docs for pi support

readme-vars.yml

@@ -34,9 +34,11 @@ opt_param_env_vars:
 opt_param_usage_include_vols: true
 opt_param_volumes:
   - { 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*." }
 opt_param_device_map: true
 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/vchiq", device_host_path: "/dev/vchiq", desc: "Only needed if you want to use your Rasberry Pi OpenMax video encoding (Bellagio)." }
 opt_param_usage_include_ports: true
 opt_param_ports:
   - { external_port: "8920", internal_port: "8920", port_desc: "Https webUI (you need to setup your own certificate)." }
@@ -49,20 +51,36 @@ app_setup_block: |
 
   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 (Rasberry 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:
+
+  ```
+  --device=/dev/vchiq:/dev/vchiq
+  -v /opt/vc/lib:/opt/vc/lib
+  ```
 
 # changelog
 changelogs:
+  - { date: "09.01.20:", desc: "Add Pi OpenMax support." }
   - { date: "02.10.19:", desc: "Improve permission fixing for render & dvb devices." }
   - { date: "31.07.19:", desc: "Add AMD drivers for vaapi support on x86." }
   - { date: "13.06.19:", desc: "Add Intel drivers for vaapi support on x86." }