i)))
count++;
}
return count;
}
BOOL8 Tesseract::acceptable_number_string(const char *s,
const char *lengths) {
BOOL8 prev_digit = FALSE;
if (*lengths == 1 && *s == '(')
s++;
if (*lengths == 1 &&
((*s == '$') || (*s == '.') || (*s == '+') || (*s == '-')))
s++;
for (; *s != '\0'; s += *(lengths++)) {
if (unicharset.get_isdigit(s, *lengths))
prev_digit = TRUE;
else if (prev_digit &&
(*lengths == 1 && ((*s == '.') || (*s == ',') || (*s == '-'))))
prev_digit = FALSE;
else if (prev_digit && *lengths == 1 &&
(*(s + *lengths) == '\0') && ((*s == '%') || (*s == ')')))
return TRUE;
else if (prev_digit &&
*lengths == 1 && (*s == '%') &&
(*(lengths + 1) == 1 && *(s + *lengths) == ')') &&
(*(s + *lengths + *(lengths + 1)) == '\0'))
return TRUE;
else
return FALSE;
}
return TRUE;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: pagesegmain.cpp
* Description: Top-level page segmenter for Tesseract.
* Author: Ray Smith
* Created: Thu Sep 25 17:12:01 PDT 2008
*
* (C) Copyright 2008, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _WIN32
#ifndef __GNUC__
#include <windows.h>
#endif // __GNUC__
#ifndef unlink
#include <io.h>
#endif
#else
#include <unistd.h>
#endif // _WIN32
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#include "allheaders.h"
#include "blobbox.h"
#include "blread.h"
#include "colfind.h"
#include "equationdetect.h"
#include "imagefind.h"
#include "linefind.h"
#include "makerow.h"
#include "osdetect.h"
#include "tabvector.h"
#include "tesseractclass.h"
#include "tessvars.h"
#include "textord.h"
#include "tordmain.h"
#include "wordseg.h"
namespace tesseract {
/// Minimum believable resolution.
const int kMinCredibleResolution = 70;
/// Default resolution used if input in not believable.
const int kDefaultResolution = 300;
// Max erosions to perform in removing an enclosing circle.
const int kMaxCircleErosions = 8;
// Helper to remove an enclosing circle from an image.
// If there isn't one, then the image will most likely get badly mangled.
// The returned pix must be pixDestroyed after use. NULL may be returned
// if the image doesn't meet the trivial conditions that it uses to determine
// success.
static Pix* RemoveEnclosingCircle(Pix* pixs) {
Pix* pixsi = pixInvert(NULL, pixs);
Pix* pixc = pixCreateTemplate(pixs);
pixSetOrClearBorder(pixc, 1, 1, 1, 1, PIX_SET);
pixSeedfillBinary(pixc, pixc, pixsi, 4);
pixInvert(pixc, pixc);
pixDestroy(&pixsi);
Pix* pixt = pixAnd(NULL, pixs, pixc);
l_int32 max_count;
pixCountConnComp(pixt, 8, &max_count);
// The count has to go up before we start looking for the minimum.
l_int32 min_count = MAX_INT32;
Pix* pixout = NULL;
for (int i = 1; i < kMaxCircleErosions; i++) {
pixDestroy(&pixt);
pixErodeBrick(pixc, pixc, 3, 3);
pixt = pixAnd(NULL, pixs, pixc);
l_int32 count;
pixCountConnComp(pixt, 8, &count);
if (i == 1 || count > max_count) {
max_count = count;
min_count = count;
} else if (i > 1 && count < min_count) {
min_count = count;
pixDestroy(&pixout);
pixout = pixCopy(NULL, pixt); // Save the best.
} else if (count >= min_count) {
break; // We have passed by the best.
}
}
pixDestroy(&pixt);
pixDestroy(&pixc);
return pixout;
}
/**
* Segment the page according to the current value of tessedit_pageseg_mode.
* pix_binary_ is used as the source image and should not be NULL.
* On return the blocks list owns all the constructed page layout.
*/
int Tesseract::SegmentPage(const STRING* input_file, BLOCK_LIST* blocks,
Tesseract* osd_tess, OSResults* osr) {
ASSERT_HOST(pix_binary_ != NULL);
int width = pixGetWidth(pix_binary_);
int height = pixGetHeight(pix_binary_);
// Get page segmentation mode.
PageSegMode pageseg_mode = static_cast<PageSegMode>(
static_cast<int>(tessedit_pageseg_mode));
// If a UNLV zone file can be found, use that instead of segmentation.
if (!PSM_COL_FIND_ENABLED(pageseg_mode) &&
input_file != NULL && input_file->length() > 0) {
STRING name = *input_file;
const char* lastdot = strrchr(name.string(), '.');
if (lastdot != NULL)
name[lastdot - name.string()] = '\0';
read_unlv_file(name, width, height, blocks);
}
if (blocks->empty()) {
// No UNLV file present. Work according to the PageSegMode.
// First make a single block covering the whole image.
BLOCK_IT block_it(blocks);
BLOCK* block = new BLOCK("", TRUE, 0, 0, 0, 0, width, height);
block->set_right_to_left(right_to_left());
block_it.add_to_end(block);
} else {
// UNLV file present. Use PSM_SINGLE_BLOCK.
pageseg_mode = PSM_SINGLE_BLOCK;
}
int auto_page_seg_ret_val = 0;
TO_BLOCK_LIST to_blocks;
if (PSM_OSD_ENABLED(pageseg_mode) || PSM_BLOCK_FIND_ENABLED(pageseg_mode) ||
PSM_SPARSE(pageseg_mode)) {
auto_page_seg_ret_val =
AutoPageSeg(pageseg_mode, blocks, &to_blocks, osd_tess, osr);
if (pageseg_mode == PSM_OSD_ONLY)
return auto_page_seg_ret_val;
// To create blobs from the image region bounds uncomment this line:
// to_blocks.clear(); // Uncomment to go back to the old mode.
} else {
deskew_ = FCOORD(1.0f, 0.0f);
reskew_ = FCOORD(1.0f, 0.0f);
if (pageseg_mode == PSM_CIRCLE_WORD) {
Pix* pixcleaned = RemoveEnclosingCircle(pix_binary_);
if (pixcleaned != NULL) {
pixDestroy(&pix_binary_);
pix_binary_ = pixcleaned;
}
}
}
if (auto_page_seg_ret_val < 0) {
return -1;
}
if (blocks->empty()) {
if (textord_debug_tabfind)
tprintf("Empty page\n");
return 0; // AutoPageSeg found an empty page.
}
bool splitting =
pageseg_devanagari_split_strategy != ShiroRekhaSplitter::NO_SPLIT;
bool cjk_mode = textord_use_cjk_fp_model;
textord_.TextordPage(pageseg_mode, reskew_, width, height, pix_binary_,
pix_thresholds_, pix_grey_, splitting || cjk_mode,
blocks, &to_blocks);
return auto_page_seg_ret_val;
}
// Helper writes a grey image to a file for use by scrollviewer.
// Normally for speed we don't display the image in the layout debug windows.
// If textord_debug_images is true, we draw the image as a background to some
// of the debug windows. printable determines whether these
// images are optimized for printing instead of screen display.
static void WriteDebugBackgroundImage(bool printable, Pix* pix_binary) {
Pix* grey_pix = pixCreate(pixGetWidth(pix_binary),
pixGetHeight(pix_binary), 8);
// Printable images are light grey on white, but for screen display
// they are black on dark grey so the other colors show up well.
if (printable) {
pixSetAll(grey_pix);
pixSetMasked(grey_pix, pix_binary, 192);
} else {
pixSetAllArbitrary(grey_pix, 64);
pixSetMasked(grey_pix, pix_binary, 0);
}
AlignedBlob::IncrementDebugPix();
pixWrite(AlignedBlob::textord_debug_pix().string(), grey_pix, IFF_PNG);
pixDestroy(&grey_pix);
}
/**
* Auto page segmentation. Divide the page image into blocks of uniform
* text linespacing and images.
*
* Resolution (in ppi) is derived from the input image.
*
* The output goes in the blocks list with corresponding TO_BLOCKs in the
* to_blocks list.
*
* If single_column is true, then no attempt is made to divide the image
* into columns, but multiple blocks are still made if the text is of
* non-uniform linespacing.
*
* If osd (orientation and script detection) is true then that is performed
* as well. If only_osd is true, then only orientation and script detection is
* performed. If osd is desired, (osd or only_osd) then osr_tess must be
* another Tesseract that was initialized especially for osd, and the results
* will be output into osr (orientation and script result).
*/
int Tesseract::AutoPageSeg(PageSegMode pageseg_mode,
BLOCK_LIST* blocks, TO_BLOCK_LIST* to_blocks,
Tesseract* osd_tess, OSResults* osr) {
if (textord_debug_images) {
WriteDebugBackgroundImage(textord_debug_printable, pix_binary_);
}
Pix* photomask_pix = NULL;
Pix* musicmask_pix = NULL;
// The blocks made by the ColumnFinder. Moved to blocks before return.
BLOCK_LIST found_blocks;
TO_BLOCK_LIST temp_blocks;
bool single_column = !PSM_COL_FIND_ENABLED(pageseg_mode);
bool osd_enabled = PSM_OSD_ENABLED(pageseg_mode);
bool osd_only = pageseg_mode == PSM_OSD_ONLY;
ColumnFinder* finder = SetupPageSegAndDetectOrientation(
single_column, osd_enabled, osd_only, blocks, osd_tess, osr,
&temp_blocks, &photomask_pix, &musicmask_pix);
int result = 0;
if (finder != NULL) {
TO_BLOCK_IT to_block_it(&temp_blocks);
TO_BLOCK* to_block = to_block_it.data();
if (musicmask_pix != NULL) {
// TODO(rays) pass the musicmask_pix into FindBlocks and mark music
// blocks separately. For now combine with photomask_pix.
pixOr(photomask_pix, photomask_pix, musicmask_pix);
}
if (equ_detect_) {
finder->SetEquationDetect(equ_detect_);
}
result = finder->FindBlocks(pageseg_mode, scaled_color_, scaled_factor_,
to_block, photomask_pix,
pix_thresholds_, pix_grey_,
&found_blocks, to_blocks);
if (result >= 0)
finder->GetDeskewVectors(&deskew_, &reskew_);
delete finder;
}
pixDestroy(&photomask_pix);
pixDestroy(&musicmask_pix);
if (result < 0) return result;
blocks->clear();
BLOCK_IT block_it(blocks);
// Move the found blocks to the input/output blocks.
block_it.add_list_after(&found_blocks);
if (textord_debug_images) {
// The debug image is no longer needed so delete it.
unlink(AlignedBlob::textord_debug_pix().string());
}
return result;
}
// Helper adds all the scripts from sid_set converted to ids from osd_set to
// allowed_ids.
static void AddAllScriptsConverted(const UNICHARSET& sid_set,
const UNICHARSET& osd_set,
GenericVector<int>* allowed_ids) {
for (int i = 0; i < sid_set.get_script_table_size(); ++i) {
if (i != sid_set.null_sid()) {
const char* script = sid_set.get_script_from_script_id(i);
allowed_ids->push_back(osd_set.get_script_id_from_name(script));
}
}
}
/**
* Sets up auto page segmentation, determines the orientation, and corrects it.
* Somewhat arbitrary chunk of functionality, factored out of AutoPageSeg to
* facilitate testing.
* photo_mask_pix is a pointer to a NULL pointer that will be filled on return
* with the leptonica photo mask, which must be pixDestroyed by the caller.
* to_blocks is an empty list that will be filled with (usually a single)
* block that is used during layout analysis. This ugly API is required
* because of the possibility of a unlv zone file.
* TODO(rays) clean this up.
* See AutoPageSeg for other arguments.
* The returned ColumnFinder must be deleted after use.
*/
ColumnFinder* Tesseract::SetupPageSegAndDetectOrientation(
bool single_column, bool osd, bool only_osd,
BLOCK_LIST* blocks, Tesseract* osd_tess, OSResults* osr,
TO_BLOCK_LIST* to_blocks, Pix** photo_mask_pix, Pix** music_mask_pix) {
int vertical_x = 0;
int vertical_y = 1;
TabVector_LIST v_lines;
TabVector_LIST h_lines;
ICOORD bleft(0, 0);
ASSERT_HOST(pix_binary_ != NULL);
if (tessedit_dump_pageseg_images) {
pixWrite("tessinput.png", pix_binary_, IFF_PNG);
}
// Leptonica is used to find the rule/separator lines in the input.
LineFinder::FindAndRemoveLines(source_resolution_,
textord_tabfind_show_vlines, pix_binary_,
&vertical_x, &vertical_y, music_mask_pix,
&v_lines, &h_lines);
if (tessedit_dump_pageseg_images)
pixWrite("tessnolines.png", pix_binary_, IFF_PNG);
// Leptonica is used to find a mask of the photo regions in the input.
*photo_mask_pix = ImageFind::FindImages(pix_binary_);
if (tessedit_dump_pageseg_images)
pixWrite("tessnoimages.png", pix_binary_, IFF_PNG);
if (single_column)
v_lines.clear();
// The rest of the algorithm uses the usual connected components.
textord_.find_components(pix_binary_, blocks, to_blocks);
TO_BLOCK_IT to_block_it(to_blocks);
// There must be exactly one input block.
// TODO(rays) handle new textline finding with a UNLV zone file.
ASSERT_HOST(to_blocks->singleton());
TO_BLOCK* to_block = to_block_it.data();
TBOX blkbox = to_block->block->bounding_box();
ColumnFinder* finder = NULL;
if (to_block->line_size >= 2) {
finder = new ColumnFinder(static_cast<int>(to_block->line_size),
blkbox.botleft(), blkbox.topright(),
source_resolution_, textord_use_cjk_fp_model,
textord_tabfind_aligned_gap_fraction,
&v_lines, &h_lines, vertical_x, vertical_y);
finder->SetupAndFilterNoise(*photo_mask_pix, to_block);
if (equ_detect_) {
equ_detect_->LabelSpecialText(to_block);
}
BLOBNBOX_CLIST osd_blobs;
// osd_orientation is the number of 90 degree rotations to make the
// characters upright. (See osdetect.h for precise definition.)
// We want the text lines horizontal, (vertical text indicates vertical
// textlines) which may conflict (eg vertically written CJK).
int osd_orientation = 0;
bool vertical_text = textord_tabfind_force_vertical_text;
if (!vertical_text && textord_tabfind_vertical_text) {
vertical_text =
finder->IsVerticallyAlignedText(textord_tabfind_vertical_text_ratio,
to_block, &osd_blobs);
}
if (osd && osd_tess != NULL && osr != NULL) {
GenericVector<int> osd_scripts;
if (osd_tess != this) {
// We are running osd as part of layout analysis, so constrain the
// scripts to those allowed by *this.
AddAllScriptsConverted(unicharset, osd_tess->unicharset, &osd_scripts);
for (int s = 0; s < sub_langs_.size(); ++s) {
AddAllScriptsConverted(sub_langs_[s]->unicharset,
osd_tess->unicharset, &osd_scripts);
}
}
os_detect_blobs(&osd_scripts, &osd_blobs, osr, osd_tess);
if (only_osd) {
delete finder;
return NULL;
}
osd_orientation = osr->best_result.orientation_id;
double osd_score = osr->orientations[osd_orientation];
double osd_margin = min_orientation_margin * 2;
for (int i = 0; i < 4; ++i) {
if (i != osd_orientation &&
osd_score - osr->orientations[i] < osd_margin) {
osd_margin = osd_score - osr->orientations[i];
}
}
int best_script_id = osr->best_result.script_id;
const char* best_script_str =
osd_tess->unicharset.get_script_from_script_id(best_script_id);
bool cjk = best_script_id == osd_tess->unicharset.han_sid() ||
best_script_id == osd_tess->unicharset.hiragana_sid() ||
best_script_id == osd_tess->unicharset.katakana_sid() ||
strcmp("Japanese", best_script_str) == 0 ||
strcmp("Korean", best_script_str) == 0 ||
strcmp("Hangul", best_script_str) == 0;
if (cjk) {
finder->set_cjk_script(true);
}
if (osd_margin < min_orientation_margin) {
// The margin is weak.
if (!cjk && !vertical_text && osd_orientation == 2) {
// upside down latin text is improbable with such a weak margin.
tprintf("OSD: Weak margin (%.2f), horiz textlines, not CJK: "
"Don't rotate.\n", osd_margin);
osd_orientation = 0;
} else {
tprintf("OSD: Weak margin (%.2f) for %d blob text block, "
"but using orientation anyway: %d\n",
osd_blobs.length(), osd_margin, osd_orientation);
}
}
}
osd_blobs.shallow_clear();
finder->CorrectOrientation(to_block, vertical_text, osd_orientation);
}
return finder;
}
} // namespace tesseract.
| C++ |
/**********************************************************************
* File: tesseract_cube_combiner.h
* Description: Declaration of the Tesseract & Cube results combiner Class
* Author: Ahmad Abdulkader
* Created: 2008
*
* (C) Copyright 2008, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
// The TesseractCubeCombiner class provides the functionality of combining
// the recognition results of Tesseract and Cube at the word level
#include <algorithm>
#include <string>
#include <vector>
#include <wctype.h>
#include "tesseract_cube_combiner.h"
#include "cube_object.h"
#include "cube_reco_context.h"
#include "cube_utils.h"
#include "neural_net.h"
#include "tesseractclass.h"
#include "word_altlist.h"
namespace tesseract {
TesseractCubeCombiner::TesseractCubeCombiner(CubeRecoContext *cube_cntxt) {
cube_cntxt_ = cube_cntxt;
combiner_net_ = NULL;
}
TesseractCubeCombiner::~TesseractCubeCombiner() {
if (combiner_net_ != NULL) {
delete combiner_net_;
combiner_net_ = NULL;
}
}
bool TesseractCubeCombiner::LoadCombinerNet() {
ASSERT_HOST(cube_cntxt_);
// Compute the path of the combiner net
string data_path;
cube_cntxt_->GetDataFilePath(&data_path);
string net_file_name = data_path + cube_cntxt_->Lang() +
".tesseract_cube.nn";
// Return false if file does not exist
FILE *fp = fopen(net_file_name.c_str(), "rb");
if (fp == NULL)
return false;
else
fclose(fp);
// Load and validate net
combiner_net_ = NeuralNet::FromFile(net_file_name);
if (combiner_net_ == NULL) {
tprintf("Could not read combiner net file %s", net_file_name.c_str());
return false;
} else if (combiner_net_->out_cnt() != 2) {
tprintf("Invalid combiner net file %s! Output count != 2\n",
net_file_name.c_str());
delete combiner_net_;
combiner_net_ = NULL;
return false;
}
return true;
}
// Normalize a UTF-8 string. Converts the UTF-8 string to UTF32 and optionally
// strips punc and/or normalizes case and then converts back
string TesseractCubeCombiner::NormalizeString(const string &str,
bool remove_punc,
bool norm_case) {
// convert to UTF32
string_32 str32;
CubeUtils::UTF8ToUTF32(str.c_str(), &str32);
// strip punc and normalize
string_32 new_str32;
for (int idx = 0; idx < str32.length(); idx++) {
// if no punc removal is required or not a punctuation character
if (!remove_punc || iswpunct(str32[idx]) == 0) {
char_32 norm_char = str32[idx];
// normalize case if required
if (norm_case && iswalpha(norm_char)) {
norm_char = towlower(norm_char);
}
new_str32.push_back(norm_char);
}
}
// convert back to UTF8
string new_str;
CubeUtils::UTF32ToUTF8(new_str32.c_str(), &new_str);
return new_str;
}
// Compares 2 strings optionally ignoring punctuation
int TesseractCubeCombiner::CompareStrings(const string &str1,
const string &str2,
bool ignore_punc,
bool ignore_case) {
if (!ignore_punc && !ignore_case) {
return str1.compare(str2);
}
string norm_str1 = NormalizeString(str1, ignore_punc, ignore_case);
string norm_str2 = NormalizeString(str2, ignore_punc, ignore_case);
return norm_str1.compare(norm_str2);
}
// Check if a string is a valid Tess dict word or not
bool TesseractCubeCombiner::ValidWord(const string &str) {
return (cube_cntxt_->TesseractObject()->getDict().valid_word(str.c_str())
> 0);
}
// Public method for computing the combiner features. The agreement
// output parameter will be true if both answers are identical,
// and false otherwise.
bool TesseractCubeCombiner::ComputeCombinerFeatures(const string &tess_str,
int tess_confidence,
CubeObject *cube_obj,
WordAltList *cube_alt_list,
vector<double> *features,
bool *agreement) {
features->clear();
*agreement = false;
if (cube_alt_list == NULL || cube_alt_list->AltCount() <= 0)
return false;
// Get Cube's best string; return false if empty
char_32 *cube_best_str32 = cube_alt_list->Alt(0);
if (cube_best_str32 == NULL || CubeUtils::StrLen(cube_best_str32) < 1)
return false;
string cube_best_str;
int cube_best_cost = cube_alt_list->AltCost(0);
int cube_best_bigram_cost = 0;
bool cube_best_bigram_cost_valid = true;
if (cube_cntxt_->Bigrams())
cube_best_bigram_cost = cube_cntxt_->Bigrams()->
Cost(cube_best_str32, cube_cntxt_->CharacterSet());
else
cube_best_bigram_cost_valid = false;
CubeUtils::UTF32ToUTF8(cube_best_str32, &cube_best_str);
// Get Tesseract's UTF32 string
string_32 tess_str32;
CubeUtils::UTF8ToUTF32(tess_str.c_str(), &tess_str32);
// Compute agreement flag
*agreement = (tess_str.compare(cube_best_str) == 0);
// Get Cube's second best string; if empty, return false
char_32 *cube_next_best_str32;
string cube_next_best_str;
int cube_next_best_cost = WORST_COST;
if (cube_alt_list->AltCount() > 1) {
cube_next_best_str32 = cube_alt_list->Alt(1);
if (cube_next_best_str32 == NULL ||
CubeUtils::StrLen(cube_next_best_str32) == 0) {
return false;
}
cube_next_best_cost = cube_alt_list->AltCost(1);
CubeUtils::UTF32ToUTF8(cube_next_best_str32, &cube_next_best_str);
}
// Rank of Tesseract's top result in Cube's alternate list
int tess_rank = 0;
for (tess_rank = 0; tess_rank < cube_alt_list->AltCount(); tess_rank++) {
string alt_str;
CubeUtils::UTF32ToUTF8(cube_alt_list->Alt(tess_rank), &alt_str);
if (alt_str == tess_str)
break;
}
// Cube's cost for tesseract's result. Note that this modifies the
// state of cube_obj, including its alternate list by calling RecognizeWord()
int tess_cost = cube_obj->WordCost(tess_str.c_str());
// Cube's bigram cost of Tesseract's string
int tess_bigram_cost = 0;
int tess_bigram_cost_valid = true;
if (cube_cntxt_->Bigrams())
tess_bigram_cost = cube_cntxt_->Bigrams()->
Cost(tess_str32.c_str(), cube_cntxt_->CharacterSet());
else
tess_bigram_cost_valid = false;
// Tesseract confidence
features->push_back(tess_confidence);
// Cube cost of Tesseract string
features->push_back(tess_cost);
// Cube Rank of Tesseract string
features->push_back(tess_rank);
// length of Tesseract OCR string
features->push_back(tess_str.length());
// Tesseract OCR string in dictionary
features->push_back(ValidWord(tess_str));
if (tess_bigram_cost_valid) {
// bigram cost of Tesseract string
features->push_back(tess_bigram_cost);
}
// Cube tess_cost of Cube best string
features->push_back(cube_best_cost);
// Cube tess_cost of Cube next best string
features->push_back(cube_next_best_cost);
// length of Cube string
features->push_back(cube_best_str.length());
// Cube string in dictionary
features->push_back(ValidWord(cube_best_str));
if (cube_best_bigram_cost_valid) {
// bigram cost of Cube string
features->push_back(cube_best_bigram_cost);
}
// case-insensitive string comparison, including punctuation
int compare_nocase_punc = CompareStrings(cube_best_str,
tess_str, false, true);
features->push_back(compare_nocase_punc == 0);
// case-sensitive string comparison, ignoring punctuation
int compare_case_nopunc = CompareStrings(cube_best_str,
tess_str, true, false);
features->push_back(compare_case_nopunc == 0);
// case-insensitive string comparison, ignoring punctuation
int compare_nocase_nopunc = CompareStrings(cube_best_str,
tess_str, true, true);
features->push_back(compare_nocase_nopunc == 0);
return true;
}
// The CubeObject parameter is used for 2 purposes: 1) to retrieve
// cube's alt list, and 2) to compute cube's word cost for the
// tesseract result. The call to CubeObject::WordCost() modifies
// the object's alternate list, so previous state will be lost.
float TesseractCubeCombiner::CombineResults(WERD_RES *tess_res,
CubeObject *cube_obj) {
// If no combiner is loaded or the cube object is undefined,
// tesseract wins with probability 1.0
if (combiner_net_ == NULL || cube_obj == NULL) {
tprintf("Cube WARNING (TesseractCubeCombiner::CombineResults): "
"Cube objects not initialized; defaulting to Tesseract\n");
return 1.0;
}
// Retrieve the alternate list from the CubeObject's current state.
// If the alt list empty, tesseract wins with probability 1.0
WordAltList *cube_alt_list = cube_obj->AlternateList();
if (cube_alt_list == NULL)
cube_alt_list = cube_obj->RecognizeWord();
if (cube_alt_list == NULL || cube_alt_list->AltCount() <= 0) {
tprintf("Cube WARNING (TesseractCubeCombiner::CombineResults): "
"Cube returned no results; defaulting to Tesseract\n");
return 1.0;
}
return CombineResults(tess_res, cube_obj, cube_alt_list);
}
// The alt_list parameter is expected to have been extracted from the
// CubeObject that recognized the word to be combined. The cube_obj
// parameter passed may be either same instance or a separate instance to
// be used only by the combiner. In both cases, its alternate
// list will be modified by an internal call to RecognizeWord().
float TesseractCubeCombiner::CombineResults(WERD_RES *tess_res,
CubeObject *cube_obj,
WordAltList *cube_alt_list) {
// If no combiner is loaded or the cube object is undefined, or the
// alt list is empty, tesseract wins with probability 1.0
if (combiner_net_ == NULL || cube_obj == NULL ||
cube_alt_list == NULL || cube_alt_list->AltCount() <= 0) {
tprintf("Cube WARNING (TesseractCubeCombiner::CombineResults): "
"Cube result cannot be retrieved; defaulting to Tesseract\n");
return 1.0;
}
// Tesseract result string, tesseract confidence, and cost of
// tesseract result according to cube
string tess_str = tess_res->best_choice->unichar_string().string();
// Map certainty [-20.0, 0.0] to confidence [0, 100]
int tess_confidence = MIN(100, MAX(1, static_cast<int>(
100 + (5 * tess_res->best_choice->certainty()))));
// Compute the combiner features. If feature computation fails or
// answers are identical, tesseract wins with probability 1.0
vector<double> features;
bool agreement;
bool combiner_success = ComputeCombinerFeatures(tess_str, tess_confidence,
cube_obj, cube_alt_list,
&features, &agreement);
if (!combiner_success || agreement)
return 1.0;
// Classify combiner feature vector and return output (probability
// of tesseract class).
double net_out[2];
if (!combiner_net_->FeedForward(&features[0], net_out))
return 1.0;
return net_out[1];
}
}
| C++ |
/******************************************************************
* File: docqual.cpp (Formerly docqual.c)
* Description: Document Quality Metrics
* Author: Phil Cheatle
* Created: Mon May 9 11:27:28 BST 1994
*
* (C) Copyright 1994, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#endif
#include <ctype.h>
#include "docqual.h"
#include "reject.h"
#include "tesscallback.h"
#include "tessvars.h"
#include "globals.h"
#include "tesseractclass.h"
namespace tesseract{
// A little class to provide the callbacks as we have no pre-bound args.
struct DocQualCallbacks {
explicit DocQualCallbacks(WERD_RES* word0)
: word(word0), match_count(0), accepted_match_count(0) {}
void CountMatchingBlobs(int index) {
++match_count;
}
void CountAcceptedBlobs(int index) {
if (word->reject_map[index].accepted())
++accepted_match_count;
++match_count;
}
void AcceptIfGoodQuality(int index) {
if (word->reject_map[index].accept_if_good_quality())
word->reject_map[index].setrej_quality_accept();
}
WERD_RES* word;
inT16 match_count;
inT16 accepted_match_count;
};
/*************************************************************************
* word_blob_quality()
* How many blobs in the box_word are identical to those of the inword?
* ASSUME blobs in both initial word and box_word are in ascending order of
* left hand blob edge.
*************************************************************************/
inT16 Tesseract::word_blob_quality(WERD_RES *word, ROW *row) {
if (word->bln_boxes == NULL ||
word->rebuild_word == NULL || word->rebuild_word->blobs.empty())
return 0;
DocQualCallbacks cb(word);
word->bln_boxes->ProcessMatchedBlobs(
*word->rebuild_word,
NewPermanentTessCallback(&cb, &DocQualCallbacks::CountMatchingBlobs));
return cb.match_count;
}
inT16 Tesseract::word_outline_errs(WERD_RES *word) {
inT16 i = 0;
inT16 err_count = 0;
if (word->rebuild_word != NULL) {
for (int b = 0; b < word->rebuild_word->NumBlobs(); ++b) {
TBLOB* blob = word->rebuild_word->blobs[b];
err_count += count_outline_errs(word->best_choice->unichar_string()[i],
blob->NumOutlines());
i++;
}
}
return err_count;
}
/*************************************************************************
* word_char_quality()
* Combination of blob quality and outline quality - how many good chars are
* there? - I.e chars which pass the blob AND outline tests.
*************************************************************************/
void Tesseract::word_char_quality(WERD_RES *word,
ROW *row,
inT16 *match_count,
inT16 *accepted_match_count) {
if (word->bln_boxes == NULL ||
word->rebuild_word == NULL || word->rebuild_word->blobs.empty())
return;
DocQualCallbacks cb(word);
word->bln_boxes->ProcessMatchedBlobs(
*word->rebuild_word,
NewPermanentTessCallback(&cb, &DocQualCallbacks::CountAcceptedBlobs));
*match_count = cb.match_count;
*accepted_match_count = cb.accepted_match_count;
}
/*************************************************************************
* unrej_good_chs()
* Unreject POTENTIAL rejects if the blob passes the blob and outline checks
*************************************************************************/
void Tesseract::unrej_good_chs(WERD_RES *word, ROW *row) {
if (word->bln_boxes == NULL ||
word->rebuild_word == NULL || word->rebuild_word->blobs.empty())
return;
DocQualCallbacks cb(word);
word->bln_boxes->ProcessMatchedBlobs(
*word->rebuild_word,
NewPermanentTessCallback(&cb, &DocQualCallbacks::AcceptIfGoodQuality));
}
inT16 Tesseract::count_outline_errs(char c, inT16 outline_count) {
int expected_outline_count;
if (STRING (outlines_odd).contains (c))
return 0; //Dont use this char
else if (STRING (outlines_2).contains (c))
expected_outline_count = 2;
else
expected_outline_count = 1;
return abs (outline_count - expected_outline_count);
}
void Tesseract::quality_based_rejection(PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc) {
if ((tessedit_good_quality_unrej && good_quality_doc))
unrej_good_quality_words(page_res_it);
doc_and_block_rejection(page_res_it, good_quality_doc);
if (unlv_tilde_crunching) {
tilde_crunch(page_res_it);
tilde_delete(page_res_it);
}
}
/*************************************************************************
* unrej_good_quality_words()
* Accept potential rejects in words which pass the following checks:
* - Contains a potential reject
* - Word looks like a sensible alpha word.
* - Word segmentation is the same as the original image
* - All characters have the expected number of outlines
* NOTE - the rejection counts are recalculated after unrejection
* - CANT do it in a single pass without a bit of fiddling
* - keep it simple but inefficient
*************************************************************************/
void Tesseract::unrej_good_quality_words( //unreject potential
PAGE_RES_IT &page_res_it) {
WERD_RES *word;
ROW_RES *current_row;
BLOCK_RES *current_block;
int i;
page_res_it.restart_page ();
while (page_res_it.word () != NULL) {
check_debug_pt (page_res_it.word (), 100);
if (bland_unrej) {
word = page_res_it.word ();
for (i = 0; i < word->reject_map.length (); i++) {
if (word->reject_map[i].accept_if_good_quality ())
word->reject_map[i].setrej_quality_accept ();
}
page_res_it.forward ();
}
else if ((page_res_it.row ()->char_count > 0) &&
((page_res_it.row ()->rej_count /
(float) page_res_it.row ()->char_count) <=
quality_rowrej_pc)) {
word = page_res_it.word ();
if (word->reject_map.quality_recoverable_rejects() &&
(tessedit_unrej_any_wd ||
acceptable_word_string(*word->uch_set,
word->best_choice->unichar_string().string(),
word->best_choice->unichar_lengths().string())
!= AC_UNACCEPTABLE)) {
unrej_good_chs(word, page_res_it.row ()->row);
}
page_res_it.forward ();
}
else {
/* Skip to end of dodgy row */
current_row = page_res_it.row ();
while ((page_res_it.word () != NULL) &&
(page_res_it.row () == current_row))
page_res_it.forward ();
}
check_debug_pt (page_res_it.word (), 110);
}
page_res_it.restart_page ();
page_res_it.page_res->char_count = 0;
page_res_it.page_res->rej_count = 0;
current_block = NULL;
current_row = NULL;
while (page_res_it.word () != NULL) {
if (current_block != page_res_it.block ()) {
current_block = page_res_it.block ();
current_block->char_count = 0;
current_block->rej_count = 0;
}
if (current_row != page_res_it.row ()) {
current_row = page_res_it.row ();
current_row->char_count = 0;
current_row->rej_count = 0;
current_row->whole_word_rej_count = 0;
}
page_res_it.rej_stat_word ();
page_res_it.forward ();
}
}
/*************************************************************************
* doc_and_block_rejection()
*
* If the page has too many rejects - reject all of it.
* If any block has too many rejects - reject all words in the block
*************************************************************************/
void Tesseract::doc_and_block_rejection( //reject big chunks
PAGE_RES_IT &page_res_it,
BOOL8 good_quality_doc) {
inT16 block_no = 0;
inT16 row_no = 0;
BLOCK_RES *current_block;
ROW_RES *current_row;
BOOL8 rej_word;
BOOL8 prev_word_rejected;
inT16 char_quality = 0;
inT16 accepted_char_quality;
if (page_res_it.page_res->rej_count * 100.0 /
page_res_it.page_res->char_count > tessedit_reject_doc_percent) {
reject_whole_page(page_res_it);
if (tessedit_debug_doc_rejection) {
tprintf("REJECT ALL #chars: %d #Rejects: %d; \n",
page_res_it.page_res->char_count,
page_res_it.page_res->rej_count);
}
} else {
if (tessedit_debug_doc_rejection) {
tprintf("NO PAGE REJECTION #chars: %d # Rejects: %d; \n",
page_res_it.page_res->char_count,
page_res_it.page_res->rej_count);
}
/* Walk blocks testing for block rejection */
page_res_it.restart_page();
WERD_RES* word;
while ((word = page_res_it.word()) != NULL) {
current_block = page_res_it.block();
block_no = current_block->block->index();
if (current_block->char_count > 0 &&
(current_block->rej_count * 100.0 / current_block->char_count) >
tessedit_reject_block_percent) {
if (tessedit_debug_block_rejection) {
tprintf("REJECTING BLOCK %d #chars: %d; #Rejects: %d\n",
block_no, current_block->char_count,
current_block->rej_count);
}
prev_word_rejected = FALSE;
while ((word = page_res_it.word()) != NULL &&
(page_res_it.block() == current_block)) {
if (tessedit_preserve_blk_rej_perfect_wds) {
rej_word = word->reject_map.reject_count() > 0 ||
word->reject_map.length () < tessedit_preserve_min_wd_len;
if (rej_word && tessedit_dont_blkrej_good_wds &&
word->reject_map.length() >= tessedit_preserve_min_wd_len &&
acceptable_word_string(
*word->uch_set,
word->best_choice->unichar_string().string(),
word->best_choice->unichar_lengths().string()) !=
AC_UNACCEPTABLE) {
word_char_quality(word, page_res_it.row()->row,
&char_quality,
&accepted_char_quality);
rej_word = char_quality != word->reject_map.length();
}
} else {
rej_word = TRUE;
}
if (rej_word) {
/*
Reject spacing if both current and prev words are rejected.
NOTE - this is NOT restricted to FUZZY spaces. - When tried this
generated more space errors.
