Update pilecaps_adr.py

pilecaps_adr.py

@@ -6,27 +6,18 @@ Automatically generated by Colaboratory.
 Original file is located at
     https://colab.research.google.com/drive/16RHtRae7VU_fqHMAjOUL4ET5slEFo3pf
 """
-
 # pip install pdf-annotate
-
 # pip install pdf-annotate
-
 #pip install pdf2image
-
 #!pip install -q gradio
-
 #pip install pygsheets
-
 # !apt-get install poppler-utils
-
 import numpy as np 
 import cv2 
 #from google.colab.patches import cv2_imshow
 from matplotlib import pyplot as plt 
 #from pdf2image import convert_from_path
-
 import math
-
 import pandas as pd
 import random
 # import imutils
@@ -54,10 +45,10 @@ def detectCircles(imgOriginal ):
   er1=cv2.erode(imgGry1,kernel, iterations=2)
  
   er1=cv2.dilate(er1,kernel, iterations=1)
-  gray_blurred = cv2.blur(er1, (3,3 ))
+  # gray_blurred = cv2.blur(er1, (3,3 ))
   # Apply Hough transform on the blurred image.
    # min distance between circles,  Upper threshold for the internal Canny edge detector.
-  detected_circles = cv2.HoughCircles( gray_blurred, cv2.HOUGH_GRADIENT, 1, 50, param1= 550,
+  detected_circles = cv2.HoughCircles( er1, cv2.HOUGH_GRADIENT, 1, 50, param1= 550,
                     param2 =21, minRadius = 20, maxRadius = 40) #18 param2
     
   # Draw circles that are detected.
@@ -91,7 +82,7 @@ def detectSmallCircles(img ):
       detected_circles = np.round(detected_circles[0, :]).astype("int")
     #DRAW CIRCLES
       for (x, y, r) in detected_circles:
-        cv2.circle(im, (x, y), r+1, (255, 255, 255), -1)
+        cv2.circle(im, (x, y), r+3, (255, 255, 255), -1)
   # cv2_imshow(im)
   return im
 # c=detectCircles(img)
@@ -175,7 +166,6 @@ def euclidian_distance(point1, point2):
 def removeDashedLinesSmall(img4, imgBW ,max,min):
 
   imgBW=cv2.cvtColor(imgBW,cv2.COLOR_GRAY2BGR)
-
   imgLines= cv2.HoughLinesP(img4,1,np.pi/100,20,minLineLength=(max-min)//2.2,maxLineGap = 70)  #2.1
 
   for i in range(len(imgLines)):
@@ -197,14 +187,14 @@ def ConnectBeamLines(smalldashesOut):
   imgLines= cv2.HoughLinesP(green1,0.05,np.pi/250,10,minLineLength=25,maxLineGap = 20)  #was w-h , gap=150  #50
   for i in range(len(imgLines)):
       for x1,y1,x2,y2 in imgLines[i]:
-          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),1)
+          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),2)
 
-  imgLines= cv2.HoughLinesP(green1,0.3,np.pi/360,10,minLineLength=25,maxLineGap = 20)  #try 180
+  imgLines= cv2.HoughLinesP(green1,1,np.pi/250,37,minLineLength=25,maxLineGap = 22)  #try 180
 
 
   for i in range(len(imgLines)):
       for x1,y1,x2,y2 in imgLines[i]:
-          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),1)
+          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),2)
   # cv2_imshow(green2)
   return green2
 
@@ -226,37 +216,47 @@ def ChangeBrightness(img,k):
   return imgdarker
 
 def preprocessold(img,number):
-  
-  # imcopy=detectCircles(img)
-  blurG = cv2.GaussianBlur(ChangeBrightness(img,6),(3,3),0)
- 
-  imgGry = cv2.cvtColor(blurG, cv2.COLOR_BGR2GRAY)
 
