deploying_3_3.py

# -*- coding: utf-8 -*-
"""Deploying 3.2

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1HEw0DdXhDcxtJN1pjs7bCnlhr-wXX3-m
"""

# pip install pymupdf

# pip install ezdxf

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


from ctypes import sizeof
# -*- 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
"""

# pip install ezdxf[draw]

# pip install --upgrade ezdxf

# pip install pymupdf #==1.22.5

# pip install PyPDF2

# pip install ezdxf scipy

"""## Imports"""
import xml.etree.ElementTree as ET
from PyPDF2 import PdfReader, PdfWriter
from PyPDF2.generic import TextStringObject, NameObject, ArrayObject, FloatObject
from PyPDF2.generic import NameObject, TextStringObject, DictionaryObject, FloatObject, ArrayObject

from typing import NewType
from ctypes import sizeof

from PyPDF2 import PdfReader, PdfWriter
from PyPDF2.generic import NameObject, TextStringObject, FloatObject, DictionaryObject

import numpy as np
import cv2
from matplotlib import pyplot as plt
import math
from PIL import Image  , ImageDraw, ImageFont , ImageColor
import fitz
import ezdxf as ez
import sys
from ezdxf import units
# from google.colab.patches import cv2_imshow
from ezdxf.math import OCS, Matrix44, Vec3
import ezdxf
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from shapely.geometry import Point, Polygon as ShapelyPolygon
from ezdxf.math import Vec2
import random
import pandas as pd
# import google_sheet_Legend
import tsadropboxretrieval
from ezdxf import bbox
from math import sin, cos, radians
import google_sheet_Legend
from PyPDF2 import PdfReader
from io import BytesIO

from ezdxf.colors import aci2rgb
from collections import Counter

from math import isclose

from typing import List, Tuple, Any, Set
from shapely.geometry import Polygon, MultiPolygon, GeometryCollection
from shapely.ops import unary_union

import random
import string
import zlib
import base64
import datetime
import uuid
from xml.etree.ElementTree import Element, SubElement, tostring, ElementTree
from xml.dom.minidom import parseString

