Work fixing template

fourcell/template.py

@@ -7,11 +7,13 @@ from common import image_resize, display, normalize_angle, read_json
 from json import dumps
 
 DEBUG = True
-registrationMarkThreshold = 0.65
+registrationMarkThreshold = 0.7
+methodIndex = 0
+marks = []
 
 #clockwise from top left
 order = [ 0, 2, 3, 5, 4, 1 ]
-matchMethods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR', 'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']
+matchMethods = [cv2.TM_CCOEFF, cv2.TM_CCOEFF_NORMED, cv2.TM_CCORR, cv2.TM_CCORR_NORMED, cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]
 
 #
 # CALIBRATE
@@ -21,8 +23,7 @@ if len(sys.argv) < 2:
 	print('Please provide path of normalized scan to build template from to')
 	exit(1)
 
-
-normalImage = sys.argv[-1]
+normalImage = sys.argv[1]
 
 if not exists(normalImage) :
 	print('Normalized scan does not exist, please provide one that does')
@@ -34,17 +35,35 @@ if not exists(normalText) :
 	print('Corresponding normalized scan text does not exist, please generate one')
 	exit(3)
 
+if len(sys.argv) > 2 :
+	if not exists(sys.argv[2]) :
+		registrationMark = cv2.imread(sys.argv[2])
+		print(f'Registration mark {sys.argv[2]} does not exist')
+		exit(4)
+	print(f'Using registration mark {sys.argv[2]}')
+
+def get_dpi (width) :
+	if width == 2550 :
+		return 300
+	if width == 5100 :
+		return 600
+	if width == 10200 :
+		return 1200
 
 print(f'Building template from scan {basename(normalImage)}')
 
-registrationMark = cv2.imread('./registrationMark.png', 0)
-w, h = registrationMark.shape[:2]
 holePunches = read_json(normalText)
 original = cv2.imread(normalImage)
 img = original.copy()
 height, width = img.shape[:2]
 orientation = height > width
-marks = []
+dpi = get_dpi(width)
+
+try: registrationMark
+except NameError: registrationMark = None
+if registrationMark is None :
+	registrationMark = cv2.imread(f'./registrationMark/{dpi}.png', 0)
+w, h = registrationMark.shape[:2]
 
 if not orientation :
 	print(f'Scan is not in portrait mode, exiting...')
@@ -79,7 +98,7 @@ def find_closest (pt, pts) :
 
 def find_in_half (half) :
 	halfGray = cv2.cvtColor(half, cv2.COLOR_BGR2GRAY)
-	res = cv2.matchTemplate(halfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
+	res = cv2.matchTemplate(halfGray, registrationMark, matchMethods[methodIndex])
 	threshold = registrationMarkThreshold
 	loc = np.where( res >= threshold )
 	for pt in zip(*loc[::-1]):
@@ -92,11 +111,23 @@ topHalf = img[ttly:holePunches['1']['y']+round(height*0.1), ttlx:holePunches['2'
 while True: 
 	topHalfPts = find_in_half(topHalf)
 	if len(topHalfPts) < 12 :
-		registrationMarkThreshold -= 0.05
+		if methodIndex == len(matchMethods) :
+			registrationMarkThreshold -= 0.005
+			methodIndex = 0
 			print(f'Found only {len(topHalfPts)}, decreasing threshold to {registrationMarkThreshold}')
+		else :
+			methodIndex += 1
+			print(f'Found only {len(topHalfPts)}, switching to method {matchMethods[methodIndex]}')
+		
 	elif len(topHalfPts) > 12 :
-		registrationMarkThreshold += 0.05
+		if methodIndex == len(matchMethods) :
+			registrationMarkThreshold += 0.005
+			methodIndex = 0
 			print(f'Found {len(topHalfPts)}, increasing threshold to {registrationMarkThreshold}')
+		else :
+			methodIndex += 1
+			print(f'Found {len(topHalfPts)}, switching to method {matchMethods[methodIndex]}')
+		
 	else :
 		break