Add static FFmpeg with rockchip hardware acceleration to rk- image (#8599)

* add static ffmpeg with rockchip hw accel

* add ffmpeg presets

* fix scaling preset and update docs for rk hwaccel

* update usage info in ffmpeg_presets docs

* Add note about hardware acceleration support

---------

Co-authored-by: MarcA711 <>
This commit is contained in:
Marc Altmann 2023-11-15 12:41:55 +01:00 committed by GitHub
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commit 8c7f6d4a76
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4 changed files with 49 additions and 3 deletions

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@ -6,12 +6,13 @@ ARG DEBIAN_FRONTEND=noninteractive
FROM wheels as rk-wheels FROM wheels as rk-wheels
COPY docker/main/requirements-wheels.txt /requirements-wheels.txt COPY docker/main/requirements-wheels.txt /requirements-wheels.txt
COPY docker/rockchip/requirements-wheels-rk.txt /requirements-wheels-rk.txt COPY docker/rockchip/requirements-wheels-rk.txt /requirements-wheels-rk.txt
RUN sed -i "/https/d" /requirements-wheels.txt RUN sed -i "/https:\/\//d" /requirements-wheels.txt
RUN pip3 wheel --wheel-dir=/rk-wheels -c /requirements-wheels.txt -r /requirements-wheels-rk.txt RUN pip3 wheel --wheel-dir=/rk-wheels -c /requirements-wheels.txt -r /requirements-wheels-rk.txt
FROM wget as rk-libs FROM wget as rk-libs
RUN wget -qO librknnrt.so https://github.com/MarcA711/rknpu2/raw/master/runtime/RK3588/Linux/librknn_api/aarch64/librknnrt.so RUN wget -qO librknnrt.so https://github.com/MarcA711/rknpu2/raw/master/runtime/RK3588/Linux/librknn_api/aarch64/librknnrt.so
RUN wget -qO ffmpeg https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/latest/ffmpeg
RUN wget -qO ffprobe https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/latest/ffprobe
FROM deps AS rk-deps FROM deps AS rk-deps
ARG TARGETARCH ARG TARGETARCH
@ -21,4 +22,11 @@ RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \
WORKDIR /opt/frigate/ WORKDIR /opt/frigate/
COPY --from=rootfs / / COPY --from=rootfs / /
COPY --from=rk-libs /rootfs/librknnrt.so /usr/lib/ COPY --from=rk-libs /rootfs/librknnrt.so /usr/lib/
COPY docker/rockchip/yolov8n-320x320.rknn /models/ COPY docker/rockchip/yolov8n-320x320.rknn /models/
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffmpeg
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffprobe
COPY --from=rk-libs /rootfs/ffmpeg /usr/lib/btbn-ffmpeg/bin/
COPY --from=rk-libs /rootfs/ffprobe /usr/lib/btbn-ffmpeg/bin/
RUN chmod +x /usr/lib/btbn-ffmpeg/bin/ffmpeg
RUN chmod +x /usr/lib/btbn-ffmpeg/bin/ffprobe

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@ -22,6 +22,8 @@ See [the hwaccel docs](/configuration/hardware_acceleration.md) for more info on
| preset-nvidia-mjpeg | Nvidia GPU with mjpeg stream | Recommend restreaming mjpeg and using nvidia-h264 | | preset-nvidia-mjpeg | Nvidia GPU with mjpeg stream | Recommend restreaming mjpeg and using nvidia-h264 |
| preset-jetson-h264 | Nvidia Jetson with h264 stream | | | preset-jetson-h264 | Nvidia Jetson with h264 stream | |
| preset-jetson-h265 | Nvidia Jetson with h265 stream | | | preset-jetson-h265 | Nvidia Jetson with h265 stream | |
| preset-rk-h264 | Rockchip MPP with h264 stream | Use image with *-rk suffix and privileged mode |
| preset-rk-h265 | Rockchip MPP with h265 stream | Use image with *-rk suffix and privileged mode |
### Input Args Presets ### Input Args Presets

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@ -319,3 +319,31 @@ ffmpeg:
If everything is working correctly, you should see a significant reduction in ffmpeg CPU load and power consumption. If everything is working correctly, you should see a significant reduction in ffmpeg CPU load and power consumption.
Verify that hardware decoding is working by running `jtop` (`sudo pip3 install -U jetson-stats`), which should show Verify that hardware decoding is working by running `jtop` (`sudo pip3 install -U jetson-stats`), which should show
that NVDEC/NVDEC1 are in use. that NVDEC/NVDEC1 are in use.
## Rockchip platform
Hardware accelerated video de-/encoding is supported on all Rockchip SoCs.
### Setup
Use a frigate docker image with `-rk` suffix and enable privileged mode by adding the `--privileged` flag to your docker run command or `privileged: true` to your `docker-compose.yml` file.
### Configuration
Add one of the following ffmpeg presets to your `config.yaml` to enable hardware acceleration:
```yaml
# if you try to decode a h264 encoded stream
ffmpeg:
hwaccel_args: preset-rk-h264
# if you try to decode a h265 (hevc) encoded stream
ffmpeg:
hwaccel_args: preset-rk-h265
```
:::note
Make sure that your SoC supports hardware acceleration for your input stream. For example, if your camera streams with h265 encoding and a 4k resolution, your SoC must be able to de- and encode h265 with a 4k resolution or higher. If you are unsure whether your SoC meets the requirements, take a look at the datasheet.
:::

