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# -*- coding: utf-8 -*-
"""2.7 Code to be deployed 21.02.2025
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1RWSQn0GW_KXoHkJLcbYzLAGGyc0tiDWl
"""
"""## Imports"""
import sys
import math
import random
import string
import zlib
import base64
import datetime
import uuid
import re
from io import BytesIO
from ctypes import sizeof
from collections import Counter
from typing import NewType
import xml.etree.ElementTree as ET
from xml.etree.ElementTree import Element, SubElement, tostring, ElementTree
from xml.dom.minidom import parseString
import numpy as np
import cv2
from matplotlib import pyplot as plt
from matplotlib.patches import Polygon
from shapely.geometry import Point, Polygon as ShapelyPolygon
from shapely.ops import unary_union
from PIL import Image, ImageDraw, ImageFont, ImageColor
import fitz
import ezdxf
from ezdxf import units, bbox
from ezdxf.colors import aci2rgb
from ezdxf.math import OCS, Matrix44, Vec3, Vec2
import pandas as pd
import google_sheet_Legend
import tsadropboxretrieval
from PyPDF2 import PdfReader, PdfWriter
from PyPDF2.generic import (
NameObject,
TextStringObject,
DictionaryObject,
ArrayObject,
FloatObject,
NumberObject,
)
from math import sin, cos, radians, isclose
def normalize_vertices(vertices):
"""Sort vertices to ensure consistent order."""
return tuple(sorted(tuple(v) for v in vertices))
def areas_are_similar(area1, area2, tolerance=0.2):
"""Check if two areas are within a given tolerance."""
return abs(area1 - area2) <= tolerance
# -*- coding: utf-8 -*-wj
"""Version to be deployed of 3.2 Calculating area/perimeter
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1XPeCoTBgWSNBYZ3aMKBteP4YG3w4bORs
"""
import ezdxf
from ezdxf.bbox import extents
def detect_scale_from_page(dxf_path, page_pixel_width, m_per_pixel_from_pdf):
"""
Detects mm/px scale factor using the bounding box of the entire DXF content.
"""
doc = ezdxf.readfile(dxf_path)
#getting the bounding box from modelspace
msp = doc.modelspace()
bbox_msp = extents(msp, fast=True)
if bbox_msp.has_data: #not empty
min_x, min_y, max_x, max_y = bbox_msp.extmin.x, bbox_msp.extmin.y, bbox_msp.extmax.x, bbox_msp.extmax.y
else:
# Try paperspace as a fallback
psp = doc.layout("Layout1")
bbox_psp = extents(psp, fast=True)
if not bbox_psp.has_data:
raise ValueError("No bounding box data found in modelspace or paperspace.")
min_x, min_y, max_x, max_y = bbox_psp.extmin.x, bbox_psp.extmin.y, bbox_psp.extmax.x, bbox_psp.extmax.y
# DXF width
dxf_width = max_x - min_x
# PDF width in m
pdf_metric_width = page_pixel_width * m_per_pixel_from_pdf
# Correction factor
correction_factor = dxf_width / pdf_metric_width
# final_scale = mm_per_pixel_from_pdf * correction_factor
return correction_factor
"""## Notes"""
#new approach to get width and height of dxf plan
'''
This portion is used to convert vertices read from dxf to pixels in order to accurately locate shapes in the image and pdf
ratio :
MeasuredMetric* PixelValue/ DxfMetric = MeasuredPixel
PixelValue: get from pixel conversion code , second number in the bracker represents the perimeter
DxfMetric: measured perimeter from foxit
divide pixelvalue by dxfmetric, will give u a ratio , this is ur dxfratio
'''
AllhatchesCodes= {
'Brick':'<</Length 172/Type/Pattern/PatternType 1/PaintType 1/TilingType 1/Resources<<>>/Matrix[1 0 0 1 0 0]/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 18 m 19.00001 18 l 9 18 m 9 9 l -1 9 m 19.00001 9 l 0 9 m 0 0 l -1 0 m 19.00001 0 l 18 0 m 18 9 l S \nendstream'
,
'DiagonalBrick': '''<</Length 138
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources <<>>
/Matrix [1 0 0 1 0 0]
/BBox [0 0 18 18]
/XStep 18/YStep 18>>stream
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 -1 m 19.00001 19.00001 l 9 9 m 0 18 l -1 17 m 1 19.00001 l 17 -1 m 19.00001 1 l S
endstream'''
,
'Horizontal':'''<</Length 113
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>
/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]
/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 13.5 m 19.00001 13.5 l -1 4.5 m 19.00001 4.5 l S
endstream'''
,
'Vertical':'''<</Length 97
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>
/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]
/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w 4.5 19.00001 m 4.5 -1 l 13.5 19.00001 m 13.5 -1 l S
endstream'''
,
'DiagonalDown':'''<</Length 133
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 19.00001 m 19.00001 -1 l -1 1 m 1 -1 l 17 19.00001 m 19.00001 17 l S
endstream'''
,
'DiagonalUp':'''<</Length 125
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 17 m 1 19.00001 l -1 -1 m 19.00001 19.00001 l 17 -1 m 19.00001 1 l S
endstream'''
,
'Grid':'''<</Length 163
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w 4.5 19.00001 m 4.5 -1 l 13.5 19.00001 m 13.5 -1 l -1 13.5 m 19.00001 13.5 l -1 4.5 m 19.00001 4.5 l S
endstream'''
,
'Weave':'''<</Length 260
/Type/Pattern/PatternType 1/PaintType 1/TilingType 1
/Resources<<>>/Matrix[1 0 0 1 0 0]
/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n
{fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w -1 19.00001 m 4.5 13.5 l -1 7.999999 m 10 19.00001 l 7.999999 19.00001 m 19.00001 7.999999 l 17 19.00001 m 19.00001 17 l -1 -1 m 13.5 13.5 l 4.5 4.5 m 10 -1 l 9 9 m 19.00001 -1 l 18 9 m 13.5 4.5 l S
endstream'''
,
'10Dots':'''<</Length 6765/Type/Pattern/PatternType 1/PaintType 1/TilingType 1/Resources<<>>
/Matrix[1 0 0 1 0 0]/BBox[0 0 18 18]/XStep 18/YStep 18>>\nstream\n
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11.29529 9.5 11.57143 c 9.5 11.84757 9.276142 12.07143 9 12.07143 c 8.723858 12.07143 8.5 11.84757 8.5 11.57143 c 8.5 11.29529 8.723858 11.07143 9 11.07143 c h 9 13.64286 m 9.276142 13.64286 9.5 13.86672 9.5 14.14286 c 9.5 14.419 9.276142 14.64286 9 14.64286 c 8.723858 14.64286 8.5 14.419 8.5 14.14286 c 8.5 13.86672 8.723858 13.64286 9 13.64286 c h 9 16.21429 m 9.276142 16.21429 9.5 16.43814 9.5 16.71429 c 9.5 16.99043 9.276142 17.21429 9 17.21429 c 8.723858 17.21429 8.5 16.99043 8.5 16.71429 c 8.5 16.43814 8.723858 16.21429 9 16.21429 c h 11.57143 0.7857141 m 11.84757 0.7857141 12.07143 1.009572 12.07143 1.285714 c 12.07143 1.561857 11.84757 1.785714 11.57143 1.785714 c 11.29529 1.785714 11.07143 1.561857 11.07143 1.285714 c 11.07143 1.009572 11.29529 0.7857141 11.57143 0.7857141 c h 11.57143 3.357143 m 11.84757 3.357143 12.07143 3.581 12.07143 3.857143 c 12.07143 4.133285 11.84757 4.357142 11.57143 4.357142 c 11.29529 4.357142 11.07143 4.133285 11.07143 3.857143 c 11.07143 3.581 11.29529 3.357143 11.57143 3.357143 c h 11.57143 5.928572 m 11.84757 5.928572 12.07143 6.15243 12.07143 6.428572 c 12.07143 6.704715 11.84757 6.928572 11.57143 6.928572 c 11.29529 6.928572 11.07143 6.704715 11.07143 6.428572 c 11.07143 6.15243 11.29529 5.928572 11.57143 5.928572 c h 11.57143 8.5 m 11.84757 8.5 12.07143 8.723858 12.07143 9 c 12.07143 9.276142 11.84757 9.5 11.57143 9.5 c 11.29529 9.5 11.07143 9.276142 11.07143 9 c 11.07143 8.723858 11.29529 8.5 11.57143 8.5 c h 11.57143 11.07143 m 11.84757 11.07143 12.07143 11.29529 12.07143 11.57143 c 12.07143 11.84757 11.84757 12.07143 11.57143 12.07143 c 11.29529 12.07143 11.07143 11.84757 11.07143 11.57143 c 11.07143 11.29529 11.29529 11.07143 11.57143 11.07143 c h 11.57143 13.64286 m 11.84757 13.64286 12.07143 13.86672 12.07143 14.14286 c 12.07143 14.419 11.84757 14.64286 11.57143 14.64286 c 11.29529 14.64286 11.07143 14.419 11.07143 14.14286 c 11.07143 13.86672 11.29529 13.64286 11.57143 13.64286 c h 11.57143 16.21429 m 11.84757 16.21429 12.07143 16.43814 12.07143 16.71429 c 12.07143 16.99043 11.84757 17.21429 11.57143 17.21429 c 11.29529 17.21429 11.07143 16.99043 11.07143 16.71429 c 11.07143 16.43814 11.29529 16.21429 11.57143 16.21429 c h 14.14286 0.7857141 m 14.419 0.7857141 14.64286 1.009572 14.64286 1.285714 c 14.64286 1.561857 14.419 1.785714 14.14286 1.785714 c 13.86672 1.785714 13.64286 1.561857 13.64286 1.285714 c 13.64286 1.009572 13.86672 0.7857141 14.14286 0.7857141 c h 14.14286 3.357143 m 14.419 3.357143 14.64286 3.581 14.64286 3.857143 c 14.64286 4.133285 14.419 4.357142 14.14286 4.357142 c 13.86672 4.357142 13.64286 4.133285 13.64286 3.857143 c 13.64286 3.581 13.86672 3.357143 14.14286 3.357143 c h 14.14286 5.928572 m 14.419 5.928572 14.64286 6.15243 14.64286 6.428572 c 14.64286 6.704715 14.419 6.928572 14.14286 6.928572 c 13.86672 6.928572 13.64286 6.704715 13.64286 6.428572 c 13.64286 6.15243 13.86672 5.928572 14.14286 5.928572 c h 14.14286 8.5 m 14.419 8.5 14.64286 8.723858 14.64286 9 c 14.64286 9.276142 14.419 9.5 14.14286 9.5 c 13.86672 9.5 13.64286 9.276142 13.64286 9 c 13.64286 8.723858 13.86672 8.5 14.14286 8.5 c h 14.14286 11.07143 m 14.419 11.07143 14.64286 11.29529 14.64286 11.57143 c 14.64286 11.84757 14.419 12.07143 14.14286 12.07143 c 13.86672 12.07143 13.64286 11.84757 13.64286 11.57143 c 13.64286 11.29529 13.86672 11.07143 14.14286 11.07143 c h 14.14286 13.64286 m 14.419 13.64286 14.64286 13.86672 14.64286 14.14286 c 14.64286 14.419 14.419 14.64286 14.14286 14.64286 c 13.86672 14.64286 13.64286 14.419 13.64286 14.14286 c 13.64286 13.86672 13.86672 13.64286 14.14286 13.64286 c h 14.14286 16.21429 m 14.419 16.21429 14.64286 16.43814 14.64286 16.71429 c 14.64286 16.99043 14.419 17.21429 14.14286 17.21429 c 13.86672 17.21429 13.64286 16.99043 13.64286 16.71429 c 13.64286 16.43814 13.86672 16.21429 14.14286 16.21429 c h 16.71429 0.7857141 m 16.99043 0.7857141 17.21429 1.009572 17.21429 1.285714 c 17.21429 1.561857 16.99043 1.785714 16.71429 1.785714 c 16.43814 1.785714 16.21429 1.561857 16.21429 1.285714 c 16.21429 1.009572 16.43814 0.7857141 16.71429 0.7857141 c h 16.71429 3.357143 m 16.99043 3.357143 17.21429 3.581 17.21429 3.857143 c 17.21429 4.133285 16.99043 4.357142 16.71429 4.357142 c 16.43814 4.357142 16.21429 4.133285 16.21429 3.857143 c 16.21429 3.581 16.43814 3.357143 16.71429 3.357143 c h 16.71429 5.928572 m 16.99043 5.928572 17.21429 6.15243 17.21429 6.428572 c 17.21429 6.704715 16.99043 6.928572 16.71429 6.928572 c 16.43814 6.928572 16.21429 6.704715 16.21429 6.428572 c 16.21429 6.15243 16.43814 5.928572 16.71429 5.928572 c h 16.71429 8.5 m 16.99043 8.5 17.21429 8.723858 17.21429 9 c 17.21429 9.276142 16.99043 9.5 16.71429 9.5 c 16.43814 9.5 16.21429 9.276142 16.21429 9 c 16.21429 8.723858 16.43814 8.5 16.71429 8.5 c h 16.71429 11.07143 m 16.99043 11.07143 17.21429 11.29529 17.21429 11.57143 c 17.21429 11.84757 16.99043 12.07143 16.71429 12.07143 c 16.43814 12.07143 16.21429 11.84757 16.21429 11.57143 c 16.21429 11.29529 16.43814 11.07143 16.71429 11.07143 c h 16.71429 13.64286 m 16.99043 13.64286 17.21429 13.86672 17.21429 14.14286 c 17.21429 14.419 16.99043 14.64286 16.71429 14.64286 c 16.43814 14.64286 16.21429 14.419 16.21429 14.14286 c 16.21429 13.86672 16.43814 13.64286 16.71429 13.64286 c h 16.71429 16.21429 m 16.99043 16.21429 17.21429 16.43814 17.21429 16.71429 c 17.21429 16.99043 16.99043 17.21429 16.71429 17.21429 c 16.43814 17.21429 16.21429 16.99043 16.21429 16.71429 c 16.21429 16.43814 16.43814 16.21429 16.71429 16.21429 c h
