improve detection, do more checking for the screws

main.py

@@ -1,5 +1,5 @@
 # import the necessary packages
-from imutils import perspective
+#from imutils import perspective
 from imutils import contours
 import numpy as np
 import argparse
@@ -17,7 +17,7 @@ def midpoint(ptA, ptB):
 def sizeVexScrew(iteml):
 	# Screw Sizing code
 	# subtract screw head size to find thread length
-	shead = 0.09
+	shead = 0.1
 	iteml -= shead
 	#print("Thread Length: " + str(iteml))
 	iteml *= 8
@@ -27,11 +27,9 @@ def sizeVexScrew(iteml):
 
 def sizeStandoff(iteml):
 	# Standoff Sizing code
-
-	#print("Thread Length: " + str(iteml))
-	iteml *= 4
+	iteml *= 2
 	iteml = round(iteml)
-	iteml /= 4
+	iteml /= 2
 	return iteml
 
 
@@ -64,7 +62,9 @@ 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]*0.2), int(image.shape[0]*0.2)), interpolation = cv2.INTER_NEAREST)
+image = cv2.resize(image, (1000, int(image.shape[0]/image.shape[1] * 1000)), interpolation = cv2.INTER_NEAREST)
+
 if args2.show:
 	cv2.imshow("Item Sorter", image)
 	cv2.waitKey(0)
@@ -109,7 +109,7 @@ for c in cnts:
 	box = cv2.minAreaRect(c)
 	box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
 	box = np.array(box, dtype="int")
-	box = perspective.order_points(box)
+	#box = perspective.order_points(box)
 	(tl, tr, br, bl) = box
 	(tltrX, tltrY) = midpoint(tl, tr)
 	(blbrX, blbrY) = midpoint(bl, br)
@@ -134,27 +134,14 @@ for c in cnts:
 
 	if pixelsPerMetric is None and circular is True:
 		pixelsPerMetric = smaller(dA, dB) / args["width"]
-	#cv2.imshow("Screw Length Detection", orig)
-	#cv2.waitKey(0)
-	# order the points in the contour such that they appear
-	# in top-left, top-right, bottom-right, and bottom-left
-	# order, then draw the outline of the rotated bounding
-	# box
 
-	#cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
-
-	
-	# if the pixels per metric has not been initialized, then
-	# compute it as the ratio of pixels to supplied metric
-	# (in this case, inches)
-    # compute the size of the object
 
 orig = image.copy()
 # loop over the contours individually
 for c in cnts:
 	num += 1
 	# if the contour is not sufficiently large, ignore it
-	if cv2.contourArea(c) < 100:
+	if cv2.contourArea(c) < 100 or pixelsPerMetric is None:
 		continue
 	# compute the rotated bounding box of the contour
 	
@@ -167,7 +154,7 @@ for c in cnts:
 	# in top-left, top-right, bottom-right, and bottom-left
 	# order, then draw the outline of the rotated bounding
 	# box
-	box = perspective.order_points(box)
+	#box = perspective.order_points(box)
 
 	# loop over the original points and draw them
 	#for (x, y) in box:
@@ -196,12 +183,7 @@ for c in cnts:
 	dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) - np.array((blbrX, blbrY, 0)))
 	dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) - np.array((trbrX, trbrY, 0)))
 
-	# if the pixels per metric has not been initialized, then
-	# compute it as the ratio of pixels to supplied metric
-	# (in this case, inches)
-	#if pixelsPerMetric is None:
-	#	pixelsPerMetric = dB / args["width"]
-    # compute the size of the object
+
 	dimA = dA / pixelsPerMetric
 	dimB = dB / pixelsPerMetric
 	
@@ -238,11 +220,19 @@ for c in cnts:
 			objtype = "Penny"
 			iteml = 0
 		else:
-			epsilon = 4#0.05*cv2.arcLength(c,True)
+			epsilon = 3#0.02*cv2.arcLength(c,True)
 			#print(str(epsilon))
 			approx = cv2.approxPolyDP(c,epsilon,True)
+			hull = cv2.convexHull(approx, returnPoints=False)
+			hull2 = cv2.convexHull(c)
+			defects = cv2.convexityDefects(c,hull)
+			#print(str(defects.size) + " match")
 			cv2.drawContours(orig, (approx.astype("int")), -1, (255, 0, 0), 8)
-			if not cv2.isContourConvex(approx):
+			convexness = area_contour / cv2.contourArea(hull2)
+			#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 or boxiness < 0.75):
 				objtype = "Screw"
 				iteml = larger(dimA, dimB)
 				#print("Screw Length (RAW): " + str(iteml))
@@ -251,10 +241,12 @@ for c in cnts:
 			else:
 				if itemhr == 0.3125:
 					objtype = "Standoff"
-					iteml = sizeStandoff(radius * 2 / pixelsPerMetric)
+					iteml = sizeStandoff(itemw)
+					
 				if itemhr == 0.1875:
 					objtype = "Axle"
-					iteml = radius * 2 / pixelsPerMetric
+					iteml = (radius * 2 / pixelsPerMetric + itemw) / 2
+
 				
 		print(str(iteml))
 		# draw the object sizes on the image