diff --git a/.cspell/frigate-dictionary.txt b/.cspell/frigate-dictionary.txt index 397584bd9..6c0e8022f 100644 --- a/.cspell/frigate-dictionary.txt +++ b/.cspell/frigate-dictionary.txt @@ -1,168 +1,303 @@ -rtmp -edgetpu -labelmap -rockchip -jetson -rocm -vaapi -CUDA -hwaccel -RTSP -Hikvision -Dahua -Amcrest -Reolink -Loryta -Beelink -Celeron -vaapi -blakeblackshear -workdir -onvif -autotracking -openvino -tflite -deepstack -codeproject -udev -tailscale -restream -restreaming -webrtc -ssdlite -mobilenet -mosquitto -datasheet -Jellyfin -Radeon -libva -Ubiquiti -Unifi -Tapo -Annke -autotracker -autotracked -variations -ONVIF -traefik -devcontainer -rootfs -ffprobe -autotrack -logpipe -imread -imwrite -imencode -imutils -thresholded -timelapse -ultrafast -sleeptime -radeontop -vainfo -tmpfs -homography -websockets -LIBAVFORMAT -NTSC -onnxruntime -fourcc -radeonsi -paho -imagestream -jsonify -cgroups -sysconf -memlimit -gpuload -nvml -setproctitle -psutil -Kalman -frontdoor -namedtuples -zeep -fflags -probesize -wallclock -rknn -socs -pydantic -shms -imdecode -colormap -webui -mse -jsmpeg -unreviewed -Chromecast -Swipeable -flac -scroller -cmdline -toggleable -bottombar -opencv -apexcharts -buildx -mqtt -rawvideo -defragment -Norfair -subclassing -yolo -tensorrt -blackshear -stylelint -HACS -homeassistant -hass -castable -mobiledet -framebuffer -mjpeg -substream -codeowner -noninteractive -restreamed -mountpoint -fstype -OWASP -iotop -letsencrypt -fullchain -lsusb -iostat -usermod -balena -passwordless -debconf -dpkg -poweroff -surveillance -qnap -homekit -colorspace -quantisation -skylake -Cuvid -foscam -onnx -numpy -protobuf aarch +absdiff +airockchip +Alloc +Amcrest amdgpu -chipset -referer -mpegts -webp +analyzeduration +Annke +apexcharts +arange +argmax +argmin +argpartition +ascontiguousarray authelia authentik -unichip -rebranded -udevadm +autodetected automations -unraid -hideable +autotrack +autotracked +autotracker +autotracking +balena +Beelink +BGRA +BHWC +blackshear +blakeblackshear +bottombar +buildx +castable +cdist +Celeron +cgroups +chipset +chromadb +Chromecast +cmdline +codeowner +CODEOWNERS +codeproject +colormap +colorspace +comms +ctypeslib +CUDA +Cuvid +Dahua +datasheet +debconf +deci +deepstack +defragment +devcontainer +DEVICEMAP +discardcorrupt +dpkg +dsize +dtype +ECONNRESET +edgetpu +faststart +fflags +ffprobe +fillna +flac +foscam +fourcc +framebuffer +fregate +frégate +fromarray +frombuffer +frontdoor +fstype +fullchain +fullscreen +genai +generativeai +genpts +getpid +gpuload +HACS +Hailo +hass +hconcat healthcheck -keepalive \ No newline at end of file +hideable +Hikvision +homeassistant +homekit +homography +hsize +hstack +httpx +hwaccel +hwdownload +hwmap +hwupload +iloc +imagestream +imdecode +imencode +imread +imutils +imwrite +interp +iostat +iotop +itemsize +Jellyfin +jetson +jetsons +joserfc +jsmpeg +jsonify +Kalman +keepalive +keepdims +labelmap +letsencrypt +levelname +LIBAVFORMAT +libedgetpu +libnvinfer +libva +libwebp +libx +libyolo +linalg +localzone +logpipe +Loryta +lstsq +lsusb +markupsafe +maxsplit +MEMHOSTALLOC +memlimit +meshgrid +metadatas +migraphx +minilm +mjpeg +mkfifo +mobiledet +mobilenet +modelpath +mosquitto +mountpoint +movflags +mpegts +mqtt +mse +msenc +namedtuples +nbytes +nchw +ndarray +ndimage +nethogs +newaxis +nhwc +NOBLOCK +nobuffer +nokey +NONBLOCK +noninteractive +noprint +Norfair +nptype +NTSC +numpy +nvenc +nvhost +nvml +nvmpi +ollama +onnx +onnxruntime +onvif +ONVIF +openai +opencv +openvino +OWASP +paho +passwordless +popleft +posthog +postprocess +poweroff +preexec +probesize +protobuf +psutil +pubkey +putenv +pycache +pydantic +pyobj +pysqlite +pytz +pywebpush +qnap +quantisation +Radeon +radeonsi +radeontop +rawvideo +rcond +RDONLY +rebranded +referer +Reolink +restream +restreamed +restreaming +rkmpp +rknn +rkrga +rockchip +rocm +rocminfo +rootfs +rtmp +RTSP +ruamel +scroller +setproctitle +setpts +shms +SIGUSR +skylake +sleeptime +SNDMORE +socs +sqliteq +ssdlite +statm +stimeout +stylelint +subclassing +substream +superfast +surveillance +svscan +Swipeable +sysconf +tailscale +Tapo +tensorrt +tflite +thresholded +timelapse +tmpfs +tobytes +toggleable +traefik +tzlocal +Ubiquiti +udev +udevadm +ultrafast +unichip +unidecode +Unifi +unixepoch +unraid +unreviewed +userdata +usermod +vaapi +vainfo +variations +vconcat +vitb +vstream +vsync +wallclock +webp +webpush +webrtc +websockets +webui +werkzeug +workdir +WRONLY +wsgirefserver +wsgiutils +wsize +xaddr +xmaxs +xmins +XPUB +XSUB +ymaxs +ymins +yolo +yolonas +yolox +zeep +zerolatency diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index e14516b04..619d71d48 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -179,57 +179,18 @@ jobs: h8l.tags=${{ steps.setup.outputs.image-name }}-h8l *.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-h8l *.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-h8l,mode=max - #- name: AMD/ROCm general build - # env: - # AMDGPU: gfx - # HSA_OVERRIDE: 0 - # uses: docker/bake-action@v3 - # with: - # push: true - # targets: rocm - # files: docker/rocm/rocm.hcl - # set: | - # rocm.tags=${{ steps.setup.outputs.image-name }}-rocm - # *.cache-from=type=gha - #- name: AMD/ROCm gfx900 - # env: - # AMDGPU: gfx900 - # HSA_OVERRIDE: 1 - # HSA_OVERRIDE_GFX_VERSION: 9.0.0 - # uses: docker/bake-action@v3 - # with: - # push: true - # targets: rocm - # files: docker/rocm/rocm.hcl - # set: | - # rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx900 - # *.cache-from=type=gha - #- name: AMD/ROCm gfx1030 - # env: - # AMDGPU: gfx1030 - # HSA_OVERRIDE: 1 - # HSA_OVERRIDE_GFX_VERSION: 10.3.0 - # uses: docker/bake-action@v3 - # with: - # push: true - # targets: rocm - # files: docker/rocm/rocm.hcl - # set: | - # rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx1030 - # *.cache-from=type=gha - #- name: AMD/ROCm gfx1100 - # env: - # AMDGPU: gfx1100 - # HSA_OVERRIDE: 1 - # HSA_OVERRIDE_GFX_VERSION: 11.0.0 - # uses: docker/bake-action@v3 - # with: - # push: true - # targets: rocm - # files: docker/rocm/rocm.hcl - # set: | - # rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx1100 - # *.cache-from=type=gha + - name: AMD/ROCm general build + env: + AMDGPU: gfx + HSA_OVERRIDE: 0 + uses: docker/bake-action@v3 + with: + push: true + targets: rocm + files: docker/rocm/rocm.hcl + set: | + rocm.tags=${{ steps.setup.outputs.image-name }}-rocm + *.cache-from=type=gha # The majority of users running arm64 are rpi users, so the rpi # build should be the primary arm64 image assemble_default_build: diff --git a/.vscode/launch.json b/.vscode/launch.json index fe709c92d..5c858267d 100644 --- a/.vscode/launch.json +++ b/.vscode/launch.json @@ -3,10 +3,9 @@ "configurations": [ { "name": "Python: Launch Frigate", - "type": "python", + "type": "debugpy", "request": "launch", - "module": "frigate", - "justMyCode": true + "module": "frigate" } ] } diff --git a/Makefile b/Makefile index 8ff6231b7..b7c6ab821 100644 --- a/Makefile +++ b/Makefile @@ -4,8 +4,6 @@ COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1) VERSION = 0.15.0 IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD) -CURRENT_UID := $(shell id -u) -CURRENT_GID := $(shell id -g) BOARDS= #Initialized empty include docker/*/*.mk @@ -18,25 +16,38 @@ version: echo 'VERSION = "$(VERSION)-$(COMMIT_HASH)"' > frigate/version.py local: version - docker buildx build --target=frigate --tag frigate:latest --load --file docker/main/Dockerfile . + docker buildx build --target=frigate --file docker/main/Dockerfile . \ + --tag frigate:latest \ + --load amd64: - docker buildx build --platform linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile . + docker buildx build --target=frigate --file docker/main/Dockerfile . \ + --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \ + --platform linux/amd64 arm64: - docker buildx build --platform linux/arm64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile . + docker buildx build --target=frigate --file docker/main/Dockerfile . \ + --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \ + --platform linux/arm64 build: version amd64 arm64 - docker buildx build --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile . + docker buildx build --target=frigate --file docker/main/Dockerfile . \ + --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \ + --platform linux/arm64/v8,linux/amd64 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 . + docker buildx build --target=frigate --file docker/main/Dockerfile . \ + --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) \ + --platform linux/arm64/v8,linux/amd64 \ + --push run: local docker run --rm --publish=5000:5000 --volume=${PWD}/config:/config frigate:latest run_tests: local - docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m unittest - docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m mypy --config-file frigate/mypy.ini frigate + docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest \ + python3 -u -m unittest + docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest \ + python3 -u -m mypy --config-file frigate/mypy.ini frigate .PHONY: run_tests diff --git a/cspell.json b/cspell.json index e325bbb69..132e51532 100644 --- a/cspell.json +++ b/cspell.json @@ -7,7 +7,8 @@ "*.db", "node_modules", "__pycache__", - "dist" + "dist", + "/audio-labelmap.txt" ], "language": "en", "dictionaryDefinitions": [ diff --git a/docker/hailo8l/h8l.mk b/docker/hailo8l/h8l.mk index 8d8a5d00f..318771802 100644 --- a/docker/hailo8l/h8l.mk +++ b/docker/hailo8l/h8l.mk @@ -1,10 +1,15 @@ BOARDS += h8l local-h8l: version - docker buildx bake --load --file=docker/hailo8l/h8l.hcl --set h8l.tags=frigate:latest-h8l h8l + docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \ + --set h8l.tags=frigate:latest-h8l \ + --load build-h8l: version - docker buildx bake --file=docker/hailo8l/h8l.hcl --set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l h8l + docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \ + --set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l push-h8l: build-h8l - docker buildx bake --push --file=docker/hailo8l/h8l.hcl --set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l h8l \ No newline at end of file + docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \ + --set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l \ + --push \ No newline at end of file diff --git a/docker/main/Dockerfile b/docker/main/Dockerfile index 92e28a381..3cd73cf95 100644 --- a/docker/main/Dockerfile +++ b/docker/main/Dockerfile @@ -170,6 +170,9 @@ RUN /build_pysqlite3.sh COPY docker/main/requirements-wheels.txt /requirements-wheels.txt RUN pip3 wheel --wheel-dir=/wheels -r /requirements-wheels.txt +COPY docker/main/requirements-wheels-post.txt /requirements-wheels-post.txt +RUN pip3 wheel --no-deps --wheel-dir=/wheels-post -r /requirements-wheels-post.txt + # Collect deps in a single layer FROM scratch AS deps-rootfs @@ -212,6 +215,14 @@ RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \ python3 -m pip install --upgrade pip && \ pip3 install -U /deps/wheels/*.whl +# We have to uninstall this dependency specifically +# as it will break onnxruntime-openvino +RUN pip3 uninstall -y onnxruntime + +RUN --mount=type=bind,from=wheels,source=/wheels-post,target=/deps/wheels \ + python3 -m pip install --upgrade pip && \ + pip3 install -U /deps/wheels/*.whl + COPY --from=deps-rootfs / / RUN ldconfig diff --git a/docker/main/install_deps.sh b/docker/main/install_deps.sh index 34f2e093e..e640a61d1 100755 --- a/docker/main/install_deps.sh +++ b/docker/main/install_deps.sh @@ -44,7 +44,7 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz" tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/5.0 --strip-components 1 rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/5.0/doc /usr/lib/ffmpeg/5.0/bin/ffplay - wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2024-09-13-12-57/ffmpeg-n7.0.2-17-gf705bc5b73-linux64-gpl-7.0.tar.xz" + wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linux64-gpl-7.0.tar.xz" tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1 rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/7.0/doc /usr/lib/ffmpeg/7.0/bin/ffplay fi @@ -56,19 +56,18 @@ if [[ "${TARGETARCH}" == "arm64" ]]; then wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/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/ffmpeg/5.0 --strip-components 1 rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/5.0/doc /usr/lib/ffmpeg/5.0/bin/ffplay - wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2024-09-13-12-57/ffmpeg-n7.0.2-17-gf705bc5b73-linuxarm64-gpl-7.0.tar.xz" + wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linuxarm64-gpl-7.0.tar.xz" tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1 rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/7.0/doc /usr/lib/ffmpeg/7.0/bin/ffplay fi # arch specific packages if [[ "${TARGETARCH}" == "amd64" ]]; then - # use debian bookworm for hwaccel packages + # use debian bookworm for amd / intel-i965 driver packages echo 'deb https://deb.debian.org/debian bookworm main contrib non-free' >/etc/apt/sources.list.d/debian-bookworm.list apt-get -qq update apt-get -qq install --no-install-recommends --no-install-suggests -y \ - intel-opencl-icd intel-media-va-driver-non-free i965-va-driver \ - libmfx-gen1.2 libmfx1 onevpl-tools intel-gpu-tools \ + i965-va-driver intel-gpu-tools onevpl-tools \ libva-drm2 \ mesa-va-drivers radeontop @@ -77,6 +76,17 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then i965-va-driver-shaders rm -f /etc/apt/sources.list.d/debian-bookworm.list + + # use intel apt intel packages + wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg + echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | tee /etc/apt/sources.list.d/intel-gpu-jammy.list + apt-get -qq update + apt-get -qq install --no-install-recommends --no-install-suggests -y \ + intel-opencl-icd intel-level-zero-gpu intel-media-va-driver-non-free \ + libmfx1 libmfxgen1 libvpl2 + + rm -f /usr/share/keyrings/intel-graphics.gpg + rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list fi if [[ "${TARGETARCH}" == "arm64" ]]; then diff --git a/docker/main/requirements-wheels-post.txt b/docker/main/requirements-wheels-post.txt new file mode 100644 index 000000000..a1686f091 --- /dev/null +++ b/docker/main/requirements-wheels-post.txt @@ -0,0 +1,3 @@ +# ONNX +onnxruntime-openvino == 1.19.* ; platform_machine == 'x86_64' +onnxruntime == 1.19.* ; platform_machine == 'aarch64' \ No newline at end of file diff --git a/docker/main/requirements-wheels.txt b/docker/main/requirements-wheels.txt index a81f6ec93..a704cde16 100644 --- a/docker/main/requirements-wheels.txt +++ b/docker/main/requirements-wheels.txt @@ -28,13 +28,11 @@ norfair == 2.2.* setproctitle == 1.3.* ws4py == 0.5.* unidecode == 1.3.* -# OpenVino & ONNX -openvino == 2024.1.* -onnxruntime-openvino == 1.18.* ; platform_machine == 'x86_64' -onnxruntime == 1.18.* ; platform_machine == 'aarch64' +# OpenVino (ONNX installed in wheels-post) +openvino == 2024.3.* # Embeddings -onnx_clip == 4.0.* chromadb == 0.5.0 +onnx_clip == 4.0.* # Generative AI google-generativeai == 0.6.* ollama == 0.2.