plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | jacksky64/imageProcessing-master | viewer3d_contrast.m | .m | imageProcessing-master/Matlab Viewer3D/SubFunctions/viewer3d_contrast.m | 8,521 | utf_8 | 23f75c7fe9be514aa92a196006737ece | function varargout = viewer3d_contrast(varargin)
% VIEWER3D_CONTRAST M-file for viewer3d_contrast.fig
% VIEWER3D_CONTRAST, by itself, creates a new VIEWER3D_CONTRAST or raises the existing
% singleton*.
%
% H = VIEWER3D_CONTRAST returns the handle to a new VIEWER3D_CONTRAST or the handle to
% the ex... |
github | jacksky64/imageProcessing-master | structfind.m | .m | imageProcessing-master/Matlab Viewer3D/SubFunctions/structfind.m | 3,025 | utf_8 | 2f5a54606251beb957c2f30704c5435d | function index=structfind(a,field,value)
% StructFind, Find the index of a certain string or value in a struct
%
% index=structfind(a,field,value)
%
% inputs,
% a : A Matlab struct, for example a(1).name='red', a(2).name='blue';
% field : The name of the field which is searched, for example 'n... |
github | jacksky64/imageProcessing-master | SnakeInternalForceMatrix3D.m | .m | imageProcessing-master/Matlab Viewer3D/SubFunctions/BasicSnake_version2d/SnakeInternalForceMatrix3D.m | 1,430 | utf_8 | 4d138c391cf1d34306cc2c49246b80c1 | function B=SnakeInternalForceMatrix3D(FV,alpha,beta,gamma)
%
% B=SnakeInternalForceMatrix3D(F,alpha,beta,gamma)
%
% inputs,
% FV : Struct (Patch) with the triangulated surface
% alpha : membrame energy (first order)
% beta : thin plate energy (second order)
% gamma : Step Size (Time)
%
% outputs,
% ... |
github | jacksky64/imageProcessing-master | MakeContourClockwise3D.m | .m | imageProcessing-master/Matlab Viewer3D/SubFunctions/BasicSnake_version2d/MakeContourClockwise3D.m | 1,065 | utf_8 | 967b2d3c686076cf81947641372d0de8 | function FV=MakeContourClockwise3D(FV)
% This function MakeContourClockwise will make a surface clockwise
% contour clockwise. This is done by calculating the volume inside the
% surface, if it is negative we change the surface orientation.
%
% FV=MakeContourClockwise2D(FV);
%
% input/output,
% FV : Tria... |
github | jacksky64/imageProcessing-master | SeparateKernel.m | .m | imageProcessing-master/Matlab Viewer3D/SubFunctions/BasicSnake_version2d/SeparateKernel.m | 8,608 | utf_8 | 460ab595164db33cf427c62f3a4f0e3b | function [K1 KN ERR]=SeparateKernel(H)
% This function SEPARATEKERNEL will separate ( do decomposition ) any
% 2D, 3D or nD kernel into 1D kernels. Ofcourse only a sub-set of Kernels
% are separable such as a Gaussian Kernel, but it will give least-squares
% sollutions for non-separatable kernels.
%
% Separatin... |
github | jacksky64/imageProcessing-master | savepgm.m | .m | imageProcessing-master/cameraCalibration/savepgm.m | 447 | utf_8 | b8fe9ed33cbd68ea4b83271b431e3667 | %SAVEPGM Write a PGM format file
%
% SAVEPGM(filename, im)
%
% Saves the specified image array in a binary (P5) format PGM image file.
%
% SEE ALSO: loadpgm
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1994
function savepgm(fname, im)
fid = fopen(fname, 'w');
[r,c] = size(... |
github | jacksky64/imageProcessing-master | ginput4.m | .m | imageProcessing-master/cameraCalibration/ginput4.m | 7,121 | utf_8 | 1d7231b0daed3533514a77f79f4e096a | function [out1,out2,out3] = ginput4(arg1)
[out1,out2,out3] = ginput(arg1);
return;
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Ar... |
github | jacksky64/imageProcessing-master | loadinr.m | .m | imageProcessing-master/cameraCalibration/loadinr.m | 1,029 | utf_8 | ac39329cc5acba186f4c5ef4c62f3a33 | %LOADINR Load an INRIMAGE format file
%
% LOADINR(filename, im)
%
% Load an INRIA image format file and return it as a matrix
%
% SEE ALSO: saveinr
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1996
function im = loadinr(fname, im)
fid = fopen(fname, 'r');
s = fgets(fid);
... |
github | jacksky64/imageProcessing-master | saveppm.m | .m | imageProcessing-master/cameraCalibration/saveppm.m | 722 | utf_8 | 9904ad3d075a120ca32bd9c10e019512 | %SAVEPPM Write a PPM format file
%
% SAVEPPM(filename, I)
%
% Saves the specified red, green and blue planes in a binary (P6)
% format PPM image file.
%
% SEE ALSO: loadppm
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1994
function saveppm(fname, I)
I = double(I);
if size(I,... |
github | jacksky64/imageProcessing-master | ginput3.m | .m | imageProcessing-master/cameraCalibration/ginput3.m | 6,344 | utf_8 | 1cc27af57f9872f05bbf0d9b8a0fdbc9 | function [out1,out2,out3] = ginput2(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Arrow Keys on some
% systems). Data points a... |
github | jacksky64/imageProcessing-master | ginput2.m | .m | imageProcessing-master/cameraCalibration/ginput2.m | 6,105 | utf_8 | 983a72db9a079ba54ab084149ced6ae9 | function [out1,out2,out3] = ginput2(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Arrow Keys on some
% systems). Data points a... |
github | jacksky64/imageProcessing-master | loadppm.m | .m | imageProcessing-master/cameraCalibration/loadppm.m | 2,355 | utf_8 | c8d750733c522f56f3aa17a4ca9f9df1 | %LOADPPM Load a PPM image
%
% I = loadppm(filename)
%
% Returns a matrix containing the image loaded from the PPM format
% file filename. Handles ASCII (P3) and binary (P6) PPM file formats.
%
% If the filename has no extension, and open fails, a '.ppm' and
% '.pnm' extension will be tried.
%
% SEE ALSO: saveppm loadp... |
github | jacksky64/imageProcessing-master | saveinr.m | .m | imageProcessing-master/cameraCalibration/saveinr.m | 949 | utf_8 | a18df4fba021be006842fbc35166bc23 | %SAVEINR Write an INRIMAGE format file
%
% SAVEINR(filename, im)
%
% Saves the specified image array in a INRIA image format file.
