linuxserver/docker-jellyfin
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thelamer
2020-01-09 20:40:39 -08:00
parent 7f57d96221
commit 71acaeede1
2 changed files with 8 additions and 8 deletions
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8
README.md
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@@ -129,9 +129,9 @@ Container images are configured using parameters passed at runtime (such as thos
| `-v /data/tvshows` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. | | `-v /data/tvshows` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
| `-v /data/movies` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. | | `-v /data/movies` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. |
| `-v /transcode` | Path for transcoding folder, *optional*. | | `-v /transcode` | Path for transcoding folder, *optional*. |
| `-v /opt/vc/lib` | Path for Rasberry Pi OpenMAX libs *optional*. | | `-v /opt/vc/lib` | Path for Raspberry Pi OpenMAX libs *optional*. |
| `--device /dev/dri` | Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi). | | `--device /dev/dri` | Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi). |
| `--device /dev/vchiq` | Only needed if you want to use your Rasberry Pi OpenMax video encoding (Bellagio). | | `--device /dev/vchiq` | Only needed if you want to use your Raspberry Pi OpenMax video encoding (Bellagio). |
## Environment variables from files (Docker secrets) ## Environment variables from files (Docker secrets)
@@ -184,9 +184,9 @@ 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. 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 (Rasberry Pi) ### OpenMAX (Raspberry Pi)
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: 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 --device=/dev/vchiq:/dev/vchiq

8
readme-vars.yml
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@@ -34,11 +34,11 @@ opt_param_env_vars:
opt_param_usage_include_vols: true opt_param_usage_include_vols: true
opt_param_volumes: opt_param_volumes:
- { vol_path: "/transcode", vol_host_path: "</path for transcoding>", desc: "Path for transcoding folder, *optional*." } - { vol_path: "/transcode", vol_host_path: "</path for transcoding>", desc: "Path for transcoding folder, *optional*." }
- { vol_path: "/opt/vc/lib", vol_host_path: "/opt/vc/lib", desc: "Path for Rasberry Pi OpenMAX libs *optional*." } - { vol_path: "/opt/vc/lib", vol_host_path: "/opt/vc/lib", desc: "Path for Raspberry Pi OpenMAX libs *optional*." }
opt_param_device_map: true opt_param_device_map: true
opt_param_devices: opt_param_devices:
- { device_path: "/dev/dri", device_host_path: "/dev/dri", desc: "Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi)." } - { device_path: "/dev/dri", device_host_path: "/dev/dri", desc: "Only needed if you want to use your Intel GPU for hardware accelerated video encoding (vaapi)." }
- { device_path: "/dev/vchiq", device_host_path: "/dev/vchiq", desc: "Only needed if you want to use your Rasberry Pi OpenMax video encoding (Bellagio)." } - { device_path: "/dev/vchiq", device_host_path: "/dev/vchiq", desc: "Only needed if you want to use your Raspberry Pi OpenMax video encoding (Bellagio)." }
opt_param_usage_include_ports: true opt_param_usage_include_ports: true
opt_param_ports: opt_param_ports:
- { external_port: "8920", internal_port: "8920", port_desc: "Https webUI (you need to setup your own certificate)." } - { external_port: "8920", internal_port: "8920", port_desc: "Https webUI (you need to setup your own certificate)." }
@@ -69,9 +69,9 @@ app_setup_block: |
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. 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 (Rasberry Pi) ### OpenMAX (Raspberry Pi)
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: 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 --device=/dev/vchiq:/dev/vchiq