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Merge branch 'dev' into 230615-feature-camera-live-preview

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This commit is contained in:
Sergey Krashevich 2023-11-27 02:39:19 +03:00
commit d8b479c5fc
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249 changed files with 21188 additions and 18614 deletions
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6
.devcontainer/devcontainer.json
View File

@ -42,7 +42,6 @@
"extensions": [
"ms-python.python",
"ms-python.vscode-pylance",
"ms-python.black-formatter",
"visualstudioexptteam.vscodeintellicode",
"mhutchie.git-graph",
"ms-azuretools.vscode-docker",
@ -53,13 +52,10 @@
"csstools.postcss",
"blanu.vscode-styled-jsx",
"bradlc.vscode-tailwindcss",
"ms-python.isort",
"charliermarsh.ruff"
],
"settings": {
"remote.autoForwardPorts": false,
"python.linting.pylintEnabled": true,
"python.linting.enabled": true,
"python.formatting.provider": "none",
"python.languageServer": "Pylance",
"editor.formatOnPaste": false,
@ -72,7 +68,7 @@
"eslint.workingDirectories": ["./web"],
"isort.args": ["--settings-path=./pyproject.toml"],
"[python]": {
"editor.defaultFormatter": "ms-python.black-formatter",
"editor.defaultFormatter": "charliermarsh.ruff",
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.fixAll": true,

39
.github/actions/setup/action.yml vendored Normal file
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@ -0,0 +1,39 @@
name: 'Setup'
description: 'Set up QEMU and Buildx'
inputs:
GITHUB_TOKEN:
required: true
outputs:
image-name:
value: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ steps.create-short-sha.outputs.SHORT_SHA }}
cache-name:
value: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:cache
runs:
using: "composite"
steps:
- name: Remove unnecessary files
run: |
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
shell: bash
- id: lowercaseRepo
uses: ASzc/change-string-case-action@v5
with:
string: ${{ github.repository }}
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Log in to the Container registry
uses: docker/login-action@465a07811f14bebb1938fbed4728c6a1ff8901fc
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ inputs.GITHUB_TOKEN }}
- name: Create version file
run: make version
shell: bash
- id: create-short-sha
run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_OUTPUT
shell: bash

8
.github/dependabot.yml vendored
View File

@ -13,7 +13,13 @@ updates:
open-pull-requests-limit: 10
target-branch: dev
- package-ecosystem: "pip"
directory: "/"
directory: "/docker/main"
schedule:
interval: daily
open-pull-requests-limit: 10
target-branch: dev
- package-ecosystem: "pip"
directory: "/docker/tensorrt"
schedule:
interval: daily
open-pull-requests-limit: 10

176
.github/workflows/ci.yml vendored
View File

@ -1,6 +1,7 @@
name: CI
on:
workflow_dispatch:
push:
branches:
- dev
@ -15,53 +16,154 @@ env:
PYTHON_VERSION: 3.9
jobs:
multi_arch_build:
amd64_build:
runs-on: ubuntu-latest
name: Image Build
name: AMD64 Build
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push amd64 standard build
uses: docker/build-push-action@v5
with:
context: .
file: docker/main/Dockerfile
push: true
platforms: linux/amd64
target: frigate
tags: ${{ steps.setup.outputs.image-name }}-amd64
cache-from: type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
- name: Build and push TensorRT (x86 GPU)
uses: docker/bake-action@v4
with:
push: true
targets: tensorrt
files: docker/tensorrt/trt.hcl
set: |
tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64,mode=max
arm64_build:
runs-on: ubuntu-latest
name: ARM Build
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push arm64 standard build
uses: docker/build-push-action@v5
with:
context: .
file: docker/main/Dockerfile
push: true
platforms: linux/arm64
target: frigate
tags: |
${{ steps.setup.outputs.image-name }}-standard-arm64
cache-from: type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64
- name: Build and push RPi build
uses: docker/bake-action@v4
with:
push: true
targets: rpi
files: docker/rpi/rpi.hcl
set: |
rpi.tags=${{ steps.setup.outputs.image-name }}-rpi
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64,mode=max
- name: Build and push RockChip build
uses: docker/bake-action@v3
with:
push: true
targets: rk
files: docker/rockchip/rk.hcl
set: |
rk.tags=${{ steps.setup.outputs.image-name }}-rk
*.cache-from=type=gha
jetson_jp4_build:
runs-on: ubuntu-latest
name: Jetson Jetpack 4
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push TensorRT (Jetson, Jetpack 4)
env:
ARCH: arm64
BASE_IMAGE: timongentzsch/l4t-ubuntu20-opencv:latest
SLIM_BASE: timongentzsch/l4t-ubuntu20-opencv:latest
TRT_BASE: timongentzsch/l4t-ubuntu20-opencv:latest
uses: docker/bake-action@v4
with:
push: true
targets: tensorrt
files: docker/tensorrt/trt.hcl
set: |
tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt-jp4
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp4
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp4,mode=max
jetson_jp5_build:
runs-on: ubuntu-latest
name: Jetson Jetpack 5
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push TensorRT (Jetson, Jetpack 5)
env:
ARCH: arm64
BASE_IMAGE: nvcr.io/nvidia/l4t-tensorrt:r8.5.2-runtime
SLIM_BASE: nvcr.io/nvidia/l4t-tensorrt:r8.5.2-runtime
TRT_BASE: nvcr.io/nvidia/l4t-tensorrt:r8.5.2-runtime
uses: docker/bake-action@v4
with:
push: true
targets: tensorrt
files: docker/tensorrt/trt.hcl
set: |
tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt-jp5
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp5
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp5,mode=max
# The majority of users running arm64 are rpi users, so the rpi
# build should be the primary arm64 image
assemble_default_build:
runs-on: ubuntu-latest
name: Assemble and push default build
needs:
- amd64_build
- arm64_build
steps:
- name: Remove unnecessary files
run: |
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
- id: lowercaseRepo
uses: ASzc/change-string-case-action@v5
uses: ASzc/change-string-case-action@v6
with:
string: ${{ github.repository }}
- name: Check out code
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Log in to the Container registry
uses: docker/login-action@465a07811f14bebb1938fbed4728c6a1ff8901fc
uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create version file
run: make version
- name: Create short sha
run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_ENV
- name: Build and push
uses: docker/build-push-action@v4
- uses: int128/docker-manifest-create-action@v1
with:
context: .
push: true
platforms: linux/amd64,linux/arm64
target: frigate
tags: |
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}
cache-from: type=gha
cache-to: type=gha,mode=max
- name: Build and push TensorRT
uses: docker/build-push-action@v4
with:
context: .
push: true
platforms: linux/amd64
target: frigate-tensorrt
tags: |
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}-tensorrt
cache-from: type=gha
tags: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}
suffixes: |
-amd64
-rpi

45
.github/workflows/maintain_cache.yml vendored
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@ -1,45 +0,0 @@
name: Maintain Cache
on:
schedule:
- cron: "13 0 * * 0,4"
env:
PYTHON_VERSION: 3.9
jobs:
multi_arch_build:
runs-on: ubuntu-latest
name: Image Build
steps:
- name: Remove unnecessary files
run: |
sudo rm -rf /usr/share/dotnet
sudo rm -rf /usr/local/lib/android
sudo rm -rf /opt/ghc
- id: lowercaseRepo
uses: ASzc/change-string-case-action@v5
with:
string: ${{ github.repository }}
- name: Check out code
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- name: Log in to the Container registry
uses: docker/login-action@465a07811f14bebb1938fbed4728c6a1ff8901fc
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create version file
run: make version
- name: Build and push
uses: docker/build-push-action@v4
with:
context: .
push: false
platforms: linux/amd64,linux/arm64
target: frigate
cache-from: type=gha

27
.github/workflows/pull_request.yml vendored
View File

@ -15,7 +15,7 @@ jobs:
env:
DOCKER_BUILDKIT: "1"
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -34,7 +34,7 @@ jobs:
name: Web - Lint
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -48,7 +48,7 @@ jobs:
name: Web - Test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -63,22 +63,19 @@ jobs:
name: Python Checks
steps:
- name: Check out the repository
uses: actions/checkout@v3
uses: actions/checkout@v4
- name: Set up Python ${{ env.DEFAULT_PYTHON }}
uses: actions/setup-python@v4.6.1
uses: actions/setup-python@v4.7.1
with:
python-version: ${{ env.DEFAULT_PYTHON }}
- name: Install requirements
run: |
python3 -m pip install -U pip
python3 -m pip install -r requirements-dev.txt
- name: Check black
python3 -m pip install -r docker/main/requirements-dev.txt
- name: Check formatting
run: |
black --check --diff frigate migrations docker *.py
- name: Check isort
run: |
isort --check --diff frigate migrations docker *.py
- name: Check ruff
ruff format --check --diff frigate migrations docker *.py
- name: Check lint
run: |
ruff check frigate migrations docker *.py
@ -87,7 +84,7 @@ jobs:
name: Python Tests
steps:
- name: Check out code
uses: actions/checkout@v3
uses: actions/checkout@v4
- uses: actions/setup-node@master
with:
node-version: 16.x
@ -97,9 +94,9 @@ jobs:
run: npm run build
working-directory: ./web
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
uses: docker/setup-buildx-action@v3
- name: Build
run: make
- name: Run mypy

37
.github/workflows/release.yml vendored Normal file
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@ -0,0 +1,37 @@
name: On release
on:
workflow_dispatch:
release:
types: [published]
jobs:
release:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- id: lowercaseRepo
uses: ASzc/change-string-case-action@v6
with:
string: ${{ github.repository }}
- name: Log in to the Container registry
uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create tag variables
run: |
BRANCH=$([[ "${{ github.ref_name }}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "master" || echo "dev")
echo "BASE=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}" >> $GITHUB_ENV
echo "BUILD_TAG=${BRANCH}-${GITHUB_SHA::7}" >> $GITHUB_ENV
echo "CLEAN_VERSION=$(echo ${GITHUB_REF##*/} | tr '[:upper:]' '[:lower:]' | sed 's/^[v]//')" >> $GITHUB_ENV
- name: Tag and push the main image
run: |
VERSION_TAG=${BASE}:${CLEAN_VERSION}
PULL_TAG=${BASE}:${BUILD_TAG}
docker run --rm -v $HOME/.docker/config.json:/config.json quay.io/skopeo/stable:latest copy --authfile /config.json --multi-arch all docker://${PULL_TAG} docker://${VERSION_TAG}
for variant in standard-arm64 tensorrt tensorrt-jp4 tensorrt-jp5 rk; do
docker run --rm -v $HOME/.docker/config.json:/config.json quay.io/skopeo/stable:latest copy --authfile /config.json --multi-arch all docker://${PULL_TAG}-${variant} docker://${VERSION_TAG}-${variant}
done

6
CODEOWNERS Normal file
View File

@ -0,0 +1,6 @@
# Community-supported boards
/docker/tensorrt/ @madsciencetist @NateMeyer
/docker/tensorrt/*arm64* @madsciencetist
/docker/tensorrt/*jetson* @madsciencetist
/docker/rockchip/ @MarcA711