%
% SEE ALSO: loadinr
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% Peter Corke 1996
function saveinr(fname, im)
fid = fopen(fname, 'w');
[r,c] = size(im');
... |
github | jacksky64/imageProcessing-master | stereo_gui.m | .m | imageProcessing-master/cameraCalibration/stereo_gui.m | 6,208 | utf_8 | 6cc48675fdf9c8c36bc147da7d046d06 | % stereo_gui
% Stereo Camera Calibration Toolbox (two cameras, internal and external calibration):
%
% It is assumed that the two cameras (left and right) have been calibrated with the pattern at the same 3D locations, and the same points
% on the pattern (select the same grid points). Therefore, in particular, the sam... |
github | jacksky64/imageProcessing-master | loadpgm.m | .m | imageProcessing-master/cameraCalibration/loadpgm.m | 1,838 | utf_8 | 6ec18330c2633d5519c72eb2e6fe963b | %LOADPGM Load a PGM image
%
% I = loadpgm(filename)
%
% Returns a matrix containing the image loaded from the PGM format
% file filename. Handles ASCII (P2) and binary (P5) PGM file formats.
%
% If the filename has no extension, and open fails, a '.pgm' will
% be appended.
%
%
% Copyright (c) Peter Corke, 1999 Machin... |
github | jacksky64/imageProcessing-master | pcamat.m | .m | imageProcessing-master/FastICA_2.5/pcamat.m | 12,075 | utf_8 | bcb1117d4132558d0d54d8b7b616a902 | function [E, D] = pcamat(vectors, firstEig, lastEig, s_interactive, ...
s_verbose);
%PCAMAT - Calculates the pca for data
%
% [E, D] = pcamat(vectors, firstEig, lastEig, ...
% interactive, verbose);
%
% Calculates the PCA matrices for given data (row) vectors. Returns
% the eigenvector (E) and diag... |
github | jacksky64/imageProcessing-master | icaplot.m | .m | imageProcessing-master/FastICA_2.5/icaplot.m | 13,259 | utf_8 | dde3e6d852f657a3c1eaacbd03f5dcc7 | function icaplot(mode, varargin);
%ICAPLOT - plot signals in various ways
%
% ICAPLOT is mainly for plottinf and comparing the mixed signals and
% separated ica-signals.
%
% ICAPLOT has many different modes. The first parameter of the function
% defines the mode. Other parameters and their order depends on the
% mode. ... |
github | jacksky64/imageProcessing-master | PhaseResidues_r1.m | .m | imageProcessing-master/PhaseUnwrap2DGoldsteinAlgorithm/PhaseResidues_r1.m | 2,399 | utf_8 | eb7ce76ac23d23d3a221874a6e9e7305 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% PhaseResidues.m calculates the phase residues for a given wrapped phase
% image. Note that by convention the positions of the phase residues are
% marked on the top left corner of the 2 by 2 regions.
%
% active---res4---right
% ... |
github | jacksky64/imageProcessing-master | BranchCuts_r1.m | .m | imageProcessing-master/PhaseUnwrap2DGoldsteinAlgorithm/BranchCuts_r1.m | 11,409 | utf_8 | 3bf75332b143ddd255309404c5a6678e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% BranchCuts.m generates branch cuts based on the phase residues. This is
% done using the Goldstein method, as described in "Two-dimensional phase
% unwrapping: theory, algorithms and software" by Dennis Ghiglia and
% Mark Pritt.
% "residue_... |
github | jacksky64/imageProcessing-master | phasesym.m | .m | imageProcessing-master/GaborImageFeatures/phasesym.m | 22,009 | utf_8 | c73a0499c75e8bb7cf10646e82e2a928 | % PHASESYM - Function for computing gabor features of a gray-scale image
%
% This function calculates gabor features. Mean-squared energy & meanAmplitude
% for each scale % and orientation is returned.
%
% There are potentially many arguments, here is the full usage:
%
% [gaborSquareEnergy, gaborMeanAmplitude] = ...... |
github | jacksky64/imageProcessing-master | phasecong2.m | .m | imageProcessing-master/GaborImageFeatures/phasecong2.m | 23,023 | utf_8 | 62cee80b9df326d89f0ffb2008658303 | % PHASECONG2 - Computes edge and corner phase congruency in an image.
%
% This function calculates the PC_2 measure of phase congruency.
% This function supersedes PHASECONG
%
% There are potentially many arguments, here is the full usage:
%
% [M m or ft pc EO] = phasecong2(im, nscale, norient, minWaveLength... |
github | jacksky64/imageProcessing-master | noisecomp.m | .m | imageProcessing-master/GaborImageFeatures/noisecomp.m | 7,750 | utf_8 | 9676f0608db5db81178e20d70f317783 | % NOISECOMP - Function for denoising an image
%
% function cleanimage = noisecomp(image, k, nscale, mult, norient, softness)
%
% Parameters:
% k - No of standard deviations of noise to reject 2-3
% nscale - No of filter scales to use (5-7) - the more scales used
% the mor... |
github | jacksky64/imageProcessing-master | loggabor.m | .m | imageProcessing-master/GaborImageFeatures/loggabor.m | 1,707 | utf_8 | c15d2b1f67996d38d0003a5309d2f76f | % LOGGABOR
%
% Plots 1D log-Gabor functions
%
% Author: Peter Kovesi
% School of Computer Science & Software Engineering
% The University of Western Australia
% pk @ csse uwa edu au http://www.csse.uwa.edu.au/~pk
function loggabor(nscale, wmin, mult, konwo)
Npts = 2048;
Nwaves = 1;
wma... |
github | jacksky64/imageProcessing-master | lowpassfilter.m | .m | imageProcessing-master/GaborImageFeatures/lowpassfilter.m | 2,446 | utf_8 | d8cb687e785e698617852ce86f35a064 | % LOWPASSFILTER - Constructs a low-pass butterworth filter.
%
% usage: f = lowpassfilter(sze, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5
% n is the order of the f... |
github | jacksky64/imageProcessing-master | odot.m | .m | imageProcessing-master/GaborImageFeatures/odot.m | 3,720 | utf_8 | 336255093ed76b067368d764f3d823d5 | % ODOT - Demonstrates odot and oslash operators on 1D signal
%
% Usage: [smooth, energy] = odot(f, K)
%
% Arguments: f - a 1D signal
% K - optional 'Weiner' type factor to condition the results
% where division by 0 occurs in the 'oslash' operation.
