blakeblackshear.frigate/benchmark_motion.py
Blake Blackshear d81dd60fef
Improve motion detection and region selection (#6741)
* 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
2023-06-11 08:45:11 -05:00

104 lines
3.4 KiB
Python

import datetime
import multiprocessing as mp
import os
from statistics import mean
import cv2
import numpy as np
from frigate.config import MotionConfig
from frigate.motion.frigate_motion import FrigateMotionDetector
from frigate.motion.improved_motion import ImprovedMotionDetector
# get info on the video
# cap = cv2.VideoCapture("debug/front_cam_2023_05_23_08_41__2023_05_23_08_43.mp4")
# cap = cv2.VideoCapture("debug/motion_test_clips/rain_1.mp4")
cap = cv2.VideoCapture("debug/motion_test_clips/ir_off.mp4")
# cap = cv2.VideoCapture("airport.mp4")
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = cap.get(cv2.CAP_PROP_FPS)
frame_shape = (height, width, 3)
# create the motion config
motion_config = MotionConfig()
motion_config.mask = np.zeros((height, width), np.uint8)
motion_config.mask[:] = 255
motion_config.improve_contrast = 1
motion_config.frame_alpha = 0.02
motion_config.threshold = 40
motion_config.contour_area = 15
save_images = True
# create motion detectors
frigate_motion_detector = FrigateMotionDetector(
frame_shape=frame_shape,
config=motion_config,
fps=fps,
improve_contrast=mp.Value("i", motion_config.improve_contrast),
threshold=mp.Value("i", motion_config.threshold),
contour_area=mp.Value("i", motion_config.contour_area),
)
frigate_motion_detector.save_images = save_images
improved_motion_detector = ImprovedMotionDetector(
frame_shape=frame_shape,
config=motion_config,
fps=fps,
improve_contrast=mp.Value("i", motion_config.improve_contrast),
threshold=mp.Value("i", motion_config.threshold),
contour_area=mp.Value("i", motion_config.contour_area),
)
improved_motion_detector.save_images = save_images
# read and process frames
frame_times = {"frigate": [], "improved": []}
ret, frame = cap.read()
frame_counter = 1
while ret:
yuv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2YUV_I420)
start_frame = datetime.datetime.now().timestamp()
frigate_motion_detector.detect(yuv_frame)
frame_times["frigate"].append(datetime.datetime.now().timestamp() - start_frame)
start_frame = datetime.datetime.now().timestamp()
improved_motion_detector.detect(yuv_frame)
frame_times["improved"].append(datetime.datetime.now().timestamp() - start_frame)
frigate_frame = f"debug/frames/frigate-{frame_counter}.jpg"
improved_frame = f"debug/frames/improved-{frame_counter}.jpg"
if os.path.exists(frigate_frame) and os.path.exists(improved_frame):
image_row_1 = cv2.hconcat(
[
cv2.imread(frigate_frame),
cv2.imread(improved_frame),
]
)
image_row_2 = cv2.resize(
frame,
dsize=(
frigate_motion_detector.motion_frame_size[1] * 2,
frigate_motion_detector.motion_frame_size[0] * 2,
),
interpolation=cv2.INTER_LINEAR,
)
cv2.imwrite(
f"debug/frames/all-{frame_counter}.jpg",
cv2.vconcat([image_row_1, image_row_2]),
)
os.unlink(frigate_frame)
os.unlink(improved_frame)
frame_counter += 1
ret, frame = cap.read()
cap.release()
print("Frigate Motion Detector")
print(f"Average frame processing time: {mean(frame_times['frigate'])*1000:.2f}ms")
print("Improved Motion Detector")
print(f"Average frame processing time: {mean(frame_times['improved'])*1000:.2f}ms")