{strokecolor} rg f
endstream'''
}
HatchStyleTemplates={
'Brick' :'/PatternName(Brick)', #BBObjPtr
'DiagonalBrick':'/PatternName(Diagonal Brick)',
'Horizontal':'/PatternName(Horizontal)',
'Vertical':'/PatternName(Vertical)',
'DiagonalDown':'/PatternName(Diagonal Down)',
'DiagonalUp':'/PatternName(Diagonal Up)',
'Grid':'/PatternName(Grid)',
'Weave':'/PatternName(Weave)',
'10Dots':'/PatternName(10% Dots)',
'20Dots':'/PatternName(20% Dots)',
'30Dots':'/PatternName(30% Dots)'
}
def calculate_bounding_rect(vertices):
xs = [pt[0] for pt in vertices]
ys = [pt[1] for pt in vertices]
min_x = min(xs)
max_x = max(xs)
min_y = min(ys)
max_y = max(ys)
return [min_x, min_y, max_x, max_y]
def generate_annotation_xml_block(vertices, area_text, author, custom_data: dict, column_order: list, index: int,
type_internal: str = 'Bluebeam.PDF.Annotations.AnnotationMeasureArea',
subject: str = 'Area Measurement',
label: str = '',opacity:str='',
color:str='', linestyle:str='',
hatchstyle:str='',hatchLinescolor:str='',
bb_objptrMeas:str=''):
now = datetime.datetime.utcnow()
mod_date = now.strftime("D:%Y%m%d%H%M%S+00'00'")
creation_date = now.isoformat() + 'Z'
id_str = generate_bb_objptr()# "fitz-" + uuid.uuid4().hex[:4].upper()
vert_str = ' '.join([f'{x:.4f}' for point in vertices for x in point])
ordered_column_values = [f'({custom_data.get(col, "")})' for col in column_order]
bsi_column_data = ''.join(ordered_column_values)
meastype=''
if subject.startswith('Area'):
meastype='129'
polygonpolylineDimension='/PolygonDimension'
polygonpolyline='/Polygon'
elif subject.startswith('Perimeter'):
meastype='130'
polygonpolylineDimension='/PolyLineDimension'
polygonpolyline='/PolyLine'
rectvertices=calculate_bounding_rect(vertices)
raw_text = f'''<<
/DS(font: Helvetica 12pt; text-align:center; line-height:13.8pt; color:#FF0000)
/Cap false
/AlignOnSegment true
/MeasurementTypes {meastype}
/SlopeType 1
/PitchRun 12
/IT
{polygonpolylineDimension}
/Vertices[{vert_str}]
/IC[{color}]
/Pattern/{hatchstyle}/PatternColor[{hatchLinescolor}]
/FillOpacity {opacity}
/T({author})
/CA {opacity}
/RC(<?xml version="1.0"?><body xmlns:xfa="http://www.xfa.org/schema/xfa-data/1.0/" xfa:contentType="text/html" xfa:APIVersion="BluebeamPDFRevu:2018" xfa:spec="2.2.0" style="font:Helvetica 12pt; text-align:center; line-height:13.8pt; color:#FF0000" xmlns="http://www.w3.org/1999/xhtml"><p>{area_text}</p></body>)
/Label({label})
/Subj({subject})
/Measure/BBObjPtr_{bb_objptrMeas}
/BSIColumnData[{bsi_column_data}]
/NM({id_str})
/Subtype/{polygonpolyline}
/Rect[{rectvertices[0]} {rectvertices[1]} {rectvertices[2]} {rectvertices[3]}]
/Contents({area_text})
/F 4
/C[{color}]
/BS{linestyle}
/M({mod_date})
>>'''.encode('utf-8')
compressed = zlib.compress(raw_text)
base64_raw = base64.b16encode(compressed).lower().decode()
annotation = Element('Annotation')
SubElement(annotation, 'Page').text = '1'
SubElement(annotation, 'Contents').text = area_text
SubElement(annotation, 'ModDate').text = creation_date
SubElement(annotation, 'Color').text = '#B7B7E8'
SubElement(annotation, 'Type').text = 'Polygon'
SubElement(annotation, 'ID').text = id_str
SubElement(annotation, 'TypeInternal').text = type_internal
SubElement(annotation, 'Raw').text = base64_raw
SubElement(annotation, 'Index').text = str(index)
custom = SubElement(annotation, 'Custom')
for key, value in custom_data.items():
SubElement(custom, key).text = value
SubElement(annotation, 'Subject').text = subject
SubElement(annotation, 'CreationDate').text = creation_date
SubElement(annotation, 'Author').text = author
SubElement(annotation, 'Label').text = label
return annotation
def generate_bb_objptr():
return ''.join(random.choices(string.ascii_uppercase, k=16))
def compresslikeBBRaw(textToCompress):
decompressedX = textToCompress.encode('utf-8')
print(decompressedX)
recompressedX = zlib.compress(decompressedX)
print(recompressedX.hex())
return recompressedX.hex()
def setBrickHatch(fillcolor,strokecolor):
# resourceid='789cf30b0877f2f40cf30f758ff48e0a0df3040029f004fd'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['Brick'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['Brick'],compressedRaw, resourceid
def setDiagonalBrickHatch(fillcolor,strokecolor):
# resourceid='789c0b0d8cf47274f60d0df28a740ef4f4f3020029ab04da'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['DiagonalBrick'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['DiagonalBrick'],compressedRaw,resourceid
def setHorizontalHatch(fillcolor,strokecolor):
# resourceid='789cf3720b76f6f072f173f58cf071f209f00000273604a3'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['Horizontal'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['Horizontal'],compressedRaw,resourceid
def setVerticalHatch(fillcolor,strokecolor):
# resourceid='789cf30d080ef4f609088b74740ff0890a7607002a1904f0'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['Vertical'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['Vertical'],compressedRaw,resourceid
def setDiagonalDownHatch(fillcolor,strokecolor):
# resourceid='789cf3f28b74f477f7770b0c7675f68f74f60300288f04c3'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['DiagonalDown'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['DiagonalDown'],compressedRaw,resourceid
def setDiagonalUpHatch(fillcolor,strokecolor):
# resourceid='789c0b8a70f30df4f70b09f40cf6f108757606002a2304dc'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['DiagonalUp'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['DiagonalUp'],compressedRaw,resourceid
def setGridHatch(fillcolor,strokecolor):
# resourceid='789c730b71738e0a760cf3758972f370740a0300286b04ba'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['Grid'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['Grid'],compressedRaw,resourceid
def setWeaveHatch(fillcolor,strokecolor):
# resourceid='789cf30af775f2f1f776720d8972740c8af40500285c04c6'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['Weave'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['Weave'],compressedRaw,resourceid
def set10DotsHatch(fillcolor,strokecolor):
# resourceid='789cf3740f71f6770d0e8c0a0f76f50e0df00600291c04e4'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['10Dots'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['10Dots'],compressedRaw,resourceid
def set20DotsHatch(fillcolor,strokecolor):
# resourceid='789c738f0cf70bf5f0f0770a0df471760df7000029b004d5'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['20Dots'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['20Dots'],compressedRaw,resourceid
def set30DotsHatch(fillcolor,strokecolor):
# resourceid='789cf38c747789f4f68a8c0cf2f6f2f676f2070029b104dc'
randombb_objptr=generate_bb_objptr()
resourceid=compresslikeBBRaw(randombb_objptr)
compressedRaw=compresslikeBBRaw(AllhatchesCodes['30Dots'].format(fillcolor=fillcolor, strokecolor=strokecolor))
return 'BBObjPtr_'+randombb_objptr+HatchStyleTemplates['30Dots'],compressedRaw,resourceid
def save_multiple_annotations_bax(annotations, output_path, column_order,pdfWidth,pdfHeight):
"""
annotations: list of dicts, each with:
- vertices: list of [x, y]
- text: str (label/tooltip)
- author: str
- custom_data: dict of custom field values
- type_internal: str (e.g., Bluebeam.PDF.Annotations.AnnotationMeasurePerimeter)
- subject: str (e.g., Perimeter Measurement)
"""
globalhatches=[]
scales=[]
doc = Element('Document', Version='1')
########## Subelement1 - page ################
page = SubElement(doc, 'Page', Index='0')
SubElement(page, 'Label').text = '1'
SubElement(page, 'Width').text = str(pdfWidth)
SubElement(page, 'Height').text = str(pdfHeight)
for i, ann in enumerate(annotations):
bb_objptrMeas=generate_bb_objptr()
resourceidComp=compresslikeBBRaw(bb_objptrMeas)
scales.append(resourceidComp)
hatchstyle_key = ann.get('hatchstyle') # e.g., 'Brick'
if hatchstyle_key not in globalhatches and hatchstyle_key:
globalhatches.append([hatchstyle_key[2],hatchstyle_key[1]]) # id, raw
hatchstyle=hatchstyle_key[0]
else:
hatchstyle='none'
annotation_xml = generate_annotation_xml_block(
vertices=ann['vertices'],
area_text=ann['text'],
author=ann['author'],
custom_data=ann['custom_data'],
column_order=column_order,
index=i,
bb_objptrMeas=bb_objptrMeas,
type_internal=ann.get('type_internal', 'Bluebeam.PDF.Annotations.AnnotationMeasureArea'),
subject=ann.get('subject', 'Area Measurement'),
label=ann.get('label', 'label1'),
opacity=ann.get('opacity', ''),
color=ann.get('color', ''),
linestyle=ann.get('linestyle', ''),
hatchstyle=hatchstyle,
hatchLinescolor=ann.get('hatchLinescolor',''),
)
page.append(annotation_xml)
################# Subelement 2 - Global resources############
GlobalResources = SubElement(doc, 'GlobalResources')
for hatch in globalhatches:
Resource = SubElement(GlobalResources, 'Resource')
SubElement(Resource, 'ID').text = hatch[0]
SubElement(Resource, 'Raw').text = hatch[1]
for scale in scales:
Resource = SubElement(GlobalResources, 'Resource')
SubElement(Resource, 'ID').text = scale
SubElement(Resource, 'Raw').text = '789c85d04f0b82401005f0af3247bd34bb46d9c11642f15411fe89c03aa80ce161b5d6dda06f9f1e148aace330efc783e779983c6f843bca5ba3086353e8fe8eb618591c4a096be0206d3c6543746f64412a6c94cc35a656f7f381cdd87ce1b8aebbc200386318c7962dc405839f8c7fa43753e9f60e6f200c402b43234ca6e0d959b26ff0d0c1511fa77469fed4e6ea4a3aad2bed37f583545b3575bf051bd610e205c9766776'
bax_xml= tostring(doc, encoding="unicode", method="xml") #tostring(doc, encoding="utf-8", method="xml").decode("utf-8")
# print(f" Saved {len(annotations)} annotations to {output_path}")
return bax_xml
"""PDF to image"""
def pdftoimg(datadoc,pdf_content=0):
if pdf_content:
doc = fitz.open(stream=pdf_content, filetype="pdf")
else:
doc =fitz.open('pdf',datadoc)
page=doc[0]
pix = page.get_pixmap() # render page to an image
pl=Image.frombytes('RGB', [pix.width,pix.height],pix.samples)
img=np.array(pl)
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
print("IMAGE")
# cv2_imshow(img)
return img,pix
# Standard ISO paper sizes in inches
ISO_SIZES_INCHES = {
"A0": (33.11, 46.81),
"A1": (23.39, 33.11),
"A2": (16.54, 23.39),
"A3": (11.69, 16.54),
"A4": (8.27, 11.69),
"A5": (5.83, 8.27),
"A6": (4.13, 5.83),
"A7": (2.91, 4.13),
"A8": (2.05, 2.91),
"A9": (1.46, 2.05),
"A10": (1.02, 1.46)
}
def get_paper_size_in_inches(width, height):
"""Find the closest matching paper size in inches."""