* diff --git a/docker/main/rootfs/usr/local/go2rtc/create_config.py b/docker/main/rootfs/usr/local/go2rtc/create_config.py index 6229586e5..a9abbe1d1 100644 --- a/docker/main/rootfs/usr/local/go2rtc/create_config.py +++ b/docker/main/rootfs/usr/local/go2rtc/create_config.py @@ -2,16 +2,19 @@ import json import os +import shutil import sys from pathlib import Path import yaml sys.path.insert(0, "/opt/frigate") -from frigate.const import BIRDSEYE_PIPE # noqa: E402 -from frigate.ffmpeg_presets import ( # noqa: E402 - parse_preset_hardware_acceleration_encode, +from frigate.const import ( + BIRDSEYE_PIPE, + DEFAULT_FFMPEG_VERSION, + INCLUDED_FFMPEG_VERSIONS, ) +from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_encode sys.path.remove("/opt/frigate") @@ -108,14 +111,12 @@ else: # ensure ffmpeg path is set correctly path = config.get("ffmpeg", {}).get("path", "default") if path == "default": - if int(os.getenv("", "59") or "59") >= 59: - ffmpeg_path = "/usr/lib/ffmpeg/7.0/bin/ffmpeg" + if shutil.which("ffmpeg") is None: + ffmpeg_path = f"/usr/lib/ffmpeg/{DEFAULT_FFMPEG_VERSION}/bin/ffmpeg" else: ffmpeg_path = "ffmpeg" -elif path == "7.0": - ffmpeg_path = "/usr/lib/ffmpeg/7.0/bin/ffmpeg" -elif path == "5.0": - ffmpeg_path = "/usr/lib/ffmpeg/5.0/bin/ffmpeg" +elif path in INCLUDED_FFMPEG_VERSIONS: + ffmpeg_path = f"/usr/lib/ffmpeg/{path}/bin/ffmpeg" else: ffmpeg_path = f"{path}/bin/ffmpeg" diff --git a/docker/rockchip/Dockerfile b/docker/rockchip/Dockerfile index 84a3cc442..e1b43c255 100644 --- a/docker/rockchip/Dockerfile +++ b/docker/rockchip/Dockerfile @@ -22,5 +22,6 @@ ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt 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/6.1-5/ffmpeg /usr/lib/btbn-ffmpeg/bin/ -ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffprobe /usr/lib/btbn-ffmpeg/bin/ +ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffmpeg /usr/lib/ffmpeg/6.0/bin/ +ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffprobe /usr/lib/ffmpeg/6.0/bin/ +ENV PATH="/usr/lib/ffmpeg/6.0/bin/:${PATH}" diff --git a/docker/rockchip/rk.mk b/docker/rockchip/rk.mk index 0d9bde16a..c8278f68b 100644 --- a/docker/rockchip/rk.mk +++ b/docker/rockchip/rk.mk @@ -1,10 +1,15 @@ BOARDS += rk local-rk: version - docker buildx bake --load --file=docker/rockchip/rk.hcl --set rk.tags=frigate:latest-rk rk + docker buildx bake --file=docker/rockchip/rk.hcl rk \ + --set rk.tags=frigate:latest-rk \ + --load build-rk: version - docker buildx bake --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk + docker buildx bake --file=docker/rockchip/rk.hcl rk \ + --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk push-rk: build-rk - docker buildx bake --push --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk \ No newline at end of file + docker buildx bake --file=docker/rockchip/rk.hcl rk \ + --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk \ + --push \ No newline at end of file diff --git a/docker/rocm/Dockerfile b/docker/rocm/Dockerfile index d13bcaead..a1d6ce832 100644 --- a/docker/rocm/Dockerfile +++ b/docker/rocm/Dockerfile @@ -23,11 +23,11 @@ COPY docker/rocm/rocm-pin-600 /etc/apt/preferences.d/ RUN apt-get update -RUN apt-get -y install --no-install-recommends migraphx +RUN apt-get -y install --no-install-recommends migraphx hipfft roctracer RUN apt-get -y install --no-install-recommends migraphx-dev RUN mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib -RUN cd /opt/rocm-$ROCM/lib && cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/ +RUN cd /opt/rocm-$ROCM/lib && cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* libroctracer*.so* librocfft*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/ RUN cd /opt/rocm-dist/opt/ && ln -s rocm-$ROCM rocm RUN mkdir -p /opt/rocm-dist/etc/ld.so.conf.d/ @@ -69,7 +69,11 @@ RUN apt-get -y install libnuma1 WORKDIR /opt/frigate/ COPY --from=rootfs / / -COPY docker/rocm/rootfs/ / + +COPY docker/rocm/requirements-wheels-rocm.txt /requirements.txt +RUN python3 -m pip install --upgrade pip \ + && pip3 uninstall -y onnxruntime-openvino \ + && pip3 install -r /requirements.txt ####################################################################### FROM scratch AS rocm-dist @@ -101,6 +105,3 @@ ENV HSA_OVERRIDE_GFX_VERSION=$HSA_OVERRIDE_GFX_VERSION ####################################################################### FROM rocm-prelim-hsa-override$HSA_OVERRIDE as rocm-deps -# Request yolov8 download at startup -ENV DOWNLOAD_YOLOV8=1 - diff --git a/docker/rocm/requirements-wheels-rocm.txt b/docker/rocm/requirements-wheels-rocm.txt new file mode 100644 index 000000000..89d0e6096 --- /dev/null +++ b/docker/rocm/requirements-wheels-rocm.txt @@ -0,0 +1 @@ +onnxruntime-rocm @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v1.0.0/onnxruntime_rocm-1.17.3-cp39-cp39-linux_x86_64.whl \ No newline at end of file diff --git a/docker/rocm/rocm.mk b/docker/rocm/rocm.mk index 2d3d034ee..c92a458f5 100644 --- a/docker/rocm/rocm.mk +++ b/docker/rocm/rocm.mk @@ -4,14 +4,50 @@ BOARDS += rocm ROCM_CHIPSETS:=gfx900:9.0.0 gfx1030:10.3.0 gfx1100:11.0.0 local-rocm: version - $(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --load --file=docker/rocm/rocm.hcl --set rocm.tags=frigate:latest-rocm-$(word 1,$(subst :, ,$(chipset))) rocm;) - unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --load --file=docker/rocm/rocm.hcl --set rocm.tags=frigate:latest-rocm rocm + $(foreach chipset,$(ROCM_CHIPSETS), \ + AMDGPU=$(word 1,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE=1 \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=frigate:latest-rocm-$(word 1,$(subst :, ,$(chipset))) \ + --load \ + &&) true + + unset HSA_OVERRIDE_GFX_VERSION && \ + HSA_OVERRIDE=0 \ + AMDGPU=gfx \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=frigate:latest-rocm \ + --load build-rocm: version - $(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) rocm;) - unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm rocm + $(foreach chipset,$(ROCM_CHIPSETS), \ + AMDGPU=$(word 1,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE=1 \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) \ + &&) true + + unset HSA_OVERRIDE_GFX_VERSION && \ + HSA_OVERRIDE=0 \ + AMDGPU=gfx \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm push-rocm: build-rocm - $(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --push --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) rocm;) - unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --push --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm rocm + $(foreach chipset,$(ROCM_CHIPSETS), \ + AMDGPU=$(word 1,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \ + HSA_OVERRIDE=1 \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) \ + --push \ + &&) true + unset HSA_OVERRIDE_GFX_VERSION && \ + HSA_OVERRIDE=0 \ + AMDGPU=gfx \ + docker buildx bake --file=docker/rocm/rocm.hcl rocm \ + --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm \ + --push diff --git a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/dependencies.d/download-models b/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/dependencies.d/download-models deleted file mode 100644 index e69de29bb..000000000 diff --git a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/run b/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/run deleted file mode 100755 index f7b084ad7..000000000 --- a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/run +++ /dev/null @@ -1,20 +0,0 @@ -#!/command/with-contenv bash -# shellcheck shell=bash -# Compile YoloV8 ONNX files into ROCm MIGraphX files - -OVERRIDE=$(cd /opt/frigate && python3 -c 'import frigate.detectors.plugins.rocm as rocm; print(rocm.auto_override_gfx_version())') - -if ! test -z "$OVERRIDE"; then - echo "Using HSA_OVERRIDE_GFX_VERSION=${OVERRIDE}" - export HSA_OVERRIDE_GFX_VERSION=$OVERRIDE -fi - -for onnx in /config/model_cache/yolov8/*.onnx -do - mxr="${onnx%.onnx}.mxr" - if ! test -f $mxr; then - echo "processing $onnx into $mxr" - /opt/rocm/bin/migraphx-driver compile $onnx --optimize --gpu --enable-offload-copy --binary -o $mxr - fi -done - diff --git a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/type b/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/type deleted file mode 100644 index bdd22a185..000000000 --- a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/type +++ /dev/null @@ -1 +0,0 @@ -oneshot diff --git a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/up b/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/up deleted file mode 100644 index 8fdcef491..000000000 --- a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/up +++ /dev/null @@ -1 +0,0 @@ -/etc/s6-overlay/s6-rc.d/compile-rocm-models/run diff --git a/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/compile-rocm-models b/docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/frigate/dependencies.d/compile-rocm-models deleted file mode 100644 index e69de29bb..000000000 diff --git a/docker/rpi/rpi.mk b/docker/rpi/rpi.mk index c1282b011..290b30c31 100644 --- a/docker/rpi/rpi.mk +++ b/docker/rpi/rpi.mk @@ -1,10 +1,15 @@ BOARDS += rpi local-rpi: version - docker buildx bake --load --file=docker/rpi/rpi.hcl --set rpi.tags=frigate:latest-rpi rpi + docker buildx bake --file=docker/rpi/rpi.hcl rpi \ + --set rpi.tags=frigate:latest-rpi \ + --load build-rpi: version - docker buildx bake --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi + docker buildx bake --file=docker/rpi/rpi.hcl rpi \ + --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi push-rpi: build-rpi - docker buildx bake --push --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi \ No newline at end of file + docker buildx bake --file=docker/rpi/rpi.hcl rpi \ + --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi \ + --push diff --git a/docker/tensorrt/Dockerfile.amd64 b/docker/tensorrt/Dockerfile.amd64 index 075726eda..3dcb42658 100644 --- a/docker/tensorrt/Dockerfile.amd64 +++ b/docker/tensorrt/Dockerfile.amd64 @@ -12,12 +12,28 @@ ARG TARGETARCH COPY docker/tensorrt/requirements-amd64.txt /requirements-tensorrt.txt RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt +# Build CuDNN +FROM wget AS cudnn-deps + +ARG COMPUTE_LEVEL + +RUN apt-get update \ + && apt-get install -y git build-essential + +RUN wget https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.1-1_all.deb \ +&& dpkg -i cuda-keyring_1.1-1_all.deb \ +&& apt-get update \ +&& apt-get -y install cuda-toolkit \ +&& rm -rf /var/lib/apt/lists/* + 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 +COPY --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda +ENV LD_LIBRARY_PATH=/usr/local/lib/python3.9/dist-packages/tensorrt:/usr/local/cuda/lib64:/usr/local/lib/python3.9/dist-packages/nvidia/cufft/lib WORKDIR /opt/frigate/ COPY --from=rootfs / / @@ -26,6 +42,7 @@ 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 --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda 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 \ diff --git a/docker/tensorrt/requirements-amd64.txt b/docker/tensorrt/requirements-amd64.txt index 214202e43..b5ad4fcbd 100644 --- a/docker/tensorrt/requirements-amd64.txt +++ b/docker/tensorrt/requirements-amd64.txt @@ -8,5 +8,7 @@ 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' +nvidia-cufft-cu11==10.*; platform_machine == 'x86_64' onnx==1.14.0; platform_machine == 'x86_64' -protobuf==3.20.3; platform_machine == 'x86_64' \ No newline at end of file +onnxruntime-gpu==1.17.*; platform_machine == 'x86_64' +protobuf==3.20.3; platform_machine == 'x86_64' diff --git a/docker/tensorrt/trt.mk b/docker/tensorrt/trt.mk index ad2425c81..455e1ee11 100644 --- a/docker/tensorrt/trt.mk +++ b/docker/tensorrt/trt.mk @@ -7,20 +7,35 @@ JETPACK4_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK4_BASE) SLIM_BASE=$(JETPACK4_BAS JETPACK5_ARGS := ARCH=arm64 BASE_IMAGE=$(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 + $(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=frigate:latest-tensorrt \ + --load local-trt-jp4: version - $(JETPACK4_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp4 tensorrt + $(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=frigate:latest-tensorrt-jp4 \ + --load local-trt-jp5: version - $(JETPACK5_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp5 tensorrt + $(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=frigate:latest-tensorrt-jp5 \ + --load 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 + $(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt + $(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 + $(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 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 + $(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt \ + --push + $(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 \ + --push + $(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \ + --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 \ + --push diff --git a/docs/docs/configuration/genai.md b/docs/docs/configuration/genai.md index 623cf588c..26954effe 100644 --- a/docs/docs/configuration/genai.md +++ b/docs/docs/configuration/genai.md @@ -124,13 +124,25 @@ genai: model: llava prompt: "Describe the {label} in these images from the {camera} security camera." object_prompts: - person: "Describe the main person in these images (gender, age, clothing, activity, etc). Do not include where the activity is occurring (sidewalk, concrete, driveway, etc). If delivering a package, include the company the package is from." + person: "Describe the main person in these images (gender, age, clothing, activity, etc). Do not include where the activity is occurring (sidewalk, concrete, driveway, etc)." car: "Label the primary vehicle in these images with just the name of the company if it is a delivery vehicle, or the color make and model." ``` +Prompts can also be overriden at the camera level to provide a more detailed prompt to the model about your specific camera, if you desire. + +```yaml +cameras: + front_door: + genai: + prompt: "Describe the {label} in these images from the {camera} security camera at the front door of a house, aimed outward toward the street." + object_prompts: + person: "Describe the main person in these images (gender, age, clothing, activity, etc). Do not include where the activity is occurring (sidewalk, concrete, driveway, etc). If delivering a package, include the company the package is from." + cat: "Describe the cat in these images (color, size, tail). Indicate whether or not the cat is by the flower pots. If the cat is chasing a mouse, make up a name for the mouse." +``` + ### Experiment with prompts -Providers also has a public facing chat interface for their models. Download a couple different thumbnails or snapshots from Frigate and try new things in the playground to get descriptions to your liking before updating the prompt in Frigate. +Many providers also have a public facing chat interface for their models. Download a couple of different thumbnails or snapshots from Frigate and try new things in the playground to get descriptions to your liking before updating the prompt in Frigate. - OpenAI - [ChatGPT](https://chatgpt.com) - Gemini - [Google AI Studio](https://aistudio.google.com) diff --git a/docs/docs/configuration/hardware_acceleration.md b/docs/docs/configuration/hardware_acceleration.md index 0b62a0f08..867d555d8 100644 --- a/docs/docs/configuration/hardware_acceleration.md +++ b/docs/docs/configuration/hardware_acceleration.md @@ -65,24 +65,33 @@ Or map in all the `/dev/video*` devices. ## Intel-based CPUs +**Recommended hwaccel Preset** + +| CPU Generation | Intel Driver | Recommended Preset | Notes | +| -------------- | ------------ | ------------------ | ----------------------------------- | +| gen1 - gen7 | i965 | preset-vaapi | qsv is not supported | +| gen8 - gen12 | iHD | preset-vaapi | preset-intel-qsv-* can also be used | +| gen13+ | iHD / Xe | preset-intel-qsv-* | | +| Intel Arc GPU | iHD / Xe | preset-intel-qsv-* | | + +:::note + +The default driver is `iHD`. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `frigate.yaml` for HA OS users](advanced.md#environment_vars). + +See [The Intel Docs](https://www.intel.com/content/www/us/en/support/articles/000005505/processors.html to figure out what generation your CPU is.) + +::: + ### Via VAAPI -VAAPI supports automatic profile selection so it will work automatically with both H.264 and H.265 streams. VAAPI is recommended for all generations of Intel-based CPUs. +VAAPI supports automatic profile selection so it will work automatically with both H.264 and H.265 streams. ```yaml ffmpeg: hwaccel_args: preset-vaapi ``` -:::note - -With some of the processors, like the J4125, the default driver `iHD` doesn't seem to work correctly for hardware acceleration. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `frigate.yaml` for HA OS users](advanced.md#environment_vars). - -::: - -### Via Quicksync (>=10th Generation only) - -If VAAPI does not work for you, you can try QSV if your processor supports it. QSV must be set specifically based on the video encoding of the stream. +### Via Quicksync #### H.264 streams diff --git a/docs/docs/configuration/object_detectors.md b/docs/docs/configuration/object_detectors.md index 154c9907f..174d7a572 100644 --- a/docs/docs/configuration/object_detectors.md +++ b/docs/docs/configuration/object_detectors.md @@ -3,6 +3,29 @@ id: object_detectors title: Object Detectors --- +# Supported Hardware + +Frigate supports multiple different detectors that work on different types of hardware: + +**Most Hardware** +- [Coral EdgeTPU](#edge-tpu-detector): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices. +- [Hailo](#hailo-8l): The Hailo8 AI Acceleration module is available in m.2 format with a HAT for RPi devices, offering a wide range of compatibility with devices. + +**AMD** +- [ROCm](#amdrocm-gpu-detector): ROCm can run on AMD Discrete GPUs to provide efficient object detection. +- [ONNX](#onnx): ROCm will automatically be detected and used as a detector in the `-rocm` Frigate image when a supported ONNX model is configured. + +**Intel** +- [OpenVino](#openvino-detector): OpenVino can run on Intel Arc GPUs, Intel integrated GPUs, and Intel CPUs to provide efficient object detection. +- [ONNX](#onnx): OpenVINO will automatically be detected and used as a detector in the default Frigate image when a supported ONNX model is configured. + +**Nvidia** +- [TensortRT](#nvidia-tensorrt-detector): TensorRT can run on Nvidia GPUs, using one of many default models. +- [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt` Frigate image when a supported ONNX model is configured. + +**Rockchip** +- [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs. + # Officially Supported Detectors Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `openvino`, `tensorrt`, `rknn`, and `hailo8l`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras. @@ -122,6 +145,22 @@ The OpenVINO device to be used is specified using the `"device"` attribute accor OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will also run on AMD CPUs despite having no official support for it. A supported Intel platform is required to use the `GPU` device with OpenVINO. For detailed system requirements, see [OpenVINO System Requirements](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino/system-requirements.html) +:::tip + +When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be: + +```yaml +detectors: + ov_0: + type: openvino + device: GPU + ov_1: + type: openvino + device: GPU +``` + +::: + ### Supported Models #### SSDLite MobileNet v2 @@ -278,6 +317,173 @@ model: height: 320 ``` +## AMD/ROCm GPU detector + +### Setup + +The `rocm` detector supports running YOLO-NAS models on AMD GPUs. Use a frigate docker image with `-rocm` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-rocm`. + +### Docker settings for GPU access + +ROCm needs access to the `/dev/kfd` and `/dev/dri` devices. When docker or frigate is not run under root then also `video` (and possibly `render` and `ssl/_ssl`) groups should be added. + +When running docker directly the following flags should be added for device access: + +```bash +$ docker run --device=/dev/kfd --device=/dev/dri \ + ... +``` + +When using docker compose: + +```yaml +services: + frigate: +--- +devices: + - /dev/dri + - /dev/kfd +``` + +For reference on recommended settings see [running ROCm/pytorch in Docker](https://rocm.docs.amd.com/projects/install-on-linux/en/develop/how-to/3rd-party/pytorch-install.html#using-docker-with-pytorch-pre-installed). + +### Docker settings for overriding the GPU chipset + +Your GPU might work just fine without any special configuration but in many cases they need manual settings. AMD/ROCm software stack comes with a limited set of GPU drivers and for newer or missing models you will have to override the chipset version to an older/generic version to get things working. + +Also AMD/ROCm does not "officially" support integrated GPUs. It still does work with most of them just fine but requires special settings. One has to configure the `HSA_OVERRIDE_GFX_VERSION` environment variable. See the [ROCm bug report](https://github.com/ROCm/ROCm/issues/1743) for context and examples. + +For the rocm frigate build there is some automatic detection: + +- gfx90c -> 9.0.0 +- gfx1031 -> 10.3.0 +- gfx1103 -> 11.0.0 + +If you have something else you might need to override the `HSA_OVERRIDE_GFX_VERSION` at Docker launch. Suppose the version you want is `9.0.0`, then you should configure it from command line as: + +```bash +$ docker run -e HSA_OVERRIDE_GFX_VERSION=9.0.0 \ + ... +``` + +When using docker compose: + +```yaml +services: + frigate: +... +environment: + HSA_OVERRIDE_GFX_VERSION: "9.0.0" +``` + +Figuring out what version you need can be complicated as you can't tell the chipset name and driver from the AMD brand name. + +- first make sure that rocm environment is running properly by running `/opt/rocm/bin/rocminfo` in the frigate container -- it should list both the CPU and the GPU with their properties +- find the chipset version you have (gfxNNN) from the output of the `rocminfo` (see below) +- use a search engine to query what `HSA_OVERRIDE_GFX_VERSION` you need for the given gfx name ("gfxNNN ROCm HSA_OVERRIDE_GFX_VERSION") +- override the `HSA_OVERRIDE_GFX_VERSION` with relevant value +- if things are not working check the frigate docker logs + +#### Figuring out if AMD/ROCm is working and found your GPU + +```bash +$ docker exec -it frigate /opt/rocm/bin/rocminfo +``` + +#### Figuring out your AMD GPU chipset version: + +We unset the `HSA_OVERRIDE_GFX_VERSION` to prevent an existing override from messing up the result: + +```bash +$ docker exec -it frigate /bin/bash -c '(unset HSA_OVERRIDE_GFX_VERSION && /opt/rocm/bin/rocminfo |grep gfx)' +``` + +### Supported Models + +There is no default model provided, the following formats are supported: + +#### YOLO-NAS + +[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb). + +:::warning + +The pre-trained YOLO-NAS weights from DeciAI are subject to their license and can't be used commercially. For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html + +::: + +The input image size in this notebook is set to 320x320. This results in lower CPU usage and faster inference times without impacting performance in most cases due to the way Frigate crops video frames to areas of interest before running detection. The notebook and config can be updated to 640x640 if desired. + +After placing the downloaded onnx model in your config folder, you can use the following configuration: + +```yaml +detectors: + onnx: + type: rocm + +model: + model_type: yolonas + width: 320 # <--- should match whatever was set in notebook + height: 320 # <--- should match whatever was set in notebook + input_pixel_format: bgr + path: /config/yolo_nas_s.onnx + labelmap_path: /labelmap/coco-80.txt +``` + +Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects. + +## ONNX + +ONNX is an open format for building machine learning models, Frigate supports running ONNX models on CPU, OpenVINO, and TensorRT. On startup Frigate will automatically try to use a GPU if one is available. + +:::tip + +When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be: + +```yaml +detectors: + onnx_0: + type: onnx + onnx_1: + type: onnx +``` + +::: + +### Supported Models + +There is no default model provided, the following formats are supported: + +#### YOLO-NAS + +[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb). + +:::warning + +The pre-trained YOLO-NAS weights from DeciAI are subject to their license and can't be used commercially. For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html + +::: + +The input image size in this notebook is set to 320x320. This results in lower CPU usage and faster inference times without impacting performance in most cases due to the way Frigate crops video frames to areas of interest before running detection. The notebook and config can be updated to 640x640 if desired. + +After placing the downloaded onnx model in your config folder, you can use the following configuration: + +```yaml +detectors: + onnx: + type: onnx + +model: + model_type: yolonas + width: 320 # <--- should match whatever was set in notebook + height: 320 # <--- should match whatever was set in notebook + input_pixel_format: bgr + path: /config/yolo_nas_s.onnx + labelmap_path: /labelmap/coco-80.txt +``` + +Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects. + ## Deepstack / CodeProject.AI Server Detector The Deepstack / CodeProject.AI Server detector for Frigate allows you to integrate Deepstack and CodeProject.AI object detection capabilities into Frigate. CodeProject.AI and DeepStack are open-source AI platforms that can be run on various devices such as the Raspberry Pi, Nvidia Jetson, and other compatible hardware. It is important to note that the integration is performed over the network, so the inference times may not be as fast as native Frigate detectors, but it still provides an efficient and reliable solution for object detection and tracking. @@ -389,7 +595,7 @@ $ cat /sys/kernel/debug/rknpu/load ## Hailo-8l -This detector is available if you are using the Raspberry Pi 5 with Hailo-8L AI Kit. This has not been tested using the Hailo-8L with other hardware. +This detector is available for use with Hailo-8 AI Acceleration Module. ### Configuration diff --git a/docs/docs/configuration/reference.md b/docs/docs/configuration/reference.md index 1ae0739e7..020e59979 100644 --- a/docs/docs/configuration/reference.md +++ b/docs/docs/configuration/reference.md @@ -504,7 +504,7 @@ semantic_search: # to Google or OpenAI's LLMs to generate descriptions. It can be overridden at # the camera level (enabled: False) to enhance privacy for indoor cameras. genai: - # Optional: Enable Google Gemini description generation (default: shown below) + # Optional: Enable AI description generation (default: shown below) enabled: False # Required if enabled: Provider must be one of ollama, gemini, or openai provider: ollama @@ -712,6 +712,18 @@ cameras: # By default the cameras are sorted alphabetically. order: 0 + # Optional: Configuration for AI generated tracked object descriptions + genai: + # Optional: Enable AI description generation (default: shown below) + enabled: False + # Optional: The default prompt for generating descriptions. Can use replacement + # variables like "label", "sub_label", "camera" to make more dynamic. (default: shown below) + prompt: "Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background." + # Optional: Object specific prompts to customize description results + # Format: {label}: {prompt} + object_prompts: + person: "My special person prompt." + # Optional ui: # Optional: Set a timezone to use in the UI (default: use browser local time) diff --git a/docs/docs/frigate/hardware.md b/docs/docs/frigate/hardware.md index 39fc4d84d..ef647e474 100644 --- a/docs/docs/frigate/hardware.md +++ b/docs/docs/frigate/hardware.md @@ -87,6 +87,10 @@ Inference speeds will vary greatly depending on the GPU and the model used. | Quadro P400 2GB | 20 - 25 ms | | Quadro P2000 | ~ 12 ms | +#### AMD GPUs + +With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many AMD GPUs. + ### Community Supported: #### Nvidia Jetson diff --git a/docs/package-lock.json b/docs/package-lock.json index 5ded270a9..e8eb75686 100644 --- a/docs/package-lock.json +++ b/docs/package-lock.json @@ -8,20 +8,20 @@ "name": "docs", "version": "0.0.0", "dependencies": { - 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"version": "1.0.0", - "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.0.0.tgz", - "integrity": "sha512-1fygroTLlHu66zi26VoTDv8yRgm0Fccecssto+MhsZ0D/DGW2sm8E8AjW7NU5VVTRt5GxbeZ5qBuJr+HyLYkjQ==" + "version": "1.1.0", + "resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.0.tgz", + "integrity": "sha512-TQ92mBOW0l3LeMeyLV6mzy/kWr8lkd/hp3mTg7wYK7zJhuBStmGMBG0BdeDZS/dZx1IukaX6Bk11zcln25o1Aw==", + "license": "ISC" }, "node_modules/picomatch": { "version": "2.3.1", @@ -12944,9 +13108,10 @@ } }, "node_modules/prism-react-renderer": { - "version": "2.3.1", - "resolved": "https://registry.npmjs.org/prism-react-renderer/-/prism-react-renderer-2.3.1.tgz", - "integrity": "sha512-Rdf+HzBLR7KYjzpJ1rSoxT9ioO85nZngQEoFIhL07XhtJHlCU3SOz0GJ6+qvMyQe0Se+BV3qpe6Yd/NmQF5Juw==", + "version": "2.4.0", + "resolved": "https://registry.npmjs.org/prism-react-renderer/-/prism-react-renderer-2.4.0.tgz", + "integrity": "sha512-327BsVCD/unU4CNLZTWVHyUHKnsqcvj2qbPlQ8MiBE2eq2rgctjigPA1Gp9HLF83kZ20zNN6jgizHJeEsyFYOw==", + "license": "MIT", "dependencies": { "@types/prismjs": "^1.26.0", "clsx": "^2.0.0" @@ -13397,9 +13562,9 @@ "integrity": "sha512-24e6ynE2H+OKt4kqsOvNd8kBpV65zoxbA4BVsEOB3ARVWQki/DHzaUoC5KuON/BiccDaCCTZBuOcfZs70kR8bQ==" }, "node_modules/react-json-view-lite": { - 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"version": "2.14.0", - "resolved": "https://registry.npmjs.org/search-insights/-/search-insights-2.14.0.tgz", - "integrity": "sha512-OLN6MsPMCghDOqlCtsIsYgtsC0pnwVTyT9Mu6A3ewOj1DxvzZF6COrn2g86E/c05xbktB0XN04m/t1Z+n+fTGw==", + "version": "2.17.2", + "resolved": "https://registry.npmjs.org/search-insights/-/search-insights-2.17.2.tgz", + "integrity": "sha512-zFNpOpUO+tY2D85KrxJ+aqwnIfdEGi06UH2+xEb+Bp9Mwznmauqc9djbnBibJO5mpfUPPa8st6Sx65+vbeO45g==", "license": "MIT", "peer": true }, @@ -15316,9 +15481,9 @@ } }, "node_modules/update-browserslist-db": { - "version": "1.0.13", - "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.0.13.tgz", - "integrity": "sha512-xebP81SNcPuNpPP3uzeW1NYXxI3rxyJzF3pD6sH4jE7o/IX+WtSpwnVU+qIsDPyk0d3hmFQ7mjqc6AtV604hbg==", + "version": "1.1.0", + "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.1.0.tgz", + "integrity": "sha512-EdRAaAyk2cUE1wOf2DkEhzxqOQvFOoRJFNS6NeyJ01Gp2beMRpBAINjM2iDXE3KCuKhwnvHIQCJm6ThL2Z+HzQ==", "funding": [ { "type": "opencollective", @@ -15333,9 +15498,10 @@ "url": "https://github.com/sponsors/ai" } ], + "license": "MIT", "dependencies": { - "escalade": "^3.1.1", - "picocolors": "^1.0.0" + "escalade": "^3.1.2", + "picocolors": "^1.0.1" }, "bin": { "update-browserslist-db": "cli.js" @@ -15609,9 +15775,9 @@ } }, "node_modules/vfile-location": { - "version": "5.0.2", - "resolved": "https://registry.npmjs.org/vfile-location/-/vfile-location-5.0.2.tgz", - "integrity": "sha512-NXPYyxyBSH7zB5U6+3uDdd6Nybz6o6/od9rk8bp9H8GR3L+cm/fC0uUTbqBmUTnMCUDslAGBOIKNfvvb+gGlDg==", + "version": "5.0.3", + "resolved": "https://registry.npmjs.org/vfile-location/-/vfile-location-5.0.3.tgz", + "integrity": "sha512-5yXvWDEgqeiYiBe1lbxYF7UMAIm/IcopxMHrMQDq3nvKcjPKIhZklUKL+AE7J7uApI4kwe2snsK+eI6UTj9EHg==", "license": "MIT", "dependencies": { "@types/unist": "^3.0.0", diff --git a/docs/package.json b/docs/package.json index d31b58671..e41023c66 100644 --- a/docs/package.json +++ b/docs/package.json @@ -14,15 +14,15 @@ "write-heading-ids": "docusaurus write-heading-ids" }, "dependencies": { - "@docusaurus/core": "^3.4.0", - "@docusaurus/preset-classic": "^3.4.0", - "@docusaurus/theme-mermaid": "^3.4.0", + "@docusaurus/core": "^3.5.2", + "@docusaurus/preset-classic": "^3.5.2", + "@docusaurus/theme-mermaid": "^3.5.2", "@mdx-js/react": "^3.0.0", "clsx": "^2.0.0", - "prism-react-renderer": "^2.1.0", + "prism-react-renderer": "^2.4.0", "raw-loader": "^4.0.2", - "react": "^18.2.0", - "react-dom": "^18.2.0" + "react": "^18.3.1", + "react-dom": "^18.3.1" }, "browserslist": { "production": [ @@ -39,7 +39,7 @@ "devDependencies": { "@docusaurus/module-type-aliases": "^3.4.0", "@docusaurus/types": "^3.4.0", - "@types/react": "^18.2.79" + "@types/react": "^18.3.7" }, "engines": { "node": ">=18.0" diff --git a/frigate/__main__.py b/frigate/__main__.py index 844206908..208af9e23 100644 --- a/frigate/__main__.py +++ b/frigate/__main__.py @@ -1,17 +1,28 @@ import faulthandler +import logging import threading from flask import cli from frigate.app import FrigateApp -faulthandler.enable() -threading.current_thread().name = "frigate" +def main() -> None: + faulthandler.enable() + + # Clear all existing handlers. + logging.basicConfig( + level=logging.INFO, + handlers=[], + force=True, + ) + + threading.current_thread().name = "frigate" + cli.show_server_banner = lambda *x: None + + # Run the main application. + FrigateApp().start() -cli.show_server_banner = lambda *x: None if __name__ == "__main__": - frigate_app = FrigateApp() - - frigate_app.start() + main() diff --git a/frigate/api/event.py b/frigate/api/event.py index fd3c4ad0b..a49b8942d 100644 --- a/frigate/api/event.py +++ b/frigate/api/event.py @@ -353,7 +353,10 @@ def events_search(): after = request.args.get("after", type=float) before = request.args.get("before", type=float) - if not query: + # for similarity search + event_id = request.args.get("event_id", type=str) + + if not query and not event_id: return make_response( jsonify( { @@ -432,7 +435,7 @@ def events_search(): if search_type == "similarity": # Grab the ids of events that match the thumbnail image embeddings try: - search_event: Event = Event.get(Event.id == query) + search_event: Event = Event.get(Event.id == event_id) except DoesNotExist: return make_response( jsonify( diff --git a/frigate/api/export.py b/frigate/api/export.py index 0993a3a87..e17416425 100644 --- a/frigate/api/export.py +++ b/frigate/api/export.py @@ -149,9 +149,9 @@ def export_delete(id: str): try: if process.name() != "ffmpeg": continue - flist = process.open_files() - if flist: - for nt in flist: + file_list = process.open_files() + if file_list: + for nt in file_list: if nt.path.startswith(EXPORT_DIR): files_in_use.append(nt.path.split("/")[-1]) except psutil.Error: diff --git a/frigate/app.py b/frigate/app.py index 342624d36..08dc31746 100644 --- a/frigate/app.py +++ b/frigate/app.py @@ -46,7 +46,7 @@ from frigate.events.audio import listen_to_audio from frigate.events.cleanup import EventCleanup from frigate.events.external import ExternalEventProcessor from frigate.events.maintainer import EventProcessor -from frigate.log import log_process, root_configurer +from frigate.log import log_thread from frigate.models import ( Event, Export, @@ -116,15 +116,6 @@ class FrigateApp: else: logger.debug(f"Skipping directory: {d}") - def init_logger(self) -> None: - self.log_process = mp.Process( - target=log_process, args=(self.log_queue,), name="log_process" - ) - self.log_process.daemon = True - self.log_process.start() - self.processes["logger"] = self.log_process.pid or 0 - root_configurer(self.log_queue) - def init_config(self) -> None: config_file = os.environ.get("CONFIG_FILE", "/config/config.yml") @@ -679,6 +670,7 @@ class FrigateApp: logger.info("********************************************************") logger.info("********************************************************") + @log_thread() def start(self) -> None: parser = argparse.ArgumentParser( prog="Frigate", @@ -687,7 +679,6 @@ class FrigateApp: parser.add_argument("--validate-config", action="store_true") args = parser.parse_args() - self.init_logger() logger.info(f"Starting Frigate ({VERSION})") try: @@ -714,13 +705,11 @@ class FrigateApp: print("*************************************************************") print("*** End Config Validation Errors ***") print("*************************************************************") - self.log_process.terminate() sys.exit(1) if args.validate_config: print("*************************************************************") print("*** Your config file is valid. ***") print("*************************************************************") - self.log_process.terminate() sys.exit(0) self.set_environment_vars() self.set_log_levels() @@ -737,7 +726,6 @@ class FrigateApp: self.init_dispatcher() except Exception as e: print(e) - self.log_process.terminate() sys.exit(1) self.start_detectors() self.start_video_output_processor() @@ -866,7 +854,4 @@ class FrigateApp: shm.close() shm.unlink() - self.log_process.terminate() - self.log_process.join() - os._exit(os.EX_OK) diff --git a/frigate/comms/webpush.py b/frigate/comms/webpush.py index 0cb75f332..602f8d11e 100644 --- a/frigate/comms/webpush.py +++ b/frigate/comms/webpush.py @@ -106,10 +106,10 @@ class WebPushClient(Communicator): # type: ignore[misc] def publish(self, topic: str, payload: Any, retain: bool = False) -> None: """Wrapper for publishing when client is in valid state.""" # check for updated notification config - _, updated_notif_config = self.config_subscriber.check_for_update() + _, updated_notification_config = self.config_subscriber.check_for_update() - if updated_notif_config: - self.config.notifications = updated_notif_config + if updated_notification_config: + self.config.notifications = updated_notification_config if not self.config.notifications.enabled: return diff --git a/frigate/config.py b/frigate/config.py index 7e557f0a3..b1af9c51b 100644 --- a/frigate/config.py +++ b/frigate/config.py @@ -3,6 +3,7 @@ from __future__ import annotations import json import logging import os +import shutil from enum import Enum from pathlib import Path from typing import Any, Dict, List, Optional, Tuple, Union @@ -25,7 +26,9 @@ from frigate.const import ( CACHE_DIR, CACHE_SEGMENT_FORMAT, DEFAULT_DB_PATH, + DEFAULT_FFMPEG_VERSION, FREQUENCY_STATS_POINTS, + INCLUDED_FFMPEG_VERSIONS, MAX_PRE_CAPTURE, REGEX_CAMERA_NAME, YAML_EXT, @@ -762,8 +765,14 @@ class GenAIConfig(FrigateBaseModel): object_prompts: Dict[str, str] = Field(default={}, title="Object specific prompts.") -class GenAICameraConfig(FrigateBaseModel): +# uses BaseModel because some global attributes are not available at the camera level +class GenAICameraConfig(BaseModel): enabled: bool = Field(default=False, title="Enable GenAI for camera.") + prompt: str = Field( + default="Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background.", + title="Default caption prompt.", + ) + object_prompts: Dict[str, str] = Field(default={}, title="Object specific prompts.") class AudioConfig(FrigateBaseModel): @@ -888,28 +897,24 @@ class FfmpegConfig(FrigateBaseModel): @property def ffmpeg_path(self) -> str: if self.path == "default": - if int(os.getenv("LIBAVFORMAT_VERSION_MAJOR", "59")) >= 59: - return "/usr/lib/ffmpeg/7.0/bin/ffmpeg" + if shutil.which("ffmpeg") is None: + return f"/usr/lib/ffmpeg/{DEFAULT_FFMPEG_VERSION}/bin/ffmpeg" else: return "ffmpeg" - elif self.path == "7.0": - return "/usr/lib/ffmpeg/7.0/bin/ffmpeg" - elif self.path == "5.0": - return "/usr/lib/ffmpeg/5.0/bin/ffmpeg" + elif self.path in INCLUDED_FFMPEG_VERSIONS: + return f"/usr/lib/ffmpeg/{self.path}/bin/ffmpeg" else: return f"{self.path}/bin/ffmpeg" @property def ffprobe_path(self) -> str: if self.path == "default": - if int(os.getenv("LIBAVFORMAT_VERSION_MAJOR", "59")) >= 59: - return "/usr/lib/ffmpeg/7.0/bin/ffprobe" + if shutil.which("ffprobe") is None: + return f"/usr/lib/ffmpeg/{DEFAULT_FFMPEG_VERSION}/bin/ffprobe" else: return "ffprobe" - elif self.path == "7.0": - return "/usr/lib/ffmpeg/7.0/bin/ffprobe" - elif self.path == "5.0": - return "/usr/lib/ffmpeg/5.0/bin/ffprobe" + elif self.path in INCLUDED_FFMPEG_VERSIONS: + return f"/usr/lib/ffmpeg/{self.path}/bin/ffprobe" else: return f"{self.path}/bin/ffprobe" @@ -1187,7 +1192,7 @@ class CameraConfig(FrigateBaseModel): + ffmpeg_output_args ) - # if there arent any outputs enabled for this input + # if there aren't any outputs enabled for this input if len(ffmpeg_output_args) == 0: return None @@ -1519,7 +1524,7 @@ class FrigateConfig(FrigateBaseModel): "live": ..., "objects": ..., "review": ..., - "genai": {"enabled"}, + "genai": ..., "motion": ..., "detect": ..., "ffmpeg": ..., diff --git a/frigate/const.py b/frigate/const.py index a6e945897..a0066774b 100644 --- a/frigate/const.py +++ b/frigate/const.py @@ -12,7 +12,7 @@ FRIGATE_LOCALHOST = "http://127.0.0.1:5000" PLUS_ENV_VAR = "PLUS_API_KEY" PLUS_API_HOST = "https://api.frigate.video" -# Attribute & Object Consts +# Attribute & Object constants ATTRIBUTE_LABEL_MAP = { "person": ["face", "amazon"], @@ -31,7 +31,7 @@ LABEL_NMS_MAP = { } LABEL_NMS_DEFAULT = 0.4 -# Audio Consts +# Audio constants AUDIO_DURATION = 0.975 AUDIO_FORMAT = "s16le" @@ -39,17 +39,19 @@ AUDIO_MAX_BIT_RANGE = 32768.0 AUDIO_SAMPLE_RATE = 16000 AUDIO_MIN_CONFIDENCE = 0.5 -# DB Consts +# DB constants MAX_WAL_SIZE = 10 # MB -# Ffmpeg Presets +# Ffmpeg constants +DEFAULT_FFMPEG_VERSION = "7.0" +INCLUDED_FFMPEG_VERSIONS = ["7.0", "5.0"] FFMPEG_HWACCEL_NVIDIA = "preset-nvidia" FFMPEG_HWACCEL_VAAPI = "preset-vaapi" FFMPEG_HWACCEL_VULKAN = "preset-vulkan" -# Regex Consts +# Regex constants REGEX_CAMERA_NAME = r"^[a-zA-Z0-9_-]+$" REGEX_RTSP_CAMERA_USER_PASS = r":\/\/[a-zA-Z0-9_-]+:[\S]+@" diff --git a/frigate/detectors/plugins/hailo8l.py b/frigate/detectors/plugins/hailo8l.py index a157e240d..b66d78bd6 100644 --- a/frigate/detectors/plugins/hailo8l.py +++ b/frigate/detectors/plugins/hailo8l.py @@ -24,7 +24,6 @@ from typing_extensions import Literal from frigate.detectors.detection_api import DetectionApi from frigate.detectors.detector_config import BaseDetectorConfig -from frigate.detectors.util import preprocess # Assuming this function is available # Set up logging logger = logging.getLogger(__name__) @@ -83,11 +82,11 @@ class HailoDetector(DetectionApi): self.network_group_params = self.network_group.create_params() # Create input and output virtual stream parameters - self.input_vstreams_params = InputVStreamParams.make( + self.input_vstream_params = InputVStreamParams.make( self.network_group, format_type=self.hef.get_input_vstream_infos()[0].format.type, ) - self.output_vstreams_params = OutputVStreamParams.make( + self.output_vstream_params = OutputVStreamParams.make( self.network_group, format_type=getattr(FormatType, output_type) ) @@ -146,24 +145,16 @@ class HailoDetector(DetectionApi): f"[detect_raw] Converted tensor_input to numpy array: shape {tensor_input.shape}" ) - # Preprocess the tensor input using Frigate's preprocess function - processed_tensor = preprocess( - tensor_input, (1, self.h8l_model_height, self.h8l_model_width, 3), np.uint8 - ) + input_data = tensor_input logger.debug( - f"[detect_raw] Tensor data and shape after preprocessing: {processed_tensor} {processed_tensor.shape}" - ) - - input_data = processed_tensor - logger.debug( - f"[detect_raw] Input data for inference shape: {processed_tensor.shape}, dtype: {processed_tensor.dtype}" + f"[detect_raw] Input data for inference shape: {tensor_input.shape}, dtype: {tensor_input.dtype}" ) try: with InferVStreams( self.network_group, - self.input_vstreams_params, - self.output_vstreams_params, + self.input_vstream_params, + self.output_vstream_params, ) as infer_pipeline: input_dict = {} if isinstance(input_data, dict): diff --git a/frigate/detectors/plugins/onnx.py b/frigate/detectors/plugins/onnx.py index 6b124f6c9..f690a232f 100644 --- a/frigate/detectors/plugins/onnx.py +++ b/frigate/detectors/plugins/onnx.py @@ -1,11 +1,15 @@ import logging +import os import numpy as np +from pydantic import Field from typing_extensions import Literal from frigate.detectors.detection_api import DetectionApi -from frigate.detectors.detector_config import BaseDetectorConfig -from frigate.detectors.util import preprocess +from frigate.detectors.detector_config import ( + BaseDetectorConfig, + ModelTypeEnum, +) logger = logging.getLogger(__name__) @@ -14,6 +18,7 @@ DETECTOR_KEY = "onnx" class ONNXDetectorConfig(BaseDetectorConfig): type: Literal[DETECTOR_KEY] + device: str = Field(default="AUTO", title="Device Type") class ONNXDetector(DetectionApi): @@ -21,7 +26,7 @@ class ONNXDetector(DetectionApi): def __init__(self, detector_config: ONNXDetectorConfig): try: - import onnxruntime + import onnxruntime as ort logger.info("ONNX: loaded onnxruntime module") except ModuleNotFoundError: @@ -32,16 +37,79 @@ class ONNXDetector(DetectionApi): path = detector_config.model.path logger.info(f"ONNX: loading {detector_config.model.path}") - self.model = onnxruntime.InferenceSession(path) + + providers = ( + ["CPUExecutionProvider"] + if detector_config.device == "CPU" + else ort.get_available_providers() + ) + options = [] + + for provider in providers: + if provider == "TensorrtExecutionProvider": + os.makedirs( + "/config/model_cache/tensorrt/ort/trt-engines", exist_ok=True + ) + options.append( + { + "trt_timing_cache_enable": True, + "trt_timing_cache_path": "/config/model_cache/tensorrt/ort", + "trt_engine_cache_enable": True, + "trt_dump_ep_context_model": True, + "trt_engine_cache_path": "/config/model_cache/tensorrt/ort/trt-engines", + "trt_ep_context_file_path": "/config/model_cache/tensorrt/ort", + } + ) + elif provider == "OpenVINOExecutionProvider": + os.makedirs("/config/model_cache/openvino/ort", exist_ok=True) + options.append( + { + "cache_dir": "/config/model_cache/openvino/ort", + "device_type": detector_config.device, + } + ) + else: + options.append({}) + + self.model = ort.InferenceSession( + path, providers=providers, provider_options=options + ) + + self.h = detector_config.model.height + self.w = detector_config.model.width + self.onnx_model_type = detector_config.model.model_type + self.onnx_model_px = detector_config.model.input_pixel_format + self.onnx_model_shape = detector_config.model.input_tensor + path = detector_config.model.path + logger.info(f"ONNX: {path} loaded") def detect_raw(self, tensor_input): model_input_name = self.model.get_inputs()[0].name - model_input_shape = self.model.get_inputs()[0].shape - tensor_input = preprocess(tensor_input, model_input_shape, np.float32) - # ruff: noqa: F841 - tensor_output = self.model.run(None, {model_input_name: tensor_input})[0] + tensor_output = self.model.run(None, {model_input_name: tensor_input}) - raise Exception( - "No models are currently supported via onnx. See the docs for more info." - ) + if self.onnx_model_type == ModelTypeEnum.yolonas: + predictions = tensor_output[0] + + detections = np.zeros((20, 6), np.float32) + + for i, prediction in enumerate(predictions): + if i == 20: + break + (_, x_min, y_min, x_max, y_max, confidence, class_id) = prediction + # when running in GPU mode, empty predictions in the output have class_id of -1 + if class_id < 0: + break + detections[i] = [ + class_id, + confidence, + y_min / self.h, + x_min / self.w, + y_max / self.h, + x_max / self.w, + ] + return detections + else: + raise Exception( + f"{self.onnx_model_type} is currently not supported for rocm. See the docs for more info on supported models." + ) diff --git a/frigate/detectors/plugins/openvino.py b/frigate/detectors/plugins/openvino.py index a6b0a51cd..5dc998487 100644 --- a/frigate/detectors/plugins/openvino.py +++ b/frigate/detectors/plugins/openvino.py @@ -30,12 +30,6 @@ class OvDetector(DetectionApi): self.h = detector_config.model.height self.w = detector_config.model.width - if detector_config.device == "AUTO": - logger.warning( - "OpenVINO AUTO device type is not currently supported. Attempting to use GPU instead." - ) - detector_config.device = "GPU" - if not os.path.isfile(detector_config.model.path): logger.error(f"OpenVino model file {detector_config.model.path} not found.") raise FileNotFoundError @@ -129,10 +123,10 @@ class OvDetector(DetectionApi): strides = [8, 16, 32] - hsizes = [self.h // stride for stride in strides] - wsizes = [self.w // stride for stride in strides] + hsize_list = [self.h // stride for stride in strides] + wsize_list = [self.w // stride for stride in strides] - for hsize, wsize, stride in zip(hsizes, wsizes, strides): + for hsize, wsize, stride in zip(hsize_list, wsize_list, strides): xv, yv = np.meshgrid(np.arange(wsize), np.arange(hsize)) grid = np.stack((xv, yv), 2).reshape(1, -1, 2) grids.append(grid) @@ -216,10 +210,12 @@ class OvDetector(DetectionApi): conf_mask = (image_pred[:, 4] * class_conf.squeeze() >= 0.3).squeeze() # Detections ordered as (x1, y1, x2, y2, obj_conf, class_conf, class_pred) - dets = np.concatenate((image_pred[:, :5], class_conf, class_pred), axis=1) - dets = dets[conf_mask] + detections = np.concatenate( + (image_pred[:, :5], class_conf, class_pred), axis=1 + ) + detections = detections[conf_mask] - ordered = dets[dets[:, 5].argsort()[::-1]][:20] + ordered = detections[detections[:, 5].argsort()[::-1]][:20] for i, object_detected in enumerate(ordered): detections[i] = self.process_yolo( diff --git a/frigate/detectors/plugins/rknn.py b/frigate/detectors/plugins/rknn.py index 7606313b5..dae5cc057 100644 --- a/frigate/detectors/plugins/rknn.py +++ b/frigate/detectors/plugins/rknn.py @@ -17,7 +17,7 @@ supported_socs = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"] supported_models = {ModelTypeEnum.yolonas: "^deci-fp16-yolonas_[sml]$"} -model_chache_dir = "/config/model_cache/rknn_cache/" +model_cache_dir = "/config/model_cache/rknn_cache/" class RknnDetectorConfig(BaseDetectorConfig): @@ -110,7 +110,7 @@ class Rknn(DetectionApi): if model_matched: model_props["filename"] = model_path + f"-{soc}-v2.0.0-1.rknn" - model_props["path"] = model_chache_dir + model_props["filename"] + model_props["path"] = model_cache_dir + model_props["filename"] if not os.path.isfile(model_props["path"]): self.download_model(model_props["filename"]) @@ -125,12 +125,12 @@ class Rknn(DetectionApi): return model_props def download_model(self, filename): - if not os.path.isdir(model_chache_dir): - os.mkdir(model_chache_dir) + if not os.path.isdir(model_cache_dir): + os.mkdir(model_cache_dir) urllib.request.urlretrieve( f"https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/{filename}", - model_chache_dir + filename, + model_cache_dir + filename, ) def check_config(self, config): diff --git a/frigate/detectors/plugins/rocm.py b/frigate/detectors/plugins/rocm.py index ea237a306..aa49e0544 100644 --- a/frigate/detectors/plugins/rocm.py +++ b/frigate/detectors/plugins/rocm.py @@ -9,8 +9,10 @@ from pydantic import Field from typing_extensions import Literal from frigate.detectors.detection_api import DetectionApi -from frigate.detectors.detector_config import BaseDetectorConfig -from frigate.detectors.util import preprocess +from frigate.detectors.detector_config import ( + BaseDetectorConfig, + ModelTypeEnum, +) logger = logging.getLogger(__name__) @@ -74,7 +76,16 @@ class ROCmDetector(DetectionApi): logger.error("AMD/ROCm: module loading failed, missing ROCm environment?") raise + if detector_config.conserve_cpu: + logger.info("AMD/ROCm: switching HIP to blocking mode to conserve CPU") + ctypes.CDLL("/opt/rocm/lib/libamdhip64.so").hipSetDeviceFlags(4) + + self.h = detector_config.model.height + self.w = detector_config.model.width + self.rocm_model_type = detector_config.model.model_type + self.rocm_model_px = detector_config.model.input_pixel_format path = detector_config.model.path + mxr_path = os.path.splitext(path)[0] + ".mxr" if path.endswith(".mxr"): logger.info(f"AMD/ROCm: loading parsed model from {mxr_path}") @@ -84,6 +95,7 @@ class ROCmDetector(DetectionApi): self.model = migraphx.load(mxr_path) else: logger.info(f"AMD/ROCm: loading model from {path}") + if path.endswith(".onnx"): self.model = migraphx.parse_onnx(path) elif ( @@ -95,30 +107,51 @@ class ROCmDetector(DetectionApi): self.model = migraphx.parse_tf(path) else: raise Exception(f"AMD/ROCm: unknown model format {path}") + logger.info("AMD/ROCm: compiling the model") + self.model.compile( migraphx.get_target("gpu"), offload_copy=True, fast_math=True ) + logger.info(f"AMD/ROCm: saving parsed model into {mxr_path}") + os.makedirs("/config/model_cache/rocm", exist_ok=True) migraphx.save(self.model, mxr_path) + logger.info("AMD/ROCm: model loaded") def detect_raw(self, tensor_input): model_input_name = self.model.get_parameter_names()[0] - model_input_shape = tuple( - self.model.get_parameter_shapes()[model_input_name].lens() - ) - tensor_input = preprocess(tensor_input, model_input_shape, np.float32) - detector_result = self.model.run({model_input_name: tensor_input})[0] - addr = ctypes.cast(detector_result.data_ptr(), ctypes.POINTER(ctypes.c_float)) - # ruff: noqa: F841 + tensor_output = np.ctypeslib.as_array( addr, shape=detector_result.get_shape().lens() ) - raise Exception( - "No models are currently supported for rocm. See the docs for more info." - ) + if self.rocm_model_type == ModelTypeEnum.yolonas: + predictions = tensor_output + + detections = np.zeros((20, 6), np.float32) + + for i, prediction in enumerate(predictions): + if i == 20: + break + (_, x_min, y_min, x_max, y_max, confidence, class_id) = prediction + # when running in GPU mode, empty predictions in the output have class_id of -1 + if class_id < 0: + break + detections[i] = [ + class_id, + confidence, + y_min / self.h, + x_min / self.w, + y_max / self.h, + x_max / self.w, + ] + return detections + else: + raise Exception( + f"{self.rocm_model_type} is currently not supported for rocm. See the docs for more info on supported models." + ) diff --git a/frigate/detectors/plugins/tensorrt.py b/frigate/detectors/plugins/tensorrt.py index 64b0849c7..901d18ee7 100644 --- a/frigate/detectors/plugins/tensorrt.py +++ b/frigate/detectors/plugins/tensorrt.py @@ -285,14 +285,14 @@ class TensorRtDetector(DetectionApi): boxes, scores, classes """ # filter low-conf detections and concatenate results of all yolo layers - detections = [] + detection_list = [] for o in trt_outputs: - dets = o.reshape((-1, 7)) - dets = dets[dets[:, 4] * dets[:, 6] >= conf_th] - detections.append(dets) - detections = np.concatenate(detections, axis=0) + detections = o.reshape((-1, 7)) + detections = detections[detections[:, 4] * detections[:, 6] >= conf_th] + detection_list.append(detections) + detection_list = np.concatenate(detection_list, axis=0) - return detections + return detection_list def detect_raw(self, tensor_input): # Input tensor has the shape of the [height, width, 3] diff --git a/frigate/detectors/util.py b/frigate/detectors/util.py deleted file mode 100644 index 74fb82a47..000000000 --- a/frigate/detectors/util.py +++ /dev/null @@ -1,36 +0,0 @@ -import logging - -import cv2 -import numpy as np - -logger = logging.getLogger(__name__) - - -def preprocess(tensor_input, model_input_shape, model_input_element_type): - model_input_shape = tuple(model_input_shape) - assert tensor_input.dtype == np.uint8, f"tensor_input.dtype: {tensor_input.dtype}" - if len(tensor_input.shape) == 3: - tensor_input = tensor_input[np.newaxis, :] - if model_input_element_type == np.uint8: - # nothing to do for uint8 model input - assert ( - model_input_shape == tensor_input.shape - ), f"model_input_shape: {model_input_shape}, tensor_input.shape: {tensor_input.shape}" - return tensor_input - assert ( - model_input_element_type == np.float32 - ), f"model_input_element_type: {model_input_element_type}" - # tensor_input must be nhwc - assert tensor_input.shape[3] == 3, f"tensor_input.shape: {tensor_input.shape}" - if tensor_input.shape[1:3] != model_input_shape[2:4]: - logger.warn( - f"preprocess: tensor_input.shape {tensor_input.shape} and model_input_shape {model_input_shape} do not match!" - ) - # cv2.dnn.blobFromImage is faster than numpying it - return cv2.dnn.blobFromImage( - tensor_input[0], - 1.0 / 255, - (model_input_shape[3], model_input_shape[2]), - None, - swapRB=False, - ) diff --git a/frigate/embeddings/embeddings.py b/frigate/embeddings/embeddings.py index c0dc51ea9..8179de15e 100644 --- a/frigate/embeddings/embeddings.py +++ b/frigate/embeddings/embeddings.py @@ -15,7 +15,7 @@ from frigate.models import Event # Squelch posthog logging logging.getLogger("chromadb.telemetry.product.posthog").setLevel(logging.CRITICAL) -# Hotsawp the sqlite3 module for Chroma compatibility +# Hot-swap the sqlite3 module for Chroma compatibility try: from chromadb import Collection from chromadb import HttpClient as ChromaClient @@ -85,7 +85,10 @@ class Embeddings: @property def description(self) -> Collection: return self.client.get_or_create_collection( - name="event_description", embedding_function=MiniLMEmbedding() + name="event_description", + embedding_function=MiniLMEmbedding( + preferred_providers=["CPUExecutionProvider"] + ), ) def reindex(self) -> None: diff --git a/frigate/embeddings/functions/clip.py b/frigate/embeddings/functions/clip.py index 867938aff..a4e75a510 100644 --- a/frigate/embeddings/functions/clip.py +++ b/frigate/embeddings/functions/clip.py @@ -1,9 +1,13 @@ """CLIP Embeddings for Frigate.""" +import errno +import logging import os +from pathlib import Path from typing import Tuple, Union import onnxruntime as ort +import requests from chromadb import EmbeddingFunction, Embeddings from chromadb.api.types import ( Documents, @@ -39,10 +43,49 @@ class Clip(OnnxClip): models = [] for model_file in [IMAGE_MODEL_FILE, TEXT_MODEL_FILE]: path = os.path.join(MODEL_CACHE_DIR, "clip", model_file) - models.append(OnnxClip._load_model(path, silent)) + models.append(Clip._load_model(path, silent)) return models[0], models[1] + @staticmethod + def _load_model(path: str, silent: bool): + providers = ["CPUExecutionProvider"] + + try: + if os.path.exists(path): + return ort.InferenceSession(path, providers=providers) + else: + raise FileNotFoundError( + errno.ENOENT, + os.strerror(errno.ENOENT), + path, + ) + except Exception: + s3_url = f"https://lakera-clip.s3.eu-west-1.amazonaws.com/{os.path.basename(path)}" + if not silent: + logging.info( + f"The model file ({path}) doesn't exist " + f"or it is invalid. Downloading it from the public S3 " + f"bucket: {s3_url}." # noqa: E501 + ) + + # Download from S3 + # Saving to a temporary file first to avoid corrupting the file + temporary_filename = Path(path).with_name(os.path.basename(path) + ".part") + + # Create any missing directories in the path + temporary_filename.parent.mkdir(parents=True, exist_ok=True) + + with requests.get(s3_url, stream=True) as r: + r.raise_for_status() + with open(temporary_filename, "wb") as f: + for chunk in r.iter_content(chunk_size=8192): + f.write(chunk) + f.flush() + # Finally move the temporary file to the correct location + temporary_filename.rename(path) + return ort.InferenceSession(path, providers=providers) + class ClipEmbedding(EmbeddingFunction): """Embedding function for CLIP model used in Chroma.""" diff --git a/frigate/embeddings/maintainer.py b/frigate/embeddings/maintainer.py index a60663e7d..8e4309d5e 100644 --- a/frigate/embeddings/maintainer.py +++ b/frigate/embeddings/maintainer.py @@ -171,8 +171,11 @@ class EmbeddingMaintainer(threading.Thread): self, event: Event, thumbnails: list[bytes], metadata: dict ) -> None: """Embed the description for an event.""" + camera_config = self.config.cameras[event.camera] - description = self.genai_client.generate_description(thumbnails, metadata) + description = self.genai_client.generate_description( + camera_config, thumbnails, metadata + ) if description is None: logger.debug("Failed to generate description for %s", event.id) diff --git a/frigate/ffmpeg_presets.py b/frigate/ffmpeg_presets.py index 19103cdf8..574dc0177 100644 --- a/frigate/ffmpeg_presets.py +++ b/frigate/ffmpeg_presets.py @@ -91,10 +91,10 @@ PRESETS_HW_ACCEL_DECODE["preset-nvidia-mjpeg"] = PRESETS_HW_ACCEL_DECODE[ PRESETS_HW_ACCEL_SCALE = { "preset-rpi-64-h264": "-r {0} -vf fps={0},scale={1}:{2}", "preset-rpi-64-h265": "-r {0} -vf fps={0},scale={1}:{2}", - FFMPEG_HWACCEL_VAAPI: "-r {0} -vf fps={0},scale_vaapi=w={1}:h={2},hwdownload,eq=gamma=1.05", + FFMPEG_HWACCEL_VAAPI: "-r {0} -vf fps={0},scale_vaapi=w={1}:h={2},hwdownload,format=nv12,eq=gamma=1.05", "preset-intel-qsv-h264": "-r {0} -vf vpp_qsv=framerate={0}:w={1}:h={2}:format=nv12,hwdownload,format=nv12,format=yuv420p", "preset-intel-qsv-h265": "-r {0} -vf vpp_qsv=framerate={0}:w={1}:h={2}:format=nv12,hwdownload,format=nv12,format=yuv420p", - FFMPEG_HWACCEL_NVIDIA: "-r {0} -vf fps={0},scale_cuda=w={1}:h={2}:format=nv12,hwdownload,format=nv12,format=yuv420p", + FFMPEG_HWACCEL_NVIDIA: "-r {0} -vf fps={0},scale_cuda=w={1}:h={2},hwdownload,format=nv12,eq=gamma=1.05", "preset-jetson-h264": "-r {0}", # scaled in decoder "preset-jetson-h265": "-r {0}", # scaled in decoder "preset-rk-h264": "-r {0} -vf scale_rkrga=w={1}:h={2}:format=yuv420p:force_original_aspect_ratio=0,hwmap=mode=read,format=yuv420p", @@ -185,6 +185,15 @@ def parse_preset_hardware_acceleration_scale( else: scale = PRESETS_HW_ACCEL_SCALE.get(arg, PRESETS_HW_ACCEL_SCALE["default"]) + if ( + ",hwdownload,format=nv12,eq=gamma=1.05" in scale + and os.environ.get("FFMPEG_DISABLE_GAMMA_EQUALIZER") is not None + ): + scale.replace( + ",hwdownload,format=nv12,eq=gamma=1.05", + ":format=nv12,hwdownload,format=nv12,format=yuv420p", + ) + scale = scale.format(fps, width, height).split(" ") scale.extend(detect_args) return scale diff --git a/frigate/genai/__init__.py b/frigate/genai/__init__.py index 3761fa62f..afc783021 100644 --- a/frigate/genai/__init__.py +++ b/frigate/genai/__init__.py @@ -4,7 +4,7 @@ import importlib import os from typing import Optional -from frigate.config import GenAIConfig, GenAIProviderEnum +from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum PROVIDERS = {} @@ -28,11 +28,14 @@ class GenAIClient: self.provider = self._init_provider() def generate_description( - self, thumbnails: list[bytes], metadata: dict[str, any] + self, + camera_config: CameraConfig, + thumbnails: list[bytes], + metadata: dict[str, any], ) -> Optional[str]: """Generate a description for the frame.""" - prompt = self.genai_config.object_prompts.get( - metadata["label"], self.genai_config.prompt + prompt = camera_config.genai.object_prompts.get( + metadata["label"], camera_config.genai.prompt ).format(**metadata) return self._send(prompt, thumbnails) diff --git a/frigate/log.py b/frigate/log.py index 2947a3e38..475be50d4 100644 --- a/frigate/log.py +++ b/frigate/log.py @@ -1,71 +1,71 @@ -# adapted from https://medium.com/@jonathonbao/python3-logging-with-multiprocessing-f51f460b8778 +import atexit import logging import multiprocessing as mp import os -import queue -import signal import threading from collections import deque -from logging import handlers -from multiprocessing import Queue -from types import FrameType +from contextlib import AbstractContextManager, ContextDecorator +from logging.handlers import QueueHandler, QueueListener +from types import TracebackType from typing import Deque, Optional -from setproctitle import setproctitle +from typing_extensions import Self from frigate.util.builtin import clean_camera_user_pass - -def listener_configurer() -> None: - root = logging.getLogger() - - if root.hasHandlers(): - root.handlers.clear() - - console_handler = logging.StreamHandler() - formatter = logging.Formatter( - "[%(asctime)s] %(name)-30s %(levelname)-8s: %(message)s", "%Y-%m-%d %H:%M:%S" +LOG_HANDLER = logging.StreamHandler() +LOG_HANDLER.setFormatter( + logging.Formatter( + "[%(asctime)s] %(name)-30s %(levelname)-8s: %(message)s", + "%Y-%m-%d %H:%M:%S", ) - console_handler.setFormatter(formatter) - root.addHandler(console_handler) - root.setLevel(logging.INFO) +) + +LOG_HANDLER.addFilter( + lambda record: not record.getMessage().startswith( + "You are using a scalar distance function" + ) +) -def root_configurer(queue: Queue) -> None: - h = handlers.QueueHandler(queue) - root = logging.getLogger() +class log_thread(AbstractContextManager, ContextDecorator): + def __init__(self, *, handler: logging.Handler = LOG_HANDLER): + super().__init__() - if root.hasHandlers(): - root.handlers.clear() + self._handler = handler - root.addHandler(h) - root.setLevel(logging.INFO) + log_queue: mp.Queue = mp.Queue() + self._queue_handler = QueueHandler(log_queue) + self._log_listener = QueueListener( + log_queue, self._handler, respect_handler_level=True + ) -def log_process(log_queue: Queue) -> None: - threading.current_thread().name = "logger" - setproctitle("frigate.logger") - listener_configurer() + @property + def handler(self) -> logging.Handler: + return self._handler - stop_event = mp.Event() + def _stop_thread(self) -> None: + self._log_listener.stop() - def receiveSignal(signalNumber: int, frame: Optional[FrameType]) -> None: - stop_event.set() + def __enter__(self) -> Self: + logging.getLogger().addHandler(self._queue_handler) - signal.signal(signal.SIGTERM, receiveSignal) - signal.signal(signal.SIGINT, receiveSignal) + atexit.register(self._stop_thread) + self._log_listener.start() - while True: - try: - record = log_queue.get(block=True, timeout=1.0) - except queue.Empty: - if stop_event.is_set(): - break - continue - if record.msg.startswith("You are using a scalar distance function"): - continue - logger = logging.getLogger(record.name) - logger.handle(record) + return self + + def __exit__( + self, + exc_type: Optional[type[BaseException]], + exc_info: Optional[BaseException], + exc_tb: Optional[TracebackType], + ) -> None: + logging.getLogger().removeHandler(self._queue_handler) + + atexit.unregister(self._stop_thread) + self._stop_thread() # based on https://codereview.stackexchange.com/a/17959 diff --git a/frigate/motion/frigate_motion.py b/frigate/motion/frigate_motion.py index 426166193..72097667b 100644 --- a/frigate/motion/frigate_motion.py +++ b/frigate/motion/frigate_motion.py @@ -55,13 +55,13 @@ class FrigateMotionDetector(MotionDetector): # Improve contrast if self.improve_contrast.value: - minval = np.percentile(resized_frame, 4) - maxval = np.percentile(resized_frame, 96) + min_value = np.percentile(resized_frame, 4) + max_value = np.percentile(resized_frame, 96) # don't adjust if the image is a single color - if minval < maxval: - resized_frame = np.clip(resized_frame, minval, maxval) + if min_value < max_value: + resized_frame = np.clip(resized_frame, min_value, max_value) resized_frame = ( - ((resized_frame - minval) / (maxval - minval)) * 255 + ((resized_frame - min_value) / (max_value - min_value)) * 255 ).astype(np.uint8) # mask frame @@ -100,13 +100,13 @@ class FrigateMotionDetector(MotionDetector): # dilate the thresholded image to fill in holes, then find contours # on thresholded image thresh_dilated = cv2.dilate(thresh, None, iterations=2) - cnts = cv2.findContours( + contours = cv2.findContours( thresh_dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE ) - cnts = imutils.grab_contours(cnts) + contours = imutils.grab_contours(contours) # loop over the contours - for c in cnts: + for c in contours: # if the contour is big enough, count it as motion contour_area = cv2.contourArea(c) if contour_area > self.contour_area.value: @@ -124,7 +124,7 @@ class FrigateMotionDetector(MotionDetector): thresh_dilated = cv2.cvtColor(thresh_dilated, cv2.COLOR_GRAY2BGR) # print("--------") # print(self.frame_counter) - for c in cnts: + for c in contours: contour_area = cv2.contourArea(c) if contour_area > self.contour_area.value: x, y, w, h = cv2.boundingRect(c) diff --git a/frigate/motion/improved_motion.py b/frigate/motion/improved_motion.py index 6fb17ec29..297337560 100644 --- a/frigate/motion/improved_motion.py +++ b/frigate/motion/improved_motion.py @@ -79,12 +79,15 @@ class ImprovedMotionDetector(MotionDetector): # Improve contrast if self.config.improve_contrast: # TODO tracking moving average of min/max to avoid sudden contrast changes - minval = np.percentile(resized_frame, 4).astype(np.uint8) - maxval = np.percentile(resized_frame, 96).astype(np.uint8) + min_value = np.percentile(resized_frame, 4).astype(np.uint8) + max_value = np.percentile(resized_frame, 96).astype(np.uint8) # skip contrast calcs if the image is a single color - if minval < maxval: + if min_value < max_value: # keep track of the last 50 contrast values - self.contrast_values[self.contrast_values_index] = [minval, maxval] + self.contrast_values[self.contrast_values_index] = [ + min_value, + max_value, + ] self.contrast_values_index += 1 if self.contrast_values_index == len(self.contrast_values): self.contrast_values_index = 0 @@ -122,14 +125,14 @@ class ImprovedMotionDetector(MotionDetector): # dilate the thresholded image to fill in holes, then find contours # on thresholded image thresh_dilated = cv2.dilate(thresh, None, iterations=1) - cnts = cv2.findContours( + contours = cv2.findContours( thresh_dilated, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE ) - cnts = imutils.grab_contours(cnts) + contours = imutils.grab_contours(contours) # loop over the contours total_contour_area = 0 - for c in cnts: + for c in contours: # if the contour is big enough, count it as motion contour_area = cv2.contourArea(c) total_contour_area += contour_area diff --git a/frigate/object_detection.py b/frigate/object_detection.py index 22ff84f89..de383dffa 100644 --- a/frigate/object_detection.py +++ b/frigate/object_detection.py @@ -125,6 +125,7 @@ def run_detector( start.value = datetime.datetime.now().timestamp() detections = object_detector.detect_raw(input_frame) duration = datetime.datetime.now().timestamp() - start.value + frame_manager.close(connection_id) outputs[connection_id]["np"][:] = detections[:] out_events[connection_id].set() start.value = 0.0 diff --git a/frigate/object_processing.py b/frigate/object_processing.py index 50d962917..e73186f46 100644 --- a/frigate/object_processing.py +++ b/frigate/object_processing.py @@ -1138,12 +1138,14 @@ class TrackedObjectProcessor(threading.Thread): ) ) or ( - not review_config.detections.labels - or obj.obj_data["label"] in review_config.detections.labels - ) - and ( - not review_config.detections.required_zones - or set(obj.entered_zones) & set(review_config.alerts.required_zones) + ( + not review_config.detections.labels + or obj.obj_data["label"] in review_config.detections.labels + ) + and ( + not review_config.detections.required_zones + or set(obj.entered_zones) & set(review_config.alerts.required_zones) + ) ) ): logger.debug( diff --git a/frigate/ptz/autotrack.py b/frigate/ptz/autotrack.py index 92c4141a7..80195f5d8 100644 --- a/frigate/ptz/autotrack.py +++ b/frigate/ptz/autotrack.py @@ -268,9 +268,9 @@ class PtzAutoTracker: self.ptz_metrics[camera]["ptz_autotracker_enabled"].value = False return - movestatus_supported = self.onvif.get_service_capabilities(camera) + move_status_supported = self.onvif.get_service_capabilities(camera) - if movestatus_supported is None or movestatus_supported.lower() != "true": + if move_status_supported is None or move_status_supported.lower() != "true": logger.warning( f"Disabling autotracking for {camera}: ONVIF MoveStatus not supported" ) @@ -807,8 +807,8 @@ class PtzAutoTracker: invalid_delta = np.any(delta > delta_thresh) # Check variance - stdevs = np.std(velocities, axis=0) - high_variances = np.any(stdevs > var_thresh) + stdev_list = np.std(velocities, axis=0) + high_variances = np.any(stdev_list > var_thresh) # Check direction difference velocities = np.round(velocities) diff --git a/frigate/ptz/onvif.py b/frigate/ptz/onvif.py index 9c20ebf62..d13b7bbc3 100644 --- a/frigate/ptz/onvif.py +++ b/frigate/ptz/onvif.py @@ -335,6 +335,10 @@ class OnvifController: ) self._stop(camera_name) + if "pt" not in self.cams[camera_name]["features"]: + logger.error(f"{camera_name} does not support ONVIF pan/tilt movement.") + return + self.cams[camera_name]["active"] = True onvif: ONVIFCamera = self.cams[camera_name]["onvif"] move_request = self.cams[camera_name]["move_request"] @@ -476,6 +480,10 @@ class OnvifController: ) self._stop(camera_name) + if "zoom" not in self.cams[camera_name]["features"]: + logger.error(f"{camera_name} does not support ONVIF zooming.") + return + self.cams[camera_name]["active"] = True onvif: ONVIFCamera = self.cams[camera_name]["onvif"] move_request = self.cams[camera_name]["move_request"] diff --git a/frigate/record/maintainer.py b/frigate/record/maintainer.py index 5bcec62e6..66036f807 100644 --- a/frigate/record/maintainer.py +++ b/frigate/record/maintainer.py @@ -90,9 +90,9 @@ class RecordingMaintainer(threading.Thread): try: if process.name() != "ffmpeg": continue - flist = process.open_files() - if flist: - for nt in flist: + file_list = process.open_files() + if file_list: + for nt in file_list: if nt.path.startswith(CACHE_DIR): files_in_use.append(nt.path.split("/")[-1]) except psutil.Error: diff --git a/frigate/stats/util.py b/frigate/stats/util.py index ac28e3d89..e9a78742f 100644 --- a/frigate/stats/util.py +++ b/frigate/stats/util.py @@ -250,7 +250,7 @@ def stats_snapshot( ffmpeg_pid = ( camera_stats["ffmpeg_pid"].value if camera_stats["ffmpeg_pid"] else None ) - cpid = ( + capture_pid = ( camera_stats["capture_process"].pid if camera_stats["capture_process"] else None @@ -262,7 +262,7 @@ def stats_snapshot( "detection_fps": round(camera_stats["detection_fps"].value, 2), "detection_enabled": config.cameras[name].detect.enabled, "pid": pid, - "capture_pid": cpid, + "capture_pid": capture_pid, "ffmpeg_pid": ffmpeg_pid, "audio_rms": round(camera_stats["audio_rms"].value, 4), "audio_dBFS": round(camera_stats["audio_dBFS"].value, 4), diff --git a/frigate/test/const.py b/frigate/test/const.py index bef02e235..3cbd37799 100644 --- a/frigate/test/const.py +++ b/frigate/test/const.py @@ -1,4 +1,4 @@ -"""Consts for testing.""" +"""Constants for testing.""" TEST_DB = "test.db" TEST_DB_CLEANUPS = ["test.db", "test.db-shm", "test.db-wal"] diff --git a/frigate/test/test_ffmpeg_presets.py b/frigate/test/test_ffmpeg_presets.py index ac5e30a2d..0275469cd 100644 --- a/frigate/test/test_ffmpeg_presets.py +++ b/frigate/test/test_ffmpeg_presets.py @@ -78,7 +78,7 @@ class TestFfmpegPresets(unittest.TestCase): " ".join(frigate_config.cameras["back"].ffmpeg_cmds[0]["cmd"]) ) assert ( - "fps=10,scale_cuda=w=2560:h=1920:format=nv12,hwdownload,format=nv12,format=yuv420p" + "fps=10,scale_cuda=w=2560:h=1920,hwdownload,format=nv12,eq=gamma=1.05" in (" ".join(frigate_config.cameras["back"].ffmpeg_cmds[0]["cmd"])) ) diff --git a/frigate/timeline.py b/frigate/timeline.py index 952bb36f4..e60638284 100644 --- a/frigate/timeline.py +++ b/frigate/timeline.py @@ -44,9 +44,10 @@ class TimelineProcessor(threading.Thread): continue if input_type == EventTypeEnum.tracked_object: - self.handle_object_detection( - camera, event_type, prev_event_data, event_data - ) + if prev_event_data is not None and event_data is not None: + self.handle_object_detection( + camera, event_type, prev_event_data, event_data + ) elif input_type == EventTypeEnum.api: self.handle_api_entry(camera, event_type, event_data) diff --git a/frigate/util/object.py b/frigate/util/object.py index 66810d5e7..da0a54279 100644 --- a/frigate/util/object.py +++ b/frigate/util/object.py @@ -511,12 +511,12 @@ def reduce_detections( # due to min score requirement of NMSBoxes confidences = [0.6 if clipped(o, frame_shape) else o[1] for o in group] - idxs = cv2.dnn.NMSBoxes( + indices = cv2.dnn.NMSBoxes( boxes, confidences, 0.5, LABEL_NMS_MAP.get(label, LABEL_NMS_DEFAULT) ) # add objects - for index in idxs: + for index in indices: index = index if isinstance(index, np.int32) else index[0] obj = group[index] selected_objects.append(obj) diff --git a/frigate/util/services.py b/frigate/util/services.py index 03787d248..d83db3095 100644 --- a/frigate/util/services.py +++ b/frigate/util/services.py @@ -122,7 +122,7 @@ def get_cpu_stats() -> dict[str, dict]: stats = f.readline().split() utime = int(stats[13]) stime = int(stats[14]) - starttime = int(stats[21]) + start_time = int(stats[21]) with open("/proc/uptime") as f: system_uptime_sec = int(float(f.read().split()[0])) @@ -131,9 +131,9 @@ def get_cpu_stats() -> dict[str, dict]: process_utime_sec = utime // clk_tck process_stime_sec = stime // clk_tck - process_starttime_sec = starttime // clk_tck + process_start_time_sec = start_time // clk_tck - process_elapsed_sec = system_uptime_sec - process_starttime_sec + process_elapsed_sec = system_uptime_sec - process_start_time_sec process_usage_sec = process_utime_sec + process_stime_sec cpu_average_usage = process_usage_sec * 100 // process_elapsed_sec diff --git a/process_clip.py b/process_clip.py index 73e2e7c41..77cfdba2c 100644 --- a/process_clip.py +++ b/process_clip.py @@ -28,8 +28,7 @@ from frigate.video import ( # noqa: E402 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"^2.2.1", + "tslib": "^2.1.0", + "use-callback-ref": "^1.3.0", + "use-sidecar": "^1.1.2" + }, + "engines": { + "node": ">=10" + }, + "peerDependencies": { + "@types/react": "^16.8.0 || ^17.0.0 || ^18.0.0", + "react": "^16.8.0 || ^17.0.0 || ^18.0.0" + }, + "peerDependenciesMeta": { + "@types/react": { + "optional": true + } + } + }, "node_modules/color-convert": { "version": "2.0.1", "resolved": "https://registry.npmjs.org/color-convert/-/color-convert-2.0.1.tgz", diff --git a/web/package.json b/web/package.json index bb15ea4b8..f8f4bc306 100644 --- a/web/package.json +++ b/web/package.json @@ -40,6 +40,7 @@ "axios": "^1.7.3", "class-variance-authority": "^0.7.0", "clsx": "^2.1.1", + "cmdk": "^1.0.0", "copy-to-clipboard": "^3.3.3", "date-fns": "^3.6.0", "embla-carousel-react": "^8.2.0", diff --git a/web/public/vite.svg b/web/public/vite.svg deleted file mode 100644 index e7b8dfb1b..000000000 --- a/web/public/vite.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/web/src/components/filter/SearchFilterGroup.tsx b/web/src/components/filter/SearchFilterGroup.tsx index 0b0b3278e..834e9e99b 100644 --- a/web/src/components/filter/SearchFilterGroup.tsx +++ b/web/src/components/filter/SearchFilterGroup.tsx @@ -43,7 +43,6 @@ type SearchFilterGroupProps = { className: string; filters?: SearchFilters[]; filter?: SearchFilter; - searchTerm: string; filterList?: FilterList; onUpdateFilter: (filter: SearchFilter) => void; }; @@ -51,7 +50,6 @@ export default function SearchFilterGroup({ className, filters = DEFAULT_REVIEW_FILTERS, filter, - searchTerm, filterList, onUpdateFilter, }: SearchFilterGroupProps) { @@ -109,11 +107,8 @@ export default function SearchFilterGroup({ return; } const cameraConfig = config.cameras[camera]; - cameraConfig.review.alerts.required_zones.forEach((zone) => { - zones.add(zone); - }); - cameraConfig.review.detections.required_zones.forEach((zone) => { - zones.add(zone); + Object.entries(cameraConfig.zones).map(([name, _]) => { + zones.add(name); }); }); @@ -216,7 +211,7 @@ export default function SearchFilterGroup({ )} {config?.semantic_search?.enabled && filters.includes("source") && - !searchTerm.includes("similarity:") && ( + !filter?.search_type?.includes("similarity") && ( { const updatedSources = currentSearchSources ? [...currentSearchSources] diff --git a/web/src/components/graph/SystemGraph.tsx b/web/src/components/graph/SystemGraph.tsx index 3f5bfead3..098a1957e 100644 --- a/web/src/components/graph/SystemGraph.tsx +++ b/web/src/components/graph/SystemGraph.tsx @@ -32,6 +32,16 @@ export function ThresholdBarGraph({ [data], ); + const yMax = useMemo(() => { + if (unit != "%") { + return undefined; + } + + // @ts-expect-error y is valid + const yValues: number[] = data[0].data.map((point) => point?.y); + return Math.max(threshold.warning, ...yValues); + }, [data, threshold, unit]); + const { theme, systemTheme } = useTheme(); const formatTime = useCallback( @@ -130,9 +140,10 @@ export function ThresholdBarGraph({ formatter: (val: number) => Math.ceil(val).toString(), }, min: 0, + max: yMax, }, } as ApexCharts.ApexOptions; - }, [graphId, threshold, unit, systemTheme, theme, formatTime]); + }, [graphId, threshold, unit, yMax, systemTheme, theme, formatTime]); useEffect(() => { ApexCharts.exec(graphId, "updateOptions", options, true, true); diff --git a/web/src/components/input/DeleteSearchDialog.tsx b/web/src/components/input/DeleteSearchDialog.tsx new file mode 100644 index 000000000..0aaabdde5 --- /dev/null +++ b/web/src/components/input/DeleteSearchDialog.tsx @@ -0,0 +1,46 @@ +import { + AlertDialog, + AlertDialogAction, + AlertDialogCancel, + AlertDialogContent, + AlertDialogDescription, + AlertDialogFooter, + AlertDialogHeader, + AlertDialogTitle, +} from "@/components/ui/alert-dialog"; + +type DeleteSearchDialogProps = { + isOpen: boolean; + onClose: () => void; + onConfirm: () => void; + searchName: string; +}; + +export function DeleteSearchDialog({ + isOpen, + onClose, + onConfirm, + searchName, +}: DeleteSearchDialogProps) { + return ( + + + + Are you sure? + + This will permanently delete the saved search "{searchName}". + + + + Cancel + + Delete + + + + + ); +} diff --git a/web/src/components/input/InputWithTags.tsx b/web/src/components/input/InputWithTags.tsx new file mode 100644 index 000000000..c21dba733 --- /dev/null +++ b/web/src/components/input/InputWithTags.tsx @@ -0,0 +1,701 @@ +import { useState, useRef, useEffect, useCallback } from "react"; +import { + LuX, + LuFilter, + LuImage, + LuChevronDown, + LuChevronUp, + LuTrash2, + LuStar, +} from "react-icons/lu"; +import { + FilterType, + SavedSearchQuery, + SearchFilter, + SearchSource, +} from "@/types/search"; +import useSuggestions from "@/hooks/use-suggestions"; +import { + Command, + CommandInput, + CommandList, + CommandGroup, + CommandItem, +} from "@/components/ui/command"; +import { + Popover, + PopoverContent, + PopoverTrigger, +} from "@/components/ui/popover"; +import { cn } from "@/lib/utils"; +import { Tooltip, TooltipContent, TooltipTrigger } from "../ui/tooltip"; +import { TooltipPortal } from "@radix-ui/react-tooltip"; +import { usePersistence } from "@/hooks/use-persistence"; +import { SaveSearchDialog } from "./SaveSearchDialog"; +import { DeleteSearchDialog } from "./DeleteSearchDialog"; +import { + convertLocalDateToTimestamp, + getIntlDateFormat, +} from "@/utils/dateUtil"; +import { toast } from "sonner"; + +type InputWithTagsProps = { + filters: SearchFilter; + setFilters: (filter: SearchFilter) => void; + search: string; + setSearch: (search: string) => void; + allSuggestions: { + [K in keyof SearchFilter]: string[]; + }; +}; + +export default function InputWithTags({ + filters, + setFilters, + search, + setSearch, + allSuggestions, +}: InputWithTagsProps) { + const [inputValue, setInputValue] = useState(search || ""); + const [currentFilterType, setCurrentFilterType] = useState( + null, + ); + const [inputFocused, setInputFocused] = useState(false); + const [isSimilaritySearch, setIsSimilaritySearch] = useState(false); + const inputRef = useRef(null); + const commandRef = useRef(null); + + // TODO: search history from browser storage + + const [searchHistory, setSearchHistory, searchHistoryLoaded] = usePersistence< + SavedSearchQuery[] + >("frigate-search-history"); + + const [isSaveDialogOpen, setIsSaveDialogOpen] = useState(false); + const [isDeleteDialogOpen, setIsDeleteDialogOpen] = useState(false); + const [searchToDelete, setSearchToDelete] = useState(null); + + const handleSetSearchHistory = useCallback(() => { + setIsSaveDialogOpen(true); + }, []); + + const handleSaveSearch = useCallback( + (name: string) => { + if (searchHistoryLoaded) { + setSearchHistory([ + ...(searchHistory ?? []), + { + name: name, + search: search, + filter: filters, + }, + ]); + } + }, + [search, filters, searchHistory, setSearchHistory, searchHistoryLoaded], + ); + + const handleLoadSavedSearch = useCallback( + (name: string) => { + if (searchHistoryLoaded) { + const savedSearchEntry = searchHistory?.find( + (entry) => entry.name === name, + ); + if (savedSearchEntry) { + setFilters(savedSearchEntry.filter!); + setSearch(savedSearchEntry.search); + } + } + }, + [searchHistory, searchHistoryLoaded, setFilters, setSearch], + ); + + const handleDeleteSearch = useCallback((name: string) => { + setSearchToDelete(name); + setIsDeleteDialogOpen(true); + }, []); + + const confirmDeleteSearch = useCallback(() => { + if (searchToDelete && searchHistory) { + setSearchHistory( + searchHistory.filter((item) => item.name !== searchToDelete) ?? [], + ); + setSearchToDelete(null); + setIsDeleteDialogOpen(false); + } + }, [searchToDelete, searchHistory, setSearchHistory]); + + // suggestions + + const { suggestions, updateSuggestions } = useSuggestions( + filters, + allSuggestions, + searchHistory, + ); + + const resetSuggestions = useCallback( + (value: string) => { + setCurrentFilterType(null); + updateSuggestions(value, null); + }, + [updateSuggestions], + ); + + const filterSuggestions = useCallback( + (current_suggestions: string[]) => { + if (!inputValue || currentFilterType) return suggestions; + const words = inputValue.split(/[\s,]+/); + const lastNonEmptyWordIndex = words + .map((word) => word.trim()) + .lastIndexOf(words.filter((word) => word.trim() !== "").pop() || ""); + const currentWord = words[lastNonEmptyWordIndex]; + return current_suggestions.filter((suggestion) => + suggestion.toLowerCase().includes(currentWord.toLowerCase()), + ); + }, + [inputValue, suggestions, currentFilterType], + ); + + const removeFilter = useCallback( + (filterType: FilterType, filterValue: string | number) => { + const newFilters = { ...filters }; + if (Array.isArray(newFilters[filterType])) { + (newFilters[filterType] as string[]) = ( + newFilters[filterType] as string[] + ).filter((v) => v !== filterValue); + if ((newFilters[filterType] as string[]).length === 0) { + delete newFilters[filterType]; + } + } else if (filterType === "before" || filterType === "after") { + if (newFilters[filterType] === filterValue) { + delete newFilters[filterType]; + } + } else { + delete newFilters[filterType]; + } + setFilters(newFilters as SearchFilter); + }, + [filters, setFilters], + ); + + const createFilter = useCallback( + (type: FilterType, value: string) => { + if (allSuggestions[type as FilterType]?.includes(value)) { + const newFilters = { ...filters }; + let timestamp = 0; + + switch (type) { + case "before": + case "after": + timestamp = convertLocalDateToTimestamp(value); + if (timestamp > 0) { + // Check for conflicts with existing before/after filters + if ( + type === "before" && + filters.after && + timestamp <= filters.after * 1000 + ) { + toast.error( + "The 'before' date must be later than the 'after' date.", + { + position: "top-center", + }, + ); + return; + } + if ( + type === "after" && + filters.before && + timestamp >= filters.before * 1000 + ) { + toast.error( + "The 'after' date must be earlier than the 'before' date.", + { + position: "top-center", + }, + ); + return; + } + if (type === "before") { + timestamp -= 1; + } + newFilters[type] = timestamp / 1000; + } + break; + case "search_type": + if (!newFilters.search_type) newFilters.search_type = []; + if ( + !