+  blurG = cv2.GaussianBlur(ChangeBrightness(img,6),(3,3),0 )
+  imgGry = cv2.cvtColor(blurG, cv2.COLOR_BGR2GRAY)
   kernel=np.ones((3,3),np.uint8)
-
   er1=cv2.dilate(imgGry,kernel, iterations=2) #thinning
-
-  er2=cv2.erode(er1,kernel, iterations=3) #thicken
-  er3=cv2.dilate(er2,kernel, iterations=4)
-
   if number == 0:
-    ret3, thresh = cv2.threshold(er3, 200, 255, cv2.THRESH_BINARY_INV  + cv2.THRESH_OTSU)
+    ret3, thresh = cv2.threshold(er1, 0, 255, cv2.THRESH_BINARY_INV  + cv2.THRESH_OTSU)
   else:
-    ret3, thresh = cv2.threshold(er3, 220, 255, cv2.THRESH_BINARY_INV) #`140 - 141
-  # cv2_imshow(thresh)
+    ret3, thresh = cv2.threshold(er1, 220, 255, cv2.THRESH_BINARY_INV) #`140 - 141
+
   return thresh
-# preprocessold(img,0)
 
-def preprocess(imgOriginal,number,green2):
+def preprocess(imgOriginal,number,green2,flag,layeredflag,BlackmaskDetected1=0):
   #first preprocessing ( old method - black img with white shapes)
   img1=preprocessold(imgOriginal,number)
-  kernel0=np.ones((3,3),np.uint8)
-  img1=cv2.dilate(img1,kernel0, iterations=3)
-  green3=ChangeBrightness(green2,6)
-  anding=cv2.bitwise_and(green3,green3,mask=img1)
-  anding = cv2.cvtColor(anding , cv2.COLOR_BGR2GRAY)
-
-  return anding
+  anding=cv2.bitwise_and(green2,green2,mask=img1)
+  anding = cv2.cvtColor(anding, cv2.COLOR_BGR2GRAY)
+  ret3, thresh2 = cv2.threshold(anding, 0, 255, cv2.THRESH_BINARY  + cv2.THRESH_OTSU)
+  if layeredflag.startswith('layer'):
+     thresh2=cv2.bitwise_and(thresh2,thresh2,mask=BlackmaskDetected1)
+  threshcontours, threshHier = cv2.findContours(thresh2, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+
+  finalcnts=[]
+  BlackmaskALL = np.zeros(imgOriginal.shape[:2], dtype="uint8")
+  for cnt in threshcontours:
+    Blackmask = np.zeros(imgOriginal.shape[:2], dtype="uint8")
+    area1 = cv2.contourArea(cnt)
+    if (area1 > 2000 ):
+        x, y , width, height = cv2.boundingRect(cnt)
+        if flag.startswith('perimeter'):
+          kernel=np.ones((2,2),np.uint8)
+          cv2.drawContours(Blackmask,[cnt],0,(255,255,255), 6)
+          Blackmask=cv2.dilate(Blackmask,kernel, iterations=1)
+        elif flag.startswith('area'):
+          kernel=np.ones((2,2),np.uint8)
+          cv2.drawContours(Blackmask,[cnt],0,(255,255,255), 5)
+          Blackmask=cv2.erode(Blackmask,kernel, iterations=1)
+        contours1, hier1 = cv2.findContours(Blackmask, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+        finalcnts.append(contours1)
+  finalcnts=tuple(finalcnts)
+  return finalcnts
 
 """# ROI (levels)
 ## Detect regions with specific color and mask them
@@ -335,7 +335,7 @@ def colorOrder(img,finalColorArray):
   
   return res
 
-def getinnerColor(BlackmaskDetected,img,detectedColors,finalColorArray,num1,num2,flag,eachcolor):
+def getinnerColor(BlackmaskDetected,img,detectedColors,finalColorArray,ratioarea,ratioperim,flag,eachcolor):
 
