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https://github.com/blakeblackshear/frigate.git
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create a simplified motion detector
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Blake Blackshear
parent
3c58d44f91
commit
e344dea4c3
103
benchmark_motion.py
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103
benchmark_motion.py
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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/low_contrast_ir.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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@ -12,9 +12,9 @@ class FrigateMotionDetector(MotionDetector):
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frame_shape,
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config: MotionConfig,
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fps: int,
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improve_contrast_enabled,
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motion_threshold,
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motion_contour_area,
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improve_contrast,
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threshold,
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contour_area,
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):
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self.config = config
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self.frame_shape = frame_shape
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@ -34,9 +34,9 @@ class FrigateMotionDetector(MotionDetector):
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)
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self.mask = np.where(resized_mask == [0])
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self.save_images = False
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self.improve_contrast = improve_contrast_enabled
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self.threshold = motion_threshold
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self.contour_area = motion_contour_area
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self.improve_contrast = improve_contrast
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self.threshold = threshold
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self.contour_area = contour_area
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def detect(self, frame):
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motion_boxes = []
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@ -132,18 +132,10 @@ class FrigateMotionDetector(MotionDetector):
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(0, 0, 255),
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2,
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)
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# print("--------")
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image_row_1 = cv2.hconcat(
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[
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cv2.cvtColor(frameDelta, cv2.COLOR_GRAY2BGR),
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cv2.cvtColor(avg_delta_image, cv2.COLOR_GRAY2BGR),
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]
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cv2.imwrite(
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f"debug/frames/frigate-{self.frame_counter}.jpg", thresh_dilated
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)
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image_row_2 = cv2.hconcat(
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[cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR), thresh_dilated]
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)
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combined_image = cv2.vconcat([image_row_1, image_row_2])
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cv2.imwrite(f"motion/motion-{self.frame_counter}.jpg", combined_image)
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if len(motion_boxes) > 0:
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self.motion_frame_count += 1
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126
frigate/motion/improved_motion.py
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126
frigate/motion/improved_motion.py
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import cv2
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import imutils
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import numpy as np
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from frigate.config import MotionConfig
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from frigate.motion import MotionDetector
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class ImprovedMotionDetector(MotionDetector):
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def __init__(
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self,
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frame_shape,
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config: MotionConfig,
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fps: int,
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improve_contrast,
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threshold,
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contour_area,
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):
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self.config = config
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self.frame_shape = frame_shape
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self.resize_factor = frame_shape[0] / config.frame_height
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self.motion_frame_size = (
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config.frame_height,
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config.frame_height * frame_shape[1] // frame_shape[0],
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)
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self.avg_frame = np.zeros(self.motion_frame_size, np.float32)
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self.avg_delta = np.zeros(self.motion_frame_size, np.float32)
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self.motion_frame_count = 0
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self.frame_counter = 0
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resized_mask = cv2.resize(
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config.mask,
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dsize=(self.motion_frame_size[1], self.motion_frame_size[0]),
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interpolation=cv2.INTER_LINEAR,
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)
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self.mask = np.where(resized_mask == [0])
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self.save_images = False
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self.improve_contrast = improve_contrast
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self.threshold = threshold
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self.contour_area = contour_area
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def detect(self, frame):
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motion_boxes = []
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gray = frame[0 : self.frame_shape[0], 0 : self.frame_shape[1]]
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# resize frame
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resized_frame = cv2.resize(
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gray,
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dsize=(self.motion_frame_size[1], self.motion_frame_size[0]),
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interpolation=cv2.INTER_LINEAR,
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)
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resized_frame = cv2.GaussianBlur(resized_frame, (3, 3), cv2.BORDER_DEFAULT)
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# Improve contrast
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if self.improve_contrast.value:
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resized_frame = cv2.equalizeHist(resized_frame)
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# mask frame
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resized_frame[self.mask] = [255]
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if self.save_images:
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self.frame_counter += 1
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# compare to average
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frameDelta = cv2.absdiff(resized_frame, cv2.convertScaleAbs(self.avg_frame))
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# compute the threshold image for the current frame
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thresh = cv2.threshold(
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frameDelta, self.threshold.value, 255, cv2.THRESH_BINARY
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)[1]
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# dilate the thresholded image to fill in holes, then find contours
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# on thresholded image
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thresh_dilated = cv2.dilate(thresh, None, iterations=1)
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cnts = cv2.findContours(
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thresh_dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
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)
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cnts = imutils.grab_contours(cnts)
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# loop over the contours
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for c in cnts:
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# if the contour is big enough, count it as motion
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contour_area = cv2.contourArea(c)
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if contour_area > self.contour_area.value:
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x, y, w, h = cv2.boundingRect(c)
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motion_boxes.append(
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(
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int(x * self.resize_factor),
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int(y * self.resize_factor),
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int((x + w) * self.resize_factor),
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int((y + h) * self.resize_factor),
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)
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)
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if self.save_images:
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thresh_dilated = cv2.cvtColor(thresh_dilated, cv2.COLOR_GRAY2BGR)
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for c in cnts:
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contour_area = cv2.contourArea(c)
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if contour_area > self.contour_area.value:
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x, y, w, h = cv2.boundingRect(c)
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cv2.rectangle(
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thresh_dilated,
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(x, y),
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(x + w, y + h),
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(0, 0, 255),
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2,
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)
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cv2.imwrite(
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f"debug/frames/improved-{self.frame_counter}.jpg", thresh_dilated
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)
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if len(motion_boxes) > 0:
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self.motion_frame_count += 1
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if self.motion_frame_count >= 10:
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# only average in the current frame if the difference persists for a bit
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cv2.accumulateWeighted(
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resized_frame, self.avg_frame, self.config.frame_alpha
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)
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else:
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# when no motion, just keep averaging the frames together
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cv2.accumulateWeighted(
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resized_frame, self.avg_frame, self.config.frame_alpha
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)
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self.motion_frame_count = 0
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return motion_boxes
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