Update app.py

app.py

@@ -85,7 +85,7 @@ def detectCircles(imgOriginal ):
       detected_circles = np.round(detected_circles[0, :]).astype("int")
     #DRAW CIRCLES
       for (x, y, r) in detected_circles:
-        cv2.circle(im, (x, y), r, (255, 255, 255), 6)
+        cv2.circle(im, (x, y), r, (255, 255, 255), 5)
   im=cv2.medianBlur(im,1)
   print('circles')
   # cv2_imshow(im)
@@ -143,7 +143,7 @@ def DashedPreprocessing(imgOriginal,imgnoSmall):
 
 def removeDashedLines(img4, imgBW ,max,min):
 
-  imgLines= cv2.HoughLinesP(img4,1,np.pi/310,250,minLineLength=(max-min)//1.8,maxLineGap = 120)  #was w-h , gap=150 0.99
+  imgLines= cv2.HoughLinesP(img4,1,np.pi/310,30,minLineLength=(max-min)//1.8,maxLineGap = 120)  #was w-h , gap=150 0.99
 #1 120
 
   for i in range(len(imgLines)):
@@ -165,7 +165,7 @@ def removeSmallDashes(imgOriginal,green):
   img2=cv2.erode(img1, kernel3, iterations=2)
 
   smalldashes=cv2.medianBlur(img2,5)
-  smalldashes=cv2.medianBlur(smalldashes,5)
+  smalldashes=cv2.medianBlur(smalldashes,7)
   # cv2_imshow(smalldashes)
   smalldashesOut=green.copy()
   smalldashesOut=cv2.cvtColor(smalldashesOut,cv2.COLOR_GRAY2BGR)
@@ -174,7 +174,7 @@ def removeSmallDashes(imgOriginal,green):
   imgCopy=imgOriginal.copy()
   for i in range(len(imgLines)):
       for x1,y1,x2,y2 in imgLines[i]:
-          cv2.line(smalldashesOut,(x1,y1),(x2,y2),(0,255,0),3)
+          cv2.line(smalldashesOut,(x1,y1),(x2,y2),(0,255,0),2)
 
 
   smalldashesOut=smalldashesOut[:,:,1]
@@ -194,13 +194,13 @@ def removeDashedLinesSmall(img4, imgBW ,max,min):
 
   imgBW=cv2.cvtColor(imgBW,cv2.COLOR_GRAY2BGR)
 
-  imgLines= cv2.HoughLinesP(img4,1,np.pi/300,150,minLineLength=(max-min)//2.2,maxLineGap = 70)  #2.1
+  imgLines= cv2.HoughLinesP(img4,1,np.pi/100,20,minLineLength=(max-min)//2.2,maxLineGap = 70)  #2.1
 
   for i in range(len(imgLines)):
       for x1,y1,x2,y2 in imgLines[i]:
            dist=euclidian_distance((x1,y1), (x2,y2))
           #  if dist > 1300 and dist <1450:
-           if dist >= (max-min)//2.1 and dist < (max-min)//1.95: #1.4
+           if dist >= (max-min)//2.1 and dist < (max-min)//1.9: #1.4
               cv2.line(imgBW,(x1,y1),(x2,y2),(0,255,0),3)
 
   im_copy=imgBW.copy()
@@ -212,17 +212,17 @@ def ConnectBeamLines(smalldashesOut):
   green1=cv2.bitwise_not(smalldashesOut)
   green2=smalldashesOut.copy()
   green2=cv2.cvtColor(green2,cv2.COLOR_GRAY2BGR)
-  imgLines= cv2.HoughLinesP(green1,0.05,np.pi/250,10,minLineLength=30,maxLineGap = 20)  #was w-h , gap=150  #50
+  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),2)
+          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),1)
 
-  imgLines= cv2.HoughLinesP(green1,0.5,np.pi/360,10,minLineLength=30,maxLineGap = 20)  #try 180
+  imgLines= cv2.HoughLinesP(green1,0.3,np.pi/360,10,minLineLength=25,maxLineGap = 20)  #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),2)
+          cv2.line(green2,(x1,y1),(x2,y2),(0,0,0),1)
   # cv2_imshow(green2)
   return green2