*/
if (tessedit_use_reject_spaces &&
prev_word_rejected &&
page_res_it.prev_row() == page_res_it.row() &&
word->word->space() == 1)
word->reject_spaces = TRUE;
word->reject_map.rej_word_block_rej();
}
prev_word_rejected = rej_word;
page_res_it.forward();
}
} else {
if (tessedit_debug_block_rejection) {
tprintf("NOT REJECTING BLOCK %d #chars: %d # Rejects: %d; \n",
block_no, page_res_it.block()->char_count,
page_res_it.block()->rej_count);
}
/* Walk rows in block testing for row rejection */
row_no = 0;
while (page_res_it.word() != NULL &&
page_res_it.block() == current_block) {
current_row = page_res_it.row();
row_no++;
/* Reject whole row if:
fraction of chars on row which are rejected exceed a limit AND
fraction rejects which occur in WHOLE WERD rejects is LESS THAN a
limit
*/
if (current_row->char_count > 0 &&
(current_row->rej_count * 100.0 / current_row->char_count) >
tessedit_reject_row_percent &&
(current_row->whole_word_rej_count * 100.0 /
current_row->rej_count) <
tessedit_whole_wd_rej_row_percent) {
if (tessedit_debug_block_rejection) {
tprintf("REJECTING ROW %d #chars: %d; #Rejects: %d\n",
row_no, current_row->char_count,
current_row->rej_count);
}
prev_word_rejected = FALSE;
while ((word = page_res_it.word()) != NULL &&
page_res_it.row () == current_row) {
/* Preserve words on good docs unless they are mostly rejected*/
if (!tessedit_row_rej_good_docs && good_quality_doc) {
rej_word = word->reject_map.reject_count() /
static_cast<float>(word->reject_map.length()) >
tessedit_good_doc_still_rowrej_wd;
} else if (tessedit_preserve_row_rej_perfect_wds) {
/* Preserve perfect words anyway */
rej_word = word->reject_map.reject_count() > 0 ||
word->reject_map.length () < tessedit_preserve_min_wd_len;
if (rej_word && tessedit_dont_rowrej_good_wds &&
word->reject_map.length() >= tessedit_preserve_min_wd_len &&
acceptable_word_string(*word->uch_set,
word->best_choice->unichar_string().string(),
word->best_choice->unichar_lengths().string()) !=
AC_UNACCEPTABLE) {
word_char_quality(word, page_res_it.row()->row,
&char_quality,
&accepted_char_quality);
rej_word = char_quality != word->reject_map.length();
}
} else {
rej_word = TRUE;
}
if (rej_word) {
/*
Reject spacing if both current and prev words are rejected.
NOTE - this is NOT restricted to FUZZY spaces. - When tried
this generated more space errors.
*/
if (tessedit_use_reject_spaces &&
prev_word_rejected &&
page_res_it.prev_row() == page_res_it.row() &&
word->word->space () == 1)
word->reject_spaces = TRUE;
word->reject_map.rej_word_row_rej();
}
prev_word_rejected = rej_word;
page_res_it.forward();
}
} else {
if (tessedit_debug_block_rejection) {
tprintf("NOT REJECTING ROW %d #chars: %d # Rejects: %d; \n",
row_no, current_row->char_count, current_row->rej_count);
}
while (page_res_it.word() != NULL &&
page_res_it.row() == current_row)
page_res_it.forward();
}
}
}
}
}
}
} // namespace tesseract
/*************************************************************************
* reject_whole_page()
* Dont believe any of it - set the reject map to 00..00 in all words
*
*************************************************************************/
void reject_whole_page(PAGE_RES_IT &page_res_it) {
page_res_it.restart_page ();
while (page_res_it.word () != NULL) {
page_res_it.word ()->reject_map.rej_word_doc_rej ();
page_res_it.forward ();
}
//whole page is rejected
page_res_it.page_res->rejected = TRUE;
}
namespace tesseract {
void Tesseract::tilde_crunch(PAGE_RES_IT &page_res_it) {
WERD_RES *word;
GARBAGE_LEVEL garbage_level;
PAGE_RES_IT copy_it;
BOOL8 prev_potential_marked = FALSE;
BOOL8 found_terrible_word = FALSE;
BOOL8 ok_dict_word;
page_res_it.restart_page();
while (page_res_it.word() != NULL) {
POLY_BLOCK* pb = page_res_it.block()->block->poly_block();
if (pb != NULL && !pb->IsText()) {
page_res_it.forward();
continue;
}
word = page_res_it.word();
if (crunch_early_convert_bad_unlv_chs)
convert_bad_unlv_chs(word);
if (crunch_early_merge_tess_fails)
word->merge_tess_fails();
if (word->reject_map.accept_count () != 0) {
found_terrible_word = FALSE;
//Forget earlier potential crunches
prev_potential_marked = FALSE;
}
else {
ok_dict_word = safe_dict_word(word);
garbage_level = garbage_word (word, ok_dict_word);
if ((garbage_level != G_NEVER_CRUNCH) &&
(terrible_word_crunch (word, garbage_level))) {
if (crunch_debug > 0) {
tprintf ("T CRUNCHING: \"%s\"\n",
word->best_choice->unichar_string().string());
}
word->unlv_crunch_mode = CR_KEEP_SPACE;
if (prev_potential_marked) {
while (copy_it.word () != word) {
if (crunch_debug > 0) {
tprintf ("P1 CRUNCHING: \"%s\"\n",
copy_it.word()->best_choice->unichar_string().string());
}
copy_it.word ()->unlv_crunch_mode = CR_KEEP_SPACE;
copy_it.forward ();
}
prev_potential_marked = FALSE;
}
found_terrible_word = TRUE;
}
else if ((garbage_level != G_NEVER_CRUNCH) &&
(potential_word_crunch (word,
garbage_level, ok_dict_word))) {
if (found_terrible_word) {
if (crunch_debug > 0) {
tprintf ("P2 CRUNCHING: \"%s\"\n",
word->best_choice->unichar_string().string());
}
word->unlv_crunch_mode = CR_KEEP_SPACE;
}
else if (!prev_potential_marked) {
copy_it = page_res_it;
prev_potential_marked = TRUE;
if (crunch_debug > 1) {
tprintf ("P3 CRUNCHING: \"%s\"\n",
word->best_choice->unichar_string().string());
}
}
}
else {
found_terrible_word = FALSE;
//Forget earlier potential crunches
prev_potential_marked = FALSE;
if (crunch_debug > 2) {
tprintf ("NO CRUNCH: \"%s\"\n",
word->best_choice->unichar_string().string());
}
}
}
page_res_it.forward ();
}
}
BOOL8 Tesseract::terrible_word_crunch(WERD_RES *word,
GARBAGE_LEVEL garbage_level) {
float rating_per_ch;
int adjusted_len;
int crunch_mode = 0;
if ((word->best_choice->unichar_string().length () == 0) ||
(strspn (word->best_choice->unichar_string().string(), " ") ==
word->best_choice->unichar_string().length ()))
crunch_mode = 1;
else {
adjusted_len = word->reject_map.length ();
if (adjusted_len > crunch_rating_max)
adjusted_len = crunch_rating_max;
rating_per_ch = word->best_choice->rating () / adjusted_len;
if (rating_per_ch > crunch_terrible_rating)
crunch_mode = 2;
else if (crunch_terrible_garbage && (garbage_level == G_TERRIBLE))
crunch_mode = 3;
else if ((word->best_choice->certainty () < crunch_poor_garbage_cert) &&
(garbage_level != G_OK))
crunch_mode = 4;
else if ((rating_per_ch > crunch_poor_garbage_rate) &&
(garbage_level != G_OK))
crunch_mode = 5;
}
if (crunch_mode > 0) {
if (crunch_debug > 2) {
tprintf ("Terrible_word_crunch (%d) on \"%s\"\n",
crunch_mode, word->best_choice->unichar_string().string());
}
return TRUE;
}
else
return FALSE;
}
BOOL8 Tesseract::potential_word_crunch(WERD_RES *word,
GARBAGE_LEVEL garbage_level,
BOOL8 ok_dict_word) {
float rating_per_ch;
int adjusted_len;
const char *str = word->best_choice->unichar_string().string();
const char *lengths = word->best_choice->unichar_lengths().string();
BOOL8 word_crunchable;
int poor_indicator_count = 0;
word_crunchable = !crunch_leave_accept_strings ||
word->reject_map.length() < 3 ||
(acceptable_word_string(*word->uch_set,
str, lengths) == AC_UNACCEPTABLE &&
!ok_dict_word);
adjusted_len = word->reject_map.length();
if (adjusted_len > 10)
adjusted_len = 10;
rating_per_ch = word->best_choice->rating() / adjusted_len;
if (rating_per_ch > crunch_pot_poor_rate) {
if (crunch_debug > 2) {
tprintf("Potential poor rating on \"%s\"\n",
word->best_choice->unichar_string().string());
}
poor_indicator_count++;
}
if (word_crunchable &&
word->best_choice->certainty() < crunch_pot_poor_cert) {
if (crunch_debug > 2) {
tprintf("Potential poor cert on \"%s\"\n",
word->best_choice->unichar_string().string());
}
poor_indicator_count++;
}
if (garbage_level != G_OK) {
if (crunch_debug > 2) {
tprintf("Potential garbage on \"%s\"\n",
word->best_choice->unichar_string().string());
}
poor_indicator_count++;
}
return poor_indicator_count >= crunch_pot_indicators;
}
void Tesseract::tilde_delete(PAGE_RES_IT &page_res_it) {
WERD_RES *word;
PAGE_RES_IT copy_it;
BOOL8 deleting_from_bol = FALSE;
BOOL8 marked_delete_point = FALSE;
inT16 debug_delete_mode;
CRUNCH_MODE delete_mode;
inT16 x_debug_delete_mode;
CRUNCH_MODE x_delete_mode;
page_res_it.restart_page();
while (page_res_it.word() != NULL) {
word = page_res_it.word();
delete_mode = word_deletable (word, debug_delete_mode);
if (delete_mode != CR_NONE) {
if (word->word->flag (W_BOL) || deleting_from_bol) {
if (crunch_debug > 0) {
tprintf ("BOL CRUNCH DELETING(%d): \"%s\"\n",
debug_delete_mode,
word->best_choice->unichar_string().string());
}
word->unlv_crunch_mode = delete_mode;
deleting_from_bol = TRUE;
} else if (word->word->flag(W_EOL)) {
if (marked_delete_point) {
while (copy_it.word() != word) {
x_delete_mode = word_deletable (copy_it.word (),
x_debug_delete_mode);
if (crunch_debug > 0) {
tprintf ("EOL CRUNCH DELETING(%d): \"%s\"\n",
x_debug_delete_mode,
copy_it.word()->best_choice->unichar_string().string());
}
copy_it.word ()->unlv_crunch_mode = x_delete_mode;
copy_it.forward ();
}
}
if (crunch_debug > 0) {
tprintf ("EOL CRUNCH DELETING(%d): \"%s\"\n",
debug_delete_mode,
word->best_choice->unichar_string().string());
}
word->unlv_crunch_mode = delete_mode;
deleting_from_bol = FALSE;
marked_delete_point = FALSE;
}
else {
if (!marked_delete_point) {
copy_it = page_res_it;
marked_delete_point = TRUE;
}
}
}
else {
deleting_from_bol = FALSE;
//Forget earlier potential crunches
marked_delete_point = FALSE;
}
/*
The following step has been left till now as the tess fails are used to
determine if the word is deletable.
*/
if (!crunch_early_merge_tess_fails)
word->merge_tess_fails();
page_res_it.forward ();
}
}
void Tesseract::convert_bad_unlv_chs(WERD_RES *word_res) {
int i;
UNICHAR_ID unichar_dash = word_res->uch_set->unichar_to_id("-");
UNICHAR_ID unichar_space = word_res->uch_set->unichar_to_id(" ");
UNICHAR_ID unichar_tilde = word_res->uch_set->unichar_to_id("~");
UNICHAR_ID unichar_pow = word_res->uch_set->unichar_to_id("^");
for (i = 0; i < word_res->reject_map.length(); ++i) {
if (word_res->best_choice->unichar_id(i) == unichar_tilde) {
word_res->best_choice->set_unichar_id(unichar_dash, i);
if (word_res->reject_map[i].accepted ())
word_res->reject_map[i].setrej_unlv_rej ();
}
if (word_res->best_choice->unichar_id(i) == unichar_pow) {
word_res->best_choice->set_unichar_id(unichar_space, i);
if (word_res->reject_map[i].accepted ())
word_res->reject_map[i].setrej_unlv_rej ();
}
}
}
GARBAGE_LEVEL Tesseract::garbage_word(WERD_RES *word, BOOL8 ok_dict_word) {
enum STATES
{
JUNK,
FIRST_UPPER,
FIRST_LOWER,
FIRST_NUM,
SUBSEQUENT_UPPER,
SUBSEQUENT_LOWER,
SUBSEQUENT_NUM
};
const char *str = word->best_choice->unichar_string().string();
const char *lengths = word->best_choice->unichar_lengths().string();
STATES state = JUNK;
int len = 0;
int isolated_digits = 0;
int isolated_alphas = 0;
int bad_char_count = 0;
int tess_rejs = 0;
int dodgy_chars = 0;
int ok_chars;
UNICHAR_ID last_char = -1;
int alpha_repetition_count = 0;
int longest_alpha_repetition_count = 0;
int longest_lower_run_len = 0;
int lower_string_count = 0;
int longest_upper_run_len = 0;
int upper_string_count = 0;
int total_alpha_count = 0;
int total_digit_count = 0;
for (; *str != '\0'; str += *(lengths++)) {
len++;
if (word->uch_set->get_isupper (str, *lengths)) {
total_alpha_count++;
switch (state) {
case SUBSEQUENT_UPPER:
case FIRST_UPPER:
state = SUBSEQUENT_UPPER;
upper_string_count++;
if (longest_upper_run_len < upper_string_count)
longest_upper_run_len = upper_string_count;
if (last_char == word->uch_set->unichar_to_id(str, *lengths)) {
alpha_repetition_count++;
if (longest_alpha_repetition_count < alpha_repetition_count) {
longest_alpha_repetition_count = alpha_repetition_count;
}
}
else {
last_char = word->uch_set->unichar_to_id(str, *lengths);
alpha_repetition_count = 1;
}
break;
case FIRST_NUM:
isolated_digits++;
default:
state = FIRST_UPPER;
last_char = word->uch_set->unichar_to_id(str, *lengths);
alpha_repetition_count = 1;
upper_string_count = 1;
break;
}
}
else if (word->uch_set->get_islower (str, *lengths)) {
total_alpha_count++;
switch (state) {
case SUBSEQUENT_LOWER:
case FIRST_LOWER:
state = SUBSEQUENT_LOWER;
lower_string_count++;
if (longest_lower_run_len < lower_string_count)
longest_lower_run_len = lower_string_count;
if (last_char == word->uch_set->unichar_to_id(str, *lengths)) {
alpha_repetition_count++;
if (longest_alpha_repetition_count < alpha_repetition_count) {
longest_alpha_repetition_count = alpha_repetition_count;
}
}
else {
last_char = word->uch_set->unichar_to_id(str, *lengths);
alpha_repetition_count = 1;
}
break;
case FIRST_NUM:
isolated_digits++;
default:
state = FIRST_LOWER;
last_char = word->uch_set->unichar_to_id(str, *lengths);
alpha_repetition_count = 1;
lower_string_count = 1;
break;
}
}
else if (word->uch_set->get_isdigit (str, *lengths)) {
total_digit_count++;
switch (state) {
case FIRST_NUM:
state = SUBSEQUENT_NUM;
case SUBSEQUENT_NUM:
break;
case FIRST_UPPER:
case FIRST_LOWER:
isolated_alphas++;
default:
state = FIRST_NUM;
break;
}
}
else {
if (*lengths == 1 && *str == ' ')
tess_rejs++;
else
bad_char_count++;
switch (state) {
case FIRST_NUM:
isolated_digits++;
break;
case FIRST_UPPER:
case FIRST_LOWER:
isolated_alphas++;
default:
break;
}
state = JUNK;
}
}
switch (state) {
case FIRST_NUM:
isolated_digits++;
break;
case FIRST_UPPER:
case FIRST_LOWER:
isolated_alphas++;
default:
break;
}
if (crunch_include_numerals) {
total_alpha_count += total_digit_count - isolated_digits;
}
if (crunch_leave_ok_strings && len >= 4 &&
2 * (total_alpha_count - isolated_alphas) > len &&
longest_alpha_repetition_count < crunch_long_repetitions) {
if ((crunch_accept_ok &&
acceptable_word_string(*word->uch_set, str, lengths) !=
AC_UNACCEPTABLE) ||
longest_lower_run_len > crunch_leave_lc_strings ||
longest_upper_run_len > crunch_leave_uc_strings)
return G_NEVER_CRUNCH;
}
if (word->reject_map.length() > 1 &&
strpbrk(str, " ") == NULL &&
(word->best_choice->permuter() == SYSTEM_DAWG_PERM ||
word->best_choice->permuter() == FREQ_DAWG_PERM ||
word->best_choice->permuter() == USER_DAWG_PERM ||
word->best_choice->permuter() == NUMBER_PERM ||
acceptable_word_string(*word->uch_set, str, lengths) !=
AC_UNACCEPTABLE || ok_dict_word))
return G_OK;
ok_chars = len - bad_char_count - isolated_digits -
isolated_alphas - tess_rejs;
if (crunch_debug > 3) {
tprintf("garbage_word: \"%s\"\n",
word->best_choice->unichar_string().string());
tprintf("LEN: %d bad: %d iso_N: %d iso_A: %d rej: %d\n",
len,
bad_char_count, isolated_digits, isolated_alphas, tess_rejs);
}
if (bad_char_count == 0 &&
tess_rejs == 0 &&
(len > isolated_digits + isolated_alphas || len <= 2))
return G_OK;
if (tess_rejs > ok_chars ||
(tess_rejs > 0 && (bad_char_count + tess_rejs) * 2 > len))
return G_TERRIBLE;
if (len > 4) {
dodgy_chars = 2 * tess_rejs + bad_char_count + isolated_digits +
isolated_alphas;
if (dodgy_chars > 5 || (dodgy_chars / (float) len) > 0.5)
return G_DODGY;
else
return G_OK;
} else {
dodgy_chars = 2 * tess_rejs + bad_char_count;
if ((len == 4 && dodgy_chars > 2) ||
(len == 3 && dodgy_chars > 2) || dodgy_chars >= len)
return G_DODGY;
else
return G_OK;
}
}
/*************************************************************************
* word_deletable()
* DELETE WERDS AT ENDS OF ROWS IF
* Word is crunched &&
* ( string length = 0 OR
* > 50% of chars are "|" (before merging) OR
* certainty < -10 OR
* rating /char > 60 OR
* TOP of word is more than 0.5 xht BELOW baseline OR
* BOTTOM of word is more than 0.5 xht ABOVE xht OR
* length of word < 3xht OR
* height of word < 0.7 xht OR
* height of word > 3.0 xht OR
* >75% of the outline BBs have longest dimension < 0.5xht
*************************************************************************/
CRUNCH_MODE Tesseract::word_deletable(WERD_RES *word, inT16 &delete_mode) {
int word_len = word->reject_map.length ();
float rating_per_ch;
TBOX box; //BB of word
if (word->unlv_crunch_mode == CR_NONE) {
delete_mode = 0;
return CR_NONE;
}
if (word_len == 0) {
delete_mode = 1;
return CR_DELETE;
}
if (word->rebuild_word != NULL) {
// Cube leaves rebuild_word NULL.
box = word->rebuild_word->bounding_box();
if (box.height () < crunch_del_min_ht * kBlnXHeight) {
delete_mode = 4;
return CR_DELETE;
}
if (noise_outlines(word->rebuild_word)) {
delete_mode = 5;
return CR_DELETE;
}
}
if ((failure_count (word) * 1.5) > word_len) {
delete_mode = 2;
return CR_LOOSE_SPACE;
}
if (word->best_choice->certainty () < crunch_del_cert) {
delete_mode = 7;
return CR_LOOSE_SPACE;
}
rating_per_ch = word->best_choice->rating () / word_len;
if (rating_per_ch > crunch_del_rating) {
delete_mode = 8;
return CR_LOOSE_SPACE;
}
if (box.top () < kBlnBaselineOffset - crunch_del_low_word * kBlnXHeight) {
delete_mode = 9;
return CR_LOOSE_SPACE;
}
if (box.bottom () >
kBlnBaselineOffset + crunch_del_high_word * kBlnXHeight) {
delete_mode = 10;
return CR_LOOSE_SPACE;
}
if (box.height () > crunch_del_max_ht * kBlnXHeight) {
delete_mode = 11;
return CR_LOOSE_SPACE;
}
if (box.width () < crunch_del_min_width * kBlnXHeight) {
delete_mode = 3;
return CR_LOOSE_SPACE;
}
delete_mode = 0;
return CR_NONE;
}
inT16 Tesseract::failure_count(WERD_RES *word) {
const char *str = word->best_choice->unichar_string().string();
int tess_rejs = 0;
for (; *str != '\0'; str++) {
if (*str == ' ')
tess_rejs++;
}
return tess_rejs;
}
BOOL8 Tesseract::noise_outlines(TWERD *word) {
TBOX box; // BB of outline
inT16 outline_count = 0;
inT16 small_outline_count = 0;
inT16 max_dimension;
float small_limit = kBlnXHeight * crunch_small_outlines_size;
for (int b = 0; b < word->NumBlobs(); ++b) {
TBLOB* blob = word->blobs[b];
for (TESSLINE* ol = blob->outlines; ol != NULL; ol = ol->next) {
outline_count++;
box = ol->bounding_box();
if (box.height() > box.width())
max_dimension = box.height();
else
max_dimension = box.width();
if (max_dimension < small_limit)
small_outline_count++;
}
}
return small_outline_count >= outline_count;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: tesseract_cube_combiner.h
* Description: Declaration of the Tesseract & Cube results combiner Class
* Author: Ahmad Abdulkader
* Created: 2008
*
* (C) Copyright 2008, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
// The TesseractCubeCombiner class provides the functionality of combining
// the recognition results of Tesseract and Cube at the word level
#ifndef TESSERACT_CCMAIN_TESSERACT_CUBE_COMBINER_H
#define TESSERACT_CCMAIN_TESSERACT_CUBE_COMBINER_H
#include <string>
#include <vector>
#include "pageres.h"
#ifdef _WIN32
#include <windows.h>
using namespace std;
#endif
#ifdef USE_STD_NAMESPACE
using std::string;
using std::vector;
#endif
namespace tesseract {
class CubeObject;
class NeuralNet;
class CubeRecoContext;
class WordAltList;
class TesseractCubeCombiner {
public:
explicit TesseractCubeCombiner(CubeRecoContext *cube_cntxt);
virtual ~TesseractCubeCombiner();
// There are 2 public methods for combining the results of tesseract
// and cube. Both return the probability that the Tesseract result is
// correct. The difference between the two interfaces is in how the
// passed-in CubeObject is used.
// The CubeObject parameter is used for 2 purposes: 1) to retrieve
// cube's alt list, and 2) to compute cube's word cost for the
// tesseract result. Both uses may modify the state of the
// CubeObject (including the BeamSearch state) with a call to
// RecognizeWord().
float CombineResults(WERD_RES *tess_res, CubeObject *cube_obj);
// The alt_list parameter is expected to have been extracted from the
// CubeObject that recognized the word to be combined. The cube_obj
// parameter passed in is a separate instance to be used only by
// the combiner.
float CombineResults(WERD_RES *tess_res, CubeObject *cube_obj,
WordAltList *alt_list);
// Public method for computing the combiner features. The agreement
// output parameter will be true if both answers are identical,
// false otherwise. Modifies the cube_alt_list, so no assumptions
// should be made about its state upon return.
bool ComputeCombinerFeatures(const string &tess_res,
int tess_confidence,
CubeObject *cube_obj,
WordAltList *cube_alt_list,
vector<double> *features,
bool *agreement);
// Is the word valid according to Tesseract's language model
bool ValidWord(const string &str);
// Loads the combiner neural network from file, using cube_cntxt_
// to find path.
bool LoadCombinerNet();
private:
// Normalize a UTF-8 string. Converts the UTF-8 string to UTF32 and optionally
// strips punc and/or normalizes case and then converts back
string NormalizeString(const string &str, bool remove_punc, bool norm_case);
// Compares 2 strings after optionally normalizing them and or stripping
// punctuation
int CompareStrings(const string &str1, const string &str2, bool ignore_punc,
bool norm_case);
NeuralNet *combiner_net_; // pointer to the combiner NeuralNet object
CubeRecoContext *cube_cntxt_; // used for language ID and data paths
};
}
#endif // TESSERACT_CCMAIN_TESSERACT_CUBE_COMBINER_H
| C++ |
/**********************************************************************
* File: paragraphs.cpp
* Description: Paragraph detection for tesseract.
* Author: David Eger
* Created: 25 February 2011
*
* (C) Copyright 2011, Google Inc.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#define __func__ __FUNCTION__
#endif
#include <ctype.h>
#include "genericvector.h"
#include "helpers.h"
#include "mutableiterator.h"
#include "ocrpara.h"
#include "pageres.h"
#include "paragraphs.h"
#include "paragraphs_internal.h"
#include "publictypes.h"
#include "ratngs.h"
#include "rect.h"
#include "statistc.h"
#include "strngs.h"
#include "tprintf.h"
#include "unicharset.h"
#include "unicodes.h"
namespace tesseract {
// Special "weak" ParagraphModels.
const ParagraphModel *kCrownLeft
= reinterpret_cast<ParagraphModel *>(0xDEAD111F);
const ParagraphModel *kCrownRight
= reinterpret_cast<ParagraphModel *>(0xDEAD888F);
// Given the width of a typical space between words, what is the threshold
// by which by which we think left and right alignments for paragraphs
// can vary and still be aligned.
static int Epsilon(int space_pix) {
return space_pix * 4 / 5;
}
static bool AcceptableRowArgs(
int debug_level, int min_num_rows, const char *function_name,
const GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end) {
if (row_start < 0 || row_end > rows->size() || row_start > row_end) {
tprintf("Invalid arguments rows[%d, %d) while rows is of size %d.\n",
row_start, row_end, rows->size());
return false;
}
if (row_end - row_start < min_num_rows) {
if (debug_level > 1) {
tprintf("# Too few rows[%d, %d) for %s.\n",
row_start, row_end, function_name);
}
return false;
}
return true;
}
// =============================== Debug Code ================================
// Convert an integer to a decimal string.
static STRING StrOf(int num) {
char buffer[30];
snprintf(buffer, sizeof(buffer), "%d", num);
return STRING(buffer);
}
// Given a row-major matrix of unicode text and a column separator, print
// a formatted table. For ASCII, we get good column alignment.
static void PrintTable(const GenericVector<GenericVector<STRING> > &rows,
const STRING &colsep) {
GenericVector<int> max_col_widths;
for (int r = 0; r < rows.size(); r++) {
int num_columns = rows[r].size();
for (int c = 0; c < num_columns; c++) {
int num_unicodes = 0;
for (int i = 0; i < rows[r][c].size(); i++) {
if ((rows[r][c][i] & 0xC0) != 0x80) num_unicodes++;
}
if (c >= max_col_widths.size()) {
max_col_widths.push_back(num_unicodes);
} else {
if (num_unicodes > max_col_widths[c])
max_col_widths[c] = num_unicodes;
}
}
}
GenericVector<STRING> col_width_patterns;
for (int c = 0; c < max_col_widths.size(); c++) {
col_width_patterns.push_back(
STRING("%-") + StrOf(max_col_widths[c]) + "s");
}
for (int r = 0; r < rows.size(); r++) {
for (int c = 0; c < rows[r].size(); c++) {
if (c > 0)
tprintf("%s", colsep.string());
tprintf(col_width_patterns[c].string(), rows[r][c].string());
}
tprintf("\n");
}
}
STRING RtlEmbed(const STRING &word, bool rtlify) {
if (rtlify)
return STRING(kRLE) + word + STRING(kPDF);
return word;
}
// Print the current thoughts of the paragraph detector.
static void PrintDetectorState(const ParagraphTheory &theory,
const GenericVector<RowScratchRegisters> &rows) {
GenericVector<GenericVector<STRING> > output;
output.push_back(GenericVector<STRING>());
output.back().push_back("#row");
output.back().push_back("space");
output.back().push_back("..");
output.back().push_back("lword[widthSEL]");
output.back().push_back("rword[widthSEL]");
RowScratchRegisters::AppendDebugHeaderFields(&output.back());
output.back().push_back("text");
for (int i = 0; i < rows.size(); i++) {
output.push_back(GenericVector<STRING>());
GenericVector<STRING> &row = output.back();
const RowInfo& ri = *rows[i].ri_;
row.push_back(StrOf(i));
row.push_back(StrOf(ri.average_interword_space));
row.push_back(ri.has_leaders ? ".." : " ");
row.push_back(RtlEmbed(ri.lword_text, !ri.ltr) +
"[" + StrOf(ri.lword_box.width()) +
(ri.lword_likely_starts_idea ? "S" : "s") +
(ri.lword_likely_ends_idea ? "E" : "e") +
(ri.lword_indicates_list_item ? "L" : "l") +
"]");
row.push_back(RtlEmbed(ri.rword_text, !ri.ltr) +
"[" + StrOf(ri.rword_box.width()) +
(ri.rword_likely_starts_idea ? "S" : "s") +
(ri.rword_likely_ends_idea ? "E" : "e") +
(ri.rword_indicates_list_item ? "L" : "l") +
"]");
rows[i].AppendDebugInfo(theory, &row);
row.push_back(RtlEmbed(ri.text, !ri.ltr));
}
PrintTable(output, " ");
tprintf("Active Paragraph Models:\n");
for (int m = 0; m < theory.models().size(); m++) {
tprintf(" %d: %s\n", m + 1, theory.models()[m]->ToString().string());
}
}
static void DebugDump(
bool should_print,
const STRING &phase,
const ParagraphTheory &theory,
const GenericVector<RowScratchRegisters> &rows) {
if (!should_print)
return;
tprintf("# %s\n", phase.string());
PrintDetectorState(theory, rows);
}
// Print out the text for rows[row_start, row_end)
static void PrintRowRange(const GenericVector<RowScratchRegisters> &rows,
int row_start, int row_end) {
tprintf("======================================\n");
for (int row = row_start; row < row_end; row++) {
tprintf("%s\n", rows[row].ri_->text.string());
}
tprintf("======================================\n");
}
// ============= Brain Dead Language Model (ASCII Version) ===================
bool IsLatinLetter(int ch) {
return (ch >= 'a' && ch <= 'z') || (ch >= 'A' && ch <= 'Z');
}
bool IsDigitLike(int ch) {
return ch == 'o' || ch == 'O' || ch == 'l' || ch == 'I';
}
bool IsOpeningPunct(int ch) {
return strchr("'\"({[", ch) != NULL;
}
bool IsTerminalPunct(int ch) {
return strchr(":'\".?!]})", ch) != NULL;
}
// Return a pointer after consuming as much text as qualifies as roman numeral.
const char *SkipChars(const char *str, const char *toskip) {
while (*str != '\0' && strchr(toskip, *str)) { str++; }
return str;
}
const char *SkipChars(const char *str, bool (*skip)(int)) {
while (*str != '\0' && skip(*str)) { str++; }
return str;
}
const char *SkipOne(const char *str, const char *toskip) {
if (*str != '\0' && strchr(toskip, *str)) return str + 1;
return str;
}
// Return whether it is very likely that this is a numeral marker that could
// start a list item. Some examples include:
// A I iii. VI (2) 3.5. [C-4]
bool LikelyListNumeral(const STRING &word) {
const char *kRomans = "ivxlmdIVXLMD";
const char *kDigits = "012345789";
const char *kOpen = "[{(";
const char *kSep = ":;-.,";
const char *kClose = "]})";
int num_segments = 0;
const char *pos = word.string();
while (*pos != '\0' && num_segments < 3) {
// skip up to two open parens.
const char *numeral_start = SkipOne(SkipOne(pos, kOpen), kOpen);
const char *numeral_end = SkipChars(numeral_start, kRomans);
if (numeral_end != numeral_start) {
// Got Roman Numeral. Great.
} else {
numeral_end = SkipChars(numeral_start, kDigits);
if (numeral_end == numeral_start) {
// If there's a single latin letter, we can use that.
numeral_end = SkipChars(numeral_start, IsLatinLetter);
if (numeral_end - numeral_start != 1)
break;
}
}
// We got some sort of numeral.
num_segments++;
// Skip any trailing parens or punctuation.
pos = SkipChars(SkipChars(numeral_end, kClose), kSep);
if (pos == numeral_end)
break;
}
return *pos == '\0';
}
bool LikelyListMark(const STRING &word) {
const char *kListMarks = "0Oo*.,+.";
return word.size() == 1 && strchr(kListMarks, word[0]) != NULL;
}
bool AsciiLikelyListItem(const STRING &word) {
return LikelyListMark(word) || LikelyListNumeral(word);
}
// ========== Brain Dead Language Model (Tesseract Version) ================
// Return the first Unicode Codepoint from werd[pos].
int UnicodeFor(const UNICHARSET *u, const WERD_CHOICE *werd, int pos) {
if (!u || !werd || pos > werd->length())
return 0;
return UNICHAR(u->id_to_unichar(werd->unichar_id(pos)), -1).first_uni();
}
// A useful helper class for finding the first j >= i so that word[j]
// does not have given character type.
class UnicodeSpanSkipper {
public:
UnicodeSpanSkipper(const UNICHARSET *unicharset, const WERD_CHOICE *word)
: u_(unicharset), word_(word) { wordlen_ = word->length(); }
// Given an input position, return the first position >= pos not punc.
int SkipPunc(int pos);
// Given an input position, return the first position >= pos not digit.
int SkipDigits(int pos);
// Given an input position, return the first position >= pos not roman.
int SkipRomans(int pos);
// Given an input position, return the first position >= pos not alpha.
int SkipAlpha(int pos);
private:
const UNICHARSET *u_;
const WERD_CHOICE *word_;
int wordlen_;
};
int UnicodeSpanSkipper::SkipPunc(int pos) {
while (pos < wordlen_ && u_->get_ispunctuation(word_->unichar_id(pos))) pos++;
return pos;
}
int UnicodeSpanSkipper::SkipDigits(int pos) {
while (pos < wordlen_ && (u_->get_isdigit(word_->unichar_id(pos)) ||
IsDigitLike(UnicodeFor(u_, word_, pos)))) pos++;
return pos;
}
int UnicodeSpanSkipper::SkipRomans(int pos) {
const char *kRomans = "ivxlmdIVXLMD";
while (pos < wordlen_) {
int ch = UnicodeFor(u_, word_, pos);
if (ch >= 0xF0 || strchr(kRomans, ch) == 0) break;
pos++;
}
return pos;
}
int UnicodeSpanSkipper::SkipAlpha(int pos) {
while (pos < wordlen_ && u_->get_isalpha(word_->unichar_id(pos))) pos++;
return pos;
}
bool LikelyListMarkUnicode(int ch) {
if (ch < 0x80) {
STRING single_ch;
single_ch += ch;
return LikelyListMark(single_ch);
}
switch (ch) {
// TODO(eger) expand this list of unicodes as needed.
case 0x00B0: // degree sign
case 0x2022: // bullet
case 0x25E6: // white bullet
case 0x00B7: // middle dot
case 0x25A1: // white square
case 0x25A0: // black square
case 0x25AA: // black small square
case 0x2B1D: // black very small square
case 0x25BA: // black right-pointing pointer
case 0x25CF: // black circle
case 0x25CB: // white circle
return true;
default:
break; // fall through
}
return false;
}
// Return whether it is very likely that this is a numeral marker that could
// start a list item. Some examples include:
// A I iii. VI (2) 3.5. [C-4]
bool UniLikelyListItem(const UNICHARSET *u, const WERD_CHOICE *werd) {
if (werd->length() == 1 && LikelyListMarkUnicode(UnicodeFor(u, werd, 0)))
return true;
UnicodeSpanSkipper m(u, werd);
int num_segments = 0;
int pos = 0;
while (pos < werd->length() && num_segments < 3) {
int numeral_start = m.SkipPunc(pos);
if (numeral_start > pos + 1) break;
int numeral_end = m.SkipRomans(numeral_start);
if (numeral_end == numeral_start) {
numeral_end = m.SkipDigits(numeral_start);
if (numeral_end == numeral_start) {
// If there's a single latin letter, we can use that.
numeral_end = m.SkipAlpha(numeral_start);
if (numeral_end - numeral_start != 1)
break;
}
}
// We got some sort of numeral.
num_segments++;
// Skip any trailing punctuation.
pos = m.SkipPunc(numeral_end);
if (pos == numeral_end)
break;
}
return pos == werd->length();
}
// ========= Brain Dead Language Model (combined entry points) ================
// Given the leftmost word of a line either as a Tesseract unicharset + werd
// or a utf8 string, set the following attributes for it:
// is_list - this word might be a list number or bullet.
// starts_idea - this word is likely to start a sentence.