for size, (w, h) in ISO_SIZES_INCHES.items():
if (abs(w - width) < 0.1 and abs(h - height) < 0.1) or (abs(w - height) < 0.1 and abs(h - width) < 0.1):
return size
return "Unknown Size"
def analyze_pdf(datadoc,pdf_content=0):
# Open the PDF file
if pdf_content:
pdf_document = fitz.open(stream=pdf_content, filetype="pdf")
else:
pdf_document = fitz.open('pdf',datadoc)
# Iterate through pages and print their sizes
for page_number in range(len(pdf_document)):
page = pdf_document[page_number]
rect = page.rect
width_points, height_points = rect.width, rect.height
# Convert points to inches
width_inches, height_inches = width_points / 72, height_points / 72
paper_size = get_paper_size_in_inches(width_inches, height_inches)
print(f"Page {page_number + 1}: {width_inches:.2f} x {height_inches:.2f} inches ({paper_size})")
pdf_document.close()
return width_inches , height_inches , paper_size
def get_dxfSize(dxfpath):
doc = ezdxf.readfile(dxfpath)
msp = doc.modelspace()
# Create a cache for bounding box calculations
# Get the overall bounding box for all entities in the modelspace
cache = bbox.Cache()
overall_bbox = bbox.extents(msp, cache=cache)
print("Overall Bounding Box:", overall_bbox)
print(overall_bbox.extmin[0]+overall_bbox.extmax[0], overall_bbox.extmin[1]+overall_bbox.extmax[1])
return overall_bbox.extmin[0]+overall_bbox.extmax[0], overall_bbox.extmin[1]+overall_bbox.extmax[1]
def switch_case(argument):
switcher = {
"A0": 1.27,
"A1": 2.54,
"A2": 5.08,
"A3": 10.16,
"A4": 20.32,
"A5": 40.64,
"A6": 81.28,
"A7": 162.56,
"A8": 325.12,
"A9": 650.24,
"A10": 1300.48
}
# Get the value from the dictionary; if not found, return a default value
print("Final Ratio=",switcher.get(argument, 1))
return switcher.get(argument, 1)
def RetriveRatio(datadoc,dxfpath,pdf_content=0):
if pdf_content:
width,height,paper_size = analyze_pdf (datadoc,pdf_content)
else:
width,height,paper_size = analyze_pdf (datadoc)
if(width > height ):
bigger=width
else:
bigger=height
width_dxf,height_dxf = get_dxfSize(dxfpath)
if(width_dxf > height_dxf ):
bigger_dxf=width_dxf
else:
bigger_dxf=height_dxf
if(0.2 < bigger_dxf/bigger < 1.2):
print("bigger_dxf/bigger",bigger/bigger_dxf)
argument = paper_size
FinalRatio=switch_case(argument)
else:
FinalRatio=1
return FinalRatio,width_dxf
"""Flips image
DXF origin is at the bottom left while img origin is top left
"""
def flip(img):
height, width = img.shape[:2]
# Define the rotation angle (clockwise)
angle = 180
# Calculate the rotation matrix
rotation_matrix = cv2.getRotationMatrix2D((width/2, height/2), angle, 1)
# Rotate the image
rotated_image = cv2.warpAffine(img, rotation_matrix, (width, height))
flipped_horizontal = cv2.flip(rotated_image, 1)
return flipped_horizontal
def aci_to_rgb(aci):
aci_rgb_map = {
0: (0, 0, 0),
1: (255, 0, 0),
2: (255, 255, 0),
3: (0, 255, 0),
4: (0, 255, 255),
5: (0, 0, 255),
6: (255, 0, 255),
7: (255, 255, 255),
8: (65, 65, 65),
9: (128, 128, 128),
10: (255, 0, 0),
11: (255, 170, 170),
12: (189, 0, 0),
13: (189, 126, 126),
14: (129, 0, 0),
15: (129, 86, 86),
16: (104, 0, 0),
17: (104, 69, 69),
18: (79, 0, 0),
19: (79, 53, 53),
20: (255, 63, 0),
21: (255, 191, 170),
22: (189, 46, 0),
23: (189, 141, 126),
24: (129, 31, 0),
25: (129, 96, 86),
26: (104, 25, 0),
27: (104, 78, 69),
28: (79, 19, 0),
29: (79, 59, 53),
30: (255, 127, 0),
31: (255, 212, 170),
32: (189, 94, 0),
33: (189, 157, 126),
34: (129, 64, 0),
35: (129, 107, 86),
36: (104, 52, 0),
37: (104, 86, 69),
38: (79, 39, 0),
39: (79, 66, 53),
40: (255, 191, 0),
41: (255, 234, 170),
42: (189, 141, 0),
43: (189, 173, 126),
44: (129, 96, 0),
45: (129, 118, 86),
46: (104, 78, 0),
47: (104, 95, 69),
48: (79, 59, 0),
49: (79, 73, 53),
50: (255, 255, 0),
51: (255, 255, 170),
52: (189, 189, 0),
53: (189, 189, 126),
54: (129, 129, 0),
55: (129, 129, 86),
56: (104, 104, 0),
57: (104, 104, 69),
58: (79, 79, 0),
59: (79, 79, 53),
60: (191, 255, 0),
61: (234, 255, 170),
62: (141, 189, 0),
63: (173, 189, 126),
64: (96, 129, 0),
65: (118, 129, 86),
66: (78, 104, 0),
67: (95, 104, 69),
68: (59, 79, 0),
69: (73, 79, 53),
70: (127, 255, 0),
71: (212, 255, 170),
72: (94, 189, 0),
73: (157, 189, 126),
74: (64, 129, 0),
75: (107, 129, 86),
76: (52, 104, 0),
77: (86, 104, 69),
78: (39, 79, 0),
79: (66, 79, 53),
80: (63, 255, 0),
81: (191, 255, 170),
82: (46, 189, 0),
83: (141, 189, 126),
84: (31, 129, 0),
85: (96, 129, 86),
86: (25, 104, 0),
87: (78, 104, 69),
88: (19, 79, 0),
89: (59, 79, 53),
90: (0, 255, 0),
91: (170, 255, 170),
92: (0, 189, 0),
93: (126, 189, 126),
94: (0, 129, 0),
95: (86, 129, 86),
96: (0, 104, 0),
97: (69, 104, 69),
98: (0, 79, 0),
99: (53, 79, 53),
100: (0, 255, 63),
101: (170, 255, 191),
102: (0, 189, 46),
103: (126, 189, 141),
104: (0, 129, 31),
105: (86, 129, 96),
106: (0, 104, 25),
107: (69, 104, 78),
108: (0, 79, 19),
109: (53, 79, 59),
110: (0, 255, 127),
111: (170, 255, 212),
112: (0, 189, 94),
113: (126, 189, 157),
114: (0, 129, 64),
115: (86, 129, 107),
116: (0, 104, 52),
117: (69, 104, 86),
118: (0, 79, 39),
119: (53, 79, 66),
120: (0, 255, 191),
121: (170, 255, 234),
122: (0, 189, 141),
123: (126, 189, 173),
124: (0, 129, 96),
125: (86, 129, 118),
126: (0, 104, 78),
127: (69, 104, 95),
128: (0, 79, 59),
129: (53, 79, 73),
130: (0, 255, 255),
131: (170, 255, 255),
132: (0, 189, 189),
133: (126, 189, 189),
134: (0, 129, 129),
135: (86, 129, 129),
136: (0, 104, 104),
137: (69, 104, 104),
138: (0, 79, 79),
139: (53, 79, 79),
140: (0, 191, 255),
141: (170, 234, 255),
142: (0, 141, 189),
143: (126, 173, 189),
144: (0, 96, 129),
145: (86, 118, 129),
146: (0, 78, 104),
147: (69, 95, 104),
148: (0, 59, 79),
149: (53, 73, 79),
150: (0, 127, 255),
151: (170, 212, 255),
152: (0, 94, 189),
153: (126, 157, 189),
154: (0, 64, 129),
155: (86, 107, 129),
156: (0, 52, 104),
157: (69, 86, 104),
158: (0, 39, 79),
159: (53, 66, 79),
160: (0, 63, 255),
161: (170, 191, 255),
162: (0, 46, 189),
163: (126, 141, 189),
164: (0, 31, 129),
165: (86, 96, 129),
166: (0, 25, 104),
167: (69, 78, 104),
168: (0, 19, 79),
169: (53, 59, 79),
170: (0, 0, 255),
171: (170, 170, 255),
172: (0, 0, 189),
173: (126, 126, 189),
174: (0, 0, 129),
175: (86, 86, 129),
176: (0, 0, 104),
177: (69, 69, 104),
178: (0, 0, 79),
179: (53, 53, 79),
180: (63, 0, 255),
181: (191, 170, 255),
182: (46, 0, 189),
183: (141, 126, 189),
184: (31, 0, 129),
185: (96, 86, 129),
186: (25, 0, 104),
187: (78, 69, 104),
188: (19, 0, 79),
189: (59, 53, 79),
190: (127, 0, 255),
191: (212, 170, 255),
192: (94, 0, 189),
193: (157, 126, 189),
194: (64, 0, 129),
195: (107, 86, 129),
196: (52, 0, 104),
197: (86, 69, 104),
198: (39, 0, 79),
199: (66, 53, 79),
200: (191, 0, 255),
201: (234, 170, 255),
202: (141, 0, 189),
203: (173, 126, 189),
204: (96, 0, 129),
205: (118, 86, 129),
206: (78, 0, 104),
207: (95, 69, 104),
208: (59, 0, 79),
209: (73, 53, 79),
210: (255, 0, 255),
211: (255, 170, 255),
212: (189, 0, 189),
213: (189, 126, 189),
214: (129, 0, 129),
215: (129, 86, 129),
216: (104, 0, 104),
217: (104, 69, 104),
218: (79, 0, 79),
219: (79, 53, 79),
220: (255, 0, 191),
221: (255, 170, 234),
222: (189, 0, 141),
223: (189, 126, 173),
224: (129, 0, 96),
225: (129, 86, 118),
226: (104, 0, 78),
227: (104, 69, 95),
228: (79, 0, 59),
229: (79, 53, 73),
230: (255, 0, 127),
231: (255, 170, 212),
232: (189, 0, 94),
233: (189, 126, 157),
234: (129, 0, 64),
235: (129, 86, 107),
236: (104, 0, 52),
237: (104, 69, 86),
238: (79, 0, 39),
239: (79, 53, 66),
240: (255, 0, 63),
241: (255, 170, 191),
242: (189, 0, 46),
243: (189, 126, 141),
244: (129, 0, 31),
245: (129, 86, 96),
246: (104, 0, 25),
247: (104, 69, 78),
248: (79, 0, 19),
249: (79, 53, 59),
250: (51, 51, 51),
251: (80, 80, 80),
252: (105, 105, 105),
253: (130, 130, 130),
254: (190, 190, 190),
255: (255, 255, 255)
}
# Default to white if index is invalid or not found
return aci_rgb_map.get(aci, (255, 255, 255))
def int_to_rgb(color_int):
"""Convert an integer to an (R, G, B) tuple."""
r = (color_int >> 16) & 255
g = (color_int >> 8) & 255
b = color_int & 255
return (r, g, b)
def get_hatch_color(entity):
"""Extract hatch color with detailed debugging."""
