clean for distribute
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+1
-14
@@ -160,13 +160,10 @@ class Sensor:
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Returns:
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Returns:
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np.ndarray: Processed grayscale image
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np.ndarray: Processed grayscale image
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"""
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"""
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t0 = time.perf_counter()
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ret, frame = self.cap.read()
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ret, frame = self.cap.read()
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if not ret:
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if not ret:
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print("Failed to get_img from video source.")
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print("Failed to get_img from video source.")
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return None
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return None
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t1 = time.perf_counter()
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print(f"read frame time: {t1 - t0} seconds")
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# Convert to grayscale
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# Convert to grayscale
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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@@ -414,18 +411,8 @@ class Sensor:
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def _open_video_source(self, override, box):
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def _open_video_source(self, override, box):
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"""Initialize video capture and calibration."""
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"""Initialize video capture and calibration."""
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# Use DirectShow backend on Windows for cameras (more stable than MSMF)
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if isinstance(self.vid_src, int):
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# For camera indices, try DirectShow first (avoids MSMF errors)
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try:
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self.cap = cv2.VideoCapture(self.vid_src, cv2.CAP_DSHOW)
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except:
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# Fallback to default backend
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self.cap = cv2.VideoCapture(self.vid_src)
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else:
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# For file paths, use default backend
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self.cap = cv2.VideoCapture(self.vid_src)
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self.cap = cv2.VideoCapture(self.vid_src)
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# Set buffer size to 1 to reduce latency and avoid frame accumulation
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# Set buffer size to 1 to reduce latency and avoid frame accumulation
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self.cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
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self.cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
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self.cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G'))
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self.cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G'))
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