remove delay

anno.txt

@@ -1,24 +0,0 @@
-/home/cole/item-sort/positives/IMG_10208.jpg 1 4 3 80 110
-/home/cole/item-sort/positives/IMG_1155.jpg 1 1 1 30 32
-/home/cole/item-sort/positives/IMG_1184.jpg 1 1 1 34 30
-/home/cole/item-sort/positives/IMG_1287.jpg 1 2 2 35 29
-/home/cole/item-sort/positives/IMG_13351.jpg 1 2 2 165 75
-/home/cole/item-sort/positives/IMG_13857.jpg 1 2 5 90 142
-/home/cole/item-sort/positives/IMG_1472.jpg 1 1 1 43 29
-/home/cole/item-sort/positives/IMG_1584.jpg 1 1 1 45 31
-/home/cole/item-sort/positives/IMG_1683.jpg 1 1 0 48 32
-/home/cole/item-sort/positives/IMG_1764.jpg 1 2 1 38 39
-/home/cole/item-sort/positives/IMG_1776.jpg 1 1 0 45 36
-/home/cole/item-sort/positives/IMG_19530.jpg 1 4 4 120 149
-/home/cole/item-sort/positives/IMG_2200.jpg 1 1 0 46 42
-/home/cole/item-sort/positives/IMG_2772.jpg 1 0 0 83 32
-/home/cole/item-sort/positives/IMG_2784.jpg 1 1 1 46 55
-/home/cole/item-sort/positives/IMG_2800.jpg 1 1 1 53 48
-/home/cole/item-sort/positives/IMG_3285.jpg 1 1 1 71 43
-/home/cole/item-sort/positives/IMG_3604.jpg 1 1 0 104 33
-/home/cole/item-sort/positives/IMG_4550.jpg 1 1 1 127 32
-
-/home/cole/item-sort/positives/IMG_4879.jpg 1 2 2 37 114
-/home/cole/item-sort/positives/IMG_7412.jpg 1 2 2 105 65
-/home/cole/item-sort/positives/IMG_7654.jpg 1 4 2 80 84
-/home/cole/item-sort/positives/IMG_7740.jpg 1 1 2 126 57

bg.txt

@@ -1,38 +0,0 @@
-negatives/IMG_10285.jpg
-negatives/IMG_1190.jpg
-negatives/IMG_1225.jpg
-negatives/IMG_1443.jpg
-negatives/IMG_1482.jpg
-negatives/IMG_17202.jpg
-negatives/IMG_18939.jpg
-negatives/IMG_19860.jpg
-negatives/IMG_2116.jpg
-negatives/IMG_2408.jpg
-negatives/IMG_2475.jpg
-negatives/IMG_2548.jpg
-negatives/IMG_2597.jpg
-negatives/IMG_2700.jpg
-negatives/IMG_27048.jpg
-negatives/IMG_2805.jpg
-negatives/IMG_28583.jpg
-negatives/IMG_30940.jpg
-negatives/IMG_35235.jpg
-negatives/IMG_3599.jpg
-negatives/IMG_36040.jpg
-negatives/IMG_36400.jpg
-negatives/IMG_3666.jpg
-negatives/IMG_3840.jpg
-negatives/IMG_3844.jpg
-negatives/IMG_40176.jpg
-negatives/IMG_42840.jpg
-negatives/IMG_5041.jpg
-negatives/IMG_5184.jpg
-negatives/IMG_5402.jpg
-negatives/IMG_5700.jpg
-negatives/IMG_5820.jpg
-negatives/IMG_6014.jpg
-negatives/IMG_6016.jpg
-negatives/IMG_6240.jpg
-negatives/IMG_6435.jpg
-negatives/IMG_7482.jpg
-negatives/IMG_9800.jpg

main.py

@@ -66,8 +66,8 @@ def swap(a, b):
 ap = argparse.ArgumentParser()
 ap.add_argument("-i", "--image", required=True,
                 help="path to the input image")
-ap.add_argument("-c", "--cascade", required=True,
-                help="path to the cascade")
+#ap.add_argument("-c", "--cascade", required=True,
+#                help="path to the cascade")
 ap.add_argument("-w", "--width", type=float, required=True,
                 help="width of the left-most object in the image (in inches)")
 ap.add_argument("-n", "--number", type=int, required=False,
@@ -91,14 +91,20 @@ if args2.show:
     cv2.imshow("Item Sorter", image)
     cv2.waitKey(0)
 gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-gray = cv2.GaussianBlur(gray, (7, 7), 0)
-
+gray = cv2.GaussianBlur(gray, (5, 5), 0)
+if args2.show:
+    cv2.imshow("Item Sorter", gray)
+    cv2.waitKey(0)
 