if not entity:
# print("No entity provided for color extraction.")
return (255, 255, 255)
# Check for true color
if entity.dxf.hasattr('true_color'):
true_color = entity.dxf.true_color
rgb_color = int_to_rgb(true_color) # Convert integer to (R, G, B)
# print(f"True color detected (RGB): {rgb_color}")
return rgb_color
# Check for color index
color_index = entity.dxf.color
# print(f"Entity color index: {color_index}")
if 1 <= color_index <= 255:
rgb_color = aci_to_rgb(color_index) # Convert ACI to RGB
# print(f"Converted ACI to RGB: {rgb_color}")
return rgb_color
# Handle ByLayer or ByBlock
if color_index == 0: # ByLayer
layer_name = entity.dxf.layer
layer = entity.doc.layers.get(layer_name)
# print(f"ByLayer detected for layer '{layer_name}'.")
if layer:
layer_color_index = layer.dxf.color
# print(layer_color_index)
rgb_color = aci_to_rgb(layer_color_index)
# print(f"Layer '{layer_name}' color index {layer_color_index} converted to RGB: {rgb_color}")
return rgb_color
else:
# print(f"Layer '{layer_name}' not found. Defaulting to white.")
return (255, 255, 255)
# Default
# print("Unhandled color case. Defaulting to white.")
return (255, 255, 255)
def point_in_rectangle(point, rect_coords):
x, y = point
(x1, y1), (x2, y2) = rect_coords
return x1 <= x <= x2 and y1 <= y <= y2
from math import sqrt
def euclidean_distance(point1, point2):
x1, y1 = point1
x2, y2 = point2
return sqrt((x2 - x1)**2 + (y2 - y1)**2)
def compute_hatch_centroid(hatch):
x_coords = []
y_coords = []
for path in hatch.paths:
if path.PATH_TYPE == "PolylinePath":
for vertex in path.vertices:
x_coords.append(vertex[0])
y_coords.append(vertex[1])
elif path.PATH_TYPE == "EdgePath":
for edge in path.edges:
if hasattr(edge, "start"):
x_coords.append(edge.start[0])
y_coords.append(edge.start[1])
if hasattr(edge, "end"):
x_coords.append(edge.end[0])
y_coords.append(edge.end[1])
if x_coords and y_coords:
return (sum(x_coords) / len(x_coords), sum(y_coords) / len(y_coords))
return None
"""### Hatched areas"""
def get_hatched_areas(datadoc,filename,FinalRatio,rotationangle,SearchArray,CollectedColors):
coloredarray = [tuple(x) for x in CollectedColors]
# coloredarray = [list(c) if isinstance(c, (tuple, list)) else [c] for c in CollectedColors]
print("CollectedColors = ",CollectedColors)
# print("coloredarray = ",coloredarray)
print("SearchArray = ",SearchArray)
doc = ezdxf.readfile(filename)
doc.header['$MEASUREMENT'] = 1
msp = doc.modelspace()
trial=0
hatched_areas = []
threshold=0.001
TextFound = 0
j=0
unique_shapes = []
text_with_positions = []
text_color_mapping = {}
color_palette = [
(255, 0, 0), (0, 0, 255), (0, 255, 255), (0, 64, 0), (255, 204, 0),
(255, 128, 64), (255, 0, 128), (255, 128, 192), (128, 128, 255),
(128, 64, 0), (0, 255, 0), (0, 200, 0), (255, 128, 255), (128, 0, 255),
(0, 128, 192), (128, 0, 128), (128, 0, 0), (0, 128, 255), (149, 1, 70),
(255, 182, 128), (222, 48, 71), (240, 0, 112), (255, 0, 255),
(192, 46, 65), (0, 0, 128), (0, 128, 64), (255, 255, 0), (128, 0, 80),
(255, 255, 128), (90, 255, 140), (255, 200, 20), (91, 16, 51),
(90, 105, 138), (114, 10, 138), (36, 82, 78), (225, 105, 190),
(108, 150, 170), (11, 35, 75), (42, 176, 170), (255, 176, 170),
(209, 151, 15), (81, 27, 85), (226, 106, 122), (67, 119, 149),
(159, 179, 140), (159, 179, 30), (255, 85, 198), (255, 27, 85),
(188, 158, 8), (140, 188, 120), (59, 61, 52), (65, 81, 21),
(212, 255, 174), (15, 164, 90), (41, 217, 245), (213, 23, 182),
(11, 85, 169), (78, 153, 239), (0, 66, 141), (64, 98, 232),
(140, 112, 255), (57, 33, 154), (194, 117, 252), (116, 92, 135),
(74, 43, 98), (188, 13, 123), (129, 58, 91), (255, 128, 100),
(171, 122, 145), (255, 98, 98), (222, 48, 77)
]
import re
text_with_positions = []
# SearchArray=[["","Wall Type","",""],["","","",""]]
# print("SearchArray=",len(SearchArray))
# print("SearchArray=",len(SearchArray[0]))
# print("SearchArray=",SearchArray[0][0])
if(SearchArray):
for i in range(len(SearchArray)):
if (SearchArray[i][0] and SearchArray[i][1] and SearchArray[i][2]):
for text_entity in doc.modelspace().query('TEXT MTEXT'):
text = text_entity.text.strip() if hasattr(text_entity, 'text') else ""
# if (text.startswith("P") and len(text) == 3) or (text.startswith("I") and len(text) == 3): # Filter for "Wall"
if(text.startswith(SearchArray[i][0]) and len(text)==int(SearchArray[i][2])):
position = text_entity.dxf.insert # Extract text position
x, y = position.x, position.y
for text_entity in doc.modelspace().query('TEXT MTEXT'):
NBS = text_entity.text.strip() if hasattr(text_entity, 'text') else ""
if (NBS.startswith(SearchArray[i][1])):
positionNBS = text_entity.dxf.insert # Extract text position
xNBS, yNBS = positionNBS.x, positionNBS.y
if(x == xNBS or y == yNBS):
textNBS=NBS
break
else:
textNBS = None
nearest_hatch = None
min_distance = float('inf') # Initialize with a very large value
detected_color = (255, 255, 255) # Default to white
# Search for the nearest hatch
for hatch in doc.modelspace().query('HATCH'): # Query only hatches
if hatch.paths:
for path in hatch.paths:
if path.type == 1: # PolylinePath
vertices = [v[:2] for v in path.vertices]
# Calculate the centroid of the hatch
centroid_x = sum(v[0] for v in vertices) / len(vertices)
centroid_y = sum(v[1] for v in vertices) / len(vertices)
centroid = (centroid_x, centroid_y)
# Calculate the distance between the text and the hatch centroid
distance = calculate_distance((x, y), centroid)
# Update the nearest hatch if a closer one is found
if distance < min_distance:
min_distance = distance
nearest_hatch = hatch
# Get the color of this hatch
current_color = get_hatch_color(hatch)
if current_color != (255, 255, 255): # Valid color found
detected_color = current_color
break # Stop checking further paths for this hatch
# Append the detected result only once
text_with_positions.append([text, textNBS, (x, y), detected_color])
print("text_with_positions=",text_with_positions)
elif (SearchArray[i][0] and SearchArray[i][2]):
for text_entity in doc.modelspace().query('TEXT MTEXT'):
text = text_entity.text.strip() if hasattr(text_entity, 'text') else ""
# if (text.startswith("P") and len(text) == 3) or (text.startswith("I") and len(text) == 3): # Filter for "Wall"
if(text.startswith(SearchArray[i][0]) and len(text)==int(SearchArray[i][2])):
position = text_entity.dxf.insert # Extract text position
x, y = position.x, position.y
textNBS = None
nearest_hatch = None
min_distance = float('inf') # Initialize with a very large value
detected_color = (255, 255, 255) # Default to white
# Search for the nearest hatch
for hatch in doc.modelspace().query('HATCH'): # Query only hatches
if hatch.paths:
for path in hatch.paths:
if path.type == 1: # PolylinePath
vertices = [v[:2] for v in path.vertices]
# Calculate the centroid of the hatch
centroid_x = sum(v[0] for v in vertices) / len(vertices)
centroid_y = sum(v[1] for v in vertices) / len(vertices)
centroid = (centroid_x, centroid_y)
# Calculate the distance between the text and the hatch centroid
distance = calculate_distance((x, y), centroid)
# Update the nearest hatch if a closer one is found
if distance < min_distance:
min_distance = distance
nearest_hatch = hatch
# Get the color of this hatch
current_color = get_hatch_color(hatch)
if current_color != (255, 255, 255): # Valid color found
detected_color = current_color
break # Stop checking further paths for this hatch
# Append the detected result only once
text_with_positions.append([text, textNBS, (x, y), detected_color])
print("text_with_positions=",text_with_positions)
elif(SearchArray[i][0]):
for text_entity in doc.modelspace().query('TEXT MTEXT'):
text = text_entity.text.strip() if hasattr(text_entity, 'text') else ""
# if (text.startswith("P") and len(text) == 3) or (text.startswith("I") and len(text) == 3): # Filter for "Wall"
if(text.startswith(SearchArray[i][0])):
position = text_entity.dxf.insert # Extract text position
x, y = position.x, position.y
textNBS = None
nearest_hatch = None
min_distance = float('inf') # Initialize with a very large value
detected_color = (255, 255, 255) # Default to white
# Search for the nearest hatch
for hatch in doc.modelspace().query('HATCH'): # Query only hatches
if hatch.paths:
for path in hatch.paths:
if path.type == 1: # PolylinePath
vertices = [v[:2] for v in path.vertices]
# Calculate the centroid of the hatch
centroid_x = sum(v[0] for v in vertices) / len(vertices)
centroid_y = sum(v[1] for v in vertices) / len(vertices)
centroid = (centroid_x, centroid_y)
# Calculate the distance between the text and the hatch centroid
distance = calculate_distance((x, y), centroid)
# Update the nearest hatch if a closer one is found
if distance < min_distance:
min_distance = distance
nearest_hatch = hatch
# Get the color of this hatch
current_color = get_hatch_color(hatch)
if current_color != (255, 255, 255): # Valid color found
detected_color = current_color
break # Stop checking further paths for this hatch
# Append the detected result only once
text_with_positions.append([text, textNBS, (x, y), detected_color])
print("text_with_positions=",text_with_positions)
grouped = {}
for entry in text_with_positions:
key = entry[0]
grouped.setdefault(key, []).append(entry)
# Filter the groups: if any entry in a group has a non-None Text Nbs, keep only one of those
filtered_results = []
for key, entries in grouped.items():
# Find the first entry with a valid textNBS (non-None)
complete = next((entry for entry in entries if entry[1] is not None), None)
if complete:
filtered_results.append(complete)
else:
# If none are complete, you can choose to keep just one entry
filtered_results.append(entries[0])
text_with_positions=filtered_results
for entity in msp:
if entity.dxftype() == 'HATCH':
cntPoints=[]
for path in entity.paths:
# path_type = path.type
# # Resolve the path type to its name
# path_type_name = BoundaryPathType(path_type).name
# print(f"Encountered path type: {path_type_name}")
vertices = [] # Reset vertices for each path
# print(str(path.type))
if str(path.type) == 'BoundaryPathType.POLYLINE' or path.type == 1:
# if path.type == 2: # Polyline path
# Handle POLYLINE type HATCH
vertices = [(vertex[0] * FinalRatio, vertex[1] * FinalRatio) for vertex in path.vertices]
# print("Hatch Vertices = ",vertices)
if len(vertices) > 3:
poly = ShapelyPolygon(vertices)
minx, miny, maxx, maxy = poly.bounds
width = maxx - minx
height = maxy - miny
if (poly.area > 0 and (height > 0 or width > 0)):
length = height
if(width > length):
length = width
area1 = round(poly.area, 3)
perimeter = round(poly.length, 3)
# print("Vertices = ",vertices)
normalized_vertices = normalize_vertices(vertices)
rgb_color = get_hatch_color(entity)
# print("rgb_color = ",rgb_color)
# if(rgb_color == (255, 255, 255)):
# if(len(text_with_positions)>0):
# for text, position, color in text_with_positions:
# text_position = Point(position[0], position[1])
# if poly.contains(text_position):
# rgb_color = color
# break
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices and areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
# rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
if length > 0.6:
# rgbconverted = tuple(rgb_color)
# print("rgb_color = ",type(rgb_color))
# print("CollectedColors = ",type(CollectedColors))
# colored_fix = [tuple(map(int, c)) for c in coloredarray]
if ( len(coloredarray) > 0 and ( rgb_color in coloredarray)):
print("rgbcolor in 2.7 hatch 1 type = ",type(rgb_color))
print("coloredarray in 2.7 hatch 1 type = ",type(coloredarray))
hatched_areas.append([vertices, area1, length, rgb_color])
elif (len(coloredarray) == 0):
hatched_areas.append([vertices, area1, length, rgb_color])
print("rgbcolor = ",rgb_color)
print("coloredarray =",coloredarray)
elif str(path.type) == 'BoundaryPathType.EDGE' or path.type == 2:
