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@ -66,6 +66,8 @@ def swap(a, b):
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ap = argparse.ArgumentParser()
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ap = argparse.ArgumentParser()
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ap.add_argument("-i", "--image", required=True,
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ap.add_argument("-i", "--image", required=True,
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help="path to the input image")
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help="path to the input image")
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#ap.add_argument("-c", "--cascade", required=True,
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# help="path to the cascade")
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ap.add_argument("-w", "--width", type=float, required=True,
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ap.add_argument("-w", "--width", type=float, required=True,
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help="width of the left-most object in the image (in inches)")
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help="width of the left-most object in the image (in inches)")
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ap.add_argument("-n", "--number", type=int, required=False,
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ap.add_argument("-n", "--number", type=int, required=False,
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@ -89,14 +91,20 @@ if args2.show:
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cv2.imshow("Item Sorter", image)
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cv2.imshow("Item Sorter", image)
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cv2.waitKey(0)
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cv2.waitKey(0)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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gray = cv2.GaussianBlur(gray, (7, 7), 0)
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gray = cv2.GaussianBlur(gray, (5, 5), 0)
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if args2.show:
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cv2.imshow("Item Sorter", gray)
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cv2.waitKey(0)
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# perform edge detection, then perform a dilation + erosion to
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# perform edge detection, then perform a dilation + erosion to
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# close gaps in between object edges
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# close gaps in between object edges
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edged = cv2.Canny(gray, 50, 100)
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edged = cv2.Canny(gray, 50, 100)
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if args2.show:
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cv2.imshow("Item Sorter", edged)
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cv2.waitKey(0)
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edged = cv2.dilate(edged, None, iterations=1)
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edged = cv2.dilate(edged, None, iterations=1)
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#edged = cv2.erode(edged, None, iterations=1)
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edged = cv2.erode(edged, None, iterations=1)
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if args2.show:
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if args2.show:
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cv2.imshow("Item Sorter", edged)
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cv2.imshow("Item Sorter", edged)
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@ -155,7 +163,7 @@ for c in cnts:
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#pixelpoints = np.transpose(np.nonzero(mask))
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#pixelpoints = np.transpose(np.nonzero(mask))
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hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
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hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
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mean_val = cv2.mean(hsv, mask=mask)
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mean_val = cv2.mean(hsv, mask=mask)
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print(str(mean_val[0]))
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#print(str(mean_val[0]))
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#print(", " + str(mean_val[0]/mean_val[2]))
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#print(", " + str(mean_val[0]/mean_val[2]))
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#print(", " + str(mean_val[2]/mean_val[1]))
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#print(", " + str(mean_val[2]/mean_val[1]))
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if pixelsPerMetric is None and circular is True and near(mean_val[0], 16, 4.5):
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if pixelsPerMetric is None and circular is True and near(mean_val[0], 16, 4.5):
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@ -246,6 +254,19 @@ for c in cnts:
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objtype = "Penny"
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objtype = "Penny"
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iteml = 0
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iteml = 0
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else:
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else:
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if circular and near(radius * 2 / pixelsPerMetric, 0.38, 0.03):
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# Keps nut or spacer
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objtype = "Spacer"
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mask = np.zeros(gray.shape, np.uint8)
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cv2.drawContours(mask, [c], 0, 255, -1)
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#pixelpoints = np.transpose(np.nonzero(mask))
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hsv = cv2.cvtColor(orig, cv2.COLOR_BGR2HSV)
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mean_val = cv2.mean(hsv, mask=mask)
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#print(str(mean_val[0]))
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if near(mean_val[0], 47, 5) and near(mean_val[1], 70, 5) and near(mean_val[2], 78, 5):
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objtype = "Keps Nut"
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if circular and near(radius / pixelsPerMetric, 0.23, 0.02):
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objtype = "Washer"
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epsilon = 3 # 0.02*cv2.arcLength(c,True)
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epsilon = 3 # 0.02*cv2.arcLength(c,True)
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# print(str(epsilon))
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# print(str(epsilon))
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approx = cv2.approxPolyDP(c, epsilon, True)