   countBlackMasks=0
   xored=detectedColors
@@ -416,14 +416,7 @@ def allLevelsofColor(BlackmaskDetected,img,levelonly, invertedmask,color,finalCo
             firstLevel=cv2.bitwise_and(invertedmask,invertedmask,mask=Blackmask)
             ####remove black pixels and let them be all white 
             # get (i, j) positions of all RGB pixels that are black (i.e. [0, 0, 0])
-            black_pixels = np.where(
-                (firstLevel[:, :, 0] == 0) & 
-                (firstLevel[:, :, 1] == 0) & 
-                (firstLevel[:, :, 2] == 0)
-            )
-
-            # set those pixels to white
-            firstLevel[black_pixels] = [255, 255, 255]
+            firstLevel[np.all(firstLevel == (0,0,0), axis=-1)] = (255, 255, 255)
             firstLevel1=cv2.bitwise_and(levelonly,firstLevel)
             # cv2_imshow(firstLevel1)
 
@@ -451,7 +444,7 @@ def allLevelsofColor(BlackmaskDetected,img,levelonly, invertedmask,color,finalCo
             # cv2_imshow(Blackmask)
   return firstLevel1, BlackmaskDetected
     
-def getColoredContour(mask,img,finalColorArray,num1,num2,flag,eachcolor):
+def getColoredContour(mask,img,finalColorArray,ratioarea,ratioperim,flag,eachcolor):
     print('uuuuuuuuummmmmmmmmmmmm')
 
     ColoredContour, Coloredhierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
@@ -480,19 +473,17 @@ def getColoredContour(mask,img,finalColorArray,num1,num2,flag,eachcolor):
             if extrema == (0, 0) :#and extremaB==(0,0): # if image is not black --> has a colored mask within
               break
     
-    levelOnly,invertedmask,BlackmaskDetected=getinnerColor(Blackmask,img,detectedColors,finalColorArray,num1,num2,flag,eachcolor) #mask inner levels b abyad 
+    levelOnly,invertedmask,BlackmaskDetected=getinnerColor(Blackmask,img,detectedColors,finalColorArray,ratioarea,ratioperim,flag,eachcolor) #mask inner levels b abyad 
     firstLevel1, BlackmaskDetected1= allLevelsofColor(BlackmaskDetected,img,levelOnly, invertedmask,eachcolor,finalColorArray)
-    # cv2.imshow('kk',firstLevel1)
-    print('AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA')
     return firstLevel1,invertedmask, BlackmaskDetected1
 
 """#  contours"""
 
-def findContoursFullImage(green2,img,number,finalColorArray,num1,num2,flag,color=[0,0,0]):
+def findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,flag,color=[0,0,0]):
   if number == 0:
-    thresh=preprocess(img,number,green2)
+    contourss=preprocess(img,number,green2,flag,'nolayer')
 
-    contourss, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    # contourss, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
     return contourss
   else:
     mask, detectedColors, rgbcolor =DetectColor(img,color)
@@ -502,18 +493,13 @@ def findContoursFullImage(green2,img,number,finalColorArray,num1,num2,flag,color
     
     extrema = pil_image.convert("L").getextrema()
     if extrema != (0, 0): # if image is not black --> has a colored mask within
-      coloredregions,invertedmask,BlackmaskDetected1=getColoredContour(mask,img,finalColorArray,num1,num2,flag,color)
-      thresh=preprocess(coloredregions,number,green2)
-      x=cv2.bitwise_and(thresh,thresh,mask=BlackmaskDetected1)
-      contourss, hierarchy = cv2.findContours(x, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+      coloredregions,invertedmask,BlackmaskDetected1=getColoredContour(mask,img,finalColorArray,ratioarea,ratioperim,flag,color)
+      contourss=preprocess(coloredregions,number,green2,flag,'layer',BlackmaskDetected1)
       return contourss,rgbcolor ,invertedmask 
 
     else:
-      print('ELSEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEE')
-      thresh=preprocess(img,number,green2)
+      contourss=preprocess(img,number,green2,flag,'nolayer')
 
-      contourss, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-      hierarchy = hierarchy[0] 
       return contourss,color ,mask
 
