tried different method for differentiating between particles and capballs. Failed

1 files changed, 19 insertions, 24 deletions

diff --git a/proc.py b/proc.py
index 7bdef13..9aa2920 100644
--- a/proc.py
+++ b/proc.py
@@ -17,8 +17,12 @@ h,s,v = cv2.split(himg)
 #blue is 195-135, 40? really that much?
 #hue only testing, not very effective.
 # better with saturation
-thresh = cv2.bitwise_and(cv2.bitwise_or(thresh(h,0,10),thresh(h,169,180)), thresh(s,60,255))
-#thresh = cv2.bitwise_and(thresh(h,95,135), thresh(s,60,255))
+
+#red
+#thresh = cv2.bitwise_and(cv2.bitwise_or(thresh(h,0,10),thresh(h,169,180)), thresh(s,60,255))
+#blue
+thresh = cv2.bitwise_and(thresh(h,95,135), thresh(s,60,255))
+
 #thresh = cv2.GaussianBlur(thresh,(29,29),0,0,cv2.BORDER_REFLECT_101)
 cv2.imwrite("stallmask.jpg",thresh);
 mask = cv2.merge((thresh,thresh,thresh))
@@ -26,7 +30,8 @@ masked = cv2.bitwise_and(himg, mask);
 cv2.imwrite("stallmasked.jpg",cv2.cvtColor(masked,cv2.COLOR_HSV2BGR));
 #only takes 1 cannel arrays?
 im2, con, heir = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
-v = 0
+#number of contours above certain size
+vc = 0
 for i in range(0, len(con)) :
 	if (cv2.contourArea(con[i]) > 2000) :
 		a = cv2.contourArea(con[i])
@@ -37,32 +42,22 @@ for i in range(0, len(con)) :
 		cv2.circle(masked, c,int(r), (150,255,255), 5)
 		if (p < .35) :
 			print("yee")
-			#find find frst child
-			#her in list mode returns the array inside of another array
-			if ( heir[0][i][2] != -1 ):
-				j = heir[0][i][2]
-				while (j != -1) :
-					cv2.drawContours(masked, con, j, (160,255,255), 3)
-					cp = 0
-					cp = cp + cv2.contourArea(con[j])
-					j = heir[0][j][0]
-				cp = cp/a
-			else :
-				cp = 0
-			print ("child area perc")
-			print(cp)
-			if (cp > 0.0005) :
-				cv2.putText(masked, "p", c, cv2.FONT_HERSHEY_PLAIN, 10, (0,255,255),cv2.LINE_AA)
-			else :
-				cv2.putText(masked, 'c', c, cv2.FONT_HERSHEY_PLAIN, 10, (0,255,255),cv2.LINE_AA)
-
+			conmask = numpy.zeros(v.shape, numpy.uint8)
+			cv2.drawContours(conmask, con, i, (255), cv2.FILLED)
+			conmasked = cv2.bitwise_and(v, conmask)
+			meanconmasked = conmasked.sum().sum() / a
+			print(meanconmasked)
+			ret, conmasked = cv2.threshold(conmasked, meanconmasked, 255, cv2.THRESH_BINARY_INV)
+			cv2.imwrite("conmasked" + str(i) + ".jpg",cv2.merge((conmasked,conmasked,conmasked)))
+			im2, rcon, rheir = cv2.findContours(conmasked, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
+			cv2.drawContours(masked, rcon, -1, (50, 255, 255),2)
 		print(p)
 		
-		v = v + 1
+		vc = vc + 1
 	else :
 		cv2.drawContours(masked, con, i, (80,255,255), 1)
 cv2.imwrite("stallmaskedcon.jpg",cv2.cvtColor(masked,cv2.COLOR_HSV2BGR))
 print("properly sized contours")
-print(v)
+print(vc)
 print("all contours")
 print(len(con))