25
Makefile
View File

@ -3,31 +3,34 @@ default_target: local
COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
VERSION = 0.13.0
IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD)
CURRENT_UID := $(shell id -u)
CURRENT_GID := $(shell id -g)
BOARDS= #Initialized empty
include docker/*/*.mk
build-boards: $(BOARDS:%=build-%)
push-boards: $(BOARDS:%=push-%)
version:
echo 'VERSION = "$(VERSION)-$(COMMIT_HASH)"' > frigate/version.py
local: version
docker buildx build --target=frigate --tag frigate:latest --load .
local-trt: version
docker buildx build --target=frigate-tensorrt --tag frigate:latest-tensorrt --load .
docker buildx build --target=frigate --tag frigate:latest --load --file docker/main/Dockerfile .
amd64:
docker buildx build --platform linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
docker buildx build --platform linux/amd64 --target=frigate-tensorrt --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH)-tensorrt .
docker buildx build --platform linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
arm64:
docker buildx build --platform linux/arm64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
docker buildx build --platform linux/arm64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
build: version amd64 arm64
docker buildx build --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
docker buildx build --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
push: build
docker buildx build --push --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) .
docker buildx build --push --platform linux/amd64 --target=frigate-tensorrt --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt .
push: push-boards
docker buildx build --push --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) --file docker/main/Dockerfile .
run: local
docker run --rm --publish=5000:5000 --volume=${PWD}/config:/config frigate:latest

20
docker-compose.yml
View File

@ -11,15 +11,19 @@ services:
shm_size: "256mb"
build:
context: .
dockerfile: docker/main/Dockerfile
# Use target devcontainer-trt for TensorRT dev
target: devcontainer
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
## Uncomment this block for nvidia gpu support
# deploy:
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: 1
# capabilities: [gpu]
environment:
YOLO_MODELS: yolov7-320
devices:
- /dev/bus/usb:/dev/bus/usb
# - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware
@ -29,8 +33,6 @@ services:
- /etc/localtime:/etc/localtime:ro
- ./config:/config
- ./debug:/media/frigate
# Create the trt-models folder using the documented method of generating TRT models
# - ./debug/trt-models:/trt-models
- /dev/bus/usb:/dev/bus/usb
mqtt:
container_name: mqtt

127
Dockerfile → docker/main/Dockerfile
View File

@ -1,13 +1,16 @@
# syntax=docker/dockerfile:1.2
# syntax=docker/dockerfile:1.6
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
FROM debian:11 AS base
ARG BASE_IMAGE=debian:11
ARG SLIM_BASE=debian:11-slim
FROM --platform=linux/amd64 debian:11 AS base_amd64
FROM ${BASE_IMAGE} AS base
FROM debian:11-slim AS slim-base
FROM --platform=${BUILDPLATFORM} debian:11 AS base_host
FROM ${SLIM_BASE} AS slim-base
FROM slim-base AS wget
ARG DEBIAN_FRONTEND
@ -23,15 +26,14 @@ ENV CCACHE_MAXSIZE 2G
# bind /var/cache/apt to tmpfs to speed up nginx build
RUN --mount=type=tmpfs,target=/tmp --mount=type=tmpfs,target=/var/cache/apt \
--mount=type=bind,source=docker/build_nginx.sh,target=/deps/build_nginx.sh \
--mount=type=bind,source=docker/main/build_nginx.sh,target=/deps/build_nginx.sh \
--mount=type=cache,target=/root/.ccache \
/deps/build_nginx.sh
FROM wget AS go2rtc
FROM scratch AS go2rtc
ARG TARGETARCH
WORKDIR /rootfs/usr/local/go2rtc/bin
RUN wget -qO go2rtc "https://github.com/AlexxIT/go2rtc/releases/download/v1.5.0/go2rtc_linux_${TARGETARCH}" \
&& chmod +x go2rtc
ADD --link --chmod=755 "https://github.com/AlexxIT/go2rtc/releases/download/v1.8.4/go2rtc_linux_${TARGETARCH}" go2rtc
####
@ -43,11 +45,11 @@ RUN wget -qO go2rtc "https://github.com/AlexxIT/go2rtc/releases/download/v1.5.0/
#
####
# Download and Convert OpenVino model
FROM base_amd64 AS ov-converter
FROM base_host AS ov-converter
ARG DEBIAN_FRONTEND
# Install OpenVino Runtime and Dev library
COPY requirements-ov.txt /requirements-ov.txt
COPY docker/main/requirements-ov.txt /requirements-ov.txt
RUN apt-get -qq update \
&& apt-get -qq install -y wget python3 python3-distutils \
&& wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
@ -69,22 +71,22 @@ ENV CCACHE_MAXSIZE 2G
# Build libUSB without udev. Needed for Openvino NCS2 support
WORKDIR /opt
RUN apt-get update && apt-get install -y unzip build-essential automake libtool ccache
RUN --mount=type=cache,target=/root/.ccache wget -q https://github.com/libusb/libusb/archive/v1.0.25.zip -O v1.0.25.zip && \
unzip v1.0.25.zip && cd libusb-1.0.25 && \
RUN apt-get update && apt-get install -y unzip build-essential automake libtool ccache pkg-config
RUN --mount=type=cache,target=/root/.ccache wget -q https://github.com/libusb/libusb/archive/v1.0.26.zip -O v1.0.26.zip && \
unzip v1.0.26.zip && cd libusb-1.0.26 && \
./bootstrap.sh && \
./configure CC='ccache gcc' CCX='ccache g++' --disable-udev --enable-shared && \
make -j $(nproc --all)
RUN apt-get update && \
apt-get install -y --no-install-recommends libusb-1.0-0-dev && \
rm -rf /var/lib/apt/lists/*
WORKDIR /opt/libusb-1.0.25/libusb
WORKDIR /opt/libusb-1.0.26/libusb
RUN /bin/mkdir -p '/usr/local/lib' && \
/bin/bash ../libtool --mode=install /usr/bin/install -c libusb-1.0.la '/usr/local/lib' && \
/bin/mkdir -p '/usr/local/include/libusb-1.0' && \
/usr/bin/install -c -m 644 libusb.h '/usr/local/include/libusb-1.0' && \
/bin/mkdir -p '/usr/local/lib/pkgconfig' && \
cd /opt/libusb-1.0.25/ && \
cd /opt/libusb-1.0.26/ && \
/usr/bin/install -c -m 644 libusb-1.0.pc '/usr/local/lib/pkgconfig' && \
ldconfig
@ -105,7 +107,7 @@ COPY audio-labelmap.txt .
FROM wget AS s6-overlay
ARG TARGETARCH
RUN --mount=type=bind,source=docker/install_s6_overlay.sh,target=/deps/install_s6_overlay.sh \
RUN --mount=type=bind,source=docker/main/install_s6_overlay.sh,target=/deps/install_s6_overlay.sh \
/deps/install_s6_overlay.sh
@ -119,13 +121,15 @@ RUN apt-get -qq update \
apt-transport-https \
gnupg \
wget \
&& apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 9165938D90FDDD2E \
&& echo "deb http://raspbian.raspberrypi.org/raspbian/ bullseye main contrib non-free rpi" | tee /etc/apt/sources.list.d/raspi.list \
# the key fingerprint can be obtained from https://ftp-master.debian.org/keys.html
&& wget -qO- "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xA4285295FC7B1A81600062A9605C66F00D6C9793" | \
gpg --dearmor > /usr/share/keyrings/debian-archive-bullseye-stable.gpg \
&& echo "deb [signed-by=/usr/share/keyrings/debian-archive-bullseye-stable.gpg] http://deb.debian.org/debian bullseye main contrib non-free" | \
tee /etc/apt/sources.list.d/debian-bullseye-nonfree.list \
&& apt-get -qq update \
&& apt-get -qq install -y \
python3 \
python3-dev \
wget \
python3.9 \
python3.9-dev \
# opencv dependencies
build-essential cmake git pkg-config libgtk-3-dev \
libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
@ -134,28 +138,20 @@ RUN apt-get -qq update \
libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
# scipy dependencies
gcc gfortran libopenblas-dev liblapack-dev \
# faster-fifo dependencies
g++ cython3 && \
gcc gfortran libopenblas-dev liblapack-dev && \
rm -rf /var/lib/apt/lists/*
# Ensure python3 defaults to python3.9
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 1
RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
&& python3 get-pip.py "pip"
COPY requirements.txt /requirements.txt
RUN pip3 install -r requirements.txt
COPY docker/main/requirements.txt /requirements.txt
RUN pip3 install -r /requirements.txt
COPY requirements-wheels.txt /requirements-wheels.txt
RUN pip3 wheel --wheel-dir=/wheels -r requirements-wheels.txt
# Make this a separate target so it can be built/cached optionally
FROM wheels as trt-wheels
ARG DEBIAN_FRONTEND
ARG TARGETARCH
# Add TensorRT wheels to another folder
COPY requirements-tensorrt.txt /requirements-tensorrt.txt
RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r requirements-tensorrt.txt
COPY docker/main/requirements-wheels.txt /requirements-wheels.txt
RUN pip3 wheel --wheel-dir=/wheels -r /requirements-wheels.txt
# Collect deps in a single layer
@ -165,7 +161,7 @@ COPY --from=go2rtc /rootfs/ /
COPY --from=libusb-build /usr/local/lib /usr/local/lib
COPY --from=s6-overlay /rootfs/ /
COPY --from=models /rootfs/ /
COPY docker/rootfs/ /
COPY docker/main/rootfs/ /
# Frigate deps (ffmpeg, python, nginx, go2rtc, s6-overlay, etc)
@ -183,10 +179,11 @@ ENV NVIDIA_DRIVER_CAPABILITIES="compute,video,utility"
ENV PATH="/usr/lib/btbn-ffmpeg/bin:/usr/local/go2rtc/bin:/usr/local/nginx/sbin:${PATH}"
# Install dependencies
RUN --mount=type=bind,source=docker/install_deps.sh,target=/deps/install_deps.sh \
RUN --mount=type=bind,source=docker/main/install_deps.sh,target=/deps/install_deps.sh \
/deps/install_deps.sh
RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \
python3 -m pip install --upgrade pip && \
pip3 install -U /deps/wheels/*.whl
COPY --from=deps-rootfs / /
@ -204,24 +201,27 @@ ENV S6_LOGGING_SCRIPT="T 1 n0 s10000000 T"
ENTRYPOINT ["/init"]
CMD []
HEALTHCHECK --start-period=120s --start-interval=5s --interval=15s --timeout=5s --retries=3 \
CMD curl --fail --silent --show-error http://127.0.0.1:5000/api/version || exit 1
# Frigate deps with Node.js and NPM for devcontainer
FROM deps AS devcontainer
# Do not start the actual Frigate service on devcontainer as it will be started by VSCode
# But start a fake service for simulating the logs
COPY docker/fake_frigate_run /etc/s6-overlay/s6-rc.d/frigate/run
COPY docker/main/fake_frigate_run /etc/s6-overlay/s6-rc.d/frigate/run
# Create symbolic link to the frigate source code, as go2rtc's create_config.sh uses it
RUN mkdir -p /opt/frigate \
&& ln -svf /workspace/frigate/frigate /opt/frigate/frigate
# Install Node 16
RUN apt-get update \
&& apt-get install wget -y \
&& wget -qO- https://deb.nodesource.com/setup_16.x | bash - \
&& apt-get install -y nodejs \
# Install Node 20
RUN curl -SLO https://deb.nodesource.com/nsolid_setup_deb.sh && \
chmod 500 nsolid_setup_deb.sh && \
./nsolid_setup_deb.sh 20 && \
apt-get install nodejs -y \
&& rm -rf /var/lib/apt/lists/* \
&& npm install -g npm@9
&& npm install -g npm@10
WORKDIR /workspace/frigate
@ -229,7 +229,7 @@ RUN apt-get update \
&& apt-get install make -y \
&& rm -rf /var/lib/apt/lists/*
RUN --mount=type=bind,source=./requirements-dev.txt,target=/workspace/frigate/requirements-dev.txt \
RUN --mount=type=bind,source=./docker/main/requirements-dev.txt,target=/workspace/frigate/requirements-dev.txt \
pip3 install -r requirements-dev.txt
CMD ["sleep", "infinity"]
@ -261,36 +261,3 @@ FROM deps AS frigate
WORKDIR /opt/frigate/
COPY --from=rootfs / /
# Build TensorRT-specific library
FROM nvcr.io/nvidia/tensorrt:23.03-py3 AS trt-deps
RUN --mount=type=bind,source=docker/support/tensorrt_detector/tensorrt_libyolo.sh,target=/tensorrt_libyolo.sh \
/tensorrt_libyolo.sh
# Frigate w/ TensorRT Support as separate image
FROM frigate AS frigate-tensorrt
#Disable S6 Global timeout
ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
ENV TRT_VER=8.5.3
ENV YOLO_MODELS="yolov7-tiny-416"
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
COPY docker/support/tensorrt_detector/rootfs/ /
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
pip3 install -U /deps/trt-wheels/*.whl && \
ldconfig
# Dev Container w/ TRT
FROM devcontainer AS devcontainer-trt
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
COPY docker/support/tensorrt_detector/rootfs/ /
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
pip3 install -U /deps/trt-wheels/*.whl