% K defaults to ... |
github | jacksky64/imageProcessing-master | dispfeat.m | .m | imageProcessing-master/GaborImageFeatures/dispfeat.m | 5,648 | utf_8 | b84431635f0865ba6f5383b095221c41 | % DISPFEAT - Displays feature types as detected by PHASECONG.
%
% This function provides a visualisation of the feature types as detected
% by PHASECONG.
%
% Usage: im = dispfeat(ft, edgeim, 'l')
%
% Arguments: ft - A complex valued image giving the weighted mean
% phase angle at every point... |
github | jacksky64/imageProcessing-master | gaborconvolve.m | .m | imageProcessing-master/GaborImageFeatures/gaborconvolve.m | 7,461 | utf_8 | e5eafdc94ab27e11c00dc229fa39b9fb | % GABORCONVOLVE - function for convolving image with log-Gabor filters
%
% Usage: EO = gaborconvolve(im, nscale, norient, minWaveLength, mult, ...
% sigmaOnf, dThetaOnSigma, feedback)
%
% Arguments:
% The convolutions are done via the FFT. Many of the parameters relate
% to the specification of the filters in ... |
github | jacksky64/imageProcessing-master | monofilt.m | .m | imageProcessing-master/GaborImageFeatures/monofilt.m | 6,435 | utf_8 | adac38e6a3a0ad2423e6f10b769dc1fd | % MONOFILT - Apply monogenic filters to an image to obtain 2D analytic signal
%
% Implementation of Felsberg's monogenic filters
%
% Usage: [f, h1f, h2f, A, theta, psi] = ...
% monofilt(im, nscale, minWaveLength, mult, sigmaOnf, orientWrap)
% 3 4 2 0.65 ... |
github | jacksky64/imageProcessing-master | plotgaborfilters.m | .m | imageProcessing-master/GaborImageFeatures/plotgaborfilters.m | 8,558 | utf_8 | 88279510c3ad351b70b45076aa576792 | % PLOTGABORFILTERS - Plots log-Gabor filters
%
% The purpose of this code is to see what effect the various parameter
% settings have on the formation of a log-Gabor filter bank.
%
% Usage: [Ffilter, Efilter, Ofilter] = plotgaborfilters(sze, nscale, norient,...
% minWaveLength, mu... |
github | jacksky64/imageProcessing-master | spatialgabor.m | .m | imageProcessing-master/GaborImageFeatures/spatialgabor.m | 2,644 | utf_8 | 0d56aa13789e5563961e97238d519790 | % SPATIALGABOR - applies single oriented gabor filter to an image
%
% Usage:
% [Eim, Oim, Aim] = spatialgabor(im, wavelength, angle, kx, ky, showfilter)
%
% Arguments:
% im - Image to be processed.
% wavelength - Wavelength in pixels of Gabor filter to construct
% angle - Angle of... |
github | jacksky64/imageProcessing-master | phasecong.m | .m | imageProcessing-master/GaborImageFeatures/phasecong.m | 16,644 | utf_8 | 693c5ec683ef5ce8c816379185261bf7 | % PHASECONG - Computes phase congruency on an image.
%
% Usage: [pc or ft] = phasecong(im)
%
% This function calculates the PC_2 measure of phase congruency.
% For maximum speed the input image should be square and have a
% size that is a power of 2, but the code will operate on images
% of arbitrary size.
%
%
% R... |
github | jacksky64/imageProcessing-master | xraymu.m | .m | imageProcessing-master/xraymu/xraymu.m | 4,840 | utf_8 | 4443d46a51b213105453a1a0c4ea46f5 | function [mus,xray_energies,ztable] = xraymu(chem_spec,egys,varargin)
% function [mus,xray_energies,ztable] = xraymu(chem_spec,egys,varargin)
% X-ray attenuation coefficients for a specified compound from tabulated data
% returns NaN's for energies beyond tabulated data range
% inputs:
% chem_spec: (case-sen... |
github | jacksky64/imageProcessing-master | mergeimports.m | .m | imageProcessing-master/yamlmatlab/+yaml/mergeimports.m | 2,907 | utf_8 | 62fc3b86ba001de3e7986f200b433f7d | function result = mergeimports(data, verb)
import yaml.*;
if ~exist('verb','var')
verb = 0;
end;
result = recurse(data, 0, [], verb);
end
function result = recurse(data, level, addit, verb)
import yaml.*;
indent = repmat(' | ',1,level); % for debugging
if iscell(data)
result = iter_ce... |
github | jacksky64/imageProcessing-master | DateTime.m | .m | imageProcessing-master/yamlmatlab/+yaml/DateTime.m | 7,819 | utf_8 | 1d32e576b384f88172041b154f0c60f4 | classdef DateTime
Copyright (c) 2011
This program is a result of a joined cooperation of Energocentrum
PLUS, s.r.o. and Czech Technical University (CTU) in Prague.