// ends_idea - this word is likely to end a sentence.
void LeftWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd,
const STRING &utf8,
bool *is_list, bool *starts_idea, bool *ends_idea) {
*is_list = false;
*starts_idea = false;
*ends_idea = false;
if (utf8.size() == 0 || (werd != NULL && werd->length() == 0)) { // Empty
*ends_idea = true;
return;
}
if (unicharset && werd) { // We have a proper werd and unicharset so use it.
if (UniLikelyListItem(unicharset, werd)) {
*is_list = true;
*starts_idea = true;
*ends_idea = true;
}
if (unicharset->get_isupper(werd->unichar_id(0))) {
*starts_idea = true;
}
if (unicharset->get_ispunctuation(werd->unichar_id(0))) {
*starts_idea = true;
*ends_idea = true;
}
} else { // Assume utf8 is mostly ASCII
if (AsciiLikelyListItem(utf8)) {
*is_list = true;
*starts_idea = true;
}
int start_letter = utf8[0];
if (IsOpeningPunct(start_letter)) {
*starts_idea = true;
}
if (IsTerminalPunct(start_letter)) {
*ends_idea = true;
}
if (start_letter >= 'A' && start_letter <= 'Z') {
*starts_idea = true;
}
}
}
// Given the rightmost word of a line either as a Tesseract unicharset + werd
// or a utf8 string, set the following attributes for it:
// is_list - this word might be a list number or bullet.
// starts_idea - this word is likely to start a sentence.
// ends_idea - this word is likely to end a sentence.
void RightWordAttributes(const UNICHARSET *unicharset, const WERD_CHOICE *werd,
const STRING &utf8,
bool *is_list, bool *starts_idea, bool *ends_idea) {
*is_list = false;
*starts_idea = false;
*ends_idea = false;
if (utf8.size() == 0 || (werd != NULL && werd->length() == 0)) { // Empty
*ends_idea = true;
return;
}
if (unicharset && werd) { // We have a proper werd and unicharset so use it.
if (UniLikelyListItem(unicharset, werd)) {
*is_list = true;
*starts_idea = true;
}
UNICHAR_ID last_letter = werd->unichar_id(werd->length() - 1);
if (unicharset->get_ispunctuation(last_letter)) {
*ends_idea = true;
}
} else { // Assume utf8 is mostly ASCII
if (AsciiLikelyListItem(utf8)) {
*is_list = true;
*starts_idea = true;
}
int last_letter = utf8[utf8.size() - 1];
if (IsOpeningPunct(last_letter) || IsTerminalPunct(last_letter)) {
*ends_idea = true;
}
}
}
// =============== Implementation of RowScratchRegisters =====================
/* static */
void RowScratchRegisters::AppendDebugHeaderFields(
GenericVector<STRING> *header) {
header->push_back("[lmarg,lind;rind,rmarg]");
header->push_back("model");
}
void RowScratchRegisters::AppendDebugInfo(const ParagraphTheory &theory,
GenericVector<STRING> *dbg) const {
char s[30];
snprintf(s, sizeof(s), "[%3d,%3d;%3d,%3d]",
lmargin_, lindent_, rindent_, rmargin_);
dbg->push_back(s);
STRING model_string;
model_string += static_cast<char>(GetLineType());
model_string += ":";
int model_numbers = 0;
for (int h = 0; h < hypotheses_.size(); h++) {
if (hypotheses_[h].model == NULL)
continue;
if (model_numbers > 0)
model_string += ",";
if (StrongModel(hypotheses_[h].model)) {
model_string += StrOf(1 + theory.IndexOf(hypotheses_[h].model));
} else if (hypotheses_[h].model == kCrownLeft) {
model_string += "CrL";
} else if (hypotheses_[h].model == kCrownRight) {
model_string += "CrR";
}
model_numbers++;
}
if (model_numbers == 0)
model_string += "0";
dbg->push_back(model_string);
}
void RowScratchRegisters::Init(const RowInfo &row) {
ri_ = &row;
lmargin_ = 0;
lindent_ = row.pix_ldistance;
rmargin_ = 0;
rindent_ = row.pix_rdistance;
}
LineType RowScratchRegisters::GetLineType() const {
if (hypotheses_.empty())
return LT_UNKNOWN;
bool has_start = false;
bool has_body = false;
for (int i = 0; i < hypotheses_.size(); i++) {
switch (hypotheses_[i].ty) {
case LT_START: has_start = true; break;
case LT_BODY: has_body = true; break;
default:
tprintf("Encountered bad value in hypothesis list: %c\n",
hypotheses_[i].ty);
break;
}
}
if (has_start && has_body)
return LT_MULTIPLE;
return has_start ? LT_START : LT_BODY;
}
LineType RowScratchRegisters::GetLineType(const ParagraphModel *model) const {
if (hypotheses_.empty())
return LT_UNKNOWN;
bool has_start = false;
bool has_body = false;
for (int i = 0; i < hypotheses_.size(); i++) {
if (hypotheses_[i].model != model)
continue;
switch (hypotheses_[i].ty) {
case LT_START: has_start = true; break;
case LT_BODY: has_body = true; break;
default:
tprintf("Encountered bad value in hypothesis list: %c\n",
hypotheses_[i].ty);
break;
}
}
if (has_start && has_body)
return LT_MULTIPLE;
return has_start ? LT_START : LT_BODY;
}
void RowScratchRegisters::SetStartLine() {
LineType current_lt = GetLineType();
if (current_lt != LT_UNKNOWN && current_lt != LT_START) {
tprintf("Trying to set a line to be START when it's already BODY.\n");
}
if (current_lt == LT_UNKNOWN || current_lt == LT_BODY) {
hypotheses_.push_back_new(LineHypothesis(LT_START, NULL));
}
}
void RowScratchRegisters::SetBodyLine() {
LineType current_lt = GetLineType();
if (current_lt != LT_UNKNOWN && current_lt != LT_BODY) {
tprintf("Trying to set a line to be BODY when it's already START.\n");
}
if (current_lt == LT_UNKNOWN || current_lt == LT_START) {
hypotheses_.push_back_new(LineHypothesis(LT_BODY, NULL));
}
}
void RowScratchRegisters::AddStartLine(const ParagraphModel *model) {
hypotheses_.push_back_new(LineHypothesis(LT_START, model));
int old_idx = hypotheses_.get_index(LineHypothesis(LT_START, NULL));
if (old_idx >= 0)
hypotheses_.remove(old_idx);
}
void RowScratchRegisters::AddBodyLine(const ParagraphModel *model) {
hypotheses_.push_back_new(LineHypothesis(LT_BODY, model));
int old_idx = hypotheses_.get_index(LineHypothesis(LT_BODY, NULL));
if (old_idx >= 0)
hypotheses_.remove(old_idx);
}
void RowScratchRegisters::StartHypotheses(SetOfModels *models) const {
for (int h = 0; h < hypotheses_.size(); h++) {
if (hypotheses_[h].ty == LT_START && StrongModel(hypotheses_[h].model))
models->push_back_new(hypotheses_[h].model);
}
}
void RowScratchRegisters::StrongHypotheses(SetOfModels *models) const {
for (int h = 0; h < hypotheses_.size(); h++) {
if (StrongModel(hypotheses_[h].model))
models->push_back_new(hypotheses_[h].model);
}
}
void RowScratchRegisters::NonNullHypotheses(SetOfModels *models) const {
for (int h = 0; h < hypotheses_.size(); h++) {
if (hypotheses_[h].model != NULL)
models->push_back_new(hypotheses_[h].model);
}
}
const ParagraphModel *RowScratchRegisters::UniqueStartHypothesis() const {
if (hypotheses_.size() != 1 || hypotheses_[0].ty != LT_START)
return NULL;
return hypotheses_[0].model;
}
const ParagraphModel *RowScratchRegisters::UniqueBodyHypothesis() const {
if (hypotheses_.size() != 1 || hypotheses_[0].ty != LT_BODY)
return NULL;
return hypotheses_[0].model;
}
// Discard any hypotheses whose model is not in the given list.
void RowScratchRegisters::DiscardNonMatchingHypotheses(
const SetOfModels &models) {
if (models.empty())
return;
for (int h = hypotheses_.size() - 1; h >= 0; h--) {
if (!models.contains(hypotheses_[h].model)) {
hypotheses_.remove(h);
}
}
}
// ============ Geometry based Paragraph Detection Algorithm =================
struct Cluster {
Cluster() : center(0), count(0) {}
Cluster(int cen, int num) : center(cen), count(num) {}
int center; // The center of the cluster.
int count; // The number of entries within the cluster.
};
class SimpleClusterer {
public:
explicit SimpleClusterer(int max_cluster_width)
: max_cluster_width_(max_cluster_width) {}
void Add(int value) { values_.push_back(value); }
int size() const { return values_.size(); }
void GetClusters(GenericVector<Cluster> *clusters);
private:
int max_cluster_width_;
GenericVectorEqEq<int> values_;
};
// Return the index of the cluster closest to value.
int ClosestCluster(const GenericVector<Cluster> &clusters, int value) {
int best_index = 0;
for (int i = 0; i < clusters.size(); i++) {
if (abs(value - clusters[i].center) <
abs(value - clusters[best_index].center))
best_index = i;
}
return best_index;
}
void SimpleClusterer::GetClusters(GenericVector<Cluster> *clusters) {
clusters->clear();
values_.sort();
for (int i = 0; i < values_.size();) {
int orig_i = i;
int lo = values_[i];
int hi = lo;
while (++i < values_.size() && values_[i] <= lo + max_cluster_width_) {
hi = values_[i];
}
clusters->push_back(Cluster((hi + lo) / 2, i - orig_i));
}
}
// Calculate left- and right-indent tab stop values seen in
// rows[row_start, row_end) given a tolerance of tolerance.
void CalculateTabStops(GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
int tolerance,
GenericVector<Cluster> *left_tabs,
GenericVector<Cluster> *right_tabs) {
if (!AcceptableRowArgs(0, 1, __func__, rows, row_start, row_end))
return;
// First pass: toss all left and right indents into clusterers.
SimpleClusterer initial_lefts(tolerance);
SimpleClusterer initial_rights(tolerance);
GenericVector<Cluster> initial_left_tabs;
GenericVector<Cluster> initial_right_tabs;
for (int i = row_start; i < row_end; i++) {
initial_lefts.Add((*rows)[i].lindent_);
initial_rights.Add((*rows)[i].rindent_);
}
initial_lefts.GetClusters(&initial_left_tabs);
initial_rights.GetClusters(&initial_right_tabs);
// Second pass: cluster only lines that are not "stray"
// An example of a stray line is a page number -- a line whose start
// and end tab-stops are far outside the typical start and end tab-stops
// for the block.
// Put another way, we only cluster data from lines whose start or end
// tab stop is frequent.
SimpleClusterer lefts(tolerance);
SimpleClusterer rights(tolerance);
// Outlier elimination. We might want to switch this to test outlier-ness
// based on how strange a position an outlier is in instead of or in addition
// to how rare it is. These outliers get re-added if we end up having too
// few tab stops, to work with, however.
int infrequent_enough_to_ignore = 0;
if (row_end - row_start >= 8) infrequent_enough_to_ignore = 1;
if (row_end - row_start >= 20) infrequent_enough_to_ignore = 2;
for (int i = row_start; i < row_end; i++) {
int lidx = ClosestCluster(initial_left_tabs, (*rows)[i].lindent_);
int ridx = ClosestCluster(initial_right_tabs, (*rows)[i].rindent_);
if (initial_left_tabs[lidx].count > infrequent_enough_to_ignore ||
initial_right_tabs[ridx].count > infrequent_enough_to_ignore) {
lefts.Add((*rows)[i].lindent_);
rights.Add((*rows)[i].rindent_);
}
}
lefts.GetClusters(left_tabs);
rights.GetClusters(right_tabs);
if ((left_tabs->size() == 1 && right_tabs->size() >= 4) ||
(right_tabs->size() == 1 && left_tabs->size() >= 4)) {
// One side is really ragged, and the other only has one tab stop,
// so those "insignificant outliers" are probably important, actually.
// This often happens on a page of an index. Add back in the ones
// we omitted in the first pass.
for (int i = row_start; i < row_end; i++) {
int lidx = ClosestCluster(initial_left_tabs, (*rows)[i].lindent_);
int ridx = ClosestCluster(initial_right_tabs, (*rows)[i].rindent_);
if (!(initial_left_tabs[lidx].count > infrequent_enough_to_ignore ||
initial_right_tabs[ridx].count > infrequent_enough_to_ignore)) {
lefts.Add((*rows)[i].lindent_);
rights.Add((*rows)[i].rindent_);
}
}
}
lefts.GetClusters(left_tabs);
rights.GetClusters(right_tabs);
// If one side is almost a two-indent aligned side, and the other clearly
// isn't, try to prune out the least frequent tab stop from that side.
if (left_tabs->size() == 3 && right_tabs->size() >= 4) {
int to_prune = -1;
for (int i = left_tabs->size() - 1; i >= 0; i--) {
if (to_prune < 0 ||
(*left_tabs)[i].count < (*left_tabs)[to_prune].count) {
to_prune = i;
}
}
if (to_prune >= 0 &&
(*left_tabs)[to_prune].count <= infrequent_enough_to_ignore) {
left_tabs->remove(to_prune);
}
}
if (right_tabs->size() == 3 && left_tabs->size() >= 4) {
int to_prune = -1;
for (int i = right_tabs->size() - 1; i >= 0; i--) {
if (to_prune < 0 ||
(*right_tabs)[i].count < (*right_tabs)[to_prune].count) {
to_prune = i;
}
}
if (to_prune >= 0 &&
(*right_tabs)[to_prune].count <= infrequent_enough_to_ignore) {
right_tabs->remove(to_prune);
}
}
}
// Given a paragraph model mark rows[row_start, row_end) as said model
// start or body lines.
//
// Case 1: model->first_indent_ != model->body_indent_
// Differentiating the paragraph start lines from the paragraph body lines in
// this case is easy, we just see how far each line is indented.
//
// Case 2: model->first_indent_ == model->body_indent_
// Here, we find end-of-paragraph lines by looking for "short lines."
// What constitutes a "short line" changes depending on whether the text
// ragged-right[left] or fully justified (aligned left and right).
//
// Case 2a: Ragged Right (or Left) text. (eop_threshold == 0)
// We have a new paragraph it the first word would have at the end
// of the previous line.
//
// Case 2b: Fully Justified. (eop_threshold > 0)
// We mark a line as short (end of paragraph) if the offside indent
// is greater than eop_threshold.
void MarkRowsWithModel(GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
const ParagraphModel *model,
bool ltr,
int eop_threshold) {
if (!AcceptableRowArgs(0, 0, __func__, rows, row_start, row_end))
return;
for (int row = row_start; row < row_end; row++) {
bool valid_first = ValidFirstLine(rows, row, model);
bool valid_body = ValidBodyLine(rows, row, model);
if (valid_first && !valid_body) {
(*rows)[row].AddStartLine(model);
} else if (valid_body && !valid_first) {
(*rows)[row].AddBodyLine(model);
} else if (valid_body && valid_first) {
bool after_eop = (row == row_start);
if (row > row_start) {
if (eop_threshold > 0) {
if (model->justification() == JUSTIFICATION_LEFT) {
after_eop = (*rows)[row - 1].rindent_ > eop_threshold;
} else {
after_eop = (*rows)[row - 1].lindent_ > eop_threshold;
}
} else {
after_eop = FirstWordWouldHaveFit((*rows)[row - 1], (*rows)[row],
model->justification());
}
}
if (after_eop) {
(*rows)[row].AddStartLine(model);
} else {
(*rows)[row].AddBodyLine(model);
}
} else {
// Do nothing. Stray row.
}
}
}
// GeometricClassifierState holds all of the information we'll use while
// trying to determine a paragraph model for the text lines in a block of
// text:
// + the rows under consideration [row_start, row_end)
// + the common left- and right-indent tab stops
// + does the block start out left-to-right or right-to-left
// Further, this struct holds the data we amass for the (single) ParagraphModel
// we'll assign to the text lines (assuming we get that far).
struct GeometricClassifierState {
GeometricClassifierState(int dbg_level,
GenericVector<RowScratchRegisters> *r,
int r_start, int r_end)
: debug_level(dbg_level), rows(r), row_start(r_start), row_end(r_end),
margin(0) {
tolerance = InterwordSpace(*r, r_start, r_end);
CalculateTabStops(r, r_start, r_end, tolerance,
&left_tabs, &right_tabs);
if (debug_level >= 3) {
tprintf("Geometry: TabStop cluster tolerance = %d; "
"%d left tabs; %d right tabs\n",
tolerance, left_tabs.size(), right_tabs.size());
}
ltr = (*r)[r_start].ri_->ltr;
}
void AssumeLeftJustification() {
just = tesseract::JUSTIFICATION_LEFT;
margin = (*rows)[row_start].lmargin_;
}
void AssumeRightJustification() {
just = tesseract::JUSTIFICATION_RIGHT;
margin = (*rows)[row_start].rmargin_;
}
// Align tabs are the tab stops the text is aligned to.
const GenericVector<Cluster> &AlignTabs() const {
if (just == tesseract::JUSTIFICATION_RIGHT) return right_tabs;
return left_tabs;
}
// Offside tabs are the tab stops opposite the tabs used to align the text.
//
// Note that for a left-to-right text which is aligned to the right such as
// this function comment, the offside tabs are the horizontal tab stops
// marking the beginning of ("Note", "this" and "marking").
const GenericVector<Cluster> &OffsideTabs() const {
if (just == tesseract::JUSTIFICATION_RIGHT) return left_tabs;
return right_tabs;
}
// Return whether the i'th row extends from the leftmost left tab stop
// to the right most right tab stop.
bool IsFullRow(int i) const {
return ClosestCluster(left_tabs, (*rows)[i].lindent_) == 0 &&
ClosestCluster(right_tabs, (*rows)[i].rindent_) == 0;
}
int AlignsideTabIndex(int row_idx) const {
return ClosestCluster(AlignTabs(), (*rows)[row_idx].AlignsideIndent(just));
}
// Given what we know about the paragraph justification (just), would the
// first word of row_b have fit at the end of row_a?
bool FirstWordWouldHaveFit(int row_a, int row_b) {
return ::tesseract::FirstWordWouldHaveFit(
(*rows)[row_a], (*rows)[row_b], just);
}
void PrintRows() const { PrintRowRange(*rows, row_start, row_end); }
void Fail(int min_debug_level, const char *why) const {
if (debug_level < min_debug_level) return;
tprintf("# %s\n", why);
PrintRows();
}
ParagraphModel Model() const {
return ParagraphModel(just, margin, first_indent, body_indent, tolerance);
}
// We print out messages with a debug level at least as great as debug_level.
int debug_level;
// The Geometric Classifier was asked to find a single paragraph model
// to fit the text rows (*rows)[row_start, row_end)
GenericVector<RowScratchRegisters> *rows;
int row_start;
int row_end;
// The amount by which we expect the text edge can vary and still be aligned.
int tolerance;
// Is the script in this text block left-to-right?
// HORRIBLE ROUGH APPROXIMATION. TODO(eger): Improve
bool ltr;
// These left and right tab stops were determined to be the common tab
// stops for the given text.
GenericVector<Cluster> left_tabs;
GenericVector<Cluster> right_tabs;
// These are parameters we must determine to create a ParagraphModel.
tesseract::ParagraphJustification just;
int margin;
int first_indent;
int body_indent;
// eop_threshold > 0 if the text is fully justified. See MarkRowsWithModel()
int eop_threshold;
};
// Given a section of text where strong textual clues did not help identifying
// paragraph breaks, and for which the left and right indents have exactly
// three tab stops between them, attempt to find the paragraph breaks based
// solely on the outline of the text and whether the script is left-to-right.
//
// Algorithm Detail:
// The selected rows are in the form of a rectangle except
// for some number of "short lines" of the same length:
//
// (A1) xxxxxxxxxxxxx (B1) xxxxxxxxxxxx
// xxxxxxxxxxx xxxxxxxxxx # A "short" line.
// xxxxxxxxxxxxx xxxxxxxxxxxx
// xxxxxxxxxxxxx xxxxxxxxxxxx
//
// We have a slightly different situation if the only short
// line is at the end of the excerpt.
//
// (A2) xxxxxxxxxxxxx (B2) xxxxxxxxxxxx
// xxxxxxxxxxxxx xxxxxxxxxxxx
// xxxxxxxxxxxxx xxxxxxxxxxxx
// xxxxxxxxxxx xxxxxxxxxx # A "short" line.
//
// We'll interpret these as follows based on the reasoning in the comment for
// GeometricClassify():
// [script direction: first indent, body indent]
// (A1) LtR: 2,0 RtL: 0,0 (B1) LtR: 0,0 RtL: 2,0
// (A2) LtR: 2,0 RtL: CrR (B2) LtR: CrL RtL: 2,0
void GeometricClassifyThreeTabStopTextBlock(
int debug_level,
GeometricClassifierState &s,
ParagraphTheory *theory) {
int num_rows = s.row_end - s.row_start;
int num_full_rows = 0;
int last_row_full = 0;
for (int i = s.row_start; i < s.row_end; i++) {
if (s.IsFullRow(i)) {
num_full_rows++;
if (i == s.row_end - 1) last_row_full++;
}
}
if (num_full_rows < 0.7 * num_rows) {
s.Fail(1, "Not enough full lines to know which lines start paras.");
return;
}
// eop_threshold gets set if we're fully justified; see MarkRowsWithModel()
s.eop_threshold = 0;
if (s.ltr) {
s.AssumeLeftJustification();
} else {
s.AssumeRightJustification();
}
if (debug_level > 0) {
tprintf("# Not enough variety for clear outline classification. "
"Guessing these are %s aligned based on script.\n",
s.ltr ? "left" : "right");
s.PrintRows();
}
if (s.AlignTabs().size() == 2) { // case A1 or A2
s.first_indent = s.AlignTabs()[1].center;
s.body_indent = s.AlignTabs()[0].center;
} else { // case B1 or B2
if (num_rows - 1 == num_full_rows - last_row_full) {
// case B2
const ParagraphModel *model = s.ltr ? kCrownLeft : kCrownRight;
(*s.rows)[s.row_start].AddStartLine(model);
for (int i = s.row_start + 1; i < s.row_end; i++) {
(*s.rows)[i].AddBodyLine(model);
}
return;
} else {
// case B1
s.first_indent = s.body_indent = s.AlignTabs()[0].center;
s.eop_threshold = (s.OffsideTabs()[0].center +
s.OffsideTabs()[1].center) / 2;
}
}
const ParagraphModel *model = theory->AddModel(s.Model());
MarkRowsWithModel(s.rows, s.row_start, s.row_end, model,
s.ltr, s.eop_threshold);
return;
}
// This function is called if strong textual clues were not available, but
// the caller hopes that the paragraph breaks will be super obvious just
// by the outline of the text.
//
// The particularly difficult case is figuring out what's going on if you
// don't have enough short paragraph end lines to tell us what's going on.
//
// For instance, let's say you have the following outline:
//
// (A1) xxxxxxxxxxxxxxxxxxxxxx
// xxxxxxxxxxxxxxxxxxxx
// xxxxxxxxxxxxxxxxxxxxxx
// xxxxxxxxxxxxxxxxxxxxxx
//
// Even if we know that the text is left-to-right and so will probably be
// left-aligned, both of the following are possible texts:
//
// (A1a) 1. Here our list item
// with two full lines.
// 2. Here a second item.
// 3. Here our third one.
//
// (A1b) so ends paragraph one.
// Here starts another
// paragraph we want to
// read. This continues
//
// These examples are obvious from the text and should have been caught
// by the StrongEvidenceClassify pass. However, for languages where we don't
// have capital letters to go on (e.g. Hebrew, Arabic, Hindi, Chinese),
// it's worth guessing that (A1b) is the correct interpretation if there are
// far more "full" lines than "short" lines.
void GeometricClassify(int debug_level,
GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
ParagraphTheory *theory) {
if (!AcceptableRowArgs(debug_level, 4, __func__, rows, row_start, row_end))
return;
if (debug_level > 1) {
tprintf("###############################################\n");
tprintf("##### GeometricClassify( rows[%d:%d) ) ####\n",
row_start, row_end);
tprintf("###############################################\n");
}
RecomputeMarginsAndClearHypotheses(rows, row_start, row_end, 10);
GeometricClassifierState s(debug_level, rows, row_start, row_end);
if (s.left_tabs.size() > 2 && s.right_tabs.size() > 2) {
s.Fail(2, "Too much variety for simple outline classification.");
return;
}
if (s.left_tabs.size() <= 1 && s.right_tabs.size() <= 1) {
s.Fail(1, "Not enough variety for simple outline classification.");
return;
}
if (s.left_tabs.size() + s.right_tabs.size() == 3) {
GeometricClassifyThreeTabStopTextBlock(debug_level, s, theory);
return;
}
// At this point, we know that one side has at least two tab stops, and the
// other side has one or two tab stops.
// Left to determine:
// (1) Which is the body indent and which is the first line indent?
// (2) Is the text fully justified?
// If one side happens to have three or more tab stops, assume that side
// is opposite of the aligned side.
if (s.right_tabs.size() > 2) {
s.AssumeLeftJustification();
} else if (s.left_tabs.size() > 2) {
s.AssumeRightJustification();
} else if (s.ltr) { // guess based on script direction
s.AssumeLeftJustification();
} else {
s.AssumeRightJustification();
}
if (s.AlignTabs().size() == 2) {
// For each tab stop on the aligned side, how many of them appear
// to be paragraph start lines? [first lines]
int firsts[2] = {0, 0};
// Count the first line as a likely paragraph start line.
firsts[s.AlignsideTabIndex(s.row_start)]++;
// For each line, if the first word would have fit on the previous
// line count it as a likely paragraph start line.
bool jam_packed = true;
for (int i = s.row_start + 1; i < s.row_end; i++) {
if (s.FirstWordWouldHaveFit(i - 1, i)) {
firsts[s.AlignsideTabIndex(i)]++;
jam_packed = false;
}
}
// Make an extra accounting for the last line of the paragraph just
// in case it's the only short line in the block. That is, take its
// first word as typical and see if this looks like the *last* line
// of a paragraph. If so, mark the *other* indent as probably a first.
if (jam_packed && s.FirstWordWouldHaveFit(s.row_end - 1, s.row_end - 1)) {
firsts[1 - s.AlignsideTabIndex(s.row_end - 1)]++;
}
int percent0firsts, percent1firsts;
percent0firsts = (100 * firsts[0]) / s.AlignTabs()[0].count;
percent1firsts = (100 * firsts[1]) / s.AlignTabs()[1].count;
// TODO(eger): Tune these constants if necessary.
if ((percent0firsts < 20 && 30 < percent1firsts) ||
percent0firsts + 30 < percent1firsts) {
s.first_indent = s.AlignTabs()[1].center;
s.body_indent = s.AlignTabs()[0].center;
} else if ((percent1firsts < 20 && 30 < percent0firsts) ||
percent1firsts + 30 < percent0firsts) {
s.first_indent = s.AlignTabs()[0].center;
s.body_indent = s.AlignTabs()[1].center;
} else {
// Ambiguous! Probably lineated (poetry)
if (debug_level > 1) {
tprintf("# Cannot determine %s indent likely to start paragraphs.\n",
s.just == tesseract::JUSTIFICATION_LEFT ? "left" : "right");
tprintf("# Indent of %d looks like a first line %d%% of the time.\n",
s.AlignTabs()[0].center, percent0firsts);
tprintf("# Indent of %d looks like a first line %d%% of the time.\n",
s.AlignTabs()[1].center, percent1firsts);
s.PrintRows();
}
return;
}
} else {
// There's only one tab stop for the "aligned to" side.
s.first_indent = s.body_indent = s.AlignTabs()[0].center;
}
// At this point, we have our model.
const ParagraphModel *model = theory->AddModel(s.Model());
// Now all we have to do is figure out if the text is fully justified or not.
// eop_threshold: default to fully justified unless we see evidence below.
// See description on MarkRowsWithModel()
s.eop_threshold =
(s.OffsideTabs()[0].center + s.OffsideTabs()[1].center) / 2;
// If the text is not fully justified, re-set the eop_threshold to 0.
if (s.AlignTabs().size() == 2) {
// Paragraphs with a paragraph-start indent.
for (int i = s.row_start; i < s.row_end - 1; i++) {
if (ValidFirstLine(s.rows, i + 1, model) &&
!NearlyEqual(s.OffsideTabs()[0].center,
(*s.rows)[i].OffsideIndent(s.just), s.tolerance)) {
// We found a non-end-of-paragraph short line: not fully justified.
s.eop_threshold = 0;
break;
}
}
} else {
// Paragraphs with no paragraph-start indent.
for (int i = s.row_start; i < s.row_end - 1; i++) {
if (!s.FirstWordWouldHaveFit(i, i + 1) &&
!NearlyEqual(s.OffsideTabs()[0].center,
(*s.rows)[i].OffsideIndent(s.just), s.tolerance)) {
// We found a non-end-of-paragraph short line: not fully justified.
s.eop_threshold = 0;
break;
}
}
}
MarkRowsWithModel(rows, row_start, row_end, model, s.ltr, s.eop_threshold);
}
// =============== Implementation of ParagraphTheory =====================
const ParagraphModel *ParagraphTheory::AddModel(const ParagraphModel &model) {
for (int i = 0; i < models_->size(); i++) {
if ((*models_)[i]->Comparable(model))
return (*models_)[i];
}
ParagraphModel *m = new ParagraphModel(model);
models_->push_back(m);
models_we_added_.push_back_new(m);
return m;
}
void ParagraphTheory::DiscardUnusedModels(const SetOfModels &used_models) {
for (int i = models_->size() - 1; i >= 0; i--) {
ParagraphModel *m = (*models_)[i];
if (!used_models.contains(m) && models_we_added_.contains(m)) {
models_->remove(i);
models_we_added_.remove(models_we_added_.get_index(m));
delete m;
}
}
}
// Examine rows[start, end) and try to determine if an existing non-centered
// paragraph model would fit them perfectly. If so, return a pointer to it.
// If not, return NULL.
const ParagraphModel *ParagraphTheory::Fits(
const GenericVector<RowScratchRegisters> *rows, int start, int end) const {
for (int m = 0; m < models_->size(); m++) {
const ParagraphModel *model = (*models_)[m];
if (model->justification() != JUSTIFICATION_CENTER &&
RowsFitModel(rows, start, end, model))
return model;
}
return NULL;
}
void ParagraphTheory::NonCenteredModels(SetOfModels *models) {
for (int m = 0; m < models_->size(); m++) {
const ParagraphModel *model = (*models_)[m];
if (model->justification() != JUSTIFICATION_CENTER)
models->push_back_new(model);
}
}
int ParagraphTheory::IndexOf(const ParagraphModel *model) const {
for (int i = 0; i < models_->size(); i++) {
if ((*models_)[i] == model)
return i;
}
return -1;
}
bool ValidFirstLine(const GenericVector<RowScratchRegisters> *rows,
int row, const ParagraphModel *model) {
if (!StrongModel(model)) {
tprintf("ValidFirstLine() should only be called with strong models!\n");
}
return StrongModel(model) &&
model->ValidFirstLine(
(*rows)[row].lmargin_, (*rows)[row].lindent_,
(*rows)[row].rindent_, (*rows)[row].rmargin_);
}
bool ValidBodyLine(const GenericVector<RowScratchRegisters> *rows,
int row, const ParagraphModel *model) {
if (!StrongModel(model)) {
tprintf("ValidBodyLine() should only be called with strong models!\n");
}
return StrongModel(model) &&
model->ValidBodyLine(
(*rows)[row].lmargin_, (*rows)[row].lindent_,
(*rows)[row].rindent_, (*rows)[row].rmargin_);
}
bool CrownCompatible(const GenericVector<RowScratchRegisters> *rows,
int a, int b, const ParagraphModel *model) {
if (model != kCrownRight && model != kCrownLeft) {
tprintf("CrownCompatible() should only be called with crown models!\n");
return false;
}
RowScratchRegisters &row_a = (*rows)[a];
RowScratchRegisters &row_b = (*rows)[b];
if (model == kCrownRight) {
return NearlyEqual(row_a.rindent_ + row_a.rmargin_,
row_b.rindent_ + row_b.rmargin_,
Epsilon(row_a.ri_->average_interword_space));
}
return NearlyEqual(row_a.lindent_ + row_a.lmargin_,
row_b.lindent_ + row_b.lmargin_,
Epsilon(row_a.ri_->average_interword_space));
}
// =============== Implementation of ParagraphModelSmearer ====================
ParagraphModelSmearer::ParagraphModelSmearer(
GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end, ParagraphTheory *theory)
: theory_(theory), rows_(rows), row_start_(row_start),
row_end_(row_end) {
if (!AcceptableRowArgs(0, 0, __func__, rows, row_start, row_end)) {
row_start_ = 0;
row_end_ = 0;
return;
}
SetOfModels no_models;
for (int row = row_start - 1; row <= row_end; row++) {
open_models_.push_back(no_models);
}
}
// see paragraphs_internal.h
void ParagraphModelSmearer::CalculateOpenModels(int row_start, int row_end) {
SetOfModels no_models;
if (row_start < row_start_) row_start = row_start_;
if (row_end > row_end_) row_end = row_end_;
for (int row = (row_start > 0) ? row_start - 1 : row_start; row < row_end;
row++) {
if ((*rows_)[row].ri_->num_words == 0) {
OpenModels(row + 1) = no_models;
} else {
SetOfModels &opened = OpenModels(row);
(*rows_)[row].StartHypotheses(&opened);
// Which models survive the transition from row to row + 1?
SetOfModels still_open;
for (int m = 0; m < opened.size(); m++) {
if (ValidFirstLine(rows_, row, opened[m]) ||
ValidBodyLine(rows_, row, opened[m])) {
// This is basic filtering; we check likely paragraph starty-ness down
// below in Smear() -- you know, whether the first word would have fit
// and such.
still_open.push_back_new(opened[m]);
}
}
OpenModels(row + 1) = still_open;
}
}
}
// see paragraphs_internal.h
void ParagraphModelSmearer::Smear() {
CalculateOpenModels(row_start_, row_end_);
// For each row which we're unsure about (that is, it is LT_UNKNOWN or
// we have multiple LT_START hypotheses), see if there's a model that
// was recently used (an "open" model) which might model it well.
for (int i = row_start_; i < row_end_; i++) {
RowScratchRegisters &row = (*rows_)[i];
if (row.ri_->num_words == 0)
continue;
// Step One:
// Figure out if there are "open" models which are left-alined or
// right-aligned. This is important for determining whether the
// "first" word in a row would fit at the "end" of the previous row.
bool left_align_open = false;
bool right_align_open = false;
for (int m = 0; m < OpenModels(i).size(); m++) {
switch (OpenModels(i)[m]->justification()) {
case JUSTIFICATION_LEFT: left_align_open = true; break;
case JUSTIFICATION_RIGHT: right_align_open = true; break;
default: left_align_open = right_align_open = true;
}
}
// Step Two:
// Use that knowledge to figure out if this row is likely to
// start a paragraph.
bool likely_start;
if (i == 0) {
likely_start = true;
} else {
if ((left_align_open && right_align_open) ||
(!left_align_open && !right_align_open)) {
likely_start = LikelyParagraphStart((*rows_)[i - 1], row,
JUSTIFICATION_LEFT) ||
LikelyParagraphStart((*rows_)[i - 1], row,
JUSTIFICATION_RIGHT);
} else if (left_align_open) {
likely_start = LikelyParagraphStart((*rows_)[i - 1], row,
JUSTIFICATION_LEFT);
} else {
likely_start = LikelyParagraphStart((*rows_)[i - 1], row,
JUSTIFICATION_RIGHT);
}
}
// Step Three:
// If this text line seems like an obvious first line of an
// open model, or an obvious continuation of an existing
// modelled paragraph, mark it up.
if (likely_start) {
// Add Start Hypotheses for all Open models that fit.
for (int m = 0; m < OpenModels(i).size(); m++) {
if (ValidFirstLine(rows_, i, OpenModels(i)[m])) {
row.AddStartLine(OpenModels(i)[m]);
}
}
} else {
// Add relevant body line hypotheses.
SetOfModels last_line_models;
if (i > 0) {
(*rows_)[i - 1].StrongHypotheses(&last_line_models);
} else {
theory_->NonCenteredModels(&last_line_models);
}
for (int m = 0; m < last_line_models.size(); m++) {
const ParagraphModel *model = last_line_models[m];
if (ValidBodyLine(rows_, i, model))
row.AddBodyLine(model);
}
}
// Step Four:
// If we're still quite unsure about this line, go through all
// models in our theory and see if this row could be the start
// of any of our models.
if (row.GetLineType() == LT_UNKNOWN ||
(row.GetLineType() == LT_START && !row.UniqueStartHypothesis())) {
SetOfModels all_models;
theory_->NonCenteredModels(&all_models);
for (int m = 0; m < all_models.size(); m++) {
if (ValidFirstLine(rows_, i, all_models[m])) {
row.AddStartLine(all_models[m]);
}
}
}
// Step Five:
// Since we may have updated the hypotheses about this row, we need
// to recalculate the Open models for the rest of rows[i + 1, row_end)
if (row.GetLineType() != LT_UNKNOWN) {
CalculateOpenModels(i + 1, row_end_);
}
}
}
// ================ Main Paragraph Detection Algorithm =======================
// Find out what ParagraphModels are actually used, and discard any
// that are not.
void DiscardUnusedModels(const GenericVector<RowScratchRegisters> &rows,
ParagraphTheory *theory) {
SetOfModels used_models;
for (int i = 0; i < rows.size(); i++) {
rows[i].StrongHypotheses(&used_models);
}
theory->DiscardUnusedModels(used_models);
}
// DowngradeWeakestToCrowns:
// Forget any flush-{left, right} models unless we see two or more
// of them in sequence.