# elif path.type == 2: # Edge path
# Handle EDGE type HATCH
vert = []
for edge in path.edges:
x, y = edge.start
x1, y1 = edge.end
vert.append((x * FinalRatio, y * FinalRatio))
vert.append((x1 * FinalRatio, y1 * FinalRatio))
poly = ShapelyPolygon(vert)
minx, miny, maxx, maxy = poly.bounds
width = maxx - minx
height = maxy - miny
if (poly.area > 0 and (height > 0 or width > 0)):
length = height
if(width > length):
length = width
area1 = round(poly.area, 3)
perimeter = round(poly.length, 3)
normalized_vertices = normalize_vertices(vert)
rgb_color = get_hatch_color(entity)
# print("rgb_color = ",rgb_color)
# if(rgb_color == (255, 255, 255)):
# if(len(text_with_positions)>0):
# for text, position, color in text_with_positions:
# text_position = Point(position[0], position[1])
# if poly.contains(text_position):
# rgb_color = color
# break
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices and areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
# rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
if length > 0.6:
rgbconverted = tuple(rgb_color)
if ( len(CollectedColors) > 0 and (rgb_color in CollectedColors)):
print("rgbcolor in 2.7 hatch 2 type = ",type(rgb_color))
print("CollectedColors in 2.7 hatch 2 type = ",type(CollectedColors))
hatched_areas.append([vert, area1, length, rgb_color])
elif (len(CollectedColors) == 0):
hatched_areas.append([vert, area1, length, rgb_color])
else:
print(f"Encountered path type: {path.type}")
elif entity.dxftype() == 'SOLID':
vertices = [entity.dxf.vtx0 * (FinalRatio), entity.dxf.vtx1* (FinalRatio), entity.dxf.vtx2* (FinalRatio), entity.dxf.vtx3* (FinalRatio)]
poly = ShapelyPolygon(vertices)
minx, miny, maxx, maxy = poly.bounds
# Calculate the width and height of the bounding box
width = maxx - minx
height = maxy - miny
if (poly.area > 0 and (height > 0 and width > 0)):
area1 = round(poly.area, 3)
perimeter = round(poly.length, 3)
normalized_vertices = normalize_vertices(vertices)
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices or areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
rgbconverted = tuple(rgb_color)
if ( len(CollectedColors) > 0 and (rgb_color in CollectedColors)):
print("rgbcolor in 2.7 solid type = ",type(rgb_color))
print("CollectedColors in 2.7 solid type = ",type(CollectedColors))
hatched_areas.append([vertices, area1, perimeter, rgb_color])
elif (len(CollectedColors) == 0):
hatched_areas.append([vertices, area1, perimeter, rgb_color])
elif entity.dxftype() == 'LWPOLYLINE':
vertices = []
lwpolyline = entity
points = lwpolyline.get_points()
flag = 0
# Collect vertices and apply the FinalRatio
for i in range(len(points)):
vertices.append([points[i][0] * FinalRatio, points[i][1] * FinalRatio])
# # Ensure there are more than 3 vertices
if len(vertices) > 3:
# Check if the polyline is closed
if vertices[0][0] == vertices[-1][0] or vertices[0][1] == vertices[-1][1]:
poly = ShapelyPolygon(vertices)
minx, miny, maxx, maxy = poly.bounds
# Calculate width and height of the bounding box
width = maxx - minx
height = maxy - miny
# Check area and size constraints
if (poly.area > 0 and (height > 0 and width > 0)):
area1 = round(poly.area, 3)
perimeter = round(poly.length, 3)
normalized_vertices = normalize_vertices(vertices)
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices or areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
hatched_areas.append([vertices, area1, perimeter, rgb_color])
elif entity.dxftype() == 'POLYLINE':
flag=0
vertices = [(v.dxf.location.x * (FinalRatio), v.dxf.location.y * (FinalRatio)) for v in entity.vertices]
# print('Vertices:', vertices)
if(len(vertices)>3):
if(vertices[0][0] == vertices[len(vertices)-1][0] or vertices[0][1] == vertices[len(vertices)-1][1]):
poly=ShapelyPolygon(vertices)
minx, miny, maxx, maxy = poly.bounds
# Calculate the width and height of the bounding box
width = maxx - minx
height = maxy - miny
if (poly.area > 0 and (height > 0 and width > 0)):
area1 = round(poly.area,3)
perimeter = round (poly.length,3)
normalized_vertices = normalize_vertices(vertices)
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices or areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
hatched_areas.append([vertices, area1, perimeter, rgb_color])
elif entity.dxftype() == 'SPLINE':
spline_entity = entity
vertices = []
control_points = spline_entity.control_points
if(len(control_points)>3):
for i in range(len(control_points)):
vertices.append([control_points[i][0]* (FinalRatio),control_points[i][1]* (FinalRatio)])
poly=ShapelyPolygon(vertices)
minx, miny, maxx, maxy = poly.bounds
# Calculate the width and height of the bounding box
width = maxx - minx
height = maxy - miny
if (poly.area > 0 and (height > 0 and width > 0)):
area1 = round(poly.area,3)
perimeter = round (poly.length,3)
normalized_vertices = normalize_vertices(vertices)
duplicate_found = False
for existing_vertices, existing_area in unique_shapes:
if normalized_vertices == existing_vertices or areas_are_similar(area1, existing_area):
duplicate_found = True
break
if not duplicate_found:
rgb_color = get_hatch_color(entity) # Assuming this function exists
unique_shapes.append((normalized_vertices, area1))
hatched_areas.append([vertices, area1, perimeter, rgb_color])
sorted_data = sorted(hatched_areas, key=lambda x: x[1])
return sorted_data,text_with_positions
"""### Rotate polygon"""
def rotate_point(point, angle,pdfrotation,width,height, center_point=(0, 0)):
"""Rotates a point around center_point(origin by default)
Angle is in degrees.
Rotation is counter-clockwise
"""
angle_rad = radians(angle % 360)
# Shift the point so that center_point becomes the origin
new_point = (point[0] - center_point[0], point[1] - center_point[1])
new_point = (new_point[0] * cos(angle_rad) - new_point[1] * sin(angle_rad),
new_point[0] * sin(angle_rad) + new_point[1] * cos(angle_rad))
# Reverse the shifting we have done
if pdfrotation!=0:
new_point = (new_point[0]+width + center_point[0], new_point[1] + center_point[1]) #pdfsize[2] is the same as +width
else:
new_point = (new_point[0] + center_point[0], new_point[1]+ height + center_point[1]) # pdfsize[3] is the same as +height
# new_point = (new_point[0] + center_point[0], new_point[1] + center_point[1])
return new_point
def rotate_polygon(polygon, angle, pdfrotation,width,height,center_point=(0, 0)):
"""Rotates the given polygon which consists of corners represented as (x,y)
around center_point (origin by default)
Rotation is counter-clockwise
Angle is in degrees
"""
rotated_polygon = []
for corner in polygon:
rotated_corner = rotate_point(corner, angle,pdfrotation,width,height, center_point)
rotated_polygon.append(rotated_corner)
return rotated_polygon
#create a dataframe containing color , count(how many times is this object found in the plan), area of 1 of these shapes, total area
#perimeter, totat perimeter, length, total length
#import pandas as pd
#SimilarAreaDictionary= pd.DataFrame(columns=['Guess','Color','Occurences','Area','Total Area','Perimeter','Total Perimeter','Length','Total Length','R','G','B'])
#loop 3la hatched areas and count the occurences of each shape w create a table bl hagat di
def Create_DF(dxfpath,datadoc,hatched_areas,pdf_content=0):
if pdf_content:
FinalRatio,width_dxf= RetriveRatio(datadoc,dxfpath,pdf_content)
else:
FinalRatio,width_dxf= RetriveRatio(datadoc,dxfpath)
# hatched_areas = get_hatched_areas(datadoc,dxfpath,FinalRatio)
# hatched_areas=remove_duplicate_shapes(new_hatched_areas)
# SimilarAreaDictionary= pd.DataFrame(columns=['Area', 'Total Area', 'Perimeter', 'Total Perimeter', 'Occurences', 'Color'])
SimilarAreaDictionary= pd.DataFrame(columns=['Guess','Color','Occurences','Area','Total Area','Perimeter','Total Perimeter','Length','Total Length','Texts','Comments'])
# colorRanges2=generate_color_array(30000)
# colorRanges = [[255, 0, 0], [0, 0, 255], [0, 255, 255], [0, 64, 0], [255, 204, 0], [255, 128, 64], [255, 0, 128], [255, 128, 192], [128, 128, 255], [128, 64, 0],[0, 255, 0],[0, 200, 0],[255, 128, 255], [128, 0, 255], [0, 128, 192], [128, 0, 128],[128, 0, 0], [0, 128, 255], [149, 1, 70], [255, 182, 128], [222, 48, 71], [240, 0, 112], [255, 0, 255], [192, 46, 65], [0, 0, 128],[0, 128, 64],[255, 255, 0], [128, 0, 80], [255, 255, 128], [90, 255, 140],[255, 200, 20],[91, 16, 51], [90, 105, 138], [114, 10, 138], [36, 82, 78], [225, 105, 190], [108, 150, 170], [11, 35, 75], [42, 176, 170], [255, 176, 170], [209, 151, 15],[81, 27, 85], [226, 106, 122], [67, 119, 149], [159, 179, 140], [159, 179, 30],[255, 85, 198], [255, 27, 85], [188, 158, 8],[140, 188, 120], [59, 61, 52], [65, 81, 21], [212, 255, 174], [15, 164, 90],[41, 217, 245], [213, 23, 182], [11, 85, 169], [78, 153, 239], [0, 66, 141],[64, 98, 232], [140, 112, 255], [57, 33, 154], [194, 117, 252], [116, 92, 135], [74, 43, 98], [188, 13, 123], [129, 58, 91], [255, 128, 100], [171, 122, 145], [255, 98, 98], [222, 48, 77]]
# colorUsed=[]
TotalArea=0
TotalPerimeter=0
for shape in hatched_areas:
area = shape[1] # area
perimeter = shape[2] # perimeter
# if(i < len(colorRanges)):
# color = colorRanges[i]
# colorUsed.append(color)
# else:
# color = colorRanges2[i]
# colorUsed.append(color)
TotalArea = area
TotalPerimeter = perimeter
tol=0
condition1 = (SimilarAreaDictionary['Area'] >= area - tol) & (SimilarAreaDictionary['Area'] <= area +tol)
condition2 = (SimilarAreaDictionary['Perimeter'] >= perimeter -tol) & (SimilarAreaDictionary['Perimeter'] <= perimeter +tol)
combined_condition = condition1 & condition2
if any(combined_condition):
index = np.where(combined_condition)[0][0]
SimilarAreaDictionary.at[index, 'Occurences'] += 1
SimilarAreaDictionary.at[index, 'Total Area'] = SimilarAreaDictionary.at[index, 'Area'] * SimilarAreaDictionary.at[index, 'Occurences']
SimilarAreaDictionary.at[index, 'Total Perimeter'] = SimilarAreaDictionary.at[index, 'Perimeter'] * SimilarAreaDictionary.at[index, 'Occurences']
else:
TotalArea=area
TotalPerimeter=perimeter
# print("Shape[3]",shape[3])
new_data = {'Area': area, 'Total Area': TotalArea ,'Perimeter': perimeter, 'Total Perimeter': TotalPerimeter, 'Occurences': 1, 'Color':shape[3],'Comments':''} #add color here and read color to insert in
SimilarAreaDictionary = pd.concat([SimilarAreaDictionary, pd.DataFrame([new_data])], ignore_index=True)
# print(SimilarAreaDictionary)
return SimilarAreaDictionary
"""### Draw on Image and PDF"""
# from sklearn.cluster import KMeans
def color_distance(color1, color2):
print("color1 = ",color1)
print("color2 = ",color2)
print("abs(color1[0] - color2[0]) = ",abs(color1[0] - color2[0]))
print("abs(color1[1] - color2[1]) = ",abs(color1[1] - color2[1]))
print("abs(color1[2] - color2[2]) = ",abs(color1[2] - color2[2]))
if(abs(color1[0] - color2[0]) < 20 and
abs(color1[1] - color2[1]) < 20 and
abs(color1[2] - color2[2]) < 20):
return 1
else:
return 100
# return np.sqrt(sum((a - b) ** 2 for a, b in zip(color1, color2)))
# Unify colors within a distance threshold
def unify_colors(df, threshold=20):
# Convert colors to tuple if they are not already in tuple format
df['Color'] = df['Color'].apply(lambda x: tuple(x) if isinstance(x, list) else x)
# Iterate through the DataFrame and compare each color with the next one
for i in range(len(df) - 1): # We don't need to compare the last color with anything
current_color = df.at[i, 'Color']
next_color = df.at[i + 1, 'Color']
# If the distance between current color and the next color is smaller than the threshold
if color_distance(current_color, next_color) <= threshold:
# Make both the same color (unify them to the current color)
df.at[i + 1, 'Color'] = current_color # Change the next color to the current color
return df
def normalize_color(color):
"""Convert PDF color (range 0-1) to RGB (range 0-255)."""