 
@@ -545,43 +531,49 @@ def StraightenImage(contour,imgArea):
     ##############  
     return angleR,width,height
 
-def getAreasPerimeter(green2,img,number,num1,num2,flag,finalColorArray,color=[0,0,0]):
+def getAreasPerimeter(green2,img,number,ratioarea,ratioperim,flag,finalColorArray,color=[0,0,0]):
   appended=[]
   if number==0:
-    contourss=findContoursFullImage(green2,img,number,finalColorArray,num1,num2,flag,color)
+    contourss=findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,flag,color)
   else:
-    contourss=findContoursFullImage(green2,img,number,finalColorArray,num1,num2,flag,color)[0]
-
-  for contour in contourss:
-
-    area1 = cv2.contourArea(contour)
-    perimeter1 = cv2.arcLength(contour, True)
-    x, y , width, height = cv2.boundingRect(contour) 
-
-    angleR,widthR ,heightR= StraightenImage(contour,img)
-
-    if (angleR != 90.0 and angleR != -90.0 and angleR != 0.0 and angleR != -0.0 ): #inclined b ay degree 
-        width=widthR
-        height=heightR
-    if (area1 > 4000 ): #check perimeter kman fl condition  -- 2800
-      if num1!=0 and num2!=0:
-        #if flag=='area':
-          # addedMargin=area1+perimeter1*2
-          # areaa=round(addedMargin* (num1/(num2+perimeter1*2) ), 3) # true value of area of any shape/ area px value of same shape
-          areaa=round(area1*num1,3)
-          appended.append([areaa,width,height])
+    contourss=findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,flag,color)[0]
+
+  for contour in range(len(contourss)):
+      #   imgArea1=img.copy()
+      area1 = cv2.contourArea(contourss[contour][0])
+      if (area1 >2000 ):
+        perimeter = cv2.arcLength(contourss[contour][0],True)
+        approx = cv2.approxPolyDP(contourss[contour][0], 0.01* perimeter, True)
+        perimeter1 = cv2.arcLength(approx, True)
+        # approx = cv2.approxPolyDP(contourss[contour][0], 0.01* perimeter, True)
+        # area1 = cv2.contourArea(approx)
+        x, y , width, height = cv2.boundingRect(contourss[contour][0])
+
+        angleR,widthR ,heightR= StraightenImage(contourss[contour][0],img)
+
+        if (angleR != 90.0 and angleR != -90.0 and angleR != 0.0 and angleR != -0.0 ): #inclined b ay degree
+            width=widthR
+            height=heightR
+        if (area1 > 2000 ): #check perimeter kman fl condition  -- 2800
+          # print('areass')
+          if ratioarea!=0 and ratioperim!=0:
+            # print('numss')
+            # if flag=='area':
+              # addedMargin=area1+perimeter1*2
+              areaa=round(area1* ratioarea , 2) # true value of area of any shape/ area px value of same shape
+              appended.append([areaa,width,height])
 
         #else:
-          #perimeter=round(perimeter1*(num1/num2),3)
+          #perimeter=round(perimeter1*(ratioarea/ratioperim),3)
           #appended.append([perimeter,width,height])
 
   return appended
 
 
-def FillDictionary(green2,SimilarAreaDictionary,img,number,num1,num2,flag,finalColorArray,rgbcolor=[0,0,0],color=[0,0,0]):
+def FillDictionary(green2,SimilarAreaDictionary,img,number,ratioarea,ratioperim,flag,finalColorArray,rgbcolor=[0,0,0],color=[0,0,0]):
   #fills dictionary with key areas and number of occurences
   print('wttttt')
-  areas_Perimeters=sorted(getAreasPerimeter(green2,img,number,num1,num2,flag,finalColorArray,color) )
+  areas_Perimeters=sorted(getAreasPerimeter(green2,img,number,ratioarea,ratioperim,flag,finalColorArray,color) )
   