2
docker/build_nginx.sh → docker/main/build_nginx.sh
View File

@ -2,7 +2,7 @@
set -euxo pipefail
NGINX_VERSION="1.25.1"
NGINX_VERSION="1.25.3"
VOD_MODULE_VERSION="1.31"
SECURE_TOKEN_MODULE_VERSION="1.5"
RTMP_MODULE_VERSION="1.2.2"

0
docker/fake_frigate_run → docker/main/fake_frigate_run
View File

28
docker/install_deps.sh → docker/main/install_deps.sh
View File

@ -10,11 +10,15 @@ apt-get -qq install --no-install-recommends -y \
wget \
procps vainfo \
unzip locales tzdata libxml2 xz-utils \
python3.9 \
python3-pip \
curl \
jq \
nethogs
# ensure python3 defaults to python3.9
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 1
mkdir -p -m 600 /root/.gnupg
# add coral repo
@ -23,8 +27,10 @@ curl -fsSLo - https://packages.cloud.google.com/apt/doc/apt-key.gpg | \
echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" | tee /etc/apt/sources.list.d/coral-edgetpu.list
echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections
# enable non-free repo
sed -i -e's/ main/ main contrib non-free/g' /etc/apt/sources.list
# enable non-free repo in Debian
if grep -q "Debian" /etc/issue; then
sed -i -e's/ main/ main contrib non-free/g' /etc/apt/sources.list
fi
# coral drivers
apt-get -qq update
@ -41,26 +47,24 @@ fi
# ffmpeg -> arm64
if [[ "${TARGETARCH}" == "arm64" ]]; then
# add raspberry pi repo
gpg --no-default-keyring --keyring /usr/share/keyrings/raspbian.gpg --keyserver keyserver.ubuntu.com --recv-keys 82B129927FA3303E
echo "deb [signed-by=/usr/share/keyrings/raspbian.gpg] https://archive.raspberrypi.org/debian/ bullseye main" | tee /etc/apt/sources.list.d/raspi.list
apt-get -qq update
apt-get -qq install --no-install-recommends --no-install-suggests -y ffmpeg
mkdir -p /usr/lib/btbn-ffmpeg
wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linuxarm64-gpl-5.1.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/btbn-ffmpeg --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/btbn-ffmpeg/doc /usr/lib/btbn-ffmpeg/bin/ffplay
fi
# arch specific packages
if [[ "${TARGETARCH}" == "amd64" ]]; then
# Use debian testing repo only for hwaccel packages
echo 'deb http://deb.debian.org/debian testing main non-free' >/etc/apt/sources.list.d/debian-testing.list
# use debian bookworm for hwaccel packages
echo 'deb https://deb.debian.org/debian bookworm main contrib non-free' >/etc/apt/sources.list.d/debian-bookworm.list
apt-get -qq update
# intel-opencl-icd specifically for GPU support in OpenVino
apt-get -qq install --no-install-recommends --no-install-suggests -y \
intel-opencl-icd \
mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 radeontop intel-gpu-tools
mesa-va-drivers radeontop libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 intel-gpu-tools
# something about this dependency requires it to be installed in a separate call rather than in the line above
apt-get -qq install --no-install-recommends --no-install-suggests -y \
i965-va-driver-shaders
rm -f /etc/apt/sources.list.d/debian-testing.list
rm -f /etc/apt/sources.list.d/debian-bookworm.list
fi
if [[ "${TARGETARCH}" == "arm64" ]]; then

2
docker/install_s6_overlay.sh → docker/main/install_s6_overlay.sh
View File

@ -2,7 +2,7 @@
set -euxo pipefail
s6_version="3.1.4.1"
s6_version="3.1.5.0"
if [[ "${TARGETARCH}" == "amd64" ]]; then
s6_arch="x86_64"

1
docker/main/requirements-dev.txt Normal file
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@ -0,0 +1 @@
ruff

5
docker/main/requirements-ov.txt Normal file
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@ -0,0 +1,5 @@
numpy
# Openvino Library - Custom built with MYRIAD support
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'
openvino-dev[tensorflow2] @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino_dev-2022.3.1-1-py3-none-any.whl

22
requirements-wheels.txt → docker/main/requirements-wheels.txt
View File

@ -1,29 +1,29 @@
click == 8.1.*
Flask == 2.3.*
faster-fifo == 1.4.*
imutils == 0.5.*
matplotlib == 3.7.*
mypy == 1.4.1
mypy == 1.6.1
numpy == 1.23.*
onvif_zeep == 0.2.12
opencv-python-headless == 4.7.0.*
paho-mqtt == 1.6.*
peewee == 3.16.*
peewee_migrate == 1.11.*
peewee == 3.17.*
peewee_migrate == 1.12.*
psutil == 5.9.*
pydantic == 1.10.*
git+https://github.com/fbcotter/py3nvml#egg=py3nvml
PyYAML == 6.0
pytz == 2023.3
ruamel.yaml == 0.17.*
tzlocal == 5.0.*
PyYAML == 6.0.*
pytz == 2023.3.post1
ruamel.yaml == 0.18.*
tzlocal == 5.2
types-PyYAML == 6.0.*
requests == 2.31.*
types-requests == 2.31.*
scipy == 1.10.*
scipy == 1.11.*
norfair == 2.2.*
setproctitle == 1.3.*
ws4py == 0.5.*
unidecode == 1.3.*
# Openvino Library - Custom built with MYRIAD support
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.2.0/openvino-2022.2.0-000-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.2.0/openvino-2022.2.0-000-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'

0
requirements.txt → docker/main/requirements.txt
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/consumer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/consumer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/dependencies.d/log-prepare → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/dependencies.d/log-prepare
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/pipeline-name → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/pipeline-name
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate-log/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/go2rtc → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/go2rtc
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/finish → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/finish
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/producer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/producer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/timeout-kill → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/timeout-kill
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/frigate/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/dependencies.d/go2rtc → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/dependencies.d/go2rtc
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/finish → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/finish
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/producer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/producer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/timeout-kill → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/timeout-kill
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/consumer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/consumer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/dependencies.d/log-prepare → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/dependencies.d/log-prepare
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/pipeline-name → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/pipeline-name
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/dependencies.d/base → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/dependencies.d/base
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/finish → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/finish
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/producer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/producer-for
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9
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/run
View File

@ -45,8 +45,13 @@ function get_ip_and_port_from_supervisor() {
export LIBAVFORMAT_VERSION_MAJOR=$(ffmpeg -version | grep -Po 'libavformat\W+\K\d+')
if [[ -f "/dev/shm/go2rtc.yaml" ]]; then
echo "[INFO] Removing stale config from last run..."
rm /dev/shm/go2rtc.yaml
fi
if [[ ! -f "/dev/shm/go2rtc.yaml" ]]; then
echo "[INFO] Preparing go2rtc config..."
echo "[INFO] Preparing new go2rtc config..."
if [[ -n "${SUPERVISOR_TOKEN:-}" ]]; then
# Running as a Home Assistant add-on, infer the IP address and port
@ -54,6 +59,8 @@ if [[ ! -f "/dev/shm/go2rtc.yaml" ]]; then
fi
python3 /usr/local/go2rtc/create_config.py
else
echo "[WARNING] Unable to remove existing go2rtc config. Changes made to your frigate config file may not be recognized. Please remove the /dev/shm/go2rtc.yaml from your docker host manually."
fi
readonly config_path="/config"

0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/timeout-kill → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/timeout-kill
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/dependencies.d/base → docker/main/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/dependencies.d/base
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/up → docker/main/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/up
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/consumer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/consumer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/dependencies.d/log-prepare → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/dependencies.d/log-prepare
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/pipeline-name → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/pipeline-name
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx-log/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/dependencies.d/frigate → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/dependencies.d/frigate
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/finish → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/finish
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/producer-for → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/producer-for
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/run → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/run
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/timeout-kill → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/timeout-kill
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/type → docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/type
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/frigate-pipeline → docker/main/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/frigate-pipeline
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0
docker/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/go2rtc-pipeline → docker/main/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/go2rtc-pipeline
View File

0
docker/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/nginx-pipeline → docker/main/rootfs/etc/s6-overlay/s6-rc.d/user/contents.d/nginx-pipeline
View File

73
docker/rootfs/usr/local/go2rtc/create_config.py → docker/main/rootfs/usr/local/go2rtc/create_config.py
View File

@ -3,6 +3,7 @@
import json
import os
import sys
from pathlib import Path
import yaml
@ -16,6 +17,14 @@ sys.path.remove("/opt/frigate")
FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
# read docker secret files as env vars too
if os.path.isdir("/run/secrets"):
for secret_file in os.listdir("/run/secrets"):
if secret_file.startswith("FRIGATE_"):
FRIGATE_ENV_VARS[secret_file] = Path(
os.path.join("/run/secrets", secret_file)
).read_text()
config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
# Check if we can use .yaml instead of .yml
@ -39,13 +48,25 @@ if go2rtc_config.get("api") is None:
elif go2rtc_config["api"].get("origin") is None:
go2rtc_config["api"]["origin"] = "*"
# Need to set default location for HA config
if go2rtc_config.get("hass") is None:
go2rtc_config["hass"] = {"config": "/config"}
# we want to ensure that logs are easy to read
if go2rtc_config.get("log") is None:
go2rtc_config["log"] = {"format": "text"}
elif go2rtc_config["log"].get("format") is None:
go2rtc_config["log"]["format"] = "text"
if not go2rtc_config.get("webrtc", {}).get("candidates", []):
# ensure there is a default webrtc config
if not go2rtc_config.get("webrtc"):
go2rtc_config["webrtc"] = {}
# go2rtc should listen on 8555 tcp & udp by default
if not go2rtc_config["webrtc"].get("listen"):
go2rtc_config["webrtc"]["listen"] = ":8555"
if not go2rtc_config["webrtc"].get("candidates", []):
default_candidates = []
# use internal candidate if it was discovered when running through the add-on
internal_candidate = os.environ.get(
@ -67,8 +88,19 @@ else:
# as source for frigate and the integration supports HLS playback
if go2rtc_config.get("rtsp") is None:
go2rtc_config["rtsp"] = {"default_query": "mp4"}
elif go2rtc_config["rtsp"].get("default_query") is None:
go2rtc_config["rtsp"]["default_query"] = "mp4"
else:
if go2rtc_config["rtsp"].get("default_query") is None:
go2rtc_config["rtsp"]["default_query"] = "mp4"
if go2rtc_config["rtsp"].get("username") is not None:
go2rtc_config["rtsp"]["username"] = go2rtc_config["rtsp"]["username"].format(
**FRIGATE_ENV_VARS
)
if go2rtc_config["rtsp"].get("password") is not None:
go2rtc_config["rtsp"]["password"] = go2rtc_config["rtsp"]["password"].format(
**FRIGATE_ENV_VARS
)
# need to replace ffmpeg command when using ffmpeg4
if int(os.environ["LIBAVFORMAT_VERSION_MAJOR"]) < 59:
@ -81,16 +113,43 @@ if int(os.environ["LIBAVFORMAT_VERSION_MAJOR"]) < 59:
"rtsp"
] = "-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
# add hardware acceleration presets for rockchip devices
# may be removed if frigate uses a go2rtc version that includes these presets
if go2rtc_config.get("ffmpeg") is None:
go2rtc_config["ffmpeg"] = {
"h264/rk": "-c:v h264_rkmpp_encoder -g 50 -bf 0",
"h265/rk": "-c:v hevc_rkmpp_encoder -g 50 -bf 0",
}
else:
if go2rtc_config["ffmpeg"].get("h264/rk") is None:
go2rtc_config["ffmpeg"]["h264/rk"] = "-c:v h264_rkmpp_encoder -g 50 -bf 0"
if go2rtc_config["ffmpeg"].get("h265/rk") is None:
go2rtc_config["ffmpeg"]["h265/rk"] = "-c:v hevc_rkmpp_encoder -g 50 -bf 0"
for name in go2rtc_config.get("streams", {}):
stream = go2rtc_config["streams"][name]
if isinstance(stream, str):
go2rtc_config["streams"][name] = go2rtc_config["streams"][name].format(
**FRIGATE_ENV_VARS
)
try:
go2rtc_config["streams"][name] = go2rtc_config["streams"][name].format(
**FRIGATE_ENV_VARS
)
except KeyError as e:
print(
"[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
)
sys.exit(e)
elif isinstance(stream, list):
for i, stream in enumerate(stream):
go2rtc_config["streams"][name][i] = stream.format(**FRIGATE_ENV_VARS)
try:
go2rtc_config["streams"][name][i] = stream.format(**FRIGATE_ENV_VARS)
except KeyError as e:
print(
"[ERROR] Invalid substitution found, see https://docs.frigate.video/configuration/restream#advanced-restream-configurations for more info."
)
sys.exit(e)
# add birdseye restream stream if enabled
if config.get("birdseye", {}).get("restream", False):

