forked from blakeblackshear/frigate
-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathbenchmark_motion.py
More file actions
123 lines (107 loc) · 3.84 KB
/
benchmark_motion.py
File metadata and controls
123 lines (107 loc) · 3.84 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
import datetime
import multiprocessing as mp
import os
import av
import cv2
import numpy as np
from frigate.config import MotionConfig
from frigate.motion.improved_motion import ImprovedMotionDetector
from frigate.util import create_mask
# 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/lawn_mower_night_1.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)
# Nick back:
# "1280,0,1280,316,1170,216,1146,126,1016,127,979,82,839,0",
# "310,350,300,402,224,405,241,354",
# "378,0,375,26,0,23,0,0",
# Front door:
# "1080,0,1080,339,1010,280,1020,169,777,163,452,170,318,299,191,365,186,417,139,470,108,516,40,530,0,514,0,0",
# "336,833,438,1024,346,1093,103,1052,24,814",
# Back
# "1855,0,1851,100,1289,96,1105,161,1045,119,890,121,890,0",
# "505,95,506,138,388,153,384,114",
# "689,72,689,122,549,134,547,89",
# "261,134,264,176,169,195,167,158",
# "145,159,146,202,70,220,65,183",
mask = create_mask(
(height, width),
[
"1080,0,1080,339,1010,280,1020,169,777,163,452,170,318,299,191,365,186,417,139,470,108,516,40,530,0,514,0,0",
"336,833,438,1024,346,1093,103,1052,24,814",
],
)
# create the motion config
motion_config_1 = MotionConfig()
motion_config_1.mask = np.zeros((height, width), np.uint8)
motion_config_1.mask[:] = mask
# motion_config_1.improve_contrast = 1
motion_config_1.frame_height = 150
# motion_config_1.frame_alpha = 0.02
# motion_config_1.threshold = 30
# motion_config_1.contour_area = 10
motion_config_2 = MotionConfig()
motion_config_2.mask = np.zeros((height, width), np.uint8)
motion_config_2.mask[:] = mask
# motion_config_2.improve_contrast = 1
motion_config_2.frame_height = 150
# motion_config_2.frame_alpha = 0.01
motion_config_2.threshold = 20
# motion_config.contour_area = 10
save_images = True
improved_motion_detector_1 = ImprovedMotionDetector(
frame_shape=frame_shape,
config=motion_config_1,
fps=fps,
improve_contrast=mp.Value("i", motion_config_1.improve_contrast),
threshold=mp.Value("i", motion_config_1.threshold),
contour_area=mp.Value("i", motion_config_1.contour_area),
name="default",
)
improved_motion_detector_1.save_images = save_images
improved_motion_detector_2 = ImprovedMotionDetector(
frame_shape=frame_shape,
config=motion_config_2,
fps=fps,
improve_contrast=mp.Value("i", motion_config_2.improve_contrast),
threshold=mp.Value("i", motion_config_2.threshold),
contour_area=mp.Value("i", motion_config_2.contour_area),
name="compare",
)
improved_motion_detector_2.save_images = save_images
# read and process frames
ret, frame = cap.read()
frame_counter = 1
while ret:
yuv_frame = (
av.VideoFrame.from_ndarray(frame, format="bgr24")
.reformat(format="nv12")
.to_ndarray()
)
start_frame = datetime.datetime.now().timestamp()
improved_motion_detector_1.detect(yuv_frame)
start_frame = datetime.datetime.now().timestamp()
improved_motion_detector_2.detect(yuv_frame)
default_frame = f"debug/frames/default-{frame_counter}.jpg"
compare_frame = f"debug/frames/compare-{frame_counter}.jpg"
if os.path.exists(default_frame) and os.path.exists(compare_frame):
images = [
cv2.imread(default_frame),
cv2.imread(compare_frame),
]
cv2.imwrite(
f"debug/frames/all-{frame_counter}.jpg",
cv2.vconcat(images)
if frame_shape[0] > frame_shape[1]
else cv2.hconcat(images),
)
os.unlink(default_frame)
os.unlink(compare_frame)
frame_counter += 1
ret, frame = cap.read()
cap.release()