//
// In pass 3, we start to classify even flush-left paragraphs (paragraphs
// where the first line and body indent are the same) as having proper Models.
// This is generally dangerous, since if you start imagining that flush-left
// is a typical paragraph model when it is not, it will lead you to chop normal
// indented paragraphs in the middle whenever a sentence happens to start on a
// new line (see "This" above). What to do?
// What we do is to take any paragraph which is flush left and is not
// preceded by another paragraph of the same model and convert it to a "Crown"
// paragraph. This is a weak pseudo-ParagraphModel which is a placeholder
// for later. It means that the paragraph is flush, but it would be desirable
// to mark it as the same model as following text if it fits. This downgrade
// FlushLeft -> CrownLeft -> Model of following paragraph. Means that we
// avoid making flush left Paragraph Models whenever we see a top-of-the-page
// half-of-a-paragraph. and instead we mark it the same as normal body text.
//
// Implementation:
//
// Comb backwards through the row scratch registers, and turn any
// sequences of body lines of equivalent type abutted against the beginning
// or a body or start line of a different type into a crown paragraph.
void DowngradeWeakestToCrowns(int debug_level,
ParagraphTheory *theory,
GenericVector<RowScratchRegisters> *rows) {
int start;
for (int end = rows->size(); end > 0; end = start) {
// Search back for a body line of a unique type.
const ParagraphModel *model = NULL;
while (end > 0 &&
(model = (*rows)[end - 1].UniqueBodyHypothesis()) == NULL) {
end--;
}
if (end == 0) break;
start = end - 1;
while (start >= 0 && (*rows)[start].UniqueBodyHypothesis() == model) {
start--; // walk back to the first line that is not the same body type.
}
if (start >= 0 && (*rows)[start].UniqueStartHypothesis() == model &&
StrongModel(model) &&
NearlyEqual(model->first_indent(), model->body_indent(),
model->tolerance())) {
start--;
}
start++;
// Now rows[start, end) is a sequence of unique body hypotheses of model.
if (StrongModel(model) && model->justification() == JUSTIFICATION_CENTER)
continue;
if (!StrongModel(model)) {
while (start > 0 &&
CrownCompatible(rows, start - 1, start, model))
start--;
}
if (start == 0 ||
(!StrongModel(model)) ||
(StrongModel(model) && !ValidFirstLine(rows, start - 1, model))) {
// crownify rows[start, end)
const ParagraphModel *crown_model = model;
if (StrongModel(model)) {
if (model->justification() == JUSTIFICATION_LEFT)
crown_model = kCrownLeft;
else
crown_model = kCrownRight;
}
(*rows)[start].SetUnknown();
(*rows)[start].AddStartLine(crown_model);
for (int row = start + 1; row < end; row++) {
(*rows)[row].SetUnknown();
(*rows)[row].AddBodyLine(crown_model);
}
}
}
DiscardUnusedModels(*rows, theory);
}
// Clear all hypotheses about lines [start, end) and reset margins.
//
// The empty space between the left of a row and the block boundary (and
// similarly for the right) is split into two pieces: margin and indent.
// In initial processing, we assume the block is tight and the margin for
// all lines is set to zero. However, if our first pass does not yield
// models for everything, it may be due to an inset paragraph like a
// block-quote. In that case, we make a second pass over that unmarked
// section of the page and reset the "margin" portion of the empty space
// to the common amount of space at the ends of the lines under consid-
// eration. This would be equivalent to percentile set to 0. However,
// sometimes we have a single character sticking out in the right margin
// of a text block (like the 'r' in 'for' on line 3 above), and we can
// really just ignore it as an outlier. To express this, we allow the
// user to specify the percentile (0..100) of indent values to use as
// the common margin for each row in the run of rows[start, end).
void RecomputeMarginsAndClearHypotheses(
GenericVector<RowScratchRegisters> *rows, int start, int end,
int percentile) {
if (!AcceptableRowArgs(0, 0, __func__, rows, start, end))
return;
int lmin, lmax, rmin, rmax;
lmin = lmax = (*rows)[start].lmargin_ + (*rows)[start].lindent_;
rmin = rmax = (*rows)[start].rmargin_ + (*rows)[start].rindent_;
for (int i = start; i < end; i++) {
RowScratchRegisters &sr = (*rows)[i];
sr.SetUnknown();
if (sr.ri_->num_words == 0)
continue;
UpdateRange(sr.lmargin_ + sr.lindent_, &lmin, &lmax);
UpdateRange(sr.rmargin_ + sr.rindent_, &rmin, &rmax);
}
STATS lefts(lmin, lmax + 1);
STATS rights(rmin, rmax + 1);
for (int i = start; i < end; i++) {
RowScratchRegisters &sr = (*rows)[i];
if (sr.ri_->num_words == 0)
continue;
lefts.add(sr.lmargin_ + sr.lindent_, 1);
rights.add(sr.rmargin_ + sr.rindent_, 1);
}
int ignorable_left = lefts.ile(ClipToRange(percentile, 0, 100) / 100.0);
int ignorable_right = rights.ile(ClipToRange(percentile, 0, 100) / 100.0);
for (int i = start; i < end; i++) {
RowScratchRegisters &sr = (*rows)[i];
int ldelta = ignorable_left - sr.lmargin_;
sr.lmargin_ += ldelta;
sr.lindent_ -= ldelta;
int rdelta = ignorable_right - sr.rmargin_;
sr.rmargin_ += rdelta;
sr.rindent_ -= rdelta;
}
}
// Return the median inter-word space in rows[row_start, row_end).
int InterwordSpace(const GenericVector<RowScratchRegisters> &rows,
int row_start, int row_end) {
if (row_end < row_start + 1) return 1;
int word_height = (rows[row_start].ri_->lword_box.height() +
rows[row_end - 1].ri_->lword_box.height()) / 2;
int word_width = (rows[row_start].ri_->lword_box.width() +
rows[row_end - 1].ri_->lword_box.width()) / 2;
STATS spacing_widths(0, 5 + word_width);
for (int i = row_start; i < row_end; i++) {
if (rows[i].ri_->num_words > 1) {
spacing_widths.add(rows[i].ri_->average_interword_space, 1);
}
}
int minimum_reasonable_space = word_height / 3;
if (minimum_reasonable_space < 2)
minimum_reasonable_space = 2;
int median = spacing_widths.median();
return (median > minimum_reasonable_space)
? median : minimum_reasonable_space;
}
// Return whether the first word on the after line can fit in the space at
// the end of the before line (knowing which way the text is aligned and read).
bool FirstWordWouldHaveFit(const RowScratchRegisters &before,
const RowScratchRegisters &after,
tesseract::ParagraphJustification justification) {
if (before.ri_->num_words == 0 || after.ri_->num_words == 0)
return true;
if (justification == JUSTIFICATION_UNKNOWN) {
tprintf("Don't call FirstWordWouldHaveFit(r, s, JUSTIFICATION_UNKNOWN).\n");
}
int available_space;
if (justification == JUSTIFICATION_CENTER) {
available_space = before.lindent_ + before.rindent_;
} else {
available_space = before.OffsideIndent(justification);
}
available_space -= before.ri_->average_interword_space;
if (before.ri_->ltr)
return after.ri_->lword_box.width() < available_space;
return after.ri_->rword_box.width() < available_space;
}
// Return whether the first word on the after line can fit in the space at
// the end of the before line (not knowing which way the text goes) in a left
// or right alignemnt.
bool FirstWordWouldHaveFit(const RowScratchRegisters &before,
const RowScratchRegisters &after) {
if (before.ri_->num_words == 0 || after.ri_->num_words == 0)
return true;
int available_space = before.lindent_;
if (before.rindent_ > available_space)
available_space = before.rindent_;
available_space -= before.ri_->average_interword_space;
if (before.ri_->ltr)
return after.ri_->lword_box.width() < available_space;
return after.ri_->rword_box.width() < available_space;
}
bool TextSupportsBreak(const RowScratchRegisters &before,
const RowScratchRegisters &after) {
if (before.ri_->ltr) {
return before.ri_->rword_likely_ends_idea &&
after.ri_->lword_likely_starts_idea;
} else {
return before.ri_->lword_likely_ends_idea &&
after.ri_->rword_likely_starts_idea;
}
}
bool LikelyParagraphStart(const RowScratchRegisters &before,
const RowScratchRegisters &after) {
return before.ri_->num_words == 0 ||
(FirstWordWouldHaveFit(before, after) &&
TextSupportsBreak(before, after));
}
bool LikelyParagraphStart(const RowScratchRegisters &before,
const RowScratchRegisters &after,
tesseract::ParagraphJustification j) {
return before.ri_->num_words == 0 ||
(FirstWordWouldHaveFit(before, after, j) &&
TextSupportsBreak(before, after));
}
// Examine rows[start, end) and try to determine what sort of ParagraphModel
// would fit them as a single paragraph.
// If we can't produce a unique model justification_ = JUSTIFICATION_UNKNOWN.
// If the rows given could be a consistent start to a paragraph, set *consistent
// true.
ParagraphModel InternalParagraphModelByOutline(
const GenericVector<RowScratchRegisters> *rows,
int start, int end, int tolerance, bool *consistent) {
int ltr_line_count = 0;
for (int i = start; i < end; i++) {
ltr_line_count += static_cast<int>((*rows)[i].ri_->ltr);
}
bool ltr = (ltr_line_count >= (end - start) / 2);
*consistent = true;
if (!AcceptableRowArgs(0, 2, __func__, rows, start, end))
return ParagraphModel();
// Ensure the caller only passed us a region with a common rmargin and
// lmargin.
int lmargin = (*rows)[start].lmargin_;
int rmargin = (*rows)[start].rmargin_;
int lmin, lmax, rmin, rmax, cmin, cmax;
lmin = lmax = (*rows)[start + 1].lindent_;
rmin = rmax = (*rows)[start + 1].rindent_;
cmin = cmax = 0;
for (int i = start + 1; i < end; i++) {
if ((*rows)[i].lmargin_ != lmargin || (*rows)[i].rmargin_ != rmargin) {
tprintf("Margins don't match! Software error.\n");
*consistent = false;
return ParagraphModel();
}
UpdateRange((*rows)[i].lindent_, &lmin, &lmax);
UpdateRange((*rows)[i].rindent_, &rmin, &rmax);
UpdateRange((*rows)[i].rindent_ - (*rows)[i].lindent_, &cmin, &cmax);
}
int ldiff = lmax - lmin;
int rdiff = rmax - rmin;
int cdiff = cmax - cmin;
if (rdiff > tolerance && ldiff > tolerance) {
if (cdiff < tolerance * 2) {
if (end - start < 3)
return ParagraphModel();
return ParagraphModel(JUSTIFICATION_CENTER, 0, 0, 0, tolerance);
}
*consistent = false;
return ParagraphModel();
}
if (end - start < 3) // Don't return a model for two line paras.
return ParagraphModel();
// These booleans keep us from saying something is aligned left when the body
// left variance is too large.
bool body_admits_left_alignment = ldiff < tolerance;
bool body_admits_right_alignment = rdiff < tolerance;
ParagraphModel left_model =
ParagraphModel(JUSTIFICATION_LEFT, lmargin, (*rows)[start].lindent_,
(lmin + lmax) / 2, tolerance);
ParagraphModel right_model =
ParagraphModel(JUSTIFICATION_RIGHT, rmargin, (*rows)[start].rindent_,
(rmin + rmax) / 2, tolerance);
// These booleans keep us from having an indent on the "wrong side" for the
// first line.
bool text_admits_left_alignment = ltr || left_model.is_flush();
bool text_admits_right_alignment = !ltr || right_model.is_flush();
// At least one of the edges is less than tolerance in variance.
// If the other is obviously ragged, it can't be the one aligned to.
// [Note the last line is included in this raggedness.]
if (tolerance < rdiff) {
if (body_admits_left_alignment && text_admits_left_alignment)
return left_model;
*consistent = false;
return ParagraphModel();
}
if (tolerance < ldiff) {
if (body_admits_right_alignment && text_admits_right_alignment)
return right_model;
*consistent = false;
return ParagraphModel();
}
// At this point, we know the body text doesn't vary much on either side.
// If the first line juts out oddly in one direction or the other,
// that likely indicates the side aligned to.
int first_left = (*rows)[start].lindent_;
int first_right = (*rows)[start].rindent_;
if (ltr && body_admits_left_alignment &&
(first_left < lmin || first_left > lmax))
return left_model;
if (!ltr && body_admits_right_alignment &&
(first_right < rmin || first_right > rmax))
return right_model;
*consistent = false;
return ParagraphModel();
}
// Examine rows[start, end) and try to determine what sort of ParagraphModel
// would fit them as a single paragraph. If nothing fits,
// justification_ = JUSTIFICATION_UNKNOWN and print the paragraph to debug
// output if we're debugging.
ParagraphModel ParagraphModelByOutline(
int debug_level,
const GenericVector<RowScratchRegisters> *rows,
int start, int end, int tolerance) {
bool unused_consistent;
ParagraphModel retval = InternalParagraphModelByOutline(
rows, start, end, tolerance, &unused_consistent);
if (debug_level >= 2 && retval.justification() == JUSTIFICATION_UNKNOWN) {
tprintf("Could not determine a model for this paragraph:\n");
PrintRowRange(*rows, start, end);
}
return retval;
}
// Do rows[start, end) form a single instance of the given paragraph model?
bool RowsFitModel(const GenericVector<RowScratchRegisters> *rows,
int start, int end, const ParagraphModel *model) {
if (!AcceptableRowArgs(0, 1, __func__, rows, start, end))
return false;
if (!ValidFirstLine(rows, start, model)) return false;
for (int i = start + 1 ; i < end; i++) {
if (!ValidBodyLine(rows, i, model)) return false;
}
return true;
}
// Examine rows[row_start, row_end) as an independent section of text,
// and mark rows that are exceptionally clear as start-of-paragraph
// and paragraph-body lines.
//
// We presume that any lines surrounding rows[row_start, row_end) may
// have wildly different paragraph models, so we don't key any data off
// of those lines.
//
// We only take the very strongest signals, as we don't want to get
// confused and marking up centered text, poetry, or source code as
// clearly part of a typical paragraph.
void MarkStrongEvidence(GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end) {
// Record patently obvious body text.
for (int i = row_start + 1; i < row_end; i++) {
const RowScratchRegisters &prev = (*rows)[i - 1];
RowScratchRegisters &curr = (*rows)[i];
tesseract::ParagraphJustification typical_justification =
prev.ri_->ltr ? JUSTIFICATION_LEFT : JUSTIFICATION_RIGHT;
if (!curr.ri_->rword_likely_starts_idea &&
!curr.ri_->lword_likely_starts_idea &&
!FirstWordWouldHaveFit(prev, curr, typical_justification)) {
curr.SetBodyLine();
}
}
// Record patently obvious start paragraph lines.
//
// It's an extremely good signal of the start of a paragraph that
// the first word would have fit on the end of the previous line.
// However, applying just that signal would have us mark random
// start lines of lineated text (poetry and source code) and some
// centered headings as paragraph start lines. Therefore, we use
// a second qualification for a paragraph start: Not only should
// the first word of this line have fit on the previous line,
// but also, this line should go full to the right of the block,
// disallowing a subsequent word from having fit on this line.
// First row:
{
RowScratchRegisters &curr = (*rows)[row_start];
RowScratchRegisters &next = (*rows)[row_start + 1];
tesseract::ParagraphJustification j =
curr.ri_->ltr ? JUSTIFICATION_LEFT : JUSTIFICATION_RIGHT;
if (curr.GetLineType() == LT_UNKNOWN &&
!FirstWordWouldHaveFit(curr, next, j) &&
(curr.ri_->lword_likely_starts_idea ||
curr.ri_->rword_likely_starts_idea)) {
curr.SetStartLine();
}
}
// Middle rows
for (int i = row_start + 1; i < row_end - 1; i++) {
RowScratchRegisters &prev = (*rows)[i - 1];
RowScratchRegisters &curr = (*rows)[i];
RowScratchRegisters &next = (*rows)[i + 1];
tesseract::ParagraphJustification j =
curr.ri_->ltr ? JUSTIFICATION_LEFT : JUSTIFICATION_RIGHT;
if (curr.GetLineType() == LT_UNKNOWN &&
!FirstWordWouldHaveFit(curr, next, j) &&
LikelyParagraphStart(prev, curr, j)) {
curr.SetStartLine();
}
}
// Last row
{ // the short circuit at the top means we have at least two lines.
RowScratchRegisters &prev = (*rows)[row_end - 2];
RowScratchRegisters &curr = (*rows)[row_end - 1];
tesseract::ParagraphJustification j =
curr.ri_->ltr ? JUSTIFICATION_LEFT : JUSTIFICATION_RIGHT;
if (curr.GetLineType() == LT_UNKNOWN &&
!FirstWordWouldHaveFit(curr, curr, j) &&
LikelyParagraphStart(prev, curr, j)) {
curr.SetStartLine();
}
}
}
// Look for sequences of a start line followed by some body lines in
// rows[row_start, row_end) and create ParagraphModels for them if
// they seem coherent.
void ModelStrongEvidence(int debug_level,
GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
bool allow_flush_models,
ParagraphTheory *theory) {
if (!AcceptableRowArgs(debug_level, 2, __func__, rows, row_start, row_end))
return;
int start = row_start;
while (start < row_end) {
while (start < row_end && (*rows)[start].GetLineType() != LT_START)
start++;
if (start >= row_end - 1)
break;
int tolerance = Epsilon((*rows)[start + 1].ri_->average_interword_space);
int end = start;
ParagraphModel last_model;
bool next_consistent;
do {
++end;
// rows[row, end) was consistent.
// If rows[row, end + 1) is not consistent,
// just model rows[row, end)
if (end < row_end - 1) {
RowScratchRegisters &next = (*rows)[end];
LineType lt = next.GetLineType();
next_consistent = lt == LT_BODY ||
(lt == LT_UNKNOWN &&
!FirstWordWouldHaveFit((*rows)[end - 1], (*rows)[end]));
} else {
next_consistent = false;
}
if (next_consistent) {
ParagraphModel next_model = InternalParagraphModelByOutline(
rows, start, end + 1, tolerance, &next_consistent);
if (((*rows)[start].ri_->ltr &&
last_model.justification() == JUSTIFICATION_LEFT &&
next_model.justification() != JUSTIFICATION_LEFT) ||
(!(*rows)[start].ri_->ltr &&
last_model.justification() == JUSTIFICATION_RIGHT &&
next_model.justification() != JUSTIFICATION_RIGHT)) {
next_consistent = false;
}
last_model = next_model;
} else {
next_consistent = false;
}
} while (next_consistent && end < row_end);
// At this point, rows[start, end) looked like it could have been a
// single paragraph. If we can make a good ParagraphModel for it,
// do so and mark this sequence with that model.
if (end > start + 1) {
// emit a new paragraph if we have more than one line.
const ParagraphModel *model = NULL;
ParagraphModel new_model = ParagraphModelByOutline(
debug_level, rows, start, end,
Epsilon(InterwordSpace(*rows, start, end)));
if (new_model.justification() == JUSTIFICATION_UNKNOWN) {
// couldn't create a good model, oh well.
} else if (new_model.is_flush()) {
if (end == start + 2) {
// It's very likely we just got two paragraph starts in a row.
end = start + 1;
} else if (start == row_start) {
// Mark this as a Crown.
if (new_model.justification() == JUSTIFICATION_LEFT) {
model = kCrownLeft;
} else {
model = kCrownRight;
}
} else if (allow_flush_models) {
model = theory->AddModel(new_model);
}
} else {
model = theory->AddModel(new_model);
}
if (model) {
(*rows)[start].AddStartLine(model);
for (int i = start + 1; i < end; i++) {
(*rows)[i].AddBodyLine(model);
}
}
}
start = end;
}
}
// We examine rows[row_start, row_end) and do the following:
// (1) Clear all existing hypotheses for the rows being considered.
// (2) Mark up any rows as exceptionally likely to be paragraph starts
// or paragraph body lines as such using both geometric and textual
// clues.
// (3) Form models for any sequence of start + continuation lines.
// (4) Smear the paragraph models to cover surrounding text.
void StrongEvidenceClassify(int debug_level,
GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
ParagraphTheory *theory) {
if (!AcceptableRowArgs(debug_level, 2, __func__, rows, row_start, row_end))
return;
if (debug_level > 1) {
tprintf("#############################################\n");
tprintf("# StrongEvidenceClassify( rows[%d:%d) )\n", row_start, row_end);
tprintf("#############################################\n");
}
RecomputeMarginsAndClearHypotheses(rows, row_start, row_end, 10);
MarkStrongEvidence(rows, row_start, row_end);
DebugDump(debug_level > 2, "Initial strong signals.", *theory, *rows);
// Create paragraph models.
ModelStrongEvidence(debug_level, rows, row_start, row_end, false, theory);
DebugDump(debug_level > 2, "Unsmeared hypotheses.s.", *theory, *rows);
// At this point, some rows are marked up as paragraphs with model numbers,
// and some rows are marked up as either LT_START or LT_BODY. Now let's
// smear any good paragraph hypotheses forward and backward.
ParagraphModelSmearer smearer(rows, row_start, row_end, theory);
smearer.Smear();
}
void SeparateSimpleLeaderLines(GenericVector<RowScratchRegisters> *rows,
int row_start, int row_end,
ParagraphTheory *theory) {
for (int i = row_start + 1; i < row_end - 1; i++) {
if ((*rows)[i - 1].ri_->has_leaders &&
(*rows)[i].ri_->has_leaders &&
(*rows)[i + 1].ri_->has_leaders) {
const ParagraphModel *model = theory->AddModel(
ParagraphModel(JUSTIFICATION_UNKNOWN, 0, 0, 0, 0));
(*rows)[i].AddStartLine(model);
}
}
}
// Collect sequences of unique hypotheses in row registers and create proper
// paragraphs for them, referencing the paragraphs in row_owners.
void ConvertHypothesizedModelRunsToParagraphs(
int debug_level,
const GenericVector<RowScratchRegisters> &rows,
GenericVector<PARA *> *row_owners,
ParagraphTheory *theory) {
int end = rows.size();
int start;
for (; end > 0; end = start) {
start = end - 1;
const ParagraphModel *model = NULL;
// TODO(eger): Be smarter about dealing with multiple hypotheses.
bool single_line_paragraph = false;
SetOfModels models;
rows[start].NonNullHypotheses(&models);
if (models.size() > 0) {
model = models[0];
if (rows[start].GetLineType(model) != LT_BODY)
single_line_paragraph = true;
}
if (model && !single_line_paragraph) {
// walk back looking for more body lines and then a start line.
while (--start > 0 && rows[start].GetLineType(model) == LT_BODY) {
// do nothing
}
if (start < 0 || rows[start].GetLineType(model) != LT_START) {
model = NULL;
}
}
if (model == NULL) {
continue;
}
// rows[start, end) should be a paragraph.
PARA *p = new PARA();
if (model == kCrownLeft || model == kCrownRight) {
p->is_very_first_or_continuation = true;
// Crown paragraph.
// If we can find an existing ParagraphModel that fits, use it,
// else create a new one.
for (int row = end; row < rows.size(); row++) {
if ((*row_owners)[row] &&
(ValidBodyLine(&rows, start, (*row_owners)[row]->model) &&
(start == 0 ||
ValidFirstLine(&rows, start, (*row_owners)[row]->model)))) {
model = (*row_owners)[row]->model;
break;
}
}
if (model == kCrownLeft) {
// No subsequent model fits, so cons one up.
model = theory->AddModel(ParagraphModel(
JUSTIFICATION_LEFT, rows[start].lmargin_ + rows[start].lindent_,
0, 0, Epsilon(rows[start].ri_->average_interword_space)));
} else if (model == kCrownRight) {
// No subsequent model fits, so cons one up.
model = theory->AddModel(ParagraphModel(
JUSTIFICATION_RIGHT, rows[start].rmargin_ + rows[start].rmargin_,
0, 0, Epsilon(rows[start].ri_->average_interword_space)));
}
}
rows[start].SetUnknown();
rows[start].AddStartLine(model);
for (int i = start + 1; i < end; i++) {
rows[i].SetUnknown();
rows[i].AddBodyLine(model);
}
p->model = model;
p->has_drop_cap = rows[start].ri_->has_drop_cap;
p->is_list_item =
model->justification() == JUSTIFICATION_RIGHT
? rows[start].ri_->rword_indicates_list_item
: rows[start].ri_->lword_indicates_list_item;
for (int row = start; row < end; row++) {
if ((*row_owners)[row] != NULL) {
tprintf("Memory leak! ConvertHypothesizeModelRunsToParagraphs() called "
"more than once!\n");
}
(*row_owners)[row] = p;
}
}
}
struct Interval {
Interval() : begin(0), end(0) {}
Interval(int b, int e) : begin(b), end(e) {}
int begin;
int end;
};
// Return whether rows[row] appears to be stranded, meaning that the evidence
// for this row is very weak due to context. For instance, two lines of source
// code may happen to be indented at the same tab vector as body text starts,
// leading us to think they are two start-of-paragraph lines. This is not
// optimal. However, we also don't want to mark a sequence of short dialog
// as "weak," so our heuristic is:
// (1) If a line is surrounded by lines of unknown type, it's weak.
// (2) If two lines in a row are start lines for a given paragraph type, but
// after that the same paragraph type does not continue, they're weak.
bool RowIsStranded(const GenericVector<RowScratchRegisters> &rows, int row) {
SetOfModels row_models;
rows[row].StrongHypotheses(&row_models);
for (int m = 0; m < row_models.size(); m++) {
bool all_starts = rows[row].GetLineType();
int run_length = 1;
bool continues = true;
for (int i = row - 1; i >= 0 && continues; i--) {
SetOfModels models;
rows[i].NonNullHypotheses(&models);
switch (rows[i].GetLineType(row_models[m])) {
case LT_START: run_length++; break;
case LT_MULTIPLE: // explicit fall-through
case LT_BODY: run_length++; all_starts = false; break;
case LT_UNKNOWN: // explicit fall-through
default: continues = false;
}
}
continues = true;
for (int i = row + 1; i < rows.size() && continues; i++) {
SetOfModels models;
rows[i].NonNullHypotheses(&models);
switch (rows[i].GetLineType(row_models[m])) {
case LT_START: run_length++; break;
case LT_MULTIPLE: // explicit fall-through
case LT_BODY: run_length++; all_starts = false; break;
case LT_UNKNOWN: // explicit fall-through
default: continues = false;
}
}
if (run_length > 2 || (!all_starts && run_length > 1)) return false;
}
return true;
}
// Go through rows[row_start, row_end) and gather up sequences that need better
// classification.
// + Sequences of non-empty rows without hypotheses.
// + Crown paragraphs not immediately followed by a strongly modeled line.
// + Single line paragraphs surrounded by text that doesn't match the
// model.
void LeftoverSegments(const GenericVector<RowScratchRegisters> &rows,
GenericVector<Interval> *to_fix,
int row_start, int row_end) {
to_fix->clear();
for (int i = row_start; i < row_end; i++) {
bool needs_fixing = false;
SetOfModels models;
SetOfModels models_w_crowns;
rows[i].StrongHypotheses(&models);
rows[i].NonNullHypotheses(&models_w_crowns);
if (models.empty() && models_w_crowns.size() > 0) {
// Crown paragraph. Is it followed by a modeled line?
for (int end = i + 1; end < rows.size(); end++) {
SetOfModels end_models;
SetOfModels strong_end_models;
rows[end].NonNullHypotheses(&end_models);
rows[end].StrongHypotheses(&strong_end_models);
if (end_models.size() == 0) {
needs_fixing = true;
break;
} else if (strong_end_models.size() > 0) {
needs_fixing = false;
break;
}
}
} else if (models.empty() && rows[i].ri_->num_words > 0) {
// No models at all.
needs_fixing = true;
}
if (!needs_fixing && !models.empty()) {
needs_fixing = RowIsStranded(rows, i);
}
if (needs_fixing) {
if (!to_fix->empty() && to_fix->back().end == i - 1)
to_fix->back().end = i;
else
to_fix->push_back(Interval(i, i));
}
}
// Convert inclusive intervals to half-open intervals.
for (int i = 0; i < to_fix->size(); i++) {
(*to_fix)[i].end = (*to_fix)[i].end + 1;
}
}
// Given a set of row_owners pointing to PARAs or NULL (no paragraph known),
// normalize each row_owner to point to an actual PARA, and output the
// paragraphs in order onto paragraphs.
void CanonicalizeDetectionResults(
GenericVector<PARA *> *row_owners,
PARA_LIST *paragraphs) {
GenericVector<PARA *> &rows = *row_owners;
paragraphs->clear();
PARA_IT out(paragraphs);
PARA *formerly_null = NULL;
for (int i = 0; i < rows.size(); i++) {
if (rows[i] == NULL) {
if (i == 0 || rows[i - 1] != formerly_null) {
rows[i] = formerly_null = new PARA();
} else {
rows[i] = formerly_null;
continue;
}
} else if (i > 0 && rows[i - 1] == rows[i]) {
continue;
}
out.add_after_then_move(rows[i]);
}
}
// Main entry point for Paragraph Detection Algorithm.
//
// Given a set of equally spaced textlines (described by row_infos),
// Split them into paragraphs.
//
// Output:
// row_owners - one pointer for each row, to the paragraph it belongs to.
// paragraphs - this is the actual list of PARA objects.
// models - the list of paragraph models referenced by the PARA objects.
// caller is responsible for deleting the models.
void DetectParagraphs(int debug_level,
GenericVector<RowInfo> *row_infos,
GenericVector<PARA *> *row_owners,
PARA_LIST *paragraphs,
GenericVector<ParagraphModel *> *models) {
GenericVector<RowScratchRegisters> rows;
ParagraphTheory theory(models);
// Initialize row_owners to be a bunch of NULL pointers.
row_owners->init_to_size(row_infos->size(), NULL);
// Set up row scratch registers for the main algorithm.
rows.init_to_size(row_infos->size(), RowScratchRegisters());
for (int i = 0; i < row_infos->size(); i++) {
rows[i].Init((*row_infos)[i]);
}
// Pass 1:
// Detect sequences of lines that all contain leader dots (.....)
// These are likely Tables of Contents. If there are three text lines in
// a row with leader dots, it's pretty safe to say the middle one should
// be a paragraph of its own.
SeparateSimpleLeaderLines(&rows, 0, rows.size(), &theory);
DebugDump(debug_level > 1, "End of Pass 1", theory, rows);
GenericVector<Interval> leftovers;
LeftoverSegments(rows, &leftovers, 0, rows.size());
for (int i = 0; i < leftovers.size(); i++) {
// Pass 2a:
// Find any strongly evidenced start-of-paragraph lines. If they're
// followed by two lines that look like body lines, make a paragraph
// model for that and see if that model applies throughout the text
// (that is, "smear" it).
StrongEvidenceClassify(debug_level, &rows,
leftovers[i].begin, leftovers[i].end, &theory);
// Pass 2b:
// If we had any luck in pass 2a, we got part of the page and didn't
// know how to classify a few runs of rows. Take the segments that
// didn't find a model and reprocess them individually.
GenericVector<Interval> leftovers2;
LeftoverSegments(rows, &leftovers2, leftovers[i].begin, leftovers[i].end);
bool pass2a_was_useful = leftovers2.size() > 1 ||
(leftovers2.size() == 1 &&
(leftovers2[0].begin != 0 || leftovers2[0].end != rows.size()));
if (pass2a_was_useful) {
for (int j = 0; j < leftovers2.size(); j++) {
StrongEvidenceClassify(debug_level, &rows,
leftovers2[j].begin, leftovers2[j].end,
&theory);
}
}
}
DebugDump(debug_level > 1, "End of Pass 2", theory, rows);
// Pass 3:
// These are the dregs for which we didn't have enough strong textual
// and geometric clues to form matching models for. Let's see if
// the geometric clues are simple enough that we could just use those.
LeftoverSegments(rows, &leftovers, 0, rows.size());
for (int i = 0; i < leftovers.size(); i++) {
GeometricClassify(debug_level, &rows,
leftovers[i].begin, leftovers[i].end, &theory);
}
// Undo any flush models for which there's little evidence.
DowngradeWeakestToCrowns(debug_level, &theory, &rows);
DebugDump(debug_level > 1, "End of Pass 3", theory, rows);
// Pass 4:
// Take everything that's still not marked up well and clear all markings.
LeftoverSegments(rows, &leftovers, 0, rows.size());
for (int i = 0; i < leftovers.size(); i++) {
for (int j = leftovers[i].begin; j < leftovers[i].end; j++) {
rows[j].SetUnknown();
}
}
DebugDump(debug_level > 1, "End of Pass 4", theory, rows);
// Convert all of the unique hypothesis runs to PARAs.
ConvertHypothesizedModelRunsToParagraphs(debug_level, rows, row_owners,
&theory);
DebugDump(debug_level > 0, "Final Paragraph Segmentation", theory, rows);
// Finally, clean up any dangling NULL row paragraph parents.
CanonicalizeDetectionResults(row_owners, paragraphs);
}
// ============ Code interfacing with the rest of Tesseract ==================
void InitializeTextAndBoxesPreRecognition(const MutableIterator &it,
RowInfo *info) {
// Set up text, lword_text, and rword_text (mostly for debug printing).
STRING fake_text;
PageIterator pit(static_cast<const PageIterator&>(it));
bool first_word = true;
if (!pit.Empty(RIL_WORD)) {
do {
fake_text += "x";
if (first_word) info->lword_text += "x";
info->rword_text += "x";
if (pit.IsAtFinalElement(RIL_WORD, RIL_SYMBOL) &&
!pit.IsAtFinalElement(RIL_TEXTLINE, RIL_SYMBOL)) {
fake_text += " ";
info->rword_text = "";
first_word = false;
}
} while (!pit.IsAtFinalElement(RIL_TEXTLINE, RIL_SYMBOL) &&
pit.Next(RIL_SYMBOL));
}
if (fake_text.size() == 0) return;
int lspaces = info->pix_ldistance / info->average_interword_space;
for (int i = 0; i < lspaces; i++) {
info->text += ' ';
}
info->text += fake_text;
// Set up lword_box, rword_box, and num_words.
PAGE_RES_IT page_res_it = *it.PageResIt();
WERD_RES *word_res = page_res_it.restart_row();
ROW_RES *this_row = page_res_it.row();
WERD_RES *lword = NULL;
WERD_RES *rword = NULL;
info->num_words = 0;
do {
if (word_res) {
if (!lword) lword = word_res;
if (rword != word_res) info->num_words++;
rword = word_res;
}
word_res = page_res_it.forward();
} while (page_res_it.row() == this_row);
info->lword_box = lword->word->bounding_box();
info->rword_box = rword->word->bounding_box();
}
// Given a Tesseract Iterator pointing to a text line, fill in the paragraph
// detector RowInfo with all relevant information from the row.
void InitializeRowInfo(bool after_recognition,
const MutableIterator &it,
RowInfo *info) {
if (it.PageResIt()->row() != NULL) {
ROW *row = it.PageResIt()->row()->row;
info->pix_ldistance = row->lmargin();
info->pix_rdistance = row->rmargin();
info->average_interword_space =
row->space() > 0 ? row->space() : MAX(row->x_height(), 1);
info->pix_xheight = row->x_height();
info->has_leaders = false;
info->has_drop_cap = row->has_drop_cap();
info->ltr = true; // set below depending on word scripts
} else {
info->pix_ldistance = info->pix_rdistance = 0;
info->average_interword_space = 1;
info->pix_xheight = 1.0;
info->has_leaders = false;
info->has_drop_cap = false;
info->ltr = true;
}
info->num_words = 0;
info->lword_indicates_list_item = false;
info->lword_likely_starts_idea = false;
info->lword_likely_ends_idea = false;
info->rword_indicates_list_item = false;
info->rword_likely_starts_idea = false;
info->rword_likely_ends_idea = false;
info->has_leaders = false;
info->ltr = 1;
if (!after_recognition) {
InitializeTextAndBoxesPreRecognition(it, info);
return;
}
info->text = "";
char *text = it.GetUTF8Text(RIL_TEXTLINE);
int trailing_ws_idx = strlen(text); // strip trailing space
while (trailing_ws_idx > 0 &&
// isspace() only takes ASCII
((text[trailing_ws_idx - 1] & 0x80) == 0) &&
isspace(text[trailing_ws_idx - 1]))
trailing_ws_idx--;
if (trailing_ws_idx > 0) {
int lspaces = info->pix_ldistance / info->average_interword_space;
for (int i = 0; i < lspaces; i++)
info->text += ' ';
for (int i = 0; i < trailing_ws_idx; i++)
info->text += text[i];
}
delete []text;
if (info->text.size() == 0) {
return;
}
PAGE_RES_IT page_res_it = *it.PageResIt();
GenericVector<WERD_RES *> werds;
WERD_RES *word_res = page_res_it.restart_row();
ROW_RES *this_row = page_res_it.row();
int num_leaders = 0;
int ltr = 0;
int rtl = 0;
do {
if (word_res && word_res->best_choice->unichar_string().length() > 0) {
werds.push_back(word_res);
ltr += word_res->AnyLtrCharsInWord() ? 1 : 0;
rtl += word_res->AnyRtlCharsInWord() ? 1 : 0;
if (word_res->word->flag(W_REP_CHAR)) num_leaders++;
}
word_res = page_res_it.forward();
} while (page_res_it.row() == this_row);
info->ltr = ltr >= rtl;
info->has_leaders = num_leaders > 3;
info->num_words = werds.size();
if (werds.size() > 0) {
WERD_RES *lword = werds[0], *rword = werds[werds.size() - 1];
info->lword_text = lword->best_choice->unichar_string().string();
info->rword_text = rword->best_choice->unichar_string().string();
info->lword_box = lword->word->bounding_box();
info->rword_box = rword->word->bounding_box();
LeftWordAttributes(lword->uch_set, lword->best_choice,
info->lword_text,
&info->lword_indicates_list_item,
&info->lword_likely_starts_idea,
&info->lword_likely_ends_idea);
RightWordAttributes(rword->uch_set, rword->best_choice,
info->rword_text,
&info->rword_indicates_list_item,
&info->rword_likely_starts_idea,
&info->rword_likely_ends_idea);
}
}
// This is called after rows have been identified and words are recognized.