124
docker/rootfs/usr/local/nginx/conf/nginx.conf → docker/main/rootfs/usr/local/nginx/conf/nginx.conf
View File

@ -32,6 +32,13 @@ http {
gzip_proxied no-cache no-store private expired auth;
gzip_vary on;
proxy_cache_path /dev/shm/nginx_cache levels=1:2 keys_zone=api_cache:10m max_size=10m inactive=1m use_temp_path=off;
map $sent_http_content_type $should_not_cache {
'application/json' 0;
default 1;
}
upstream frigate_api {
server 127.0.0.1:5001;
keepalive 1024;
@ -93,10 +100,6 @@ http {
secure_token $args;
secure_token_types application/vnd.apple.mpegurl;
add_header Access-Control-Allow-Headers '*';
add_header Access-Control-Expose-Headers 'Server,range,Content-Length,Content-Range';
add_header Access-Control-Allow-Methods 'GET, HEAD, OPTIONS';
add_header Access-Control-Allow-Origin '*';
add_header Cache-Control "no-store";
expires off;
}
@ -104,16 +107,6 @@ http {
location /stream/ {
add_header Cache-Control "no-store";
expires off;
add_header 'Access-Control-Allow-Origin' "$http_origin" always;
add_header 'Access-Control-Allow-Credentials' 'true';
add_header 'Access-Control-Expose-Headers' 'Content-Length';
if ($request_method = 'OPTIONS') {
add_header 'Access-Control-Allow-Origin' "$http_origin";
add_header 'Access-Control-Max-Age' 1728000;
add_header 'Content-Type' 'text/plain charset=UTF-8';
add_header 'Content-Length' 0;
return 204;
}
types {
application/dash+xml mpd;
@ -126,16 +119,6 @@ http {
}
location /clips/ {
add_header 'Access-Control-Allow-Origin' "$http_origin" always;
add_header 'Access-Control-Allow-Credentials' 'true';
add_header 'Access-Control-Expose-Headers' 'Content-Length';
if ($request_method = 'OPTIONS') {
add_header 'Access-Control-Allow-Origin' "$http_origin";
add_header 'Access-Control-Max-Age' 1728000;
add_header 'Content-Type' 'text/plain charset=UTF-8';
add_header 'Content-Length' 0;
return 204;
}
types {
video/mp4 mp4;
@ -152,17 +135,6 @@ http {
}
location /recordings/ {
add_header 'Access-Control-Allow-Origin' "$http_origin" always;
add_header 'Access-Control-Allow-Credentials' 'true';
add_header 'Access-Control-Expose-Headers' 'Content-Length';
if ($request_method = 'OPTIONS') {
add_header 'Access-Control-Allow-Origin' "$http_origin";
add_header 'Access-Control-Max-Age' 1728000;
add_header 'Content-Type' 'text/plain charset=UTF-8';
add_header 'Content-Length' 0;
return 204;
}
types {
video/mp4 mp4;
}
@ -173,17 +145,6 @@ http {
}
location /exports/ {
add_header 'Access-Control-Allow-Origin' "$http_origin" always;
add_header 'Access-Control-Allow-Credentials' 'true';
add_header 'Access-Control-Expose-Headers' 'Content-Length';
if ($request_method = 'OPTIONS') {
add_header 'Access-Control-Allow-Origin' "$http_origin";
add_header 'Access-Control-Max-Age' 1728000;
add_header 'Content-Type' 'text/plain charset=UTF-8';
add_header 'Content-Length' 0;
return 204;
}
types {
video/mp4 mp4;
}
@ -195,68 +156,69 @@ http {
location /ws {
proxy_pass http://mqtt_ws/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;
include proxy.conf;
}
location /live/jsmpeg/ {
proxy_pass http://jsmpeg/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;
include proxy.conf;
}
location /live/mse/ {
proxy_pass http://go2rtc/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;
include proxy.conf;
}
location /live/webrtc/ {
proxy_pass http://go2rtc/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;
include proxy.conf;
}
location ~* /api/go2rtc([/]?.*)$ {
proxy_pass http://go2rtc;
rewrite ^/api/go2rtc(.*)$ /api$1 break;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;
include proxy.conf;
}
location ~* /api/.*\.(jpg|jpeg|png)$ {
add_header 'Access-Control-Allow-Origin' '*';
add_header 'Access-Control-Allow-Methods' 'GET, POST, PUT, DELETE, OPTIONS';
rewrite ^/api/(.*)$ $1 break;
proxy_pass http://frigate_api;
proxy_pass_request_headers on;
proxy_set_header Host $host;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
include proxy.conf;
}
location /api/ {
add_header Cache-Control "no-store";
expires off;
add_header 'Access-Control-Allow-Origin' '*';
add_header 'Access-Control-Allow-Methods' 'GET, POST, PUT, DELETE, OPTIONS';
add_header 'Access-Control-Allow-Headers' 'DNT,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Range';
proxy_pass http://frigate_api/;
proxy_pass_request_headers on;
proxy_set_header Host $host;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
include proxy.conf;
proxy_cache api_cache;
proxy_cache_lock on;
proxy_cache_use_stale updating;
proxy_cache_valid 200 5s;
proxy_cache_bypass $http_x_cache_bypass;
proxy_no_cache $should_not_cache;
add_header X-Cache-Status $upstream_cache_status;
location /api/vod/ {
proxy_pass http://frigate_api/vod/;
include proxy.conf;
proxy_cache off;
}
location /api/stats {
access_log off;
rewrite ^/api/(.*)$ $1 break;
proxy_pass http://frigate_api;
include proxy.conf;
}
location /api/version {
access_log off;
rewrite ^/api/(.*)$ $1 break;
proxy_pass http://frigate_api;
include proxy.conf;
}
}
location / {
@ -299,4 +261,4 @@ rtmp {
meta copy;
}
}
}
}

4
docker/main/rootfs/usr/local/nginx/conf/proxy.conf Normal file
View File

@ -0,0 +1,4 @@
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "Upgrade";
proxy_set_header Host $host;

32
docker/rockchip/Dockerfile Normal file
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@ -0,0 +1,32 @@
# syntax=docker/dockerfile:1.6
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
FROM wheels as rk-wheels
COPY docker/main/requirements-wheels.txt /requirements-wheels.txt
COPY docker/rockchip/requirements-wheels-rk.txt /requirements-wheels-rk.txt
RUN sed -i "/https:\/\//d" /requirements-wheels.txt
RUN pip3 wheel --wheel-dir=/rk-wheels -c /requirements-wheels.txt -r /requirements-wheels-rk.txt
FROM deps AS rk-deps
ARG TARGETARCH
RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \
pip3 install -U /deps/rk-wheels/*.whl
WORKDIR /opt/frigate/
COPY --from=rootfs / /
ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk356x.so /usr/lib/
ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk3588.so /usr/lib/
ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3562/yolov8n-320x320-rk3562.rknn /models/rknn/
ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3566/yolov8n-320x320-rk3566.rknn /models/rknn/
ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3568/yolov8n-320x320-rk3568.rknn /models/rknn/
ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3588/yolov8n-320x320-rk3588.rknn /models/rknn/
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffmpeg
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffprobe
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.0-1/ffmpeg /usr/lib/btbn-ffmpeg/bin/
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.0-1/ffprobe /usr/lib/btbn-ffmpeg/bin/

2
docker/rockchip/requirements-wheels-rk.txt Normal file
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@ -0,0 +1,2 @@
hide-warnings == 0.17
rknn-toolkit-lite2 @ https://github.com/MarcA711/rknn-toolkit2/releases/download/v1.5.2/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl

34
docker/rockchip/rk.hcl Normal file
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@ -0,0 +1,34 @@
target wget {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "wget"
}
target wheels {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "wheels"
}
target deps {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "deps"
}
target rootfs {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "rootfs"
}
target rk {
dockerfile = "docker/rockchip/Dockerfile"
contexts = {
wget = "target:wget",
wheels = "target:wheels",
deps = "target:deps",
rootfs = "target:rootfs"
}
platforms = ["linux/arm64"]
}

10
docker/rockchip/rk.mk Normal file
View File

@ -0,0 +1,10 @@
BOARDS += rk
local-rk: version
docker buildx bake --load --file=docker/rockchip/rk.hcl --set rk.tags=frigate:latest-rk rk
build-rk: version
docker buildx bake --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk
push-rk: build-rk
docker buildx bake --push --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk

16
docker/rpi/Dockerfile Normal file
View File

@ -0,0 +1,16 @@
# syntax=docker/dockerfile:1.4
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
FROM deps AS rpi-deps
ARG TARGETARCH
RUN rm -rf /usr/lib/btbn-ffmpeg/
# Install dependencies
RUN --mount=type=bind,source=docker/rpi/install_deps.sh,target=/deps/install_deps.sh \
/deps/install_deps.sh
WORKDIR /opt/frigate/
COPY --from=rootfs / /

30
docker/rpi/install_deps.sh Executable file
View File

@ -0,0 +1,30 @@
#!/bin/bash
set -euxo pipefail
apt-get -qq update
apt-get -qq install --no-install-recommends -y \
apt-transport-https \
gnupg \
wget \
procps vainfo \
unzip locales tzdata libxml2 xz-utils \
python3-pip \
curl \
jq \
nethogs
mkdir -p -m 600 /root/.gnupg
# enable non-free repo
sed -i -e's/ main/ main contrib non-free/g' /etc/apt/sources.list
# ffmpeg -> arm64
if [[ "${TARGETARCH}" == "arm64" ]]; then
# add raspberry pi repo
gpg --no-default-keyring --keyring /usr/share/keyrings/raspbian.gpg --keyserver keyserver.ubuntu.com --recv-keys 82B129927FA3303E
echo "deb [signed-by=/usr/share/keyrings/raspbian.gpg] https://archive.raspberrypi.org/debian/ bullseye main" | tee /etc/apt/sources.list.d/raspi.list
apt-get -qq update
apt-get -qq install --no-install-recommends --no-install-suggests -y ffmpeg
fi

