check penny color

main.py

@@ -68,7 +68,7 @@ if type(args["number"]) == type(selected):
 
 # load the image, convert it to grayscale, and blur it slightly
 image = cv2.imread(args["image"])
-#image = cv2.resize(image, (int(image.shape[1]*0.2), int(image.shape[0]*0.2)), interpolation = cv2.INTER_NEAREST)
+#image = cv2.resize(image, (int(image.shape[1]*1), int(image.shape[0]*1)))
 image = cv2.resize(image, (1000, int(image.shape[0]/image.shape[1] * 1000)), interpolation = cv2.INTER_NEAREST)
 
 if args2.show:
@@ -137,9 +137,13 @@ for c in cnts:
 		mask = np.zeros(gray.shape,np.uint8)
 		cv2.drawContours(mask,[c],0,255,-1)
 		#pixelpoints = np.transpose(np.nonzero(mask))
-		mean_val = cv2.mean(orig,mask = mask)
+		hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
-		#print(str(mean_val))
+		mean_val = cv2.mean(hsv,mask = mask)
-	if pixelsPerMetric is None and circular is True and near(mean_val[0], 63, 30) is True and near(mean_val[1], 108, 30) is True and near(mean_val[2], 104, 30) is True:
+		print(str(mean_val[0]))
+		#print(", " + str(mean_val[0]/mean_val[2]))
+		#print(", " + str(mean_val[2]/mean_val[1]))
+	if pixelsPerMetric is None and circular is True and near(mean_val[0], 16, 4.5):
+		# and near(mean_val[0], 63, 40) is True and near(mean_val[1], 108, 40) is True and near(mean_val[2], 104, 40) is True:
 		pixelsPerMetric = smaller(dA, dB) / args["width"]
 		
 
@@ -242,7 +246,7 @@ for c in cnts:
 			#print(str(convexness) + " % fill")
 			#if not cv2.isContourConvex(approx):
 			#if cv2.matchShapes(hull, c, 1, 0.0) > 1:
-			if defects.size > 5 and (convexness < 0.9 and boxiness < 0.7):
+			if defects.size > 5 and (convexness < 0.9 or boxiness < 0.75):
 				objtype = "Screw"
 				iteml = larger(dimA, dimB)
 				#print("Screw Length (RAW): " + str(iteml))