import colorsys
from xml.etree.ElementTree import Element, SubElement, tostring

import re

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
  {fillcolor} rg 0 0 18 18 re f {strokecolor} RG 1 w 0 -0.5 m 0.2761424 -0.5 0.5 -0.2761424 0.5 0 c 0.5 0.2761424 0.2761424 0.5 0 0.5 c -0.2761424 0.5 -0.5 0.2761424 -0.5 0 c -0.5 -0.2761424 -0.2761424 -0.5 0 -0.5 c h 0 4 m 0.2761424 4 0.5 4.223857 0.5 4.5 c 0.5 4.776143 0.2761424 5 0 5 c -0.2761424 5 -0.5 4.776143 -0.5 4.5 c -0.5 4.223857 -0.2761424 4 0 4 c h 0 8.5 m 0.2761424 8.5 0.5 8.723858 0.5 9 c 0.5 9.276142 0.2761424 9.5 0 9.5 c -0.2761424 9.5 -0.5 9.276142 -0.5 9 c -0.5 8.723858 -0.2761424 8.5 0 8.5 c h 0 13 m 0.2761424 13 0.5 13.22386 0.5 13.5 c 0.5 13.77614 0.2761424 14 0 14 c -0.2761424 14 -0.5 13.77614 -0.5 13.5 c -0.5 13.22386 -0.2761424 13 0 13 c h 0 17.5 m 0.2761424 17.5 0.5 17.72386 0.5 18 c 0.5 18.27614 0.2761424 18.5 0 18.5 c -0.2761424 18.5 -0.5 18.27614 -0.5 18 c -0.5 17.72386 -0.2761424 17.5 0 17.5 c h 4.5 -0.5 m 4.776143 -0.5 5 -0.2761424 5 0 c 5 0.2761424 4.776143 0.5 4.5 0.5 c 4.223857 0.5 4 0.2761424 4 0 c 4 -0.2761424 4.223857 -0.5 4.5 -0.5 c h 4.5 4 m 4.776143 4 5 4.223857 5 4.5 c 5 4.776143 4.776143 5 4.5 5 c 4.223857 5 4 4.776143 4 4.5 c 4 4.223857 4.223857 4 4.5 4 c h 4.5 8.5 m 4.776143 8.5 5 8.723858 5 9 c 5 9.276142 4.776143 9.5 4.5 9.5 c 4.223857 9.5 4 9.276142 4 9 c 4 8.723858 4.223857 8.5 4.5 8.5 c h 4.5 13 m 4.776143 13 5 13.22386 5 13.5 c 5 13.77614 4.776143 14 4.5 14 c 4.223857 14 4 13.77614 4 13.5 c 4 13.22386 4.223857 13 4.5 13 c h 4.5 17.5 m 4.776143 17.5 5 17.72386 5 18 c 5 18.27614 4.776143 18.5 4.5 18.5 c 4.223857 18.5 4 18.27614 4 18 c 4 17.72386 4.223857 17.5 4.5 17.5 c h 9 -0.5 m 9.276142 -0.5 9.5 -0.2761424 9.5 0 c 9.5 0.2761424 9.276142 0.5 9 0.5 c 8.723858 0.5 8.5 0.2761424 8.5 0 c 8.5 -0.2761424 8.723858 -0.5 9 -0.5 c h 9 4 m 9.276142 4 9.5 4.223857 9.5 4.5 c 9.5 4.776143 9.276142 5 9 5 c 8.723858 5 8.5 4.776143 8.5 4.5 c 8.5 4.223857 8.723858 4 9 4 c h 9 8.5 m 9.276142 8.5 9.5 8.723858 9.5 9 c 9.5 9.276142 9.276142 9.5 9 9.5 c 8.723858 9.5 8.5 9.276142 8.5 9 c 8.5 8.723858 8.723858 8.5 9 8.5 c h 9 13 m 9.276142 13 9.5 13.22386 9.5 13.5 c 9.5 13.77614 9.276142 14 9 14 c 8.723858 14 8.5 13.77614 8.5 13.5 c 8.5 13.22386 8.723858 13 9 13 c h 9 17.5 m 9.276142 17.5 9.5 17.72386 9.5 18 c 9.5 18.27614 9.276142 18.5 9 18.5 c 8.723858 18.5 8.5 18.27614 8.5 18 c 8.5 17.72386 8.723858 17.5 9 17.5 c h 13.5 -0.5 m 13.77614 -0.5 14 -0.2761424 14 0 c 14 0.2761424 13.77614 0.5 13.5 0.5 c 13.22386 0.5 13 0.2761424 13 0 c 13 -0.2761424 13.22386 -0.5 13.5 -0.5 c h 13.5 4 m 13.77614 4 14 4.223857 14 4.5 c 14 4.776143 13.77614 5 13.5 5 c 13.22386 5 13 4.776143 13 4.5 c 13 4.223857 13.22386 4 13.5 4 c h 13.5 8.5 m 13.77614 8.5 14 8.723858 14 9 c 14 9.276142 13.77614 9.5 13.5 9.5 c 13.22386 9.5 13 9.276142 13 9 c 13 8.723858 13.22386 8.5 13.5 8.5 c h 13.5 13 m 13.77614 13 14 13.22386 14 13.5 c 14 13.77614 13.77614 14 13.5 14 c 13.22386 14 13 13.77614 13 13.5 c 13 13.22386 13.22386 13 13.5 13 c h 13.5 17.5 m 13.77614 17.5 14 17.72386 14 18 c 14 18.27614 13.77614 18.5 13.5 18.5 c 13.22386 18.5 13 18.27614 13 18 c 13 17.72386 13.22386 17.5 13.5 17.5 c h 18 -0.5 m 18.27614 -0.5 18.5 -0.2761424 18.5 0 c 18.5 0.2761424 18.27614 0.5 18 0.5 c 17.72386 0.5 17.5 0.2761424 17.5 0 c 17.5 -0.2761424 17.72386 -0.5 18 -0.5 c h 18 4 m 18.27614 4 18.5 4.223857 18.5 4.5 c 18.5 4.776143 18.27614 5 18 5 c 17.72386 5 17.5 4.776143 17.5 4.5 c 17.5 4.223857 17.72386 4 18 4 c h 18 8.5 m 18.27614 8.5 18.5 8.723858 18.5 9 c 18.5 9.276142 18.27614 9.5 18 9.5 c 17.72386 9.5 17.5 9.276142 17.5 9 c 17.5 8.723858 17.72386 8.5 18 8.5 c h 18 13 m 18.27614 13 18.5 13.22386 18.5 13.5 c 18.5 13.77614 18.27614 14 18 14 c 17.72386 14 17.5 13.77614 17.5 13.5 c 17.5 13.22386 17.72386 13 18 13 c h 18 17.5 m 18.27614 17.5 18.5 17.72386 18.5 18 c 18.5 18.27614 18.27614 18.5 18 18.5 c 17.72386 18.5 17.5 18.27614 17.5 18 c 17.5 17.72386 17.72386 17.5 18 17.5 c h 2.25 1.75 m 2.526142 1.75 2.75 1.973858 2.75 2.25 c 2.75 2.526142 2.526142 2.75 2.25 2.75 c 1.973858 2.75 1.75 2.526142 1.75 2.25 c 1.75 1.973858 1.973858 1.75 2.25 1.75 c h 2.25 6.25 m 2.526142 6.25 2.75 6.473857 2.75 6.75 c 2.75 7.026143 2.526142 7.25 2.25 7.25 c 1.973858 7.25 1.75 7.026143 1.75 6.75 c 1.75 6.473857 1.973858 6.25 2.25 6.25 c h 2.25 10.75 m 2.526142 10.75 2.75 10.97386 2.75 11.25 c 2.75 11.52614 2.526142 11.75 2.25 11.75 c 1.973858 11.75 1.75 11.52614 1.75 11.25 c 1.75 10.97386 1.973858 10.75 2.25 10.75 c h 2.25 15.25 m 2.526142 15.25 2.75 15.47386 2.75 15.75 c 2.75 16.02614 2.526142 16.25 2.25 16.25 c 1.973858 16.25 1.75 16.02614 1.75 15.75 c 1.75 15.47386 1.973858 15.25 2.25 15.25 c h 6.75 1.75 m 7.026143 1.75 7.25 1.973858 7.25 2.25 c 7.25 2.526142 7.026143 2.75 6.75 2.75 c 6.473857 2.75 6.25 2.526142 6.25 2.25 c 6.25 1.973858 6.473857 1.75 6.75 1.75 c h 6.75 6.25 m 7.026143 6.25 7.25 6.473857 7.25 6.75 c 7.25 7.026143 7.026143 7.25 6.75 7.25 c 6.473857 7.25 6.25 7.026143 6.25 6.75 c 6.25 6.473857 6.473857 6.25 6.75 6.25 c h 6.75 10.75 m 7.026143 10.75 7.25 10.97386 7.25 11.25 c 7.25 11.52614 7.026143 11.75 6.75 11.75 c 6.473857 11.75 6.25 11.52614 6.25 11.25 c 6.25 10.97386 6.473857 10.75 6.75 10.75 c h 6.75 15.25 m 7.026143 15.25 7.25 15.47386 7.25 15.75 c 7.25 16.02614 7.026143 16.25 6.75 16.25 c 6.473857 16.25 6.25 16.02614 6.25 15.75 c 6.25 15.47386 6.473857 15.25 6.75 15.25 c h 11.25 1.75 m 11.52614 1.75 11.75 1.973858 11.75 2.25 c 11.75 2.526142 11.52614 2.75 11.25 2.75 c 10.97386 2.75 10.75 2.526142 10.75 2.25 c 10.75 1.973858 10.97386 1.75 11.25 1.75 c h 11.25 6.25 m 11.52614 6.25 11.75 6.473857 11.75 6.75 c 11.75 7.026143 11.52614 7.25 11.25 7.25 c 10.97386 7.25 10.75 7.026143 10.75 6.75 c 10.75 6.473857 10.97386 6.25 11.25 6.25 c h 11.25 10.75 m 11.52614 10.75 11.75 10.97386 11.75 11.25 c 11.75 11.52614 11.52614 11.75 11.25 11.75 c 10.97386 11.75 10.75 11.52614 10.75 11.25 c 10.75 10.97386 10.97386 10.75 11.25 10.75 c h 11.25 15.25 m 11.52614 15.25 11.75 15.47386 11.75 15.75 c 11.75 16.02614 11.52614 16.25 11.25 16.25 c 10.97386 16.25 10.75 16.02614 10.75 15.75 c 10.75 15.47386 10.97386 15.25 11.25 15.25 c h 15.75 1.75 m 16.02614 1.75 16.25 1.973858 16.25 2.25 c 16.25 2.526142 16.02614 2.75 15.75 2.75 c 15.47386 2.75 15.25 2.526142 15.25 2.25 c 15.25 1.973858 15.47386 1.75 15.75 1.75 c h 15.75 6.25 m 16.02614 6.25 16.25 6.473857 16.25 6.75 c 16.25 7.026143 16.02614 7.25 15.75 7.25 c 15.47386 7.25 15.25 7.026143 15.25 6.75 c 15.25 6.473857 15.47386 6.25 15.75 6.25 c h 15.75 10.75 m 16.02614 10.75 16.25 10.97386 16.25 11.25 c 16.25 11.52614 16.02614 11.75 15.75 11.75 c 15.47386 11.75 15.25 11.52614 15.25 11.25 c 15.25 10.97386 15.47386 10.75 15.75 10.75 c h 15.75 15.25 m 16.02614 15.25 16.25 15.47386 16.25 15.75 c 16.25 16.02614 16.02614 16.25 15.75 16.25 c 15.47386 16.25 15.25 16.02614 15.25 15.75 c 15.25 15.47386 15.47386 15.25 15.75 15.25 c h
  {strokecolor} rg f
  endstream'''
,
'20Dots':'''<</Length 13441/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 0 -0.5 m 0.2761424 -0.5 0.5 -0.2761424 0.5 0 c 0.5 0.2761424 0.2761424 0.5 0 0.5 c -0.2761424 0.5 -0.5 0.2761424 -0.5 0 c -0.5 -0.2761424 -0.2761424 -0.5 0 -0.5 c h 0 2.500001 m 0.2761424 2.500001 0.5 2.723858 0.5 3.000001 c 0.5 3.276143 0.2761424 3.500001 0 3.500001 c -0.2761424 3.500001 -0.5 3.276143 -0.5 3.000001 c -0.5 2.723858 -0.2761424 2.500001 0 2.500001 c h 0 5.5 m 0.2761424 5.5 0.5 5.723857 0.5 6 c 0.5 6.276142 0.2761424 6.5 0 6.5 c -0.2761424 6.5 -0.5 6.276142 -0.5 6 c -0.5 5.723857 -0.2761424 5.5 0 5.5 c h 0 8.5 m 0.2761424 8.5 0.5 8.723858 0.5 9 c 0.5 9.276142 0.2761424 9.5 0 9.5 c -0.2761424 9.5 -0.5 9.276142 -0.5 9 c -0.5 8.723858 -0.2761424 8.5 0 8.5 c h 0 11.5 m 0.2761424 11.5 0.5 11.72386 0.5 12 c 0.5 12.27614 0.2761424 12.5 0 12.5 c -0.2761424 12.5 -0.5 12.27614 -0.5 12 c -0.5 11.72386 -0.2761424 11.5 0 11.5 c h 0 14.5 m 0.2761424 14.5 0.5 14.72386 0.5 15 c 0.5 15.27614 0.2761424 15.5 0 15.5 c -0.2761424 15.5 -0.5 15.27614 -0.5 15 c -0.5 14.72386 -0.2761424 14.5 0 14.5 c h 0 17.5 m 0.2761424 17.5 0.5 17.72386 0.5 18 c 0.5 18.27614 0.2761424 18.5 0 18.5 c -0.2761424 18.5 -0.5 18.27614 -0.5 18 c -0.5 17.72386 -0.2761424 17.5 0 17.5 c h 3.000001 -0.5 m 3.276143 -0.5 3.500001 -0.2761424 3.500001 0 c 3.500001 0.2761424 3.276143 0.5 3.000001 0.5 c 2.723858 0.5 2.500001 0.2761424 2.500001 0 c 2.500001 -0.2761424 2.723858 -0.5 3.000001 -0.5 c h 3.000001 2.500001 m 3.276143 2.500001 3.500001 2.723858 3.500001 3.000001 c 3.500001 3.276143 3.276143 3.500001 3.000001 3.500001 c 2.723858 3.500001 2.500001 3.276143 2.500001 3.000001 c 2.500001 2.723858 2.723858 2.500001 3.000001 2.500001 c h 3.000001 5.5 m 3.276143 5.5 3.500001 5.723857 3.500001 6 c 3.500001 6.276142 3.276143 6.5 3.000001 6.5 c 2.723858 6.5 2.500001 6.276142 2.500001 6 c 2.500001 5.723857 2.723858 5.5 3.000001 5.5 c h 3.000001 8.5 m 3.276143 8.5 3.500001 8.723858 3.500001 9 c 3.500001 9.276142 3.276143 9.5 3.000001 9.5 c 2.723858 9.5 2.500001 9.276142 2.500001 9 c 2.500001 8.723858 2.723858 8.5 3.000001 8.5 c h 3.000001 11.5 m 3.276143 11.5 3.500001 11.72386 3.500001 12 c 3.500001 12.27614 3.276143 12.5 3.000001 12.5 c 2.723858 12.5 2.500001 12.27614 2.500001 12 c 2.500001 11.72386 2.723858 11.5 3.000001 11.5 c h 3.000001 14.5 m 3.276143 14.5 3.500001 14.72386 3.500001 15 c 3.500001 15.27614 3.276143 15.5 3.000001 15.5 c 2.723858 15.5 2.500001 15.27614 2.500001 15 c 2.500001 14.72386 2.723858 14.5 3.000001 14.5 c h 3.000001 17.5 m 3.276143 17.5 3.500001 17.72386 3.500001 18 c 3.500001 18.27614 3.276143 18.5 3.000001 18.5 c 2.723858 18.5 2.500001 18.27614 2.500001 18 c 2.500001 17.72386 2.723858 17.5 3.000001 17.5 c h 6 -0.5 m 6.276142 -0.5 6.5 -0.2761424 6.5 0 c 6.5 0.2761424 6.276142 0.5 6 0.5 c 5.723857 0.5 5.5 0.2761424 5.5 0 c 5.5 -0.2761424 5.723857 -0.5 6 -0.5 c h 6 2.500001 m 6.276142 2.500001 6.5 2.723858 6.5 3.000001 c 6.5 3.276143 6.276142 3.500001 6 3.500001 c 5.723857 3.500001 5.5 3.276143 5.5 3.000001 c 5.5 2.723858 5.723857 2.500001 6 2.500001 c h 6 5.5 m 6.276142 5.5 6.5 5.723857 6.5 6 c 6.5 6.276142 6.276142 6.5 6 6.5 c 5.723857 6.5 5.5 6.276142 5.5 6 c 5.5 5.723857 5.723857 5.5 6 5.5 c h 6 8.5 m 6.276142 8.5 6.5 8.723858 6.5 9 c 6.5 9.276142 6.276142 9.5 6 9.5 c 5.723857 9.5 5.5 9.276142 5.5 9 c 5.5 8.723858 5.723857 8.5 6 