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LinuxServer-CI 2020-01-10 07:04:19 -05:00
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@ -47,7 +47,9 @@ docker create \
-v <path/to/tvseries>:/data/tvshows \
-v </path/to/movies>:/data/movies \
-v </path for transcoding>:/transcode `#optional` \
-v /opt/vc/lib:/opt/vc/lib `#optional` \
--device /dev/dri:/dev/dri `#optional` \
--device /dev/vchiq:/dev/vchiq `#optional` \
--restart unless-stopped \
linuxserver/jellyfin
```
@ -75,12 +77,14 @@ services:
- </path/to/movies>:/data/movies
volumes:
- </path for transcoding>:/transcode #optional
- /opt/vc/lib:/opt/vc/lib #optional
ports:
- 8096:8096
ports:
- 8920:8920 #optional
devices:
- /dev/dri:/dev/dri #optional
- /dev/vchiq:/dev/vchiq #optional
restart: unless-stopped
```
@ -113,11 +117,13 @@ Docker images are configured using parameters passed at runtime (such as those a
| `/data/tvshows` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
| `/data/movies` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
| `/transcode` | Path for transcoding folder, *optional*. |
| `/opt/vc/lib` | Path for Raspberry Pi OpenMAX libs *optional*. |
#### Device Mappings (`--device`)
| Parameter | Function |
| :-----: | --- |
| `/dev/dri` | Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi). |
| `/dev/vchiq` | Only needed if you want to use your Raspberry Pi OpenMax video encoding (Bellagio). |
## User / Group Identifiers
@ -139,18 +145,33 @@ Webui can be found at `http://<your-ip>:8096`
More information can be found in their official documentation [here](https://github.com/MediaBrowser/Wiki/wiki) .
## Hardware Acceleration
### Intel
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:
```--device=/dev/dri:/dev/dri```
We will automatically ensure the abc user inside of the container has the proper permissions to access this device.
### Nvidia
Hardware acceleration users for Nvidia will need to install the container runtime provided by Nvidia on their host, instructions can be found here:
https://github.com/NVIDIA/nvidia-docker
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.
### OpenMAX (Raspberry Pi)
Hardware acceleration users for Raspberry 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:
```
--device=/dev/vchiq:/dev/vchiq
-v /opt/vc/lib:/opt/vc/lib
```
## Support Info
@ -166,6 +187,7 @@ We automatically add the necessary environment variable that will utilise all th
## Versions
* **09.01.20:** - Add Pi OpenMax support.
* **02.10.19:** - Improve permission fixing for render & dvb devices.
* **31.07.19:** - Add AMD drivers for vaapi support on x86.
* **13.06.19:** - Add Intel drivers for vaapi support on x86.