Add item differentiation: screws, standoffs, axles, penny, plus a lot more
This commit is contained in:
Cole Deck
174
main.py
174
main.py
@@ -24,13 +24,28 @@ def sizeVexScrew(iteml):
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iteml = round(iteml)
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iteml /= 8
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return iteml
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def sizeStandoff(iteml):
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# Standoff Sizing code
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#print("Thread Length: " + str(iteml))
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iteml *= 4
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iteml = round(iteml)
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iteml /= 4
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return iteml
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def larger(a, b):
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if a >= b:
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return a
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else:
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return b
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def smaller(a, b):
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if a < b:
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return a
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else:
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return b
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# construct the argument parse and parse the arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-i", "--image", required=True,
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@@ -49,12 +64,15 @@ if type(args["number"]) == type(selected):
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# load the image, convert it to grayscale, and blur it slightly
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image = cv2.imread(args["image"])
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image = cv2.resize(image, (image.shape[1]*2, image.shape[0]*2), interpolation = cv2.INTER_NEAREST)
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image = cv2.resize(image, (int(image.shape[1]*0.2), int(image.shape[0]*0.2)), interpolation = cv2.INTER_NEAREST)
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if args2.show:
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cv2.imshow("Screw Length Detection", image)
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cv2.imshow("Item Sorter", image)
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cv2.waitKey(0)
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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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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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@@ -62,8 +80,9 @@ gray = cv2.GaussianBlur(gray, (7, 7), 0)
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edged = cv2.Canny(gray, 50, 100)
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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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if args2.show:
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cv2.imshow("Screw Length Detection", edged)
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cv2.imshow("Item Sorter", edged)
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cv2.waitKey(0)
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# find contours in the edge map
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cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
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@@ -75,6 +94,62 @@ cnts = imutils.grab_contours(cnts)
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(cnts, _) = contours.sort_contours(cnts)
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pixelsPerMetric = None
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num = 0
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# Calibration loop
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for c in cnts:
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# if the contour is not sufficiently large, ignore it
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if cv2.contourArea(c) < 100:
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continue
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# compute the rotated bounding box of the contour
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orig = image.copy()
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box = cv2.minAreaRect(c)
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box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
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box = np.array(box, dtype="int")
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box = perspective.order_points(box)
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(tl, tr, br, bl) = box
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(tltrX, tltrY) = midpoint(tl, tr)
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(blbrX, blbrY) = midpoint(bl, br)
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(tlblX, tlblY) = midpoint(tl, bl)
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(trbrX, trbrY) = midpoint(tr, br)
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dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) - np.array((blbrX, blbrY, 0)))
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dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) - np.array((trbrX, trbrY, 0)))
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area_box = dA * dB
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(x,y),radius = cv2.minEnclosingCircle(c)
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area_contour = cv2.contourArea(c)
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area_circle = math.pi * pow(radius, 2)
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boxiness = area_contour / area_box
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circleness = area_contour / area_circle
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circular = False
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rectangular = False
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if boxiness > circleness:
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rectangular = True
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cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
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else:
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circular = True
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cv2.circle(orig,(int(x),int(y)),int(radius),(0,255,0),2)
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if pixelsPerMetric is None and circular is True:
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pixelsPerMetric = smaller(dA, dB) / args["width"]
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#cv2.imshow("Screw Length Detection", orig)
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#cv2.waitKey(0)
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# order the points in the contour such that they appear
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# in top-left, top-right, bottom-right, and bottom-left
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# order, then draw the outline of the rotated bounding
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# box
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#cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
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# if the pixels per metric has not been initialized, then
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# compute it as the ratio of pixels to supplied metric
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# (in this case, inches)
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# compute the size of the object
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orig = image.copy()
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# loop over the contours individually
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for c in cnts:
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num += 1
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@@ -82,7 +157,7 @@ for c in cnts:
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if cv2.contourArea(c) < 100:
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continue
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# compute the rotated bounding box of the contour
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orig = image.copy()
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box = cv2.minAreaRect(c)
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box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
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@@ -93,7 +168,6 @@ for c in cnts:
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# order, then draw the outline of the rotated bounding