20
docker/rpi/rpi.hcl Normal file
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@ -0,0 +1,20 @@
target deps {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "deps"
}
target rootfs {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64"]
target = "rootfs"
}
target rpi {
dockerfile = "docker/rpi/Dockerfile"
contexts = {
deps = "target:deps",
rootfs = "target:rootfs"
}
platforms = ["linux/arm64"]
}

10
docker/rpi/rpi.mk Normal file
View File

@ -0,0 +1,10 @@
BOARDS += rpi
local-rpi: version
docker buildx bake --load --file=docker/rpi/rpi.hcl --set rpi.tags=frigate:latest-rpi rpi
build-rpi: version
docker buildx bake --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi
push-rpi: build-rpi
docker buildx bake --push --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi

53
docker/support/tensorrt_detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/run
View File

@ -1,53 +0,0 @@
#!/command/with-contenv bash
# shellcheck shell=bash
# Generate models for the TensorRT detector
set -o errexit -o nounset -o pipefail
MODEL_CACHE_DIR=${MODEL_CACHE_DIR:-"/config/model_cache/tensorrt"}
OUTPUT_FOLDER="${MODEL_CACHE_DIR}/${TRT_VER}"
# Create output folder
mkdir -p ${OUTPUT_FOLDER}
FIRST_MODEL=true
MODEL_CONVERT=""
for model in ${YOLO_MODELS//,/ }
do
# Remove old link in case path/version changed
rm -f ${MODEL_CACHE_DIR}/${model}.trt
if [[ ! -f ${OUTPUT_FOLDER}/${model}.trt ]]; then
if [[ ${FIRST_MODEL} = true ]]; then
MODEL_CONVERT="${model}"
FIRST_MODEL=false;
else
MODEL_CONVERT+=",${model}";
fi
else
ln -s ${OUTPUT_FOLDER}/${model}.trt ${MODEL_CACHE_DIR}/${model}.trt
fi
done
if [[ -z ${MODEL_CONVERT} ]]; then
echo "No models to convert."
exit 0
fi
echo "Generating the following TRT Models: ${MODEL_CONVERT}"
# Build trt engine
cd /usr/local/src/tensorrt_demos/yolo
# Download yolo weights
./download_yolo.sh $MODEL_CONVERT > /dev/null
for model in ${MODEL_CONVERT//,/ }
do
echo "Converting ${model} model"
python3 yolo_to_onnx.py -m ${model} > /dev/null
python3 onnx_to_tensorrt.py -m ${model} > /dev/null
cp ${model}.trt ${OUTPUT_FOLDER}/${model}.trt
ln -s ${OUTPUT_FOLDER}/${model}.trt ${MODEL_CACHE_DIR}/${model}.trt
done

32
docker/tensorrt/Dockerfile.amd64 Normal file
View File

@ -0,0 +1,32 @@
# syntax=docker/dockerfile:1.4
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
# Make this a separate target so it can be built/cached optionally
FROM wheels as trt-wheels
ARG DEBIAN_FRONTEND
ARG TARGETARCH
# Add TensorRT wheels to another folder
COPY docker/tensorrt/requirements-amd64.txt /requirements-tensorrt.txt
RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt
FROM tensorrt-base AS frigate-tensorrt
ENV TRT_VER=8.5.3
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
pip3 install -U /deps/trt-wheels/*.whl && \
ldconfig
WORKDIR /opt/frigate/
COPY --from=rootfs / /
# Dev Container w/ TRT
FROM devcontainer AS devcontainer-trt
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
COPY docker/tensorrt/detector/rootfs/ /
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
pip3 install -U /deps/trt-wheels/*.whl

79
docker/tensorrt/Dockerfile.arm64 Normal file
View File

@ -0,0 +1,79 @@
# syntax=docker/dockerfile:1.4
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
ARG BASE_IMAGE
FROM ${BASE_IMAGE} AS build-wheels
ARG DEBIAN_FRONTEND
# Use a separate container to build wheels to prevent build dependencies in final image
RUN apt-get -qq update \
&& apt-get -qq install -y --no-install-recommends \
python3.9 python3.9-dev \
wget build-essential cmake git \
&& rm -rf /var/lib/apt/lists/*
# Ensure python3 defaults to python3.9
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 1
RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
&& python3 get-pip.py "pip"
FROM build-wheels AS trt-wheels
ARG DEBIAN_FRONTEND
ARG TARGETARCH
# python-tensorrt build deps are 3.4 GB!
RUN apt-get update \
&& apt-get install -y ccache cuda-cudart-dev-* cuda-nvcc-* libnvonnxparsers-dev libnvparsers-dev libnvinfer-plugin-dev \
&& ([ -e /usr/local/cuda ] || ln -s /usr/local/cuda-* /usr/local/cuda) \
&& rm -rf /var/lib/apt/lists/*;
# Determine version of tensorrt already installed in base image, e.g. "Version: 8.4.1-1+cuda11.4"
RUN NVINFER_VER=$(dpkg -s libnvinfer8 | grep -Po "Version: \K.*") \
&& echo $NVINFER_VER | grep -Po "^\d+\.\d+\.\d+" > /etc/TENSORRT_VER
RUN --mount=type=bind,source=docker/tensorrt/detector/build_python_tensorrt.sh,target=/deps/build_python_tensorrt.sh \
--mount=type=cache,target=/root/.ccache \
export PATH="/usr/lib/ccache:$PATH" CCACHE_DIR=/root/.ccache CCACHE_MAXSIZE=2G \
&& TENSORRT_VER=$(cat /etc/TENSORRT_VER) /deps/build_python_tensorrt.sh
COPY docker/tensorrt/requirements-arm64.txt /requirements-tensorrt.txt
RUN pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt
FROM build-wheels AS trt-model-wheels
ARG DEBIAN_FRONTEND
RUN apt-get update \
&& apt-get install -y protobuf-compiler libprotobuf-dev \
&& rm -rf /var/lib/apt/lists/*
RUN --mount=type=bind,source=docker/tensorrt/requirements-models-arm64.txt,target=/requirements-tensorrt-models.txt \
pip3 wheel --wheel-dir=/trt-model-wheels -r /requirements-tensorrt-models.txt
FROM wget AS jetson-ffmpeg
ARG DEBIAN_FRONTEND
ENV CCACHE_DIR /root/.ccache
ENV CCACHE_MAXSIZE 2G
RUN --mount=type=bind,source=docker/tensorrt/build_jetson_ffmpeg.sh,target=/deps/build_jetson_ffmpeg.sh \
--mount=type=cache,target=/root/.ccache \
/deps/build_jetson_ffmpeg.sh
# Frigate w/ TensorRT for NVIDIA Jetson platforms
FROM tensorrt-base AS frigate-tensorrt
RUN apt-get update \
&& apt-get install -y python-is-python3 libprotobuf17 \
&& rm -rf /var/lib/apt/lists/*
RUN rm -rf /usr/lib/btbn-ffmpeg/
COPY --from=jetson-ffmpeg /rootfs /
COPY --from=trt-wheels /etc/TENSORRT_VER /etc/TENSORRT_VER
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
--mount=type=bind,from=trt-model-wheels,source=/trt-model-wheels,target=/deps/trt-model-wheels \
pip3 install -U /deps/trt-wheels/*.whl /deps/trt-model-wheels/*.whl \
&& ldconfig
WORKDIR /opt/frigate/
COPY --from=rootfs / /

29
docker/tensorrt/Dockerfile.base Normal file
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@ -0,0 +1,29 @@
# syntax=docker/dockerfile:1.6
# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
ARG DEBIAN_FRONTEND=noninteractive
ARG TRT_BASE=nvcr.io/nvidia/tensorrt:23.03-py3
# Build TensorRT-specific library
FROM ${TRT_BASE} AS trt-deps
RUN apt-get update \
&& apt-get install -y git build-essential cuda-nvcc-* cuda-nvtx-* libnvinfer-dev libnvinfer-plugin-dev libnvparsers-dev libnvonnxparsers-dev \
&& rm -rf /var/lib/apt/lists/*
RUN --mount=type=bind,source=docker/tensorrt/detector/tensorrt_libyolo.sh,target=/tensorrt_libyolo.sh \
/tensorrt_libyolo.sh
# Frigate w/ TensorRT Support as separate image
FROM deps AS tensorrt-base
#Disable S6 Global timeout
ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
COPY docker/tensorrt/detector/rootfs/ /
ENV YOLO_MODELS="yolov7-320"
HEALTHCHECK --start-period=600s --start-interval=5s --interval=15s --timeout=5s --retries=3 \
CMD curl --fail --silent --show-error http://127.0.0.1:5000/api/version || exit 1

59
docker/tensorrt/build_jetson_ffmpeg.sh Executable file
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@ -0,0 +1,59 @@
#!/bin/bash
# For jetson platforms, build ffmpeg with custom patches. NVIDIA supplies a deb
# with accelerated decoding, but it doesn't have accelerated scaling or encoding
set -euxo pipefail
INSTALL_PREFIX=/rootfs/usr/local
apt-get -qq update
apt-get -qq install -y --no-install-recommends build-essential ccache clang cmake pkg-config
apt-get -qq install -y --no-install-recommends libx264-dev libx265-dev
pushd /tmp
# Install libnvmpi to enable nvmpi decoders (h264_nvmpi, hevc_nvmpi)
if [ -e /usr/local/cuda-10.2 ]; then
# assume Jetpack 4.X
wget -q https://developer.nvidia.com/embedded/L4T/r32_Release_v5.0/T186/Jetson_Multimedia_API_R32.5.0_aarch64.tbz2 -O jetson_multimedia_api.tbz2
else
# assume Jetpack 5.X
wget -q https://developer.nvidia.com/downloads/embedded/l4t/r35_release_v3.1/release/jetson_multimedia_api_r35.3.1_aarch64.tbz2 -O jetson_multimedia_api.tbz2
fi
tar xaf jetson_multimedia_api.tbz2 -C / && rm jetson_multimedia_api.tbz2
wget -q https://github.com/madsciencetist/jetson-ffmpeg/archive/refs/heads/master.zip
unzip master.zip && rm master.zip && cd jetson-ffmpeg-master
LD_LIBRARY_PATH=$(pwd)/stubs:$LD_LIBRARY_PATH # tegra multimedia libs aren't available in image, so use stubs for ffmpeg build
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=$INSTALL_PREFIX
make -j$(nproc)
make install
cd ../../
# Install nv-codec-headers to enable ffnvcodec filters (scale_cuda)
wget -q https://github.com/FFmpeg/nv-codec-headers/archive/refs/heads/master.zip
unzip master.zip && rm master.zip && cd nv-codec-headers-master
make PREFIX=$INSTALL_PREFIX install
cd ../ && rm -rf nv-codec-headers-master
# Build ffmpeg with nvmpi patch
wget -q https://ffmpeg.org/releases/ffmpeg-6.0.tar.xz
tar xaf ffmpeg-*.tar.xz && rm ffmpeg-*.tar.xz && cd ffmpeg-*
patch -p1 < ../jetson-ffmpeg-master/ffmpeg_patches/ffmpeg6.0_nvmpi.patch
export PKG_CONFIG_PATH=$INSTALL_PREFIX/lib/pkgconfig
# enable Jetson codecs but disable dGPU codecs
./configure --cc='ccache gcc' --cxx='ccache g++' \
--enable-shared --disable-static --prefix=$INSTALL_PREFIX \
--enable-gpl --enable-libx264 --enable-libx265 \
--enable-nvmpi --enable-ffnvcodec --enable-cuda-llvm \
--disable-cuvid --disable-nvenc --disable-nvdec \
|| { cat ffbuild/config.log && false; }
make -j$(nproc)
make install
cd ../
rm -rf /var/lib/apt/lists/*
popd