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approx = cv2.approxPolyDP(c, epsilon, True)
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@ -259,18 +280,18 @@ for c in cnts:
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#print(str(convexness) + " % fill")
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#print(str(convexness) + " % fill")
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# if not cv2.isContourConvex(approx):
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# if not cv2.isContourConvex(approx):
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# if cv2.matchShapes(hull, c, 1, 0.0) > 1:
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# if cv2.matchShapes(hull, c, 1, 0.0) > 1:
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if defects.size > 5 and (convexness < 0.9 or boxiness < 0.75):
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if defects is not None and defects.size > 5 and (convexness < 0.9 or boxiness < 0.75) and rectangular:
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objtype = "Screw"
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objtype = "Screw"
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iteml = larger(dimA, dimB)
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iteml = larger(dimA, dimB)
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#print("Screw Length (RAW): " + str(iteml))
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#print("Screw Length (RAW): " + str(iteml))
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iteml = sizeVexScrew(radius * 2 / pixelsPerMetric)
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iteml = sizeVexScrew(radius * 2 / pixelsPerMetric)
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#print("Rounded Length: " + str(iteml))
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#print("Rounded Length: " + str(iteml))
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else:
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else:
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if itemhr == 0.3125:
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if itemhr == 0.3125 and rectangular:
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objtype = "Standoff"
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objtype = "Standoff"
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iteml = sizeStandoff(itemw)
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iteml = sizeStandoff(itemw)
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if itemhr == 0.1875:
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if itemhr == 0.1875 and rectangular:
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objtype = "Axle"
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objtype = "Axle"
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iteml = (radius * 2 / pixelsPerMetric + itemw) / 2
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iteml = (radius * 2 / pixelsPerMetric + itemw) / 2
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@ -297,10 +318,16 @@ for c in cnts:
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# cv2.putText(orig, "{:.5f}in".format(itemhr),
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# cv2.putText(orig, "{:.5f}in".format(itemhr),
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# (int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
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# (int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
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# 0.65, (255, 255, 255), 2)
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# 0.65, (255, 255, 255), 2)
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if circular:
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cv2.putText(orig, str(objtype),
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(int(x - 25), int(y + radius + 20)
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), cv2.FONT_HERSHEY_SIMPLEX,
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0.55, (255, 255, 255), 2)
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else:
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cv2.putText(orig, str(objtype),
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cv2.putText(orig, str(objtype),
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(int(xpos2 + 10), int(ypos2 + 20)
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(int(xpos2 + 10), int(ypos2 + 20)
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), cv2.FONT_HERSHEY_SIMPLEX,
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), cv2.FONT_HERSHEY_SIMPLEX,
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0.65, (255, 255, 255), 2)
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0.55, (255, 255, 255), 2)
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output = ""
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output = ""
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if objtype == "Unknown":
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if objtype == "Unknown":
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output = "{:.2f}in".format(itemw) + " x {:.2f}in".format(itemh)
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output = "{:.2f}in".format(itemw) + " x {:.2f}in".format(itemh)
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@ -308,10 +335,16 @@ for c in cnts:
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output = str(iteml) + "in"
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output = str(iteml) + "in"
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if objtype == "Axle":
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if objtype == "Axle":
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output = "{:.2f}in".format(iteml)
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output = "{:.2f}in".format(iteml)
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if circular:
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cv2.putText(orig, output, # print data
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(int(x - 25), int(y + radius + 35)
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), cv2.FONT_HERSHEY_SIMPLEX,
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0.5, (255, 255, 255), 1)
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else:
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cv2.putText(orig, output, # print data
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cv2.putText(orig, output, # print data
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(int(xpos2 + 10), int(ypos2 + 40)
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(int(xpos2 + 10), int(ypos2 + 35)
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), cv2.FONT_HERSHEY_SIMPLEX,
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), cv2.FONT_HERSHEY_SIMPLEX,
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0.65, (255, 255, 255), 2)
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0.5, (255, 255, 255), 1)
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# show the output image
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# show the output image
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cv2.imshow("Item Sorter", orig)
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cv2.imshow("Item Sorter", orig)
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