return tuple(min(max(round(c * 255), 0), 255) for c in color)
def color_close_enough(c1, c2, threshold=10):
return all(abs(a - b) <= threshold for a, b in zip(c1, c2))
def adjustannotations(OutputPdfStage1,text_with_positions,CollectedColors):
input_pdf_path = OutputPdfStage1
output_pdf_path = "Final-WallsAdjusted.pdf"
annotations_data = []
paired_colors = []
for i in range(0, len(CollectedColors), 2):
name = CollectedColors[i] # take the current name
color_list = CollectedColors[i+1] # take the next item as color list
# convert each component to int
color = tuple(int(c) for c in color_list)
paired_colors.append([name, color])
CollectedColors = paired_colors
# Load the input PDF
pdf_bytes_io = BytesIO(OutputPdfStage1)
reader = PdfReader(pdf_bytes_io)
writer = PdfWriter()
# Append all pages to the writer
writer.append_pages_from_reader(reader)
# Add metadata (optional)
metadata = reader.metadata
writer.add_metadata(metadata)
for page_index, page in enumerate(writer.pages):
if "/Annots" not in page:
continue
for annot in page["/Annots"]:
obj = annot.get_object()
subtype = obj.get("/Subtype")
# Group vertices for metadata
if subtype == "/Line":
raw_vertices = obj.get("/L", [])
else:
raw_vertices = obj.get("/Vertices", [])
vertices = group_vertices(raw_vertices)
# Normalize color
raw_color = obj.get("/C")
try:
annot_color = normalize_color(raw_color)
except:
annot_color = raw_color
# Extract measurement from annotation content
measurement = extract_measurement(obj)
# Assign to area or perimeter based on subtype
area = measurement if subtype == "/Polygon" else None
perimeter = measurement if subtype in ["/Line", "/PolyLine"] else None
# Match text and NBS
matched_text = None
matched_nbs = None
if subtype in ["/Line", "/PolyLine", "/Polygon"] and raw_color:
matched_entry = next(
((t, n) for t, n, _, c in text_with_positions if color_close_enough(annot_color, c)),
(None, None)
)
matched_text, matched_nbs = matched_entry
print("1st entry nbs: " ,type(matched_nbs))
print("1st entry text: ",type(matched_text))
combined = ""
if matched_text and matched_nbs:
combined = f"{matched_text} - {matched_nbs}"
elif matched_text:
combined = matched_text
elif matched_nbs:
combined = matched_nbs
if combined:
obj.update({NameObject("/T"): TextStringObject(combined)})
if subtype in ["/Line", "/PolyLine", "/Polygon"] and raw_color:
matched_entry2 = next(
((name,color) for name,color in CollectedColors if color_close_enough(annot_color,color)),
(None, None)
)
matched_text2, matched_nbs2 = matched_entry2
# print("2nd entry nbs: " ,type(matched_nbs2))
# print("2nd entry text: ",type(matched_text2))
combined2 = ""
if matched_text2 and matched_nbs2:
combined2 = f"{matched_text2} - {matched_nbs2}"
elif matched_text:
combined2 = str(matched_text2)
elif matched_nbs:
combined2 = str(matched_nbs2)
if combined2:
obj.update({NameObject("/T"): TextStringObject(combined2)})
# Update annotation dictionaries for measurement type
if subtype == "/Line" and obj.get("/Subj", "") == "Perimeter Measurement":
obj.update({
NameObject("/Measure"): DictionaryObject({
NameObject("/Type"): NameObject("/Measure"),
NameObject("/L"): DictionaryObject({
NameObject("/G"): FloatObject(1),
NameObject("/U"): TextStringObject("m"),
}),
}),
NameObject("/IT"): NameObject("/LineDimension"),
NameObject("/Subj"): TextStringObject("Length Measurement"),
})
if subtype == "/Polygon" and obj.get("/Subj", "") == "Area Measurement":
obj.update({
NameObject("/Measure"): DictionaryObject({
NameObject("/Type"): NameObject("/Measure"),
NameObject("/Area"): DictionaryObject({
NameObject("/G"): FloatObject(1),
NameObject("/U"): TextStringObject("sq m"),
}),
}),
NameObject("/IT"): NameObject("/Area_Annotation"),
NameObject("/Subj"): TextStringObject("Area Measurement"),
})
# Append metadata
annotations_data.append([
vertices,
area,
perimeter,
annot_color,
matched_text,
matched_nbs,
matched_text2,
matched_nbs2,
])
output_pdf_io = BytesIO()
writer.write(output_pdf_io)
output_pdf_io.seek(0)
print(f"Annotations updated and saved to {output_pdf_path}")
return output_pdf_io.read() , annotations_data
def distance(rect1, rect2):
"""Calculate the Euclidean distance between two annotation centers."""
x1, y1 = (float(rect1[0]) + float(rect1[2])) / 2, (float(rect1[1]) + float(rect1[3])) / 2
x2, y2 = (float(rect2[0]) + float(rect2[2])) / 2, (float(rect2[1]) + float(rect2[3])) / 2
return math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
def group_vertices(raw):
"""Convert flat list [x1,y1,x2,y2,...] into [[x1,y1],[x2,y2],...]"""
if not raw or len(raw) < 2:
return []
return [[float(raw[i]), float(raw[i+1])] for i in range(0, len(raw), 2)]
def group_rect(verts):
"""Convert list of [x,y] vertices into a bounding rect [x_min, y_min, x_max, y_max]."""
xs = [v[0] for v in verts]
ys = [v[1] for v in verts]
return [min(xs), min(ys), max(xs), max(ys)] if verts else None
def extract_measurement(obj):
"""Extract first numeric measurement from an annotation's /Contents."""
contents = obj.get("/Contents")
if not contents:
return None
match = re.search(r"([0-9]*\.?[0-9]+)", str(contents))
return float(match.group(1)) if match else None
def remove_duplicate_annotations(pdf_path, threshold):
"""Remove one of the duplicate annotations if they are close and have the same color."""
input_pdf_path = pdf_path
output_pdf_path = "Filtered-Walls.pdf"
# Load the input PDF
pdf_bytes_io = BytesIO(pdf_path)
reader = PdfReader(pdf_bytes_io)
writer = PdfWriter()
# Append all pages to the writer
# writer.append_pages_from_reader(reader)
# Add metadata (optional)
metadata = reader.metadata
writer.add_metadata(metadata)
for page_index in range(len(reader.pages)):
page = reader.pages[page_index]
if "/Annots" in page:
annotations = page["/Annots"]
annots_data = []
to_delete = set()
# Extract annotation positions and colors
# for annot_index, annot_ref in enumerate(annotations):
# annot = annot_ref.get_object()
# if "/Rect" in annot and "/C" in annot:
# rect = annot["/Rect"]
# if isinstance(rect, ArrayObject): # Ensure rect is a list
# rect = list(rect)
# color = normalize_color(annot["/C"])
# annots_data.append((annot_index, rect, color))
for i, annot_ref in enumerate(annotations):
annot = annot_ref.get_object()
rect = annot.get("/Rect")
color = annot.get("/C")
if rect and color and isinstance(rect, ArrayObject) and len(rect) == 4:
norm_color = normalize_color(color)
annots_data.append((i, list(rect), norm_color))
for i, (idx1, rect1, color1) in enumerate(annots_data):
if idx1 in to_delete:
continue
for j in range(i + 1, len(annots_data)):
idx2, rect2, color2 = annots_data[j]
if idx2 in to_delete:
continue
if color_close_enough(color1, color2) and distance(rect1, rect2) < threshold:
to_delete.add(idx2)
# Keep only non-duplicates
new_annots = [annotations[i] for i in range(len(annotations)) if i not in to_delete]
page[NameObject("/Annots")] = ArrayObject(new_annots)
# Compare distances and mark duplicates
# for i, (idx1, rect1, color1) in enumerate(annots_data):
# if idx1 in to_delete:
# continue
# for j, (idx2, rect2, color2) in enumerate(annots_data[i+1:], start=i+1):
# if idx2 in to_delete:
# continue
# if color1 == color2 and distance(rect1, rect2) < threshold:
# to_delete.add(idx2) # Mark second annotation for deletion
# # Remove duplicates
# new_annotations = [annotations[i] for i in range(len(annotations)) if i not in to_delete]
# page[NameObject("/Annots")] = ArrayObject(new_annotations)
writer.add_page(page)
output_pdf_io = BytesIO()
writer.write(output_pdf_io)
output_pdf_io.seek(0)
return output_pdf_io.read()
def rect_distance(r1, r2):
"""Euclidean distance between rect centers."""
if not r1 or not r2:
return float('inf')
cx1, cy1 = (r1[0]+r1[2])/2, (r1[1]+r1[3])/2
cx2, cy2 = (r2[0]+r2[2])/2, (r2[1]+r2[3])/2
return math.hypot(cx2-cx1, cy2-cy1)
def group_rect(verts):
"""Turn [[x,y],…] into (x_min, y_min, x_max, y_max)."""
xs = [x for x,_ in verts]
ys = [y for _,y in verts]
return (min(xs), min(ys), max(xs), max(ys)) if verts else None
def clean_annotations(annotations_data, threshold):
"""
Remove “nearby” duplicates from annotations_data,
where each entry is EITHER a dict with a 'vertices' key
OR a list/tuple whose first element *is* the vertices list.