The program is maintained by Energocentrum PLUS, s.r.o. and
licensed under the terms of MIT license. Full text of the license
... |
github | jacksky64/imageProcessing-master | ReadYamlRaw.m | .m | imageProcessing-master/yamlmatlab/+yaml/ReadYamlRaw.m | 4,999 | utf_8 | 348b70ee95f28e77a5059ca9b30517cd | function result = ReadYamlRaw(filename, verbose, nosuchfileaction, treatasdata)
import yaml.*;
if ~exist('verbose','var')
verbose = 0;
end;
if ~exist('nosuchfileaction','var')
nosuchfileaction = 0;
end;
if ~ismember(nosuchfileaction,[0,1])
error('nosuchfileexception parame... |
github | jacksky64/imageProcessing-master | makematrices.m | .m | imageProcessing-master/yamlmatlab/+yaml/makematrices.m | 2,998 | utf_8 | b6ccf836e3e3a122d7868b15a1151df9 | function result = makematrices(r, makeords)
import yaml.*;
result = recurse(r, 0, [], makeords);
end
function result = recurse(data, level, addit, makeords)
import yaml.*;
if iscell(data)
result = iter_cell(data, level, addit, makeords);
elseif isstruct(data)
result = iter_struct(data, level, a... |
github | jacksky64/imageProcessing-master | deflateimports.m | .m | imageProcessing-master/yamlmatlab/+yaml/deflateimports.m | 1,597 | utf_8 | 9b2a562969b1be978543af1bbc9340c7 | function result = deflateimports(r)
import yaml.*;
result = recurse(r, 0, []);
end
function result = recurse(data, level, addit)
import yaml.*;
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, addit);
elseif isstruct(data)
result = iter_struct(data, level, addit);
else
... |
github | jacksky64/imageProcessing-master | dosubstitution.m | .m | imageProcessing-master/yamlmatlab/+yaml/dosubstitution.m | 963 | utf_8 | feed736691fdf3f1b56ad4f33f9b89f4 | function result = dosubstitution(r, dictionary)
import yaml.*;
if ~exist('dictionary','var')
dictionary = {};
end;
result = recurse(r, 0, dictionary);
end
function result = recurse(data, level, dictionary)
import yaml.*;
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, ... |
github | jacksky64/imageProcessing-master | datadump.m | .m | imageProcessing-master/yamlmatlab/+yaml/datadump.m | 1,104 | utf_8 | 38ebb873fefdc3b54d2b504c19a31a50 | function datadump(data)
import yaml.*;
recurse(data, 0, []);
end
function result = recurse(data, level, addit)
import yaml.*;
indent = repmat(' | ',1,level);
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, addit);
elseif isstruct(data)
result = iter_struct(data, level,... |
github | jacksky64/imageProcessing-master | doinheritance.m | .m | imageProcessing-master/yamlmatlab/+yaml/doinheritance.m | 2,631 | utf_8 | cc275395af98bd16ac7c446484686b8d | function result = doinheritance(r, tr)
import yaml.*;
if ~exist('tr','var')
tr = r;
end;
result = recurse(r, 0, {tr});
end
function result = recurse(data, level, addit)
import yaml.*;
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, addit);
elseif isstruct(data)
... |
github | jacksky64/imageProcessing-master | WriteYaml.m | .m | imageProcessing-master/yamlmatlab/+yaml/WriteYaml.m | 5,246 | utf_8 | a8261807d51be1f0a8dc7a11661d379b | function result = WriteYaml(filename, data, flowstyle)
import yaml.*;
if ~exist('flowstyle','var')
flowstyle = 0;
end;
if ~ismember(flowstyle, [0,1])
error('Flowstyle must be 0,1 or empty.');
end;
result = [];
[pth,~,~] = fileparts(mfilename('fullpath'));
try
imp... |
github | jacksky64/imageProcessing-master | selftest_yamlmatlab.m | .m | imageProcessing-master/yamlmatlab/+yaml/Tests/selftest_yamlmatlab.m | 2,954 | utf_8 | 4b0ea27db95878c651e0c46855f39e18 | function selftest_yamlmatlab(varargin)
% This function tests consistency of YAMLMatlab, by default, the results
% are stored in selftest_report.html in current work folder.
% Example
% >> selftest_yamlmatlab()
% >> selftest_yamlmatlab(outFileName)
%
% %=================================================================... |
github | jacksky64/imageProcessing-master | test_ReadYaml.m | .m | imageProcessing-master/yamlmatlab/+yaml/Tests/test_ReadYaml.m | 8,883 | utf_8 | 1647e455763d95a6c10948a007741f02 | function stat = test_ReadYaml()
% this function tests reading in the yaml file
stat.ok = 1;
stat.desc = '';
try
%stat.test_ReadYaml_SimpleStructure = test_ReadYaml_SimpleStructure();
%stat.test_ReadYaml_DateTime = test_ReadYaml_DateTime();
fprintf('Testing read ');
stat.test_RY_Matrices = test_RY_... |
github | jacksky64/imageProcessing-master | test_WriteYaml.m | .m | imageProcessing-master/yamlmatlab/+yaml/Tests/test_WriteYaml.m | 1,745 | utf_8 | de37cbde8a33d40a7b1f05ef8e7f16cf | function stat = test_WriteYaml()
stat.ok = 1;
stat.desc = '';
try
fprintf('Testing write ');
stat.test_WY_Matrices = test_WY_Universal(PTH_PRIMITIVES(), 'matrices');
fprintf('.');
stat.test_WY_FloatingPoints = test_WY_Universal(PTH_PRIMITIVES(), 'floating_points');
fprintf('.');
stat.test_WY_In... |
github | jacksky64/imageProcessing-master | dirPlus.m | .m | imageProcessing-master/dirPlus/dirPlus.m | 11,958 | utf_8 | 457bfd9e6ab55181cc8c367f5e9f417a | function output = dirPlus(rootPath, varargin)
%dirPlus Recursively collect files or directories within a folder.