8.5 c h 6 11.5 m 6.276142 11.5 6.5 11.72386 6.5 12 c 6.5 12.27614 6.276142 12.5 6 12.5 c 5.723857 12.5 5.5 12.27614 5.5 12 c 5.5 11.72386 5.723857 11.5 6 11.5 c h 6 14.5 m 6.276142 14.5 6.5 14.72386 6.5 15 c 6.5 15.27614 6.276142 15.5 6 15.5 c 5.723857 15.5 5.5 15.27614 5.5 15 c 5.5 14.72386 5.723857 14.5 6 14.5 c h 6 17.5 m 6.276142 17.5 6.5 17.72386 6.5 18 c 6.5 18.27614 6.276142 18.5 6 18.5 c 5.723857 18.5 5.5 18.27614 5.5 18 c 5.5 17.72386 5.723857 17.5 6 17.5 c h 9 -0.5 m 9.276142 -0.5 9.5 -0.2761424 9.5 0 c 9.5 0.2761424 9.276142 0.5 9 0.5 c 8.723858 0.5 8.5 0.2761424 8.5 0 c 8.5 -0.2761424 8.723858 -0.5 9 -0.5 c h 9 2.500001 m 9.276142 2.500001 9.5 2.723858 9.5 3.000001 c 9.5 3.276143 9.276142 3.500001 9 3.500001 c 8.723858 3.500001 8.5 3.276143 8.5 3.000001 c 8.5 2.723858 8.723858 2.500001 9 2.500001 c h 9 5.5 m 9.276142 5.5 9.5 5.723857 9.5 6 c 9.5 6.276142 9.276142 6.5 9 6.5 c 8.723858 6.5 8.5 6.276142 8.5 6 c 8.5 5.723857 8.723858 5.5 9 5.5 c h 9 8.5 m 9.276142 8.5 9.5 8.723858 9.5 9 c 9.5 9.276142 9.276142 9.5 9 9.5 c 8.723858 9.5 8.5 9.276142 8.5 9 c 8.5 8.723858 8.723858 8.5 9 8.5 c h 9 11.5 m 9.276142 11.5 9.5 11.72386 9.5 12 c 9.5 12.27614 9.276142 12.5 9 12.5 c 8.723858 12.5 8.5 12.27614 8.5 12 c 8.5 11.72386 8.723858 11.5 9 11.5 c h 9 14.5 m 9.276142 14.5 9.5 14.72386 9.5 15 c 9.5 15.27614 9.276142 15.5 9 15.5 c 8.723858 15.5 8.5 15.27614 8.5 15 c 8.5 14.72386 8.723858 14.5 9 14.5 c h 9 17.5 m 9.276142 17.5 9.5 17.72386 9.5 18 c 9.5 18.27614 9.276142 18.5 9 18.5 c 8.723858 18.5 8.5 18.27614 8.5 18 c 8.5 17.72386 8.723858 17.5 9 17.5 c h 12 -0.5 m 12.27614 -0.5 12.5 -0.2761424 12.5 0 c 12.5 0.2761424 12.27614 0.5 12 0.5 c 11.72386 0.5 11.5 0.2761424 11.5 0 c 11.5 -0.2761424 11.72386 -0.5 12 -0.5 c h 12 2.500001 m 12.27614 2.500001 12.5 2.723858 12.5 3.000001 c 12.5 3.276143 12.27614 3.500001 12 3.500001 c 11.72386 3.500001 11.5 3.276143 11.5 3.000001 c 11.5 2.723858 11.72386 2.500001 12 2.500001 c h 12 5.5 m 12.27614 5.5 12.5 5.723857 12.5 6 c 12.5 6.276142 12.27614 6.5 12 6.5 c 11.72386 6.5 11.5 6.276142 11.5 6 c 11.5 5.723857 11.72386 5.5 12 5.5 c h 12 8.5 m 12.27614 8.5 12.5 8.723858 12.5 9 c 12.5 9.276142 12.27614 9.5 12 9.5 c 11.72386 9.5 11.5 9.276142 11.5 9 c 11.5 8.723858 11.72386 8.5 12 8.5 c h 12 11.5 m 12.27614 11.5 12.5 11.72386 12.5 12 c 12.5 12.27614 12.27614 12.5 12 12.5 c 11.72386 12.5 11.5 12.27614 11.5 12 c 11.5 11.72386 11.72386 11.5 12 11.5 c h 12 14.5 m 12.27614 14.5 12.5 14.72386 12.5 15 c 12.5 15.27614 12.27614 15.5 12 15.5 c 11.72386 15.5 11.5 15.27614 11.5 15 c 11.5 14.72386 11.72386 14.5 12 14.5 c h 12 17.5 m 12.27614 17.5 12.5 17.72386 12.5 18 c 12.5 18.27614 12.27614 18.5 12 18.5 c 11.72386 18.5 11.5 18.27614 11.5 18 c 11.5 17.72386 11.72386 17.5 12 17.5 c h 15 -0.5 m 15.27614 -0.5 15.5 -0.2761424 15.5 0 c 15.5 0.2761424 15.27614 0.5 15 0.5 c 14.72386 0.5 14.5 0.2761424 14.5 0 c 14.5 -0.2761424 14.72386 -0.5 15 -0.5 c h 15 2.500001 m 15.27614 2.500001 15.5 2.723858 15.5 3.000001 c 15.5 3.276143 15.27614 3.500001 15 3.500001 c 14.72386 3.500001 14.5 3.276143 14.5 3.000001 c 14.5 2.723858 14.72386 2.500001 15 2.500001 c h 15 5.5 m 15.27614 5.5 15.5 5.723857 15.5 6 c 15.5 6.276142 15.27614 6.5 15 6.5 c 14.72386 6.5 14.5 6.276142 14.5 6 c 14.5 5.723857 14.72386 5.5 15 5.5 c h 15 8.5 m 15.27614 8.5 15.5 8.723858 15.5 9 c 15.5 9.276142 15.27614 9.5 15 9.5 c 14.72386 9.5 14.5 9.276142 14.5 9 c 14.5 8.723858 14.72386 8.5 15 8.5 c h 15 11.5 m 15.27614 11.5 15.5 11.72386 15.5 12 c 15.5 12.27614 15.27614 12.5 15 12.5 c 14.72386 12.5 14.5 12.27614 14.5 12 c 14.5 11.72386 14.72386 11.5 15 11.5 c h 15 14.5 m 15.27614 14.5 15.5 14.72386 15.5 15 c 15.5 15.27614 15.27614 15.5 15 15.5 c 14.72386 15.5 14.5 15.27614 14.5 15 c 14.5 14.72386 14.72386 14.5 15 14.5 c h 15 17.5 m 15.27614 17.5 15.5 17.72386 15.5 18 c 15.5 18.27614 15.27614 18.5 15 18.5 c 14.72386 18.5 14.5 18.27614 14.5 18 c 14.5 17.72386 14.72386 17.5 15 17.5 c h 18 -0.5 m 18.27614 -0.5 18.5 -0.2761424 18.5 0 c 18.5 0.2761424 18.27614 0.5 18 0.5 c 17.72386 0.5 17.5 0.2761424 17.5 0 c 17.5 -0.2761424 17.72386 -0.5 18 -0.5 c h 18 2.500001 m 18.27614 2.500001 18.5 2.723858 18.5 3.000001 c 18.5 3.276143 18.27614 3.500001 18 3.500001 c 17.72386 3.500001 17.5 3.276143 17.5 3.000001 c 17.5 2.723858 17.72386 2.500001 18 2.500001 c h 18 5.5 m 18.27614 5.5 18.5 5.723857 18.5 6 c 18.5 6.276142 18.27614 6.5 18 6.5 c 17.72386 6.5 17.5 6.276142 17.5 6 c 17.5 5.723857 17.72386 5.5 18 5.5 c h 18 8.5 m 18.27614 8.5 18.5 8.723858 18.5 9 c 18.5 9.276142 18.27614 9.5 18 9.5 c 17.72386 9.5 17.5 9.276142 17.5 9 c 17.5 8.723858 17.72386 8.5 18 8.5 c h 18 11.5 m 18.27614 11.5 18.5 11.72386 18.5 12 c 18.5 12.27614 18.27614 12.5 18 12.5 c 17.72386 12.5 17.5 12.27614 17.5 12 c 17.5 11.72386 17.72386 11.5 18 11.5 c h 18 14.5 m 18.27614 14.5 18.5 14.72386 18.5 15 c 18.5 15.27614 18.27614 15.5 18 15.5 c 17.72386 15.5 17.5 15.27614 17.5 15 c 17.5 14.72386 17.72386 14.5 18 14.5 c h 18 17.5 m 18.27614 17.5 18.5 17.72386 18.5 18 c 18.5 18.27614 18.27614 18.5 18 18.5 c 17.72386 18.5 17.5 18.27614 17.5 18 c 17.5 17.72386 17.72386 17.5 18 17.5 c h 1.5 1 m 1.776143 1 2 1.223858 2 1.5 c 2 1.776143 1.776143 2 1.5 2 c 1.223858 2 1 1.776143 1 1.5 c 1 1.223858 1.223858 1 1.5 1 c h 1.5 4 m 1.776143 4 2 4.223857 2 4.5 c 2 4.776143 1.776143 5 1.5 5 c 1.223858 5 1 4.776143 1 4.5 c 1 4.223857 1.223858 4 1.5 4 c h 1.5 7 m 1.776143 7 2 7.223858 2 7.5 c 2 7.776143 1.776143 8 1.5 8 c 1.223858 8 1 7.776143 1 7.5 c 1 7.223858 1.223858 7 1.5 7 c h 1.5 10 m 1.776143 10 2 10.22386 2 10.5 c 2 10.77614 1.776143 11 1.5 11 c 1.223858 11 1 10.77614 1 10.5 c 1 10.22386 1.223858 10 1.5 10 c h 1.5 13 m 1.776143 13 2 13.22386 2 13.5 c 2 13.77614 1.776143 14 1.5 14 c 1.223858 14 1 13.77614 1 13.5 c 1 13.22386 1.223858 13 1.5 13 c h 1.5 16 m 1.776143 16 2 16.22386 2 16.5 c 2 16.77614 1.776143 17 1.5 17 c 1.223858 17 1 16.77614 1 16.5 c 1 16.22386 1.223858 16 1.5 16 c h 4.5 1 m 4.776143 1 5 1.223858 5 1.5 c 5 1.776143 4.776143 2 4.5 2 c 4.223857 2 4 1.776143 4 1.5 c 4 1.223858 4.223857 1 4.5 1 c h 4.5 4 m 4.776143 4 5 4.223857 5 4.5 c 5 4.776143 4.776143 5 4.5 5 c 4.223857 5 4 4.776143 4 4.5 c 4 4.223857 4.223857 4 4.5 4 c h 4.5 7 m 4.776143 7 5 7.223858 5 7.5 c 5 7.776143 4.776143 8 4.5 8 c 4.223857 8 4 7.776143 4 7.5 c 4 7.223858 4.223857 7 4.5 7 c h 4.5 10 m 4.776143 10 5 10.22386 5 10.5 c 5 10.77614 4.776143 11 4.5 11 c 4.223857 11 4 10.77614 4 10.5 c 4 10.22386 4.223857 10 4.5 10 c h 4.5 13 m 4.776143 13 5 13.22386 5 13.5 c 5 13.77614 4.776143 14 4.5 14 c 4.223857 14 4 13.77614 4 13.5 c 4 13.22386 4.223857 13 4.5 13 c h 4.5 16 m 4.776143 16 5 16.22386 5 16.5 c 5 16.77614 4.776143 17 4.5 17 c 4.223857 17 4 16.77614 4 16.5 c 4 16.22386 4.223857 16 4.5 16 c h 7.5 1 m 7.776143 1 8 1.223858 8 1.5 c 8 1.776143 7.776143 2 7.5 2 c 7.223858 2 7 1.776143 7 1.5 c 7 1.223858 7.223858 1 7.5 1 c h 7.5 4 m 7.776143 4 8 4.223857 8 4.5 c 8 4.776143 7.776143 5 7.5 5 c 7.223858 5 7 4.776143 7 4.5 c 7 4.223857 7.223858 4 7.5 4 c h 7.5 7 m 7.776143 7 8 7.223858 8 7.5 c 8 7.776143 7.776143 8 7.5 8 c 7.223858 8 7 7.776143 7 7.5 c 7 7.223858 7.223858 7 7.5 7 c h 7.5 10 m 7.776143 10 8 10.22386 8 10.5 c 8 10.77614 7.776143 11 7.5 11 c 7.223858 11 7 10.77614 7 10.5 c 7 10.22386 7.223858 10 7.5 10 c h 7.5 13 m 7.776143 13 8 13.22386 8 13.5 c 8 13.77614 7.776143 14 7.5 14 c 7.223858 14 7 13.77614 7 13.5 c 7 13.22386 7.223858 13 7.5 13 c h 7.5 16 m 7.776143 16 8 16.22386 8 16.5 c 8 16.77614 7.776143 17 7.5 17 c 7.223858 17 7 16.77614 7 16.5 c 7 16.22386 7.223858 16 7.5 16 c h 10.5 1 m 10.77614 1 11 1.223858 11 1.5 c 11 1.776143 10.77614 2 10.5 2 c 10.22386 2 10 1.776143 10 1.5 c 10 1.223858 10.22386 1 10.5 1 c h 10.5 4 m 10.77614 4 11 4.223857 11 4.5 c 11 4.776143 10.77614 5 10.5 5 c 10.22386 5 10 4.776143 10 4.5 c 10 4.223857 10.22386 4 10.5 4 c h 10.5 7 m 10.77614 7 11 7.223858 11 7.5 c 11 7.776143 10.77614 8 10.5 8 c 10.22386 8 10 7.776143 10 7.5 c 10 7.223858 10.22386 7 10.5 7 c h 10.5 10 m 10.77614 10 11 10.22386 11 10.5 c 11 10.77614 10.77614 11 10.5 11 c 10.22386 11 10 10.77614 10 10.5 c 10 10.22386 10.22386 10 10.5 10 c h 10.5 13 m 10.77614 13 11 13.22386 11 13.5 c 11 13.77614 10.77614 14 10.5 14 c 10.22386 14 10 13.77614 10 13.5 c 10 13.22386 10.22386 13 10.5 13 c h 10.5 16 m 10.77614 16 11 16.22386 11 16.5 c 11 16.77614 10.77614 17 10.5 17 c 10.22386 17 10 16.77614 10 16.5 c 10 16.22386 10.22386 16 10.5 16 c h 13.5 1 m 13.77614 1 14 1.223858 14 1.5 c 14 1.776143 13.77614 2 13.5 2 c 13.22386 2 13 1.776143 13 1.5 c 13 1.223858 13.22386 1 13.5 1 c h 13.5 4 m 13.77614 4 14 4.223857 14 4.5 c 14 4.776143 13.77614 5 13.5 5 c 13.22386 5 13 4.776143 13 4.5 c 13 4.223857 13.22386 4 13.5 4 c h 13.5 7 m 13.77614 7 14 7.223858 14 7.5 c 14 7.776143 13.77614 8 13.5 8 c 13.22386 8 13 7.776143 13 7.5 c 13 7.223858 13.22386 7 13.5 7 c h 13.5 10 m 13.77614 10 14 10.22386 14 10.5 c 14 10.77614 13.77614 11 13.5 11 c 13.22386 11 13 10.77614 13 10.5 c 13 10.22386 13.22386 10 13.5 10 c h 13.5 13 m 13.77614 13 14 13.22386 14 13.5 c 14 13.77614 13.77614 14 13.5 14 c 13.22386 14 13 13.77614 13 13.5 c 13 13.22386 13.22386 13 13.5 13 c h 13.5 16 m 13.77614 16 14 16.22386 14 16.5 c 14 16.77614 13.77614 17 13.5 17 c 13.22386 17 13 16.77614 13 16.5 c 13 16.22386 13.22386 16 13.5 16 c h 16.5 1 m 16.77614 1 17 1.223858 17 1.5 c 17 1.776143 16.77614 2 16.5 2 c 16.22386 2 16 1.776143 16 1.5 c 16 1.223858 16.22386 1 16.5 1 c h 16.5 4 m 16.77614 4 17 4.223857 17 4.5 c 17 4.776143 16.77614 5 16.5 5 c 16.22386 5 16 4.776143 16 4.5 c 16 4.223857 16.22386 4 16.5 4 c h 16.5 7 m 16.77614 7 17 7.223858 17 7.5 c 17 7.776143 16.77614 8 16.5 8 c 16.22386 8 16 7.776143 16 7.5 c 16 7.223858 16.22386 7 16.5 7 c h 16.5 10 m 16.77614 10 17 10.22386 17 10.5 c 17 10.77614 16.77614 11 16.5 11 c 16.22386 11 16 10.77614 16 10.5 c 16 10.22386 16.22386 10 16.5 10 c h 16.5 13 m 16.77614 13 17 13.22386 17 13.5 c 17 13.77614 16.77614 14 16.5 14 c 16.22386 14 16 13.77614 16 13.5 c 16 13.22386 16.22386 13 16.5 13 c h 16.5 16 m 16.77614 16 17 16.22386 17 16.5 c 17 16.77614 16.77614 17 16.5 17 c 16.22386 17 16 16.77614 16 16.5 c 16 16.22386 16.22386 16 16.5 16 c h
  {strokecolor} rg f
  endstream'''
,