// Much of this could be implemented before word recognition, but text helps
// to identify bulleted lists and gives good signals for sentence boundaries.
void DetectParagraphs(int debug_level,
bool after_text_recognition,
const MutableIterator *block_start,
GenericVector<ParagraphModel *> *models) {
// Clear out any preconceived notions.
if (block_start->Empty(RIL_TEXTLINE)) {
return;
}
BLOCK *block = block_start->PageResIt()->block()->block;
block->para_list()->clear();
bool is_image_block = block->poly_block() && !block->poly_block()->IsText();
// Convert the Tesseract structures to RowInfos
// for the paragraph detection algorithm.
MutableIterator row(*block_start);
if (row.Empty(RIL_TEXTLINE))
return; // end of input already.
GenericVector<RowInfo> row_infos;
do {
if (!row.PageResIt()->row())
continue; // empty row.
row.PageResIt()->row()->row->set_para(NULL);
row_infos.push_back(RowInfo());
RowInfo &ri = row_infos.back();
InitializeRowInfo(after_text_recognition, row, &ri);
} while (!row.IsAtFinalElement(RIL_BLOCK, RIL_TEXTLINE) &&
row.Next(RIL_TEXTLINE));
// If we're called before text recognition, we might not have
// tight block bounding boxes, so trim by the minimum on each side.
if (row_infos.size() > 0) {
int min_lmargin = row_infos[0].pix_ldistance;
int min_rmargin = row_infos[0].pix_rdistance;
for (int i = 1; i < row_infos.size(); i++) {
if (row_infos[i].pix_ldistance < min_lmargin)
min_lmargin = row_infos[i].pix_ldistance;
if (row_infos[i].pix_rdistance < min_rmargin)
min_rmargin = row_infos[i].pix_rdistance;
}
if (min_lmargin > 0 || min_rmargin > 0) {
for (int i = 0; i < row_infos.size(); i++) {
row_infos[i].pix_ldistance -= min_lmargin;
row_infos[i].pix_rdistance -= min_rmargin;
}
}
}
// Run the paragraph detection algorithm.
GenericVector<PARA *> row_owners;
GenericVector<PARA *> the_paragraphs;
if (!is_image_block) {
DetectParagraphs(debug_level, &row_infos, &row_owners, block->para_list(),
models);
} else {
row_owners.init_to_size(row_infos.size(), NULL);
CanonicalizeDetectionResults(&row_owners, block->para_list());
}
// Now stitch in the row_owners into the rows.
row = *block_start;
for (int i = 0; i < row_owners.size(); i++) {
while (!row.PageResIt()->row())
row.Next(RIL_TEXTLINE);
row.PageResIt()->row()->row->set_para(row_owners[i]);
row.Next(RIL_TEXTLINE);
}
}
} // namespace
| C++ |
///////////////////////////////////////////////////////////////////////
// File: ltrresultiterator.h
// Description: Iterator for tesseract results in strict left-to-right
// order that avoids using tesseract internal data structures.
// Author: Ray Smith
// Created: Fri Feb 26 11:01:06 PST 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_LTR_RESULT_ITERATOR_H__
#define TESSERACT_CCMAIN_LTR_RESULT_ITERATOR_H__
#include "platform.h"
#include "pageiterator.h"
#include "unichar.h"
class BLOB_CHOICE_IT;
class WERD_RES;
namespace tesseract {
class Tesseract;
// Class to iterate over tesseract results, providing access to all levels
// of the page hierarchy, without including any tesseract headers or having
// to handle any tesseract structures.
// WARNING! This class points to data held within the TessBaseAPI class, and
// therefore can only be used while the TessBaseAPI class still exists and
// has not been subjected to a call of Init, SetImage, Recognize, Clear, End
// DetectOS, or anything else that changes the internal PAGE_RES.
// See apitypes.h for the definition of PageIteratorLevel.
// See also base class PageIterator, which contains the bulk of the interface.
// LTRResultIterator adds text-specific methods for access to OCR output.
class TESS_API LTRResultIterator : public PageIterator {
friend class ChoiceIterator;
public:
// page_res and tesseract come directly from the BaseAPI.
// The rectangle parameters are copied indirectly from the Thresholder,
// via the BaseAPI. They represent the coordinates of some rectangle in an
// original image (in top-left-origin coordinates) and therefore the top-left
// needs to be added to any output boxes in order to specify coordinates
// in the original image. See TessBaseAPI::SetRectangle.
// The scale and scaled_yres are in case the Thresholder scaled the image
// rectangle prior to thresholding. Any coordinates in tesseract's image
// must be divided by scale before adding (rect_left, rect_top).
// The scaled_yres indicates the effective resolution of the binary image
// that tesseract has been given by the Thresholder.
// After the constructor, Begin has already been called.
LTRResultIterator(PAGE_RES* page_res, Tesseract* tesseract,
int scale, int scaled_yres,
int rect_left, int rect_top,
int rect_width, int rect_height);
virtual ~LTRResultIterator();
// LTRResultIterators may be copied! This makes it possible to iterate over
// all the objects at a lower level, while maintaining an iterator to
// objects at a higher level. These constructors DO NOT CALL Begin, so
// iterations will continue from the location of src.
// TODO: For now the copy constructor and operator= only need the base class
// versions, but if new data members are added, don't forget to add them!
// ============= Moving around within the page ============.
// See PageIterator.
// ============= Accessing data ==============.
// Returns the null terminated UTF-8 encoded text string for the current
// object at the given level. Use delete [] to free after use.
char* GetUTF8Text(PageIteratorLevel level) const;
// Set the string inserted at the end of each text line. "\n" by default.
void SetLineSeparator(const char *new_line);
// Set the string inserted at the end of each paragraph. "\n" by default.
void SetParagraphSeparator(const char *new_para);
// Returns the mean confidence of the current object at the given level.
// The number should be interpreted as a percent probability. (0.0f-100.0f)
float Confidence(PageIteratorLevel level) const;
// ============= Functions that refer to words only ============.
// Returns the font attributes of the current word. If iterating at a higher
// level object than words, eg textlines, then this will return the
// attributes of the first word in that textline.
// The actual return value is a string representing a font name. It points
// to an internal table and SHOULD NOT BE DELETED. Lifespan is the same as
// the iterator itself, ie rendered invalid by various members of
// TessBaseAPI, including Init, SetImage, End or deleting the TessBaseAPI.
// Pointsize is returned in printers points (1/72 inch.)
const char* WordFontAttributes(bool* is_bold,
bool* is_italic,
bool* is_underlined,
bool* is_monospace,
bool* is_serif,
bool* is_smallcaps,
int* pointsize,
int* font_id) const;
// Return the name of the language used to recognize this word.
// On error, NULL. Do not delete this pointer.
const char* WordRecognitionLanguage() const;
// Return the overall directionality of this word.
StrongScriptDirection WordDirection() const;
// Returns true if the current word was found in a dictionary.
bool WordIsFromDictionary() const;
// Returns true if the current word is numeric.
bool WordIsNumeric() const;
// Returns true if the word contains blamer information.
bool HasBlamerInfo() const;
// Returns the pointer to ParamsTrainingBundle stored in the BlamerBundle
// of the current word.
const void *GetParamsTrainingBundle() const;
// Returns a pointer to the string with blamer information for this word.
// Assumes that the word's blamer_bundle is not NULL.
const char *GetBlamerDebug() const;
// Returns a pointer to the string with misadaption information for this word.
// Assumes that the word's blamer_bundle is not NULL.
const char *GetBlamerMisadaptionDebug() const;
// Returns true if a truth string was recorded for the current word.
bool HasTruthString() const;
// Returns true if the given string is equivalent to the truth string for
// the current word.
bool EquivalentToTruth(const char *str) const;
// Returns a null terminated UTF-8 encoded truth string for the current word.
// Use delete [] to free after use.
char* WordTruthUTF8Text() const;
// Returns a null terminated UTF-8 encoded normalized OCR string for the
// current word. Use delete [] to free after use.
char* WordNormedUTF8Text() const;
// Returns a pointer to serialized choice lattice.
// Fills lattice_size with the number of bytes in lattice data.
const char *WordLattice(int *lattice_size) const;
// ============= Functions that refer to symbols only ============.
// Returns true if the current symbol is a superscript.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool SymbolIsSuperscript() const;
// Returns true if the current symbol is a subscript.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool SymbolIsSubscript() const;
// Returns true if the current symbol is a dropcap.
// If iterating at a higher level object than symbols, eg words, then
// this will return the attributes of the first symbol in that word.
bool SymbolIsDropcap() const;
protected:
const char *line_separator_;
const char *paragraph_separator_;
};
// Class to iterate over the classifier choices for a single RIL_SYMBOL.
class ChoiceIterator {
public:
// Construction is from a LTRResultIterator that points to the symbol of
// interest. The ChoiceIterator allows a one-shot iteration over the
// choices for this symbol and after that is is useless.
explicit ChoiceIterator(const LTRResultIterator& result_it);
~ChoiceIterator();
// Moves to the next choice for the symbol and returns false if there
// are none left.
bool Next();
// ============= Accessing data ==============.
// Returns the null terminated UTF-8 encoded text string for the current
// choice.
// NOTE: Unlike LTRResultIterator::GetUTF8Text, the return points to an
// internal structure and should NOT be delete[]ed to free after use.
const char* GetUTF8Text() const;
// Returns the confidence of the current choice.
// The number should be interpreted as a percent probability. (0.0f-100.0f)
float Confidence() const;
private:
// Pointer to the WERD_RES object owned by the API.
WERD_RES* word_res_;
// Iterator over the blob choices.
BLOB_CHOICE_IT* choice_it_;
};
} // namespace tesseract.
#endif // TESSERACT_CCMAIN_LTR_RESULT_ITERATOR_H__
| C++ |
///////////////////////////////////////////////////////////////////////
// File: osdetect.cpp
// Description: Orientation and script detection.
// Author: Samuel Charron
// Ranjith Unnikrishnan
//
// (C) Copyright 2008, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "osdetect.h"
#include "blobbox.h"
#include "blread.h"
#include "colfind.h"
#include "fontinfo.h"
#include "imagefind.h"
#include "linefind.h"
#include "oldlist.h"
#include "qrsequence.h"
#include "ratngs.h"
#include "strngs.h"
#include "tabvector.h"
#include "tesseractclass.h"
#include "textord.h"
const int kMinCharactersToTry = 50;
const int kMaxCharactersToTry = 5 * kMinCharactersToTry;
const float kSizeRatioToReject = 2.0;
const int kMinAcceptableBlobHeight = 10;
const float kOrientationAcceptRatio = 1.3;
const float kScriptAcceptRatio = 1.3;
const float kHanRatioInKorean = 0.7;
const float kHanRatioInJapanese = 0.3;
const float kNonAmbiguousMargin = 1.0;
// General scripts
static const char* han_script = "Han";
static const char* latin_script = "Latin";
static const char* katakana_script = "Katakana";
static const char* hiragana_script = "Hiragana";
static const char* hangul_script = "Hangul";
// Pseudo-scripts Name
const char* ScriptDetector::korean_script_ = "Korean";
const char* ScriptDetector::japanese_script_ = "Japanese";
const char* ScriptDetector::fraktur_script_ = "Fraktur";
// Minimum believable resolution.
const int kMinCredibleResolution = 70;
// Default resolution used if input is not believable.
const int kDefaultResolution = 300;
void OSResults::update_best_orientation() {
float first = orientations[0];
float second = orientations[1];
best_result.orientation_id = 0;
if (orientations[0] < orientations[1]) {
first = orientations[1];
second = orientations[0];
best_result.orientation_id = 1;
}
for (int i = 2; i < 4; ++i) {
if (orientations[i] > first) {
second = first;
first = orientations[i];
best_result.orientation_id = i;
} else if (orientations[i] > second) {
second = orientations[i];
}
}
// Store difference of top two orientation scores.
best_result.oconfidence = first - second;
}
void OSResults::set_best_orientation(int orientation_id) {
best_result.orientation_id = orientation_id;
best_result.oconfidence = 0;
}
void OSResults::update_best_script(int orientation) {
// We skip index 0 to ignore the "Common" script.
float first = scripts_na[orientation][1];
float second = scripts_na[orientation][2];
best_result.script_id = 1;
if (scripts_na[orientation][1] < scripts_na[orientation][2]) {
first = scripts_na[orientation][2];
second = scripts_na[orientation][1];
best_result.script_id = 2;
}
for (int i = 3; i < kMaxNumberOfScripts; ++i) {
if (scripts_na[orientation][i] > first) {
best_result.script_id = i;
second = first;
first = scripts_na[orientation][i];
} else if (scripts_na[orientation][i] > second) {
second = scripts_na[orientation][i];
}
}
best_result.sconfidence =
(first / second - 1.0) / (kScriptAcceptRatio - 1.0);
}
int OSResults::get_best_script(int orientation_id) const {
int max_id = -1;
for (int j = 0; j < kMaxNumberOfScripts; ++j) {
const char *script = unicharset->get_script_from_script_id(j);
if (strcmp(script, "Common") && strcmp(script, "NULL")) {
if (max_id == -1 ||
scripts_na[orientation_id][j] > scripts_na[orientation_id][max_id])
max_id = j;
}
}
return max_id;
}
// Print the script scores for all possible orientations.
void OSResults::print_scores(void) const {
for (int i = 0; i < 4; ++i) {
tprintf("Orientation id #%d", i);
print_scores(i);
}
}
// Print the script scores for the given candidate orientation.
void OSResults::print_scores(int orientation_id) const {
for (int j = 0; j < kMaxNumberOfScripts; ++j) {
if (scripts_na[orientation_id][j]) {
tprintf("%12s\t: %f\n", unicharset->get_script_from_script_id(j),
scripts_na[orientation_id][j]);
}
}
}
// Accumulate scores with given OSResults instance and update the best script.
void OSResults::accumulate(const OSResults& osr) {
for (int i = 0; i < 4; ++i) {
orientations[i] += osr.orientations[i];
for (int j = 0; j < kMaxNumberOfScripts; ++j)
scripts_na[i][j] += osr.scripts_na[i][j];
}
unicharset = osr.unicharset;
update_best_orientation();
update_best_script(best_result.orientation_id);
}
// Detect and erase horizontal/vertical lines and picture regions from the
// image, so that non-text blobs are removed from consideration.
void remove_nontext_regions(tesseract::Tesseract *tess, BLOCK_LIST *blocks,
TO_BLOCK_LIST *to_blocks) {
Pix *pix = tess->pix_binary();
ASSERT_HOST(pix != NULL);
int vertical_x = 0;
int vertical_y = 1;
tesseract::TabVector_LIST v_lines;
tesseract::TabVector_LIST h_lines;
const int kMinCredibleResolution = 70;
int resolution = (kMinCredibleResolution > pixGetXRes(pix)) ?
kMinCredibleResolution : pixGetXRes(pix);
tesseract::LineFinder::FindAndRemoveLines(resolution, false, pix,
&vertical_x, &vertical_y,
NULL, &v_lines, &h_lines);
Pix* im_pix = tesseract::ImageFind::FindImages(pix);
if (im_pix != NULL) {
pixSubtract(pix, pix, im_pix);
pixDestroy(&im_pix);
}
tess->mutable_textord()->find_components(tess->pix_binary(),
blocks, to_blocks);
}
// Find connected components in the page and process a subset until finished or
// a stopping criterion is met.
// Returns the number of blobs used in making the estimate. 0 implies failure.
int orientation_and_script_detection(STRING& filename,
OSResults* osr,
tesseract::Tesseract* tess) {
STRING name = filename; //truncated name
const char *lastdot; //of name
TBOX page_box;
lastdot = strrchr (name.string (), '.');
if (lastdot != NULL)
name[lastdot-name.string()] = '\0';
ASSERT_HOST(tess->pix_binary() != NULL)
int width = pixGetWidth(tess->pix_binary());
int height = pixGetHeight(tess->pix_binary());
BLOCK_LIST blocks;
if (!read_unlv_file(name, width, height, &blocks))
FullPageBlock(width, height, &blocks);
// Try to remove non-text regions from consideration.
TO_BLOCK_LIST land_blocks, port_blocks;
remove_nontext_regions(tess, &blocks, &port_blocks);
if (port_blocks.empty()) {
// page segmentation did not succeed, so we need to find_components first.
tess->mutable_textord()->find_components(tess->pix_binary(),
&blocks, &port_blocks);
} else {
page_box.set_left(0);
page_box.set_bottom(0);
page_box.set_right(width);
page_box.set_top(height);
// Filter_blobs sets up the TO_BLOCKs the same as find_components does.
tess->mutable_textord()->filter_blobs(page_box.topright(),
&port_blocks, true);
}
return os_detect(&port_blocks, osr, tess);
}
// Filter and sample the blobs.
// Returns a non-zero number of blobs if the page was successfully processed, or
// zero if the page had too few characters to be reliable
int os_detect(TO_BLOCK_LIST* port_blocks, OSResults* osr,
tesseract::Tesseract* tess) {
int blobs_total = 0;
TO_BLOCK_IT block_it;
block_it.set_to_list(port_blocks);
BLOBNBOX_CLIST filtered_list;
BLOBNBOX_C_IT filtered_it(&filtered_list);
for (block_it.mark_cycle_pt(); !block_it.cycled_list();
block_it.forward ()) {
TO_BLOCK* to_block = block_it.data();
if (to_block->block->poly_block() &&
!to_block->block->poly_block()->IsText()) continue;
BLOBNBOX_IT bbox_it;
bbox_it.set_to_list(&to_block->blobs);
for (bbox_it.mark_cycle_pt (); !bbox_it.cycled_list ();
bbox_it.forward ()) {
BLOBNBOX* bbox = bbox_it.data();
C_BLOB* blob = bbox->cblob();
TBOX box = blob->bounding_box();
++blobs_total;
float y_x = fabs((box.height() * 1.0) / box.width());
float x_y = 1.0f / y_x;
// Select a >= 1.0 ratio
float ratio = x_y > y_x ? x_y : y_x;
// Blob is ambiguous
if (ratio > kSizeRatioToReject) continue;
if (box.height() < kMinAcceptableBlobHeight) continue;
filtered_it.add_to_end(bbox);
}
}
return os_detect_blobs(NULL, &filtered_list, osr, tess);
}
// Detect orientation and script from a list of blobs.
// Returns a non-zero number of blobs if the list was successfully processed, or
// zero if the list had too few characters to be reliable.
// If allowed_scripts is non-null and non-empty, it is a list of scripts that
// constrains both orientation and script detection to consider only scripts
// from the list.
int os_detect_blobs(const GenericVector<int>* allowed_scripts,
BLOBNBOX_CLIST* blob_list, OSResults* osr,
tesseract::Tesseract* tess) {
OSResults osr_;
if (osr == NULL)
osr = &osr_;
osr->unicharset = &tess->unicharset;
OrientationDetector o(allowed_scripts, osr);
ScriptDetector s(allowed_scripts, osr, tess);
BLOBNBOX_C_IT filtered_it(blob_list);
int real_max = MIN(filtered_it.length(), kMaxCharactersToTry);
// tprintf("Total blobs found = %d\n", blobs_total);
// tprintf("Number of blobs post-filtering = %d\n", filtered_it.length());
// tprintf("Number of blobs to try = %d\n", real_max);
// If there are too few characters, skip this page entirely.
if (real_max < kMinCharactersToTry / 2) {
tprintf("Too few characters. Skipping this page\n");
return 0;
}
BLOBNBOX** blobs = new BLOBNBOX*[filtered_it.length()];
int number_of_blobs = 0;
for (filtered_it.mark_cycle_pt (); !filtered_it.cycled_list ();
filtered_it.forward ()) {
blobs[number_of_blobs++] = (BLOBNBOX*)filtered_it.data();
}
QRSequenceGenerator sequence(number_of_blobs);
int num_blobs_evaluated = 0;
for (int i = 0; i < real_max; ++i) {
if (os_detect_blob(blobs[sequence.GetVal()], &o, &s, osr, tess)
&& i > kMinCharactersToTry) {
break;
}
++num_blobs_evaluated;
}
delete [] blobs;
// Make sure the best_result is up-to-date
int orientation = o.get_orientation();
osr->update_best_script(orientation);
return num_blobs_evaluated;
}
// Processes a single blob to estimate script and orientation.
// Return true if estimate of orientation and script satisfies stopping
// criteria.
bool os_detect_blob(BLOBNBOX* bbox, OrientationDetector* o,
ScriptDetector* s, OSResults* osr,
tesseract::Tesseract* tess) {
tess->tess_cn_matching.set_value(true); // turn it on
tess->tess_bn_matching.set_value(false);
C_BLOB* blob = bbox->cblob();
TBLOB* tblob = TBLOB::PolygonalCopy(tess->poly_allow_detailed_fx, blob);
TBOX box = tblob->bounding_box();
FCOORD current_rotation(1.0f, 0.0f);
FCOORD rotation90(0.0f, 1.0f);
BLOB_CHOICE_LIST ratings[4];
// Test the 4 orientations
for (int i = 0; i < 4; ++i) {
// Normalize the blob. Set the origin to the place we want to be the
// bottom-middle after rotation.
// Scaling is to make the rotated height the x-height.
float scaling = static_cast<float>(kBlnXHeight) / box.height();
float x_origin = (box.left() + box.right()) / 2.0f;
float y_origin = (box.bottom() + box.top()) / 2.0f;
if (i == 0 || i == 2) {
// Rotation is 0 or 180.
y_origin = i == 0 ? box.bottom() : box.top();
} else {
// Rotation is 90 or 270.
scaling = static_cast<float>(kBlnXHeight) / box.width();
x_origin = i == 1 ? box.left() : box.right();
}
TBLOB* rotated_blob = new TBLOB(*tblob);
rotated_blob->Normalize(NULL, ¤t_rotation, NULL,
x_origin, y_origin, scaling, scaling,
0.0f, static_cast<float>(kBlnBaselineOffset),
false, NULL);
tess->AdaptiveClassifier(rotated_blob, ratings + i);
delete rotated_blob;
current_rotation.rotate(rotation90);
}
delete tblob;
bool stop = o->detect_blob(ratings);
s->detect_blob(ratings);
int orientation = o->get_orientation();
stop = s->must_stop(orientation) && stop;
return stop;
}
OrientationDetector::OrientationDetector(
const GenericVector<int>* allowed_scripts, OSResults* osr) {
osr_ = osr;
allowed_scripts_ = allowed_scripts;
}
// Score the given blob and return true if it is now sure of the orientation
// after adding this block.
bool OrientationDetector::detect_blob(BLOB_CHOICE_LIST* scores) {
float blob_o_score[4] = {0.0f, 0.0f, 0.0f, 0.0f};
float total_blob_o_score = 0.0f;
for (int i = 0; i < 4; ++i) {
BLOB_CHOICE_IT choice_it(scores + i);
if (!choice_it.empty()) {
BLOB_CHOICE* choice = NULL;
if (allowed_scripts_ != NULL && !allowed_scripts_->empty()) {
// Find the top choice in an allowed script.
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list() &&
choice == NULL; choice_it.forward()) {
int choice_script = choice_it.data()->script_id();
int s = 0;
for (s = 0; s < allowed_scripts_->size(); ++s) {
if ((*allowed_scripts_)[s] == choice_script) {
choice = choice_it.data();
break;
}
}
}
} else {
choice = choice_it.data();
}
if (choice != NULL) {
// The certainty score ranges between [-20,0]. This is converted here to
// [0,1], with 1 indicating best match.
blob_o_score[i] = 1 + 0.05 * choice->certainty();
total_blob_o_score += blob_o_score[i];
}
}
}
if (total_blob_o_score == 0.0) return false;
// Fill in any blanks with the worst score of the others. This is better than
// picking an arbitrary probability for it and way better than -inf.
float worst_score = 0.0f;
int num_good_scores = 0;
for (int i = 0; i < 4; ++i) {
if (blob_o_score[i] > 0.0f) {
++num_good_scores;
if (worst_score == 0.0f || blob_o_score[i] < worst_score)
worst_score = blob_o_score[i];
}
}
if (num_good_scores == 1) {
// Lower worst if there is only one.
worst_score /= 2.0f;
}
for (int i = 0; i < 4; ++i) {
if (blob_o_score[i] == 0.0f) {
blob_o_score[i] = worst_score;
total_blob_o_score += worst_score;
}
}
// Normalize the orientation scores for the blob and use them to
// update the aggregated orientation score.
for (int i = 0; total_blob_o_score != 0 && i < 4; ++i) {
osr_->orientations[i] += log(blob_o_score[i] / total_blob_o_score);
}
// TODO(ranjith) Add an early exit test, based on min_orientation_margin,
// as used in pagesegmain.cpp.
return false;
}
int OrientationDetector::get_orientation() {
osr_->update_best_orientation();
return osr_->best_result.orientation_id;
}
ScriptDetector::ScriptDetector(const GenericVector<int>* allowed_scripts,
OSResults* osr, tesseract::Tesseract* tess) {
osr_ = osr;
tess_ = tess;
allowed_scripts_ = allowed_scripts;
katakana_id_ = tess_->unicharset.add_script(katakana_script);
hiragana_id_ = tess_->unicharset.add_script(hiragana_script);
han_id_ = tess_->unicharset.add_script(han_script);
hangul_id_ = tess_->unicharset.add_script(hangul_script);
japanese_id_ = tess_->unicharset.add_script(japanese_script_);
korean_id_ = tess_->unicharset.add_script(korean_script_);
latin_id_ = tess_->unicharset.add_script(latin_script);
fraktur_id_ = tess_->unicharset.add_script(fraktur_script_);
}
// Score the given blob and return true if it is now sure of the script after
// adding this blob.
void ScriptDetector::detect_blob(BLOB_CHOICE_LIST* scores) {
bool done[kMaxNumberOfScripts];
for (int i = 0; i < 4; ++i) {
for (int j = 0; j < kMaxNumberOfScripts; ++j)
done[j] = false;
BLOB_CHOICE_IT choice_it;
choice_it.set_to_list(scores + i);
float prev_score = -1;
int script_count = 0;
int prev_id = -1;
int prev_fontinfo_id = -1;
const char* prev_unichar = "";
const char* unichar = "";
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
choice_it.forward()) {
BLOB_CHOICE* choice = choice_it.data();
int id = choice->script_id();
if (allowed_scripts_ != NULL && !allowed_scripts_->empty()) {
// Check that the choice is in an allowed script.
int s = 0;
for (s = 0; s < allowed_scripts_->size(); ++s) {
if ((*allowed_scripts_)[s] == id) break;
}
if (s == allowed_scripts_->size()) continue; // Not found in list.
}
// Script already processed before.
if (done[id]) continue;
done[id] = true;
unichar = tess_->unicharset.id_to_unichar(choice->unichar_id());
// Save data from the first match
if (prev_score < 0) {
prev_score = -choice->certainty();
script_count = 1;
prev_id = id;
prev_unichar = unichar;
prev_fontinfo_id = choice->fontinfo_id();
} else if (-choice->certainty() < prev_score + kNonAmbiguousMargin) {
++script_count;
}
if (strlen(prev_unichar) == 1)
if (unichar[0] >= '0' && unichar[0] <= '9')
break;
// if script_count is >= 2, character is ambiguous, skip other matches
// since they are useless.
if (script_count >= 2)
break;
}
// Character is non ambiguous
if (script_count == 1) {
// Update the score of the winning script
osr_->scripts_na[i][prev_id] += 1.0;
// Workaround for Fraktur
if (prev_id == latin_id_) {
if (prev_fontinfo_id >= 0) {
const tesseract::FontInfo &fi =
tess_->get_fontinfo_table().get(prev_fontinfo_id);
//printf("Font: %s i:%i b:%i f:%i s:%i k:%i (%s)\n", fi.name,
// fi.is_italic(), fi.is_bold(), fi.is_fixed_pitch(),
// fi.is_serif(), fi.is_fraktur(),
// prev_unichar);
if (fi.is_fraktur()) {
osr_->scripts_na[i][prev_id] -= 1.0;
osr_->scripts_na[i][fraktur_id_] += 1.0;
}
}
}
// Update Japanese / Korean pseudo-scripts
if (prev_id == katakana_id_)
osr_->scripts_na[i][japanese_id_] += 1.0;
if (prev_id == hiragana_id_)
osr_->scripts_na[i][japanese_id_] += 1.0;
if (prev_id == hangul_id_)
osr_->scripts_na[i][korean_id_] += 1.0;
if (prev_id == han_id_) {
osr_->scripts_na[i][korean_id_] += kHanRatioInKorean;
osr_->scripts_na[i][japanese_id_] += kHanRatioInJapanese;
}
}
} // iterate over each orientation
}
bool ScriptDetector::must_stop(int orientation) {
osr_->update_best_script(orientation);
return osr_->best_result.sconfidence > 1;
}
// Helper method to convert an orientation index to its value in degrees.
// The value represents the amount of clockwise rotation in degrees that must be
// applied for the text to be upright (readable).
const int OrientationIdToValue(const int& id) {
switch (id) {
case 0:
return 0;
case 1:
return 270;
case 2:
return 180;
case 3:
return 90;
default:
return -1;
}
}
| C++ |
/**********************************************************************
* File: adaptions.cpp (Formerly adaptions.c)
* Description: Functions used to adapt to blobs already confidently
* identified
* Author: Chris Newton
* Created: Thu Oct 7 10:17:28 BST 1993
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef _MSC_VER
#pragma warning(disable:4244) // Conversion warnings
#pragma warning(disable:4305) // int/float warnings
#endif
#ifdef __UNIX__
#include <assert.h>
#endif
#include <ctype.h>
#include <string.h>
#include "tessbox.h"
#include "tessvars.h"
#include "memry.h"
#include "reject.h"
#include "control.h"
#include "stopper.h"
#include "tesseractclass.h"
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
namespace tesseract {
BOOL8 Tesseract::word_adaptable( //should we adapt?
WERD_RES *word,
uinT16 mode) {
if (tessedit_adaption_debug) {
tprintf("Running word_adaptable() for %s rating %.4f certainty %.4f\n",
word->best_choice == NULL ? "" :
word->best_choice->unichar_string().string(),
word->best_choice->rating(), word->best_choice->certainty());
}
BOOL8 status = FALSE;
BITS16 flags(mode);
enum MODES
{
ADAPTABLE_WERD,
ACCEPTABLE_WERD,
CHECK_DAWGS,
CHECK_SPACES,
CHECK_ONE_ELL_CONFLICT,
CHECK_AMBIG_WERD
};
/*
0: NO adaption
*/
if (mode == 0) {
if (tessedit_adaption_debug) tprintf("adaption disabled\n");
return FALSE;
}
if (flags.bit (ADAPTABLE_WERD)) {
status |= word->tess_would_adapt; // result of Classify::AdaptableWord()
if (tessedit_adaption_debug && !status) {
tprintf("tess_would_adapt bit is false\n");
}
}
if (flags.bit (ACCEPTABLE_WERD)) {
status |= word->tess_accepted;
if (tessedit_adaption_debug && !status) {
tprintf("tess_accepted bit is false\n");
}
}
if (!status) { // If not set then
return FALSE; // ignore other checks
}
if (flags.bit (CHECK_DAWGS) &&
(word->best_choice->permuter () != SYSTEM_DAWG_PERM) &&
(word->best_choice->permuter () != FREQ_DAWG_PERM) &&
(word->best_choice->permuter () != USER_DAWG_PERM) &&
(word->best_choice->permuter () != NUMBER_PERM)) {
if (tessedit_adaption_debug) tprintf("word not in dawgs\n");
return FALSE;
}
if (flags.bit (CHECK_ONE_ELL_CONFLICT) && one_ell_conflict (word, FALSE)) {
if (tessedit_adaption_debug) tprintf("word has ell conflict\n");
return FALSE;
}
if (flags.bit (CHECK_SPACES) &&
(strchr(word->best_choice->unichar_string().string(), ' ') != NULL)) {
if (tessedit_adaption_debug) tprintf("word contains spaces\n");
return FALSE;
}
if (flags.bit (CHECK_AMBIG_WERD) &&
word->best_choice->dangerous_ambig_found()) {
if (tessedit_adaption_debug) tprintf("word is ambiguous\n");
return FALSE;
}
if (tessedit_adaption_debug) {
tprintf("returning status %d\n", status);
}
return status;
}
} // namespace tesseract
| C++ |
/**********************************************************************
* File: tessvars.cpp (Formerly tessvars.c)
* Description: Variables and other globals for tessedit.
* Author: Ray Smith
* Created: Mon Apr 13 13:13:23 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#include <stdio.h>
#include "tessvars.h"
FILE *debug_fp = stderr; // write debug stuff here
| C++ |
///////////////////////////////////////////////////////////////////////
// File: pageiterator.h
// Description: Iterator for tesseract page structure that avoids using
// tesseract internal data structures.
// Author: Ray Smith
// Created: Fri Feb 26 11:01:06 PST 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#ifndef TESSERACT_CCMAIN_PAGEITERATOR_H__
#define TESSERACT_CCMAIN_PAGEITERATOR_H__
#include "publictypes.h"
#include "platform.h"
struct BlamerBundle;
class C_BLOB_IT;
class PAGE_RES;
class PAGE_RES_IT;
class WERD;
struct Pix;
struct Pta;
namespace tesseract {
class Tesseract;
/**
* Class to iterate over tesseract page structure, providing access to all
* levels of the page hierarchy, without including any tesseract headers or
* having to handle any tesseract structures.
* WARNING! This class points to data held within the TessBaseAPI class, and
* therefore can only be used while the TessBaseAPI class still exists and
* has not been subjected to a call of Init, SetImage, Recognize, Clear, End
* DetectOS, or anything else that changes the internal PAGE_RES.
* See apitypes.h for the definition of PageIteratorLevel.
* See also ResultIterator, derived from PageIterator, which adds in the
* ability to access OCR output with text-specific methods.
*/
class TESS_API PageIterator {
public:
/**
* page_res and tesseract come directly from the BaseAPI.
* The rectangle parameters are copied indirectly from the Thresholder,
* via the BaseAPI. They represent the coordinates of some rectangle in an
* original image (in top-left-origin coordinates) and therefore the top-left
* needs to be added to any output boxes in order to specify coordinates
* in the original image. See TessBaseAPI::SetRectangle.
* The scale and scaled_yres are in case the Thresholder scaled the image
* rectangle prior to thresholding. Any coordinates in tesseract's image
* must be divided by scale before adding (rect_left, rect_top).
* The scaled_yres indicates the effective resolution of the binary image
* that tesseract has been given by the Thresholder.
* After the constructor, Begin has already been called.
*/
PageIterator(PAGE_RES* page_res, Tesseract* tesseract,
int scale, int scaled_yres,
int rect_left, int rect_top,
int rect_width, int rect_height);
virtual ~PageIterator();
/**
* Page/ResultIterators may be copied! This makes it possible to iterate over
* all the objects at a lower level, while maintaining an iterator to
* objects at a higher level. These constructors DO NOT CALL Begin, so
* iterations will continue from the location of src.
