Mirrors
/
blakeblackshear.frigate
mirror of https://github.com/blakeblackshear/frigate
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

use a different method for blur and contrast to reduce CPU (#6940)

Browse Source 
* use a different method for blur and contrast to reduce CPU

* blur with radius instead

* use faster interpolation for motion

* improve contrast based on averages

* increase default threshold to 30

* ensure mask is applied after contrast improvement

* update opencv

* update benchmark script
pull/6921/head
Blake Blackshear 11 months ago committed by GitHub
parent d2a2643cd6
commit d51197eaa2
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 60 additions and 23 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 29
      benchmark_motion.py
  2. 2
      docs/docs/configuration/index.md
  3. 2
      frigate/config.py
  4. 48
      frigate/motion/improved_motion.py
  5. 2
      requirements-wheels.txt

29
benchmark_motion.py
Unescape View File

@ -12,16 +12,32 @@ 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/ir_off.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
@ -29,7 +45,7 @@ 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_height = 150
# motion_config_1.frame_alpha = 0.02
# motion_config_1.threshold = 30
# motion_config_1.contour_area = 10
@ -38,10 +54,11 @@ 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_height = 150
# motion_config_2.frame_alpha = 0.01
# motion_config_2.threshold = 20
motion_config_2.threshold = 20
# motion_config.contour_area = 10
save_images = True
improved_motion_detector_1 = ImprovedMotionDetector(
@ -52,8 +69,6 @@ improved_motion_detector_1 = ImprovedMotionDetector(
threshold=mp.Value("i", motion_config_1.threshold),
contour_area=mp.Value("i", motion_config_1.contour_area),
name="default",
clipLimit=2.0,
tileGridSize=(8, 8),
)
improved_motion_detector_1.save_images = save_images

2
docs/docs/configuration/index.md
Unescape View File

@ -280,7 +280,7 @@ motion:
# Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below)
# Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.
# The value should be between 1 and 255.
threshold: 20
threshold: 30
# Optional: The percentage of the image used to detect lightning or other substantial changes where motion detection
# needs to recalibrate. (default: shown below)
# Increasing this value will make motion detection more likely to consider lightning or ir mode changes as valid motion.

2
frigate/config.py
Unescape View File

@ -187,7 +187,7 @@ class RecordConfig(FrigateBaseModel):
class MotionConfig(FrigateBaseModel):
threshold: int = Field(
default=20,
default=30,
title="Motion detection threshold (1-255).",
ge=1,
le=255,

48
frigate/motion/improved_motion.py
Unescape View File

@ -1,6 +1,7 @@
import cv2
import imutils
import numpy as np
from scipy.ndimage import gaussian_filter
from frigate.config import MotionConfig
from frigate.motion import MotionDetector
@ -15,9 +16,10 @@ class ImprovedMotionDetector(MotionDetector):
improve_contrast,
threshold,
contour_area,
clipLimit=2.0,
tileGridSize=(2, 2),
name="improved",
blur_radius=1,
interpolation=cv2.INTER_NEAREST,
contrast_frame_history=50,
):
self.name = name
self.config = config
@ -28,13 +30,12 @@ class ImprovedMotionDetector(MotionDetector):
config.frame_height * frame_shape[1] // frame_shape[0],
)
self.avg_frame = np.zeros(self.motion_frame_size, np.float32)
self.avg_delta = np.zeros(self.motion_frame_size, np.float32)
self.motion_frame_count = 0
self.frame_counter = 0
resized_mask = cv2.resize(
config.mask,
dsize=(self.motion_frame_size[1], self.motion_frame_size[0]),
interpolation=cv2.INTER_LINEAR,
interpolation=cv2.INTER_AREA,
)
self.mask = np.where(resized_mask == [0])
self.save_images = False
@ -42,7 +43,11 @@ class ImprovedMotionDetector(MotionDetector):
self.improve_contrast = improve_contrast
self.threshold = threshold
self.contour_area = contour_area
self.clahe = cv2.createCLAHE(clipLimit=clipLimit, tileGridSize=tileGridSize)
self.blur_radius = blur_radius
self.interpolation = interpolation
self.contrast_values = np.zeros((contrast_frame_history, 2), np.uint8)
self.contrast_values[:, 1:2] = 255
self.contrast_values_index = 0
def detect(self, frame):
motion_boxes = []
@ -53,27 +58,44 @@ class ImprovedMotionDetector(MotionDetector):
resized_frame = cv2.resize(
gray,
dsize=(self.motion_frame_size[1], self.motion_frame_size[0]),
interpolation=cv2.INTER_LINEAR,
interpolation=self.interpolation,
)
if self.save_images:
resized_saved = resized_frame.copy()
resized_frame = cv2.GaussianBlur(resized_frame, (3, 3), cv2.BORDER_DEFAULT)
if self.save_images:
blurred_saved = resized_frame.copy()
# Improve contrast
if self.improve_contrast.value:
resized_frame = self.clahe.apply(resized_frame)
# TODO tracking moving average of min/max to avoid sudden contrast changes
minval = np.percentile(resized_frame, 4).astype(np.uint8)
maxval = np.percentile(resized_frame, 96).astype(np.uint8)
# skip contrast calcs if the image is a single color
if minval < maxval:
# keep track of the last 50 contrast values
self.contrast_values[self.contrast_values_index] = [minval, maxval]
self.contrast_values_index += 1
if self.contrast_values_index == len(self.contrast_values):
self.contrast_values_index = 0
avg_min, avg_max = np.mean(self.contrast_values, axis=0)
resized_frame = np.clip(resized_frame, avg_min, avg_max)
resized_frame = (
((resized_frame - avg_min) / (avg_max - avg_min)) * 255
).astype(np.uint8)
if self.save_images:
contrasted_saved = resized_frame.copy()
# mask frame
# this has to come after contrast improvement
resized_frame[self.mask] = [255]
resized_frame = gaussian_filter(resized_frame, sigma=1, radius=self.blur_radius)
if self.save_images:
blurred_saved = resized_frame.copy()
if self.save_images or self.calibrating:
self.frame_counter += 1
# compare to average
@ -134,8 +156,8 @@ class ImprovedMotionDetector(MotionDetector):
)
frames = [
cv2.cvtColor(resized_saved, cv2.COLOR_GRAY2BGR),
cv2.cvtColor(blurred_saved, cv2.COLOR_GRAY2BGR),
cv2.cvtColor(contrasted_saved, cv2.COLOR_GRAY2BGR),
cv2.cvtColor(blurred_saved, cv2.COLOR_GRAY2BGR),
cv2.cvtColor(frameDelta, cv2.COLOR_GRAY2BGR),
cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR),
thresh_dilated,

2
requirements-wheels.txt
Unescape View File

@ -6,7 +6,7 @@ matplotlib == 3.7.*
mypy == 0.942
numpy == 1.23.*
onvif_zeep == 0.2.12
opencv-python-headless == 4.5.5.*
opencv-python-headless == 4.7.0.*
paho-mqtt == 1.6.*
peewee == 3.16.*
peewee_migrate == 1.10.*

Write Preview
Loading…
Cancel
Save