From adf465fd4c00ebede54dd08c46e36301dc81a934 Mon Sep 17 00:00:00 2001
From: mmattmcw <matt@sixteenmillimeter.com>
Date: Sun, 29 Jan 2023 22:53:51 -0500
Subject: [PATCH] Select and group registration marks

---
 fourcell/calibrate.py | 56 +++++++++++++++++++++++++++++++++++--------
 1 file changed, 46 insertions(+), 10 deletions(-)

diff --git a/fourcell/calibrate.py b/fourcell/calibrate.py
index c4bf35c..ee32b9f 100644
--- a/fourcell/calibrate.py
+++ b/fourcell/calibrate.py
@@ -45,7 +45,7 @@ outputTmpl = sys.argv[-1]
 
 print(f'Calibrating to scan {basename(normalImage)}')
 
-registrationMark = cv2.imread('./registration_mark.png', 0)
+registrationMark = cv2.imread('./registrationMark.png', 0)
 w, h = registrationMark.shape[:2]
 holePunches = read_text(normalText)
 original = cv2.imread(normalImage)
@@ -59,13 +59,49 @@ if not orientation :
 
 print(holePunches)
 
-topHalf = img[holePunches['0']['y']:holePunches['1']['y']+round(height*0.1), holePunches['0']['x']:holePunches['2']['x']]
-topHalfGray = cv2.cvtColor(topHalf, cv2.COLOR_BGR2GRAY)
-res = cv2.matchTemplate(topHalfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
-threshold = 0.5
-loc = np.where( res >= threshold)
-for pt in zip(*loc[::-1]):
-	print(f'{pt[0]},{pt[1]}')
-	cv2.rectangle(topHalf, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
+def get_distance(ref, point):
+	# print('ref: {} , point: {}'.format(ref, point))
+	x1, y1 = ref[0], ref[1]
+	x2, y2 = point[0], point[1]
+	return math.hypot(x2 - x1, y2 - y1)
+
+def group_points(points):
+    groups = {}
+    groupnum = 0
+    while len(points) > 1:
+        groupnum += 1
+        key = str(groupnum)
+        groups[key] = []
+        ref = points.pop(0)
+        for i, point in enumerate(points):
+            d = get_distance(ref, point)
+            if d < 30:
+                groups[key].append(points[i])
+                points[i] = None
+        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])
+
+def find_in_half (half) :
+	halfGray = cv2.cvtColor(half, cv2.COLOR_BGR2GRAY)
+	res = cv2.matchTemplate(halfGray, registrationMark, cv2.TM_CCOEFF_NORMED)
+	threshold = 0.7
+	loc = np.where( res >= threshold)
+	for pt in zip(*loc[::-1]):
+		cv2.rectangle(half, pt, (pt[0] + w, pt[1] + h), (0,0,255), 2)
+	#display(half)
+	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']]
+topHalfPts = find_in_half(topHalf)
+thpts = group_points(topHalfPts)
+for pt in thpts :
+	print(f'{pt[0]},{pt[1]}')
+
+bottomHalf = img[holePunches['4']['y']-round(height*0.1):holePunches['5']['y']+round(height*0.05), holePunches['3']['x']:holePunches['4']['x']]
+bottomHalfPts = find_in_half(bottomHalf)
+bhpts = group_points(bottomHalfPts)
+for pt in bhpts :
+	print(f'{pt[0]},{pt[1]}')
+display(bottomHalf)
 
-display(topHalf)
\ No newline at end of file