Update dxf__omar3_2.py

dxf__omar3_2.py

@@ -420,7 +420,7 @@ def Create_DF(dxfpath,datadoc):
   SimilarAreaDictionary= pd.DataFrame(columns=['Guess','Color','Occurences','Area','Total Area','Perimeter','Total Perimeter','Length','Total Length','Texts','Comments'])
     
   colorRanges2=generate_color_array(300)
-  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],[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],[110,50,64],[255,255,128],[180,255,128],[128,210,166],[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],[140,188,80],[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]]
+  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
@@ -443,8 +443,8 @@ def Create_DF(dxfpath,datadoc):
       if any(combined_condition):
           index = np.where(combined_condition)[0][0]
           SimilarAreaDictionary.at[index, 'Occurences'] += 1
-          SimilarAreaDictionary.at[index, 'Total Area'] = SimilarAreaDictionary.at[index, 'Area'] * SimilarAreaDictionary.at[index, 'Occurences']
-          SimilarAreaDictionary.at[index, 'Total Perimeter'] = SimilarAreaDictionary.at[index, 'Perimeter'] * SimilarAreaDictionary.at[index, 'Occurences']
+          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
@@ -529,7 +529,7 @@ def mainFunctionDrawImgPdf(datadoc,dxfpath, dxfratio,pdfpath,pdfname):
       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='Area='+str(polygon[1])+' m^2',subject='ADR Team')
-      annot11.set_opacity(0.8)
+      annot11.set_opacity(0.9)
       # annot.set_line_ends(fitz.PDF_ANNOT_LE_DIAMOND, fitz.PDF_ANNOT_LE_CIRCLE)
       annot11.update()
 
@@ -556,9 +556,76 @@ def mainFunctionDrawImgPdf(datadoc,dxfpath, dxfratio,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'])
-  for page in doc:
-      for annot in page.annots():
-          list1.loc[len(list1)] =annot.info
+  list1=pd.DataFrame(columns=['content',  'id',  'subject','color'])
+
+  for page in doc:    
+    # 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]]
   return doc,image_new1, SimilarAreaDictionary ,spreadsheetId, spreadsheet_url , namepathArr , list1,hatched_areas
 
+
+def deletemarkupsDXF(list1, dbPath, path):
+    '''list1 : original markup pdf
+       list2 : deleted markup pdf
+       deletedrows : deleted markups - difference between both dfs
+    '''
+
+    myDict1 = eval(list1)
+    list1 = pd.DataFrame(myDict1)
+
+    dbxTeam = tsadropboxretrieval.ADR_Access_DropboxTeam('user')
+    md, res = dbxTeam.files_download(path=dbPath + path)
+    data = res.content
+    doc = fitz.open("pdf", data)
+    
+    # Prepare a DataFrame for the annotations in the new PDF
+    list2 = pd.DataFrame(columns=['content', 'id', 'subject', 'color'])
+
+    for page in doc:
+        # 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:
+                # Check for fill or stroke color
+                stroke_color = annot_color.get('stroke')
+                fill_color = annot_color.get('fill')
+
+                v = 'stroke' if stroke_color else 'fill'
+                color = annot_color.get(v)
+                if color:
+                    # Convert color to tuple and multiply by 255 to get RGB values
+                    color_tuple = (int(color[0] * 255), int(color[1] * 255), int(color[2] * 255))
+                    # Append annotation data to list2
+                    list2.loc[len(list2)] = [annot.info['content'], annot.info['id'], annot.info['subject'], color_tuple]
+
+    # Ensure that colors are stored as tuples (which are hashable)
+    list1['color'] = list1['color'].apply(lambda x: tuple(x) if isinstance(x, list) else x)
+    
+    # Find the deleted rows by checking the difference between original and current annotations
+    deletedrows = pd.concat([list1, list2]).drop_duplicates(keep=False)
+
+    print(deletedrows, len(deletedrows))
+    flag = 0
+    if len(deletedrows) != 0:
+        flag = 1
+        deletedrows = deletedrows[['content', 'id', 'subject', 'color']]
+        # Drop rows where 'content' starts with 'Scale'
+        deletedrows = deletedrows.drop(deletedrows.index[deletedrows['content'].str.startswith('Scale')])
+    else:
+        flag = 0
+    
+    return deletedrows