   indices=[]
   colorRanges=[[255,153,153],[51,255,51],[201,56,147],[255,0,0],[255,0,255],[0,102,204],[102,0,102],[153,0,76],[200,92,135],[52,161,99],[235,250,24],[40,30,170],[98,149,63],[100,30,179],[200,55,67],[150,80,200],[0,102,102],[250,28,191],[101,27,101],[230,150,76],[3,65,127],[114,39,39],[250,36,100],[180,30,40],[10,250,60],[140,30,253],[114,58,245],[47,255,255],[18,236,206],[225,105,29],[189,65,121],[206,204,48],[126,7,247],[3,168,251]]
@@ -691,7 +683,8 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
       if eachcolor==firstcolor: # 3shan a3rf el array of colors et3adet kam mara - to support embedded levels 
         counter+=1
 
-      contourss,rgbcolor,invertedmask=findContoursFullImage(green2,maskDone,number,finalColorArray,ratioarea,ratioperim,flag,eachcolor) 
+      contourss,rgbcolor,invertedmask=findContoursFullImage(green2,maskDone,number,finalColorArray,ratioarea,ratioperim,'area',eachcolor) 
+      contourssA,rgbcolor,invertedmask=findContoursFullImage(green2,maskDone,number,finalColorArray,ratioarea,ratioperim,'perimeter',eachcolor) 
       SimilarAreaDictionary, colorsUsed , areas_Perimeters= FillDictionary(green2,SimilarAreaDictionary,maskDone,number,ratioarea,ratioperim,flag,finalColorArray,rgbcolor,eachcolor)
   
       a = SimilarAreaDictionary.to_numpy()
@@ -699,25 +692,31 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
       # for component in zip(contourss,hierarchy):
       #     contour = component[0]
       #     currentHierarchy = component[1]
-      for contour in contourss:
+      for contour in range(len(contourss)):
           shape=[]
           
           # cv2_imshow(imgStraight)
-          area1 = cv2.contourArea(contour)
-          perimeter1 = cv2.arcLength(contour, True)  
-          if (area1 > 4000 ): #check perimeter kman fl condition  -- 2800
-            angleR,widthR ,heightR= StraightenImage(contour,imgArea1)
-            rect = cv2.minAreaRect(contour)
-    
-            (center, (width, height), angleR) = cv2.minAreaRect(contour)
-            
+          area1 = cv2.contourArea(contourss[contour][0])
+          
+          # perimeter1 = cv2.arcLength(contourss[contour][0], True)  
+          if (area1 > 2000 ): #check perimeter kman fl condition  -- 2800
+            rect = cv2.minAreaRect(contourss[contour][0])
+
+            angleR,widthR ,heightR= StraightenImage(contourss[contour][0],imgArea1)
+            x, y , width, height = cv2.boundingRect(contourss[contour][0])
+            # (center, (width, height), angleR) = cv2.minAreaRect(contourss[contour][0])
+
             box = cv2.boxPoints(rect)
             box = box.astype('int')
             print(box)
 
-            x, y , width, height = cv2.boundingRect(contour) 
-            # cv2.drawContours(imgArea1,contours=[box], contourIdx=0 , color=(0, 0, 255), thickness=10) 
-            approx = cv2.approxPolyDP(contour, 0.005 * perimeter1, True)
+            x, y , width, height = cv2.boundingRect(contourss[contour][0])
+            perimeter = cv2.arcLength(contourss[contour][0], True)
+            approx = cv2.approxPolyDP(contourssA[contour][0], 0.0002* perimeter, True)
+            area1 = cv2.contourArea(approx)
+            approx = cv2.approxPolyDP(contourss[contour][0], 0.01 * perimeter, True) #0.0009
+            perimeter1 = cv2.arcLength(approx, True)
+
             for point in approx:
                 x1, y1 = point[0]
                 
@@ -747,7 +746,8 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
               areaa=round(area1* ratioarea, 3) # true value of area of any shape/ area px value of same shape
               
