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Add item differentiation: screws, standoffs, axles, penny, plus a lot more

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cascade
Cole Deck 5 years ago
parent dfc47a8dec
commit d41d79cdc5
2 changed files with 151 additions and 23 deletions
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main.py
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@ -25,12 +25,27 @@ def sizeVexScrew(iteml):
iteml /= 8
return iteml
def sizeStandoff(iteml):
# Standoff Sizing code
#print("Thread Length: " + str(iteml))
iteml *= 4
iteml = round(iteml)
iteml /= 4
return iteml
def larger(a, b):
if a >= b:
return a
else:
return b
def smaller(a, b):
if a < b:
return a
else:
return b
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
@ -49,12 +64,15 @@ 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, (image.shape[1]*2, image.shape[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)
if args2.show:
cv2.imshow("Screw Length Detection", image)
cv2.imshow("Item Sorter", image)
cv2.waitKey(0)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (7, 7), 0)
if args2.show:
cv2.imshow("Item Sorter", gray)
cv2.waitKey(0)
# perform edge detection, then perform a dilation + erosion to
@ -62,8 +80,9 @@ gray = cv2.GaussianBlur(gray, (7, 7), 0)
edged = cv2.Canny(gray, 50, 100)
edged = cv2.dilate(edged, None, iterations=1)
edged = cv2.erode(edged, None, iterations=1)
if args2.show:
cv2.imshow("Screw Length Detection", edged)
cv2.imshow("Item Sorter", edged)
cv2.waitKey(0)
# find contours in the edge map
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
@ -75,6 +94,62 @@ cnts = imutils.grab_contours(cnts)
(cnts, _) = contours.sort_contours(cnts)
pixelsPerMetric = None
num = 0
# Calibration loop
for c in cnts:
# if the contour is not sufficiently large, ignore it
if cv2.contourArea(c) < 100:
continue
# compute the rotated bounding box of the contour
orig = image.copy()
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)
(tl, tr, br, bl) = box
(tltrX, tltrY) = midpoint(tl, tr)
(blbrX, blbrY) = midpoint(bl, br)
(tlblX, tlblY) = midpoint(tl, bl)
(trbrX, trbrY) = midpoint(tr, br)
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)))
area_box = dA * dB
(x,y),radius = cv2.minEnclosingCircle(c)
area_contour = cv2.contourArea(c)
area_circle = math.pi * pow(radius, 2)
boxiness = area_contour / area_box
circleness = area_contour / area_circle
circular = False
rectangular = False
if boxiness > circleness:
rectangular = True
cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
else:
circular = True
cv2.circle(orig,(int(x),int(y)),int(radius),(0,255,0),2)
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
@ -82,7 +157,7 @@ for c in cnts:
if cv2.contourArea(c) < 100:
continue
# compute the rotated bounding box of the contour
orig = image.copy()
box = cv2.minAreaRect(c)
box = cv2.cv.BoxPoints(box) if imutils.is_cv2() else cv2.boxPoints(box)
@ -93,7 +168,6 @@ for c in cnts:
# order, then draw the outline of the rotated bounding
# box
box = perspective.order_points(box)
cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
# loop over the original points and draw them
#for (x, y) in box:
@ -118,38 +192,92 @@ for c in cnts:
#cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)
# draw lines between the midpoints
cv2.line(orig, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)),
(255, 0, 255), 2)
cv2.line(orig, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),
(255, 0, 255), 2)
# compute the Euclidean distance between the midpoints
# compute the Euclidean distance between the midpoints
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"]
#if pixelsPerMetric is None:
# pixelsPerMetric = dB / args["width"]
# compute the size of the object
dimA = dA / pixelsPerMetric
dimB = dB / pixelsPerMetric
if num == num:
iteml = larger(dimA, dimB)
print("Screw Length (RAW): " + str(iteml))
iteml = sizeVexScrew(iteml)
print("Rounded Length: " + str(iteml))
# draw the object sizes on the image
if num == selected or args2.show:
area_box = dA * dB
(x,y),radius = cv2.minEnclosingCircle(c)
area_contour = cv2.contourArea(c)
area_circle = math.pi * pow(radius, 2)
boxiness = area_contour / area_box
circleness = area_contour / area_circle
circular = False
rectangular = False
if boxiness > circleness:
rectangular = True
cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
else:
circular = True
cv2.circle(orig,(int(x),int(y)),int(radius),(0,255,0),2)
objtype = "Unknown"
itemw = larger(dimA, dimB)
itemwr = itemw
itemwr *= 8
itemwr = round(itemwr)
itemwr /= 8
itemh = smaller(dimA, dimB)
itemhr = itemh
itemhr *= 16
itemhr = round(itemhr)
itemhr /= 16
if circular and itemwr == 0.75:
objtype = "Penny"
iteml = 0
else:
epsilon = 4#0.05*cv2.arcLength(c,True)
#print(str(epsilon))
approx = cv2.approxPolyDP(c,epsilon,True)
cv2.drawContours(orig, (approx.astype("int")), -1, (255, 0, 0), 8)
if not cv2.isContourConvex(approx):
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:
objtype = "Standoff"
iteml = sizeStandoff(radius * 2 / pixelsPerMetric)
if itemhr == 0.1875:
objtype = "Axle"
iteml = radius * 2 / pixelsPerMetric
print(str(iteml))
# draw the object sizes on the image
if args2.show:
cv2.putText(orig, "{:.5f}in".format(larger(dimA, dimB)),
#cv2.putText(orig, "{:.5f}in".format(itemhr),
# (int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
# 0.65, (255, 255, 255), 2)
cv2.putText(orig, str(objtype),
(int(trbrX + 20), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
0.65, (255, 255, 255), 2)
if num > 1:
cv2.putText(orig, "{:.3f}in screw".format(iteml), # print screw length
if objtype == "Screw":
cv2.putText(orig, str(iteml) + "in thread", # print screw length
(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
0.65, (255, 255, 255), 2)
if objtype == "Standoff":
cv2.putText(orig, str(iteml) + "in", # print standoff length
(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
0.65, (255, 255, 255), 2)
if objtype == "Axle":
cv2.putText(orig, "{:.2f}in".format(iteml), # print axle length
(int(trbrX + 20), int(trbrY + 20)), cv2.FONT_HERSHEY_SIMPLEX,
0.65, (255, 255, 255), 2)
# show the output image
cv2.imshow("Screw Length Detection", orig)
cv2.imshow("Item Sorter", orig)
cv2.waitKey(0)
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