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reduce the motion detection timeout to 5 seconds
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@ -387,7 +387,7 @@ def process_frames(shared_arr, shared_output_arr, shared_frame_time, shared_moti
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# copy the detected objects to the output array, filling the array when needed
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# copy the detected objects to the output array, filling the array when needed
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shared_output_arr[:] = objects + [0.0] * (60-len(objects))
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shared_output_arr[:] = objects + [0.0] * (60-len(objects))
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# do the actual object detection
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# do the actual motion detection
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def detect_motion(shared_arr, shared_frame_time, ready_for_frame, shared_motion, frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area):
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def detect_motion(shared_arr, shared_frame_time, ready_for_frame, shared_motion, frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area):
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# shape shared input array into frame for processing
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# shape shared input array into frame for processing
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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arr = tonumpyarray(shared_arr).reshape(frame_shape)
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@ -398,8 +398,8 @@ def detect_motion(shared_arr, shared_frame_time, ready_for_frame, shared_motion,
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frame_time = 0.0
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frame_time = 0.0
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while True:
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while True:
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now = datetime.datetime.now().timestamp()
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now = datetime.datetime.now().timestamp()
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# if it has been 30 seconds since the last motion, clear the flag
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# if it has been long enough since the last motion, clear the flag
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if last_motion > 0 and (now - last_motion) > 30:
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if last_motion > 0 and (now - last_motion) > 5:
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last_motion = -1
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last_motion = -1
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shared_motion.value = 0
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shared_motion.value = 0
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# if there isnt a frame ready for processing
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# if there isnt a frame ready for processing
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