% LIST = dirPlus(ROOTPATH) will search recursively through the folder
% tree beneath ROOTPATH and collect a cell array LIST of all files it
% finds. The list will contain the absolute paths to each f... |
github | jacksky64/imageProcessing-master | main_FiltImage.m | .m | imageProcessing-master/poissonEditing/src/main_FiltImage.m | 10,390 | utf_8 | a37410e03ca5b2e0d87897afdf432515 | % ============================================================ %
% Poisson image editing
% ------------------------------------------------------------ %
% FiltImage(Im, Solver, Mode, OutIm, AdditionalParameters)
% inputs:
% - Im > input image e.g 'dog.png'
% - Solver> String containing 'I' or 'II',
% ... |
github | jacksky64/imageProcessing-master | main_SeamlessCloning.m | .m | imageProcessing-master/poissonEditing/src/main_SeamlessCloning.m | 8,789 | utf_8 | b7b37149c2e289f5676d40cd3622d481 | % ============================================================ %
% Poisson image editing
% ------------------------------------------------------------ %
% main_SeamlessCloning(BackIm, ObjIm, Omega, x0, y0, Solv, Mode, OutIm)
% inputs:
% - BackgroundIm > background image filename, e.g. 'Sunset.png'
% - ObjIm > Obj... |
github | jacksky64/imageProcessing-master | CombineGradients.m | .m | imageProcessing-master/poissonEditing/src/lib/CombineGradients.m | 3,194 | utf_8 | 01cf9c44ea8f850e41ba65e78beba866 |
% ======================================================= %
% G = CombineGradients(G_Background, G_Object, Omega, Mode)
% ======================================================= %
function G = CombineGradients(G_Ba, G_Ob, Omega, Mode)
% Input,
% - G_Ba: Struct that contains, G.x and G.y (HxWxC) images that
% ... |
github | jacksky64/imageProcessing-master | SolvePoissonEq_II.m | .m | imageProcessing-master/poissonEditing/src/lib/SolvePoissonEq_II.m | 6,186 | utf_8 | 001ac8fb1fc43c7002d3d84f2804a1af | % ======================================================= %
% I = SolvePoissonEq_II(G) %
% ======================================================= %
function I = SolvePoissonEq_II(gx,gy,Omega,F)
% ------------------------------------------------------- %
% Problem: Find the function I ... |
github | jacksky64/imageProcessing-master | ComputeGradient.m | .m | imageProcessing-master/poissonEditing/src/lib/ComputeGradient.m | 3,444 | utf_8 | bd1d03aeb86f6542fd37171344e32bd4 | % ======================================================= %
% GradF = ComputeGradient(F,Method) %
% ======================================================= %
function GradF = ComputeGradient(F,Method)
% Input,
% - F: (HxWxC) image (C=1 gray, C=3 color image)
% - Method: [def = 'Fourier'] {'For... |
github | jacksky64/imageProcessing-master | SolvePoissonEq_I.m | .m | imageProcessing-master/poissonEditing/src/lib/SolvePoissonEq_I.m | 3,235 | utf_8 | 393a84c514368a5031b9f92cb1ff7c91 | % ======================================================= %
% I = SolvePoissonEq_I(Gx,Gy) %
% ======================================================= %
function I = SolvePoissonEq_I(gx,gy)
% ------------------------------------------------------------ %
% Problem: Find the function I that sa... |
github | jacksky64/imageProcessing-master | findiff3.m | .m | imageProcessing-master/vecdenoise3d/findiff3.m | 903 | utf_8 | 199829b233fd9bfe30c4758b69510536 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | shiftmirror.m | .m | imageProcessing-master/vecdenoise3d/shiftmirror.m | 1,373 | utf_8 | 5d1e42fa481a63116aef98eaebfc8186 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | fmin1.m | .m | imageProcessing-master/vecdenoise3d/fmin1.m | 3,387 | utf_8 | 8912e0b35f55070abdf22e2bf29ca655 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | AFproduct.m | .m | imageProcessing-master/vecdenoise3d/AFproduct.m | 1,984 | utf_8 | 7400183a2fe4cc1d57bb9313a8c3bc85 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | sigmaNest.m | .m | imageProcessing-master/vecdenoise3d/sigmaNest.m | 1,286 | utf_8 | 77c3a80a332f8702b81f57ed9a0fa7ac | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | MSEest_GCV.m | .m | imageProcessing-master/vecdenoise3d/MSEest_GCV.m | 1,246 | utf_8 | a90a0b21a5ef4a9dbc5f20b0ce08ba6d | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | MSEest_SURE.m | .m | imageProcessing-master/vecdenoise3d/MSEest_SURE.m | 1,279 | utf_8 | 5754188fbd396ed8025272bd4994a942 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | MSEest.m | .m | imageProcessing-master/vecdenoise3d/MSEest.m | 2,285 | utf_8 | 614ddcbf1e795cc78a677330fb08f62a | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | vecdenoise3.m | .m | imageProcessing-master/vecdenoise3d/vecdenoise3.m | 3,724 | utf_8 | 00fa793db67147d4a79bac1ea3791701 | % Vector Field Denoising with DIV-CURL Regularization
%
% Author: Pouya Dehghani Tafti <pouya.tafti@a3.epfl.ch>
% Biomedical Imaging Group, EPFL, Lausanne
% http://bigwww.epfl.ch/
%
% Dates: 08 Feb. 2012 (current release)
% ?? Feb. 2011 (this implementation)
%
% References:
%
% P. D. Tafti ... |
github | jacksky64/imageProcessing-master | QC_signatures.m | .m | imageProcessing-master/QC/QC_signatures.m | 4,365 | utf_8 | f04870a73e5c0cb3b6f451f4b7fa6998 | % [dist]= QC_signatures(PF, QF, PW, QW, F_sim, m)
%
% Computes the Quadratic-Chi (QC) histogram distance between two
% signatures (a convenient representation for sparse histograms).
% QC distances are Quadratic-Form distances with a cross-bin
% chi-squared-like normalization. This normalization reduces the effect of
... |
github | jacksky64/imageProcessing-master | struct2xml.m | .m | imageProcessing-master/str2xml/struct2xml.m | 7,457 | utf_8 | 24791efbc3f8e2ee07c5fc9e192b90c9 | function varargout = struct2xml( s, varargin )
%Convert a MATLAB structure into a xml file
% [ ] = struct2xml( s, file )
% xml = struct2xml( s )
%
% A structure containing:
% s.XMLname.Attributes.attrib1 = "Some value";
% s.XMLname.Element.Text = "Some text";
% s.XMLname.DifferentElement{1}.Attributes.attrib2 ... |
github | jacksky64/imageProcessing-master | xml2struct.m | .m | imageProcessing-master/str2xml/xml2struct.m | 6,955 | utf_8 | 58f0b998cc71b30b4a6a12b330cfe950 | function [ s ] = xml2struct( file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even more t... |
github | jacksky64/imageProcessing-master | Registration.m | .m | imageProcessing-master/LmRegistration/Registration.m | 22,902 | utf_8 | 3ffdabb779c0cebe002f96fc7d225a22 | function varargout = Registration(varargin)
% REGISTRATION MATLAB code for Registration.fig
% REGISTRATION, by itself, creates a new REGISTRATION or raises the existing
% singleton*.
%
% H = REGISTRATION returns the handle to a new REGISTRATION or the handle to
% the existing singleton*.
%
% RE... |
github | jacksky64/imageProcessing-master | lmRegistration.m | .m | imageProcessing-master/LmRegistration/common/lmRegistration.m | 8,629 | utf_8 | bf6732a28dec675581a967a8422e81d0 |
function [matchinfo, lsmatchinfo] = lmRegistration(sourcepts, targetpts, params)
%
%lmRegistration - Landmark/Fiducial based Registraiton
%
%Input:
% sourcepts: landmarks/fiducials in source image
% targetpts: lamdmarks/fiducials in target image
% params : parameters for registration
%
%O... |
github | jacksky64/imageProcessing-master | imagesAlign.m | .m | imageProcessing-master/piotr/toolbox/videos/imagesAlign.m | 8,167 | utf_8 | d125eb5beb502d940be5bd145521f34b | function [H,Ip] = imagesAlign( I, Iref, varargin )
% Fast and robust estimation of homography relating two images.
