halo center shift deleted; binarization parameters adjusted (e14d7ff7) · Commits · Ziqin Wang / ArmorDetection

src/car_target.py

+4 −2

Original line number	Diff line number	Diff line
		@@ -219,11 +219,13 @@ if __name__ == "__main__":

		# app = ImgCarTargetApp(color=BarColor.BLUE, folder="/home/jeeken/Pictures/blue",
		# frame_size=(640, 480), ext_name="jpg", debug=True)
		app = ImgCarTargetApp(color=BarColor.BLUE, folder="/home/jeeken/Pictures/blue_dark",
		frame_size=(640, 480), ext_name="jpg", debug=True)
		# app = ImgCarTargetApp(color=BarColor.RED, folder="/home/jeeken/Pictures/red_dark",
		# frame_size=(640, 480), ext_name="jpg", debug=True)

		app = VideoCarTargetApp(file="/home/jeeken/Videos/live_blue.avi",
		color=BarColor.BLUE, frame_size=(640, 480), debug=False)
		# app = VideoCarTargetApp(file="/home/jeeken/Videos/live_blue.avi",
		# color=BarColor.BLUE, frame_size=(640, 480), debug=False)
		# app = VideoCarTargetApp(file="/home/jeeken/Videos/red.avi",
		# color=BarColor.RED, frame_size=(640, 480), debug=False)
		app.run()

src/detector.py

+4 −6

Original line number	Diff line number	Diff line
		@@ -76,10 +76,9 @@ class Detector:
		self.add_debug_img("Red to Blue", cv2.cvtColor(hsv_frame, cv2.COLOR_HSV2BGR))

		# TODO: decide the range of lightness based on histogram
		# lower_light = np.array([90, 0, 180])
		lower_light = np.array([90, 0, 200])
		upper_light = np.array([120, 130, 255])
		lower_halo = np.array([90, 100, 185])
		upper_light = np.array([120, 200, 255])
		lower_halo = np.array([90, 120, 185])
		upper_halo = np.array([120, 255, 255])
		# lower_light = np.array([90, 0, 185])
		# upper_light = np.array([120, 230, 255])
		@@ -116,8 +115,7 @@ class Detector:
		if len(selected_contours) > 0:
		combined_halo_points = np.concatenate(selected_contours)
		original_center, original_radius = cv2.minEnclosingCircle(combined_halo_points)
		x, y = original_center
		center = round(x), round(y - original_radius * 0.6) # shift up
		center = round_point(original_center)

		# zoom
		if original_radius > width / 4:
		@@ -220,6 +218,7 @@ class Detector:

		judge_results = [(pair, judge(pair)) for pair in pairs]
		(i1, i2), winner_score = min(judge_results, key=lambda x: x[1])
		self.debug_print("score:", winner_score)

		if winner_score > 7:
		return None
		@@ -234,7 +233,6 @@ class Detector:
		# self.debug_print("shape_similarity:", 5 * size_similarity(l1, l2))
		# self.debug_print("square_ratio:", 5 * square_ratio(l1, l2))
		# self.debug_print("y_dis:", 20 * y_dis(l1, l2))
		self.debug_print("score:", winner_score)
		c1, s1, a1 = l1
		c2, s2, a2 = l2
		cv2.drawMarker(selected_pair_show, position=round_point(c1), color=BGR_GREEN, markerSize=15, thickness=2)

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