11 KiB
linuxserver/jellyfin
Jellyfin is a Free Software Media System that puts you in control of managing and streaming your media. It is an alternative to the proprietary Emby and Plex, to provide media from a dedicated server to end-user devices via multiple apps. Jellyfin is descended from Emby's 3.5.2 release and ported to the .NET Core framework to enable full cross-platform support. There are no strings attached, no premium licenses or features, and no hidden agendas: just a team who want to build something better and work together to achieve it.
Supported Architectures
Our images support multiple architectures such as x86-64, arm64 and armhf. We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.
Simply pulling linuxserver/jellyfin should retrieve the correct image for your arch, but you can also pull specific arch images via tags.
The architectures supported by this image are:
| Architecture | Tag |
|---|---|
| x86-64 | amd64-latest |
| arm64 | arm64v8-latest |
| armhf | arm32v7-latest |
Version Tags
This image provides various versions that are available via tags. latest tag usually provides the latest stable version. Others are considered under development and caution must be exercised when using them.
| Tag | Description |
|---|---|
| latest | Stable Jellyfin releases |
| nightly | Nightly Jellyfin releases |
Usage
Here are some example snippets to help you get started creating a container from this image.
docker
docker create \
--name=jellyfin \
-e PUID=1000 \
-e PGID=1000 \
-e TZ=Europe/London \
-e UMASK_SET=<022> `#optional` \
-p 8096:8096 \
-p 8920:8920 `#optional` \
-v /path/to/library:/config \
-v /path/to/tvseries:/data/tvshows \
-v /path/to/movies:/data/movies \
-v /opt/vc/lib:/opt/vc/lib `#optional` \
--device /dev/dri:/dev/dri `#optional` \
--device /dev/vc-mem:/dev/vc-mem `#optional` \
--device /dev/vchiq:/dev/vchiq `#optional` \
--device /dev/video10:/dev/video10 `#optional` \
--device /dev/video11:/dev/video11 `#optional` \
--device /dev/video12:/dev/video12 `#optional` \
--restart unless-stopped \
linuxserver/jellyfin
docker-compose
Compatible with docker-compose v2 schemas.
---
version: "2.1"
services:
jellyfin:
image: linuxserver/jellyfin
container_name: jellyfin
environment:
- PUID=1000
- PGID=1000
- TZ=Europe/London
- UMASK_SET=<022> #optional
volumes:
- /path/to/library:/config
- /path/to/tvseries:/data/tvshows
- /path/to/movies:/data/movies
volumes:
- /opt/vc/lib:/opt/vc/lib #optional
ports:
- 8096:8096
ports:
- 8920:8920 #optional
devices:
- /dev/dri:/dev/dri #optional
- /dev/vc-mem:/dev/vc-mem #optional
- /dev/vchiq:/dev/vchiq #optional
- /dev/video10:/dev/video10 #optional
- /dev/video11:/dev/video11 #optional
- /dev/video12:/dev/video12 #optional
restart: unless-stopped
Parameters
Docker images are configured using parameters passed at runtime (such as those above). These parameters are separated by a colon and indicate <external>:<internal> respectively. For example, -p 8080:80 would expose port 80 from inside the container to be accessible from the host's IP on port 8080 outside the container.
Ports (-p)
| Parameter | Function |
|---|---|
8096 |
Http webUI. |
8920 |
Https webUI (you need to set up your own certificate). |
Environment Variables (-e)
| Env | Function |
|---|---|
PUID=1000 |
for UserID - see below for explanation |
PGID=1000 |
for GroupID - see below for explanation |
TZ=Europe/London |
Specify a timezone to use EG Europe/London |
UMASK_SET=<022> |
for umask setting of Emby, default if left unset is 022. |
Volume Mappings (-v)
| Volume | Function |
|---|---|
/config |
Jellyfin data storage location. This can grow very large, 50gb+ is likely for a large collection. |
/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. |
/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/vc-mem |
Only needed if you want to use your Raspberry Pi MMAL video decoding (Enabled as OpenMax H264 decode in gui settings). |
/dev/vchiq |
Only needed if you want to use your Raspberry Pi OpenMax video encoding. |
/dev/video10 |
Only needed if you want to use your Raspberry Pi V4L2 video encoding. |
/dev/video11 |
Only needed if you want to use your Raspberry Pi V4L2 video encoding. |
/dev/video12 |
Only needed if you want to use your Raspberry Pi V4L2 video encoding. |
User / Group Identifiers
When using volumes (-v flags), permissions issues can arise between the host OS and the container, we avoid this issue by allowing you to specify the user PUID and group PGID.
Ensure any volume directories on the host are owned by the same user you specify and any permissions issues will vanish like magic.
In this instance PUID=1000 and PGID=1000, to find yours use id user as below:
$ id username
uid=1000(dockeruser) gid=1000(dockergroup) groups=1000(dockergroup)
Application Setup
Webui can be found at http://<your-ip>:8096
More information can be found in their official documentation here .
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 MMAL/OpenMAX will need to mount their /dev/vc-mem and /dev/vchiq video devices inside of the container and their system OpenMax libs by passing the following options when running or creating the container:
--device=/dev/vc-mem:/dev/vc-mem
--device=/dev/vchiq:/dev/vchiq
-v /opt/vc/lib:/opt/vc/lib
V4L2 (Raspberry Pi)
Hardware acceleration users for Raspberry Pi V4L2 will need to mount their /dev/video1X devices inside of the container by passing the following options when running or creating the container:
--device=/dev/video10:/dev/video10
--device=/dev/video11:/dev/video11
--device=/dev/video12:/dev/video12
Docker Mods
We publish various Docker Mods to enable additional functionality within the containers. The list of Mods available for this image (if any) can be accessed via the dynamic badge above.
Support Info
- Shell access whilst the container is running:
docker exec -it jellyfin /bin/bash
- To monitor the logs of the container in realtime:
docker logs -f jellyfin
- Container version number
docker inspect -f '{{ index .Config.Labels "build_version" }}' jellyfin
- Image version number
docker inspect -f '{{ index .Config.Labels "build_version" }}' linuxserver/jellyfin
Versions
- 11.04.20: - Enable hw decode (mmal) on Raspberry Pi, update readme instructions, add donation info, create missing default transcodes folder.
- 11.03.20: - Add Pi V4L2 support, remove optional transcode mapping (location is selected in the gui, defaults to path under
/config). - 30.01.20: - Add nightly tag.
- 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.
- 07.06.19: - Initial release.