*/
PageIterator(const PageIterator& src);
const PageIterator& operator=(const PageIterator& src);
/** Are we positioned at the same location as other? */
bool PositionedAtSameWord(const PAGE_RES_IT* other) const;
// ============= Moving around within the page ============.
/**
* Moves the iterator to point to the start of the page to begin an
* iteration.
*/
virtual void Begin();
/**
* Moves the iterator to the beginning of the paragraph.
* This class implements this functionality by moving it to the zero indexed
* blob of the first (leftmost) word on the first row of the paragraph.
*/
virtual void RestartParagraph();
/**
* Return whether this iterator points anywhere in the first textline of a
* paragraph.
*/
bool IsWithinFirstTextlineOfParagraph() const;
/**
* Moves the iterator to the beginning of the text line.
* This class implements this functionality by moving it to the zero indexed
* blob of the first (leftmost) word of the row.
*/
virtual void RestartRow();
/**
* Moves to the start of the next object at the given level in the
* page hierarchy, and returns false if the end of the page was reached.
* NOTE that RIL_SYMBOL will skip non-text blocks, but all other
* PageIteratorLevel level values will visit each non-text block once.
* Think of non text blocks as containing a single para, with a single line,
* with a single imaginary word.
* Calls to Next with different levels may be freely intermixed.
* This function iterates words in right-to-left scripts correctly, if
* the appropriate language has been loaded into Tesseract.
*/
virtual bool Next(PageIteratorLevel level);
/**
* Returns true if the iterator is at the start of an object at the given
* level.
*
* For instance, suppose an iterator it is pointed to the first symbol of the
* first word of the third line of the second paragraph of the first block in
* a page, then:
* it.IsAtBeginningOf(RIL_BLOCK) = false
* it.IsAtBeginningOf(RIL_PARA) = false
* it.IsAtBeginningOf(RIL_TEXTLINE) = true
* it.IsAtBeginningOf(RIL_WORD) = true
* it.IsAtBeginningOf(RIL_SYMBOL) = true
*/
virtual bool IsAtBeginningOf(PageIteratorLevel level) const;
/**
* Returns whether the iterator is positioned at the last element in a
* given level. (e.g. the last word in a line, the last line in a block)
*
* Here's some two-paragraph example
* text. It starts off innocuously
* enough but quickly turns bizarre.
* The author inserts a cornucopia
* of words to guard against confused
* references.
*
* Now take an iterator it pointed to the start of "bizarre."
* it.IsAtFinalElement(RIL_PARA, RIL_SYMBOL) = false
* it.IsAtFinalElement(RIL_PARA, RIL_WORD) = true
* it.IsAtFinalElement(RIL_BLOCK, RIL_WORD) = false
*/
virtual bool IsAtFinalElement(PageIteratorLevel level,
PageIteratorLevel element) const;
/**
* Returns whether this iterator is positioned
* before other: -1
* equal to other: 0
* after other: 1
*/
int Cmp(const PageIterator &other) const;
// ============= Accessing data ==============.
// Coordinate system:
// Integer coordinates are at the cracks between the pixels.
// The top-left corner of the top-left pixel in the image is at (0,0).
// The bottom-right corner of the bottom-right pixel in the image is at
// (width, height).
// Every bounding box goes from the top-left of the top-left contained
// pixel to the bottom-right of the bottom-right contained pixel, so
// the bounding box of the single top-left pixel in the image is:
// (0,0)->(1,1).
// If an image rectangle has been set in the API, then returned coordinates
// relate to the original (full) image, rather than the rectangle.
/**
* Returns the bounding rectangle of the current object at the given level.
* See comment on coordinate system above.
* Returns false if there is no such object at the current position.
* The returned bounding box is guaranteed to match the size and position
* of the image returned by GetBinaryImage, but may clip foreground pixels
* from a grey image. The padding argument to GetImage can be used to expand
* the image to include more foreground pixels. See GetImage below.
*/
bool BoundingBox(PageIteratorLevel level,
int* left, int* top, int* right, int* bottom) const;
bool BoundingBox(PageIteratorLevel level, const int padding,
int* left, int* top, int* right, int* bottom) const;
/**
* Returns the bounding rectangle of the object in a coordinate system of the
* working image rectangle having its origin at (rect_left_, rect_top_) with
* respect to the original image and is scaled by a factor scale_.
*/
bool BoundingBoxInternal(PageIteratorLevel level,
int* left, int* top, int* right, int* bottom) const;
/** Returns whether there is no object of a given level. */
bool Empty(PageIteratorLevel level) const;
/**
* Returns the type of the current block. See apitypes.h for
* PolyBlockType.
*/
PolyBlockType BlockType() const;
/**
* Returns the polygon outline of the current block. The returned Pta must
* be ptaDestroy-ed after use. Note that the returned Pta lists the vertices
* of the polygon, and the last edge is the line segment between the last
* point and the first point. NULL will be returned if the iterator is
* at the end of the document or layout analysis was not used.
*/
Pta* BlockPolygon() const;
/**
* Returns a binary image of the current object at the given level.
* The position and size match the return from BoundingBoxInternal, and so
* this could be upscaled with respect to the original input image.
* Use pixDestroy to delete the image after use.
*/
Pix* GetBinaryImage(PageIteratorLevel level) const;
/**
* Returns an image of the current object at the given level in greyscale
* if available in the input. To guarantee a binary image use BinaryImage.
* NOTE that in order to give the best possible image, the bounds are
* expanded slightly over the binary connected component, by the supplied
* padding, so the top-left position of the returned image is returned
* in (left,top). These will most likely not match the coordinates
* returned by BoundingBox.
* If you do not supply an original image, you will get a binary one.
* Use pixDestroy to delete the image after use.
*/
Pix* GetImage(PageIteratorLevel level, int padding, Pix* original_img,
int* left, int* top) const;
/**
* Returns the baseline of the current object at the given level.
* The baseline is the line that passes through (x1, y1) and (x2, y2).
* WARNING: with vertical text, baselines may be vertical!
* Returns false if there is no baseline at the current position.
*/
bool Baseline(PageIteratorLevel level,
int* x1, int* y1, int* x2, int* y2) const;
/**
* Returns orientation for the block the iterator points to.
* orientation, writing_direction, textline_order: see publictypes.h
* deskew_angle: after rotating the block so the text orientation is
* upright, how many radians does one have to rotate the
* block anti-clockwise for it to be level?
* -Pi/4 <= deskew_angle <= Pi/4
*/
void Orientation(tesseract::Orientation *orientation,
tesseract::WritingDirection *writing_direction,
tesseract::TextlineOrder *textline_order,
float *deskew_angle) const;
/**
* Returns information about the current paragraph, if available.
*
* justification -
* LEFT if ragged right, or fully justified and script is left-to-right.
* RIGHT if ragged left, or fully justified and script is right-to-left.
* unknown if it looks like source code or we have very few lines.
* is_list_item -
* true if we believe this is a member of an ordered or unordered list.
* is_crown -
* true if the first line of the paragraph is aligned with the other
* lines of the paragraph even though subsequent paragraphs have first
* line indents. This typically indicates that this is the continuation
* of a previous paragraph or that it is the very first paragraph in
* the chapter.
* first_line_indent -
* For LEFT aligned paragraphs, the first text line of paragraphs of
* this kind are indented this many pixels from the left edge of the
* rest of the paragraph.
* for RIGHT aligned paragraphs, the first text line of paragraphs of
* this kind are indented this many pixels from the right edge of the
* rest of the paragraph.
* NOTE 1: This value may be negative.
* NOTE 2: if *is_crown == true, the first line of this paragraph is
* actually flush, and first_line_indent is set to the "common"
* first_line_indent for subsequent paragraphs in this block
* of text.
*/
void ParagraphInfo(tesseract::ParagraphJustification *justification,
bool *is_list_item,
bool *is_crown,
int *first_line_indent) const;
// If the current WERD_RES (it_->word()) is not NULL, sets the BlamerBundle
// of the current word to the given pointer (takes ownership of the pointer)
// and returns true.
// Can only be used when iterating on the word level.
bool SetWordBlamerBundle(BlamerBundle *blamer_bundle);
protected:
/**
* Sets up the internal data for iterating the blobs of a new word, then
* moves the iterator to the given offset.
*/
TESS_LOCAL void BeginWord(int offset);
/** Pointer to the page_res owned by the API. */
PAGE_RES* page_res_;
/** Pointer to the Tesseract object owned by the API. */
Tesseract* tesseract_;
/**
* The iterator to the page_res_. Owned by this ResultIterator.
* A pointer just to avoid dragging in Tesseract includes.
*/
PAGE_RES_IT* it_;
/**
* The current input WERD being iterated. If there is an output from OCR,
* then word_ is NULL. Owned by the API
*/
WERD* word_;
/** The length of the current word_. */
int word_length_;
/** The current blob index within the word. */
int blob_index_;
/**
* Iterator to the blobs within the word. If NULL, then we are iterating
* OCR results in the box_word.
* Owned by this ResultIterator.
*/
C_BLOB_IT* cblob_it_;
/** Parameters saved from the Thresholder. Needed to rebuild coordinates.*/
int scale_;
int scaled_yres_;
int rect_left_;
int rect_top_;
int rect_width_;
int rect_height_;
};
} // namespace tesseract.
#endif // TESSERACT_CCMAIN_PAGEITERATOR_H__
| C++ |
///////////////////////////////////////////////////////////////////////
// File: paramsd.cpp
// Description: Tesseract parameter Editor
// Author: Joern Wanke
// Created: Wed Jul 18 10:05:01 PDT 2007
//
// (C) Copyright 2007, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
//
// The parameters editor is used to edit all the parameters used within
// tesseract from the ui.
#ifdef _WIN32
#else
#include <stdlib.h>
#include <stdio.h>
#endif
#include <map>
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#ifndef GRAPHICS_DISABLED
#include "paramsd.h"
#include "params.h"
#include "scrollview.h"
#include "svmnode.h"
#define VARDIR "configs/" /*parameters files */
#define MAX_ITEMS_IN_SUBMENU 30
// The following variables should remain static globals, since they
// are used by debug editor, which uses a single Tesseract instance.
//
// Contains the mappings from unique VC ids to their actual pointers.
static std::map<int, ParamContent*> vcMap;
static int nrParams = 0;
static int writeCommands[2];
ELISTIZE(ParamContent)
// Constructors for the various ParamTypes.
ParamContent::ParamContent(tesseract::StringParam* it) {
my_id_ = nrParams;
nrParams++;
param_type_ = VT_STRING;
sIt = it;
vcMap[my_id_] = this;
}
// Constructors for the various ParamTypes.
ParamContent::ParamContent(tesseract::IntParam* it) {
my_id_ = nrParams;
nrParams++;
param_type_ = VT_INTEGER;
iIt = it;
vcMap[my_id_] = this;
}
// Constructors for the various ParamTypes.
ParamContent::ParamContent(tesseract::BoolParam* it) {
my_id_ = nrParams;
nrParams++;
param_type_ = VT_BOOLEAN;
bIt = it;
vcMap[my_id_] = this;
}
// Constructors for the various ParamTypes.
ParamContent::ParamContent(tesseract::DoubleParam* it) {
my_id_ = nrParams;
nrParams++;
param_type_ = VT_DOUBLE;
dIt = it;
vcMap[my_id_] = this;
}
// Gets a VC object identified by its ID.
ParamContent* ParamContent::GetParamContentById(int id) {
return vcMap[id];
}
// Copy the first N words from the source string to the target string.
// Words are delimited by "_".
void ParamsEditor::GetFirstWords(
const char *s, // source string
int n, // number of words
char *t // target string
) {
int full_length = strlen(s);
int reqd_len = 0; // No. of chars requird
const char *next_word = s;
while ((n > 0) && reqd_len < full_length) {
reqd_len += strcspn(next_word, "_") + 1;
next_word += reqd_len;
n--;
}
strncpy(t, s, reqd_len);
t[reqd_len] = '\0'; // ensure null terminal
}
// Getter for the name.
const char* ParamContent::GetName() const {
if (param_type_ == VT_INTEGER) { return iIt->name_str(); }
else if (param_type_ == VT_BOOLEAN) { return bIt->name_str(); }
else if (param_type_ == VT_DOUBLE) { return dIt->name_str(); }
else if (param_type_ == VT_STRING) { return sIt->name_str(); }
else
return "ERROR: ParamContent::GetName()";
}
// Getter for the description.
const char* ParamContent::GetDescription() const {
if (param_type_ == VT_INTEGER) { return iIt->info_str(); }
else if (param_type_ == VT_BOOLEAN) { return bIt->info_str(); }
else if (param_type_ == VT_DOUBLE) { return dIt->info_str(); }
else if (param_type_ == VT_STRING) { return sIt->info_str(); }
else return NULL;
}
// Getter for the value.
STRING ParamContent::GetValue() const {
STRING result;
if (param_type_ == VT_INTEGER) {
result.add_str_int("", *iIt);
} else if (param_type_ == VT_BOOLEAN) {
result.add_str_int("", *bIt);
} else if (param_type_ == VT_DOUBLE) {
result.add_str_double("", *dIt);
} else if (param_type_ == VT_STRING) {
if (((STRING) * (sIt)).string() != NULL) {
result = sIt->string();
} else {
result = "Null";
}
}
return result;
}
// Setter for the value.
void ParamContent::SetValue(const char* val) {
// TODO (wanke) Test if the values actually are properly converted.
// (Quickly visible impacts?)
changed_ = TRUE;
if (param_type_ == VT_INTEGER) {
iIt->set_value(atoi(val));
} else if (param_type_ == VT_BOOLEAN) {
bIt->set_value(atoi(val));
} else if (param_type_ == VT_DOUBLE) {
dIt->set_value(strtod(val, NULL));
} else if (param_type_ == VT_STRING) {
sIt->set_value(val);
}
}
// Gets the up to the first 3 prefixes from s (split by _).
// For example, tesseract_foo_bar will be split into tesseract,foo and bar.
void ParamsEditor::GetPrefixes(const char* s, STRING* level_one,
STRING* level_two,
STRING* level_three) {
char* p = new char[1024];
GetFirstWords(s, 1, p);
*level_one = p;
GetFirstWords(s, 2, p);
*level_two = p;
GetFirstWords(s, 3, p);
*level_three = p;
delete[] p;
}
// Compare two VC objects by their name.
int ParamContent::Compare(const void* v1, const void* v2) {
const ParamContent* one =
*reinterpret_cast<const ParamContent* const *>(v1);
const ParamContent* two =
*reinterpret_cast<const ParamContent* const *>(v2);
return strcmp(one->GetName(), two->GetName());
}
// Find all editable parameters used within tesseract and create a
// SVMenuNode tree from it.
// TODO (wanke): This is actually sort of hackish.
SVMenuNode* ParamsEditor::BuildListOfAllLeaves(tesseract::Tesseract *tess) {
SVMenuNode* mr = new SVMenuNode();
ParamContent_LIST vclist;
ParamContent_IT vc_it(&vclist);
// Amount counts the number of entries for a specific char*.
// TODO(rays) get rid of the use of std::map.
std::map<const char*, int> amount;
// Add all parameters to a list.
int v, i;
int num_iterations = (tess->params() == NULL) ? 1 : 2;
for (v = 0; v < num_iterations; ++v) {
tesseract::ParamsVectors *vec = (v == 0) ? GlobalParams() : tess->params();
for (i = 0; i < vec->int_params.size(); ++i) {
vc_it.add_after_then_move(new ParamContent(vec->int_params[i]));
}
for (i = 0; i < vec->bool_params.size(); ++i) {
vc_it.add_after_then_move(new ParamContent(vec->bool_params[i]));
}
for (i = 0; i < vec->string_params.size(); ++i) {
vc_it.add_after_then_move(new ParamContent(vec->string_params[i]));
}
for (i = 0; i < vec->double_params.size(); ++i) {
vc_it.add_after_then_move(new ParamContent(vec->double_params[i]));
}
}
// Count the # of entries starting with a specific prefix.
for (vc_it.mark_cycle_pt(); !vc_it.cycled_list(); vc_it.forward()) {
ParamContent* vc = vc_it.data();
STRING tag;
STRING tag2;
STRING tag3;
GetPrefixes(vc->GetName(), &tag, &tag2, &tag3);
amount[tag.string()]++;
amount[tag2.string()]++;
amount[tag3.string()]++;
}
vclist.sort(ParamContent::Compare); // Sort the list alphabetically.
SVMenuNode* other = mr->AddChild("OTHER");
// go through the list again and this time create the menu structure.
vc_it.move_to_first();
for (vc_it.mark_cycle_pt(); !vc_it.cycled_list(); vc_it.forward()) {
ParamContent* vc = vc_it.data();
STRING tag;
STRING tag2;
STRING tag3;
GetPrefixes(vc->GetName(), &tag, &tag2, &tag3);
if (amount[tag.string()] == 1) {
other->AddChild(vc->GetName(), vc->GetId(), vc->GetValue().string(),
vc->GetDescription());
} else { // More than one would use this submenu -> create submenu.
SVMenuNode* sv = mr->AddChild(tag.string());
if ((amount[tag.string()] <= MAX_ITEMS_IN_SUBMENU) ||
(amount[tag2.string()] <= 1)) {
sv->AddChild(vc->GetName(), vc->GetId(),
vc->GetValue().string(), vc->GetDescription());
} else { // Make subsubmenus.
SVMenuNode* sv2 = sv->AddChild(tag2.string());
sv2->AddChild(vc->GetName(), vc->GetId(),
vc->GetValue().string(), vc->GetDescription());
}
}
}
return mr;
}
// Event listener. Waits for SVET_POPUP events and processes them.
void ParamsEditor::Notify(const SVEvent* sve) {
if (sve->type == SVET_POPUP) { // only catch SVET_POPUP!
char* param = sve->parameter;
if (sve->command_id == writeCommands[0]) {
WriteParams(param, false);
} else if (sve->command_id == writeCommands[1]) {
WriteParams(param, true);
} else {
ParamContent* vc = ParamContent::GetParamContentById(
sve->command_id);
vc->SetValue(param);
sv_window_->AddMessage("Setting %s to %s",
vc->GetName(), vc->GetValue().string());
}
}
}
// Integrate the parameters editor as popupmenu into the existing scrollview
// window (usually the pg editor). If sv == null, create a new empty
// empty window and attach the parameters editor to that window (ugly).
ParamsEditor::ParamsEditor(tesseract::Tesseract* tess,
ScrollView* sv) {
if (sv == NULL) {
const char* name = "ParamEditorMAIN";
sv = new ScrollView(name, 1, 1, 200, 200, 300, 200);
}
sv_window_ = sv;
//Only one event handler per window.
//sv->AddEventHandler((SVEventHandler*) this);
SVMenuNode* svMenuRoot = BuildListOfAllLeaves(tess);
STRING paramfile;
paramfile = tess->datadir;
paramfile += VARDIR; // parameters dir
paramfile += "edited"; // actual name
SVMenuNode* std_menu = svMenuRoot->AddChild ("Build Config File");
writeCommands[0] = nrParams+1;
std_menu->AddChild("All Parameters", writeCommands[0],
paramfile.string(), "Config file name?");
writeCommands[1] = nrParams+2;
std_menu->AddChild ("changed_ Parameters Only", writeCommands[1],
paramfile.string(), "Config file name?");
svMenuRoot->BuildMenu(sv, false);
}
// Write all (changed_) parameters to a config file.
void ParamsEditor::WriteParams(char *filename,
bool changes_only) {
FILE *fp; // input file
char msg_str[255];
// if file exists
if ((fp = fopen (filename, "rb")) != NULL) {
fclose(fp);
sprintf (msg_str, "Overwrite file " "%s" "? (Y/N)", filename);
int a = sv_window_->ShowYesNoDialog(msg_str);
if (a == 'n') { return; } // dont write
}
fp = fopen (filename, "wb"); // can we write to it?
if (fp == NULL) {
sv_window_->AddMessage("Cant write to file " "%s" "", filename);
return;
}
for (std::map<int, ParamContent*>::iterator iter = vcMap.begin();
iter != vcMap.end();
++iter) {
ParamContent* cur = iter->second;
if (!changes_only || cur->HasChanged()) {
fprintf(fp, "%-25s %-12s # %s\n",
cur->GetName(), cur->GetValue().string(), cur->GetDescription());
}
}
fclose(fp);
}
#endif
| C++ |
///////////////////////////////////////////////////////////////////////
// File: pageiterator.cpp
// Description: Iterator for tesseract page structure that avoids using
// tesseract internal data structures.
// Author: Ray Smith
// Created: Fri Feb 26 14:32:09 PST 2010
//
// (C) Copyright 2010, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "pageiterator.h"
#include "allheaders.h"
#include "helpers.h"
#include "pageres.h"
#include "tesseractclass.h"
namespace tesseract {
PageIterator::PageIterator(PAGE_RES* page_res, Tesseract* tesseract,
int scale, int scaled_yres,
int rect_left, int rect_top,
int rect_width, int rect_height)
: page_res_(page_res), tesseract_(tesseract),
word_(NULL), word_length_(0), blob_index_(0), cblob_it_(NULL),
scale_(scale), scaled_yres_(scaled_yres),
rect_left_(rect_left), rect_top_(rect_top),
rect_width_(rect_width), rect_height_(rect_height) {
it_ = new PAGE_RES_IT(page_res);
PageIterator::Begin();
}
PageIterator::~PageIterator() {
delete it_;
delete cblob_it_;
}
/**
* PageIterators may be copied! This makes it possible to iterate over
* all the objects at a lower level, while maintaining an iterator to
* objects at a higher level.
*/
PageIterator::PageIterator(const PageIterator& src)
: page_res_(src.page_res_), tesseract_(src.tesseract_),
word_(NULL), word_length_(src.word_length_),
blob_index_(src.blob_index_), cblob_it_(NULL),
scale_(src.scale_), scaled_yres_(src.scaled_yres_),
rect_left_(src.rect_left_), rect_top_(src.rect_top_),
rect_width_(src.rect_width_), rect_height_(src.rect_height_) {
it_ = new PAGE_RES_IT(*src.it_);
BeginWord(src.blob_index_);
}
const PageIterator& PageIterator::operator=(const PageIterator& src) {
page_res_ = src.page_res_;
tesseract_ = src.tesseract_;
scale_ = src.scale_;
scaled_yres_ = src.scaled_yres_;
rect_left_ = src.rect_left_;
rect_top_ = src.rect_top_;
rect_width_ = src.rect_width_;
rect_height_ = src.rect_height_;
if (it_ != NULL) delete it_;
it_ = new PAGE_RES_IT(*src.it_);
BeginWord(src.blob_index_);
return *this;
}
bool PageIterator::PositionedAtSameWord(const PAGE_RES_IT* other) const {
return (it_ == NULL && it_ == other) ||
((other != NULL) && (it_ != NULL) && (*it_ == *other));
}
// ============= Moving around within the page ============.
/** Resets the iterator to point to the start of the page. */
void PageIterator::Begin() {
it_->restart_page_with_empties();
BeginWord(0);
}
void PageIterator::RestartParagraph() {
if (it_->block() == NULL) return; // At end of the document.
PAGE_RES_IT para(page_res_);
PAGE_RES_IT next_para(para);
next_para.forward_paragraph();
while (next_para.cmp(*it_) <= 0) {
para = next_para;
next_para.forward_paragraph();
}
*it_ = para;
BeginWord(0);
}
bool PageIterator::IsWithinFirstTextlineOfParagraph() const {
PageIterator p_start(*this);
p_start.RestartParagraph();
return p_start.it_->row() == it_->row();
}
void PageIterator::RestartRow() {
it_->restart_row();
BeginWord(0);
}
/**
* Moves to the start of the next object at the given level in the
* page hierarchy, and returns false if the end of the page was reached.
* NOTE (CHANGED!) that ALL PageIteratorLevel level values will visit each
* non-text block at least once.
* Think of non text blocks as containing a single para, with at least one
* line, with a single imaginary word, containing a single symbol.
* The bounding boxes mark out any polygonal nature of the block, and
* PTIsTextType(BLockType()) is false for non-text blocks.
* Calls to Next with different levels may be freely intermixed.
* This function iterates words in right-to-left scripts correctly, if
* the appropriate language has been loaded into Tesseract.
*/
bool PageIterator::Next(PageIteratorLevel level) {
if (it_->block() == NULL) return false; // Already at the end!
if (it_->word() == NULL)
level = RIL_BLOCK;
switch (level) {
case RIL_BLOCK:
it_->forward_block();
break;
case RIL_PARA:
it_->forward_paragraph();
break;
case RIL_TEXTLINE:
for (it_->forward_with_empties(); it_->row() == it_->prev_row();
it_->forward_with_empties());
break;
case RIL_WORD:
it_->forward_with_empties();
break;
case RIL_SYMBOL:
if (cblob_it_ != NULL)
cblob_it_->forward();
++blob_index_;
if (blob_index_ >= word_length_)
it_->forward_with_empties();
else
return true;
break;
}
BeginWord(0);
return it_->block() != NULL;
}
/**
* Returns true if the iterator is at the start of an object at the given
* level. Possible uses include determining if a call to Next(RIL_WORD)
* moved to the start of a RIL_PARA.
*/
bool PageIterator::IsAtBeginningOf(PageIteratorLevel level) const {
if (it_->block() == NULL) return false; // Already at the end!
if (it_->word() == NULL) return true; // In an image block.
switch (level) {
case RIL_BLOCK:
return blob_index_ == 0 && it_->block() != it_->prev_block();
case RIL_PARA:
return blob_index_ == 0 &&
(it_->block() != it_->prev_block() ||
it_->row()->row->para() != it_->prev_row()->row->para());
case RIL_TEXTLINE:
return blob_index_ == 0 && it_->row() != it_->prev_row();
case RIL_WORD:
return blob_index_ == 0;
case RIL_SYMBOL:
return true;
}
return false;
}
/**
* Returns whether the iterator is positioned at the last element in a
* given level. (e.g. the last word in a line, the last line in a block)
*/
bool PageIterator::IsAtFinalElement(PageIteratorLevel level,
PageIteratorLevel element) const {
if (Empty(element)) return true; // Already at the end!
// The result is true if we step forward by element and find we are
// at the the end of the page or at beginning of *all* levels in:
// [level, element).
// When there is more than one level difference between element and level,
// we could for instance move forward one symbol and still be at the first
// word on a line, so we also have to be at the first symbol in a word.
PageIterator next(*this);
next.Next(element);
if (next.Empty(element)) return true; // Reached the end of the page.
while (element > level) {
element = static_cast<PageIteratorLevel>(element - 1);
if (!next.IsAtBeginningOf(element))
return false;
}
return true;
}
/**
* Returns whether this iterator is positioned
* before other: -1
* equal to other: 0
* after other: 1
*/
int PageIterator::Cmp(const PageIterator &other) const {
int word_cmp = it_->cmp(*other.it_);
if (word_cmp != 0)
return word_cmp;
if (blob_index_ < other.blob_index_)
return -1;
if (blob_index_ == other.blob_index_)
return 0;
return 1;
}
// ============= Accessing data ==============.
// Coordinate system:
// Integer coordinates are at the cracks between the pixels.
// The top-left corner of the top-left pixel in the image is at (0,0).
// The bottom-right corner of the bottom-right pixel in the image is at
// (width, height).
// Every bounding box goes from the top-left of the top-left contained
// pixel to the bottom-right of the bottom-right contained pixel, so
// the bounding box of the single top-left pixel in the image is:
// (0,0)->(1,1).
// If an image rectangle has been set in the API, then returned coordinates
// relate to the original (full) image, rather than the rectangle.
/**
* Returns the bounding rectangle of the current object at the given level in
* the coordinates of the working image that is pix_binary().
* See comment on coordinate system above.
* Returns false if there is no such object at the current position.
*/
bool PageIterator::BoundingBoxInternal(PageIteratorLevel level,
int* left, int* top,
int* right, int* bottom) const {
if (Empty(level))
return false;
TBOX box;
PARA *para = NULL;
switch (level) {
case RIL_BLOCK:
box = it_->block()->block->bounding_box();
break;
case RIL_PARA:
para = it_->row()->row->para();
// explicit fall-through.
case RIL_TEXTLINE:
box = it_->row()->row->bounding_box();
break;
case RIL_WORD:
box = it_->word()->word->bounding_box();
break;
case RIL_SYMBOL:
if (cblob_it_ == NULL)
box = it_->word()->box_word->BlobBox(blob_index_);
else
box = cblob_it_->data()->bounding_box();
}
if (level == RIL_PARA) {
PageIterator other = *this;
other.Begin();
do {
if (other.it_->block() &&
other.it_->block()->block == it_->block()->block &&
other.it_->row() && other.it_->row()->row &&
other.it_->row()->row->para() == para) {
box = box.bounding_union(other.it_->row()->row->bounding_box());
}
} while (other.Next(RIL_TEXTLINE));
}
if (level != RIL_SYMBOL || cblob_it_ != NULL)
box.rotate(it_->block()->block->re_rotation());
// Now we have a box in tesseract coordinates relative to the image rectangle,
// we have to convert the coords to a top-down system.
const int pix_height = pixGetHeight(tesseract_->pix_binary());
const int pix_width = pixGetWidth(tesseract_->pix_binary());
*left = ClipToRange(static_cast<int>(box.left()), 0, pix_width);
*top = ClipToRange(pix_height - box.top(), 0, pix_height);
*right = ClipToRange(static_cast<int>(box.right()), *left, pix_width);
*bottom = ClipToRange(pix_height - box.bottom(), *top, pix_height);
return true;
}
/**
* Returns the bounding rectangle of the current object at the given level in
* coordinates of the original image.
* See comment on coordinate system above.
* Returns false if there is no such object at the current position.
*/
bool PageIterator::BoundingBox(PageIteratorLevel level,
int* left, int* top,
int* right, int* bottom) const {
return BoundingBox(level, 0, left, top, right, bottom);
}
bool PageIterator::BoundingBox(PageIteratorLevel level, const int padding,
int* left, int* top,
int* right, int* bottom) const {
if (!BoundingBoxInternal(level, left, top, right, bottom))
return false;
// Convert to the coordinate system of the original image.
*left = ClipToRange(*left / scale_ + rect_left_ - padding,
rect_left_, rect_left_ + rect_width_);
*top = ClipToRange(*top / scale_ + rect_top_ - padding,
rect_top_, rect_top_ + rect_height_);
*right = ClipToRange((*right + scale_ - 1) / scale_ + rect_left_ + padding,
*left, rect_left_ + rect_width_);
*bottom = ClipToRange((*bottom + scale_ - 1) / scale_ + rect_top_ + padding,
*top, rect_top_ + rect_height_);
return true;
}
/** Return that there is no such object at a given level. */
bool PageIterator::Empty(PageIteratorLevel level) const {
if (it_->block() == NULL) return true; // Already at the end!
if (it_->word() == NULL && level != RIL_BLOCK) return true; // image block
if (level == RIL_SYMBOL && blob_index_ >= word_length_)
return true; // Zero length word, or already at the end of it.
return false;
}
/** Returns the type of the current block. See apitypes.h for PolyBlockType. */
PolyBlockType PageIterator::BlockType() const {
if (it_->block() == NULL || it_->block()->block == NULL)
return PT_UNKNOWN; // Already at the end!
if (it_->block()->block->poly_block() == NULL)
return PT_FLOWING_TEXT; // No layout analysis used - assume text.
return it_->block()->block->poly_block()->isA();
}
/** Returns the polygon outline of the current block. The returned Pta must
* be ptaDestroy-ed after use. */
Pta* PageIterator::BlockPolygon() const {
if (it_->block() == NULL || it_->block()->block == NULL)
return NULL; // Already at the end!
if (it_->block()->block->poly_block() == NULL)
return NULL; // No layout analysis used - no polygon.
ICOORDELT_IT it(it_->block()->block->poly_block()->points());
Pta* pta = ptaCreate(it.length());
int num_pts = 0;
for (it.mark_cycle_pt(); !it.cycled_list(); it.forward(), ++num_pts) {
ICOORD* pt = it.data();
// Convert to top-down coords within the input image.
float x = static_cast<float>(pt->x()) / scale_ + rect_left_;
float y = rect_top_ + rect_height_ - static_cast<float>(pt->y()) / scale_;
ptaAddPt(pta, x, y);
}
return pta;
}
/**
* Returns a binary image of the current object at the given level.
* The position and size match the return from BoundingBoxInternal, and so this
* could be upscaled with respect to the original input image.
* Use pixDestroy to delete the image after use.
* The following methods are used to generate the images:
* RIL_BLOCK: mask the page image with the block polygon.
* RIL_TEXTLINE: Clip the rectangle of the line box from the page image.
* TODO(rays) fix this to generate and use a line polygon.
* RIL_WORD: Clip the rectangle of the word box from the page image.
* RIL_SYMBOL: Render the symbol outline to an image for cblobs (prior
* to recognition) or the bounding box otherwise.
* A reconstruction of the original image (using xor to check for double
* representation) should be reasonably accurate,
* apart from removed noise, at the block level. Below the block level, the
* reconstruction will be missing images and line separators.
* At the symbol level, kerned characters will be invade the bounding box
* if rendered after recognition, making an xor reconstruction inaccurate, but
* an or construction better. Before recognition, symbol-level reconstruction
* should be good, even with xor, since the images come from the connected
* components.
*/
Pix* PageIterator::GetBinaryImage(PageIteratorLevel level) const {
int left, top, right, bottom;
if (!BoundingBoxInternal(level, &left, &top, &right, &bottom))
return NULL;
Pix* pix = NULL;
switch (level) {
case RIL_BLOCK:
case RIL_PARA:
int bleft, btop, bright, bbottom;
BoundingBoxInternal(RIL_BLOCK, &bleft, &btop, &bright, &bbottom);
pix = it_->block()->block->render_mask();
// AND the mask and the image.
pixRasterop(pix, 0, 0, pixGetWidth(pix), pixGetHeight(pix),
PIX_SRC & PIX_DST, tesseract_->pix_binary(),
bleft, btop);
if (level == RIL_PARA) {
// RIL_PARA needs further attention:
// clip the paragraph from the block mask.
Box* box = boxCreate(left - bleft, top - btop,
right - left, bottom - top);
Pix* pix2 = pixClipRectangle(pix, box, NULL);
boxDestroy(&box);
pixDestroy(&pix);
pix = pix2;
}
break;
case RIL_TEXTLINE:
case RIL_WORD:
case RIL_SYMBOL:
if (level == RIL_SYMBOL && cblob_it_ != NULL &&
cblob_it_->data()->area() != 0)
return cblob_it_->data()->render();
// Just clip from the bounding box.
Box* box = boxCreate(left, top, right - left, bottom - top);
pix = pixClipRectangle(tesseract_->pix_binary(), box, NULL);
boxDestroy(&box);
break;
}
return pix;
}
/**
* Returns an image of the current object at the given level in greyscale
* if available in the input. To guarantee a binary image use BinaryImage.
* NOTE that in order to give the best possible image, the bounds are
* expanded slightly over the binary connected component, by the supplied
* padding, so the top-left position of the returned image is returned
* in (left,top). These will most likely not match the coordinates
* returned by BoundingBox.
* If you do not supply an original image, you will get a binary one.
* Use pixDestroy to delete the image after use.
*/
Pix* PageIterator::GetImage(PageIteratorLevel level, int padding,
Pix* original_img,
int* left, int* top) const {
int right, bottom;
if (!BoundingBox(level, left, top, &right, &bottom))
return NULL;
if (original_img == NULL)
return GetBinaryImage(level);
// Expand the box.
*left = MAX(*left - padding, 0);
*top = MAX(*top - padding, 0);
right = MIN(right + padding, rect_width_);
bottom = MIN(bottom + padding, rect_height_);
Box* box = boxCreate(*left, *top, right - *left, bottom - *top);
Pix* grey_pix = pixClipRectangle(original_img, box, NULL);
boxDestroy(&box);
if (level == RIL_BLOCK) {
Pix* mask = it_->block()->block->render_mask();
Pix* expanded_mask = pixCreate(right - *left, bottom - *top, 1);
pixRasterop(expanded_mask, padding, padding,
pixGetWidth(mask), pixGetHeight(mask),
PIX_SRC, mask, 0, 0);
pixDestroy(&mask);
pixDilateBrick(expanded_mask, expanded_mask, 2*padding + 1, 2*padding + 1);
pixInvert(expanded_mask, expanded_mask);
pixSetMasked(grey_pix, expanded_mask, MAX_UINT32);
pixDestroy(&expanded_mask);
}
return grey_pix;
}
/**
* Returns the baseline of the current object at the given level.
* The baseline is the line that passes through (x1, y1) and (x2, y2).
* WARNING: with vertical text, baselines may be vertical!
*/
bool PageIterator::Baseline(PageIteratorLevel level,
int* x1, int* y1, int* x2, int* y2) const {
if (it_->word() == NULL) return false; // Already at the end!