%
% The algorithm for image alignment is a simple but effective variant of
% the inverse compositional algorithm. For a thorough overview, see:
% "Lucas-kanade 20 years on A unifying framework,"
% S. B... |
github | jacksky64/imageProcessing-master | opticalFlow.m | .m | imageProcessing-master/piotr/toolbox/videos/opticalFlow.m | 7,361 | utf_8 | b97e8c1f623eca07c6f1a0fff26d171e | function [Vx,Vy,reliab] = opticalFlow( I1, I2, varargin )
% Coarse-to-fine optical flow using Lucas&Kanade or Horn&Schunck.
%
% Implemented 'type' of optical flow estimation:
% LK: http://en.wikipedia.org/wiki/Lucas-Kanade_method
% HS: http://en.wikipedia.org/wiki/Horn-Schunck_method
% SD: Simple block-based sum of ... |
github | jacksky64/imageProcessing-master | seqWriterPlugin.m | .m | imageProcessing-master/piotr/toolbox/videos/seqWriterPlugin.m | 8,280 | utf_8 | 597792f79fff08b8bb709313267c3860 | function varargout = seqWriterPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow writing of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (swp=seqWriterPlugin):
% h=swp('open',h,fName,info) % Open a seq file for writing ... |
github | jacksky64/imageProcessing-master | kernelTracker.m | .m | imageProcessing-master/piotr/toolbox/videos/kernelTracker.m | 9,315 | utf_8 | 4a7d0235f1e518ab5f1c9f1b5450b3f0 | function [allRct, allSim, allIc] = kernelTracker( I, prm )
% Kernel Tracker from Comaniciu, Ramesh and Meer PAMI 2003.
%
% Implements the algorithm described in "Kernel-Based Object Tracking" by
% Dorin Comaniciu, Visvanathan Ramesh and Peter Meer, PAMI 25, 564-577,
% 2003. This is a fast tracking algorithm that utili... |
github | jacksky64/imageProcessing-master | seqIo.m | .m | imageProcessing-master/piotr/toolbox/videos/seqIo.m | 17,019 | utf_8 | 9c631b324bb527372ec3eed3416c5dcc | function out = seqIo( fName, action, varargin )
% Utilities for reading and writing seq files.
%
% A seq file is a series of concatentated image frames with a fixed size
% header. It is essentially the same as merging a directory of images into
% a single file. seq files are convenient for storing videos because: (1)
%... |
github | jacksky64/imageProcessing-master | seqReaderPlugin.m | .m | imageProcessing-master/piotr/toolbox/videos/seqReaderPlugin.m | 9,617 | utf_8 | ad8f912634cafe13df6fc7d67aeff05a | function varargout = seqReaderPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow reading of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (srp=seqReaderPlugin):
% h = srp('open',h,fName) % Open a seq file for reading ... |
github | jacksky64/imageProcessing-master | pcaApply.m | .m | imageProcessing-master/piotr/toolbox/classify/pcaApply.m | 3,320 | utf_8 | a06fc0e54d85930cbc0536c874ac63b7 | function varargout = pcaApply( X, U, mu, k )
% Companion function to pca.
%
% Use pca.m to retrieve the principal components U and the mean mu from a
% set of vectors x, then use pcaApply to get the first k coefficients of
% x in the space spanned by the columns of U. See pca for general usage.
%
% If x is large, pcaAp... |
github | jacksky64/imageProcessing-master | forestTrain.m | .m | imageProcessing-master/piotr/toolbox/classify/forestTrain.m | 6,138 | utf_8 | de534e2a010f452a7b13167dbf9df239 | function forest = forestTrain( data, hs, varargin )
% Train random forest classifier.
%
% Dimensions:
% M - number trees
% F - number features
% N - number input vectors
% H - number classes
%
% USAGE
% forest = forestTrain( data, hs, [varargin] )
%
% INPUTS
% data - [NxF] N length F feature vectors
% hs ... |
github | jacksky64/imageProcessing-master | fernsRegTrain.m | .m | imageProcessing-master/piotr/toolbox/classify/fernsRegTrain.m | 5,914 | utf_8 | b9ed2d87a22cb9cbb1e2632495ddaf1d | function [ferns,ysPr] = fernsRegTrain( data, ys, varargin )
% Train boosted fern regressor.
%
% Boosted regression using random ferns as the weak regressor. See "Greedy
% function approximation: A gradient boosting machine", Friedman, Annals of
% Statistics 2001, for more details on boosted regression.
%
% A few notes ... |
github | jacksky64/imageProcessing-master | rbfDemo.m | .m | imageProcessing-master/piotr/toolbox/classify/rbfDemo.m | 2,929 | utf_8 | 14cc64fb77bcac3edec51cf6b84ab681 | function rbfDemo( dataType, noiseSig, scale, k, cluster, show )
% Demonstration of rbf networks for regression.
%
% See rbfComputeBasis for discussion of rbfs.
%
% USAGE
% rbfDemo( dataType, noiseSig, scale, k, cluster, show )
%
% INPUTS
% dataType - 0: 1D sinusoid
% 1: 2D sinusoid
% 2: ... |
github | jacksky64/imageProcessing-master | pdist2.m | .m | imageProcessing-master/piotr/toolbox/classify/pdist2.m | 5,162 | utf_8 | 768ff9e8818251f756c8325368ee7d90 | function D = pdist2( X, Y, metric )
% Calculates the distance between sets of vectors.
%
% Let X be an m-by-p matrix representing m points in p-dimensional space
% and Y be an n-by-p matrix representing another set of points in the same
% space. This function computes the m-by-n distance matrix D where D(i,j)
% is the ... |
github | jacksky64/imageProcessing-master | pca.m | .m | imageProcessing-master/piotr/toolbox/classify/pca.m | 3,244 | utf_8 | 848f2eb05c18a6e448e9d22af27b9422 | function [U,mu,vars] = pca( X )
% Principal components analysis (alternative to princomp).
