Frigate NVR: Difference between revisions
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privileged: true # this may not be necessary for all setups | privileged: true # this may not be necessary for all setups | ||
restart: unless-stopped | restart: unless-stopped | ||
image: blakeblackshear/frigate:stable | image: ghcr.io/blakeblackshear/frigate:stable-tensorrt | ||
network_mode: bridge | network_mode: bridge | ||
deploy: | deploy: | ||
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shm_size: "128mb" # update for your cameras based on calculation above | shm_size: "128mb" # update for your cameras based on calculation above | ||
devices: | devices: | ||
# - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions | |||
volumes: | volumes: | ||
- /etc/localtime:/etc/localtime:ro | - /etc/localtime:/etc/localtime:ro | ||
- /etc/frigate/config.yml:/config/config.yml | - /etc/frigate/trt-models:/trt-models:ro | ||
- /etc/frigate/config.yml:/config/config.yml | |||
- /srv/cctv:/media/frigate | - /srv/cctv:/media/frigate | ||
- type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear | - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear | ||
Line 148: | Line 148: | ||
size: 1000000000 | size: 1000000000 | ||
ports: | ports: | ||
- "5000:5000" | |||
- "8554:8554" # RTSP feeds | |||
- "8555:8555/tcp" # WebRTC over tcp | |||
- "8555:8555/udp" # WebRTC over udp | |||
environment: | environment: | ||
FRIGATE_RTSP_PASSWORD: "<Strong Password>" | FRIGATE_RTSP_PASSWORD: "<Strong Password>" |
Revision as of 21:28, 9 May 2023
Frigate NVR
Docker
Download and save the Docker repository signing key:
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | gpg --dearmor -o /etc/apt/keyrings/docker.gpg
Add the Docker repository in /etc/apt/sources.list.d/docker.list:
deb [arch=amd64 signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu jammy stable
Allow unattended updates from this repository by add to /etc/apt/apt.conf.d/50unattended-upgrades:
Unattended-Upgrade::Allowed-Origins { // Append to end of existing entries "Docker:${distro_codename}"; };
Update the repositories and install the package:
apt update apt install docker-ce docker-ce-cli containerd.io docker-compose-plugin
Check all is working with:
docker version
Stop the services:
systemctl stop docker.service systemctl stop docker.socket systemctl stop containerd.service
Move the Docker root directory:
mv /var/lib/docker /srv/data
Edit the systemd service for Docker:
systemctl edit docker.service
Add the following to the top of the override file:
[Service] ExecStart= ExecStart=/usr/bin/dockerd -–data-root=/srv/data/docker -H fd:// --containerd=/run/containerd/containerd.sock
Restart Docker:
systemctl daemon-reload systemctl start docker.service
Check it still works with:
docker run hello-world
GPU Hardware Acceleration
Download and save the NVIDIA repository signing key:
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | gpg --dearmor -o /etc/apt/keyrings/nvidia-container.gpg
Add the Docker repository in /etc/apt/sources.list.d/nvidia-container.list:
deb [signed-by=/etc/apt/keyrings/nvidia-container.gpg] https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/$(ARCH) /
Allow unattended updates from this repository by add to /etc/apt/apt.conf.d/50unattended-upgrades:
Unattended-Upgrade::Origins-Pattern { "site=nvidia.github.io"; };
Update the repositories and install the package:
apt update apt install nvidia-docker2
Restart Docker:
systemctl start docker.service
Frigate
If using ZFS, create a filesystem to store the video recordings (not used currently)
zfs create -o recordsize=1M -o compression=off -o quota=256G data/cctv
Create a configuration directory for Frigate:
mkdir /etc/frigate
If using NVidia TensorRT object detection, download and train the models:
Get the training image
cd /etc/frigate wget https://github.com/blakeblackshear/frigate/raw/master/docker/tensorrt_models.sh chmod +x tensorrt_models.sh
Run the script to train.
docker run --gpus=all --rm -it -e USE_FP16=False -v `pwd`/trt-models:/tensorrt_models -v `pwd`/tensorrt_models.sh:/tensorrt_models.sh nvcr.io/nvidia/tensorrt:22.07-py3 /tensorrt_models.sh
Cleanup the image used to train with this.
docker image prune -a
Create /etc/frigate/docker-compose.yml:
version: "3.9"
services:
frigate:
container_name: frigate
privileged: true # this may not be necessary for all setups
restart: unless-stopped
image: ghcr.io/blakeblackshear/frigate:stable-tensorrt
network_mode: bridge
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
shm_size: "128mb" # update for your cameras based on calculation above
devices:
# - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions
volumes:
- /etc/localtime:/etc/localtime:ro
- /etc/frigate/trt-models:/trt-models:ro
- /etc/frigate/config.yml:/config/config.yml
- /srv/cctv:/media/frigate
- type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
target: /tmp/cache
tmpfs:
size: 1000000000
ports:
- "5000:5000"
- "8554:8554" # RTSP feeds
- "8555:8555/tcp" # WebRTC over tcp
- "8555:8555/udp" # WebRTC over udp
environment:
FRIGATE_RTSP_PASSWORD: "<Strong Password>"
Create /etc/frigate/config.yml:
mqtt: host: mqtt.example.net user: mqttbr password: <Broker Password> detectors: coral: type: edgetpu device: usb ffmpeg: hwaccel_args: -c:v h264_cuvid input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rw_timeout 5000000 -use_wallclock_as_timestamps 1 -f live_flv cameras: BackGarden: ffmpeg: inputs: - path: rtmp://backgarden.iot.example.net/bcs/channel0_sub.bcs?channel=0&stream=0&user=frigate&password=<Camera Password> roles: - detect - rtmp - path: rtmp://backgarden.iot.example.net/bcs/channel0_main.bcs?channel=0&stream=0&user=frigate&password=<Camera Password> roles: - record detect: width: 640 height: 360 fps: 4 record: enabled: True retain: days: 14 mode: motion events: retain: default: 90 mode: active_objects
Start Frigate with:
docker compose -f /etc/frigate/docker-compose.yml up -d
Visit the Frigate interface via:
http://server:5000/