               # elif flag=='perimeter':
-              perimeterr=round(perimeter1* ratioperim, 3)
+              perimeterr=round(perimeter1* ratioperim,3)
+              lengthShape=round(lengthShape* ratioperim,3)
             else:
               areaa=area1
               perimeterr=perimeter1
@@ -776,7 +776,7 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
                         passed=1
                           # print(index)
             # cv2.drawContours(imgArea1, [contour], 0, (int(rgbcolor[2]), int(rgbcolor[1]), int(rgbcolor[0])), -1)
-                        cv2.drawContours(imgArea1, [contour], 0, ( int(SimilarAreaDictionary['B'].loc[i]),  int(SimilarAreaDictionary['G'].loc[i]), int(SimilarAreaDictionary['R'].loc[i])), -1)
+                        cv2.drawContours(imgArea1, [contourss[contour][0]], 0, ( int(SimilarAreaDictionary['B'].loc[i]),  int(SimilarAreaDictionary['G'].loc[i]), int(SimilarAreaDictionary['R'].loc[i])), -1)
                         annot = page.add_polygon_annot( points=shape )  # 'Polygon'
                         annot.set_border(width=0.3, dashes=[2])
                         annot.set_colors( fill=(  int(SimilarAreaDictionary['R'].loc[i])/255 ,  int(SimilarAreaDictionary['G'].loc[i])/255 ,  int(SimilarAreaDictionary['B'].loc[i])/255 ) ) 
@@ -790,13 +790,14 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
             # cv2.putText(imgtransparent1,'Length= '+str(height) , (x+50,y-20)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
             areasinImage.append(areaa)
 
-            cv2.putText(imgPerimeter1,'Perimeter'+str(perimeterr), (x+70,y-30)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
+            cv2.putText(imgPerimeter1,'Perimeter: '+str(perimeterr)+ ' m', (x+70,y-30)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
+            cv2.putText(imgPerimeter1,'Area: '+str(areaa)+' m2', (x+50,y-40)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
 
   
-    for i,row in SimilarAreaDictionary.iterrows():
-      # print(row)
-      if row[5] not in areasinImage: # column of area 
-        SimilarAreaDictionary = SimilarAreaDictionary.drop(SimilarAreaDictionary.loc[SimilarAreaDictionary.index==i].index)
+    # for i,row in SimilarAreaDictionary.iterrows():
+    #   # print(row)
+    #   if row[5] not in areasinImage: # column of area 
+    #     SimilarAreaDictionary = SimilarAreaDictionary.drop(SimilarAreaDictionary.loc[SimilarAreaDictionary.index==i].index)
 
     print(SimilarAreaDictionary)
     # display(totaldf)
@@ -804,56 +805,54 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
   else:
     
     SimilarAreaDictionary= pd.DataFrame(columns=['Color','Rounded','Width','Height','Occurences','Area','Total Area','Perimeter','Total Perimeter','Length','Total Length','R','G','B'])  
-    contourss=findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,flag)
+    contourss=findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,'perimeter')
+    contourssA=findContoursFullImage(green2,img,number,finalColorArray,ratioarea,ratioperim,'area')
     SimilarAreaDictionary,colorsUsed , areas_Perimeters= FillDictionary(green2,SimilarAreaDictionary,img,number,ratioarea,ratioperim,flag,finalColorArray)
     # print('filled')
-    for contour in contourss:
-      # shape=[]
-      area1 = cv2.contourArea(contour)
-      perimeter1 = cv2.arcLength(contour, True)  
-      if (area1 >4000 ):
-        shape=[]
-        angleR,widthR ,heightR= StraightenImage(contour,imgArea1)
-        x, y , width, height = cv2.boundingRect(contour) 
+    for contour in range(len(contourss)):
+    #   imgArea1=img.copy()
+      area1 = cv2.contourArea(contourss[contour][0])
+      if (area1 >2000 ):
+        perimeter = cv2.arcLength(contourss[contour][0],True)
 
