- added reference center

- scaled up working with more accuracy

ocv_track.py

@@ -3,7 +3,7 @@ import sys
 import numpy as np
 import imutils as im
 
-IMG_SCALE_UP = 2
+IMG_SCALE_UP = 4
 TEMPLATE_SEARCH_AREA = 0.5
 
 (major_ver, minor_ver, subminor_ver) = cv2.__version__.split('.')
@@ -39,32 +39,58 @@ def process_image_bbox(src):
 	return gray
 
 
-def match(source, template, current_angle):
+def match(source, template, angle, center):
 	best_angle = 0
 	best_r = 0
-	best_maxLoc = 0
+	best_max_loc = 0
 
-	image_source = im.resize(source, IMG_SCALE_UP * source.shape[0], IMG_SCALE_UP * source.shape[1])
+	im_source = im.resize(source, IMG_SCALE_UP * source.shape[0], IMG_SCALE_UP * source.shape[1])
 
 	for dangle in np.linspace(-1.0, +1.0, 10):
-		# scale up to IMG_SCALE_UP-size
-		image_template = im.resize(template, IMG_SCALE_UP * template.shape[0], IMG_SCALE_UP * template.shape[1])
-		# rotated
-		image_template = im.rotate(image_template, current_angle + dangle)
+		# rotated and scale up to IMG_SCALE_UP-size
+		im_template = im.rotate(template, angle + dangle, center=center, scale=IMG_SCALE_UP)
 
 		# Perform template match operations
-		res = cv2.matchTemplate(image_source, image_template, cv2.TM_CCOEFF_NORMED)
+		res = cv2.matchTemplate(im_source, im_template, cv2.TM_CCOEFF_NORMED)
 		(minVal, maxVal, minLoc, maxLoc) = cv2.minMaxLoc(res)
 
 		r = maxVal
 		if r > best_r:
 			best_r = r
 			best_angle = dangle
-			best_maxLoc = maxLoc
+			best_max_loc = (maxLoc[0]/IMG_SCALE_UP, maxLoc[1]/IMG_SCALE_UP)
 
-	current_angle += best_angle
+	angle += best_angle
 
-	return current_angle, best_maxLoc
+	return angle, best_max_loc
+
+
+class Reference:
+	def __init__(self, ref_gray):
+		self.center = (0, 0)
+		self.ref = cv2.cvtColor(ref_gray, cv2.COLOR_GRAY2BGR)
+		self.work = self.ref.copy()
+		cv2.namedWindow('Ref')
+		cv2.setMouseCallback('Ref', self.extract_coordinates)
+
+	def set(self):
+		while True:
+			cv2.imshow("Ref", self.work)
+			key = cv2.waitKey(1)
+			if key == 32:
+				break
+			elif key == 27:
+				break
+		return self.center
+
+	def extract_coordinates(self, event, x, y, flags, parameters):
+		if event == cv2.EVENT_LBUTTONDOWN:
+			self.work = self.ref.copy()
+			self.center = (x, y)
+
+			print(f"Pixel at {self.center} = {self.work[y, x]}")
+			self.work[y, x] = (0, 0, 255)
+			print(f"Pixel at {self.center} = {self.work[y, x]}")
 
 
 trackers = {
@@ -95,10 +121,12 @@ if not ok:
 	print('Cannot read video file')
 	sys.exit()
 
-# Uncomment the line below to select a different bounding box
 bbox = cv2.selectROI("Frame", frame, False)
 image_template = process_image_bbox(image_crop(frame, bbox, TEMPLATE_SEARCH_AREA))
+ref = Reference(image_template)
+ref_center = ref.set()
 
+print(f"ref_center = {ref_center}")
 # Initialize tracker with first frame and bounding box
 tracker.create()
 tracker.init(frame, bbox)
@@ -120,22 +148,17 @@ while True:
 	image_template_rotated = image_template
 
 	if ok:
-		current_angle, max_loc = match(image_bbox, image_template, current_angle)
-		image_template_rotated = im.rotate(image_template, current_angle)
+		current_angle, max_loc = match(image_bbox, image_template, current_angle, ref_center)
 
 		# determine the starting and ending (x, y)-coordinates of the
 		# bounding box
 		(startX, startY) = max_loc
-		startX += bbox[0]
-		startY += bbox[1]
-		endX = startX + bbox[2]
-		endY = startY + bbox[3]
-
 		print(f"startX: {startX}, startY: {startY}")
+		image_template_rotated = im.rotate(image_template, current_angle, center=ref_center)
 
 		# draw the bounding box on the image
-		p1 = (int(bbox[0]), int(bbox[1]))
-		p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
+		p1 = (int(startX + bbox[0]), int(startY + bbox[1]))
+		p2 = (int(bbox[0]+bbox[2]), int(bbox[1]+bbox[3]))
 		cv2.rectangle(frame, p1, p2, (255, 0, 0), 3)
 
 		# Calculate Frames per second (FPS)