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106 lines
4.7 KiB
Markdown
106 lines
4.7 KiB
Markdown
# nVidia hardware decoder (NVDEC)
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Certain nvidia cards include a hardware decoder, which can greatly improve the
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performance of video decoding. In order to use NVDEC, a special build of
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ffmpeg with NVDEC support is required. The special docker architecture 'amd64nvidia'
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includes this support for amd64 platforms. An aarch64 for the Jetson, which
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also includes NVDEC may be added in the future.
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## Docker setup
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### Requirements
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[nVidia closed source driver](https://www.nvidia.com/en-us/drivers/unix/) required to access NVDEC.
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[nvidia-docker](https://github.com/NVIDIA/nvidia-docker) required to pass NVDEC to docker.
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### Setting up docker-compose
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In order to pass NVDEC, the docker engine must be set to `nvidia` and the environment variables
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`NVIDIA_VISIBLE_DEVICES=all` and `NVIDIA_DRIVER_CAPABILITIES=compute,utility,video` must be set.
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In a docker compose file, these lines need to be set:
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```
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services:
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frigate:
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...
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image: blakeblackshear/frigate:stable-amd64nvidia
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runtime: nvidia
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environment:
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- NVIDIA_VISIBLE_DEVICES=all
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- NVIDIA_DRIVER_CAPABILITIES=compute,utility,video
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```
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### Setting up the configuration file
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In your frigate config.yml, you'll need to set ffmpeg to use the hardware decoder.
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The decoder you choose will depend on the input video.
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A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the container to get a list)
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```
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V..... h263_cuvid Nvidia CUVID H263 decoder (codec h263)
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V..... h264_cuvid Nvidia CUVID H264 decoder (codec h264)
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V..... hevc_cuvid Nvidia CUVID HEVC decoder (codec hevc)
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V..... mjpeg_cuvid Nvidia CUVID MJPEG decoder (codec mjpeg)
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V..... mpeg1_cuvid Nvidia CUVID MPEG1VIDEO decoder (codec mpeg1video)
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V..... mpeg2_cuvid Nvidia CUVID MPEG2VIDEO decoder (codec mpeg2video)
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V..... mpeg4_cuvid Nvidia CUVID MPEG4 decoder (codec mpeg4)
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V..... vc1_cuvid Nvidia CUVID VC1 decoder (codec vc1)
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V..... vp8_cuvid Nvidia CUVID VP8 decoder (codec vp8)
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V..... vp9_cuvid Nvidia CUVID VP9 decoder (codec vp9)
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```
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For example, for H265 video (hevc), you'll select `hevc_cuvid`. Add
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`-c:v hevc_covid` to your ffmpeg input arguments:
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```
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ffmpeg:
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input_args:
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...
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- -c:v
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- hevc_cuvid
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```
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If everything is working correctly, you should see a significant improvement in performance.
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Verify that hardware decoding is working by running `nvidia-smi`, which should show the ffmpeg
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processes:
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```
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+-----------------------------------------------------------------------------+
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| NVIDIA-SMI 455.38 Driver Version: 455.38 CUDA Version: 11.1 |
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|-------------------------------+----------------------+----------------------+
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| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
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| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
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| | | MIG M. |
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|===============================+======================+======================|
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| 0 GeForce GTX 166... Off | 00000000:03:00.0 Off | N/A |
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| 38% 41C P2 36W / 125W | 2082MiB / 5942MiB | 5% Default |
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| | | N/A |
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+-------------------------------+----------------------+----------------------+
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+-----------------------------------------------------------------------------+
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| Processes: |
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| GPU GI CI PID Type Process name GPU Memory |
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| ID ID Usage |
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|=============================================================================|
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| 0 N/A N/A 12737 C ffmpeg 249MiB |
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| 0 N/A N/A 12751 C ffmpeg 249MiB |
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| 0 N/A N/A 12772 C ffmpeg 249MiB |
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| 0 N/A N/A 12775 C ffmpeg 249MiB |
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| 0 N/A N/A 12800 C ffmpeg 249MiB |
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| 0 N/A N/A 12811 C ffmpeg 417MiB |
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| 0 N/A N/A 12827 C ffmpeg 417MiB |
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+-----------------------------------------------------------------------------+
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```
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To further improve performance, you can set ffmpeg to skip frames in the output,
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using the fps filter:
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```
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output_args:
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- -filter:v
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- fps=fps=5
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```
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This setting, for example, allows Frigate to consume my 10-15fps camera streams on
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my relatively low powered Haswell machine with relatively low cpu usage.
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