(newFilters.search_type as SearchSource[]).includes( + value as SearchSource, + ) + ) { + (newFilters.search_type as SearchSource[]).push( + value as SearchSource, + ); + } + break; + case "event_id": + newFilters.event_id = value; + break; + default: + // Handle array types (cameras, labels, subLabels, zones) + if (!newFilters[type]) newFilters[type] = []; + if (Array.isArray(newFilters[type])) { + if (!(newFilters[type] as string[]).includes(value)) { + (newFilters[type] as string[]).push(value); + } + } + break; + } + + setFilters(newFilters); + setInputValue((prev) => prev.replace(`${type}:${value}`, "").trim()); + setCurrentFilterType(null); + } + }, + [filters, setFilters, allSuggestions], + ); + + // handlers + + const handleFilterCreation = useCallback( + (filterType: FilterType, filterValue: string) => { + const trimmedValue = filterValue.trim(); + if ( + allSuggestions[filterType]?.includes(trimmedValue) || + ((filterType === "before" || filterType === "after") && + trimmedValue.match(/^\d{8}$/)) + ) { + createFilter(filterType, trimmedValue); + setInputValue((prev) => { + const regex = new RegExp( + `${filterType}:${filterValue.trim()}[,\\s]*`, + ); + const newValue = prev.replace(regex, "").trim(); + return newValue.endsWith(",") + ? newValue.slice(0, -1).trim() + : newValue; + }); + setCurrentFilterType(null); + } + }, + [allSuggestions, createFilter], + ); + + const handleInputChange = useCallback( + (value: string) => { + setInputValue(value); + + const words = value.split(/[\s,]+/); + const lastNonEmptyWordIndex = words + .map((word) => word.trim()) + .lastIndexOf(words.filter((word) => word.trim() !== "").pop() || ""); + const currentWord = words[lastNonEmptyWordIndex]; + const isLastCharSpaceOrComma = value.endsWith(" ") || value.endsWith(","); + + // Check if the current word is a filter type + const filterTypeMatch = currentWord.match(/^(\w+):(.*)$/); + if (filterTypeMatch) { + const [_, filterType, filterValue] = filterTypeMatch as [ + string, + FilterType, + string, + ]; + + // Check if filter type is valid + if ( + filterType in allSuggestions || + filterType === "before" || + filterType === "after" + ) { + setCurrentFilterType(filterType); + + if (filterType === "before" || filterType === "after") { + // For before and after, we don't need to update suggestions + if (filterValue.match(/^\d{8}$/)) { + handleFilterCreation(filterType, filterValue); + } + } else { + updateSuggestions(filterValue, filterType); + + // Check if the last character is a space or comma + if (isLastCharSpaceOrComma) { + handleFilterCreation(filterType, filterValue); + } + } + } else { + resetSuggestions(value); + } + } else { + resetSuggestions(value); + } + }, + [updateSuggestions, resetSuggestions, allSuggestions, handleFilterCreation], + ); + + const handleInputFocus = useCallback(() => { + setInputFocused(true); + }, []); + + const handleClearInput = useCallback(() => { + setInputFocused(false); + setInputValue(""); + resetSuggestions(""); + setSearch(""); + inputRef?.current?.blur(); + setFilters({}); + setCurrentFilterType(null); + setIsSimilaritySearch(false); + }, [setFilters, resetSuggestions, setSearch]); + + const handleInputBlur = useCallback((e: React.FocusEvent) => { + if ( + commandRef.current && + !commandRef.current.contains(e.relatedTarget as Node) + ) { + setInputFocused(false); + } + }, []); + + const handleSuggestionClick = useCallback( + (suggestion: string) => { + if (currentFilterType) { + // Apply the selected suggestion to the current filter type + createFilter(currentFilterType, suggestion); + setInputValue((prev) => { + const regex = new RegExp(`${currentFilterType}:[^\\s,]*`, "g"); + return prev.replace(regex, "").trim(); + }); + } else if (suggestion in allSuggestions) { + // Set the suggestion as a new filter type + setCurrentFilterType(suggestion as FilterType); + setInputValue((prev) => { + // Remove any partial match of the filter type, including incomplete matches + const words = prev.split(/\s+/); + const lastWord = words[words.length - 1]; + if (lastWord && suggestion.startsWith(lastWord.toLowerCase())) { + words[words.length - 1] = suggestion + ":"; + } else { + words.push(suggestion + ":"); + } + return words.join(" ").trim(); + }); + } else { + // Add the suggestion as a standalone word + setInputValue((prev) => `${prev}${suggestion} `); + } + + inputRef.current?.focus(); + }, + [createFilter, currentFilterType, allSuggestions], + ); + + const handleSearch = useCallback( + (value: string) => { + setSearch(value); + setInputFocused(false); + inputRef?.current?.blur(); + }, + [setSearch], + ); + + const handleInputKeyDown = useCallback( + (e: React.KeyboardEvent) => { + if ( + e.key === "Enter" && + inputValue.trim() !== "" && + filterSuggestions(suggestions).length == 0 + ) { + e.preventDefault(); + + handleSearch(inputValue); + } + }, + [inputValue, handleSearch, filterSuggestions, suggestions], + ); + + // effects + + useEffect(() => { + updateSuggestions(inputValue, currentFilterType); + }, [currentFilterType, inputValue, updateSuggestions]); + + useEffect(() => { + if (filters?.search_type && filters?.search_type.includes("similarity")) { + setIsSimilaritySearch(true); + setInputValue(""); + } else { + setIsSimilaritySearch(false); + setInputValue(search || ""); + } + }, [filters, search]); + + return ( + <> + +
+ +
+ {(search || Object.keys(filters).length > 0) && ( + + + + + + Clear search + + + )} + + {(search || Object.keys(filters).length > 0) && ( + + + + + + Save search + + + )} + + {isSimilaritySearch && ( + + + + + + Similarity search active + + + )} + + + + + + +
+

How to use text filters

+

+ Filters help you narrow down your search results. Here's how + to use them: +

+
    +
  • + Type a filter name followed by a colon (e.g., "cameras:"). +
    • +
  • + Select a value from the suggestions or type your own. +
    • +
  • + Use multiple filters by adding them one after another. +
    • +
  • + Date filters (before: and after:) use{" "} + {getIntlDateFormat()} format. +
    • +
  • Remove filters by clicking the 'x' next to them.
    • +
+

+ Example:{" "} + + cameras:front_door label:person before:01012024 + +

+
+ + + + {inputFocused ? ( + setInputFocused(false)} + className="size-4 cursor-pointer text-secondary-foreground" + /> + ) : ( + setInputFocused(true)} + className="size-4 cursor-pointer text-secondary-foreground" + /> + )} +
+
+ + + {(Object.keys(filters).length > 0 || isSimilaritySearch) && ( + +
+ {isSimilaritySearch && ( + + Similarity Search + + + )} + {Object.entries(filters).map(([filterType, filterValues]) => + Array.isArray(filterValues) + ? filterValues + .filter(() => filterType !== "query") + .filter(() => !filterValues.includes("similarity")) + .map((value, index) => ( + + {filterType.replaceAll("_", " ")}:{" "} + {value.replaceAll("_", " ")} + + + )) + : filterType !== "event_id" && ( + + {filterType}: + {filterType === "before" || filterType === "after" + ? new Date( + (filterType === "before" + ? (filterValues as number) + 1 + : (filterValues as number)) * 1000, + ).toLocaleDateString( + window.navigator?.language || "en-US", + ) + : filterValues} + + + ), + )} +
+ + )} + + {!currentFilterType && + !inputValue && + searchHistoryLoaded && + (searchHistory?.length ?? 0) > 0 && ( + + {searchHistory?.map((suggestion, index) => ( + handleLoadSavedSearch(suggestion.name)} + > + {suggestion.name} + + + + + + Delete saved search + + + + ))} + + )} + + {filterSuggestions(suggestions) + .filter( + (item) => + !searchHistory?.some((history) => history.name === item), + ) + .map((suggestion, index) => ( + handleSuggestionClick(suggestion)} + > + {suggestion} + + ))} + + + + setIsSaveDialogOpen(false)} + onSave={handleSaveSearch} + /> + setIsDeleteDialogOpen(false)} + onConfirm={confirmDeleteSearch} + searchName={searchToDelete || ""} + /> + + ); +} diff --git a/web/src/components/input/SaveSearchDialog.tsx b/web/src/components/input/SaveSearchDialog.tsx new file mode 100644 index 000000000..c5bf29001 --- /dev/null +++ b/web/src/components/input/SaveSearchDialog.tsx @@ -0,0 +1,74 @@ +import { + Dialog, + DialogContent, + DialogHeader, + DialogTitle, + DialogFooter, + DialogDescription, +} from "@/components/ui/dialog"; + +import { Button } from "@/components/ui/button"; +import { Input } from "@/components/ui/input"; +import { useState } from "react"; +import { isMobile } from "react-device-detect"; +import { toast } from "sonner"; + +type SaveSearchDialogProps = { + isOpen: boolean; + onClose: () => void; + onSave: (name: string) => void; +}; + +export function SaveSearchDialog({ + isOpen, + onClose, + onSave, +}: SaveSearchDialogProps) { + const [searchName, setSearchName] = useState(""); + + const handleSave = () => { + if (searchName.trim()) { + onSave(searchName.trim()); + setSearchName(""); + toast.success(`Search (${searchName.trim()}) has been saved.`, { + position: "top-center", + }); + onClose(); + } + }; + + return ( + + { + if (isMobile) { + e.preventDefault(); + } + }} + > + + Save Search + + Provide a name for this saved search. + + + setSearchName(e.target.value)} + placeholder="Enter a name for your search" + /> + + + + + + + ); +} diff --git a/web/src/components/overlay/detail/AnnotationSettingsPane.tsx b/web/src/components/overlay/detail/AnnotationSettingsPane.tsx index 64f41d4d4..e073f72a6 100644 --- a/web/src/components/overlay/detail/AnnotationSettingsPane.tsx +++ b/web/src/components/overlay/detail/AnnotationSettingsPane.tsx @@ -121,7 +121,7 @@ export function AnnotationSettingsPane({ } return ( -
+
Annotation Settings @@ -152,8 +152,8 @@ export function AnnotationSettingsPane({ render={({ field }) => ( Annotation Offset -
-
+
+
This data comes from your camera's detect feed but is @@ -161,7 +161,7 @@ export function AnnotationSettingsPane({ unlikely that the two streams are perfectly in sync. As a result, the bounding box and the footage will not line up perfectly. However, the annotation_offset{" "} - field in your config can be used to adjust this. + field can be used to adjust this.
- + {eventSequence.map((item, index) => ( diff --git a/web/src/components/overlay/detail/ReviewDetailDialog.tsx b/web/src/components/overlay/detail/ReviewDetailDialog.tsx index 52c8091e0..492ccc992 100644 --- a/web/src/components/overlay/detail/ReviewDetailDialog.tsx +++ b/web/src/components/overlay/detail/ReviewDetailDialog.tsx @@ -234,7 +234,7 @@ export default function ReviewDetailDialog({ )} {pane == "details" && selectedEvent && ( -
+
)} @@ -370,7 +370,9 @@ function EventItem({ { - navigate(`/explore?similarity_search_id=${event.id}`); + navigate( + `/explore?search_type=similarity&event_id=${event.id}`, + ); }} > diff --git a/web/src/components/ui/command.tsx b/web/src/components/ui/command.tsx new file mode 100644 index 000000000..64be5e01a --- /dev/null +++ b/web/src/components/ui/command.tsx @@ -0,0 +1,153 @@ +import * as React from "react"; +import { type DialogProps } from "@radix-ui/react-dialog"; +import { Command as CommandPrimitive } from "cmdk"; +import { Search } from "lucide-react"; + +import { cn } from "@/lib/utils"; +import { Dialog, DialogContent } from "@/components/ui/dialog"; + +const Command = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +Command.displayName = CommandPrimitive.displayName; + +interface CommandDialogProps extends DialogProps {} + +const CommandDialog = ({ children, ...props }: CommandDialogProps) => { + return ( + + + + {children} + + + + ); +}; + +const CommandInput = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( +
+ + +
+)); + +CommandInput.displayName = CommandPrimitive.Input.displayName; + +const CommandList = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); + +CommandList.displayName = CommandPrimitive.List.displayName; + +const CommandEmpty = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>((props, ref) => ( + +)); + +CommandEmpty.displayName = CommandPrimitive.Empty.displayName; + +const CommandGroup = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); + +CommandGroup.displayName = CommandPrimitive.Group.displayName; + +const CommandSeparator = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); +CommandSeparator.displayName = CommandPrimitive.Separator.displayName; + +const CommandItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)); + +CommandItem.displayName = CommandPrimitive.Item.displayName; + +const CommandShortcut = ({ + className, + ...props +}: React.HTMLAttributes) => { + return ( + + ); +}; +CommandShortcut.displayName = "CommandShortcut"; + +export { + Command, + CommandDialog, + CommandInput, + CommandList, + CommandEmpty, + CommandGroup, + CommandItem, + CommandShortcut, + CommandSeparator, +}; diff --git a/web/src/hooks/use-overlay-state.tsx b/web/src/hooks/use-overlay-state.tsx index e68476682..75d738e61 100644 --- a/web/src/hooks/use-overlay-state.tsx +++ b/web/src/hooks/use-overlay-state.tsx @@ -125,7 +125,7 @@ export function useSearchEffect( const remove = callback(param[1]); if (remove) { - setSearchParams(); + setSearchParams(undefined, { replace: true }); } }, [param, callback, setSearchParams]); } diff --git a/web/src/hooks/use-suggestions.ts b/web/src/hooks/use-suggestions.ts new file mode 100644 index 000000000..9222c866c --- /dev/null +++ b/web/src/hooks/use-suggestions.ts @@ -0,0 +1,63 @@ +import { FilterType, SavedSearchQuery, SearchFilter } from "@/types/search"; +import { useCallback, useState } from "react"; + +// Custom hook for managing suggestions +export type UseSuggestionsType = ( + filters: SearchFilter, + allSuggestions: { [K in keyof SearchFilter]: string[] }, + searchHistory: SavedSearchQuery[], +) => ReturnType; + +// Define and export the useSuggestions hook +export default function useSuggestions( + filters: SearchFilter, + allSuggestions: { [K in keyof SearchFilter]: string[] }, + searchHistory?: SavedSearchQuery[], +) { + const [suggestions, setSuggestions] = useState([]); + + const updateSuggestions = useCallback( + (value: string, currentFilterType: FilterType | null) => { + if (currentFilterType && currentFilterType in allSuggestions) { + const filterValue = value.split(":").pop() || ""; + const currentFilterValues = filters[currentFilterType] || []; + setSuggestions( + allSuggestions[currentFilterType]?.filter( + (item) => + item.toLowerCase().startsWith(filterValue.toLowerCase()) && + !(currentFilterValues as (string | number)[]).includes(item), + ) ?? [], + ); + } else { + const availableFilters = Object.keys(allSuggestions).filter( + (filter) => { + const filterKey = filter as FilterType; + const filterValues = filters[filterKey]; + const suggestionValues = allSuggestions[filterKey]; + + if (!filterValues) return true; + if ( + Array.isArray(filterValues) && + Array.isArray(suggestionValues) + ) { + return filterValues.length < suggestionValues.length; + } + return false; + }, + ); + setSuggestions([ + ...