28
docker/tensorrt/detector/build_python_tensorrt.sh Executable file
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@ -0,0 +1,28 @@
#!/bin/bash
set -euxo pipefail
mkdir -p /trt-wheels
if [[ "${TARGETARCH}" == "arm64" ]]; then
# NVIDIA supplies python-tensorrt for python3.8, but frigate uses python3.9,
# so we must build python-tensorrt ourselves.
# Get python-tensorrt source
mkdir /workspace
cd /workspace
git clone -b ${TENSORRT_VER} https://github.com/NVIDIA/TensorRT.git --depth=1
# Collect dependencies
EXT_PATH=/workspace/external && mkdir -p $EXT_PATH
pip3 install pybind11 && ln -s /usr/local/lib/python3.9/dist-packages/pybind11 $EXT_PATH/pybind11
ln -s /usr/include/python3.9 $EXT_PATH/python3.9
ln -s /usr/include/aarch64-linux-gnu/NvOnnxParser.h /workspace/TensorRT/parsers/onnx/
# Build wheel
cd /workspace/TensorRT/python
EXT_PATH=$EXT_PATH PYTHON_MAJOR_VERSION=3 PYTHON_MINOR_VERSION=9 TARGET_ARCHITECTURE=aarch64 /bin/bash ./build.sh
mv build/dist/*.whl /trt-wheels/
fi

0
docker/support/tensorrt_detector/rootfs/etc/ld.so.conf.d/cuda_tensorrt.conf → docker/tensorrt/detector/rootfs/etc/ld.so.conf.d/cuda_tensorrt.conf
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0
docker/support/tensorrt_detector/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/trt-model-prepare → docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/trt-model-prepare
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0
docker/support/tensorrt_detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/dependencies.d/base → docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/dependencies.d/base
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109
docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/run Executable file
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@ -0,0 +1,109 @@
#!/command/with-contenv bash
# shellcheck shell=bash
# Generate models for the TensorRT detector
# One or more comma-separated models may be specified via the YOLO_MODELS env.
# Append "-dla" to the model name to generate a DLA model with GPU fallback;
# otherwise a GPU-only model will be generated.
set -o errexit -o nounset -o pipefail
MODEL_CACHE_DIR=${MODEL_CACHE_DIR:-"/config/model_cache/tensorrt"}
TRT_VER=${TRT_VER:-$(cat /etc/TENSORRT_VER)}
OUTPUT_FOLDER="${MODEL_CACHE_DIR}/${TRT_VER}"
# Create output folder
mkdir -p ${OUTPUT_FOLDER}
FIRST_MODEL=true
MODEL_DOWNLOAD=""
MODEL_CONVERT=""
for model in ${YOLO_MODELS//,/ }
do
# Remove old link in case path/version changed
rm -f ${MODEL_CACHE_DIR}/${model}.trt
if [[ ! -f ${OUTPUT_FOLDER}/${model}.trt ]]; then
if [[ ${FIRST_MODEL} = true ]]; then
MODEL_DOWNLOAD="${model%-dla}";
MODEL_CONVERT="${model}"
FIRST_MODEL=false;
else
MODEL_DOWNLOAD+=",${model%-dla}";
MODEL_CONVERT+=",${model}";
fi
else
ln -s ${OUTPUT_FOLDER}/${model}.trt ${MODEL_CACHE_DIR}/${model}.trt
fi
done
if [[ -z ${MODEL_CONVERT} ]]; then
echo "No models to convert."
exit 0
fi
# Setup ENV to select GPU for conversion
if [ ! -z ${TRT_MODEL_PREP_DEVICE+x} ]; then
if [ ! -z ${CUDA_VISIBLE_DEVICES+x} ]; then
PREVIOUS_CVD="$CUDA_VISIBLE_DEVICES"
unset CUDA_VISIBLE_DEVICES
fi
export CUDA_VISIBLE_DEVICES="$TRT_MODEL_PREP_DEVICE"
fi
# On Jetpack 4.6, the nvidia container runtime will mount several host nvidia libraries into the
# container which should not be present in the image - if they are, TRT model generation will
# fail or produce invalid models. Thus we must request the user to install them on the host in
# order to run libyolo here.
# On Jetpack 5.0, these libraries are not mounted by the runtime and are supplied by the image.
if [[ "$(arch)" == "aarch64" ]]; then
if [[ ! -e /usr/lib/aarch64-linux-gnu/tegra ]]; then
echo "ERROR: Container must be launched with nvidia runtime"
exit 1
elif [[ ! -e /usr/lib/aarch64-linux-gnu/libnvinfer.so.8 ||
! -e /usr/lib/aarch64-linux-gnu/libnvinfer_plugin.so.8 ||
! -e /usr/lib/aarch64-linux-gnu/libnvparsers.so.8 ||
! -e /usr/lib/aarch64-linux-gnu/libnvonnxparser.so.8 ]]; then
echo "ERROR: Please run the following on the HOST:"
echo " sudo apt install libnvinfer8 libnvinfer-plugin8 libnvparsers8 libnvonnxparsers8 nvidia-container"
exit 1
fi
fi
echo "Generating the following TRT Models: ${MODEL_CONVERT}"
# Build trt engine
cd /usr/local/src/tensorrt_demos/yolo
echo "Downloading yolo weights"
./download_yolo.sh $MODEL_DOWNLOAD 2> /dev/null
for model in ${MODEL_CONVERT//,/ }
do
python3 yolo_to_onnx.py -m ${model%-dla} > /dev/null
echo -e "\nGenerating ${model}.trt. This may take a few minutes.\n"; start=$(date +%s)
if [[ $model == *-dla ]]; then
cmd="python3 onnx_to_tensorrt.py -m ${model%-dla} --dla_core 0"
else
cmd="python3 onnx_to_tensorrt.py -m ${model}"
fi
$cmd > /tmp/onnx_to_tensorrt.log || { cat /tmp/onnx_to_tensorrt.log && continue; }
mv ${model%-dla}.trt ${OUTPUT_FOLDER}/${model}.trt;
ln -s ${OUTPUT_FOLDER}/${model}.trt ${MODEL_CACHE_DIR}/${model}.trt
echo "Generated ${model}.trt in $(($(date +%s)-start)) seconds"
done
# Restore ENV after conversion
if [ ! -z ${TRT_MODEL_PREP_DEVICE+x} ]; then
unset CUDA_VISIBLE_DEVICES
if [ ! -z ${PREVIOUS_CVD+x} ]; then
export CUDA_VISIBLE_DEVICES="$PREVIOUS_CVD"
fi
fi
# Print which models exist in output folder
echo "Available tensorrt models:"
cd ${OUTPUT_FOLDER} && ls *.trt;

0
docker/support/tensorrt_detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/type → docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/type
View File

0
docker/support/tensorrt_detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/up → docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/up
View File

5
docker/support/tensorrt_detector/tensorrt_libyolo.sh → docker/tensorrt/detector/tensorrt_libyolo.sh
View File

@ -8,7 +8,10 @@ SCRIPT_DIR="/usr/local/src/tensorrt_demos"
git clone --depth 1 https://github.com/NateMeyer/tensorrt_demos.git -b conditional_download
# Build libyolo
cd ./tensorrt_demos/plugins && make all
if [ ! -e /usr/local/cuda ]; then
ln -s /usr/local/cuda-* /usr/local/cuda
fi
cd ./tensorrt_demos/plugins && make all -j$(nproc)
cp libyolo_layer.so /usr/local/lib/libyolo_layer.so
# Store yolo scripts for later conversion

0
requirements-tensorrt.txt → docker/tensorrt/requirements-amd64.txt
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1
docker/tensorrt/requirements-arm64.txt Normal file
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@ -0,0 +1 @@
cuda-python == 11.7; platform_machine == 'aarch64'

3
docker/tensorrt/requirements-models-arm64.txt Normal file
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@ -0,0 +1,3 @@
onnx == 1.14.0; platform_machine == 'aarch64'
protobuf == 3.20.3; platform_machine == 'aarch64'
numpy == 1.23.*; platform_machine == 'aarch64' # required by python-tensorrt 8.2.1 (Jetpack 4.6)

94
docker/tensorrt/trt.hcl Normal file
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@ -0,0 +1,94 @@
variable "ARCH" {
default = "amd64"
}
variable "BASE_IMAGE" {
default = null
}
variable "SLIM_BASE" {
default = null
}
variable "TRT_BASE" {
default = null
}
target "_build_args" {
args = {
BASE_IMAGE = BASE_IMAGE,
SLIM_BASE = SLIM_BASE,
TRT_BASE = TRT_BASE
}
platforms = ["linux/${ARCH}"]
}
target wget {
dockerfile = "docker/main/Dockerfile"
target = "wget"
inherits = ["_build_args"]
}
target deps {
dockerfile = "docker/main/Dockerfile"
target = "deps"
inherits = ["_build_args"]
}
target rootfs {
dockerfile = "docker/main/Dockerfile"
target = "rootfs"
inherits = ["_build_args"]
}
target wheels {
dockerfile = "docker/main/Dockerfile"
target = "wheels"
inherits = ["_build_args"]
}
target devcontainer {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/amd64"]
target = "devcontainer"
}
target "trt-deps" {
dockerfile = "docker/tensorrt/Dockerfile.base"
context = "."
contexts = {
deps = "target:deps",
}
inherits = ["_build_args"]
}
target "tensorrt-base" {
dockerfile = "docker/tensorrt/Dockerfile.base"
context = "."
contexts = {
deps = "target:deps",
}
inherits = ["_build_args"]
}
target "tensorrt" {
dockerfile = "docker/tensorrt/Dockerfile.${ARCH}"
context = "."
contexts = {
wget = "target:wget",
tensorrt-base = "target:tensorrt-base",
rootfs = "target:rootfs"
wheels = "target:wheels"
}
target = "frigate-tensorrt"
inherits = ["_build_args"]
}
target "devcontainer-trt" {
dockerfile = "docker/tensorrt/Dockerfile.amd64"
context = "."
contexts = {
wheels = "target:wheels",
trt-deps = "target:trt-deps",
devcontainer = "target:devcontainer"
}
platforms = ["linux/amd64"]
target = "devcontainer-trt"
}

26
docker/tensorrt/trt.mk Normal file
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@ -0,0 +1,26 @@
BOARDS += trt
JETPACK4_BASE ?= timongentzsch/l4t-ubuntu20-opencv:latest # L4T 32.7.1 JetPack 4.6.1
JETPACK5_BASE ?= nvcr.io/nvidia/l4t-tensorrt:r8.5.2-runtime # L4T 35.3.1 JetPack 5.1.1
X86_DGPU_ARGS := ARCH=amd64
JETPACK4_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK4_BASE) SLIM_BASE=$(JETPACK4_BASE) TRT_BASE=$(JETPACK4_BASE)
JETPACK5_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK5_BASE) SLIM_BASE=$(JETPACK5_BASE) TRT_BASE=$(JETPACK5_BASE)
local-trt: version
$(X86_DGPU_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt tensorrt
local-trt-jp4: version
$(JETPACK4_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp4 tensorrt
local-trt-jp5: version
$(JETPACK5_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp5 tensorrt
build-trt:
$(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt tensorrt
$(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 tensorrt
$(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 tensorrt
push-trt: build-trt
$(X86_DGPU_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt tensorrt
$(JETPACK4_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 tensorrt
$(JETPACK5_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 tensorrt