 # perform edge detection, then perform a dilation + erosion to
 # close gaps in between object edges
 edged = cv2.Canny(gray, 50, 100)
+if args2.show:
+    cv2.imshow("Item Sorter", edged)
+    cv2.waitKey(0)
+
 edged = cv2.dilate(edged, None, iterations=1)
-#edged = cv2.erode(edged, None, iterations=1)
+edged = cv2.erode(edged, None, iterations=1)
 
 if args2.show:
     cv2.imshow("Item Sorter", edged)
@@ -114,18 +120,7 @@ cnts = imutils.grab_contours(cnts)
 pixelsPerMetric = None
 num = 0
 
-cascade = cv2.CascadeClassifier()
-if not cascade.load(cv2.samples.findFile(args2.cascade)):
-    print('--(!)Error loading face cascade')
-    exit(0)
-screws = cascade.detectMultiScale(image)
-frame = image.copy()
-for (x,y,w,h) in screws:
-    center = (x + w//2, y + h//2)
-    frame = cv2.ellipse(frame, center, (w//2, h//2), 0, 0, 360, (255, 0, 255), 4)
-if args2.show:
-    cv2.imshow("Item Sorter", frame)
-    cv2.waitKey(0)
+
 # Calibration loop
 for c in cnts:
     # if the contour is not sufficiently large, ignore it
@@ -168,7 +163,7 @@ for c in cnts:
         #pixelpoints = np.transpose(np.nonzero(mask))
         hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
         mean_val = cv2.mean(hsv, mask=mask)
-        print(str(mean_val[0]))
+        #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):
@@ -259,6 +254,19 @@ for c in cnts:
             objtype = "Penny"
             iteml = 0
         else:
+            if circular and near(radius * 2 / pixelsPerMetric, 0.38, 0.03):
+                # Keps nut or spacer
+                objtype = "Spacer"
+                mask = np.zeros(gray.shape, np.uint8)
+                cv2.drawContours(mask, [c], 0, 255, -1)
+                #pixelpoints = np.transpose(np.nonzero(mask))
+                hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
+                mean_val = cv2.mean(hsv, mask=mask)
+                #print(str(mean_val[0]))
+                if near(mean_val[0], 47, 5) and near(mean_val[1], 70, 5) and near(mean_val[2], 78, 5):
+                    objtype = "Keps Nut"
+            if circular and near(radius / pixelsPerMetric, 0.23, 0.02):
+                objtype = "Washer"
             epsilon = 3  # 0.02*cv2.arcLength(c,True)
             # print(str(epsilon))
             approx = cv2.approxPolyDP(c, epsilon, True)
@@ -272,18 +280,18 @@ 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 or boxiness < 0.75):
+            if defects is not None and defects.size > 5 and (convexness < 0.9 or boxiness < 0.75) and rectangular:
                 objtype = "Screw"
                 iteml = larger(dimA, dimB)
                 #print("Screw Length (RAW): " + str(iteml))
                 iteml = sizeVexScrew(radius * 2 / pixelsPerMetric)
                 #print("Rounded Length: " + str(iteml))
             else:
-                if itemhr == 0.3125:
+                if itemhr == 0.3125 and rectangular:
                     objtype = "Standoff"
                     iteml = sizeStandoff(itemw)
 
-                if itemhr == 0.1875:
+                if itemhr == 0.1875 and rectangular:
                     objtype = "Axle"
                     iteml = (radius * 2 / pixelsPerMetric + itemw) / 2
 
@@ -310,10 +318,16 @@ for c in cnts:
             # cv2.putText(orig, "{:.5f}in".format(itemhr),
             #	(int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
             #	0.65, (255, 255, 255), 2)
+            if circular:
+                cv2.putText(orig, str(objtype),
+                            (int(x - 25), int(y + radius + 20)
+                             ), cv2.FONT_HERSHEY_SIMPLEX,
+                            0.55, (255, 255, 255), 2)
+            else:
                 cv2.putText(orig, str(objtype),
                             (int(xpos2 + 10), int(ypos2 + 20)
                              ), cv2.FONT_HERSHEY_SIMPLEX,
-                        0.65, (255, 255, 255), 2)
+                            0.55, (255, 255, 255), 2)
             output = ""
             if objtype == "Unknown":
                 output = "{:.2f}in".format(itemw) + " x {:.2f}in".format(itemh)
@@ -321,13 +335,19 @@ for c in cnts:
                 output = str(iteml) + "in"
             if objtype == "Axle":
                 output = "{:.2f}in".format(iteml)
+            if circular:
                 cv2.putText(orig, output,  # print data
-                        (int(xpos2 + 10), int(ypos2 + 40)
+                            (int(x - 25), int(y + radius + 35)
                              ), cv2.FONT_HERSHEY_SIMPLEX,
-                        0.65, (255, 255, 255), 2)
+                            0.5, (255, 255, 255), 1)
+            else:
+                cv2.putText(orig, output,  # print data
+                            (int(xpos2 + 10), int(ypos2 + 35)
+                             ), cv2.FONT_HERSHEY_SIMPLEX,
+                            0.5, (255, 255, 255), 1)
 
     # show the output image
             cv2.imshow("Item Sorter", orig)
-            cv2.waitKey(25)
+            cv2.waitKey(1)
 
 cv2.waitKey(0)