%
% A simple linear dimensionality reduction technique. Use to create an
% orthonormal basis for the points in R^d such that the coordinates of a
% vector x in this basis are of decreasing importance. Instead of using all
% d bas... |
github | jacksky64/imageProcessing-master | kmeans2.m | .m | imageProcessing-master/piotr/toolbox/classify/kmeans2.m | 5,251 | utf_8 | f941053f03c3e9eda40389a4cc64ee00 | function [ IDX, C, d ] = kmeans2( X, k, varargin )
% Fast version of kmeans clustering.
%
% Cluster the N x p matrix X into k clusters using the kmeans algorithm. It
% returns the cluster memberships for each data point in the N x 1 vector
% IDX and the K x p matrix of cluster means in C.
%
% This function is in some w... |
github | jacksky64/imageProcessing-master | acfModify.m | .m | imageProcessing-master/piotr/toolbox/detector/acfModify.m | 4,202 | utf_8 | 7a49406d51e7a9431b8fd472be0476e8 | function detector = acfModify( detector, varargin )
% Modify aggregate channel features object detector.
%
% Takes an object detector trained by acfTrain() and modifies it. Only
% certain modifications are allowed to the detector and the detector should
% never be modified directly (this may cause the detector to be in... |
github | jacksky64/imageProcessing-master | acfDetect.m | .m | imageProcessing-master/piotr/toolbox/detector/acfDetect.m | 3,659 | utf_8 | cf1384311b16371be6fa4715140e5c81 | function bbs = acfDetect( I, detector, fileName )
% Run aggregate channel features object detector on given image(s).
%
% The input 'I' can either be a single image (or filename) or a cell array
% of images (or filenames). In the first case, the return is a set of bbs
% where each row has the format [x y w h score] and... |
github | jacksky64/imageProcessing-master | bbGt.m | .m | imageProcessing-master/piotr/toolbox/detector/bbGt.m | 34,046 | utf_8 | 69e66c9a0cc143fb9a794fbc9233246e | function varargout = bbGt( action, varargin )
% Bounding box (bb) annotations struct, evaluation and sampling routines.
%
% bbGt gives access to two types of routines:
% (1) Data structure for storing bb image annotations.
% (2) Routines for evaluating the Pascal criteria for object detection.
%
% The bb annotation sto... |
github | jacksky64/imageProcessing-master | bbApply.m | .m | imageProcessing-master/piotr/toolbox/detector/bbApply.m | 21,195 | utf_8 | cc9744e55c6b8442486ba7f71e3f84ce | function varargout = bbApply( action, varargin )
% Functions for manipulating bounding boxes (bb).
%
% A bounding box (bb) is also known as a position vector or a rectangle
% object. It is a four element vector with the fields: [x y w h]. A set of
% n bbs can be stores as an [nx4] array, most funcitons below can handle... |
github | jacksky64/imageProcessing-master | imwrite2.m | .m | imageProcessing-master/piotr/toolbox/images/imwrite2.m | 5,086 | utf_8 | c98d66c2cddd9ec90beb9b1bbde31fe0 | function I = imwrite2( I, mulFlag, imagei, path, ...
name, ext, nDigits, nSplits, spliti, varargin )
% Similar to imwrite, except follows a strict naming convention.
%
% Wrapper for imwrite that writes file to the filename:
% fName = [path name int2str2(i,nDigits) '.' ext];
% Using imwrite:
% imwrite( I, fName, wri... |
github | jacksky64/imageProcessing-master | convnFast.m | .m | imageProcessing-master/piotr/toolbox/images/convnFast.m | 9,102 | utf_8 | 03d05e74bb7ae2ecb0afd0ac115fda39 | function C = convnFast( A, B, shape )
% Fast convolution, replacement for both conv2 and convn.
%
% See conv2 or convn for more information on convolution in general.
%
% This works as a replacement for both conv2 and convn. Basically,
% performs convolution in either the frequency or spatial domain, depending
% on wh... |
github | jacksky64/imageProcessing-master | imMlGauss.m | .m | imageProcessing-master/piotr/toolbox/images/imMlGauss.m | 5,674 | utf_8 | 56ead1b25fbe356f7912993d46468d02 | function varargout = imMlGauss( G, symmFlag, show )
% Calculates max likelihood params of Gaussian that gave rise to image G.
%
% Suppose G contains an image of a gaussian distribution. One way to
% recover the parameters of the gaussian is to threshold the image, and
% then estimate the mean/covariance based on the c... |
github | jacksky64/imageProcessing-master | montage2.m | .m | imageProcessing-master/piotr/toolbox/images/montage2.m | 7,484 | utf_8 | 828f57d7b1f67d36eeb6056f06568ebf | function varargout = montage2( IS, prm )
% Used to display collections of images and videos.
%
% Improved version of montage, with more control over display.
% NOTE: Can convert between MxNxT and MxNx3xT image stack via:
% I = repmat( I, [1,1,1,3] ); I = permute(I, [1,2,4,3] );
%
% USAGE
% varargout = montage2( IS, ... |
github | jacksky64/imageProcessing-master | jitterImage.m | .m | imageProcessing-master/piotr/toolbox/images/jitterImage.m | 5,252 | utf_8 | 3310f8412af00fd504c6f94b8c48992c | function IJ = jitterImage( I, varargin )
% Creates multiple, slightly jittered versions of an image.
%
% Takes an image I, and generates a number of images that are copies of the
% original image with slight translation, rotation and scaling applied. If
% the input image is actually an MxNxK stack of images then applie... |
github | jacksky64/imageProcessing-master | movieToImages.m | .m | imageProcessing-master/piotr/toolbox/images/movieToImages.m | 889 | utf_8 | 28c71798642af276951ee27e2d332540 | function I = movieToImages( M )
% Creates a stack of images from a matlab movie M.
%
% Repeatedly calls frame2im. Useful for playback with playMovie.
%
% USAGE
% I = movieToImages( M )
%
% INPUTS
% M - a matlab movie
%
% OUTPUTS
% I - MxNxT array (of images)
%
% EXAMPLE
% load( 'images.mat' ); [X,map]=gray2ind... |
github | jacksky64/imageProcessing-master | toolboxUpdateHeader.m | .m | imageProcessing-master/piotr/toolbox/external/toolboxUpdateHeader.m | 2,255 | utf_8 | 7a5b75e586be48da97c84d20b59887ff | function toolboxUpdateHeader
% Update the headers of all the files.
