Select and group registration marks
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@ -45,7 +45,7 @@ outputTmpl = sys.argv[-1]
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print(f'Calibrating to scan {basename(normalImage)}')
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registrationMark = cv2.imread('./registration_mark.png', 0)
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registrationMark = cv2.imread('./registrationMark.png', 0)
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w, h = registrationMark.shape[:2]
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holePunches = read_text(normalText)
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original = cv2.imread(normalImage)
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@ -59,13 +59,49 @@ if not orientation :
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print(holePunches)
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topHalf = img[holePunches['0']['y']:holePunches['1']['y']+round(height*0.1), holePunches['0']['x']:holePunches['2']['x']]
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topHalfGray = cv2.cvtColor(topHalf, cv2.COLOR_BGR2GRAY)
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res = cv2.matchTemplate(topHalfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
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threshold = 0.5
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loc = np.where( res >= threshold)
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for pt in zip(*loc[::-1]):
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print(f'{pt[0]},{pt[1]}')
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cv2.rectangle(topHalf, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
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def get_distance(ref, point):
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# print('ref: {} , point: {}'.format(ref, point))
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x1, y1 = ref[0], ref[1]
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x2, y2 = point[0], point[1]
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return math.hypot(x2 - x1, y2 - y1)
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def group_points(points):
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groups = {}
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groupnum = 0
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while len(points) > 1:
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groupnum += 1
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key = str(groupnum)
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groups[key] = []
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ref = points.pop(0)
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for i, point in enumerate(points):
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d = get_distance(ref, point)
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if d < 30:
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groups[key].append(points[i])
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points[i] = None
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points = list(filter(lambda x: x is not None, points))
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# perform average operation on each group
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return list([[int(np.mean(list([x[0] for x in groups[arr]]))), int(np.mean(list([x[1] for x in groups[arr]])))] for arr in groups])
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def find_in_half (half) :
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halfGray = cv2.cvtColor(half, cv2.COLOR_BGR2GRAY)
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res = cv2.matchTemplate(halfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
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threshold = 0.7
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loc = np.where( res >= threshold)
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for pt in zip(*loc[::-1]):
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cv2.rectangle(half, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
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#display(half)
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return list(zip(*loc[::-1]))
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topHalf = img[holePunches['0']['y']-round(height*0.05):holePunches['1']['y']+round(height*0.1), holePunches['0']['x']:holePunches['2']['x']]
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topHalfPts = find_in_half(topHalf)
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thpts = group_points(topHalfPts)
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for pt in thpts :
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print(f'{pt[0]},{pt[1]}')
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bottomHalf = img[holePunches['4']['y']-round(height*0.1):holePunches['5']['y']+round(height*0.05), holePunches['3']['x']:holePunches['4']['x']]
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bottomHalfPts = find_in_half(bottomHalf)
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bhpts = group_points(bottomHalfPts)
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for pt in bhpts :
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print(f'{pt[0]},{pt[1]}')
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display(bottomHalf)
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display(topHalf)
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