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# box
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box = perspective.order_points(box)
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cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
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# loop over the original points and draw them
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#for (x, y) in box:
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@@ -118,38 +192,92 @@ for c in cnts:
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#cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)
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# draw lines between the midpoints
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cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)),
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(255, 0, 255), 2)
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cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),
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(255, 0, 255), 2)
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# compute the Euclidean distance between the midpoints
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# compute the Euclidean distance between the midpoints
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dA = np.linalg.norm(np.array((tltrX, tltrY, 0)) - np.array((blbrX, blbrY, 0)))
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dB = np.linalg.norm(np.array((tlblX, tlblY, 0)) - np.array((trbrX, trbrY, 0)))
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# if the pixels per metric has not been initialized, then
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# compute it as the ratio of pixels to supplied metric
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# (in this case, inches)
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if pixelsPerMetric is None:
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pixelsPerMetric = dB / args["width"]
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#if pixelsPerMetric is None:
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# pixelsPerMetric = dB / args["width"]
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# compute the size of the object
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dimA = dA / pixelsPerMetric
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dimB = dB / pixelsPerMetric
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if num == num:
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iteml = larger(dimA, dimB)
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print("Screw Length (RAW): " + str(iteml))
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iteml = sizeVexScrew(iteml)
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print("Rounded Length: " + str(iteml))
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# draw the object sizes on the image
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if num == selected or args2.show:
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area_box = dA * dB
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(x,y),radius = cv2.minEnclosingCircle(c)
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area_contour = cv2.contourArea(c)
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area_circle = math.pi * pow(radius, 2)
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boxiness = area_contour / area_box
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circleness = area_contour / area_circle
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circular = False
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rectangular = False
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if boxiness > circleness:
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rectangular = True
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cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
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else:
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circular = True
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cv2.circle(orig,(int(x),int(y)),int(radius),(0,255,0),2)
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objtype = "Unknown"
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itemw = larger(dimA, dimB)
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itemwr = itemw
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itemwr *= 8
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itemwr = round(itemwr)
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itemwr /= 8
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itemh = smaller(dimA, dimB)
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itemhr = itemh
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itemhr *= 16
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itemhr = round(itemhr)
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itemhr /= 16
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if circular and itemwr == 0.75:
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objtype = "Penny"
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iteml = 0
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else:
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epsilon = 4#0.05*cv2.arcLength(c,True)
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#print(str(epsilon))
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approx = cv2.approxPolyDP(c,epsilon,True)
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cv2.drawContours(orig, (approx.astype("int")), -1, (255, 0, 0), 8)
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if not cv2.isContourConvex(approx):
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objtype = "Screw"
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iteml = larger(dimA, dimB)
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#print("Screw Length (RAW): " + str(iteml))
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iteml = sizeVexScrew(radius * 2 / pixelsPerMetric)
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#print("Rounded Length: " + str(iteml))
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else:
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if itemhr == 0.3125:
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objtype = "Standoff"
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iteml = sizeStandoff(radius * 2 / pixelsPerMetric)
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if itemhr == 0.1875:
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objtype = "Axle"
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iteml = radius * 2 / pixelsPerMetric
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print(str(iteml))
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# draw the object sizes on the image
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if args2.show:
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cv2.putText(orig, "{:.5f}in".format(larger(dimA, dimB)),
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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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# 0.65, (255, 255, 255), 2)
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cv2.putText(orig, str(objtype),
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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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if num > 1:
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cv2.putText(orig, "{:.3f}in screw".format(iteml), # print screw length
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if objtype == "Screw":
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cv2.putText(orig, str(iteml) + "in thread", # print screw length
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(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
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0.65, (255, 255, 255), 2)
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if objtype == "Standoff":
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cv2.putText(orig, str(iteml) + "in", # print standoff length
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(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
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0.65, (255, 255, 255), 2)
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if objtype == "Axle":
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cv2.putText(orig, "{:.2f}in".format(iteml), # print axle length
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(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
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0.65, (255, 255, 255), 2)
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# show the output image
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cv2.imshow("Screw Length Detection", orig)
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cv2.imshow("Item Sorter", orig)
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cv2.waitKey(0)
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