'30Dots':'''<</Length 25547/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 0 -0.5 m 0.2761424 -0.5 0.5 -0.2761424 0.5 0 c 0.5 0.2761424 0.2761424 0.5 0 0.5 c -0.2761424 0.5 -0.5 0.2761424 -0.5 0 c -0.5 -0.2761424 -0.2761424 -0.5 0 -0.5 c h 0 2.071428 m 0.2761424 2.071428 0.5 2.295285 0.5 2.571428 c 0.5 2.84757 0.2761424 3.071428 0 3.071428 c -0.2761424 3.071428 -0.5 2.84757 -0.5 2.571428 c -0.5 2.295285 -0.2761424 2.071428 0 2.071428 c h 0 4.642858 m 0.2761424 4.642858 0.5 4.866715 0.5 5.142858 c 0.5 5.419 0.2761424 5.642858 0 5.642858 c -0.2761424 5.642858 -0.5 5.419 -0.5 5.142858 c -0.5 4.866715 -0.2761424 4.642858 0 4.642858 c h 0 7.214287 m 0.2761424 7.214287 0.5 7.438144 0.5 7.714287 c 0.5 7.990429 0.2761424 8.214287 0 8.214287 c -0.2761424 8.214287 -0.5 7.990429 -0.5 7.714287 c -0.5 7.438144 -0.2761424 7.214287 0 7.214287 c h 0 9.785715 m 0.2761424 9.785715 0.5 10.00957 0.5 10.28572 c 0.5 10.56186 0.2761424 10.78572 0 10.78572 c -0.2761424 10.78572 -0.5 10.56186 -0.5 10.28572 c -0.5 10.00957 -0.2761424 9.785715 0 9.785715 c h 0 12.35714 m 0.2761424 12.35714 0.5 12.581 0.5 12.85714 c 0.5 13.13328 0.2761424 13.35714 0 13.35714 c -0.2761424 13.35714 -0.5 13.13328 -0.5 12.85714 c -0.5 12.581 -0.2761424 12.35714 0 12.35714 c h 0 14.92857 m 0.2761424 14.92857 0.5 15.15243 0.5 15.42857 c 0.5 15.70471 0.2761424 15.92857 0 15.92857 c -0.2761424 15.92857 -0.5 15.70471 -0.5 15.42857 c -0.5 15.15243 -0.2761424 14.92857 0 14.92857 c h 0 17.5 m 0.2761424 17.5 0.5 17.72386 0.5 18 c 0.5 18.27614 0.2761424 18.5 0 18.5 c -0.2761424 18.5 -0.5 18.27614 -0.5 18 c -0.5 17.72386 -0.2761424 17.5 0 17.5 c h 2.571428 -0.5 m 2.84757 -0.5 3.071428 -0.2761424 3.071428 0 c 3.071428 0.2761424 2.84757 0.5 2.571428 0.5 c 2.295285 0.5 2.071428 0.2761424 2.071428 0 c 2.071428 -0.2761424 2.295285 -0.5 2.571428 -0.5 c h 2.571428 2.071428 m 2.84757 2.071428 3.071428 2.295285 3.071428 2.571428 c 3.071428 2.84757 2.84757 3.071428 2.571428 3.071428 c 2.295285 3.071428 2.071428 2.84757 2.071428 2.571428 c 2.071428 2.295285 2.295285 2.071428 2.571428 2.071428 c h 2.571428 4.642858 m 2.84757 4.642858 3.071428 4.866715 3.071428 5.142858 c 3.071428 5.419 2.84757 5.642858 2.571428 5.642858 c 2.295285 5.642858 2.071428 5.419 2.071428 5.142858 c 2.071428 4.866715 2.295285 4.642858 2.571428 4.642858 c h 2.571428 7.214287 m 2.84757 7.214287 3.071428 7.438144 3.071428 7.714287 c 3.071428 7.990429 2.84757 8.214287 2.571428 8.214287 c 2.295285 8.214287 2.071428 7.990429 2.071428 7.714287 c 2.071428 7.438144 2.295285 7.214287 2.571428 7.214287 c h 2.571428 9.785715 m 2.84757 9.785715 3.071428 10.00957 3.071428 10.28572 c 3.071428 10.56186 2.84757 10.78572 2.571428 10.78572 c 2.295285 10.78572 2.071428 10.56186 2.071428 10.28572 c 2.071428 10.00957 2.295285 9.785715 2.571428 9.785715 c h 2.571428 12.35714 m 2.84757 12.35714 3.071428 12.581 3.071428 12.85714 c 3.071428 13.13328 2.84757 13.35714 2.571428 13.35714 c 2.295285 13.35714 2.071428 13.13328 2.071428 12.85714 c 2.071428 12.581 2.295285 12.35714 2.571428 12.35714 c h 2.571428 14.92857 m 2.84757 14.92857 3.071428 15.15243 3.071428 15.42857 c 3.071428 15.70471 2.84757 15.92857 2.571428 15.92857 c 2.295285 15.92857 2.071428 15.70471 2.071428 15.42857 c 2.071428 15.15243 2.295285 14.92857 2.571428 14.92857 c h 2.571428 17.5 m 2.84757 17.5 3.071428 17.72386 3.071428 18 c 3.071428 18.27614 2.84757 18.5 2.571428 18.5 c 2.295285 18.5 2.071428 18.27614 2.071428 18 c 2.071428 17.72386 2.295285 17.5 2.571428 17.5 c h 5.142858 -0.5 m 5.419 -0.5 5.642858 -0.2761424 5.642858 0 c 5.642858 0.2761424 5.419 0.5 5.142858 0.5 c 4.866715 0.5 4.642858 0.2761424 4.642858 0 c 4.642858 -0.2761424 4.866715 -0.5 5.142858 -0.5 c h 5.142858 2.071428 m 5.419 2.071428 5.642858 2.295285 5.642858 2.571428 c 5.642858 2.84757 5.419 3.071428 5.142858 3.071428 c 4.866715 3.071428 4.642858 2.84757 4.642858 2.571428 c 4.642858 2.295285 4.866715 2.071428 5.142858 2.071428 c h 5.142858 4.642858 m 5.419 4.642858 5.642858 4.866715 5.642858 5.142858 c 5.642858 5.419 5.419 5.642858 5.142858 5.642858 c 4.866715 5.642858 4.642858 5.419 4.642858 5.142858 c 4.642858 4.866715 4.866715 4.642858 5.142858 4.642858 c h 5.142858 7.214287 m 5.419 7.214287 5.642858 7.438144 5.642858 7.714287 c 5.642858 7.990429 5.419 8.214287 5.142858 8.214287 c 4.866715 8.214287 4.642858 7.990429 4.642858 7.714287 c 4.642858 7.438144 4.866715 7.214287 5.142858 7.214287 c h 5.142858 9.785715 m 5.419 9.785715 5.642858 10.00957 5.642858 10.28572 c 5.642858 10.56186 5.419 10.78572 5.142858 10.78572 c 4.866715 10.78572 4.642858 10.56186 4.642858 10.28572 c 4.642858 10.00957 4.866715 9.785715 5.142858 9.785715 c h 5.142858 12.35714 m 5.419 12.35714 5.642858 12.581 5.642858 12.85714 c 5.642858 13.13328 5.419 13.35714 5.142858 13.35714 c 4.866715 13.35714 4.642858 13.13328 4.642858 12.85714 c 4.642858 12.581 4.866715 12.35714 5.142858 12.35714 c h 5.142858 14.92857 m 5.419 14.92857 5.642858 15.15243 5.642858 15.42857 c 5.642858 15.70471 5.419 15.92857 5.142858 15.92857 c 4.866715 15.92857 4.642858 15.70471 4.642858 15.42857 c 4.642858 15.15243 4.866715 14.92857 5.142858 14.92857 c h 5.142858 17.5 m 5.419 17.5 5.642858 17.72386 5.642858 18 c 5.642858 18.27614 5.419 18.5 5.142858 18.5 c 4.866715 18.5 4.642858 18.27614 4.642858 18 c 4.642858 17.72386 4.866715 17.5 5.142858 17.5 c h 7.714287 -0.5 m 7.990429 -0.5 8.214287 -0.2761424 8.214287 0 c 8.214287 0.2761424 7.990429 0.5 7.714287 0.5 c 7.438144 0.5 7.214287 0.2761424 7.214287 0 c 7.214287 -0.2761424 7.438144 -0.5 7.714287 -0.5 c h 7.714287 2.071428 m 7.990429 2.071428 8.214287 2.295285 8.214287 2.571428 c 8.214287 2.84757 7.990429 3.071428 7.714287 3.071428 c 7.438144 3.071428 7.214287 2.84757 7.214287 2.571428 c 7.214287 2.295285 7.438144 2.071428 7.714287 2.071428 c h 7.714287 4.642858 m 7.990429 4.642858 8.214287 4.866715 8.214287 5.142858 c 8.214287 5.419 7.990429 5.642858 7.714287 5.642858 c 7.438144 5.642858 7.214287 5.419 7.214287 5.142858 c 7.214287 4.866715 7.438144 4.642858 7.714287 4.642858 c h 7.714287 7.214287 m 7.990429 7.214287 8.214287 7.438144 8.214287 7.714287 c 8.214287 7.990429 7.990429 8.214287 7.714287 8.214287 c 7.438144 8.214287 7.214287 7.990429 7.214287 7.714287 c 7.214287 7.438144 7.438144 7.214287 7.714287 7.214287 c h 7.714287 9.785715 m 7.990429 9.785715 8.214287 10.00957 8.214287 10.28572 c 8.214287 10.56186 7.990429 10.78572 7.714287 10.78572 c 7.438144 10.78572 7.214287 10.56186 7.214287 10.28572 c 7.214287 10.00957 7.438144 9.785715 7.714287 9.785715 c h 7.714287 12.35714 m 7.990429 12.35714 8.214287 12.581 8.214287 12.85714 c 8.214287 13.13328 7.990429 13.35714 7.714287 13.35714 c 7.438144 13.35714 7.214287 13.13328 7.214287 12.85714 c 7.214287 12.581 7.438144 12.35714 7.714287 12.35714 c h 7.714287 14.92857 m 7.990429 14.92857 8.214287 15.15243 8.214287 15.42857 c 8.214287 15.70471 7.990429 15.92857 7.714287 15.92857 c 7.438144 15.92857 7.214287 15.70471 7.214287 15.42857 c 7.214287 15.15243 7.438144 14.92857 7.714287 14.92857 c h 7.714287 17.5 m 7.990429 17.5 8.214287 17.72386 8.214287 18 c 8.214287 18.27614 7.990429 18.5 7.714287 18.5 c 7.438144 18.5 7.214287 18.27614 7.214287 18 c 7.214287 17.72386 7.438144 17.5 7.714287 17.5 c h 10.28572 -0.5 m 10.56186 -0.5 10.78572 -0.2761424 10.78572 0 c 10.78572 0.2761424 10.56186 0.5 10.28572 0.5 c 10.00957 0.5 9.785715 0.2761424 9.785715 0 c 9.785715 -0.2761424 10.00957 -0.5 10.28572 -0.5 c h 10.28572 2.071428 m 10.56186 2.071428 10.78572 2.295285 10.78572 2.571428 c 10.78572 2.84757 10.56186 3.071428 10.28572 3.071428 c 10.00957 3.071428 9.785715 2.84757 9.785715 2.571428 c 9.785715 2.295285 10.00957 2.071428 10.28572 2.071428 c h 10.28572 4.642858 m 10.56186 4.642858 10.78572 4.866715 10.78572 5.142858 c 10.78572 5.419 10.56186 5.642858 10.28572 5.642858 c 10.00957 5.642858 9.785715 5.419 9.785715 5.142858 c 9.785715 4.866715 10.00957 4.642858 10.28572 4.642858 c h 10.28572 7.214287 m 10.56186 7.214287 10.78572 7.438144 10.78572 7.714287 c 10.78572 7.990429 10.56186 8.214287 10.28572 8.214287 c 10.00957 8.214287 9.785715 7.990429 9.785715 7.714287 c 9.785715 7.438144 10.00957 7.214287 10.28572 7.214287 c h 10.28572 9.785715 m 10.56186 9.785715 10.78572 10.00957 10.78572 10.28572 c 10.78572 10.56186 10.56186 10.78572 10.28572 10.78572 c 10.00957 10.78572 9.785715 10.56186 9.785715 10.28572 c 9.785715 10.00957 10.00957 9.785715 10.28572 9.785715 c h 10.28572 12.35714 m 10.56186 12.35714 10.78572 12.581 10.78572 12.85714 c 10.78572 13.13328 10.56186 13.35714 10.28572 13.35714 c 10.00957 13.35714 9.785715 13.13328 9.785715 12.85714 c 9.785715 12.581 10.00957 12.35714 10.28572 12.35714 c h 10.28572 14.92857 m 10.56186 14.92857 10.78572 15.15243 10.78572 15.42857 c 10.78572 15.70471 10.56186 15.92857 10.28572 15.92857 c 10.00957 15.92857 9.785715 15.70471 9.785715 15.42857 c 9.785715 15.15243 10.00957 14.92857 10.28572 14.92857 c h 10.28572 17.5 m 10.56186 17.5 10.78572 17.72386 10.78572 18 c 10.78572 18.27614 10.56186 18.5 10.28572 18.5 c 10.00957 18.5 9.785715 18.27614 9.785715 18 c 9.785715 17.72386 10.00957 17.5 10.28572 17.5 c h 12.85714 -0.5 m 13.13328 -0.5 13.35714 -0.2761424 13.35714 0 c 13.35714 0.2761424 13.13328 0.5 12.85714 0.5 c 12.581 0.5 12.35714 0.2761424 12.35714 0 c 12.35714 -0.2761424 12.581 -0.5 12.85714 -0.5 c h 12.85714 2.071428 m 13.13328 2.071428 13.35714 2.295285 13.35714 2.571428 c 13.35714 2.84757 13.13328 3.071428 12.85714 3.071428 c 12.581 3.071428 12.35714 2.84757 12.35714 2.571428 c 12.35714 2.295285 12.581 2.071428 12.85714 2.071428 c h 12.85714 4.642858 m 13.13328 4.642858 13.35714 4.866715 13.35714 5.142858 c 13.35714 5.419 13.13328 5.642858 12.85714 5.642858 c 12.581 5.642858 12.35714 5.419 12.35714 5.142858 c 12.35714 4.866715 12.581 4.642858 12.85714 4.642858 c h 12.85714 7.214287 m 13.13328 7.214287 13.35714 7.438144 13.35714 7.714287 c 13.35714 7.990429 13.13328 8.214287 12.85714 8.214287 c 12.581 8.214287 12.35714 7.990429 12.35714 7.714287 c 12.35714 7.438144 12.581 7.214287 12.85714 7.214287 c h 12.85714 9.785715 m 13.13328 9.785715 13.35714 10.00957 13.35714 10.28572 c 13.35714 10.56186 13.13328 10.78572 12.85714 10.78572 c 12.581 10.78572 12.35714 10.56186 12.35714 10.28572 c 12.35714 10.00957 12.581 9.785715 12.85714 9.785715 c h 12.85714 12.35714 m 13.13328 12.35714 13.35714 12.581 13.35714 12.85714 c 13.35714 13.13328 13.13328 13.35714 12.85714 13.35714 c 12.581 13.35714 12.35714 13.13328 12.35714 12.85714 c 12.35714 12.581 