-        approx = cv2.approxPolyDP(contour, 0.005 * perimeter1, True)
+        shape=[]
+        angleR,widthR ,heightR= StraightenImage(contourss[contour][0],imgArea1)
+        x, y , width, height = cv2.boundingRect(contourss[contour][0])
+        # approxo = cv2.approxPolyDP(contourss[contour],0.1*cv2.arcLength(contourss[contour],True),True)
+        # approx = cv2.approxPolyDP(contourss[contour][0], 0.005 * perimeter, True)
+        approx = cv2.approxPolyDP(contourssA[contour][0], 0.0002* perimeter, True)
+        area1 = cv2.contourArea(approx)
+        approx = cv2.approxPolyDP(contourss[contour][0], 0.01 * perimeter, True) #0.0009
+        perimeter1 = cv2.arcLength(approx, True)
         for point in approx:
             x1, y1 = point[0]
             shape.append([int(x1*ratio),int(y1*ratio)])
         allpoints.append(shape)
-        if (angleR != 90.0 and angleR != -90.0 and angleR != 0.0 and angleR != -0.0 ): #inclined b ay degree 
+        if (angleR != 90.0 and angleR != -90.0 and angleR != 0.0 and angleR != -0.0 ): #inclined b ay degree
             width=widthR
             height=heightR
         if width>height:
           lengthShape = width
         if height>width:
           lengthShape = height
-        widthMin= width-10 #5
+
+        widthMin= width-10
         widthMax= width+10
         heightMin=height-10
         heightMax= height+10
 
-        
         if ratioarea !=0 and ratioperim!=0:
-          # if flag=='area':
-            # addedMargin=area1+perimeter1*2
-            # areaa=round(addedMargin* (num1/(num2+perimeter1*2) ), 3) # true value of area of any shape/ area px value of same shape
-          # elif flag=='perimeter':
-            areaa=round(area1* ratioarea, 3) # true value of area of any shape/ area px value of same shape
-            perimeterr=round(perimeter1* ratioperim, 3)
+            areaa=round(area1* ratioarea ,3) # true value of area of any shape/ area px value of same shape
+            perimeterr=round(perimeter1* ratioperim,3)
+            lengthShape=round(lengthShape* ratioperim,3)
         else:
-          areaa=area1
           perimeterr=perimeter1
-        # if flag=='area': 
-        areaPerimeterMin= round(areaa,1) - 0.3
-        areaPerimeterMax= round(areaa,1) + 0.3
+        areaPerimeterMin= round(areaa,1) - 0.4
+        areaPerimeterMax= round(areaa,1) + 0.4
         masked=SimilarAreaDictionary.loc[SimilarAreaDictionary.index[((SimilarAreaDictionary['Rounded'] >=areaPerimeterMin) & (SimilarAreaDictionary['Rounded']<=areaPerimeterMax)  )]]
         passed=0
-        # if (round(areaa,1) in masked['Rounded'].values ) :
-
         for i, row in masked.iterrows():
           if passed ==0:
-            # if SimilarAreaDictionary['Rounded'].loc[i] == round(areaa,1) :
             if (   SimilarAreaDictionary['Rounded'].loc[i]  <= areaPerimeterMax and SimilarAreaDictionary['Rounded'].loc[i]  >= areaPerimeterMin) :
               if (SimilarAreaDictionary['Width'].loc[i] <=widthMax and SimilarAreaDictionary['Width'].loc[i] >= widthMin)  and (SimilarAreaDictionary['Height'].loc[i] <= heightMax  and SimilarAreaDictionary['Height'].loc[i] >= heightMin  ) or (SimilarAreaDictionary['Width'].loc[i] <=heightMax and SimilarAreaDictionary['Width'].loc[i] >= heightMin)  and (SimilarAreaDictionary['Height'].loc[i] <= widthMax  and SimilarAreaDictionary['Height'].loc[i] >= widthMin  ) :
                     SimilarAreaDictionary['Total Area'].loc[i]+=areaa
@@ -861,44 +860,32 @@ def drawAllContours(img,number,finalColorArray,ratioarea,ratioperim,flag , path,
 
