![]() | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. How you do this depends on how Docker is being run: Docker Compose - Nvidia GPU The supported method for this is to install the NVIDIA Container Toolkit and specify the GPU to Docker. Configuring Nvidia GPUs in Docker Īdditional configuration is needed for the Docker container to be able to access the NVIDIA GPU. If your distribution does not offer NVIDIA driver packages, you can download them here. The only way around this is to provide your own FFmpeg that will work with your driver version, but this is unsupported and may not work well if at all.Ī more complete list of cards and their compatible drivers is available in the driver release readme. YUV 4:2:0 means that each 2x2 block of luma samples shares a single pair of chroma (UV) samples. Lets for example consider a video with the incredibly high resolution 4x4 pixels. Older driver versions may be missing symbols and fail to work, and older cards are not supported by newer driver versions. yuv420p planar 8-bit YUV 4:2:0 nv12 semi-planar 8-bit YUV 4:2:0 They contain the same data, the only difference is how it is arranged in memory. However, you must also use a driver version that will work with FFmpeg. If your card is on the list and supports CUVID/NVDEC, it will most likely work with Frigate for decoding. NVIDIA provides a matrix of supported GPUs and features. While older GPUs may work, it is recommended to use modern, supported GPUs.
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