12.581 12.35714 12.85714 12.35714 c h 12.85714 14.92857 m 13.13328 14.92857 13.35714 15.15243 13.35714 15.42857 c 13.35714 15.70471 13.13328 15.92857 12.85714 15.92857 c 12.581 15.92857 12.35714 15.70471 12.35714 15.42857 c 12.35714 15.15243 12.581 14.92857 12.85714 14.92857 c h 12.85714 17.5 m 13.13328 17.5 13.35714 17.72386 13.35714 18 c 13.35714 18.27614 13.13328 18.5 12.85714 18.5 c 12.581 18.5 12.35714 18.27614 12.35714 18 c 12.35714 17.72386 12.581 17.5 12.85714 17.5 c h 15.42857 -0.5 m 15.70471 -0.5 15.92857 -0.2761424 15.92857 0 c 15.92857 0.2761424 15.70471 0.5 15.42857 0.5 c 15.15243 0.5 14.92857 0.2761424 14.92857 0 c 14.92857 -0.2761424 15.15243 -0.5 15.42857 -0.5 c h 15.42857 2.071428 m 15.70471 2.071428 15.92857 2.295285 15.92857 2.571428 c 15.92857 2.84757 15.70471 3.071428 15.42857 3.071428 c 15.15243 3.071428 14.92857 2.84757 14.92857 2.571428 c 14.92857 2.295285 15.15243 2.071428 15.42857 2.071428 c h 15.42857 4.642858 m 15.70471 4.642858 15.92857 4.866715 15.92857 5.142858 c 15.92857 5.419 15.70471 5.642858 15.42857 5.642858 c 15.15243 5.642858 14.92857 5.419 14.92857 5.142858 c 14.92857 4.866715 15.15243 4.642858 15.42857 4.642858 c h 15.42857 7.214287 m 15.70471 7.214287 15.92857 7.438144 15.92857 7.714287 c 15.92857 7.990429 15.70471 8.214287 15.42857 8.214287 c 15.15243 8.214287 14.92857 7.990429 14.92857 7.714287 c 14.92857 7.438144 15.15243 7.214287 15.42857 7.214287 c h 15.42857 9.785715 m 15.70471 9.785715 15.92857 10.00957 15.92857 10.28572 c 15.92857 10.56186 15.70471 10.78572 15.42857 10.78572 c 15.15243 10.78572 14.92857 10.56186 14.92857 10.28572 c 14.92857 10.00957 15.15243 9.785715 15.42857 9.785715 c h 15.42857 12.35714 m 15.70471 12.35714 15.92857 12.581 15.92857 12.85714 c 15.92857 13.13328 15.70471 13.35714 15.42857 13.35714 c 15.15243 13.35714 14.92857 13.13328 14.92857 12.85714 c 14.92857 12.581 15.15243 12.35714 15.42857 12.35714 c h 15.42857 14.92857 m 15.70471 14.92857 15.92857 15.15243 15.92857 15.42857 c 15.92857 15.70471 15.70471 15.92857 15.42857 15.92857 c 15.15243 15.92857 14.92857 15.70471 14.92857 15.42857 c 14.92857 15.15243 15.15243 14.92857 15.42857 14.92857 c h 15.42857 17.5 m 15.70471 17.5 15.92857 17.72386 15.92857 18 c 15.92857 18.27614 15.70471 18.5 15.42857 18.5 c 15.15243 18.5 14.92857 18.27614 14.92857 18 c 14.92857 17.72386 15.15243 17.5 15.42857 17.5 c h 18 -0.5 m 18.27614 -0.5 18.5 -0.2761424 18.5 0 c 18.5 0.2761424 18.27614 0.5 18 0.5 c 17.72386 0.5 17.5 0.2761424 17.5 0 c 17.5 -0.2761424 17.72386 -0.5 18 -0.5 c h 18 2.071428 m 18.27614 2.071428 18.5 2.295285 18.5 2.571428 c 18.5 2.84757 18.27614 3.071428 18 3.071428 c 17.72386 3.071428 17.5 2.84757 17.5 2.571428 c 17.5 2.295285 17.72386 2.071428 18 2.071428 c h 18 4.642858 m 18.27614 4.642858 18.5 4.866715 18.5 5.142858 c 18.5 5.419 18.27614 5.642858 18 5.642858 c 17.72386 5.642858 17.5 5.419 17.5 5.142858 c 17.5 4.866715 17.72386 4.642858 18 4.642858 c h 18 7.214287 m 18.27614 7.214287 18.5 7.438144 18.5 7.714287 c 18.5 7.990429 18.27614 8.214287 18 8.214287 c 17.72386 8.214287 17.5 7.990429 17.5 7.714287 c 17.5 7.438144 17.72386 7.214287 18 7.214287 c h 18 9.785715 m 18.27614 9.785715 18.5 10.00957 18.5 10.28572 c 18.5 10.56186 18.27614 10.78572 18 10.78572 c 17.72386 10.78572 17.5 10.56186 17.5 10.28572 c 17.5 10.00957 17.72386 9.785715 18 9.785715 c h 18 12.35714 m 18.27614 12.35714 18.5 12.581 18.5 12.85714 c 18.5 13.13328 18.27614 13.35714 18 13.35714 c 17.72386 13.35714 17.5 13.13328 17.5 12.85714 c 17.5 12.581 17.72386 12.35714 18 12.35714 c h 18 14.92857 m 18.27614 14.92857 18.5 15.15243 18.5 15.42857 c 18.5 15.70471 18.27614 15.92857 18 15.92857 c 17.72386 15.92857 17.5 15.70471 17.5 15.42857 c 17.5 15.15243 17.72386 14.92857 18 14.92857 c h 18 17.5 m 18.27614 17.5 18.5 17.72386 18.5 18 c 18.5 18.27614 18.27614 18.5 18 18.5 c 17.72386 18.5 17.5 18.27614 17.5 18 c 17.5 17.72386 17.72386 17.5 18 17.5 c h 1.285714 0.7857141 m 1.561857 0.7857141 1.785714 1.009572 1.785714 1.285714 c 1.785714 1.561857 1.561857 1.785714 1.285714 1.785714 c 1.009572 1.785714 0.7857141 1.561857 0.7857141 1.285714 c 0.7857141 1.009572 1.009572 0.7857141 1.285714 0.7857141 c h 1.285714 3.357143 m 1.561857 3.357143 1.785714 3.581 1.785714 3.857143 c 1.785714 4.133285 1.561857 4.357142 1.285714 4.357142 c 1.009572 4.357142 0.7857141 4.133285 0.7857141 3.857143 c 0.7857141 3.581 1.009572 3.357143 1.285714 3.357143 c h 1.285714 5.928572 m 1.561857 5.928572 1.785714 6.15243 1.785714 6.428572 c 1.785714 6.704715 1.561857 6.928572 1.285714 6.928572 c 1.009572 6.928572 0.7857141 6.704715 0.7857141 6.428572 c 0.7857141 6.15243 1.009572 5.928572 1.285714 5.928572 c h 1.285714 8.5 m 1.561857 8.5 1.785714 8.723858 1.785714 9 c 1.785714 9.276142 1.561857 9.5 1.285714 9.5 c 1.009572 9.5 0.7857141 9.276142 0.7857141 9 c 0.7857141 8.723858 1.009572 8.5 1.285714 8.5 c h 1.285714 11.07143 m 1.561857 11.07143 1.785714 11.29529 1.785714 11.57143 c 1.785714 11.84757 1.561857 12.07143 1.285714 12.07143 c 1.009572 12.07143 0.7857141 11.84757 0.7857141 11.57143 c 0.7857141 11.29529 1.009572 11.07143 1.285714 11.07143 c h 1.285714 13.64286 m 1.561857 13.64286 1.785714 13.86672 1.785714 14.14286 c 1.785714 14.419 1.561857 14.64286 1.285714 14.64286 c 1.009572 14.64286 0.7857141 14.419 0.7857141 14.14286 c 0.7857141 13.86672 1.009572 13.64286 1.285714 13.64286 c h 1.285714 16.21429 m 1.561857 16.21429 1.785714 16.43814 1.785714 16.71429 c 1.785714 16.99043 1.561857 17.21429 1.285714 17.21429 c 1.009572 17.21429 0.7857141 16.99043 0.7857141 16.71429 c 0.7857141 16.43814 1.009572 16.21429 1.285714 16.21429 c h 3.857143 0.7857141 m 4.133285 0.7857141 4.357142 1.009572 4.357142 1.285714 c 4.357142 1.561857 4.133285 1.785714 3.857143 1.785714 c 3.581 1.785714 3.357143 1.561857 3.357143 1.285714 c 3.357143 1.009572 3.581 0.7857141 3.857143 0.7857141 c h 3.857143 3.357143 m 4.133285 3.357143 4.357142 3.581 4.357142 3.857143 c 4.357142 4.133285 4.133285 4.357142 3.857143 4.357142 c 3.581 4.357142 3.357143 4.133285 3.357143 3.857143 c 3.357143 3.581 3.581 3.357143 3.857143 3.357143 c h 3.857143 5.928572 m 4.133285 5.928572 4.357142 6.15243 4.357142 6.428572 c 4.357142 6.704715 4.133285 6.928572 3.857143 6.928572 c 3.581 6.928572 3.357143 6.704715 3.357143 6.428572 c 3.357143 6.15243 3.581 5.928572 3.857143 5.928572 c h 3.857143 8.5 m 4.133285 8.5 4.357142 8.723858 4.357142 9 c 4.357142 9.276142 4.133285 9.5 3.857143 9.5 c 3.581 9.5 3.357143 9.276142 3.357143 9 c 3.357143 8.723858 3.581 8.5 3.857143 8.5 c h 3.857143 11.07143 m 4.133285 11.07143 4.357142 11.29529 4.357142 11.57143 c 4.357142 11.84757 4.133285 12.07143 3.857143 12.07143 c 3.581 12.07143 3.357143 11.84757 3.357143 11.57143 c 3.357143 11.29529 3.581 11.07143 3.857143 11.07143 c h 3.857143 13.64286 m 4.133285 13.64286 4.357142 13.86672 4.357142 14.14286 c 4.357142 14.419 4.133285 14.64286 3.857143 14.64286 c 3.581 14.64286 3.357143 14.419 3.357143 14.14286 c 3.357143 13.86672 3.581 13.64286 3.857143 13.64286 c h 3.857143 16.21429 m 4.133285 16.21429 4.357142 16.43814 4.357142 16.71429 c 4.357142 16.99043 4.133285 17.21429 3.857143 17.21429 c 3.581 17.21429 3.357143 16.99043 3.357143 16.71429 c 3.357143 16.43814 3.581 16.21429 3.857143 16.21429 c h 6.428572 0.7857141 m 6.704715 0.7857141 6.928572 1.009572 6.928572 1.285714 c 6.928572 1.561857 6.704715 1.785714 6.428572 1.785714 c 6.15243 1.785714 5.928572 1.561857 5.928572 1.285714 c 5.928572 1.009572 6.15243 0.7857141 6.428572 0.7857141 c h 6.428572 3.357143 m 6.704715 3.357143 6.928572 3.581 6.928572 3.857143 c 6.928572 4.133285 6.704715 4.357142 6.428572 4.357142 c 6.15243 4.357142 5.928572 4.133285 5.928572 3.857143 c 5.928572 3.581 6.15243 3.357143 6.428572 3.357143 c h 6.428572 5.928572 m 6.704715 5.928572 6.928572 6.15243 6.928572 6.428572 c 6.928572 6.704715 6.704715 6.928572 6.428572 6.928572 c 6.15243 6.928572 5.928572 6.704715 5.928572 6.428572 c 5.928572 6.15243 6.15243 5.928572 6.428572 5.928572 c h 6.428572 8.5 m 6.704715 8.5 6.928572 8.723858 6.928572 9 c 6.928572 9.276142 6.704715 9.5 6.428572 9.5 c 6.15243 9.5 5.928572 9.276142 5.928572 9 c 5.928572 8.723858 6.15243 8.5 6.428572 8.5 c h 6.428572 11.07143 m 6.704715 11.07143 6.928572 11.29529 6.928572 11.57143 c 6.928572 11.84757 6.704715 12.07143 6.428572 12.07143 c 6.15243 12.07143 5.928572 11.84757 5.928572 11.57143 c 5.928572 11.29529 6.15243 11.07143 6.428572 11.07143 c h 6.428572 13.64286 m 6.704715 13.64286 6.928572 13.86672 6.928572 14.14286 c 6.928572 14.419 6.704715 14.64286 6.428572 14.64286 c 6.15243 14.64286 5.928572 14.419 5.928572 14.14286 c 5.928572 13.86672 6.15243 13.64286 6.428572 13.64286 c h 6.428572 16.21429 m 6.704715 16.21429 6.928572 16.43814 6.928572 16.71429 c 6.928572 16.99043 6.704715 17.21429 6.428572 17.21429 c 6.15243 17.21429 5.928572 16.99043 5.928572 16.71429 c 5.928572 16.43814 6.15243 16.21429 6.428572 16.21429 c h 9 0.7857141 m 9.276142 0.7857141 9.5 1.009572 9.5 1.285714 c 9.5 1.561857 9.276142 1.785714 9 1.785714 c 8.723858 1.785714 8.5 1.561857 8.5 1.285714 c 8.5 1.009572 8.723858 0.7857141 9 0.7857141 c h 9 3.357143 m 9.276142 3.357143 9.5 3.581 9.5 3.857143 c 9.5 4.133285 9.276142 4.357142 9 4.357142 c 8.723858 4.357142 8.5 4.133285 8.5 3.857143 c 8.5 3.581 8.723858 3.357143 9 3.357143 c h 9 5.928572 m 9.276142 5.928572 9.5 6.15243 9.5 6.428572 c 9.5 6.704715 9.276142 6.928572 9 6.928572 c 8.723858 6.928572 8.5 6.704715 8.5 6.428572 c 8.5 6.15243 8.723858 5.928572 9 5.928572 c h 9 8.5 m 9.276142 8.5 9.5 8.723858 9.5 9 c 9.5 9.276142 9.276142 9.5 9 9.5 c 8.723858 9.5 8.5 9.276142 8.5 9 c 8.5 8.723858 8.723858 8.5 9 8.5 c h 9 11.07143 m 9.276142 11.07143 9.5
  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 = "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 = '789c85d04f0b82401005f0af3247bd34a35176b085503c55847f22a80e2a4b7858ad7537e8dba7951ea2a5e330efc783e7fb983eae1c373c6fb5e498e842f577bcc6d872a014b00407848d87e310dd6a5170193552e40a33abfb0540139ace5ccff316188243844962d98c9d3134b297eba2f4255626d1dee06d3e200a4149cd47989ae0c99dd32fb8ebe0a8f7265dea3fb5b9bc7095d5950a9aface655b3575bf070d8b30f604438f6873'
    bax_xml= tostring(doc, encoding="unicode", method="xml") #tostring(doc, encoding="utf-8", method="xml").decode("utf-8")
    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)
  return img