33
docs/docs/configuration/advanced.md
View File

@ -120,7 +120,7 @@ NOTE: The folder that is mapped from the host needs to be the folder that contai
## Custom go2rtc version
Frigate currently includes go2rtc v1.5.0, there may be certain cases where you want to run a different version of go2rtc.
Frigate currently includes go2rtc v1.8.4, there may be certain cases where you want to run a different version of go2rtc.
To do this:
@ -128,3 +128,34 @@ To do this:
2. Rename the build to `go2rtc`.
3. Give `go2rtc` execute permission.
4. Restart Frigate and the custom version will be used, you can verify by checking go2rtc logs.
## Validating your config.yaml file updates
When frigate starts up, it checks whether your config file is valid, and if it is not, the process exits. To minimize interruptions when updating your config, you have three options -- you can edit the config via the WebUI which has built in validation, use the config API, or you can validate on the command line using the frigate docker container.
### Via API
Frigate can accept a new configuration file as JSON at the `/config/save` endpoint. When updating the config this way, Frigate will validate the config before saving it, and return a `400` if the config is not valid.
```bash
curl -X POST http://frigate_host:5000/config/save -d @config.json
```
if you'd like you can use your yaml config directly by using [`yq`](https://github.com/mikefarah/yq) to convert it to json:
```bash
yq r -j config.yml | curl -X POST http://frigate_host:5000/config/save -d @-
```
### Via Command Line
You can also validate your config at the command line by using the docker container itself. In CI/CD, you leverage the return code to determine if your config is valid, Frigate will return `1` if the config is invalid, or `0` if it's valid.
```bash
docker run \
-v $(pwd)/config.yml:/config/config.yml \
--entrypoint python3 \
ghcr.io/blakeblackshear/frigate:stable \
-u -m frigate \
--validate_config
```

13
docs/docs/configuration/audio_detectors.md
View File

@ -48,15 +48,26 @@ cameras:
- detect
```
### Configuring Minimum Volume
The audio detector uses volume levels in the same way that motion in a camera feed is used for object detection. This means that frigate will not run audio detection unless the audio volume is above the configured level in order to reduce resource usage. Audio levels can vary widely between camera models so it is important to run tests to see what volume levels are. MQTT explorer can be used on the audio topic to see what volume level is being detected.
:::tip
Volume is considered motion for recordings, this means when the `record -> retain -> mode` is set to `motion` any time audio volume is > min_volume that recording segment for that camera will be kept.
:::
### Configuring Audio Events
The included audio model has over 500 different types of audio that can be detected, many of which are not practical. By default `bark`, `speech`, `yell`, and `scream` are enabled but these can be customized.
The included audio model has over [500 different types](https://github.com/blakeblackshear/frigate/blob/dev/audio-labelmap.txt) of audio that can be detected, many of which are not practical. By default `bark`, `fire_alarm`, `scream`, `speech`, and `yell` are enabled but these can be customized.
```yaml
audio:
enabled: True
listen:
- bark
- fire_alarm
- scream
- speech
- yell

166
docs/docs/configuration/autotracking.md Normal file
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@ -0,0 +1,166 @@
---
id: autotracking
title: Camera Autotracking
---
An ONVIF-capable, PTZ (pan-tilt-zoom) camera that supports relative movement within the field of view (FOV) can be configured to automatically track moving objects and keep them in the center of the frame.
![Autotracking example with zooming](/img/frigate-autotracking-example.gif)
## Autotracking behavior
Once Frigate determines that an object is not a false positive and has entered one of the required zones, the autotracker will move the PTZ camera to keep the object centered in the frame until the object either moves out of the frame, the PTZ is not capable of any more movement, or Frigate loses track of it.
Upon loss of tracking, Frigate will scan the region of the lost object for `timeout` seconds. If an object of the same type is found in that region, Frigate will autotrack that new object.
When tracking has ended, Frigate will return to the camera firmware's PTZ preset specified by the `return_preset` configuration entry.
## Checking ONVIF camera support
Frigate autotracking functions with PTZ cameras capable of relative movement within the field of view (as specified in the [ONVIF spec](https://www.onvif.org/specs/srv/ptz/ONVIF-PTZ-Service-Spec-v1712.pdf) as `RelativePanTiltTranslationSpace` having a `TranslationSpaceFov` entry).
Many cheaper or older PTZs may not support this standard. Frigate will report an error message in the log and disable autotracking if your PTZ is unsupported.
Alternatively, you can download and run [this simple Python script](https://gist.github.com/hawkeye217/152a1d4ba80760dac95d46e143d37112), replacing the details on line 4 with your camera's IP address, ONVIF port, username, and password to check your camera.
A growing list of cameras and brands that have been reported by users to work with Frigate's autotracking can be found [here](cameras.md).
## Configuration
First, set up a PTZ preset in your camera's firmware and give it a name. If you're unsure how to do this, consult the documentation for your camera manufacturer's firmware. Some tutorials for common brands: [Amcrest](https://www.youtube.com/watch?v=lJlE9-krmrM), [Reolink](https://www.youtube.com/watch?v=VAnxHUY5i5w), [Dahua](https://www.youtube.com/watch?v=7sNbc5U-k54).
Edit your Frigate configuration file and enter the ONVIF parameters for your camera. Specify the object types to track, a required zone the object must enter to begin autotracking, and the camera preset name you configured in your camera's firmware to return to when tracking has ended. Optionally, specify a delay in seconds before Frigate returns the camera to the preset.
An [ONVIF connection](cameras.md) is required for autotracking to function. Also, a [motion mask](masks.md) over your camera's timestamp and any overlay text is recommended to ensure they are completely excluded from scene change calculations when the camera is moving.
Note that `autotracking` is disabled by default but can be enabled in the configuration or by MQTT.
```yaml
cameras:
ptzcamera:
...
onvif:
# Required: host of the camera being connected to.
host: 0.0.0.0
# Optional: ONVIF port for device (default: shown below).
port: 8000
# Optional: username for login.
# NOTE: Some devices require admin to access ONVIF.
user: admin
# Optional: password for login.
password: admin
# Optional: PTZ camera object autotracking. Keeps a moving object in
# the center of the frame by automatically moving the PTZ camera.
autotracking:
# Optional: enable/disable object autotracking. (default: shown below)
enabled: False
# Optional: calibrate the camera on startup (default: shown below)
# A calibration will move the PTZ in increments and measure the time it takes to move.
# The results are used to help estimate the position of tracked objects after a camera move.
# Frigate will update your config file automatically after a calibration with
# a "movement_weights" entry for the camera. You should then set calibrate_on_startup to False.
calibrate_on_startup: False
# Optional: the mode to use for zooming in/out on objects during autotracking. (default: shown below)
# Available options are: disabled, absolute, and relative
# disabled - don't zoom in/out on autotracked objects, use pan/tilt only
# absolute - use absolute zooming (supported by most PTZ capable cameras)
# relative - use relative zooming (not supported on all PTZs, but makes concurrent pan/tilt/zoom movements)
zooming: disabled
# Optional: A value to change the behavior of zooming on autotracked objects. (default: shown below)
# A lower value will keep more of the scene in view around a tracked object.
# A higher value will zoom in more on a tracked object, but Frigate may lose tracking more quickly.
# The value should be between 0.1 and 0.75
zoom_factor: 0.3
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
- person
# Required: Begin automatically tracking an object when it enters any of the listed zones.
required_zones:
- zone_name
# Required: Name of ONVIF preset in camera's firmware to return to when tracking is over. (default: shown below)
return_preset: home
# Optional: Seconds to delay before returning to preset. (default: shown below)
timeout: 10
# Optional: Values generated automatically by a camera calibration. Do not modify these manually. (default: shown below)
movement_weights: []
```
## Calibration
PTZ motors operate at different speeds. Performing a calibration will direct Frigate to measure this speed over a variety of movements and use those measurements to better predict the amount of movement necessary to keep autotracked objects in the center of the frame.
Calibration is optional, but will greatly assist Frigate in autotracking objects that move across the camera's field of view more quickly.
To begin calibration, set the `calibrate_on_startup` for your camera to `True` and restart Frigate. Frigate will then make a series of small and large movements with your camera. Don't move the PTZ manually while calibration is in progress. Once complete, camera motion will stop and your config file will be automatically updated with a `movement_weights` parameter to be used in movement calculations. You should not modify this parameter manually.
After calibration has ended, your PTZ will be moved to the preset specified by `return_preset`.
:::note
Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal to avoid excessive network traffic or CPU usage during calibration. Calibration for most PTZs will take about two minutes. The Frigate log will show calibration progress and any errors.
:::
At this point, Frigate will be running and will continue to refine and update the `movement_weights` parameter in your config automatically as the PTZ moves during autotracking and more measurements are obtained.
Before restarting Frigate, you should set `calibrate_on_startup` in your config file to `False`, otherwise your refined `movement_weights` will be overwritten and calibration will occur when starting again.
You can recalibrate at any time by removing the `movement_weights` parameter, setting `calibrate_on_startup` to `True`, and then restarting Frigate. You may need to recalibrate or remove `movement_weights` from your config altogether if autotracking is erratic. If you change your `return_preset` in any way or if you change your camera's detect `fps` value, a recalibration is also recommended.
If you initially calibrate with zooming disabled and then enable zooming at a later point, you should also recalibrate.
## Best practices and considerations
Every PTZ camera is different, so autotracking may not perform ideally in every situation. This experimental feature was initially developed using an EmpireTech/Dahua SD1A404XB-GNR.
The object tracker in Frigate estimates the motion of the PTZ so that tracked objects are preserved when the camera moves. In most cases 5 fps is sufficient, but if you plan to track faster moving objects, you may want to increase this slightly. Higher frame rates (> 10fps) will only slow down Frigate and the motion estimator and may lead to dropped frames, especially if you are using experimental zooming.
A fast [detector](object_detectors.md) is recommended. CPU detectors will not perform well or won't work at all. You can watch Frigate's debug viewer for your camera to see a thicker colored box around the object currently being autotracked.
![Autotracking Debug View](/img/autotracking-debug.gif)
A full-frame zone in `required_zones` is not recommended, especially if you've calibrated your camera and there are `movement_weights` defined in the configuration file. Frigate will continue to autotrack an object that has entered one of the `required_zones`, even if it moves outside of that zone.
Some users have found it helpful to adjust the zone `inertia` value. See the [configuration reference](index.md).
## Zooming
Zooming is a very experimental feature and may use significantly more CPU when tracking objects than panning/tilting only.
Absolute zooming makes zoom movements separate from pan/tilt movements. Most PTZ cameras will support absolute zooming. Absolute zooming was developed to be very conservative to work best with a variety of cameras and scenes. Absolute zooming usually will not occur until an object has stopped moving or is moving very slowly.
Relative zooming attempts to make a zoom movement concurrently with any pan/tilt movements. It was tested to work with some Dahua and Amcrest PTZs. But the ONVIF specification indicates that there no assumption about how the generic zoom range is mapped to magnification, field of view or other physical zoom dimension when using relative zooming. So if relative zooming behavior is erratic or just doesn't work, try absolute zooming.
You can optionally adjust the `zoom_factor` for your camera in your configuration file. Lower values will leave more space from the scene around the tracked object while higher values will cause your camera to zoom in more on the object. However, keep in mind that Frigate needs a fair amount of pixels and scene details outside of the bounding box of the tracked object to estimate the motion of your camera. If the object is taking up too much of the frame, Frigate will not be able to track the motion of the camera and your object will be lost.
The range of this option is from 0.1 to 0.75. The default value of 0.3 is conservative and should be sufficient for most users. Because every PTZ and scene is different, you should experiment to determine what works best for you.
## Usage applications
In security and surveillance, it's common to use "spotter" cameras in combination with your PTZ. When your fixed spotter camera detects an object, you could use an automation platform like Home Assistant to move the PTZ to a specific preset so that Frigate can begin automatically tracking the object. For example: a residence may have fixed cameras on the east and west side of the property, capturing views up and down a street. When the spotter camera on the west side detects a person, a Home Assistant automation could move the PTZ to a camera preset aimed toward the west. When the object enters the specified zone, Frigate's autotracker could then continue to track the person as it moves out of view of any of the fixed cameras.
## Troubleshooting and FAQ
### The autotracker loses track of my object. Why?
There are many reasons this could be the case. If you are using experimental zooming, your `zoom_factor` value might be too high, the object might be traveling too quickly, the scene might be too dark, there are not enough details in the scene (for example, a PTZ looking down on a driveway or other monotone background without a sufficient number of hard edges or corners), or the scene is otherwise less than optimal for Frigate to maintain tracking.
Your camera's shutter speed may also be set too low so that blurring occurs with motion. Check your camera's firmware to see if you can increase the shutter speed.
Watching Frigate's debug view can help to determine a possible cause. The autotracked object will have a thicker colored box around it.
### I'm seeing an error in the logs that my camera "is still in ONVIF 'MOVING' status." What does this mean?
There are two possible known reasons for this (and perhaps others yet unknown): a slow PTZ motor or buggy camera firmware. Frigate uses an ONVIF parameter provided by the camera, `MoveStatus`, to determine when the PTZ's motor is moving or idle. According to some users, Hikvision PTZs (even with the latest firmware), are not updating this value after PTZ movement. Unfortunately there is no workaround to this bug in Hikvision firmware, so autotracking will not function correctly and should be disabled in your config. This may also be the case with other non-Hikvision cameras utilizing Hikvision firmware.
### I tried calibrating my camera, but the logs show that it is stuck at 0% and Frigate is not starting up.
This is often caused by the same reason as above - the `MoveStatus` ONVIF parameter is not changing due to a bug in your camera's firmware. Also, see the note above: Frigate's web UI and all other cameras will be unresponsive while calibration is in progress. This is expected and normal. But if you don't see log entries every few seconds for calibration progress, your camera is not compatible with autotracking.
### I'm seeing this error in the logs: "Autotracker: motion estimator couldn't get transformations". What does this mean?
To maintain object tracking during PTZ moves, Frigate tracks the motion of your camera based on the details of the frame. If you are seeing this message, it could mean that your `zoom_factor` may be set too high, the scene around your detected object does not have enough details (like hard edges or color variatons), or your camera's shutter speed is too slow and motion blur is occurring. Try reducing `zoom_factor`, finding a way to alter the scene around your object, or changing your camera's shutter speed.
### Calibration seems to have completed, but the camera is not actually moving to track my object. Why?
Some cameras have firmware that reports that FOV RelativeMove, the ONVIF command that Frigate uses for autotracking, is supported. However, if the camera does not pan or tilt when an object comes into the required zone, your camera's firmware does not actually support FOV RelativeMove. One such camera is the Uniview IPC672LR-AX4DUPK. It actually moves its zoom motor instead of panning and tilting and does not follow the ONVIF standard whatsoever.