%
% USAGE
% toolboxUpdateHeader
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
%
% See also
%
% Piotr's Computer Vision Matlab Toolbox Version 3.40
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Licensed under the Simplified BSD License [see extern... |
github | jacksky64/imageProcessing-master | toolboxGenDoc.m | .m | imageProcessing-master/piotr/toolbox/external/toolboxGenDoc.m | 3,639 | utf_8 | 4c21fb34fa9b6002a1a98a28ab40c270 | function toolboxGenDoc
% Generate documentation, must run from dir toolbox.
%
% 1) Make sure to update and run toolboxUpdateHeader.m
% 2) Update history.txt appropriately, including w current version
% 3) Update overview.html file with the version/date/link to zip:
% edit external/m2html/templates/frame-piotr/overv... |
github | jacksky64/imageProcessing-master | toolboxHeader.m | .m | imageProcessing-master/piotr/toolbox/external/toolboxHeader.m | 2,391 | utf_8 | 30c24a94fb54ca82622719adcab17903 | function [y1,y2] = toolboxHeader( x1, x2, x3, prm )
% One line description of function (will appear in file summary).
%
% General commments explaining purpose of function [width is 75
% characters]. There may be multiple paragraphs. In special cases some or
% all of these guidelines may need to be broken.
%
% Next come... |
github | jacksky64/imageProcessing-master | mdot.m | .m | imageProcessing-master/piotr/toolbox/external/m2html/mdot.m | 2,516 | utf_8 | 34a14428c433e118d1810e23f5a6caf5 | function mdot(mmat, dotfile,f)
%MDOT - Export a dependency graph into DOT language
% MDOT(MMAT, DOTFILE) loads a .mat file generated by M2HTML using option
% ('save','on') and writes an ascii file using the DOT language that can
% be drawn using <dot> or <neato> .
% MDOT(MMAT, DOTFILE,F) builds the graph containing... |
github | jacksky64/imageProcessing-master | m2html.m | .m | imageProcessing-master/piotr/toolbox/external/m2html/m2html.m | 49,063 | utf_8 | 472047b4c36a4f8b162012840e31b59b | function m2html(varargin)
%M2HTML - Documentation Generator for Matlab M-files and Toolboxes in HTML
% M2HTML by itself generates an HTML documentation of the Matlab M-files found
% in the direct subdirectories of the current directory. HTML files are
% written in a 'doc' directory (created if necessary). All the o... |
github | jacksky64/imageProcessing-master | doxysearch.m | .m | imageProcessing-master/piotr/toolbox/external/m2html/private/doxysearch.m | 7,724 | utf_8 | 8331cde8495f34b86aef8c18656b37f2 | function result = doxysearch(query,filename)
%DOXYSEARCH Search a query in a 'search.idx' file
% RESULT = DOXYSEARCH(QUERY,FILENAME) looks for request QUERY
% in FILENAME (Doxygen search.idx format) and returns a list of
% files responding to the request in RESULT.
%
% See also DOXYREAD, DOXYWRITE
% Copyright (C)... |
github | jacksky64/imageProcessing-master | doxywrite.m | .m | imageProcessing-master/piotr/toolbox/external/m2html/private/doxywrite.m | 3,584 | utf_8 | 3255d8f824957ebc173dde374d0f78af | function doxywrite(filename, kw, statinfo, docinfo)
%DOXYWRITE Write a 'search.idx' file compatible with DOXYGEN
% DOXYWRITE(FILENAME, KW, STATINFO, DOCINFO) writes file FILENAME
% (Doxygen search.idx. format) using the cell array KW containing the
% word list, the sparse matrix (nbword x nbfile) with non-null value... |
github | jacksky64/imageProcessing-master | doxyread.m | .m | imageProcessing-master/piotr/toolbox/external/m2html/private/doxyread.m | 3,093 | utf_8 | 3152e7d26bf7ac64118be56f72832a20 | function [statlist, docinfo] = doxyread(filename)
%DOXYREAD Read a 'search.idx' file generated by DOXYGEN
% STATLIST = DOXYREAD(FILENAME) reads FILENAME (Doxygen search.idx
% format) and returns the list of keywords STATLIST as a cell array.
% [STATLIST, DOCINFO] = DOXYREAD(FILENAME) also returns a cell array
% con... |
github | jacksky64/imageProcessing-master | imwrite2split.m | .m | imageProcessing-master/piotr/toolbox/external/deprecated/imwrite2split.m | 1,617 | utf_8 | 4222fd45df123e6dec9ef40ae793004f | % Writes/reads a large set of images into/from multiple directories.
%
% This is useful since certain OS handle very large directories (of say
% >20K images) rather poorly (I'm talking to you Bill). Thus, can take
% 100K images, and write into 5 separate directories, then read them back
% in.
%
% USAGE
% I = imwrite2... |
github | jacksky64/imageProcessing-master | playmovies.m | .m | imageProcessing-master/piotr/toolbox/external/deprecated/playmovies.m | 1,935 | utf_8 | ef2eaad8a130936a1a281f1277ca0ea1 | % [4D] shows R videos simultaneously as a movie.
%
% Plays a movie.
%
% USAGE
% playmovies( I, [fps], [loop] )
%
% INPUTS
% I - MxNxTxR or MxNx1xTxR or MxNx3xTxR array (if MxNxT calls
% playmovie)
% fps - [100] maximum number of frames to display per second use
% fps==0 to introduce n... |
github | jacksky64/imageProcessing-master | pca_apply_large.m | .m | imageProcessing-master/piotr/toolbox/external/deprecated/pca_apply_large.m | 2,062 | utf_8 | af84a2179b9d8042519bc6b378736a88 | % Wrapper for pca_apply that allows for application to large X.
%
% Wrapper for pca_apply that splits and processes X in parts, this may be
% useful if processing cannot be done fully in parallel because of memory
% constraints. See pca_apply for usage.
%
% USAGE
% same as pca_apply
%
% INPUTS
% same as pca_apply
%
%... |
github | jacksky64/imageProcessing-master | montages2.m | .m | imageProcessing-master/piotr/toolbox/external/deprecated/montages2.m | 2,269 | utf_8 | 505e2be915d65fff8bfef8473875cc98 | % MONTAGES2 [4D] Used to display R sets of T images each.
%
% Displays one montage (see montage2) per row. Each of the R image sets is
% flattened to a single long image by concatenating the T images in the
% set. Alternative to montages.
%
% USAGE
% varargout = montages2( IS, [montage2prms], [padSiz] )
%
% INPUTS
% ... |
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