jellyfin/readme.md

Jellyfin Docker Setup with Hardware Acceleration

This repository contains Docker configurations for running Jellyfin with hardware-accelerated transcoding support for various GPU types.

Features

• Hardware-accelerated transcoding support for:
  • Intel ARC GPUs
  • Intel integrated graphics (iGPU)
  • NVIDIA GPUs
  • AMD GPUs
• HDR to SDR tonemapping
• Configurable environment variables
• Optimized for performance

Prerequisites

• Docker and Docker Compose
• One of the supported GPUs
• Linux host system (recommended)
• Proper GPU drivers installed

Quick Start

1. Create a new directory and download the required files:

   # Create and enter directory
   mkdir jellyfin-docker && cd jellyfin-docker
   
   # Download base docker-compose.yml
   curl -O https://raw.githubusercontent.com/yourusername/jellyfin-docker/main/docker-compose.yml
   
   # Download sample.env
   curl -O https://raw.githubusercontent.com/yourusername/jellyfin-docker/main/sample.env
   
   # Download transcoding file for your GPU:
   
   # For Intel ARC:
   curl -O https://raw.githubusercontent.com/yourusername/jellyfin-docker/main/intel-arc.transcoding.yml
   
   # OR for Intel iGPU:
   curl -O https://raw.githubusercontent.com/yourusername/jellyfin-docker/main/intel-igpu.transcoding.yml
   

2. Copy the sample environment file:

   cp sample.env .env
   

3. Edit the .env file with your settings:

   nano .env
   

4. Verify your GPU setup:

   # Check render group ID
   getent group render | cut -d: -f3
   
   # Verify GPU devices
   ls -l /dev/dri
   

5. Start Jellyfin with the appropriate configuration:

   # For Intel ARC
   docker compose -f docker-compose.yml -f intel-arc.transcoding.yml up -d
   
   # For Intel iGPU
   docker compose -f docker-compose.yml -f intel-igpu.transcoding.yml up -d
   

6. Access Jellyfin at:

   • HTTP: http://localhost:8096
   • HTTPS: https://localhost:8920

Quick Start

Useful Commands

List only named Docker volumes:

docker volume ls | grep -v "^local.*[0-9a-f]\{64\}$"

This will show:

DRIVER    VOLUME NAME
local     cifs-volume_downloads
local     cifs-volume_music
local     cifs-volume_videos
local     cifs_immich
local     portainer_data

Hardware Acceleration Setup

Verify GPU Access

# Check render group ID
getent group render | cut -d: -f3

# Verify GPU devices
ls -l /dev/dri

Check Driver Installation

For Intel

vainfo

For NVIDIA

nvidia-smi

For AMD

rocm-smi

Configuration Files

• docker-compose.yml: Base configuration
• intel-arc.transcoding.yml: Intel ARC specific settings
• intel-igpu.transcoding.yml: Intel iGPU specific settings
• .env: Environment variables (copy from sample.env)
• tonemapping.md: Detailed explanation of HDR tonemapping options

docker-compose.yml

Base configuration file that includes:

• Container name and image settings
• Volume mappings for media, config, and cache
• Network ports (HTTP/HTTPS)
• Basic environment variables

intel-arc.transcoding.yml

Intel ARC GPU specific settings:

• Hardware acceleration configuration
• GPU device mappings
• Optimized tonemapping settings
• Intel ARC specific drivers and libraries

intel-igpu.transcoding.yml

Intel integrated GPU settings:

• Hardware acceleration for QuickSync
• iGPU device mappings
• Compatible tonemapping settings
• Required driver configurations

.env

Environment variables file containing:

• Port configurations (8096 for HTTP, 8920 for HTTPS)
• Domain settings for remote access
• Timezone configuration
• Render group ID for GPU access
• Cache and config directory paths

tonemapping.md

Comprehensive guide covering:

• What tonemapping is and why it's needed
• Available algorithms and their use cases
• Performance implications
• Hardware-specific recommendations
• Troubleshooting tips

Environment Variables

See sample.env for available options:

• JELLYFIN_PORT_HTTP: HTTP port (default: 8096)
• JELLYFIN_PORT_HTTPS: HTTPS port (default: 8920)
• DOMAIN: Your domain name
• TZ: Timezone
• RENDER_GID: Render group ID (get with getent group render)

Tonemapping

For detailed information about HDR tonemapping options, see tonemapping.md

Troubleshooting

1. Hardware Acceleration Not Working

   • Verify GPU devices are properly mapped
   • Check render group ID matches your system
   • Ensure proper drivers are installed

2. Performance Issues

   • Try different tonemapping algorithms
   • Check CPU/GPU usage
   • Limit concurrent transcoding sessions

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Jellyfin Project
• Docker
• Hardware acceleration guides from various sources

Support

If you encounter any issues, please open an issue on GitHub.