# 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


"""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):
    # Check if the entity has a "true color" set
    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

    color_index = entity.dxf.color
    print("color_index = ", color_index)

    # Check if the color is set to ByLayer or ByBlock
    if color_index == 0:  # ByLayer color
        print("Color is ByLayer, checking layer color...")
        layer_name = entity.dxf.layer
        layer = entity.doc.layers.get(layer_name)

        if layer:  # Ensure layer exists
            layer_color_index = layer.dxf.color
            print(f"Layer '{layer_name}' Color Index = {layer_color_index}")
            return aci_to_rgb(layer_color_index)  # Use custom aci_to_rgb function
        else:
            print(f"Layer '{layer_name}' not found, defaulting to white.")
            return (255, 255, 255)  # Default to white if layer not found

    elif color_index == 256:  # ByBlock color
        print("Color is ByBlock, checking block color or defaulting to white.")
        block_color = (255, 255, 255)  # White as default

        # Check if the entity is inside a block reference and inherit its color
        if hasattr(entity, 'block'):  # Check if the entity belongs to a block
            block_ref = entity.block
            if block_ref.dxf.hasattr('color'):
                block_color = aci_to_rgb(block_ref.dxf.color)
                print(f"Block reference color found: {block_color}")
            else:
                print("Block has no color attribute, using default (white).")
        return block_color

    # Otherwise, convert the ACI color to RGB
    print(f"Entity Color Index = {color_index}")
    if 1 <= color_index <= 255:
        rgb_color = aci_to_rgb(color_index)  # Use custom aci_to_rgb function
        print(f"Converted RGB = {rgb_color}")
        return rgb_color

    # Default to white if color index is out of bounds or invalid
    print("Invalid or unhandled color index, defaulting to white.")
    return (255, 255, 255)

def calculate_distance(p1, p2):
    return math.sqrt((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)

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))
    
    
"""### Hatched areas"""
def get_hatched_areas(datadoc,filename,FinalRatio,rotationangle,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

      Legendarray = []

      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
                          Legendarray.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
                          Legendarray.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
                          Legendarray.append([text, textNBS, (x, y), detected_color])
            print("text_with_positions=",Legendarray)








      grouped = {}
      for entry in Legendarray:
          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])

      Legendarray=filtered_results
    


      for entity in doc.modelspace().query('TEXT MTEXT'):
        if hasattr(entity, 'text'):  # Ensure the entity has text content
            text = entity.text
            if text.startswith('C') and (len(text) > 1 and (text[1].isdigit() or text[1].upper() == 'T' or text[1].upper() == 'L')):
                parts = text.split(' ')  # Split into two parts: before and after the first newline
                # print("Parts = ",parts[0])
                main_text = parts[0]  # Text before the first newline

                # Check if the main text starts with 'C' followed by a number or 'T'
                # if pattern.match(main_text):
                position = entity.dxf.insert


                # Check if the text already has a color assigned
                if main_text not in text_color_mapping:
                    # Assign a new color from the palette
                    color_index = len(text_color_mapping) % len(color_palette)
                    text_color_mapping[main_text] = color_palette[color_index]

                # Get the assigned color
                color = text_color_mapping[main_text]

                # Set the entity's true color
                # entity.dxf.true_color = rgb_to_true_color(color)

                # Append text, position, and color to the array
                text_with_positions.append([main_text, position, color])
                
      for entity in msp:
        if entity.dxftype() == 'HATCH':
            # print(f"Processing HATCH entity: {entity}")
            for path in entity.paths:
                vertices = []  # Reset vertices for each path

                if path.type == 1:
                    # Handle POLYLINE type HATCH
                    vertices = [(vertex[0] * FinalRatio, vertex[1] * FinalRatio) for vertex in path.vertices]

                    if len(vertices) > 3:
                        poly = ShapelyPolygon(vertices)
                        minx, miny, maxx, maxy = poly.bounds
                        width = maxx - minx
                        height = maxy - miny

                        if (poly.area > 0.9 and (height > 0.7 and width > 0.7)):
                            area1 = round(poly.area, 3)
                            perimeter = round(poly.length, 3)
                            normalized_vertices = normalize_vertices(vertices)

                            rgb_color = get_hatch_color(entity)
                            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))
                                hatched_areas.append([vertices, area1, perimeter, rgb_color])

                elif path.type == 2:
                  # convert any spline edges to line edges (approximates splines)
                  # factor controls approximation density: control_points_count * factor
                  try:
                      path.spline_edges_to_line_edges(factor=8)  # increase factor for finer approx
                  except Exception:
                      # defensive: some versions / unexpected objects might raise — ignore and continue
                      pass

                  vert = []
                  # After conversion most edges will be LineEdge with .start and .end
                  for edge in path.edges:
                      # If edge has start/end attributes (LineEdge), use them
                      if hasattr(edge, "start") and hasattr(edge, "end"):
                          sx, sy = edge.start
                          ex, ey = edge.end
                          # append only start point; we'll append the end of the last edge too to close path
                          vert.append((sx * FinalRatio, sy * FinalRatio))
                      else:
                          # fallback: try control_points or fit_points if present (rare after conversion)
                          if hasattr(edge, "control_points") and edge.control_points:
                              for cp in edge.control_points:
                                  vert.append((cp[0] * FinalRatio, cp[1] * FinalRatio))
                          elif hasattr(edge, "fit_points") and edge.fit_points:
                              for fp in edge.fit_points:
                                  vert.append((fp[0] * FinalRatio, fp[1] * FinalRatio))
                          else:
                              # last resort: try to string-represent and skip if nothing usable
                              continue

                  # After loop, ensure polygon is closed: append last edge.end if available
                  if path.edges and hasattr(path.edges[-1], "end"):
                      ex, ey = path.edges[-1].end
                      vert.append((ex * FinalRatio, ey * FinalRatio))

                  # remove possible duplicate consecutive points (optional)
                  cleaned = []
                  for p in vert:
                      if not cleaned or (abs(cleaned[-1][0] - p[0]) > 1e-9 or abs(cleaned[-1][1] - p[1]) > 1e-9):
                          cleaned.append(p)
                  vert = cleaned

                  # validate and use Shapely as before
                  if len(vert) >= 3:
                      poly = ShapelyPolygon(vert)
                      minx, miny, maxx, maxy = poly.bounds
                      width = maxx - minx
                      height = maxy - miny

                      if (poly.area > 0.1 and (height > 0.1 and width > 0.1)):
                          area1 = round(poly.area, 3)
                          perimeter = round(poly.length, 3)
                          normalized_vertices = normalize_vertices(vert)
                          rgb_color = get_hatch_color(entity)
                          if rgb_color == (255, 255, 255) and 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:
                              unique_shapes.append((normalized_vertices, area1))
                              hatched_areas.append([vert, area1, perimeter, rgb_color])

        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 > 0.9 and (height > 0.7 and width > 0.7)):
              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() == '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 > 0.9 and (height > 0.7 and width > 0.7)):
                      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':

          # print("In 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 > 0.9 and (height > 0.7 and width > 0.7)):
                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 > 0.9 and (height > 0.7 and width > 0.7)):
                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,Legendarray

"""### 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= RetriveRatio(datadoc,dxfpath,pdf_content)
  else:
     FinalRatio= RetriveRatio(datadoc,dxfpath)

  # hatched_areas = get_hatched_areas(dxfpath,FinalRatio)
  # print('hatched_areas',hatched_areas)
  # 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, 'Total Area'] + area
          SimilarAreaDictionary.at[index, 'Total Perimeter'] = SimilarAreaDictionary.at[index, 'Total Perimeter'] + perimeter
      else:
          TotalArea=area
          TotalPerimeter=perimeter
          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"""
def color_close_enough(c1, c2, threshold=10):
    return all(abs(a - b) <= threshold for a, b in zip(c1, c2))



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 [[raw[i], raw[i+1]] for i in range(0, len(raw), 2)]


def extract_measurement(obj):
    """Extract numeric measurement from annotation's /Contents field."""
    contents = obj.get("/Contents")
    if not contents:
        return None
    # Find first numeric occurrence
    text = str(contents)
    m = re.search(r"([0-9]*\.?[0-9]+)", text)
    return float(m.group(1)) if m else None

def adjustannotations(OutputPdfStage1,text_with_positions):
  input_pdf_path = OutputPdfStage1
  output_pdf_path = "Final-WallsAdjusted.pdf"
  annotations_data = []
  Trim=0

  # 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
                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)})

            # Update annotation dictionaries for measurement type
            if subtype == "/PolyLine" and obj.get("/Subj", "") == "Perimeter Measurement":
                
                title = obj.get("/T", "")                 # read the /T field
                title_str = str(title).strip()            # cast to str and trim whitespace
                # print(title_str)
                if title_str == "Skirting Measurement":
                    # print("Skirting")
                    Trim=0
                elif title_str == "Trim Measurement":
                    # print("Trim")
                    Trim=1
                    
