From 71acaeede1a426400ff7b90b1eef415a409dbb2a Mon Sep 17 00:00:00 2001 From: thelamer Date: Thu, 9 Jan 2020 20:40:39 -0800 Subject: [PATCH] typos --- README.md | 8 ++++---- readme-vars.yml | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 44cdd3a..c320897 100644 --- a/README.md +++ b/README.md @@ -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/movies` | Media goes here. Add as many as needed e.g. `/data/movies`, `/data/tv`, etc. | | `-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/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) @@ -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. -### 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 diff --git a/readme-vars.yml b/readme-vars.yml index 372c3f3..0f6d8ed 100644 --- a/readme-vars.yml +++ b/readme-vars.yml @@ -34,11 +34,11 @@ opt_param_env_vars: opt_param_usage_include_vols: true opt_param_volumes: - { vol_path: "/transcode", vol_host_path: "", 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_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)." } + - { 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_ports: - { 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. - ### 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