Community Supported Boards Framework (#7114)

* Make main frigate build non rpi specific and build rpi using base image

* Add boards to sidebar

* Fix docker build

* Fix docs build

* Update pr branch for testing

* remove target from rpi build

* Remove manual build

* Add push build for rpi

* fix typos, improve wording

* Add arm build for rpi

* Cleanup and add default github ref name

* Cleanup docker build file system

* Setup to use docker bake

* Add ci/cd for bake

* Fix path

* Fix devcontainer

* Set targets

* Fix build

* Fix syntax

* Add wheels target

* Move dev container to trt

* Update key and fix rpi local

* Move requirements files and set intermediate targets

* Add back --load

* Update docs for community board development

* Update installation docs to reflect different builds available

* Update docs with official and community supported headers

* Update codeowners docs

* Update docs

* Assemble main and standard builds

* Change order of pushes

* Remove community board after successful build

* Fix rpi bake file names

docker/tensorrt/Dockerfile

@@ -0,0 +1,49 @@
+# 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.txt /requirements-tensorrt.txt
+RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt
+
+# Build TensorRT-specific library
+FROM nvcr.io/nvidia/tensorrt:23.03-py3 AS trt-deps
+
+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 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/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
+
+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

docker/tensorrt/detector/rootfs/etc/ld.so.conf.d/cuda_tensorrt.conf

@@ -0,0 +1,6 @@
+/usr/local/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cudnn/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cuda_runtime/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cublas/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cuda_nvrtc/lib
+/usr/local/lib/python3.9/dist-packages/tensorrt

docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/run

@@ -0,0 +1,53 @@
+#!/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

docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/type

@@ -0,0 +1 @@
+oneshot

docker/tensorrt/detector/rootfs/etc/s6-overlay/s6-rc.d/trt-model-prepare/up

@@ -0,0 +1 @@
+/etc/s6-overlay/s6-rc.d/trt-model-prepare/run

docker/tensorrt/detector/tensorrt_libyolo.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+SCRIPT_DIR="/usr/local/src/tensorrt_demos"
+
+# Clone tensorrt_demos repo
+git clone --depth 1 https://github.com/NateMeyer/tensorrt_demos.git -b conditional_download
+
+# Build libyolo
+cd ./tensorrt_demos/plugins && make all
+cp libyolo_layer.so /usr/local/lib/libyolo_layer.so
+
+# Store yolo scripts for later conversion
+cd ../
+mkdir -p ${SCRIPT_DIR}/plugins
+cp plugins/libyolo_layer.so ${SCRIPT_DIR}/plugins/libyolo_layer.so
+cp -a yolo ${SCRIPT_DIR}/

docker/tensorrt/requirements.txt

@@ -0,0 +1,12 @@
+# NVidia TensorRT Support (amd64 only)
+--extra-index-url 'https://pypi.nvidia.com'
+numpy < 1.24; platform_machine == 'x86_64'
+tensorrt == 8.5.3.*; platform_machine == 'x86_64'
+cuda-python == 11.8; platform_machine == 'x86_64'
+cython == 0.29.*; platform_machine == 'x86_64'
+nvidia-cuda-runtime-cu12 == 12.1.*; platform_machine == 'x86_64'
+nvidia-cuda-runtime-cu11 == 11.8.*; platform_machine == 'x86_64'
+nvidia-cublas-cu11 == 11.11.3.6; platform_machine == 'x86_64'
+nvidia-cudnn-cu11 == 8.6.0.*; platform_machine == 'x86_64'
+onnx==1.14.0; platform_machine == 'x86_64'
+protobuf==3.20.3; platform_machine == 'x86_64'

docker/tensorrt/trt.hcl

@@ -0,0 +1,48 @@
+target deps {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "deps"
+}
+
+target rootfs {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "rootfs"
+}
+
+target wheels {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "wheels"
+}
+
+target devcontainer {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "devcontainer"
+}
+
+target tensorrt {
+  dockerfile = "docker/tensorrt/Dockerfile"
+  context = "."
+  contexts = {
+    deps = "target:deps",
+    rootfs = "target:rootfs"
+    wheels = "target:wheels"
+  }
+  platforms = ["linux/amd64"]
+  target = "frigate-tensorrt"
+}
+
+target devcontainer-trt {
+  dockerfile = "docker/tensorrt/Dockerfile"
+  context = "."
+  contexts = {
+    deps = "target:deps",
+    rootfs = "target:rootfs"
+    wheels = "target:wheels"
+    devcontainer = "target:devcontainer"
+  }
+  platforms = ["linux/amd64"]
+  target = "devcontainer-trt"
+}

docker/tensorrt/trt.mk

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