25
docs/docs/configuration/camera_specific.md
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@ -80,8 +80,8 @@ cameras:
rtmp:
enabled: False # <-- RTMP should be disabled if your stream is not H264
detect:
width: # <---- update for your camera's resolution
height: # <---- update for your camera's resolution
width: # <- optional, by default Frigate tries to automatically detect resolution
height: # <- optional, by default Frigate tries to automatically detect resolution
```
### Blue Iris RTSP Cameras
@ -108,21 +108,20 @@ According to [this discussion](https://github.com/blakeblackshear/frigate/issues
```yaml
go2rtc:
streams:
reolink:
- http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password
- "ffmpeg:reolink#audio=opus"
reolink_sub:
- http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password
your_reolink_camera:
- "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password#video=copy#audio=copy#audio=opus"
your_reolink_camera_sub:
- "ffmpeg:http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password"
cameras:
reolink:
your_reolink_camera:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/reolink?video=copy&audio=aac
- path: rtsp://127.0.0.1:8554/your_reolink_camera
input_args: preset-rtsp-restream
roles:
- record
- path: rtsp://127.0.0.1:8554/reolink_sub?video=copy
- path: rtsp://127.0.0.1:8554/your_reolink_camera_sub
input_args: preset-rtsp-restream
roles:
- detect
@ -141,7 +140,7 @@ go2rtc:
- rtspx://192.168.1.1:7441/abcdefghijk
```
[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.5.0#source-rtsp)
[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.8.4#source-rtsp)
In the Unifi 2.0 update Unifi Protect Cameras had a change in audio sample rate which causes issues for ffmpeg. The input rate needs to be set for record and rtmp if used directly with unifi protect.
@ -151,3 +150,7 @@ ffmpeg:
record: preset-record-ubiquiti
rtmp: preset-rtmp-ubiquiti # recommend using go2rtc instead
```
### TP-Link VIGI Cameras
TP-Link VIGI cameras need some adjustments to the main stream settings on the camera itself to avoid issues. The stream needs to be configured as `H264` with `Smart Coding` set to `off`. Without these settings you may have problems when trying to watch recorded events. For example Firefox will stop playback after a few seconds and show the following error message: `The media playback was aborted due to a corruption problem or because the media used features your browser did not support.`.

54
docs/docs/configuration/cameras.md
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@ -1,6 +1,6 @@
---
id: cameras
title: Cameras
title: Camera Configuration
---
## Setting Up Camera Inputs
@ -11,11 +11,12 @@ A camera is enabled by default but can be temporarily disabled by using `enabled
Each role can only be assigned to one input per camera. The options for roles are as follows:
| Role | Description |
| ---------- | ---------------------------------------------------------------------------------------- |
| `detect` | Main feed for object detection |
| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md) |
| `rtmp` | Deprecated: Broadcast as an RTMP feed for other services to consume. [docs](restream.md) |
| Role | Description |
| -------- | ---------------------------------------------------------------------------------------- |
| `detect` | Main feed for object detection. [docs](object_detectors.md) |
| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md) |
| `audio` | Feed for audio based detection. [docs](audio_detectors.md) |
| `rtmp` | Deprecated: Broadcast as an RTMP feed for other services to consume. [docs](restream.md) |
```yaml
mqtt:
@ -33,8 +34,8 @@ cameras:
roles:
- record
detect:
width: 1280
height: 720
width: 1280 # <- optional, by default Frigate tries to automatically detect resolution
height: 720 # <- optional, by default Frigate tries to automatically detect resolution
```
Additional cameras are simply added to the config under the `cameras` entry.
@ -51,13 +52,18 @@ For camera model specific settings check the [camera specific](camera_specific.m
## Setting up camera PTZ controls
Add onvif config to camera
:::caution
Not every PTZ supports ONVIF, which is the standard protocol Frigate uses to communicate with your camera. Check the [official list of ONVIF conformant products](https://www.onvif.org/conformant-products/), your camera documentation, or camera manufacturer's website to ensure your PTZ supports ONVIF. Also, ensure your camera is running the latest firmware.
:::
Add the onvif section to your camera in your configuration file:
```yaml
cameras:
back:
ffmpeg:
...
ffmpeg: ...
onvif:
host: 10.0.10.10
port: 8000
@ -65,4 +71,28 @@ cameras:
password: password
```
then PTZ controls will be available in the cameras WebUI.
If the ONVIF connection is successful, PTZ controls will be available in the camera's WebUI.
An ONVIF-capable camera that supports relative movement within the field of view (FOV) can also be configured to automatically track moving objects and keep them in the center of the frame. For autotracking setup, see the [autotracking](autotracking.md) docs.
## ONVIF PTZ camera recommendations
This list of working and non-working PTZ cameras is based on user feedback.
| Brand or specific camera | PTZ Controls | Autotracking | Notes |
| ------------------------ | :----------: | :----------: | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Amcrest | ✅ | ✅ | ⛔️ Generally, Amcrest should work, but some older models (like the common IP2M-841) don't support autotracking |
| Amcrest ASH21 | ❌ | ❌ | No ONVIF support |
| Ctronics PTZ | ✅ | ❌ | |
| Dahua | ✅ | ✅ | |
| Foscam R5 | ✅ | ❌ | |
| Hikvision | ✅ | ❌ | Incomplete ONVIF support (MoveStatus won't update even on latest firmware) - reported with HWP-N4215IH-DE and DS-2DE3304W-DE, but likely others |
| Reolink 511WA | ✅ | ❌ | Zoom only |
| Reolink E1 Pro | ✅ | ❌ | |
| Reolink E1 Zoom | ✅ | ❌ | |
| Reolink RLC-823A 16x | ✅ | ❌ | |
| Sunba 405-D20X | ✅ | ❌ | |
| Tapo C200 | ✅ | ❌ | Incomplete ONVIF support |
| Tapo C210 | ❌ | ❌ | Incomplete ONVIF support |
| Uniview IPC672LR-AX4DUPK | ✅ | ❌ | Firmware says FOV relative movement is supported, but camera doesn't actually move when sending ONVIF commands |
| Vikylin PTZ-2804X-I2 | ❌ | ❌ | Incomplete ONVIF support |

24
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@ -11,16 +11,20 @@ It is highly recommended to use hwaccel presets in the config. These presets not
See [the hwaccel docs](/configuration/hardware_acceleration.md) for more info on how to setup hwaccel for your GPU / iGPU.
| Preset | Usage | Other Notes |
| --------------------- | ---------------------------- | ----------------------------------------------------- |
| preset-rpi-32-h264 | 32 bit Rpi with h264 stream | |
| preset-rpi-64-h264 | 64 bit Rpi with h264 stream | |
| preset-vaapi | Intel & AMD VAAPI | Check hwaccel docs to ensure correct driver is chosen |
| preset-intel-qsv-h264 | Intel QSV with h264 stream | If issues occur recommend using vaapi preset instead |
| preset-intel-qsv-h265 | Intel QSV with h265 stream | If issues occur recommend using vaapi preset instead |
| preset-nvidia-h264 | Nvidia GPU with h264 stream | |
| preset-nvidia-h265 | Nvidia GPU with h265 stream | |
| preset-nvidia-mjpeg | Nvidia GPU with mjpeg stream | Recommend restreaming mjpeg and using nvidia-h264 |
| Preset | Usage | Other Notes |
| --------------------- | ------------------------------ | ----------------------------------------------------- |
| preset-rpi-64-h264 | 64 bit Rpi with h264 stream | |
| preset-rpi-64-h265 | 64 bit Rpi with h265 stream | |
| preset-vaapi | Intel & AMD VAAPI | Check hwaccel docs to ensure correct driver is chosen |
| preset-intel-qsv-h264 | Intel QSV with h264 stream | If issues occur recommend using vaapi preset instead |
| preset-intel-qsv-h265 | Intel QSV with h265 stream | If issues occur recommend using vaapi preset instead |
| preset-nvidia-h264 | Nvidia GPU with h264 stream | |
| preset-nvidia-h265 | Nvidia GPU with h265 stream | |
| preset-nvidia-mjpeg | Nvidia GPU with mjpeg stream | Recommend restreaming mjpeg and using nvidia-h264 |
| preset-jetson-h264 | Nvidia Jetson with h264 stream | |
| preset-jetson-h265 | Nvidia Jetson with h265 stream | |
| preset-rk-h264 | Rockchip MPP with h264 stream | Use image with *-rk suffix and privileged mode |
| preset-rk-h265 | Rockchip MPP with h265 stream | Use image with *-rk suffix and privileged mode |
### Input Args Presets

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