ROW* row = it_->row()->row;
WERD* word = it_->word()->word;
TBOX box = (level == RIL_WORD || level == RIL_SYMBOL)
? word->bounding_box()
: row->bounding_box();
int left = box.left();
ICOORD startpt(left, static_cast<inT16>(row->base_line(left) + 0.5));
int right = box.right();
ICOORD endpt(right, static_cast<inT16>(row->base_line(right) + 0.5));
// Rotate to image coordinates and convert to global image coords.
startpt.rotate(it_->block()->block->re_rotation());
endpt.rotate(it_->block()->block->re_rotation());
*x1 = startpt.x() / scale_ + rect_left_;
*y1 = (rect_height_ - startpt.y()) / scale_ + rect_top_;
*x2 = endpt.x() / scale_ + rect_left_;
*y2 = (rect_height_ - endpt.y()) / scale_ + rect_top_;
return true;
}
void PageIterator::Orientation(tesseract::Orientation *orientation,
tesseract::WritingDirection *writing_direction,
tesseract::TextlineOrder *textline_order,
float *deskew_angle) const {
BLOCK* block = it_->block()->block;
// Orientation
FCOORD up_in_image(0.0, 1.0);
up_in_image.unrotate(block->classify_rotation());
up_in_image.rotate(block->re_rotation());
if (up_in_image.x() == 0.0F) {
if (up_in_image.y() > 0.0F) {
*orientation = ORIENTATION_PAGE_UP;
} else {
*orientation = ORIENTATION_PAGE_DOWN;
}
} else if (up_in_image.x() > 0.0F) {
*orientation = ORIENTATION_PAGE_RIGHT;
} else {
*orientation = ORIENTATION_PAGE_LEFT;
}
// Writing direction
bool is_vertical_text = (block->classify_rotation().x() == 0.0);
bool right_to_left = block->right_to_left();
*writing_direction =
is_vertical_text
? WRITING_DIRECTION_TOP_TO_BOTTOM
: (right_to_left
? WRITING_DIRECTION_RIGHT_TO_LEFT
: WRITING_DIRECTION_LEFT_TO_RIGHT);
// Textline Order
bool is_mongolian = false; // TODO(eger): fix me
*textline_order = is_vertical_text
? (is_mongolian
? TEXTLINE_ORDER_LEFT_TO_RIGHT
: TEXTLINE_ORDER_RIGHT_TO_LEFT)
: TEXTLINE_ORDER_TOP_TO_BOTTOM;
// Deskew angle
FCOORD skew = block->skew(); // true horizontal for textlines
*deskew_angle = -skew.angle();
}
void PageIterator::ParagraphInfo(tesseract::ParagraphJustification *just,
bool *is_list_item,
bool *is_crown,
int *first_line_indent) const {
*just = tesseract::JUSTIFICATION_UNKNOWN;
if (!it_->row() || !it_->row()->row || !it_->row()->row->para() ||
!it_->row()->row->para()->model)
return;
PARA *para = it_->row()->row->para();
*is_list_item = para->is_list_item;
*is_crown = para->is_very_first_or_continuation;
*first_line_indent = para->model->first_indent() -
para->model->body_indent();
}
/**
* Sets up the internal data for iterating the blobs of a new word, then
* moves the iterator to the given offset.
*/
void PageIterator::BeginWord(int offset) {
WERD_RES* word_res = it_->word();
if (word_res == NULL) {
// This is a non-text block, so there is no word.
word_length_ = 0;
blob_index_ = 0;
word_ = NULL;
return;
}
if (word_res->best_choice != NULL) {
// Recognition has been done, so we are using the box_word, which
// is already baseline denormalized.
word_length_ = word_res->best_choice->length();
if (word_res->box_word != NULL) {
if (word_res->box_word->length() != word_length_) {
tprintf("Corrupted word! best_choice[len=%d] = %s, box_word[len=%d]: ",
word_length_, word_res->best_choice->unichar_string().string(),
word_res->box_word->length());
word_res->box_word->bounding_box().print();
}
ASSERT_HOST(word_res->box_word->length() == word_length_);
}
word_ = NULL;
// We will be iterating the box_word.
if (cblob_it_ != NULL) {
delete cblob_it_;
cblob_it_ = NULL;
}
} else {
// No recognition yet, so a "symbol" is a cblob.
word_ = word_res->word;
ASSERT_HOST(word_->cblob_list() != NULL);
word_length_ = word_->cblob_list()->length();
if (cblob_it_ == NULL) cblob_it_ = new C_BLOB_IT;
cblob_it_->set_to_list(word_->cblob_list());
}
for (blob_index_ = 0; blob_index_ < offset; ++blob_index_) {
if (cblob_it_ != NULL)
cblob_it_->forward();
}
}
bool PageIterator::SetWordBlamerBundle(BlamerBundle *blamer_bundle) {
if (it_->word() != NULL) {
it_->word()->blamer_bundle = blamer_bundle;
return true;
} else {
return false;
}
}
} // namespace tesseract.
| C++ |
///////////////////////////////////////////////////////////////////////
// File: resultiterator.cpp
// Description: Iterator for tesseract results that is capable of
// iterating in proper reading order over Bi Directional
// (e.g. mixed Hebrew and English) text.
// Author: David Eger
// Created: Fri May 27 13:58:06 PST 2011
//
// (C) Copyright 2011, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////
#include "resultiterator.h"
#include "allheaders.h"
#include "pageres.h"
#include "strngs.h"
#include "tesseractclass.h"
#include "unicharset.h"
#include "unicodes.h"
namespace tesseract {
ResultIterator::ResultIterator(const LTRResultIterator &resit)
: LTRResultIterator(resit) {
in_minor_direction_ = false;
at_beginning_of_minor_run_ = false;
preserve_interword_spaces_ = false;
BoolParam *p = ParamUtils::FindParam<BoolParam>(
"preserve_interword_spaces", GlobalParams()->bool_params,
tesseract_->params()->bool_params);
if (p != NULL) preserve_interword_spaces_ = (bool)(*p);
current_paragraph_is_ltr_ = CurrentParagraphIsLtr();
MoveToLogicalStartOfTextline();
}
ResultIterator *ResultIterator::StartOfParagraph(
const LTRResultIterator &resit) {
return new ResultIterator(resit);
}
bool ResultIterator::ParagraphIsLtr() const {
return current_paragraph_is_ltr_;
}
bool ResultIterator::CurrentParagraphIsLtr() const {
if (!it_->word())
return true; // doesn't matter.
LTRResultIterator it(*this);
it.RestartParagraph();
// Try to figure out the ltr-ness of the paragraph. The rules below
// make more sense in the context of a difficult paragraph example.
// Here we denote {ltr characters, RTL CHARACTERS}:
//
// "don't go in there!" DAIS EH
// EHT OTNI DEPMUJ FELSMIH NEHT DNA
// .GNIDLIUB GNINRUB
//
// On the first line, the left-most word is LTR and the rightmost word
// is RTL. Thus, we are better off taking the majority direction for
// the whole paragraph contents. So instead of "the leftmost word is LTR"
// indicating an LTR paragraph, we use a heuristic about what RTL paragraphs
// would not do: Typically an RTL paragraph would *not* start with an LTR
// word. So our heuristics are as follows:
//
// (1) If the first text line has an RTL word in the left-most position
// it is RTL.
// (2) If the first text line has an LTR word in the right-most position
// it is LTR.
// (3) If neither of the above is true, take the majority count for the
// paragraph -- if there are more rtl words, it is RTL. If there
// are more LTR words, it's LTR.
bool leftmost_rtl = it.WordDirection() == DIR_RIGHT_TO_LEFT;
bool rightmost_ltr = it.WordDirection() == DIR_LEFT_TO_RIGHT;
int num_ltr, num_rtl;
num_rtl = leftmost_rtl ? 1 : 0;
num_ltr = (it.WordDirection() == DIR_LEFT_TO_RIGHT) ? 1 : 0;
for (it.Next(RIL_WORD);
!it.Empty(RIL_WORD) && !it.IsAtBeginningOf(RIL_TEXTLINE);
it.Next(RIL_WORD)) {
StrongScriptDirection dir = it.WordDirection();
rightmost_ltr = (dir == DIR_LEFT_TO_RIGHT);
num_rtl += (dir == DIR_RIGHT_TO_LEFT) ? 1 : 0;
num_ltr += rightmost_ltr ? 1 : 0;
}
if (leftmost_rtl)
return false;
if (rightmost_ltr)
return true;
// First line is ambiguous. Take statistics on the whole paragraph.
if (!it.Empty(RIL_WORD) && !it.IsAtBeginningOf(RIL_PARA)) do {
StrongScriptDirection dir = it.WordDirection();
num_rtl += (dir == DIR_RIGHT_TO_LEFT) ? 1 : 0;
num_ltr += (dir == DIR_LEFT_TO_RIGHT) ? 1 : 0;
} while (it.Next(RIL_WORD) && !it.IsAtBeginningOf(RIL_PARA));
return num_ltr >= num_rtl;
}
const int ResultIterator::kMinorRunStart = -1;
const int ResultIterator::kMinorRunEnd = -2;
const int ResultIterator::kComplexWord = -3;
void ResultIterator::CalculateBlobOrder(
GenericVector<int> *blob_indices) const {
bool context_is_ltr = current_paragraph_is_ltr_ ^ in_minor_direction_;
blob_indices->clear();
if (Empty(RIL_WORD)) return;
if (context_is_ltr || it_->word()->UnicharsInReadingOrder()) {
// Easy! just return the blobs in order;
for (int i = 0; i < word_length_; i++)
blob_indices->push_back(i);
return;
}
// The blobs are in left-to-right order, but the current reading context
// is right-to-left.
const int U_LTR = UNICHARSET::U_LEFT_TO_RIGHT;
const int U_RTL = UNICHARSET::U_RIGHT_TO_LEFT;
const int U_EURO_NUM = UNICHARSET::U_EUROPEAN_NUMBER;
const int U_EURO_NUM_SEP = UNICHARSET::U_EUROPEAN_NUMBER_SEPARATOR;
const int U_EURO_NUM_TERM = UNICHARSET::U_EUROPEAN_NUMBER_TERMINATOR;
const int U_COMMON_NUM_SEP = UNICHARSET::U_COMMON_NUMBER_SEPARATOR;
const int U_OTHER_NEUTRAL = UNICHARSET::U_OTHER_NEUTRAL;
// Step 1: Scan for and mark European Number sequences
// [:ET:]*[:EN:]+(([:ES:]|[:CS:])?[:EN:]+)*[:ET:]*
GenericVector<int> letter_types;
for (int i = 0; i < word_length_; i++) {
letter_types.push_back(it_->word()->SymbolDirection(i));
}
// Convert a single separtor sandwiched between two EN's into an EN.
for (int i = 0; i + 2 < word_length_; i++) {
if (letter_types[i] == U_EURO_NUM && letter_types[i + 2] == U_EURO_NUM &&
(letter_types[i + 1] == U_EURO_NUM_SEP ||
letter_types[i + 1] == U_COMMON_NUM_SEP)) {
letter_types[i + 1] = U_EURO_NUM;
}
}
// Scan for sequences of European Number Terminators around ENs and convert
// them to ENs.
for (int i = 0; i < word_length_; i++) {
if (letter_types[i] == U_EURO_NUM_TERM) {
int j = i + 1;
while (j < word_length_ && letter_types[j] == U_EURO_NUM_TERM) { j++; }
if (j < word_length_ && letter_types[j] == U_EURO_NUM) {
// The sequence [i..j] should be converted to all European Numbers.
for (int k = i; k < j; k++) letter_types[k] = U_EURO_NUM;
}
j = i - 1;
while (j > -1 && letter_types[j] == U_EURO_NUM_TERM) { j--; }
if (j > -1 && letter_types[j] == U_EURO_NUM) {
// The sequence [j..i] should be converted to all European Numbers.
for (int k = j; k <= i; k++) letter_types[k] = U_EURO_NUM;
}
}
}
// Step 2: Convert all remaining types to either L or R.
// Sequences ([:L:]|[:EN:])+ (([:CS:]|[:ON:])+ ([:L:]|[:EN:])+)* -> L.
// All other are R.
for (int i = 0; i < word_length_;) {
int ti = letter_types[i];
if (ti == U_LTR || ti == U_EURO_NUM) {
// Left to right sequence; scan to the end of it.
int last_good = i;
for (int j = i + 1; j < word_length_; j++) {
int tj = letter_types[j];
if (tj == U_LTR || tj == U_EURO_NUM) {
last_good = j;
} else if (tj == U_COMMON_NUM_SEP || tj == U_OTHER_NEUTRAL) {
// do nothing.
} else {
break;
}
}
// [i..last_good] is the L sequence
for (int k = i; k <= last_good; k++) letter_types[k] = U_LTR;
i = last_good + 1;
} else {
letter_types[i] = U_RTL;
i++;
}
}
// At this point, letter_types is entirely U_LTR or U_RTL.
for (int i = word_length_ - 1; i >= 0;) {
if (letter_types[i] == U_RTL) {
blob_indices->push_back(i);
i--;
} else {
// left to right sequence. scan to the beginning.
int j = i - 1;
for (; j >= 0 && letter_types[j] != U_RTL; j--) { } // pass
// Now (j, i] is LTR
for (int k = j + 1; k <= i; k++) blob_indices->push_back(k);
i = j;
}
}
ASSERT_HOST(blob_indices->size() == word_length_);
}
static void PrintScriptDirs(const GenericVector<StrongScriptDirection> &dirs) {
for (int i = 0; i < dirs.size(); i++) {
switch (dirs[i]) {
case DIR_NEUTRAL: tprintf ("N "); break;
case DIR_LEFT_TO_RIGHT: tprintf("L "); break;
case DIR_RIGHT_TO_LEFT: tprintf("R "); break;
case DIR_MIX: tprintf("Z "); break;
default: tprintf("? "); break;
}
}
tprintf("\n");
}
void ResultIterator::CalculateTextlineOrder(
bool paragraph_is_ltr,
const LTRResultIterator &resit,
GenericVectorEqEq<int> *word_indices) const {
GenericVector<StrongScriptDirection> directions;
CalculateTextlineOrder(paragraph_is_ltr, resit, &directions, word_indices);
}
void ResultIterator::CalculateTextlineOrder(
bool paragraph_is_ltr,
const LTRResultIterator &resit,
GenericVector<StrongScriptDirection> *dirs_arg,
GenericVectorEqEq<int> *word_indices) const {
GenericVector<StrongScriptDirection> dirs;
GenericVector<StrongScriptDirection> *directions;
directions = (dirs_arg != NULL) ? dirs_arg : &dirs;
directions->truncate(0);
// A LTRResultIterator goes strictly left-to-right word order.
LTRResultIterator ltr_it(resit);
ltr_it.RestartRow();
if (ltr_it.Empty(RIL_WORD)) return;
do {
directions->push_back(ltr_it.WordDirection());
} while (ltr_it.Next(RIL_WORD) && !ltr_it.IsAtBeginningOf(RIL_TEXTLINE));
word_indices->truncate(0);
CalculateTextlineOrder(paragraph_is_ltr, *directions, word_indices);
}
void ResultIterator::CalculateTextlineOrder(
bool paragraph_is_ltr,
const GenericVector<StrongScriptDirection> &word_dirs,
GenericVectorEqEq<int> *reading_order) {
reading_order->truncate(0);
if (word_dirs.size() == 0) return;
// Take all of the runs of minor direction words and insert them
// in reverse order.
int minor_direction, major_direction, major_step, start, end;
if (paragraph_is_ltr) {
start = 0;
end = word_dirs.size();
major_step = 1;
major_direction = DIR_LEFT_TO_RIGHT;
minor_direction = DIR_RIGHT_TO_LEFT;
} else {
start = word_dirs.size() - 1;
end = -1;
major_step = -1;
major_direction = DIR_RIGHT_TO_LEFT;
minor_direction = DIR_LEFT_TO_RIGHT;
// Special rule: if there are neutral words at the right most side
// of a line adjacent to a left-to-right word in the middle of the
// line, we interpret the end of the line as a single LTR sequence.
if (word_dirs[start] == DIR_NEUTRAL) {
int neutral_end = start;
while (neutral_end > 0 && word_dirs[neutral_end] == DIR_NEUTRAL) {
neutral_end--;
}
if (neutral_end >= 0 && word_dirs[neutral_end] == DIR_LEFT_TO_RIGHT) {
// LTR followed by neutrals.
// Scan for the beginning of the minor left-to-right run.
int left = neutral_end;
for (int i = left; i >= 0 && word_dirs[i] != DIR_RIGHT_TO_LEFT; i--) {
if (word_dirs[i] == DIR_LEFT_TO_RIGHT) left = i;
}
reading_order->push_back(kMinorRunStart);
for (int i = left; i < word_dirs.size(); i++) {
reading_order->push_back(i);
if (word_dirs[i] == DIR_MIX) reading_order->push_back(kComplexWord);
}
reading_order->push_back(kMinorRunEnd);
start = left - 1;
}
}
}
for (int i = start; i != end;) {
if (word_dirs[i] == minor_direction) {
int j = i;
while (j != end && word_dirs[j] != major_direction)
j += major_step;
if (j == end) j -= major_step;
while (j != i && word_dirs[j] != minor_direction)
j -= major_step;
// [j..i] is a minor direction run.
reading_order->push_back(kMinorRunStart);
for (int k = j; k != i; k -= major_step) {
reading_order->push_back(k);
}
reading_order->push_back(i);
reading_order->push_back(kMinorRunEnd);
i = j + major_step;
} else {
reading_order->push_back(i);
if (word_dirs[i] == DIR_MIX) reading_order->push_back(kComplexWord);
i += major_step;
}
}
}
int ResultIterator::LTRWordIndex() const {
int this_word_index = 0;
LTRResultIterator textline(*this);
textline.RestartRow();
while (!textline.PositionedAtSameWord(it_)) {
this_word_index++;
textline.Next(RIL_WORD);
}
return this_word_index;
}
void ResultIterator::MoveToLogicalStartOfWord() {
if (word_length_ == 0) {
BeginWord(0);
return;
}
GenericVector<int> blob_order;
CalculateBlobOrder(&blob_order);
if (blob_order.size() == 0 || blob_order[0] == 0) return;
BeginWord(blob_order[0]);
}
bool ResultIterator::IsAtFinalSymbolOfWord() const {
if (!it_->word()) return true;
GenericVector<int> blob_order;
CalculateBlobOrder(&blob_order);
return blob_order.size() == 0 || blob_order.back() == blob_index_;
}
bool ResultIterator::IsAtFirstSymbolOfWord() const {
if (!it_->word()) return true;
GenericVector<int> blob_order;
CalculateBlobOrder(&blob_order);
return blob_order.size() == 0 || blob_order[0] == blob_index_;
}
void ResultIterator::AppendSuffixMarks(STRING *text) const {
if (!it_->word()) return;
bool reading_direction_is_ltr =
current_paragraph_is_ltr_ ^ in_minor_direction_;
// scan forward to see what meta-information the word ordering algorithm
// left us.
// If this word is at the *end* of a minor run, insert the other
// direction's mark; else if this was a complex word, insert the
// current reading order's mark.
GenericVectorEqEq<int> textline_order;
CalculateTextlineOrder(current_paragraph_is_ltr_,
*this, &textline_order);
int this_word_index = LTRWordIndex();
int i = textline_order.get_index(this_word_index);
if (i < 0) return;
int last_non_word_mark = 0;
for (i++; i < textline_order.size() && textline_order[i] < 0; i++) {
last_non_word_mark = textline_order[i];
}
if (last_non_word_mark == kComplexWord) {
*text += reading_direction_is_ltr ? kLRM : kRLM;
} else if (last_non_word_mark == kMinorRunEnd) {
if (current_paragraph_is_ltr_) {
*text += kLRM;
} else {
*text += kRLM;
}
}
}
void ResultIterator::MoveToLogicalStartOfTextline() {
GenericVectorEqEq<int> word_indices;
RestartRow();
CalculateTextlineOrder(current_paragraph_is_ltr_,
dynamic_cast<const LTRResultIterator&>(*this),
&word_indices);
int i = 0;
for (; i < word_indices.size() && word_indices[i] < 0; i++) {
if (word_indices[i] == kMinorRunStart) in_minor_direction_ = true;
else if (word_indices[i] == kMinorRunEnd) in_minor_direction_ = false;
}
if (in_minor_direction_) at_beginning_of_minor_run_ = true;
if (i >= word_indices.size()) return;
int first_word_index = word_indices[i];
for (int j = 0; j < first_word_index; j++) {
PageIterator::Next(RIL_WORD);
}
MoveToLogicalStartOfWord();
}
void ResultIterator::Begin() {
LTRResultIterator::Begin();
current_paragraph_is_ltr_ = CurrentParagraphIsLtr();
in_minor_direction_ = false;
at_beginning_of_minor_run_ = false;
MoveToLogicalStartOfTextline();
}
bool ResultIterator::Next(PageIteratorLevel level) {
if (it_->block() == NULL) return false; // already at end!
switch (level) {
case RIL_BLOCK: // explicit fall-through
case RIL_PARA: // explicit fall-through
case RIL_TEXTLINE:
if (!PageIterator::Next(level)) return false;
if (IsWithinFirstTextlineOfParagraph()) {
// if we've advanced to a new paragraph,
// recalculate current_paragraph_is_ltr_
current_paragraph_is_ltr_ = CurrentParagraphIsLtr();
}
in_minor_direction_ = false;
MoveToLogicalStartOfTextline();
return it_->block() != NULL;
case RIL_SYMBOL:
{
GenericVector<int> blob_order;
CalculateBlobOrder(&blob_order);
int next_blob = 0;
while (next_blob < blob_order.size() &&
blob_index_ != blob_order[next_blob])
next_blob++;
next_blob++;
if (next_blob < blob_order.size()) {
// we're in the same word; simply advance one blob.
BeginWord(blob_order[next_blob]);
at_beginning_of_minor_run_ = false;
return true;
}
level = RIL_WORD; // we've fallen through to the next word.
}
case RIL_WORD: // explicit fall-through.
{
if (it_->word() == NULL) return Next(RIL_BLOCK);
GenericVectorEqEq<int> word_indices;
int this_word_index = LTRWordIndex();
CalculateTextlineOrder(current_paragraph_is_ltr_,
*this,
&word_indices);
int final_real_index = word_indices.size() - 1;
while (final_real_index > 0 && word_indices[final_real_index] < 0)
final_real_index--;
for (int i = 0; i < final_real_index; i++) {
if (word_indices[i] == this_word_index) {
int j = i + 1;
for (; j < final_real_index && word_indices[j] < 0; j++) {
if (word_indices[j] == kMinorRunStart) in_minor_direction_ = true;
if (word_indices[j] == kMinorRunEnd) in_minor_direction_ = false;
}
at_beginning_of_minor_run_ = (word_indices[j - 1] == kMinorRunStart);
// awesome, we move to word_indices[j]
if (BidiDebug(3)) {
tprintf("Next(RIL_WORD): %d -> %d\n",
this_word_index, word_indices[j]);
}
PageIterator::RestartRow();
for (int k = 0; k < word_indices[j]; k++) {
PageIterator::Next(RIL_WORD);
}
MoveToLogicalStartOfWord();
return true;
}
}
if (BidiDebug(3)) {
tprintf("Next(RIL_WORD): %d -> EOL\n", this_word_index);
}
// we're going off the end of the text line.
return Next(RIL_TEXTLINE);
}
}
ASSERT_HOST(false); // shouldn't happen.
return false;
}
bool ResultIterator::IsAtBeginningOf(PageIteratorLevel level) const {
if (it_->block() == NULL) return false; // Already at the end!
if (it_->word() == NULL) return true; // In an image block.
if (level == RIL_SYMBOL) return true; // Always at beginning of a symbol.
bool at_word_start = IsAtFirstSymbolOfWord();
if (level == RIL_WORD) return at_word_start;
ResultIterator line_start(*this);
// move to the first word in the line...
line_start.MoveToLogicalStartOfTextline();
bool at_textline_start = at_word_start && *line_start.it_ == *it_;
if (level == RIL_TEXTLINE) return at_textline_start;
// now we move to the left-most word...
line_start.RestartRow();
bool at_block_start = at_textline_start &&
line_start.it_->block() != line_start.it_->prev_block();
if (level == RIL_BLOCK) return at_block_start;
bool at_para_start = at_block_start ||
(at_textline_start &&
line_start.it_->row()->row->para() !=
line_start.it_->prev_row()->row->para());
if (level == RIL_PARA) return at_para_start;
ASSERT_HOST(false); // shouldn't happen.
return false;
}
/**
* NOTE! This is an exact copy of PageIterator::IsAtFinalElement with the
* change that the variable next is now a ResultIterator instead of a
* PageIterator.
*/
bool ResultIterator::IsAtFinalElement(PageIteratorLevel level,
PageIteratorLevel element) const {
if (Empty(element)) return true; // Already at the end!
// The result is true if we step forward by element and find we are
// at the the end of the page or at beginning of *all* levels in:
// [level, element).
// When there is more than one level difference between element and level,
// we could for instance move forward one symbol and still be at the first
// word on a line, so we also have to be at the first symbol in a word.
ResultIterator next(*this);
next.Next(element);
if (next.Empty(element)) return true; // Reached the end of the page.
while (element > level) {
element = static_cast<PageIteratorLevel>(element - 1);
if (!next.IsAtBeginningOf(element))
return false;
}
return true;
}
/**
* Returns the null terminated UTF-8 encoded text string for the current
* object at the given level. Use delete [] to free after use.
*/
char* ResultIterator::GetUTF8Text(PageIteratorLevel level) const {
if (it_->word() == NULL) return NULL; // Already at the end!
STRING text;
switch (level) {
case RIL_BLOCK:
{
ResultIterator pp(*this);
do {
pp.AppendUTF8ParagraphText(&text);
} while (pp.Next(RIL_PARA) && pp.it_->block() == it_->block());
}
break;
case RIL_PARA:
AppendUTF8ParagraphText(&text);
break;
case RIL_TEXTLINE:
{
ResultIterator it(*this);
it.MoveToLogicalStartOfTextline();
it.IterateAndAppendUTF8TextlineText(&text);
}
break;
case RIL_WORD:
AppendUTF8WordText(&text);
break;
case RIL_SYMBOL:
{
bool reading_direction_is_ltr =
current_paragraph_is_ltr_ ^ in_minor_direction_;
if (at_beginning_of_minor_run_) {
text += reading_direction_is_ltr ? kLRM : kRLM;
}
text = it_->word()->BestUTF8(blob_index_, !reading_direction_is_ltr);
if (IsAtFinalSymbolOfWord()) AppendSuffixMarks(&text);
}
break;
}
int length = text.length() + 1;
char* result = new char[length];
strncpy(result, text.string(), length);
return result;
}
void ResultIterator::AppendUTF8WordText(STRING *text) const {
if (!it_->word()) return;
ASSERT_HOST(it_->word()->best_choice != NULL);
bool reading_direction_is_ltr =
current_paragraph_is_ltr_ ^ in_minor_direction_;
if (at_beginning_of_minor_run_) {
*text += reading_direction_is_ltr ? kLRM : kRLM;
}
GenericVector<int> blob_order;
CalculateBlobOrder(&blob_order);
for (int i = 0; i < blob_order.size(); i++) {
*text += it_->word()->BestUTF8(blob_order[i], !reading_direction_is_ltr);
}
AppendSuffixMarks(text);
}
void ResultIterator::IterateAndAppendUTF8TextlineText(STRING *text) {
if (Empty(RIL_WORD)) {
Next(RIL_WORD);
return;
}
if (BidiDebug(1)) {
GenericVectorEqEq<int> textline_order;
GenericVector<StrongScriptDirection> dirs;
CalculateTextlineOrder(current_paragraph_is_ltr_,
*this, &dirs, &textline_order);
tprintf("Strong Script dirs [%p/P=%s]: ", it_->row(),
current_paragraph_is_ltr_ ? "ltr" : "rtl");
PrintScriptDirs(dirs);
tprintf("Logical textline order [%p/P=%s]: ", it_->row(),
current_paragraph_is_ltr_ ? "ltr" : "rtl");
for (int i = 0; i < textline_order.size(); i++) {
tprintf("%d ", textline_order[i]);
}
tprintf("\n");
}
int words_appended = 0;
do {
int numSpaces = preserve_interword_spaces_ ? it_->word()->word->space() :
(words_appended > 0);
for(int i = 0 ; i < numSpaces ; ++i) {
*text += " ";
}
AppendUTF8WordText(text);
words_appended++;
} while (Next(RIL_WORD) && !IsAtBeginningOf(RIL_TEXTLINE));
if (BidiDebug(1)) {
tprintf("%d words printed\n", words_appended);
}
*text += line_separator_;
// If we just finished a paragraph, add an extra newline.
if (it_->block() == NULL || IsAtBeginningOf(RIL_PARA))
*text += paragraph_separator_;
}
void ResultIterator::AppendUTF8ParagraphText(STRING *text) const {
ResultIterator it(*this);
it.RestartParagraph();
it.MoveToLogicalStartOfTextline();
if (it.Empty(RIL_WORD)) return;
do {
it.IterateAndAppendUTF8TextlineText(text);
} while (it.it_->block() != NULL && !it.IsAtBeginningOf(RIL_PARA));
}
bool ResultIterator::BidiDebug(int min_level) const {
int debug_level = 1;
IntParam *p = ParamUtils::FindParam<IntParam>(
"bidi_debug", GlobalParams()->int_params,
tesseract_->params()->int_params);
if (p != NULL) debug_level = (inT32)(*p);
return debug_level >= min_level;
}
} // namespace tesseract.
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// neuron.cpp: The implementation of a class for an object
// that represents a single neuron in a neural network
#include "neuron.h"
#include "input_file_buffer.h"
namespace tesseract {
// Instantiate all supported templates
template bool Neuron::ReadBinary(InputFileBuffer *input_buffer);
// default and only constructor
Neuron::Neuron() {
Init();
}
// virtual destructor
Neuron::~Neuron() {
}
// Initializer
void Neuron::Init() {
id_ = -1;
frwd_dirty_ = false;
fan_in_.clear();
fan_in_weights_.clear();
activation_ = 0.0f;
output_ = 0.0f;
bias_ = 0.0f;
node_type_ = Unknown;
}
// Computes the activation and output of the neuron if not fresh
// by pulling the outputs of all fan-in neurons
void Neuron::FeedForward() {
if (!frwd_dirty_ ) {
return;
}
// nothing to do for input nodes: just pass the input to the o/p
// otherwise, pull the output of all fan-in neurons
if (node_type_ != Input) {
int fan_in_cnt = fan_in_.size();
// sum out the activation
activation_ = -bias_;
for (int in = 0; in < fan_in_cnt; in++) {
if (fan_in_[in]->frwd_dirty_) {
fan_in_[in]->FeedForward();
}
activation_ += ((*(fan_in_weights_[in])) * fan_in_[in]->output_);
}
// sigmoid it
output_ = Sigmoid(activation_);
}
frwd_dirty_ = false;
}
// set the type of the neuron
void Neuron::set_node_type(NeuronTypes Type) {
node_type_ = Type;
}
// Adds new connections *to* this neuron *From*
// a target neuron using specfied params
// Note that what is actually copied in this function are pointers to the
// specified Neurons and weights and not the actualt values. This is by
// design to centralize the alloction of neurons and weights and so
// increase the locality of reference and improve cache-hits resulting
// in a faster net. This technique resulted in a 2X-10X speedup
// (depending on network size and processor)
void Neuron::AddFromConnection(Neuron *neurons,
float *wts_offset,
int from_cnt) {
for (int in = 0; in < from_cnt; in++) {
fan_in_.push_back(neurons + in);
fan_in_weights_.push_back(wts_offset + in);
}
}
// fast computation of sigmoid function using a lookup table
// defined in sigmoid_table.cpp
float Neuron::Sigmoid(float activation) {
if (activation <= -10.0f) {
return 0.0f;
} else if (activation >= 10.0f) {
return 1.0f;
} else {
return kSigmoidTable[static_cast<int>(100 * (activation + 10.0))];
}
}
}
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// neuron.h: Declarations of a class for an object that
// represents a single neuron in a neural network
//
#ifndef NEURON_H
#define NEURON_H
#include <math.h>
#include <vector>
#ifdef USE_STD_NAMESPACE
using std::vector;
#endif
namespace tesseract {
// Input Node bias values
static const float kInputNodeBias = 0.0f;
class Neuron {
public:
// Types of nodes
enum NeuronTypes {
Unknown = 0,
Input,
Hidden,
Output
};
Neuron();
~Neuron();
// set the forward dirty flag indicating that the
// activation of the net is not fresh
void Clear() {
frwd_dirty_ = true;
}
// Read a binary representation of the neuron info from
// an input buffer.