"""
# 1) Extract a parallel list of bounding rects
rects = []
for item in annotations_data:
if isinstance(item, dict):
verts = item.get('vertices', [])
elif isinstance(item, (list, tuple)) and item:
# heuristically assume the first element is vertices
verts = item[0] if isinstance(item[0], list) else []
else:
verts = []
rects.append(group_rect(verts))
# 2) Mark duplicates
to_delete = set()
for i, r1 in enumerate(rects):
if i in to_delete:
continue
for j in range(i+1, len(rects)):
if j in to_delete:
continue
if rect_distance(r1, rects[j]) < threshold:
to_delete.add(j)
# 3) Build cleaned list
cleaned = []
for idx, item in enumerate(annotations_data):
if idx not in to_delete:
cleaned.append(item)
return cleaned
def calculate_distance(p1, p2):
return math.sqrt((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)
def ROI_boundingBoxCoor(img):
# Threshold (invert: walls are white)
imgGray= cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(imgGray, 250, 255, cv2.THRESH_BINARY_INV)
# Morphological cleanup
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
walls = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
# --- Connected components ---
num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(walls, connectivity=8)
best_idx = None
best_score = -1
h, w = walls.shape
cx_img, cy_img = w//2, h//2 # image center
for i in range(1, num_labels): # ignore background (0)
x, y, bw, bh, area = stats[i]
cx, cy = centroids[i]
# Score = area minus distance penalty
#prefer large area AND closeness to image center
dist = np.hypot(cx - cx_img, cy - cy_img)
score = area - 0.5 * dist #tune 0.5
if score > best_score:
best_score = score
best_idx = i
# --- Get bounding box of best region ---
bbox = None
if best_idx is not None:
x, y, bw, bh, _ = stats[best_idx]
margin = 50
x = int(max(x - margin, 0))
y = int(max(y - margin, 0))
bw = int(min(bw + 2*margin, w-x))
bh = int(min(bh + 2*margin, h-y))
# Define bounding box as (x_min, y_min, x_max, y_max)
bbox = (x, y, x+bw, y+bh)
# Draw ROI
imgcopy = img.copy()
cv2.rectangle(imgcopy, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0,255,0), 2)
mask = np.zeros_like(img)
cv2.rectangle(mask, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (255,255,255), -1)
main_zone = cv2.bitwise_and(img, mask)
return imgcopy, main_zone, bbox
return img, img, bbox
def draw_bb_onPDF(doc,bbox):
page = doc[0]
x1, y1 = bbox[0],bbox[1]
x2, y2 = bbox[2],bbox[3]
p1 = fitz.Point(x1,y1)
p2 = fitz.Point(x2,y2)
p1=p1*page.derotation_matrix
p2=p2*page.derotation_matrix
rect = fitz.Rect(p1, p2).normalize()
x0, y0, x1, y1 = rect.x0, rect.y0, rect.x1, rect.y1
pdf_bbox=[x0, y0, x1, y1]
page.draw_rect(rect) #for visualization only
doc.save('kk.pdf') #ffor visualization only
return pdf_bbox
def mainFunctionDrawImgPdf(datadoc,dxfpath, dxfratio,SearchArray,CorrectionRatio,CollectedColors,points_Of_drawing_Canvas,Thickness,pdfpath=0,pdfname=0,pdf_content=0):
# print("points_Of_drawing_Canvas in 2.7 = ",points_Of_drawing_Canvas)
# print("CollectedColors in 2.7 = ",CollectedColors)
OutputPdfStage1='BB Trial.pdf'
if pdf_content:
FinalRatio,width_dxf= RetriveRatio(datadoc,dxfpath,pdf_content)
else:
FinalRatio,width_dxf= RetriveRatio(datadoc,dxfpath)
# hatched_areas = get_hatched_areas(datadoc,dxfpath,FinalRatio)
# hatched_areas=remove_duplicate_shapes(new_hatched_areas)
if pdf_content:
img,pix2=pdftoimg(datadoc,pdf_content)
else:
img,pix2=pdftoimg(datadoc)
flipped_horizontal=flip(img)
allcnts = []
imgg = flipped_horizontal
# imgtransparent1=imgg.copy()
if pdf_content:
doc = fitz.open(stream=pdf_content, filetype="pdf")
else:
doc = fitz.open('pdf',datadoc)
page2 = doc[0]
rotationOld=page2.rotation
derotationMatrix=page2.derotation_matrix
# print("Derotation Matrix = ",derotationMatrix)
pix=page2.get_pixmap()
width=abs(page2.mediabox[2])+abs(page2.mediabox[0])
height=abs(page2.mediabox[3])+abs(page2.mediabox[1])
print('mediabox', width , height)
Correction = CorrectionRatio / width_dxf
print("Correction Factor = ",round((Correction/FinalRatio),1))
dxfratio = dxfratio * round((Correction/FinalRatio),1)
print("new omar dxfRatio = ",dxfratio)
imgcopy, main_zone, bbox = ROI_boundingBoxCoor(img) #send here bgr img not gray
pdf_bbox=draw_bb_onPDF(doc,bbox)
bxmin, bymin, bxmax, bymax = pdf_bbox
# print('olddxfratio',dxfratio)
# correction_factor= detect_scale_from_page(dxfpath,width,dxfratio/1000)
# factor=1
# print('corr_factor',correction_factor)
# if correction_factor <0.26: #if less than 0.25 then the dxf ratio is correeect, if greater then *2
# factor=1
# print('Ratio working: keep as it is')
# else:
# factor =2
# print('Ratio was adjusted to be ur input ratio x2')
# dxfratio=dxfratio*factor
# print('new dxfratio', dxfratio)
if page2.rotation!=0:
rotationangle = page2.rotation
page2.set_rotation(0)
ratio = pix.width/ img.shape[0]
else:
ratio = pix.width/ img.shape[1]
rotationangle = 270
hatched_areas,text_with_positions = get_hatched_areas(datadoc,dxfpath,FinalRatio,rotationangle,SearchArray,CollectedColors)
allshapes=[]
# Iterate through each polygon in metric units
NewColors = []
if pdf_content:
SimilarAreaDictionary=Create_DF(dxfpath,datadoc,hatched_areas,pdf_content)
else:
SimilarAreaDictionary=Create_DF(dxfpath,datadoc,hatched_areas)
i=0
flagcolor = 0
ColorCounter = 0
ColorCheck=[]
deleterows = []
# def color_distance(color1, color2):
# return np.sqrt(sum((a - b) ** 2 for a, b in zip(color1, color2)))
color_margin = 2 # Define margin threshold
for polygon in hatched_areas:
cntPoints = []
cntPoints1 = []
shapeePerimeter = []
shapeeArea = []
Text_Detected = 0
blackImgShapes = np.zeros(imgg.shape[:2], dtype="uint8")
blackImgShapes= cv2.cvtColor(blackImgShapes, cv2.COLOR_GRAY2BGR)
# Convert each vertex from metric to pixel coordinates
for vertex in polygon[0]:
x = (vertex[0]) *dxfratio
y = (vertex[1]) *dxfratio
if rotationangle==0:
if y<0:
y=y*-1
cntPoints.append([int(x), int(y)])
cntPoints1.append([x, y])
cv2.drawContours(blackImgShapes, [np.array(cntPoints)], -1, ([255,255,255]), thickness=-1)
x, y, w, h = cv2.boundingRect(np.array(cntPoints))
firstpoint = 0
for poi in np.array(cntPoints1):
if firstpoint == 0:
x2, y2 = poi
p2 = fitz.Point(x2,y2)
# p1 = fitz.Point(x1,y1)
p2=p2*derotationMatrix
shapeePerimeter.append([p2[0],p2[1]])
firstpoint = 1
else:
x1, y1 = poi
p1 = fitz.Point(x1,y1)
# p1 = fitz.Point(x1,y1)
p1=p1*derotationMatrix
# print("P1 = ",p1)
shapeePerimeter.append([p1[0],p1[1]])
shapeePerimeter.append([p2[0],p2[1]])
shapeePerimeter=np.flip(shapeePerimeter,1)
shapeePerimeter=rotate_polygon(shapeePerimeter,rotationangle,rotationOld,width,height)
for poi in np.array(cntPoints1):
x1, y1 = poi
p1 = fitz.Point(x1,y1)
# p1 = fitz.Point(x1,y1)
p1=p1*derotationMatrix
# print("P1 = ",p1)
shapeeArea.append([p1[0],p1[1]])
shapeeArea.append([p2[0],p2[1]])
shapeeArea=np.flip(shapeeArea,1)
shapeeArea=rotate_polygon(shapeeArea,rotationangle,rotationOld,width,height)
tol=0
condition1 = (SimilarAreaDictionary['Area'] >= polygon[1] - tol) & (SimilarAreaDictionary['Area'] <= polygon[1] +tol)
condition2 = (SimilarAreaDictionary['Perimeter'] >= polygon[2] -tol) & (SimilarAreaDictionary['Perimeter'] <= polygon[2] +tol)
combined_condition = condition1 & condition2
# print("combined_condition = ",combined_condition)
if any(combined_condition):
flagcolor = 1
index = np.where(combined_condition)[0][0]
# print(SimilarAreaDictionary.at[index, 'Color'])
NewColors=SimilarAreaDictionary.at[index, 'Color']
else:
flagcolor = 2
NewColors=SimilarAreaDictionary.at[i, 'Color']
# flagcolor = 2
# cv2.drawContours(imgg, [np.array(cntPoints)], -1, (NewColors), thickness=2)
# print("new color = ",NewColors)
# print("New Colors = ",NewColors)
# if img is not None or img.shape[0] != 0 or img.shape[1] != 0:
if(int(NewColors[0])==255 and int(NewColors[1])==255 and int(NewColors[2])==255):
WhiteImgFinal = cv2.bitwise_and(blackImgShapes,imgg)
# print("length = ",WhiteImgFinal.shape[0])
# print("width = ",WhiteImgFinal.shape[1])
flipped=flip(WhiteImgFinal)
# print("Flipped")
# cv2_imshow(flipped)
imgslice = WhiteImgFinal[y:y+h, x:x+w]
# print("length slice = ",imgslice.shape[0])
# print("width slice = ",imgslice.shape[1])
if(imgslice.shape[0] != 0 and imgslice.shape[1] != 0):
flippedSlice=flip(imgslice)
# print("Sliced & Flipped")
# cv2_imshow(flippedSlice)
# Convert flippedSlice to PIL for color extraction
flippedSlice_pil = Image.fromarray(flippedSlice)
# Define patch size for color sampling (e.g., 10x10 pixels)
patch_size = 100
patch_colors = []
# Loop through patches in the image
for i in range(0, flippedSlice_pil.width, patch_size):
for j in range(0, flippedSlice_pil.height, patch_size):
# Crop a patch from the original image
patch = flippedSlice_pil.crop((i, j, i + patch_size, j + patch_size))
patch_colors += patch.getcolors(patch_size * patch_size)
# Calculate the dominant color from all patches
max_count = 0
dominant_color = None
tolerance = 5
black_threshold = 30 # Max RGB value for a color to be considered "black"
white_threshold = 225 # Min RGB value for a color to be considered "white"
for count, color in patch_colors:
# Exclude colors within the black and white ranges
if not (all(c <= black_threshold for c in color) or all(c >= white_threshold for c in color)):
# Update if the current color has a higher count than previous max
if count > max_count:
max_count = count
dominant_color = color
# print("Dominant Color =", dominant_color)
# Append dominant color to ColorCheck and update NewColors
if dominant_color is not None:
ColorCheck.append(dominant_color)
NewColors = None # Initialize NewColors
for color in ColorCheck:
# Check if the current color is within the tolerance
# print("color = ",color)
# print("dominant_color = ",dominant_color)
if (abs(color[0] - dominant_color[0]) < 20 and
abs(color[1] - dominant_color[1]) < 20 and
abs(color[2] - dominant_color[2]) < 20):
NewColors = (color[2], color[1], color[0]) # Set the new color
break
else:
# If no color in ColorCheck meets the tolerance, use the dominant color
NewColors = (dominant_color[2], dominant_color[1], dominant_color[0])
# break
# Avoid appending `dominant_color` again unnecessarily
if NewColors not in ColorCheck:
ColorCheck.append(NewColors)
if flagcolor == 1:
SimilarAreaDictionary.at[index, 'Color'] = NewColors
# # print(f"Updated Color at index {index} with {NewColors}.")
elif flagcolor == 2:
SimilarAreaDictionary.at[i, 'Color'] = NewColors
# print("New Colors = ",NewColors)
cv2.drawContours(imgg, [np.array(cntPoints)], -1, ([NewColors[2],NewColors[1],NewColors[0]]), thickness=3)
start_point1 = shapeePerimeter[0]
end_point1 = shapeePerimeter[1]
start_point2 = shapeePerimeter[0]
end_point2 = shapeePerimeter[-2]
distance1 = calculate_distance(start_point1, end_point1)
distance2 = calculate_distance(start_point2, end_point2)
# Divide the shapePerimeter into two halves
half_index = len(shapeePerimeter) // 2
half1 = shapeePerimeter[1:half_index+1]
half2 = shapeePerimeter[half_index:]
# half1 = shapeePerimeter[1:half_index]
# half2 = shapeePerimeter[half_index:-1]
# Calculate distances for the halves
if len(half1) >= 2:
half1_distance = sum(calculate_distance(half1[i], half1[i + 1]) for i in range(len(half1) - 1))
else:
half1_distance = 0
if len(half2) >= 2:
half2_distance = sum(calculate_distance(half2[i], half2[i + 1]) for i in range(len(half2) - 1))
else:
half2_distance = 0
max_distance = max(distance1, distance2, half1_distance)
if max_distance == distance1:
# Draw the line annotation for distance1
chosen_start = start_point1
chosen_end = end_point1
# annot12 = page2.add_line_annot(chosen_start, chosen_end)
points=[]
points.append(chosen_start)
points.append(chosen_end)
discard = False
# if(points_Of_drawing_Canvas):
# print("Canva points = ",points_Of_drawing_Canvas)
if(points_Of_drawing_Canvas):
Boundingpolygon = np.array(
[(p.x, p.y) for p in points_Of_drawing_Canvas],
dtype=np.float32
)
for x, y in points:
# Check if the point is outside the polygon
result = cv2.pointPolygonTest(Boundingpolygon, (x, y), False)
if result < 0: # < 0 means point is outside
discard = True
break
else:
for point in points:
if not (bxmin <= point[0] <= bxmax and bymin <= point[1] <= bymax):
discard = True
break
# for point in points:
# if not (bxmin <= point[0] <= bxmax and bymin <= point[1] <= bymax):
# discard = True
# break
if not discard:
annot12 = page2.add_polyline_annot(points)
elif max_distance == distance2:
# Draw the line annotation for distance2
chosen_start = start_point2
chosen_end = end_point2
# annot12 = page2.add_line_annot(chosen_start, chosen_end)
points=[]
points.append(chosen_start)
points.append(chosen_end)
# annot12 = page2.add_polyline_annot(points)
points=[]
points.append(chosen_start)
points.append(chosen_end)
discard = False
# print("Canva points = ",points_Of_drawing_Canvas)
if(points_Of_drawing_Canvas):
Boundingpolygon = np.array(
[(p.x, p.y) for p in points_Of_drawing_Canvas],
dtype=np.float32
)
for x, y in points:
# Check if the point is outside the polygon
result = cv2.pointPolygonTest(Boundingpolygon, (x, y), False)
if result < 0: # < 0 means point is outside
discard = True
break
else:
for point in points:
if not (bxmin <= point[0] <= bxmax and bymin <= point[1] <= bymax):
discard = True
break
if not discard:
annot12 = page2.add_polyline_annot(points)
elif max_distance == half1_distance:
# annot12 = page2.add_polyline_annot(half1)
max_pair_distance = 0.0
max_pair_start = None
max_pair_end = None
# 2. Loop through each consecutive pair in half1
for i in range(len(half1) - 1):
p_current = half1[i]
p_next = half1[i + 1]
# 3. Compute distance between these two points
dist = calculate_distance(p_current, p_next)
# 4. Update max if this distance is greater
if dist > max_pair_distance:
max_pair_distance = dist
max_pair_start = p_current
max_pair_end = p_next
# 5. After the loop, max_pair_start and max_pair_end represent
# the two consecutive points with the greatest separation.
if max_pair_start is not None and max_pair_end is not None:
# 6. Draw the line annotation using these two points
# annot12 = page2.add_line_annot(max_pair_start, max_pair_end)
points=[]
points.append(max_pair_start)
points.append(max_pair_end)
discard = False
# print("Canva points = ",points_Of_drawing_Canvas)
if(points_Of_drawing_Canvas):
Boundingpolygon = np.array(
[(p.x, p.y) for p in points_Of_drawing_Canvas],
dtype=np.float32
)
for x, y in points:
# Check if the point is outside the polygon
result = cv2.pointPolygonTest(Boundingpolygon, (x, y), False)
if result < 0: # < 0 means point is outside
discard = True
break
else:
for point in points:
if not (bxmin <= point[0] <= bxmax and bymin <= point[1] <= bymax):
discard = True
break
if not discard:
annot12 = page2.add_polyline_annot(points)
# print(f"Drew line annotation between {max_pair_start} and {max_pair_end}")
else:
# This case only occurs if half1 has fewer than 2 points
print("Not enough points in half1 to compute a line.")
discard = False
# print("Canva points = ",points_Of_drawing_Canvas)
if(points_Of_drawing_Canvas):
Boundingpolygon = np.array(
[(p.x, p.y) for p in points_Of_drawing_Canvas],
dtype=np.float32
)
for x, y in points:
# Check if the point is outside the polygon
result = cv2.pointPolygonTest(Boundingpolygon, (x, y), False)
if result < 0: # < 0 means point is outside
discard = True
break
else:
for point in points:
if not (bxmin <= point[0] <= bxmax and bymin <= point[1] <= bymax):
discard = True
break
if not discard:
annot12.set_border(width=0.8)
annot12.set_colors(stroke=(int(NewColors[0])/255,int(NewColors[1])/255,int(NewColors[2])/255))
# annot12.set_info(content=str(polygon[2])+' m',subject='Perimeter Measurement', title="ADR Team")
annot12.set_info(subject='Perimeter Measurement',content=str(polygon[2])+' m')
annot12.set_opacity(0.8)
annot12.update()
i += 1
alpha = 0.8 # Transparency factor.
page2.set_rotation(rotationOld)
Correct_img=flip(imgg)
image_new1 = cv2.addWeighted(Correct_img, alpha, img, 1 - alpha, 0)
SimilarAreaDictionary = SimilarAreaDictionary.fillna(' ')
# Define white color to filter out
white_color = (255, 255, 255)
# Delete rows where 'Guess' equals white_color
SimilarAreaDictionary = SimilarAreaDictionary[SimilarAreaDictionary['Color'] != white_color]
# Reset the index to update row numbering
SimilarAreaDictionary.reset_index(drop=True, inplace=True)
grouped_df = SimilarAreaDictionary.groupby('Color').agg({
'Guess': 'first',
'Occurences': 'sum', # Sum of occurrences for each color
'Area':'first',
'Total Area': 'sum', # Sum of areas for each color
'Perimeter':'first',
'Total Perimeter': 'sum', # Sum of perimeters for each color
'Length':'first',
'Total Length': 'sum', # Sum of lengths for each color
'Texts': 'first', # Keep the first occurrence of 'Texts'
'Comments': 'first' # Keep the first occurrence of 'Comments'
}).reset_index()
# doc.save(OutputPdfStage1)
# OutputPdfStage2=adjustannotations(OutputPdfStage1,text_with_positions)
modified_pdf_data = doc.tobytes()
OutputPdfStage2 , annotations_data=adjustannotations(modified_pdf_data,text_with_positions,CollectedColors)
if (Thickness):
threshold = round((float(Thickness) * float(dxfratio) ),1)
cleaned_list = clean_annotations(annotations_data, threshold)
else:
cleaned_list = clean_annotations(annotations_data, threshold=10)
allvertices = cleaned_list
# PerimeterVertices = XMLPerimeter
#Example Color : this is in RGB normalized format as for e.g.: 200/255 for r g b
hatchcolorR= '0'
hatchcolorG= '1'
hatchcolorB= '1'
# Define templates with placeholder {w} instead of hardcoded LINEWIDTH
LinestyleTemplates = {
'Solid': '<</W {w}/S/S/Type/Border>>',
'Dashed1':'<</W {w}/S/D/D[2 2]/Type/Border>>',
'Dashed2': '<</W {w}/S/D/D[3 3]/Type/Border>>',
'Dashed3': '<</W {w}/S/D/D[4 4]/Type/Border>>',
'Dashed4': '<</W {w}/S/D/D[4 3 2 3]/Type/Border>>',
'Dashed5': '<</W {w}/S/D/D[4 3 16 3]/Type/Border>>',
'Dashed6': '<</W {w}/S/D/D[8 4 4 4]/Type/Border>>'
}
#/BS<</W 1/S/D/D[4 4]/Type/Border>>
HatchFunctions = {
'None':'',
'Brick': setBrickHatch,
'DiagonalBrick':setDiagonalBrickHatch,
'Horizontal':setHorizontalHatch,
'Vertical':setVerticalHatch,
'DiagonalDown':setDiagonalDownHatch,
'DiagonalUp':setDiagonalUpHatch,
'Grid': setGridHatch,
'Weave':setWeaveHatch,
'10Dots':set10DotsHatch,
'20Dots':set20DotsHatch,
'30Dots':set30DotsHatch
}
#Area and perimeter numbers example
area = 20
perimeter = 30
import colorsys
annotations=[]
for shapeinvertices in allvertices:
rn=shapeinvertices[3][0]/255
gn=shapeinvertices[3][1]/255
bn=shapeinvertices[3][2]/255
h, s, v = colorsys.rgb_to_hsv(rn, gn, bn)
# snap to full saturation, 50% brightness
s2, v2 = 0.6, 0.9
# back to RGB
r2, g2, b2 = colorsys.hsv_to_rgb(h, s2, v2)
R=str(r2)
G=str(g2)
B=str(b2)
if shapeinvertices[6]:
annotations.append(
{
'vertices': shapeinvertices[0], # [[x,y],[x1,y1],[....]] position of ur markup
'text': str(shapeinvertices[2])+' m',
'author': 'ADR',
'custom_data': {'Specification':shapeinvertices[5]},#identify custom colums here as( Column name: Text to add )
'type_internal': 'Bluebeam.PDF.Annotations.AnnotationMeasurePerimeter',
'subject': 'Perimeter Measurement',
'label':shapeinvertices[6],
'opacity': '0.7',#opacity of ur shape fill
'color': R+ ' '+G + ' '+B,# normalized (RGB --> R/255 G/255 B/255)
'linestyle': LinestyleTemplates['Dashed6'].format(w=2) # LineStyles as in BB ,this w is the linewidth
}
)
else:
annotations.append(
{
'vertices': shapeinvertices[0], # [[x,y],[x1,y1],[....]] position of ur markup
'text': str(shapeinvertices[2])+' m',
'author': 'ADR',
'custom_data': {'Specification':shapeinvertices[5]},#identify custom colums here as( Column name: Text to add )
'type_internal': 'Bluebeam.PDF.Annotations.AnnotationMeasurePerimeter',
'subject': 'Perimeter Measurement',
'label':shapeinvertices[4],
'opacity': '0.7',#opacity of ur shape fill
'color': R+ ' '+G + ' '+B,# normalized (RGB --> R/255 G/255 B/255)
'linestyle': LinestyleTemplates['Dashed6'].format(w=2) # LineStyles as in BB ,this w is the linewidth
}
)
column_order = ['Specification'] #specify here the custom columns in order
# print(bax_annotations)
#replace with ur pdf width and height variables
pdfWidth=1684
pdfHeight=2384
# save_multiple_annotations_bax(
# bax_annotations, 'Area_Perimeter_OMAR_output.bax', column_order, pdfWidth, pdfHeight
# )
bax_xml=save_multiple_annotations_bax(
annotations, '2552 Page 1.bax', column_order, pdfWidth, pdfHeight
)
from xml.etree.ElementTree import Element, SubElement, tostring
def generate_bluebeam_columns_raw(column_names):
"""
Generate BluebeamUserDefinedColumns XML as raw string, without headers or extra fields.
"""
root = Element("BluebeamUserDefinedColumns")
for idx, name in enumerate(column_names):
item = SubElement(root, "BSIColumnItem", Index=str(idx), Subtype="Text")
SubElement(item, "Name").text = name
SubElement(item, "DisplayOrder").text = str(idx)
SubElement(item, "Deleted").text = "False"
SubElement(item, "Multiline").text = "False"
# Convert to string and decode raw bytes
return tostring(root, encoding="unicode", method="xml")
column_xml = generate_bluebeam_columns_raw(column_order)
# with open("2552 Page 1.xml", "w", encoding="utf-8") as f:
# f.write(column_xml)
# print(column_xml)
if pdf_content:
latestimg,pix=pdftoimg(OutputPdfStage2,pdf_content)
else:
latestimg,pix=pdftoimg(OutputPdfStage2)
doc2 =fitz.open('pdf',OutputPdfStage2)
if pdf_content:
gc,spreadsheet_service,spreadsheetId, spreadsheet_url , namepathArr=google_sheet_Legend.legendGoogleSheets(grouped_df , pdfname,pdfpath,pdf_content)
else:
gc,spreadsheet_service,spreadsheetId, spreadsheet_url , namepathArr=google_sheet_Legend.legendGoogleSheets(grouped_df , pdfname,pdfpath)
list1=pd.DataFrame(columns=['content', 'id', 'subject','color'])
# for page in doc:
for page in doc2:
# Iterate through annotations on the page
for annot in page.annots():
# Get the color of the annotation
annot_color = annot.colors
if annot_color is not None:
# annot_color is a dictionary with 'stroke' and 'fill' keys
stroke_color = annot_color.get('stroke') # Border color
fill_color = annot_color.get('fill') # Fill color
if fill_color:
v='fill'
# print('fill')
if stroke_color:
v='stroke'
x,y,z=int(annot_color.get(v)[0]*255),int(annot_color.get(v)[1]*255),int(annot_color.get(v)[2]*255)
list1.loc[len(list1)] =[annot.info['content'],annot.info['id'],annot.info['subject'],[x,y,z]]
print('LISTTT',list1)
return doc2,latestimg, SimilarAreaDictionary ,spreadsheetId, spreadsheet_url , namepathArr , list1,hatched_areas, bax_xml, column_xml
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