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Work on matching registration marks against document. Segmenting image without copying is causing errors.

This commit is contained in:
Matt McWilliams 2023-01-30 09:26:43 -05:00
parent adf465fd4c
commit 1589076974
1 changed files with 32 additions and 9 deletions
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41
fourcell/calibrate.py
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@ -8,8 +8,7 @@ from json import load
#clockwise from top left #clockwise from top left
order = [ 0, 2, 3, 5, 4, 1 ] order = [ 0, 2, 3, 5, 4, 1 ]
matchMethods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR', matchMethods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR', 'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']
'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']
def read_text (textPath) : def read_text (textPath) :
holePunches = {} holePunches = {}
@ -52,6 +51,7 @@ original = cv2.imread(normalImage)
img = original.copy() img = original.copy()
height, width = img.shape[:2] height, width = img.shape[:2]
orientation = height > width orientation = height > width
marks = []
if not orientation : if not orientation :
print(f'Scan is not in portrait mode, exiting...') print(f'Scan is not in portrait mode, exiting...')
@ -79,9 +79,11 @@ def group_points(points):
groups[key].append(points[i]) groups[key].append(points[i])
points[i] = None points[i] = None
points = list(filter(lambda x: x is not None, points)) points = list(filter(lambda x: x is not None, points))
# perform average operation on each group
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]) 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])
def find_closest (pt, pts) :
return pts[min(range(len(pts)), key = lambda i: get_distance(pts[i], pt))]
def find_in_half (half) : def find_in_half (half) :
halfGray = cv2.cvtColor(half, cv2.COLOR_BGR2GRAY) halfGray = cv2.cvtColor(half, cv2.COLOR_BGR2GRAY)
res = cv2.matchTemplate(halfGray, registrationMark, cv2.TM_CCOEFF_NORMED) res = cv2.matchTemplate(halfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
@ -89,19 +91,40 @@ def find_in_half (half) :
loc = np.where( res >= threshold) loc = np.where( res >= threshold)
for pt in zip(*loc[::-1]): for pt in zip(*loc[::-1]):
cv2.rectangle(half, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2) cv2.rectangle(half, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
#display(half)
return list(zip(*loc[::-1])) return list(zip(*loc[::-1]))
topHalf = img[holePunches['0']['y']-round(height*0.05):holePunches['1']['y']+round(height*0.1), holePunches['0']['x']:holePunches['2']['x']]
ttly = holePunches['0']['y']-round(height*0.05)
ttlx = holePunches['0']['x']
topHalf = img[ttly:holePunches['1']['y']+round(height*0.1), ttlx:holePunches['2']['x']]
topHalfPts = find_in_half(topHalf) topHalfPts = find_in_half(topHalf)
thpts = group_points(topHalfPts) thpts = group_points(topHalfPts)
for pt in thpts : for pt in thpts :
print(f'{pt[0]},{pt[1]}') #print(f'{ttlx + pt[0]},{ttly + pt[1]}')
marks.append((ttlx + pt[0], ttly + pt[1],))
bottomHalf = img[holePunches['4']['y']-round(height*0.1):holePunches['5']['y']+round(height*0.05), holePunches['3']['x']:holePunches['4']['x']] print(f'Found {len(thpts)} points')
#display(topHalf)
btly = holePunches['4']['y']-round(height*0.1)
btlx = holePunches['3']['x']
bottomHalf = img[btly:holePunches['5']['y']+round(height*0.05), btlx:holePunches['4']['x']]
bottomHalfPts = find_in_half(bottomHalf) bottomHalfPts = find_in_half(bottomHalf)
bhpts = group_points(bottomHalfPts) bhpts = group_points(bottomHalfPts)
for pt in bhpts : for pt in bhpts :
print(f'{pt[0]},{pt[1]}') #print(f'{btlx + pt[0]},{btly + pt[1]}')
display(bottomHalf) marks.append((btlx + pt[0], btly + pt[1], ))
print(f'Found {len(bhpts)} points')
if len(marks) != 16 :
print(f'{len(marks)} != 16 marks')
exit(1)
print(find_closest((0,0,), marks))
print(find_closest((width,0,), marks))
print(find_closest((0,height,), marks))
print(find_closest((width,height,), marks))