(searchHistory?.map((search) => search.name) ?? []), + ...availableFilters, + "before", + "after", + ]); + } + }, + [filters, allSuggestions, searchHistory], + ); + + return { + suggestions, + updateSuggestions, + }; +} diff --git a/web/src/pages/ConfigEditor.tsx b/web/src/pages/ConfigEditor.tsx index dc351e7f7..58a36b65d 100644 --- a/web/src/pages/ConfigEditor.tsx +++ b/web/src/pages/ConfigEditor.tsx @@ -31,6 +31,7 @@ function ConfigEditor() { const editorRef = useRef(null); const modelRef = useRef(null); const configRef = useRef(null); + const schemaConfiguredRef = useRef(false); const onHandleSaveConfig = useCallback( async (save_option: SaveOptions) => { @@ -79,50 +80,59 @@ function ConfigEditor() { return; } - if (modelRef.current != null) { - // we don't need to recreate the editor if it already exists - editorRef.current?.layout(); - return; + const modelUri = monaco.Uri.parse( + `a://b/api/config/schema_${Date.now()}.json`, + ); + + // Configure Monaco YAML schema only once + if (!schemaConfiguredRef.current) { + configureMonacoYaml(monaco, { + enableSchemaRequest: true, + hover: true, + completion: true, + validate: true, + format: true, + schemas: [ + { + uri: `${apiHost}api/config/schema.json`, + fileMatch: [String(modelUri)], + }, + ], + }); + schemaConfiguredRef.current = true; } - const modelUri = monaco.Uri.parse("a://b/api/config/schema.json"); - - if (monaco.editor.getModels().length > 0) { - modelRef.current = monaco.editor.getModel(modelUri); - } else { + if (!modelRef.current) { modelRef.current = monaco.editor.createModel(config, "yaml", modelUri); + } else { + modelRef.current.setValue(config); } - configureMonacoYaml(monaco, { - enableSchemaRequest: true, - hover: true, - completion: true, - validate: true, - format: true, - schemas: [ - { - uri: `${apiHost}api/config/schema.json`, - fileMatch: [String(modelUri)], - }, - ], - }); - const container = configRef.current; - if (container != null) { + if (container && !editorRef.current) { editorRef.current = monaco.editor.create(container, { language: "yaml", model: modelRef.current, scrollBeyondLastLine: false, theme: (systemTheme || theme) == "dark" ? "vs-dark" : "vs-light", }); + } else if (editorRef.current) { + editorRef.current.setModel(modelRef.current); } return () => { - configRef.current = null; - modelRef.current = null; + if (editorRef.current) { + editorRef.current.dispose(); + editorRef.current = null; + } + if (modelRef.current) { + modelRef.current.dispose(); + modelRef.current = null; + } + schemaConfiguredRef.current = false; }; - }); + }, [config, apiHost, systemTheme, theme]); // monitoring state diff --git a/web/src/pages/Events.tsx b/web/src/pages/Events.tsx index bf9105131..fa582ca3b 100644 --- a/web/src/pages/Events.tsx +++ b/web/src/pages/Events.tsx @@ -14,6 +14,10 @@ import { ReviewSummary, SegmentedReviewData, } from "@/types/review"; +import { + getBeginningOfDayTimestamp, + getEndOfDayTimestamp, +} from "@/utils/dateUtil"; import EventView from "@/views/events/EventView"; import { RecordingView } from "@/views/recording/RecordingView"; import axios from "axios"; @@ -43,10 +47,17 @@ export default function Events() { .get(`review/${reviewId}`) .then((resp) => { if (resp.status == 200 && resp.data) { + const startTime = resp.data.start_time - REVIEW_PADDING; + const date = new Date(startTime * 1000); + + setReviewFilter({ + after: getBeginningOfDayTimestamp(date), + before: getEndOfDayTimestamp(date), + }); setRecording( { camera: resp.data.camera, - startTime: resp.data.start_time - REVIEW_PADDING, + startTime, severity: resp.data.severity, }, true, diff --git a/web/src/pages/Explore.tsx b/web/src/pages/Explore.tsx index 21ab01f71..a1be7badc 100644 --- a/web/src/pages/Explore.tsx +++ b/web/src/pages/Explore.tsx @@ -1,105 +1,60 @@ import { useApiFilterArgs } from "@/hooks/use-api-filter"; -import { useCameraPreviews } from "@/hooks/use-camera-previews"; -import { useOverlayState, useSearchEffect } from "@/hooks/use-overlay-state"; -import { FrigateConfig } from "@/types/frigateConfig"; -import { RecordingStartingPoint } from "@/types/record"; import { SearchFilter, SearchQuery, SearchResult } from "@/types/search"; -import { TimeRange } from "@/types/timeline"; -import { RecordingView } from "@/views/recording/RecordingView"; import SearchView from "@/views/search/SearchView"; import { useCallback, useEffect, useMemo, useState } from "react"; -import useSWR from "swr"; +import { TbExclamationCircle } from "react-icons/tb"; import useSWRInfinite from "swr/infinite"; const API_LIMIT = 25; export default function Explore() { - const { data: config } = useSWR("config", { - revalidateOnFocus: false, - }); - // search field handler - const [searchTimeout, setSearchTimeout] = useState(); const [search, setSearch] = useState(""); - const [searchTerm, setSearchTerm] = useState(""); - - const [recording, setRecording] = - useOverlayState("recording"); - - // search filter - - const similaritySearch = useMemo(() => { - if (!searchTerm.includes("similarity:")) { - return undefined; - } - - return searchTerm.split(":")[1]; - }, [searchTerm]); const [searchFilter, setSearchFilter, searchSearchParams] = useApiFilterArgs(); - // search api + const searchTerm = useMemo( + () => searchSearchParams?.["query"] || "", + [searchSearchParams], + ); - useSearchEffect("similarity_search_id", (similarityId) => { - setSearch(`similarity:${similarityId}`); - // @ts-expect-error we want to clear this - setSearchFilter({ ...searchFilter, similarity_search_id: undefined }); - return false; - }); + const similaritySearch = useMemo( + () => searchSearchParams["search_type"] == "similarity", + [searchSearchParams], + ); useEffect(() => { - if (searchTimeout) { - clearTimeout(searchTimeout); + if (!searchTerm && !search) { + return; } - setSearchTimeout( - setTimeout(() => { - setSearchTimeout(undefined); - setSearchTerm(search); - }, 750), - ); - // we only want to update the searchTerm when search changes + // switch back to normal search when query is entered + setSearchFilter({ + ...searchFilter, + search_type: + similaritySearch && search ? undefined : searchFilter?.search_type, + event_id: similaritySearch && search ? undefined : searchFilter?.event_id, + query: search.length > 0 ? search : undefined, + }); + // only update when search is updated // eslint-disable-next-line react-hooks/exhaustive-deps }, [search]); const searchQuery: SearchQuery = useMemo(() => { - if (similaritySearch) { - return [ - "events/search", - { - query: similaritySearch, - cameras: searchSearchParams["cameras"], - labels: searchSearchParams["labels"], - sub_labels: searchSearchParams["subLabels"], - zones: searchSearchParams["zones"], - before: searchSearchParams["before"], - after: searchSearchParams["after"], - include_thumbnails: 0, - search_type: "similarity", - }, - ]; + // no search parameters + if (searchSearchParams && Object.keys(searchSearchParams).length === 0) { + return null; } - if (searchTerm) { - return [ - "events/search", - { - query: searchTerm, - cameras: searchSearchParams["cameras"], - labels: searchSearchParams["labels"], - sub_labels: searchSearchParams["subLabels"], - zones: searchSearchParams["zones"], - before: searchSearchParams["before"], - after: searchSearchParams["after"], - search_type: searchSearchParams["search_type"], - include_thumbnails: 0, - }, - ]; - } - - if (searchSearchParams && Object.keys(searchSearchParams).length !== 0) { + // parameters, but no search term and not similarity + if ( + searchSearchParams && + Object.keys(searchSearchParams).length !== 0 && + !searchTerm && + !similaritySearch + ) { return [ "events", { @@ -118,15 +73,38 @@ export default function Explore() { ]; } - return null; + // parameters and search term + if (!similaritySearch) { + setSearch(searchTerm); + } + + return [ + "events/search", + { + query: similaritySearch ? undefined : searchTerm, + cameras: searchSearchParams["cameras"], + labels: searchSearchParams["labels"], + sub_labels: searchSearchParams["subLabels"], + zones: searchSearchParams["zones"], + before: searchSearchParams["before"], + after: searchSearchParams["after"], + search_type: searchSearchParams["search_type"], + event_id: searchSearchParams["event_id"], + include_thumbnails: 0, + }, + ]; }, [searchTerm, searchSearchParams, similaritySearch]); // paging + // usually slow only on first run while downloading models + const [isSlowLoading, setIsSlowLoading] = useState(false); + const getKey = ( pageIndex: number, previousPageData: SearchResult[] | null, ): SearchQuery => { + if (isSlowLoading && !similaritySearch) return null; if (previousPageData && !previousPageData.length) return null; // reached the end if (!searchQuery) return null; @@ -148,8 +126,14 @@ export default function Explore() { const { data, size, setSize, isValidating } = useSWRInfinite( getKey, { - revalidateFirstPage: false, + revalidateFirstPage: true, revalidateAll: false, + onLoadingSlow: () => { + if (!similaritySearch) { + setIsSlowLoading(true); + } + }, + loadingTimeout: 10000, }, ); @@ -180,108 +164,40 @@ export default function Explore() { } }, [isReachingEnd, isLoadingMore, setSize, size, searchResults, searchQuery]); - // previews - - const previewTimeRange = useMemo(() => { - if (!searchResults) { - return { after: 0, before: 0 }; - } - - return { - after: Math.min(...searchResults.map((res) => res.start_time)), - before: Math.max( - ...searchResults.map((res) => res.end_time ?? Date.now() / 1000), - ), - }; - }, [searchResults]); - - const allPreviews = useCameraPreviews(previewTimeRange, { - autoRefresh: false, - fetchPreviews: searchResults != undefined, - }); - - // selection - - const onOpenSearch = useCallback( - (item: SearchResult) => { - setRecording({ - camera: item.camera, - startTime: item.start_time, - severity: "alert", - }); - }, - [setRecording], - ); - - const selectedReviewData = useMemo(() => { - if (!recording) { - return undefined; - } - - if (!config) { - return undefined; - } - - if (!searchResults) { - return undefined; - } - - const allCameras = searchFilter?.cameras ?? Object.keys(config.cameras); - - return { - camera: recording.camera, - start_time: recording.startTime, - allCameras: allCameras, - }; - - // previews will not update after item is selected - // eslint-disable-next-line react-hooks/exhaustive-deps - }, [recording, searchResults]); - - const selectedTimeRange = useMemo(() => { - if (!recording) { - return undefined; - } - - const time = new Date(recording.startTime * 1000); - time.setUTCMinutes(0, 0, 0); - const start = time.getTime() / 1000; - time.setHours(time.getHours() + 2); - const end = time.getTime() / 1000; - return { - after: start, - before: end, - }; - }, [recording]); - - if (recording) { - if (selectedReviewData && selectedTimeRange) { - return ( - + {isSlowLoading && !similaritySearch ? ( +
+
+

Search Unavailable

+ +

+ If this is your first time using Search, be patient while Frigate + downloads the necessary embeddings models. Check Frigate logs. +

+
+
+ ) : ( + { + setSearchFilter({ + ...searchFilter, + search_type: ["similarity"], + event_id: search.id, + }); + }} + setSearchFilter={setSearchFilter} + onUpdateFilter={setSearchFilter} + loadMore={loadMore} + hasMore={!isReachingEnd} /> - ); - } - } else { - return ( - setSearch(`similarity:${search.id}`)} - onUpdateFilter={setSearchFilter} - onOpenSearch={onOpenSearch} - loadMore={loadMore} - hasMore={!isReachingEnd} - /> - ); - } + )} + + ); } diff --git a/web/src/types/search.ts b/web/src/types/search.ts index 762da2c82..c83e1aed2 100644 --- a/web/src/types/search.ts +++ b/web/src/types/search.ts @@ -29,6 +29,7 @@ export type SearchResult = { }; export type SearchFilter = { + query?: string; cameras?: string[]; labels?: string[]; subLabels?: string[]; @@ -54,4 +55,11 @@ export type SearchQueryParams = { page?: number; }; -export type SearchQuery = [string, SearchQueryParams] | null; \ No newline at end of file +export type SearchQuery = [string, SearchQueryParams] | null; +export type FilterType = Exclude; + +export type SavedSearchQuery = { + name: string; + search: string; + filter: SearchFilter | undefined; +}; diff --git a/web/src/utils/dateUtil.ts b/web/src/utils/dateUtil.ts index 3699d63f7..deb1dc850 100644 --- a/web/src/utils/dateUtil.ts +++ b/web/src/utils/dateUtil.ts @@ -285,6 +285,11 @@ export function endOfHourOrCurrentTime(timestamp: number) { return Math.min(timestamp, now.getTime() / 1000); } +export function getBeginningOfDayTimestamp(date: Date) { + date.setHours(0, 0, 0, 0); + return date.getTime() / 1000; +} + export function getEndOfDayTimestamp(date: Date) { date.setHours(23, 59, 59, 999); return date.getTime() / 1000; @@ -296,3 +301,75 @@ export function isCurrentHour(timestamp: number) { return timestamp > now.getTime() / 1000; } + +export const convertLocalDateToTimestamp = (dateString: string): number => { + // Ensure the date string is in the correct format (8 digits) + if (!/^\d{8}$/.test(dateString)) { + return 0; + } + + // Determine the local date format + const format = new Intl.DateTimeFormat() + .formatToParts(new Date()) + .reduce((acc, part) => { + if (part.type === "day") acc.push("D"); + if (part.type === "month") acc.push("M"); + if (part.type === "year") acc.push("Y"); + return acc; + }, [] as string[]) + .join(""); + + let day: string, month: string, year: string; + + // Parse the date string according to the detected format + switch (format) { + case "DMY": + [day, month, year] = [ + dateString.slice(0, 2), + dateString.slice(2, 4), + dateString.slice(4), + ]; + break; + case "MDY": + [month, day, year] = [ + dateString.slice(0, 2), + dateString.slice(2, 4), + dateString.slice(4), + ]; + break; + case "YMD": + [year, month, day] = [ + dateString.slice(0, 2), + dateString.slice(2, 4), + dateString.slice(4), + ]; + break; + default: + return 0; + } + + // Create a Date object based on the local timezone + const localDate = new Date(`${year}-${month}-${day}T00:00:00`); + + // Check if the date is valid + if (isNaN(localDate.getTime())) { + return 0; + } + + // Convert local date to UTC timestamp + const timestamp = localDate.getTime(); + + return timestamp; +}; + +export function getIntlDateFormat() { + return new Intl.DateTimeFormat() + .formatToParts(new Date()) + .reduce((acc, part) => { + if (part.type === "day") acc.push("DD"); + if (part.type === "month") acc.push("MM"); + if (part.type === "year") acc.push("YYYY"); + return acc; + }, [] as string[]) + .join(""); +} diff --git a/web/src/views/search/SearchView.tsx b/web/src/views/search/SearchView.tsx index e031d211c..56257ee3e 100644 --- a/web/src/views/search/SearchView.tsx +++ b/web/src/views/search/SearchView.tsx @@ -3,7 +3,6 @@ import SearchFilterGroup from "@/components/filter/SearchFilterGroup"; import ActivityIndicator from "@/components/indicators/activity-indicator"; import Chip from "@/components/indicators/Chip"; import SearchDetailDialog from "@/components/overlay/detail/SearchDetailDialog"; -import { Input } from "@/components/ui/input"; import { Toaster } from "@/components/ui/sonner"; import { Tooltip, @@ -12,16 +11,17 @@ import { } from "@/components/ui/tooltip"; import { cn } from "@/lib/utils"; import { FrigateConfig } from "@/types/frigateConfig"; -import { SearchFilter, SearchResult } from "@/types/search"; +import { SearchFilter, SearchResult, SearchSource } from "@/types/search"; import { useCallback, useEffect, useMemo, useRef, useState } from "react"; import { isMobileOnly } from "react-device-detect"; -import { LuImage, LuSearchX, LuText, LuXCircle } from "react-icons/lu"; +import { LuImage, LuSearchX, LuText } from "react-icons/lu"; import useSWR from "swr"; import ExploreView from "../explore/ExploreView"; import useKeyboardListener, { KeyModifiers, } from "@/hooks/use-keyboard-listener"; import scrollIntoView from "scroll-into-view-if-needed"; +import InputWithTags from "@/components/input/InputWithTags"; type SearchViewProps = { search: string; @@ -31,8 +31,8 @@ type SearchViewProps = { isLoading: boolean; setSearch: (search: string) => void; setSimilaritySearch: (search: SearchResult) => void; + setSearchFilter: (filter: SearchFilter) => void; onUpdateFilter: (filter: SearchFilter) => void; - onOpenSearch: (item: SearchResult) => void; loadMore: () => void; hasMore: boolean; }; @@ -44,6 +44,7 @@ export default function SearchView({ isLoading, setSearch, setSimilaritySearch, + setSearchFilter, onUpdateFilter, loadMore, hasMore, @@ -52,6 +53,69 @@ export default function SearchView({ revalidateOnFocus: false, }); + // suggestions values + + const allLabels = useMemo(() => { + if (!config) { + return []; + } + + const labels = new Set(); + const cameras = searchFilter?.cameras || Object.keys(config.cameras); + + cameras.forEach((camera) => { + if (camera == "birdseye") { + return; + } + const cameraConfig = config.cameras[camera]; + cameraConfig.objects.track.forEach((label) => { + labels.add(label); + }); + + if (cameraConfig.audio.enabled_in_config) { + cameraConfig.audio.listen.forEach((label) => { + labels.add(label); + }); + } + }); + + return [...labels].sort(); + }, [config, searchFilter]); + + const { data: allSubLabels } = useSWR("sub_labels"); + + const allZones = useMemo(() => { + if (!config) { + return []; + } + + const zones = new Set(); + const cameras = searchFilter?.cameras || Object.keys(config.cameras); + + cameras.forEach((camera) => { + if (camera == "birdseye") { + return; + } + const cameraConfig = config.cameras[camera]; + Object.entries(cameraConfig.zones).map(([name, _]) => { + zones.add(name); + }); + }); + + return [...zones].sort(); + }, [config, searchFilter]); + + const suggestionsValues = useMemo( + () => ({ + cameras: Object.keys(config?.cameras || {}), + labels: Object.values(allLabels || {}), + zones: Object.values(allZones || {}), + sub_labels: allSubLabels, + search_type: ["thumbnail", "description"] as SearchSource[], + }), + [config, allLabels, allZones, allSubLabels], + ); + // remove duplicate event ids const uniqueResults = useMemo(() => { @@ -192,7 +256,7 @@ export default function SearchView({
{config?.semantic_search?.enabled && ( -
- setSearch(e.target.value)} +
+ - {search && ( - setSearch("")} - /> - )}
)} @@ -227,7 +281,6 @@ export default function SearchView({ "w-full justify-between md:justify-start lg:justify-end", )} filter={searchFilter} - searchTerm={searchTerm} onUpdateFilter={onUpdateFilter} /> )}