                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,
                 Trim,
            ])



  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 _order_points_monotonic(points, eps=1e-9):
    """
    Order a list of (x,y) points along their main axis (PCA),
    then refine ordering by greedy nearest-neighbor but never stepping
    backward along the principal-axis projection (monotonic).
    Returns ordered list of (x,y).
    """
    if not points:
        return []
    if len(points) <= 2:
        return list(points)

    pts = np.array(points, dtype=float)  # shape (n,2)
    mean = pts.mean(axis=0)
    centered = pts - mean

    # PCA via SVD
    try:
        _, _, vt = np.linalg.svd(centered, full_matrices=False)
        principal = vt[0]  # principal axis direction (unit-ish)
    except Exception:
        # fallback to simple x or y sort if SVD fails
        return sorted(points, key=lambda p: (p[0], p[1]))

    # projection scalars along principal axis
    proj = centered.dot(principal)  # length n array

    # sort indices by projection (ascending)
    idxs = list(np.argsort(proj))
    proj_sorted = proj[idxs]

    # greedy monotonic walk: start from first index (smallest projection)
    ordered = []
    remaining = set(idxs)
    curr_idx = idxs[0]
    ordered.append(tuple(pts[curr_idx].tolist()))
    remaining.remove(curr_idx)

    while remaining:
        # candidates that do not go backwards along projection
        cand = [i for i in remaining if proj[i] >= proj[curr_idx] - eps]
        if not cand:
            # if none, pick nearest among remaining (rare)
            cand = list(remaining)

        # choose candidate with minimum Euclidean distance to current point
        curr_pt = pts[curr_idx]
        best = min(cand, key=lambda i: np.hypot(*(pts[i] - curr_pt)))
        ordered.append(tuple(pts[best].tolist()))
        remaining.remove(best)
        curr_idx = best

    return ordered


def find_nearby_vertices(shapes, distance_threshold=0.5):
    """
    shapes: list structured as [ vertices_list, area, perimeter, color_tuple ]
            where vertices_list is [(x,y), ...]
    distance_threshold: maximum absolute difference in x and y to consider two vertices 'close'

    Returns:
        intersections: [ [ [(x,y), ...] ], ... ]
        grouped_shapes: list of grouped shapes (each group is a merged list of shape indices)
    """
    intersections = []
    grouped_shapes = []  # new array to collect shape groups
    used = set()

    n = len(shapes)
    for i in range(n):
        for j in range(i + 1, n):
            shape1 = shapes[i]
            shape2 = shapes[j]

            # Skip if same or invalid color
            if (
                shape1[3] == shape2[3] or
                shape1[3] in [(0,0,0), (255,255,255)] or
                shape2[3] in [(0,0,0), (255,255,255)]
            ):
                continue

            verts1 = list(shape1[0])
            verts2 = list(shape2[0])
            if len(verts1) > 1 and verts1[0] == verts1[-1]:
                verts1 = verts1[:-1]
            if len(verts2) > 1 and verts2[0] == verts2[-1]:
                verts2 = verts2[:-1]

            close_points = []
            for (x1, y1) in verts1:
                for (x2, y2) in verts2:
                    if abs(x1 - x2) <= distance_threshold and abs(y1 - y2) <= distance_threshold:
                        p = (float(x2), float(y2))
                        if p not in close_points:
                            close_points.append(p)

            if close_points:
                # Order + dedup (optional)
                ordered = _order_points_monotonic(close_points)
                dedup = []
                for pt in ordered:
                    if not dedup or (abs(pt[0]-dedup[-1][0])>1e-6 or abs(pt[1]-dedup[-1][1])>1e-6):
                        dedup.append(pt)

                if len(dedup) >= 2:
                    intersections.append([dedup])

                # ---- new: group these two shapes together ----
                group = {i, j}
                # merge if overlapping with existing groups
                merged = False
                for g in grouped_shapes:
                    if not group.isdisjoint(g):
                        g.update(group)
                        merged = True
                        break
                if not merged:
                    grouped_shapes.append(group)

    # Convert grouped indices into grouped shapes
    grouped_shapes_final = []
    for g in grouped_shapes:
        merged_verts = []
        colors = set()
        for idx in g:
            merged_verts.extend(shapes[idx][0])
            colors.add(shapes[idx][3])
        grouped_shapes_final.append([merged_verts, None, None, list(colors)])

    return intersections, grouped_shapes_final

def process_polygons(polygons, imgg, dxfratio, rotationangle, derotationMatrix, rotationOld, width, height):
    processed_shapes = []

    for polygon in polygons:
        cntPoints = []
        cntPoints1 = []
        shapeePerimeter = []
        shapeeArea = []
        Text_Detected = 0

        blackImgShapes = np.zeros(imgg.shape[:2], dtype="uint8")
        blackImgShapes = cv2.cvtColor(blackImgShapes, cv2.COLOR_GRAY2BGR)

        # Handle nested or flat structure
        vertices = polygon
        print("vertices = ", vertices)

        for vertex in vertices:
            for pt in vertex:
                x = pt[0] * dxfratio
                y = pt[1] * dxfratio
                if rotationangle == 0 and y < 0:
                    y = -y
                cntPoints.append([int(x), int(y)])
                cntPoints1.append([x, y])

        # Draw contour (for mask/image purposes)
        cv2.drawContours(blackImgShapes, [np.array(cntPoints)], -1, (255, 255, 255), thickness=-1)

        # Build perimeter points after derotation
        for px, py in cntPoints1:
            p = fitz.Point(px, py) * derotationMatrix
            shapeePerimeter.append([p[0], p[1]])

        # Apply flip and rotation to this polygon only
        shapeePerimeter = np.flip(np.array(shapeePerimeter), 1).tolist()
        shapeePerimeter = rotate_polygon(shapeePerimeter, rotationangle, rotationOld, width, height)

        # Append in [[polygon_points]] format
        processed_shapes.append(shapeePerimeter)

    return processed_shapes


def process_grouped_shapes(grouped_shapes, imgg, dxfratio, rotationangle, derotationMatrix, rotationOld, width, height):
    """
    Processes grouped shapes (merged polygons).

    grouped_shapes: list of [vertices_list, None, None, colors_list]
    Returns: list of [coords, area, perimeter, color]
    """
    processed_shapes = []

    for group in grouped_shapes:
        merged_vertices = group[0]   # all vertices from the group
        colors = group[3]            # list of colors (can pick the first or merge info)

        cntPoints = []
        cntPoints1 = []
        shapeePerimeter = []

        blackImgShapes = np.zeros(imgg.shape[:2], dtype="uint8")
        blackImgShapes = cv2.cvtColor(blackImgShapes, cv2.COLOR_GRAY2BGR)

        for pt in merged_vertices:
            x = pt[0] * dxfratio
            y = pt[1] * dxfratio
            if rotationangle == 0 and y < 0:
                y = -y
            cntPoints.append([int(x), int(y)])
            cntPoints1.append([x, y])

        if not cntPoints:
            continue

        # Draw contour for area/perimeter
        contour_np = np.array(cntPoints, dtype=np.int32)
        cv2.drawContours(blackImgShapes, [contour_np], -1, (255, 255, 255), thickness=-1)

        area = cv2.contourArea(contour_np)
        perimeter = cv2.arcLength(contour_np, True)

        # Apply derotation + transform
        for px, py in cntPoints1:
            p = fitz.Point(px, py) * derotationMatrix
            shapeePerimeter.append([p[0], p[1]])

        # Flip + rotate polygon
        shapeePerimeter = np.flip(np.array(shapeePerimeter), 1).tolist()
        shapeePerimeter = rotate_polygon(shapeePerimeter, rotationangle, rotationOld, width, height)

        # Pack result in full structure
        processed_shapes.append([shapeePerimeter, area, perimeter, colors[0] if colors else (0,0,0)])

    return processed_shapes

class DSU:
    def __init__(self, n: int):
        self.p = list(range(n))
        self.r = [0]*n
    def find(self, x: int) -> int:
        while self.p[x] != x:
            self.p[x] = self.p[self.p[x]]
            x = self.p[x]
        return x
    def union(self, a: int, b: int):
        ra, rb = self.find(a), self.find(b)
        if ra == rb: return
        if self.r[ra] < self.r[rb]:
            self.p[ra] = rb
        elif self.r[ra] > self.r[rb]:
            self.p[rb] = ra
        else:
            self.p[rb] = ra
            self.r[ra] += 1

# ---------- small helpers ----------
def _ensure_vertices_list(verts_any) -> List[Tuple[float, float]]:
    """Accept [(x,y), ...] or [[(x,y), ...]] and return a flat list of (x,y) floats."""
    if verts_any and isinstance(verts_any[0], (list, tuple)) and len(verts_any) == 1 \
       and verts_any[0] and isinstance(verts_any[0][0], (list, tuple)):
        verts_any = verts_any[0]
    return [(float(x), float(y)) for (x, y) in verts_any]

def _bbox(verts):
    xs = [p[0] for p in verts]; ys = [p[1] for p in verts]
    return (min(xs), min(ys), max(xs), max(ys))

def _boxes_manhattan_gap(b1, b2):
    minx1, miny1, maxx1, maxy1 = b1
    minx2, miny2, maxx2, maxy2 = b2
    dx = max(0.0, max(minx1 - maxx2, minx2 - maxx1))
    dy = max(0.0, max(miny1 - maxy2, miny2 - maxy1))
    return dx, dy

def _shapes_quick_close(verts1, verts2, axis_threshold):
    """Quick AABB gate then vertex-vertex proximity check (axis threshold)."""
    b1 = _bbox(verts1); b2 = _bbox(verts2)
    dx_box, dy_box = _boxes_manhattan_gap(b1, b2)
    if dx_box > axis_threshold or dy_box > axis_threshold:
        return False
    for (x1,y1) in verts1:
        for (x2,y2) in verts2:
            if abs(x1 - x2) <= axis_threshold and abs(y1 - y2) <= axis_threshold:
                return True
    return False

# --------------------------
# 1) Gather groups and produce unioned polygons
# --------------------------
def gather_and_union_groups(
    hatched_areas: List[Any],
    axis_threshold: float = 0.5,
    require_diff_color: bool = True,
    skip_colors: Set[Tuple[int,int,int]] = None,
) -> List[Tuple[List[Tuple[float,float]], float, float, Tuple[int,int,int]]]:
    """
    Group shapes that are close (chain merging), then UNITE the original polygons of each group.
    Returns list of (coords, area, perimeter, color) where coords is the outer boundary of each polygon
    produced by the union (for MultiPolygon each part is appended as a separate result).
    - hatched_areas items: [ vertices, area, perimeter, color ]
    """
    if skip_colors is None:
        skip_colors = set()

    # collect valid polygon geometries and metadata
    polys = []
    colors = []
    areas = []
    perims = []
    for item in hatched_areas:
        if not item or len(item) < 4:
            continue
        verts_any, area, perim, color = item[0], item[1], item[2], item[3]
        if color in skip_colors:
            continue
        verts = _ensure_vertices_list(verts_any)
        if len(verts) < 3:
            continue
        try:
            poly = Polygon(verts)
            if not poly.is_valid or poly.is_empty:
                # try fix by buffering 0
                poly = poly.buffer(0)
            if poly.is_empty:
                continue
            polys.append(poly)
            colors.append(tuple(color))
            areas.append(float(area) if isinstance(area, (int,float)) else poly.area)
            perims.append(float(perim) if isinstance(perim, (int,float)) else poly.length)
        except Exception:
            continue

    m = len(polys)
    if m == 0:
        return []

    # group indices using DSU with chain merging
    dsu = DSU(m)
    for i in range(m):
        for j in range(i+1, m):
            if require_diff_color and colors[i] == colors[j]:
                continue
            verts_i = list(polys[i].exterior.coords)
            verts_j = list(polys[j].exterior.coords)
            if _shapes_quick_close(verts_i, verts_j, axis_threshold):
                dsu.union(i, j)

    # collect components
    comp = {}
    for i in range(m):
        r = dsu.find(i)
        comp.setdefault(r, []).append(i)

    results = []
    for root, members in comp.items():
        group_polys = [polys[k] for k in members]
        try:
            unioned = unary_union(group_polys)
        except Exception:
            # fallback: union iteratively
            u = group_polys[0]
            for p in group_polys[1:]:
                u = u.union(p)
            unioned = u

        # unioned might be Polygon, MultiPolygon, GeometryCollection
        def _handle_polygon(polygon_geom, rep_color):
            coords = [(float(x), float(y)) for x,y in polygon_geom.exterior.coords]
            area = polygon_geom.area
            perim = polygon_geom.length
            results.append((coords, area, perim, rep_color))