                     SimilarAreaDictionary['Total Perimeter'].loc[i]+=perimeterr
                     SimilarAreaDictionary['Perimeter'].loc[i]=perimeterr
-                    
+
                     SimilarAreaDictionary['Total Length'].loc[i]+=lengthShape
                     SimilarAreaDictionary['Length'].loc[i]=lengthShape
+
                     passed=1
-                    cv2.drawContours(imgArea1, [contour], 0, ( int(SimilarAreaDictionary['B'].loc[i]),  int(SimilarAreaDictionary['G'].loc[i]), int(SimilarAreaDictionary['R'].loc[i])), -1)
-                    
+                    cv2.drawContours(imgArea1, [contourss[contour][0]], 0, ( int(SimilarAreaDictionary['B'].loc[i]),  int(SimilarAreaDictionary['G'].loc[i]), int(SimilarAreaDictionary['R'].loc[i])), -1)
+
                     annot = page.add_polygon_annot( points=shape )  # 'Polygon'
                     annot.set_border(width=0.3, dashes=[2])
-                    annot.set_colors( fill=(  int(SimilarAreaDictionary['R'].loc[i])/255 ,  int(SimilarAreaDictionary['G'].loc[i])/255 ,  int(SimilarAreaDictionary['B'].loc[i])/255 ) ) 
+                    annot.set_colors( fill=(  int(SimilarAreaDictionary['B'].loc[i])/255 ,  int(SimilarAreaDictionary['G'].loc[i])/255 ,  int(SimilarAreaDictionary['R'].loc[i])/255 ) )
                     # annot.set_colors( fill=(1,0,1) )
                     annot.set_opacity(0.5)
                     annot.set_info(content='Area='+str(areaa)+' m2' +'\n \nPerimeter='+str(perimeterr)+' m',subject='ADR Team')#,title='uuum')
                     # annot.set_line_ends(fitz.PDF_ANNOT_LE_DIAMOND, fitz.PDF_ANNOT_LE_CIRCLE)
                     annot.update()
-        cv2.putText(imgtransparent1,'area= '+str(area1) + ' m', (x+50,y-10)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
-        # cv2.putText(imgtransparent1,'Width= '+str(width) , (x+50,y-10)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
-        # cv2.putText(imgtransparent1,'Length= '+str(height) , (x+50,y-40)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
-        cv2.drawContours(imgArea1, [contour], 0, (0, 0, 255),2)
-        cv2.drawContours(imgPerimeter1, [contour], 0, (0, 0, 255), 4)
-        cv2.putText(imgPerimeter1,'Perimeter='+str(perimeter1), (x+30,y-30)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
+        cv2.putText(imgtransparent1,'Area: '+str(areaa)+' m2' , (x+50,y-10)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
+        cv2.putText(imgtransparent1,'Perimeter: '+str(perimeterr)+' m' , (x+50,y-40)  ,cv2.FONT_HERSHEY_SIMPLEX, 0.6, (50, 50, 255), 2)
 
-  
   alpha = 0.4  # Transparency factor.
   image_new1 = cv2.addWeighted(imgArea1, alpha,  imgtransparent1, 1 - alpha, 0)
-  
   # SimilarAreaDictionary.drop(['Rounded', 'Width','Height','R','G','B'], axis=1, inplace=True)
 
   print(SimilarAreaDictionary)
  
   # annotationsSave
-  # doc.save('k.pdf', deflate=True)
   pdflink= db.dropbox_upload_file(doc=doc,pdfname=path,pdfpath=pdfpath)
-  # list1=pd.DataFrame(columns=['content', 'creationDate', 'id', 'modDate', 'name', 'subject', 'title'])
-  # doc1 = fitz.open('k.pdf')
-  # for page in doc1:
-  #   for annot in page.annots():
-  #       list1.loc[len(list1)] =annot.info
-  # print(list1)
   dbx=db.dropbox_connect()
   md, res =dbx.files_download(path= pdfpath+path)
   data = res.content