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@ -64,6 +64,8 @@ PRESETS_HW_ACCEL_DECODE = {
"preset-nvidia-mjpeg": "-hwaccel cuda -hwaccel_output_format cuda", "preset-nvidia-mjpeg": "-hwaccel cuda -hwaccel_output_format cuda",
"preset-jetson-h264": "-c:v h264_nvmpi -resize {1}x{2}", "preset-jetson-h264": "-c:v h264_nvmpi -resize {1}x{2}",
"preset-jetson-h265": "-c:v hevc_nvmpi -resize {1}x{2}", "preset-jetson-h265": "-c:v hevc_nvmpi -resize {1}x{2}",
"preset-rk-h264": "-c:v h264_rkmpp_decoder",
"preset-rk-h265": "-c:v hevc_rkmpp_decoder",
} }
PRESETS_HW_ACCEL_SCALE = { PRESETS_HW_ACCEL_SCALE = {
@ -75,6 +77,8 @@ PRESETS_HW_ACCEL_SCALE = {
"preset-nvidia-h265": "-r {0} -vf fps={0},scale_cuda=w={1}:h={2}:format=nv12,hwdownload,format=nv12,format=yuv420p", "preset-nvidia-h265": "-r {0} -vf fps={0},scale_cuda=w={1}:h={2}:format=nv12,hwdownload,format=nv12,format=yuv420p",
"preset-jetson-h264": "-r {0}", # scaled in decoder "preset-jetson-h264": "-r {0}", # scaled in decoder
"preset-jetson-h265": "-r {0}", # scaled in decoder "preset-jetson-h265": "-r {0}", # scaled in decoder
"preset-rk-h264": "-r {0} -vf fps={0},scale={1}:{2}",
"preset-rk-h265": "-r {0} -vf fps={0},scale={1}:{2}",
"default": "-r {0} -vf fps={0},scale={1}:{2}", "default": "-r {0} -vf fps={0},scale={1}:{2}",
} }
@ -87,6 +91,8 @@ PRESETS_HW_ACCEL_ENCODE_BIRDSEYE = {
"preset-nvidia-h265": "ffmpeg -hide_banner {0} -c:v h264_nvenc -g 50 -profile:v high -level:v auto -preset:v p2 -tune:v ll {1}", "preset-nvidia-h265": "ffmpeg -hide_banner {0} -c:v h264_nvenc -g 50 -profile:v high -level:v auto -preset:v p2 -tune:v ll {1}",
"preset-jetson-h264": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}", "preset-jetson-h264": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}",
"preset-jetson-h265": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}", "preset-jetson-h265": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}",
"preset-rk-h264": "ffmpeg -hide_banner {0} -c:v h264_rkmpp_encoder -profile high {1}",
"preset-rk-h265": "ffmpeg -hide_banner {0} -c:v hevc_rkmpp_encoder -profile high {1}",
"default": "ffmpeg -hide_banner {0} -c:v libx264 -g 50 -profile:v high -level:v 4.1 -preset:v superfast -tune:v zerolatency {1}", "default": "ffmpeg -hide_banner {0} -c:v libx264 -g 50 -profile:v high -level:v 4.1 -preset:v superfast -tune:v zerolatency {1}",
} }
@ -99,6 +105,8 @@ PRESETS_HW_ACCEL_ENCODE_TIMELAPSE = {
"preset-nvidia-h265": "ffmpeg -hide_banner -hwaccel cuda -hwaccel_output_format cuda -extra_hw_frames 8 {0} -c:v hevc_nvenc {1}", "preset-nvidia-h265": "ffmpeg -hide_banner -hwaccel cuda -hwaccel_output_format cuda -extra_hw_frames 8 {0} -c:v hevc_nvenc {1}",
"preset-jetson-h264": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}", "preset-jetson-h264": "ffmpeg -hide_banner {0} -c:v h264_nvmpi -profile high {1}",
"preset-jetson-h265": "ffmpeg -hide_banner {0} -c:v hevc_nvmpi -profile high {1}", "preset-jetson-h265": "ffmpeg -hide_banner {0} -c:v hevc_nvmpi -profile high {1}",
"preset-rk-h264": "ffmpeg -hide_banner {0} -c:v h264_rkmpp_encoder -profile high {1}",
"preset-rk-h265": "ffmpeg -hide_banner {0} -c:v hevc_rkmpp_encoder -profile high {1}",
"default": "ffmpeg -hide_banner {0} -c:v libx264 -preset:v ultrafast -tune:v zerolatency {1}", "default": "ffmpeg -hide_banner {0} -c:v libx264 -preset:v ultrafast -tune:v zerolatency {1}",
} }