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docs for pi support
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22
README.md
22
README.md
@@ -74,7 +74,9 @@ docker create \
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-v <path/to/tvseries>:/data/tvshows \
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-v </path/to/movies>:/data/movies \
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-v </path for transcoding>:/transcode `#optional` \
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-v /opt/vc/lib:/opt/vc/lib `#optional` \
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--device /dev/dri:/dev/dri `#optional` \
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--device /dev/vchiq:/dev/vchiq `#optional` \
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--restart unless-stopped \
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linuxserver/jellyfin
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```
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@@ -101,11 +103,13 @@ services:
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- <path/to/tvseries>:/data/tvshows
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- </path/to/movies>:/data/movies
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- </path for transcoding>:/transcode #optional
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- /opt/vc/lib:/opt/vc/lib #optional
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ports:
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- 8096:8096
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- 8920:8920 #optional
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devices:
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- /dev/dri:/dev/dri #optional
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- /dev/vchiq:/dev/vchiq #optional
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restart: unless-stopped
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```
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@@ -125,7 +129,9 @@ Container images are configured using parameters passed at runtime (such as thos
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| `-v /data/tvshows` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
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| `-v /data/movies` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
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| `-v /transcode` | Path for transcoding folder, *optional*. |
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| `-v /opt/vc/lib` | Path for Rasberry Pi OpenMAX libs *optional*. |
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| `--device /dev/dri` | Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi). |
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| `--device /dev/vchiq` | Only needed if you want to use your Rasberry Pi OpenMax video encoding (Bellagio). |
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## Environment variables from files (Docker secrets)
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@@ -160,18 +166,33 @@ Webui can be found at `http://<your-ip>:8096`
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More information can be found in their official documentation [here](https://github.com/MediaBrowser/Wiki/wiki) .
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## Hardware Acceleration
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### Intel
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Hardware acceleration users for Intel Quicksync will need to mount their /dev/dri video device inside of the container by passing the following command when running or creating the container:
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```--device=/dev/dri:/dev/dri```
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We will automatically ensure the abc user inside of the container has the proper permissions to access this device.
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### Nvidia
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Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
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https://github.com/NVIDIA/nvidia-docker
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We automatically add the necessary environment variable that will utilise all the features available on a GPU on the host. Once nvidia-docker is installed on your host you will need to re/create the docker container with the nvidia container runtime `--runtime=nvidia` and add an environment variable `-e NVIDIA_VISIBLE_DEVICES=all` (can also be set to a specific gpu's UUID, this can be discovered by running `nvidia-smi --query-gpu=gpu_name,gpu_uuid --format=csv` ). NVIDIA automatically mounts the GPU and drivers from your host into the jellyfin docker container.
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### OpenMAX (Rasberry Pi)
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Hardware acceleration users for Rasberry Pi OpenMAX will need to mount their /dev/vchiq video device inside of the container and their system OpenMax libs by passing the following options when running or creating the container:
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```
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--device=/dev/vchiq:/dev/vchiq
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-v /opt/vc/lib:/opt/vc/lib
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```
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## Support Info
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@@ -238,6 +259,7 @@ Once registered you can define the dockerfile to use with `-f Dockerfile.aarch64
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## Versions
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* **09.01.20:** - Add Pi OpenMax support.
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* **02.10.19:** - Improve permission fixing for render & dvb devices.
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* **31.07.19:** - Add AMD drivers for vaapi support on x86.
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* **13.06.19:** - Add Intel drivers for vaapi support on x86.
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