template <class BuffType> bool ReadBinary(BuffType *input_buff) {
float val;
if (input_buff->Read(&val, sizeof(val)) != sizeof(val)) {
return false;
}
// input nodes should have no biases
if (node_type_ == Input) {
bias_ = kInputNodeBias;
} else {
bias_ = val;
}
// read fanin count
int fan_in_cnt;
if (input_buff->Read(&fan_in_cnt, sizeof(fan_in_cnt)) !=
sizeof(fan_in_cnt)) {
return false;
}
// validate fan-in cnt
if (fan_in_cnt != fan_in_.size()) {
return false;
}
// read the weights
for (int in = 0; in < fan_in_cnt; in++) {
if (input_buff->Read(&val, sizeof(val)) != sizeof(val)) {
return false;
}
*(fan_in_weights_[in]) = val;
}
return true;
}
// Add a new connection from this neuron *From*
// a target neuron using specfied params
// Note that what is actually copied in this function are pointers to the
// specified Neurons and weights and not the actualt values. This is by
// design to centralize the alloction of neurons and weights and so
// increase the locality of reference and improve cache-hits resulting
// in a faster net. This technique resulted in a 2X-10X speedup
// (depending on network size and processor)
void AddFromConnection(Neuron *neuron_vec,
float *wts_offset,
int from_cnt);
// Set the type of a neuron
void set_node_type(NeuronTypes type);
// Computes the output of the node by
// "pulling" the output of the fan-in nodes
void FeedForward();
// fast computation of sigmoid function using a lookup table
// defined in sigmoid_table.cpp
static float Sigmoid(float activation);
// Accessor functions
float output() const {
return output_;
}
void set_output(float out_val) {
output_ = out_val;
}
int id() const {
return id_;
}
int fan_in_cnt() const {
return fan_in_.size();
}
Neuron * fan_in(int idx) const {
return fan_in_[idx];
}
float fan_in_wts(int idx) const {
return *(fan_in_weights_[idx]);
}
void set_id(int id) {
id_ = id;
}
float bias() const {
return bias_;
}
Neuron::NeuronTypes node_type() const {
return node_type_;
}
protected:
// Type of Neuron
NeuronTypes node_type_;
// unqique id of the neuron
int id_;
// node bias
float bias_;
// node net activation
float activation_;
// node output
float output_;
// pointers to fanin nodes
vector<Neuron *> fan_in_;
// pointers to fanin weights
vector<float *> fan_in_weights_;
// Sigmoid function lookup table used for fast computation
// of sigmoid function
static const float kSigmoidTable[];
// flag determining if the activation of the node
// is fresh or not (dirty)
bool frwd_dirty_;
// Initializer
void Init();
};
}
#endif // NEURON_H__
| C++ |
// Copyright 2007 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// sigmoid_table.cpp: Sigmoid function lookup table
#include "neuron.h"
namespace tesseract {
const float Neuron::kSigmoidTable[] = {
4.53979E-05f, 4.58541E-05f, 4.63149E-05f, 4.67804E-05f,
4.72505E-05f, 4.77254E-05f, 4.8205E-05f, 4.86894E-05f,
4.91787E-05f, 4.9673E-05f, 5.01722E-05f, 5.06764E-05f,
5.11857E-05f, 5.17001E-05f, 5.22196E-05f, 5.27444E-05f,
5.32745E-05f, 5.38099E-05f, 5.43506E-05f, 5.48968E-05f,
5.54485E-05f, 5.60058E-05f, 5.65686E-05f, 5.71371E-05f,
5.77113E-05f, 5.82913E-05f, 5.88771E-05f, 5.94688E-05f,
6.00664E-05f, 6.067E-05f, 6.12797E-05f, 6.18956E-05f,
6.25176E-05f, 6.31459E-05f, 6.37805E-05f, 6.44214E-05f,
6.50688E-05f, 6.57227E-05f, 6.63832E-05f, 6.70503E-05f,
6.77241E-05f, 6.84047E-05f, 6.90922E-05f, 6.97865E-05f,
7.04878E-05f, 7.11962E-05f, 7.19117E-05f, 7.26343E-05f,
7.33643E-05f, 7.41016E-05f, 7.48462E-05f, 7.55984E-05f,
7.63581E-05f, 7.71255E-05f, 7.79005E-05f, 7.86834E-05f,
7.94741E-05f, 8.02728E-05f, 8.10794E-05f, 8.18942E-05f,
8.27172E-05f, 8.35485E-05f, 8.43881E-05f, 8.52361E-05f,
8.60927E-05f, 8.69579E-05f, 8.78317E-05f, 8.87144E-05f,
8.96059E-05f, 9.05064E-05f, 9.14159E-05f, 9.23345E-05f,
9.32624E-05f, 9.41996E-05f, 9.51463E-05f, 9.61024E-05f,
9.70682E-05f, 9.80436E-05f, 9.90289E-05f, 0.000100024f,
0.000101029f, 0.000102044f, 0.00010307f, 0.000104106f,
0.000105152f, 0.000106209f, 0.000107276f, 0.000108354f,
0.000109443f, 0.000110542f, 0.000111653f, 0.000112775f,
0.000113909f, 0.000115053f, 0.000116209f, 0.000117377f,
0.000118557f, 0.000119748f, 0.000120951f, 0.000122167f,
0.000123395f, 0.000124635f, 0.000125887f, 0.000127152f,
0.00012843f, 0.00012972f, 0.000131024f, 0.000132341f,
0.00013367f, 0.000135014f, 0.00013637f, 0.000137741f,
0.000139125f, 0.000140523f, 0.000141935f, 0.000143361f,
0.000144802f, 0.000146257f, 0.000147727f, 0.000149211f,
0.00015071f, 0.000152225f, 0.000153754f, 0.000155299f,
0.00015686f, 0.000158436f, 0.000160028f, 0.000161636f,
0.000163261f, 0.000164901f, 0.000166558f, 0.000168232f,
0.000169922f, 0.00017163f, 0.000173354f, 0.000175096f,
0.000176856f, 0.000178633f, 0.000180428f, 0.000182241f,
0.000184072f, 0.000185922f, 0.00018779f, 0.000189677f,
0.000191583f, 0.000193508f, 0.000195452f, 0.000197416f,
0.0001994f, 0.000201403f, 0.000203427f, 0.000205471f,
0.000207536f, 0.000209621f, 0.000211727f, 0.000213855f,
0.000216003f, 0.000218174f, 0.000220366f, 0.00022258f,
0.000224817f, 0.000227076f, 0.000229357f, 0.000231662f,
0.00023399f, 0.000236341f, 0.000238715f, 0.000241114f,
0.000243537f, 0.000245984f, 0.000248455f, 0.000250951f,
0.000253473f, 0.00025602f, 0.000258592f, 0.00026119f,
0.000263815f, 0.000266465f, 0.000269143f, 0.000271847f,
0.000274578f, 0.000277337f, 0.000280123f, 0.000282938f,
0.000285781f, 0.000288652f, 0.000291552f, 0.000294481f,
0.00029744f, 0.000300429f, 0.000303447f, 0.000306496f,
0.000309575f, 0.000312685f, 0.000315827f, 0.000319f,
0.000322205f, 0.000325442f, 0.000328712f, 0.000332014f,
0.00033535f, 0.000338719f, 0.000342122f, 0.00034556f,
0.000349031f, 0.000352538f, 0.00035608f, 0.000359657f,
0.00036327f, 0.00036692f, 0.000370606f, 0.000374329f,
0.00037809f, 0.000381888f, 0.000385725f, 0.0003896f,
0.000393514f, 0.000397467f, 0.00040146f, 0.000405494f,
0.000409567f, 0.000413682f, 0.000417838f, 0.000422035f,
0.000426275f, 0.000430557f, 0.000434882f, 0.000439251f,
0.000443664f, 0.000448121f, 0.000452622f, 0.000457169f,
0.000461762f, 0.0004664f, 0.000471085f, 0.000475818f,
0.000480597f, 0.000485425f, 0.000490301f, 0.000495226f,
0.000500201f, 0.000505226f, 0.000510301f, 0.000515427f,
0.000520604f, 0.000525833f, 0.000531115f, 0.00053645f,
0.000541839f, 0.000547281f, 0.000552779f, 0.000558331f,
0.000563939f, 0.000569604f, 0.000575325f, 0.000581104f,
0.00058694f, 0.000592836f, 0.00059879f, 0.000604805f,
0.000610879f, 0.000617015f, 0.000623212f, 0.000629472f,
0.000635794f, 0.00064218f, 0.00064863f, 0.000655144f,
0.000661724f, 0.00066837f, 0.000675083f, 0.000681863f,
0.000688711f, 0.000695628f, 0.000702614f, 0.00070967f,
0.000716798f, 0.000723996f, 0.000731267f, 0.000738611f,
0.000746029f, 0.000753521f, 0.000761088f, 0.000768731f,
0.000776451f, 0.000784249f, 0.000792124f, 0.000800079f,
0.000808113f, 0.000816228f, 0.000824425f, 0.000832703f,
0.000841065f, 0.000849511f, 0.000858041f, 0.000866657f,
0.00087536f, 0.000884149f, 0.000893027f, 0.000901994f,
0.000911051f, 0.000920199f, 0.000929439f, 0.000938771f,
0.000948197f, 0.000957717f, 0.000967333f, 0.000977045f,
0.000986855f, 0.000996763f, 0.001006771f, 0.001016879f,
0.001027088f, 0.0010374f, 0.001047815f, 0.001058334f,
0.00106896f, 0.001079691f, 0.00109053f, 0.001101478f,
0.001112536f, 0.001123705f, 0.001134985f, 0.001146379f,
0.001157887f, 0.00116951f, 0.00118125f, 0.001193108f,
0.001205084f, 0.001217181f, 0.001229399f, 0.001241739f,
0.001254203f, 0.001266792f, 0.001279507f, 0.00129235f,
0.001305321f, 0.001318423f, 0.001331655f, 0.001345021f,
0.00135852f, 0.001372155f, 0.001385926f, 0.001399835f,
0.001413884f, 0.001428073f, 0.001442405f, 0.00145688f,
0.001471501f, 0.001486267f, 0.001501182f, 0.001516247f,
0.001531462f, 0.001546829f, 0.001562351f, 0.001578028f,
0.001593862f, 0.001609855f, 0.001626008f, 0.001642323f,
0.001658801f, 0.001675444f, 0.001692254f, 0.001709233f,
0.001726381f, 0.001743701f, 0.001761195f, 0.001778864f,
0.00179671f, 0.001814734f, 0.001832939f, 0.001851326f,
0.001869898f, 0.001888655f, 0.0019076f, 0.001926735f,
0.001946061f, 0.001965581f, 0.001985296f, 0.002005209f,
0.00202532f, 0.002045634f, 0.00206615f, 0.002086872f,
0.002107801f, 0.00212894f, 0.00215029f, 0.002171854f,
0.002193633f, 0.002215631f, 0.002237849f, 0.002260288f,
0.002282953f, 0.002305844f, 0.002328964f, 0.002352316f,
0.002375901f, 0.002399721f, 0.002423781f, 0.00244808f,
0.002472623f, 0.002497411f, 0.002522447f, 0.002547734f,
0.002573273f, 0.002599068f, 0.00262512f, 0.002651433f,
0.002678009f, 0.002704851f, 0.002731961f, 0.002759342f,
0.002786996f, 0.002814927f, 0.002843137f, 0.002871629f,
0.002900406f, 0.00292947f, 0.002958825f, 0.002988472f,
0.003018416f, 0.003048659f, 0.003079205f, 0.003110055f,
0.003141213f, 0.003172683f, 0.003204467f, 0.003236568f,
0.00326899f, 0.003301735f, 0.003334807f, 0.00336821f,
0.003401946f, 0.003436018f, 0.003470431f, 0.003505187f,
0.00354029f, 0.003575744f, 0.003611551f, 0.003647715f,
0.00368424f, 0.003721129f, 0.003758387f, 0.003796016f,
0.00383402f, 0.003872403f, 0.00391117f, 0.003950322f,
0.003989865f, 0.004029802f, 0.004070138f, 0.004110875f,
0.004152019f, 0.004193572f, 0.00423554f, 0.004277925f,
0.004320734f, 0.004363968f, 0.004407633f, 0.004451734f,
0.004496273f, 0.004541256f, 0.004586687f, 0.004632571f,
0.004678911f, 0.004725713f, 0.00477298f, 0.004820718f,
0.004868931f, 0.004917624f, 0.004966802f, 0.005016468f,
0.005066629f, 0.005117289f, 0.005168453f, 0.005220126f,
0.005272312f, 0.005325018f, 0.005378247f, 0.005432006f,
0.005486299f, 0.005541132f, 0.005596509f, 0.005652437f,
0.005708921f, 0.005765966f, 0.005823577f, 0.005881761f,
0.005940522f, 0.005999867f, 0.006059801f, 0.006120331f,
0.006181461f, 0.006243198f, 0.006305547f, 0.006368516f,
0.006432108f, 0.006496332f, 0.006561193f, 0.006626697f,
0.006692851f, 0.006759661f, 0.006827132f, 0.006895273f,
0.006964089f, 0.007033587f, 0.007103774f, 0.007174656f,
0.00724624f, 0.007318533f, 0.007391541f, 0.007465273f,
0.007539735f, 0.007614933f, 0.007690876f, 0.00776757f,
0.007845023f, 0.007923242f, 0.008002235f, 0.008082009f,
0.008162571f, 0.00824393f, 0.008326093f, 0.008409068f,
0.008492863f, 0.008577485f, 0.008662944f, 0.008749246f,
0.0088364f, 0.008924415f, 0.009013299f, 0.009103059f,
0.009193705f, 0.009285246f, 0.009377689f, 0.009471044f,
0.009565319f, 0.009660523f, 0.009756666f, 0.009853756f,
0.009951802f, 0.010050814f, 0.010150801f, 0.010251772f,
0.010353738f, 0.010456706f, 0.010560688f, 0.010665693f,
0.01077173f, 0.01087881f, 0.010986943f, 0.011096138f,
0.011206406f, 0.011317758f, 0.011430203f, 0.011543752f,
0.011658417f, 0.011774206f, 0.011891132f, 0.012009204f,
0.012128435f, 0.012248835f, 0.012370415f, 0.012493186f,
0.012617161f, 0.012742349f, 0.012868764f, 0.012996417f,
0.013125318f, 0.013255481f, 0.013386918f, 0.01351964f,
0.013653659f, 0.013788989f, 0.01392564f, 0.014063627f,
0.014202961f, 0.014343656f, 0.014485724f, 0.014629178f,
0.014774032f, 0.014920298f, 0.01506799f, 0.015217121f,
0.015367706f, 0.015519757f, 0.015673288f, 0.015828314f,
0.015984848f, 0.016142905f, 0.016302499f, 0.016463645f,
0.016626356f, 0.016790648f, 0.016956536f, 0.017124033f,
0.017293157f, 0.01746392f, 0.01763634f, 0.017810432f,
0.01798621f, 0.018163691f, 0.018342891f, 0.018523825f,
0.01870651f, 0.018890962f, 0.019077197f, 0.019265233f,
0.019455085f, 0.01964677f, 0.019840306f, 0.020035709f,
0.020232997f, 0.020432187f, 0.020633297f, 0.020836345f,
0.021041347f, 0.021248323f, 0.02145729f, 0.021668266f,
0.021881271f, 0.022096322f, 0.022313439f, 0.022532639f,
0.022753943f, 0.02297737f, 0.023202938f, 0.023430668f,
0.023660578f, 0.023892689f, 0.024127021f, 0.024363594f,
0.024602428f, 0.024843544f, 0.025086962f, 0.025332703f,
0.025580788f, 0.025831239f, 0.026084075f, 0.02633932f,
0.026596994f, 0.026857119f, 0.027119717f, 0.027384811f,
0.027652422f, 0.027922574f, 0.028195288f, 0.028470588f,
0.028748496f, 0.029029036f, 0.029312231f, 0.029598104f,
0.02988668f, 0.030177981f, 0.030472033f, 0.030768859f,
0.031068484f, 0.031370932f, 0.031676228f, 0.031984397f,
0.032295465f, 0.032609455f, 0.032926395f, 0.033246309f,
0.033569223f, 0.033895164f, 0.034224158f, 0.03455623f,
0.034891409f, 0.035229719f, 0.035571189f, 0.035915846f,
0.036263716f, 0.036614828f, 0.036969209f, 0.037326887f,
0.037687891f, 0.038052247f, 0.038419986f, 0.038791134f,
0.039165723f, 0.03954378f, 0.039925334f, 0.040310415f,
0.040699054f, 0.041091278f, 0.041487119f, 0.041886607f,
0.042289772f, 0.042696644f, 0.043107255f, 0.043521635f,
0.043939815f, 0.044361828f, 0.044787703f, 0.045217473f,
0.045651171f, 0.046088827f, 0.046530475f, 0.046976146f,
0.047425873f, 0.04787969f, 0.048337629f, 0.048799723f,
0.049266006f, 0.049736512f, 0.050211273f, 0.050690325f,
0.051173701f, 0.051661435f, 0.052153563f, 0.052650118f,
0.053151136f, 0.053656652f, 0.0541667f, 0.054681317f,
0.055200538f, 0.055724398f, 0.056252934f, 0.056786181f,
0.057324176f, 0.057866955f, 0.058414556f, 0.058967013f,
0.059524366f, 0.06008665f, 0.060653903f, 0.061226163f,
0.061803466f, 0.062385851f, 0.062973356f, 0.063566018f,
0.064163876f, 0.064766969f, 0.065375333f, 0.065989009f,
0.066608036f, 0.067232451f, 0.067862294f, 0.068497604f,
0.06913842f, 0.069784783f, 0.070436731f, 0.071094304f,
0.071757542f, 0.072426485f, 0.073101173f, 0.073781647f,
0.074467945f, 0.075160109f, 0.07585818f, 0.076562197f,
0.077272202f, 0.077988235f, 0.078710337f, 0.079438549f,
0.080172912f, 0.080913467f, 0.081660255f, 0.082413318f,
0.083172696f, 0.083938432f, 0.084710566f, 0.085489139f,
0.086274194f, 0.087065772f, 0.087863915f, 0.088668663f,
0.089480059f, 0.090298145f, 0.091122961f, 0.09195455f,
0.092792953f, 0.093638212f, 0.094490369f, 0.095349465f,
0.096215542f, 0.097088641f, 0.097968804f, 0.098856073f,
0.099750489f, 0.100652094f, 0.101560928f, 0.102477033f,
0.103400451f, 0.104331223f, 0.10526939f, 0.106214992f,
0.10716807f, 0.108128667f, 0.109096821f, 0.110072574f,
0.111055967f, 0.112047039f, 0.11304583f, 0.114052381f,
0.115066732f, 0.116088922f, 0.117118991f, 0.118156978f,
0.119202922f, 0.120256862f, 0.121318838f, 0.122388887f,
0.123467048f, 0.124553358f, 0.125647857f, 0.12675058f,
0.127861566f, 0.128980852f, 0.130108474f, 0.131244469f,
0.132388874f, 0.133541723f, 0.134703052f, 0.135872897f,
0.137051293f, 0.138238273f, 0.139433873f, 0.140638126f,
0.141851065f, 0.143072723f, 0.144303134f, 0.145542329f,
0.14679034f, 0.148047198f, 0.149312935f, 0.15058758f,
0.151871164f, 0.153163716f, 0.154465265f, 0.15577584f,
0.157095469f, 0.158424179f, 0.159761997f, 0.16110895f,
0.162465063f, 0.163830361f, 0.16520487f, 0.166588614f,
0.167981615f, 0.169383897f, 0.170795482f, 0.172216392f,
0.173646647f, 0.175086268f, 0.176535275f, 0.177993686f,
0.179461519f, 0.180938793f, 0.182425524f, 0.183921727f,
0.185427419f, 0.186942614f, 0.188467325f, 0.190001566f,
0.191545349f, 0.193098684f, 0.194661584f, 0.196234056f,
0.197816111f, 0.199407757f, 0.201009f, 0.202619846f,
0.204240302f, 0.205870372f, 0.207510059f, 0.209159365f,
0.210818293f, 0.212486844f, 0.214165017f, 0.215852811f,
0.217550224f, 0.219257252f, 0.220973892f, 0.222700139f,
0.224435986f, 0.226181426f, 0.227936451f, 0.229701051f,
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0.999808417f, 0.999810323f, 0.99981221f, 0.999814078f,
0.999815928f, 0.999817759f, 0.999819572f, 0.999821367f,
0.999823144f, 0.999824904f, 0.999826646f, 0.99982837f,
0.999830078f, 0.999831768f, 0.999833442f, 0.999835099f,
0.999836739f, 0.999838364f, 0.999839972f, 0.999841564f,
0.99984314f, 0.999844701f, 0.999846246f, 0.999847775f,
0.99984929f, 0.999850789f, 0.999852273f, 0.999853743f,
0.999855198f, 0.999856639f, 0.999858065f, 0.999859477f,
0.999860875f, 0.999862259f, 0.99986363f, 0.999864986f,
0.99986633f, 0.999867659f, 0.999868976f, 0.99987028f,
0.99987157f, 0.999872848f, 0.999874113f, 0.999875365f,
0.999876605f, 0.999877833f, 0.999879049f, 0.999880252f,
0.999881443f, 0.999882623f, 0.999883791f, 0.999884947f,
0.999886091f, 0.999887225f, 0.999888347f, 0.999889458f,
0.999890557f, 0.999891646f, 0.999892724f, 0.999893791f,
0.999894848f, 0.999895894f, 0.99989693f, 0.999897956f,
0.999898971f, 0.999899976f, 0.999900971f, 0.999901956f,
0.999902932f, 0.999903898f, 0.999904854f, 0.9999058f,
0.999906738f, 0.999907665f, 0.999908584f, 0.999909494f,
0.999910394f, 0.999911286f, 0.999912168f, 0.999913042f,
0.999913907f, 0.999914764f, 0.999915612f, 0.999916452f,
0.999917283f, 0.999918106f, 0.999918921f, 0.999919727f,
0.999920526f, 0.999921317f, 0.999922099f, 0.999922875f,
0.999923642f, 0.999924402f, 0.999925154f, 0.999925898f,
0.999926636f, 0.999927366f, 0.999928088f, 0.999928804f,
0.999929512f, 0.999930213f, 0.999930908f, 0.999931595f,
0.999932276f, 0.99993295f, 0.999933617f, 0.999934277f,
0.999934931f, 0.999935579f, 0.99993622f, 0.999936854f,
0.999937482f, 0.999938104f, 0.99993872f, 0.99993933f,
0.999939934f, 0.999940531f, 0.999941123f, 0.999941709f,
0.999942289f, 0.999942863f, 0.999943431f, 0.999943994f,
0.999944551f, 0.999945103f, 0.999945649f, 0.99994619f,
0.999946726f, 0.999947256f, 0.99994778f, 0.9999483f,
0.999948814f, 0.999949324f, 0.999949828f, 0.999950327f,
0.999950821f, 0.999951311f, 0.999951795f, 0.999952275f,
0.999952749f, 0.99995322f, 0.999953685f, 0.999954146f,
0.999954602f
};
} // namespace tesseract
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// neural_net.cpp: Declarations of a class for an object that
// represents an arbitrary network of neurons
//
#include <vector>
#include <string>
#include "neural_net.h"
#include "input_file_buffer.h"
namespace tesseract {
NeuralNet::NeuralNet() {
Init();
}
NeuralNet::~NeuralNet() {
// clean up the wts chunks vector
for (int vec = 0; vec < static_cast<int>(wts_vec_.size()); vec++) {
delete wts_vec_[vec];
}
// clean up neurons
delete []neurons_;
// clean up nodes
for (int node_idx = 0; node_idx < neuron_cnt_; node_idx++) {
delete []fast_nodes_[node_idx].inputs;
}
}
// Initiaization function
void NeuralNet::Init() {
read_only_ = true;
auto_encoder_ = false;
alloc_wgt_cnt_ = 0;
wts_cnt_ = 0;
neuron_cnt_ = 0;
in_cnt_ = 0;
out_cnt_ = 0;
wts_vec_.clear();
neurons_ = NULL;
inputs_mean_.clear();
inputs_std_dev_.clear();
inputs_min_.clear();
inputs_max_.clear();
}
// Does a fast feedforward for read_only nets
// Templatized for float and double Types
template <typename Type> bool NeuralNet::FastFeedForward(const Type *inputs,
Type *outputs) {
int node_idx = 0;
Node *node = &fast_nodes_[0];
// feed inputs in and offset them by the pre-computed bias
for (node_idx = 0; node_idx < in_cnt_; node_idx++, node++) {
node->out = inputs[node_idx] - node->bias;
}
// compute nodes activations and outputs
for (;node_idx < neuron_cnt_; node_idx++, node++) {
double activation = -node->bias;
for (int fan_in_idx = 0; fan_in_idx < node->fan_in_cnt; fan_in_idx++) {
activation += (node->inputs[fan_in_idx].input_weight *
node->inputs[fan_in_idx].input_node->out);
}
node->out = Neuron::Sigmoid(activation);
}
// copy the outputs to the output buffers
node = &fast_nodes_[neuron_cnt_ - out_cnt_];
for (node_idx = 0; node_idx < out_cnt_; node_idx++, node++) {
outputs[node_idx] = node->out;
}
return true;
}
// Performs a feedforward for general nets. Used mainly in training mode
// Templatized for float and double Types
template <typename Type> bool NeuralNet::FeedForward(const Type *inputs,
Type *outputs) {
// call the fast version in case of readonly nets
if (read_only_) {
return FastFeedForward(inputs, outputs);
}
// clear all neurons
Clear();
// for auto encoders, apply no input normalization
if (auto_encoder_) {
for (int in = 0; in < in_cnt_; in++) {
neurons_[in].set_output(inputs[in]);
}
} else {
// Input normalization : subtract mean and divide by stddev
for (int in = 0; in < in_cnt_; in++) {
neurons_[in].set_output((inputs[in] - inputs_min_[in]) /
(inputs_max_[in] - inputs_min_[in]));
neurons_[in].set_output((neurons_[in].output() - inputs_mean_[in]) /
inputs_std_dev_[in]);
}
}
// compute the net outputs: follow a pull model each output pulls the
// outputs of its input nodes and so on
for (int out = neuron_cnt_ - out_cnt_; out < neuron_cnt_; out++) {
neurons_[out].FeedForward();
// copy the values to the output buffer
outputs[out] = neurons_[out].output();
}
return true;
}
// Sets a connection between two neurons
bool NeuralNet::SetConnection(int from, int to) {
// allocate the wgt
float *wts = AllocWgt(1);
if (wts == NULL) {
return false;
}
// register the connection
neurons_[to].AddFromConnection(neurons_ + from, wts, 1);
return true;
}
// Create a fast readonly version of the net
bool NeuralNet::CreateFastNet() {
fast_nodes_.resize(neuron_cnt_);
// build the node structures
int wts_cnt = 0;
for (int node_idx = 0; node_idx < neuron_cnt_; node_idx++) {
Node *node = &fast_nodes_[node_idx];
if (neurons_[node_idx].node_type() == Neuron::Input) {
// Input neurons have no fan-in
node->fan_in_cnt = 0;
node->inputs = NULL;
// Input bias is the normalization offset computed from
// training input stats
if (fabs(inputs_max_[node_idx] - inputs_min_[node_idx]) <
kMinInputRange) {
// if the range approaches zero, the stdev is not defined,
// this indicates that this input does not change.
// Set the bias to zero
node->bias = 0.0f;
} else {
node->bias = inputs_min_[node_idx] + (inputs_mean_[node_idx] *
(inputs_max_[node_idx] - inputs_min_[node_idx]));
}
} else {
node->bias = neurons_[node_idx].bias();
node->fan_in_cnt = neurons_[node_idx].fan_in_cnt();
// allocate memory for fan-in nodes
node->inputs = new WeightedNode[node->fan_in_cnt];
if (node->inputs == NULL) {
return false;
}
for (int fan_in = 0; fan_in < node->fan_in_cnt; fan_in++) {
// identify fan-in neuron
const int id = neurons_[node_idx].fan_in(fan_in)->id();
// Feedback connections are not allowed and should never happen
if (id >= node_idx) {
return false;
}
// add the the fan-in neuron and its wgt
node->inputs[fan_in].input_node = &fast_nodes_[id];
float wgt_val = neurons_[node_idx].fan_in_wts(fan_in);
// for input neurons normalize the wgt by the input scaling
// values to save time during feedforward
if (neurons_[node_idx].fan_in(fan_in)->node_type() == Neuron::Input) {
// if the range approaches zero, the stdev is not defined,
// this indicates that this input does not change.
// Set the weight to zero
if (fabs(inputs_max_[id] - inputs_min_[id]) < kMinInputRange) {
wgt_val = 0.0f;
} else {
wgt_val /= ((inputs_max_[id] - inputs_min_[id]) *
inputs_std_dev_[id]);
}
}
node->inputs[fan_in].input_weight = wgt_val;
}
// incr wgt count to validate against at the end
wts_cnt += node->fan_in_cnt;
}
}
// sanity check
return wts_cnt_ == wts_cnt;
}
// returns a pointer to the requested set of weights
// Allocates in chunks
float * NeuralNet::AllocWgt(int wgt_cnt) {
// see if need to allocate a new chunk of wts
if (wts_vec_.size() == 0 || (alloc_wgt_cnt_ + wgt_cnt) > kWgtChunkSize) {
// add the new chunck to the wts_chunks vector
wts_vec_.push_back(new vector<float> (kWgtChunkSize));
alloc_wgt_cnt_ = 0;
}
float *ret_ptr = &((*wts_vec_.back())[alloc_wgt_cnt_]);
// incr usage counts
alloc_wgt_cnt_ += wgt_cnt;
wts_cnt_ += wgt_cnt;
return ret_ptr;
}
// create a new net object using an input file as a source
NeuralNet *NeuralNet::FromFile(const string file_name) {
// open the file
InputFileBuffer input_buff(file_name);
// create a new net object using input buffer
NeuralNet *net_obj = FromInputBuffer(&input_buff);
return net_obj;
}
// create a net object from an input buffer
NeuralNet *NeuralNet::FromInputBuffer(InputFileBuffer *ib) {
// create a new net object
NeuralNet *net_obj = new NeuralNet();
if (net_obj == NULL) {
return NULL;
}
// load the net
if (!net_obj->ReadBinary(ib)) {
delete net_obj;
net_obj = NULL;
}
return net_obj;
}
// Compute the output of a specific output node.
// This function is useful for application that are interested in a single
// output of the net and do not want to waste time on the rest
// This is the fast-read-only version of this function
template <typename Type> bool NeuralNet::FastGetNetOutput(const Type *inputs,
int output_id,
Type *output) {
// feed inputs in and offset them by the pre-computed bias
int node_idx = 0;
Node *node = &fast_nodes_[0];
for (node_idx = 0; node_idx < in_cnt_; node_idx++, node++) {
node->out = inputs[node_idx] - node->bias;
}
// compute nodes' activations and outputs for hidden nodes if any
int hidden_node_cnt = neuron_cnt_ - out_cnt_;
for (;node_idx < hidden_node_cnt; node_idx++, node++) {
double activation = -node->bias;
for (int fan_in_idx = 0; fan_in_idx < node->fan_in_cnt; fan_in_idx++) {
activation += (node->inputs[fan_in_idx].input_weight *
node->inputs[fan_in_idx].input_node->out);
}
node->out = Neuron::Sigmoid(activation);
}
// compute the output of the required output node
node += output_id;
double activation = -node->bias;
for (int fan_in_idx = 0; fan_in_idx < node->fan_in_cnt; fan_in_idx++) {
activation += (node->inputs[fan_in_idx].input_weight *
node->inputs[fan_in_idx].input_node->out);
}
(*output) = Neuron::Sigmoid(activation);
return true;
}
// Performs a feedforward for general nets. Used mainly in training mode
// Templatized for float and double Types
template <typename Type> bool NeuralNet::GetNetOutput(const Type *inputs,
int output_id,
Type *output) {
// validate output id
if (output_id < 0 || output_id >= out_cnt_) {
return false;
}
// call the fast version in case of readonly nets
if (read_only_) {
return FastGetNetOutput(inputs, output_id, output);
}
// For the slow version, we'll just call FeedForward and return the
// appropriate output
vector<Type> outputs(out_cnt_);
if (!FeedForward(inputs, &outputs[0])) {
return false;
}
(*output) = outputs[output_id];
return true;
}
// Instantiate all supported templates now that the functions have been defined.
template bool NeuralNet::FeedForward(const float *inputs, float *outputs);
template bool NeuralNet::FeedForward(const double *inputs, double *outputs);
template bool NeuralNet::FastFeedForward(const float *inputs, float *outputs);
template bool NeuralNet::FastFeedForward(const double *inputs,
double *outputs);
template bool NeuralNet::GetNetOutput(const float *inputs, int output_id,
float *output);
template bool NeuralNet::GetNetOutput(const double *inputs, int output_id,
double *output);
template bool NeuralNet::FastGetNetOutput(const float *inputs, int output_id,
float *output);
template bool NeuralNet::FastGetNetOutput(const double *inputs, int output_id,
double *output);
template bool NeuralNet::ReadBinary(InputFileBuffer *input_buffer);
}
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// neural_net.h: Declarations of a class for an object that
// represents an arbitrary network of neurons
//
#ifndef NEURAL_NET_H
#define NEURAL_NET_H
#include <string>
#include <vector>
#include "neuron.h"
#include "input_file_buffer.h"
namespace tesseract {
// Minimum input range below which we set the input weight to zero
static const float kMinInputRange = 1e-6f;
class NeuralNet {
public:
NeuralNet();
virtual ~NeuralNet();
// create a net object from a file. Uses stdio
static NeuralNet *FromFile(const string file_name);
// create a net object from an input buffer
static NeuralNet *FromInputBuffer(InputFileBuffer *ib);
// Different flavors of feed forward function
template <typename Type> bool FeedForward(const Type *inputs,
Type *outputs);
// Compute the output of a specific output node.
// This function is useful for application that are interested in a single
// output of the net and do not want to waste time on the rest
template <typename Type> bool GetNetOutput(const Type *inputs,
int output_id,
Type *output);
// Accessor functions
int in_cnt() const { return in_cnt_; }
int out_cnt() const { return out_cnt_; }
protected:
struct Node;
// A node-weight pair
struct WeightedNode {
Node *input_node;
float input_weight;
};
// node struct used for fast feedforward in
// Read only nets
struct Node {
float out;
float bias;
int fan_in_cnt;
WeightedNode *inputs;
};
// Read-Only flag (no training: On by default)
// will presumeably be set to false by
// the inherting TrainableNeuralNet class
bool read_only_;
// input count
int in_cnt_;
// output count
int out_cnt_;
// Total neuron count (including inputs)
int neuron_cnt_;
// count of unique weights
int wts_cnt_;
// Neuron vector
Neuron *neurons_;
// size of allocated weight chunk (in weights)
// This is basically the size of the biggest network
// that I have trained. However, the class will allow
// a bigger sized net if desired
static const int kWgtChunkSize = 0x10000;
// Magic number expected at the beginning of the NN
// binary file
static const unsigned int kNetSignature = 0xFEFEABD0;
// count of allocated wgts in the last chunk
int alloc_wgt_cnt_;
// vector of weights buffers
vector<vector<float> *>wts_vec_;
// Is the net an auto-encoder type
bool auto_encoder_;
// vector of input max values
vector<float> inputs_max_;
// vector of input min values
vector<float> inputs_min_;
// vector of input mean values
vector<float> inputs_mean_;
// vector of input standard deviation values
vector<float> inputs_std_dev_;
// vector of input offsets used by fast read-only
// feedforward function
vector<Node> fast_nodes_;
// Network Initialization function
void Init();
// Clears all neurons
void Clear() {
for (int node = 0; node < neuron_cnt_; node++) {
neurons_[node].Clear();
}
}
// Reads the net from an input buffer
template<class ReadBuffType> bool ReadBinary(ReadBuffType *input_buff) {
// Init vars
Init();
// is this an autoencoder
unsigned int read_val;
unsigned int auto_encode;
// read and verify signature
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
if (read_val != kNetSignature) {
return false;
}
if (input_buff->Read(&auto_encode, sizeof(auto_encode)) !=
sizeof(auto_encode)) {
return false;
}
auto_encoder_ = auto_encode;
// read and validate total # of nodes
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
neuron_cnt_ = read_val;
if (neuron_cnt_ <= 0) {
return false;
}
// set the size of the neurons vector
neurons_ = new Neuron[neuron_cnt_];
if (neurons_ == NULL) {
return false;
}
// read & validate inputs
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
in_cnt_ = read_val;
if (in_cnt_ <= 0) {
return false;
}
// read outputs
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
out_cnt_ = read_val;
if (out_cnt_ <= 0) {
return false;
}
// set neuron ids and types
for (int idx = 0; idx < neuron_cnt_; idx++) {
neurons_[idx].set_id(idx);
// input type
if (idx < in_cnt_) {
neurons_[idx].set_node_type(Neuron::Input);
} else if (idx >= (neuron_cnt_ - out_cnt_)) {
neurons_[idx].set_node_type(Neuron::Output);
} else {
neurons_[idx].set_node_type(Neuron::Hidden);
}
}
// read the connections
for (int node_idx = 0; node_idx < neuron_cnt_; node_idx++) {
// read fanout
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
// read the neuron's info
int fan_out_cnt = read_val;
for (int fan_out_idx = 0; fan_out_idx < fan_out_cnt; fan_out_idx++) {
// read the neuron id
if (input_buff->Read(&read_val, sizeof(read_val)) != sizeof(read_val)) {
return false;
}
// create the connection
if (!SetConnection(node_idx, read_val)) {
return false;
}
}
}
// read all the neurons' fan-in connections
for (int node_idx = 0; node_idx < neuron_cnt_; node_idx++) {
// read
if (!neurons_[node_idx].ReadBinary(input_buff)) {
return false;
}
}
// size input stats vector to expected input size
inputs_mean_.resize(in_cnt_);
inputs_std_dev_.resize(in_cnt_);
inputs_min_.resize(in_cnt_);
inputs_max_.resize(in_cnt_);
// read stats
if (input_buff->Read(&(inputs_mean_.front()),
sizeof(inputs_mean_[0]) * in_cnt_) !=
sizeof(inputs_mean_[0]) * in_cnt_) {
return false;
}
if (input_buff->Read(&(inputs_std_dev_.front()),
sizeof(inputs_std_dev_[0]) * in_cnt_) !=
sizeof(inputs_std_dev_[0]) * in_cnt_) {
return false;
}
if (input_buff->Read(&(inputs_min_.front()),
sizeof(inputs_min_[0]) * in_cnt_) !=
sizeof(inputs_min_[0]) * in_cnt_) {
return false;
}
if (input_buff->Read(&(inputs_max_.front()),
sizeof(inputs_max_[0]) * in_cnt_) !=
sizeof(inputs_max_[0]) * in_cnt_) {
return false;
}
// create a readonly version for fast feedforward
if (read_only_) {
return CreateFastNet();
}
return true;
}
// creates a connection between two nodes
bool SetConnection(int from, int to);
// Create a read only version of the net that
// has faster feedforward performance
bool CreateFastNet();
// internal function to allocate a new set of weights
// Centralized weight allocation attempts to increase
// weights locality of reference making it more cache friendly
float *AllocWgt(int wgt_cnt);
// different flavors read-only feedforward function
template <typename Type> bool FastFeedForward(const Type *inputs,
Type *outputs);
// Compute the output of a specific output node.
// This function is useful for application that are interested in a single
// output of the net and do not want to waste time on the rest
// This is the fast-read-only version of this function
template <typename Type> bool FastGetNetOutput(const Type *inputs,
int output_id,
Type *output);
};
}
#endif // NEURAL_NET_H__
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// input_file_buffer.h: Declarations of a class for an object that
// represents an input file buffer.
#include <string>
#include "input_file_buffer.h"
namespace tesseract {
// default and only contsructor
InputFileBuffer::InputFileBuffer(const string &file_name)
: file_name_(file_name) {
fp_ = NULL;
}
// virtual destructor
InputFileBuffer::~InputFileBuffer() {
if (fp_ != NULL) {
fclose(fp_);
}
}
// Read the specified number of bytes to the specified input buffer
int InputFileBuffer::Read(void *buffer, int bytes_to_read) {
// open the file if necessary
if (fp_ == NULL) {
fp_ = fopen(file_name_.c_str(), "rb");
if (fp_ == NULL) {
return 0;
}
}
return fread(buffer, 1, bytes_to_read, fp_);
}
}
| C++ |
// Copyright 2008 Google Inc.
// All Rights Reserved.
// Author: ahmadab@google.com (Ahmad Abdulkader)
//
// input_file_buffer.h: Declarations of a class for an object that
// represents an input file buffer.
//
#ifndef INPUT_FILE_BUFFER_H
#define INPUT_FILE_BUFFER_H
#include <stdio.h>
#include <string>
#ifdef USE_STD_NAMESPACE
using std::string;
#endif
namespace tesseract {
class InputFileBuffer {
public:
explicit InputFileBuffer(const string &file_name);
virtual ~InputFileBuffer();
int Read(void *buffer, int bytes_to_read);
protected:
string file_name_;
FILE *fp_;
};
}
#endif // INPUT_FILE_BUFFER_H__
| C++ |
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