update nvidia docs.
This commit is contained in:
Miroslav Šedivý
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14777501ee
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7b7c876775
3 changed files with 39 additions and 6 deletions
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@ -279,6 +279,33 @@ See documentation for [ximagesrc](https://gstreamer.freedesktop.org/documentatio
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This configuration requires [Nvidia GPU](https://developer.nvidia.com/cuda-gpus) with [NVENC](https://developer.nvidia.com/nvidia-video-codec-sdk) support.
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```yaml title="config.yaml"
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capture:
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video:
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codec: h264
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ids: [ main ]
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pipelines:
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main:
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gst_pipeline: |
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ximagesrc display-name={display} show-pointer=true use-damage=false
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! cudaupload ! cudaconvert ! queue
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! video/x-raw(memory:CUDAMemory),format=NV12
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! nvh264enc
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name=encoder
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preset=2
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gop-size=25
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spatial-aq=true
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temporal-aq=true
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bitrate=4096
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vbv-buffer-size=4096
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rc-mode=6
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! h264parse config-interval=-1
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! video/x-h264,stream-format=byte-stream
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! appsink name=appsink
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```
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This configuration requires [Nvidia GPU](https://developer.nvidia.com/cuda-gpus) with [NVENC](https://developer.nvidia.com/nvidia-video-codec-sdk) support and [Cuda](https://developer.nvidia.com/cuda-zone) support.
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</TabItem>
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</Tabs>
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@ -241,7 +241,7 @@ For images with Nvidia GPU hardware acceleration using EGL use:
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- [`ghcr.io/m1k1o/neko/nvidia-microsoft-edge`](https://ghcr.io/m1k1o/neko/nvidia-microsoft-edge)
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- [`ghcr.io/m1k1o/neko/nvidia-brave`](https://ghcr.io/m1k1o/neko/nvidia-brave)
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The base image is available at [`ghcr.io/m1k1o/neko/nvidia-base`](https://ghcr.io/m1k1o/neko/nvidia-base).
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The base image is available at [`ghcr.io/m1k1o/neko/nvidia-base`](https://ghcr.io/m1k1o/neko/nvidia-base). See [Examples](/docs/v3/installation/examples#nvidia) for more information and usage.
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## Supported Architectures {#arch}
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@ -113,9 +113,9 @@ services:
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## Nvidia GPU Acceleration {#nvidia}
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Neko supports hardware acceleration using Nvidia GPUs. To use this feature, you need to have the Nvidia Container Toolkit installed on your system. You can find the installation instructions [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html).
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Neko supports hardware acceleration using Nvidia GPUs. To use this feature, you need to have the Nvidia Container Toolkit installed on your system. You can find the installation instructions [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html). Check if your GPU supports hardware encoding with [this list](https://developer.nvidia.com/video-encode-decode-gpu-support-matrix).
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This example shows how to accelerate video encoding and as well the browser rendering using the GPU. You can test if the GPU is used by running `nvidia-smi`, which should show the GPU usage of both the browser and neko. In the browser, you can run the [WebGL Aquarium Demo](https://webglsamples.org/aquarium/aquarium.html) to test the GPU usage.
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This example shows how to accelerate video encoding and as well the browser rendering using the GPU. You can test if the GPU is used by running `nvtop` or `nvidia-smi`, which should show the GPU usage of both the browser and neko. In the browser, you can run the [WebGL Aquarium Demo](https://webglsamples.org/aquarium/aquarium.html) to test the GPU usage.
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```yaml title="docker-compose.yaml"
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services:
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@ -130,8 +130,8 @@ services:
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NEKO_CAPTURE_VIDEO_PIPELINE: |
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ximagesrc display-name={display} show-pointer=true use-damage=false
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! video/x-raw,framerate=25/1
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! videoconvert ! queue
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! video/x-raw,format=NV12
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! cudaupload ! cudaconvert ! queue
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! video/x-raw(memory:CUDAMemory),format=NV12
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! nvh264enc
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name=encoder
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preset=2
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@ -161,7 +161,11 @@ services:
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See available [Nvidia Docker Images](/docs/v3/installation/docker-images#nvidia).
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If you only want to accelerate the encoding, **not the browser rendering**, you can use the default image with additional environment variables:
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:::note
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If your Nvidia GPU does not support CUDA, you can use the pipeline below without `cudaupload` and `cudaconvert`. This should work with older GPUs, but the performance might be lower.
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:::
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If you only want to accelerate the encoding, **not the browser rendering**, and you do not need [Cuda library](https://gstreamer.freedesktop.org/documentation/cuda/index.html?gi-language=c), you can use the default image with additional environment variables:
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```yaml title="docker-compose.yaml"
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services:
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@ -181,8 +185,10 @@ services:
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NEKO_CAPTURE_VIDEO_PIPELINE: |
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ximagesrc display-name={display} show-pointer=true use-damage=false
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! video/x-raw,framerate=25/1
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# highlight-start
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! videoconvert ! queue
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! video/x-raw,format=NV12
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# highlight-end
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! nvh264enc
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name=encoder
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preset=2
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