mirror of
https://github.com/blakeblackshear/frigate.git
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d81dd60fef
* refactor existing motion detector * implement and use cnt bgsub * pass fps to motion detector * create a simplified motion detector * lightning detection * update default motion config * lint imports * use estimated boxes for regions * use improved motion detector * update test * use a different strategy for clustering motion and object boxes * increase alpha during calibration * simplify object consolidation * add some reasonable constraints to the estimated box * adjust cluster boundary to 10% * refactor * add disabled debug code * fix variable scope
104 lines
3.4 KiB
Python
104 lines
3.4 KiB
Python
import datetime
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import multiprocessing as mp
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import os
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from statistics import mean
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import cv2
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import numpy as np
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from frigate.config import MotionConfig
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from frigate.motion.frigate_motion import FrigateMotionDetector
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from frigate.motion.improved_motion import ImprovedMotionDetector
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# get info on the video
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# cap = cv2.VideoCapture("debug/front_cam_2023_05_23_08_41__2023_05_23_08_43.mp4")
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# cap = cv2.VideoCapture("debug/motion_test_clips/rain_1.mp4")
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cap = cv2.VideoCapture("debug/motion_test_clips/ir_off.mp4")
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# cap = cv2.VideoCapture("airport.mp4")
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width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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fps = cap.get(cv2.CAP_PROP_FPS)
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frame_shape = (height, width, 3)
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# create the motion config
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motion_config = MotionConfig()
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motion_config.mask = np.zeros((height, width), np.uint8)
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motion_config.mask[:] = 255
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motion_config.improve_contrast = 1
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motion_config.frame_alpha = 0.02
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motion_config.threshold = 40
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motion_config.contour_area = 15
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save_images = True
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# create motion detectors
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frigate_motion_detector = FrigateMotionDetector(
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frame_shape=frame_shape,
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config=motion_config,
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fps=fps,
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improve_contrast=mp.Value("i", motion_config.improve_contrast),
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threshold=mp.Value("i", motion_config.threshold),
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contour_area=mp.Value("i", motion_config.contour_area),
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)
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frigate_motion_detector.save_images = save_images
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improved_motion_detector = ImprovedMotionDetector(
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frame_shape=frame_shape,
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config=motion_config,
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fps=fps,
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improve_contrast=mp.Value("i", motion_config.improve_contrast),
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threshold=mp.Value("i", motion_config.threshold),
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contour_area=mp.Value("i", motion_config.contour_area),
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)
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improved_motion_detector.save_images = save_images
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# read and process frames
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frame_times = {"frigate": [], "improved": []}
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ret, frame = cap.read()
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frame_counter = 1
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while ret:
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yuv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV_I420)
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start_frame = datetime.datetime.now().timestamp()
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frigate_motion_detector.detect(yuv_frame)
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frame_times["frigate"].append(datetime.datetime.now().timestamp() - start_frame)
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start_frame = datetime.datetime.now().timestamp()
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improved_motion_detector.detect(yuv_frame)
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frame_times["improved"].append(datetime.datetime.now().timestamp() - start_frame)
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frigate_frame = f"debug/frames/frigate-{frame_counter}.jpg"
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improved_frame = f"debug/frames/improved-{frame_counter}.jpg"
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if os.path.exists(frigate_frame) and os.path.exists(improved_frame):
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image_row_1 = cv2.hconcat(
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[
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cv2.imread(frigate_frame),
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cv2.imread(improved_frame),
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]
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)
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image_row_2 = cv2.resize(
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frame,
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dsize=(
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frigate_motion_detector.motion_frame_size[1] * 2,
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frigate_motion_detector.motion_frame_size[0] * 2,
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),
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interpolation=cv2.INTER_LINEAR,
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)
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cv2.imwrite(
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f"debug/frames/all-{frame_counter}.jpg",
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cv2.vconcat([image_row_1, image_row_2]),
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)
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os.unlink(frigate_frame)
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os.unlink(improved_frame)
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frame_counter += 1
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ret, frame = cap.read()
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cap.release()
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print("Frigate Motion Detector")
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print(f"Average frame processing time: {mean(frame_times['frigate'])*1000:.2f}ms")
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print("Improved Motion Detector")
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print(f"Average frame processing time: {mean(frame_times['improved'])*1000:.2f}ms")
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