        # choose representative color: first member's color
        rep_color = colors[members[0]] if members else (0,0,0)

        if isinstance(unioned, Polygon):
            _handle_polygon(unioned, rep_color)
        elif isinstance(unioned, MultiPolygon) or isinstance(unioned, GeometryCollection):
            # GeometryCollection may have polygons inside
            for geom in getattr(unioned, "geoms", []):
                if isinstance(geom, Polygon):
                    _handle_polygon(geom, rep_color)
        else:
            # unexpected geometry — skip
            continue

    return results

# --------------------------
# 2) process_grouped_shapes -> produce processed list ready for drawing
# --------------------------
def process_grouped_shapes(
    grouped_polys: List[Tuple[List[Tuple[float,float]], float, float, Tuple[int,int,int]]],
    imgg, dxfratio, rotationangle, derotationMatrix, rotationOld, width, height
) -> List[Tuple[List[Tuple[float,float]], float, float, Tuple[int,int,int]]]:
    """
    For each grouped polygon (coords, area, perim, color), scale, derotate, rotate and return
    processed polygon in same (coords, area, perim, color) format, coords as list of [x,y] floats.
    """
    processed = []
    for coords, area, perim, color in grouped_polys:
        if not coords:
            continue

        cntPoints = []
        cntPoints1 = []
        # convert/scaling
        for (x,y) in coords:
            xs = x * dxfratio
            ys = y * dxfratio
            if rotationangle == 0 and ys < 0:
                ys = -ys
            cntPoints.append([int(xs), int(ys)])
            cntPoints1.append([xs, ys])

        if not cntPoints1:
            continue

        # build derotated perimeter points
        shapeePerimeter = []
        for px, py in cntPoints1:
            p = fitz.Point(px, py) * derotationMatrix
            shapeePerimeter.append([p[0], p[1]])

        # flip and rotate (use your rotate_polygon)
        shapeePerimeter = np.flip(np.array(shapeePerimeter), 1).tolist()
        shapeePerimeter = rotate_polygon(shapeePerimeter, rotationangle, rotationOld, width, height)

        # ensure type and length
        final_coords = [(float(x), float(y)) for x,y in shapeePerimeter]
        if len(final_coords) < 3:
            continue

        processed.append((final_coords, area, perim, color))

    return processed

    
def mainFunctionDrawImgPdf(datadoc,dxfpath, dxfratio,SearchArray,pdfpath=0,pdfname=0,pdf_content=0):
  OutputPdfStage1='BB Trial.pdf'
  if pdf_content:
     FinalRatio= RetriveRatio(datadoc,dxfpath,pdf_content)
  else:
      FinalRatio= RetriveRatio(datadoc,dxfpath)
    

  # hatched_areas = get_hatched_areas(dxfpath,FinalRatio)
  # hatched_areas=remove_duplicate_shapes(new_hatched_areas)
  if pdf_content:
    img=pdftoimg(datadoc,pdf_content)
  else:
     img=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
  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)

  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,Legendarray = get_hatched_areas(datadoc,dxfpath,FinalRatio,rotationangle,SearchArray)
    
  nearby,grouped_shapes_final=find_nearby_vertices(hatched_areas)
  processed_intersections = process_polygons(nearby, img, dxfratio, rotationangle, derotationMatrix,rotationOld,width,height)

  groups = gather_and_union_groups(hatched_areas, axis_threshold=0.5,
                                 require_diff_color=True,
                                 skip_colors={(0,0,0),(255,255,255)})

  processed_grouped_shapes = process_grouped_shapes(groups,
    imgg, dxfratio, rotationangle, derotationMatrix, rotationOld, width, height)
    
  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
  ColorCheck=[]
    
  XMLArea = []
  XMLPerimeter = []


  for polygon in hatched_areas:
      cntPoints = []
      cntPoints1 = []
      shapeePerimeter = []
      shapeeArea = []

      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

      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']

      if(int(NewColors[0])==255 and int(NewColors[1])==255 and int(NewColors[2])==255):
        WhiteImgFinal = cv2.bitwise_and(blackImgShapes,imgg)
        flipped=flip(WhiteImgFinal)
        

        imgslice = WhiteImgFinal[y:y+h, x:x+w]
        if(imgslice.shape[0] != 0 and imgslice.shape[1] != 0):
            flippedSlice=flip(imgslice)
            
    
        # 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
    
            
    
            # Append dominant color to ColorCheck and update NewColors
            if dominant_color is not None:
                ColorCheck.append(dominant_color)
    
                NewColors = None
    
                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])
    
                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

            
      cv2.drawContours(imgg, [np.array(cntPoints)], -1, ([NewColors[2],NewColors[1],NewColors[0]]), thickness=-1)

      vertices_area = [
        [[float(x), float(y)] for x, y in shapeeArea],  # vertices
        str(polygon[1]),NewColors                                  # area
      ]
      XMLArea.append(vertices_area)

      vertices_Perimeter = [
        [[float(x), float(y)] for x, y in shapeePerimeter],  # vertices
        str(polygon[1]),NewColors                                  # area
      ]
      XMLPerimeter.append(vertices_Perimeter)
                    
      annot11 = page2.add_polygon_annot( points=shapeeArea)  # 'Polygon'
      annot11.set_border(width=0.2)
      annot11.set_colors(stroke=(int(NewColors[0])/255,int(NewColors[1])/255,int(NewColors[2])/255), fill= (int(NewColors[0])/255,int(NewColors[1])/255,int(NewColors[2])/255) )
      annot11.set_info(content=str(polygon[1])+' sq m',subject='Area Measurement', title="ADR Team")
      annot11.set_opacity(0.8)
      # annot.set_line_ends(fitz.PDF_ANNOT_LE_DIAMOND, fitz.PDF_ANNOT_LE_CIRCLE)
      annot11.update()



      annot12 = page2.add_polyline_annot( points=shapeePerimeter )  # 'Polygon'
      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_opacity(0.8)
      # annot.set_line_ends(fitz.PDF_ANNOT_LE_DIAMOND, fitz.PDF_ANNOT_LE_CIRCLE)
      annot12.update()
      i += 1
  alpha = 0.8  # Transparency factor.

  for shapes in processed_intersections:
      annot13 = page2.add_polyline_annot(points=shapes)  # 'Polygon'
      annot13.set_border(width=0.8)
      annot13.set_colors(stroke=(0,0,1))
      annot13.set_info(content='Perimeter='+str(1)+' m',subject='Perimeter Measurement', title="Trim Measurement")
      annot13.set_opacity(0.7)
      annot13.update()

  for coords, area, perimeter, color in processed_grouped_shapes:

    if len(coords) < 3:
        continue

    annot14 = page2.add_polyline_annot(points=coords)
    annot14.set_border(width=0.8)
    annot14.set_colors(fill=(1, 0, 0))
    annot14.set_info(content='Perimeter='+str(1)+' m',subject='Perimeter Measurement', title="Skirting Measurement")
    annot14.set_opacity(0.7)
    annot14.update()

    

    
#   with open("3.2_custom_columns.xml", "w", encoding="utf-8") as f:
#         f.write(column_xml)

  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':'first',
            'Texts':'first',
            'Comments':'first'
      
        }).reset_index()
    
  SimilarAreaDictionary = grouped_df
  # doc.save(OutputPdfStage1)
  modified_pdf_data = doc.tobytes()
  # OutputPdfStage2=adjustannotations(modified_pdf_data)
  OutputPdfStage2,annotations_data=adjustannotations(modified_pdf_data,Legendarray)
    
  allvertices = annotations_data
  hatchcolorR= '0'
  hatchcolorG= '1'
  hatchcolorB= '1'
  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 = 1
  perimeter = 1

  import colorsys

  annotations=[]
  for shapeinvertices in allvertices:
      # print("shapeinvertices[3] = ",shapeinvertices[3])
      
      if(shapeinvertices[3] == None):
          rn=0
          gn=0
          bn=0

      else:
          rn=shapeinvertices[3][0]-150/255
          gn=shapeinvertices[3][1]-150/255
          bn=shapeinvertices[3][2]-150/255
    
      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)
      # print(r2,g2,b2)
      R=str(r2)
      G=str(g2)
      B=str(b2)
      # print(R,G,B)
      r2, g2, b2 = colorsys.hsv_to_rgb(h, s2, v2)
      color_str = f"{r2:.3f} {g2:.3f} {b2:.3f}"
      hatch_color = f"{float(hatchcolorR):.0f} {float(hatchcolorG):.0f} {float(hatchcolorB):.0f}"
      # print(color_str,hatch_color)
      if(shapeinvertices[1] is not None):
    
        annotations.append(
            {
    
                'vertices': shapeinvertices[0], # [[x,y],[x1,y1],[....]] position of ur markup
                'text': str(shapeinvertices[1])+' sq m',
                'author': 'ADR',
                'custom_data': {'Legend': shapeinvertices[4],'NBS':shapeinvertices[5]},#identify custom colums here as( Column name: Text to add )
                'type_internal': 'Bluebeam.PDF.Annotations.AnnotationMeasureArea',
                'subject': 'Area Measurement',
                'label': 'label',#change label to whatever u want
                'opacity': '0.5',#opacity of ur shape fill
                'color': color_str,# normalized (RGB --> R/255 G/255 B/255)
                'linestyle': LinestyleTemplates['Solid'].format(w=0),
                'hatchstyle': HatchFunctions['DiagonalDown'](color_str, hatch_color),#this is the hatchstyle and the hatch color fill and the hatch line color,
                #if u want the hatch to be none (as in a solid color only) just pass HatchFunctions['None'] without any colors here
                'hatchLinescolor':hatch_color,
    
    
            }
        )
      elif(shapeinvertices[2] is not None):
          
        annotations.append(
          {

              'vertices': shapeinvertices[0], # [[x,y],[x1,y1],[....]] position of ur markup
              'text': str(shapeinvertices[2])+' m',
              'author': 'ADR',
              'custom_data': {'Legend': shapeinvertices[4],'NBS':shapeinvertices[5]},#identify custom colums here as( Column name: Text to add )
              'type_internal': 'Bluebeam.PDF.Annotations.AnnotationMeasurePerimeter',
              'subject': 'Perimeter Measurement',
              'label':'label2',
              'opacity': '0.7',#opacity of ur shape fill
              'color': R+ ' '+G + ' '+B,# normalized (RGB --> R/255 G/255 B/255)
              'linestyle': LinestyleTemplates['Solid'].format(w=2), # LineStyles as in BB ,this w is the linewidth
              'hatchstyle': '',
              'hatchLinescolor':'',

          }
      )


    
        



  column_order = ['Legend','NBS'] #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, 'FF-Ceiling.bax', column_order, pdfWidth, pdfHeight
  )

  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("Adjusted_PDF.pdf", "wb") as f:
  #   f.write(OutputPdfStage2)
      
  # doc2 = fitz.open(stream=OutputPdfStage2, filetype="pdf")
  # doc2 = fitz.open(stream=OutputPdfStage2, filetype="pdf")
      
  doc2 =fitz.open('pdf',OutputPdfStage2)
  if pdf_content:
     gc,spreadsheet_service,spreadsheetId, spreadsheet_url , namepathArr=google_sheet_Legend.legendGoogleSheets(SimilarAreaDictionary , pdfname,pdfpath,pdf_content)  
  else:
    gc,spreadsheet_service,spreadsheetId, spreadsheet_url , namepathArr=google_sheet_Legend.legendGoogleSheets(SimilarAreaDictionary , pdfname,pdfpath)
  # dbxTeam=tsadropboxretrieval.ADR_Access_DropboxTeam('user')
  # md, res =dbxTeam.files_download(path= pdfpath+pdfname)
  # data = res.content
  # doc=fitz.open("pdf", data)
  # list1=pd.DataFrame(columns=['content', 'creationDate', 'id', 'modDate', 'name', 'subject', 'title'])
  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,image_new1, SimilarAreaDictionary ,spreadsheetId, spreadsheet_url , namepathArr , list1,hatched_areas, bax_xml, column_xml

  # doc.save('Testing(2.7).pdf')
  # return doc,image_new1#, SimilarAreaDictionary ,spreadsheetId, spreadsheet_url , namepathArr , list1,hatched_areas

# datadoc='/content/3.3 - Ceiling finishes - Example 1 - Sheet 1.pdf' #pdf path here
# dxfpath='/content/3.3 - Ceiling finishes - Example 1 - Sheet 1.dxf'#dxfpath here
# dxfratio=28.3464527867108
# doc,image_new1=mainFunctionDrawImgPdf(datadoc,dxfpath, dxfratio)
# cv2_imshow(image_new1)