Frigate

git clone -b rpi-axcl https://huggingface.co/AXERA-TECH/frigate-resource

m5stack@raspberrypi:~/rsp/frigate-resource $ ls -lh
total 2.8G
-rw-rw-r-- 1 m5stack m5stack  48M Oct  9 16:46 axcl_host_aarch64_V3.6.5_20250908154509_NO4973.deb
-rw-rw-r-- 1 m5stack m5stack  648 Oct  9 16:41 docker-compose.yml
-rw-rw-r-- 1 m5stack m5stack 2.8G Oct  9 16:46 frigate-rpi-axcl-f8f387a.tar
-rw-rw-r-- 1 m5stack m5stack 3.7K Oct  9 16:41 README.md

docker load -i frigate-resource/frigate-rpi-axcl-f8f387a.tar # The image file may be updated, use the actual file name.

mkdir -p ~/frigate-runtime/{config,storage}
cp frigate-resource/docker-compose.yml ~/frigate-runtime/

cd ~/frigate-runtime/
docker compose up -d

#ffmpeg global variables, required
ffmpeg:
  global_args: ["-hide_banner", "-loglevel", "warning", "-threads", "1"]
  output_args:
    detect: ["-threads", "1", "-f", "rawvideo",  "-pix_fmt", "yuv420p"]
mqtt:
  enabled: false
go2rtc:
  streams:
    #main stream
    road1:
      - rtsp://192.168.20.57:8554/road1.264
    #sub stream
    road1_sub:
      - rtsp://192.168.20.57:8554/road1_sub.264
cameras:
  road1:
    enabled: true
    ffmpeg:
      inputs:
        #path to the recording stream, here using the main stream set in go2rtc
        #during debugging, you can use local stream files here
        - path: rtsp://127.0.0.1:8554/road1
          roles:
            - record
        #path to the detection stream, here using the sub stream set in go2rtc
        #during debugging, you can use local stream files here
        - path: rtsp://127.0.0.1:8554/road1_sub
          roles:
            - detect
      #preset-rpi-64-h264 for decoding h264 stream
      #preset-rpi-64-h265 for decoding h265 stream
      hwaccel_args: preset-rpi-64-h264
record:
  enabled: true
 
#Enable detection function
#If detection width/height is not set, it will default to the native resolution of the detection stream
detect:
  enabled: true
  width: 1280
  height: 720
  fps: 5
 
#Configure detection engine to use axengine
detectors:
  axengine:
    type: axengine
 
#Configure object detection model for axengine
model:
  path: yolov5s_320
  width: 320
  height: 320
  input_pixel_format: bgr
  labelmap_path: /labelmap/coco-80.txt
 
#Object types to track
objects:
  track:
    - person
    - car
    - bicycle
    - motorcycle
 
version: 0.16-0