Caution
๐งช TEST PHASE - v1.5.0.2
This is an EXPERIMENTAL version with the new Docker AI microservice architecture! AI upscaling now runs in a separate Docker container instead of directly in Jellyfin.
๐ณ Docker Image: kuscheltier/jellyfin-ai-upscaler
Please report bugs: GitHub Issues
Jellyfin's plugin system tries to load ALL .dll files as .NET assemblies. Native C++ libraries (ONNX Runtime, CUDA, OpenCV) caused:
System.BadImageFormatException: Bad IL format
Failed to load assembly "onnxruntime_providers_shared.dll"
Result: Plugin was disabled, no AI upscaling possible.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Jellyfin Server โ
โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ
โ โ AI Upscaler Plugin v1.5.0.0 โ โ
โ โ โ
Only ~1.6 MB (instead of 417MB)โ โ
โ โ โ
No native DLLs โ โ
โ โ โ
Sends frames via HTTP โ โ
โ โโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโ โ
โโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโ
โ HTTP POST /upscale
โผ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ AI Upscaler Docker Container โ
โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ
โ โ Python + FastAPI + OpenCV DNN โ โ
โ โ โ
CUDA / GPU Acceleration โ โ
โ โ โ
FSRCNN, ESPCN, LapSRN, EDSR โ โ
โ โ โ
Web UI for Model Management โ โ
โ โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
| Feature | Old (v1.4.9.x) | New (v1.5.0.0) |
|---|---|---|
| ZIP Size | 417 MB | ~1.6 MB |
| Native DLLs | In plugin โ Crashes | In Docker โ Isolated |
| GPU Support | Issues with Jellyfin | Full CUDA support |
| Updates | Rebuild plugin | Pull Docker image |
Option A - Docker Hub (easiest):
docker run -d --name jellyfin-ai-upscaler \
-p 5000:5000 \
-v ai-models:/app/models \
kuscheltier/jellyfin-ai-upscaler:latestOption B - Build locally:
cd docker-ai-service
docker-compose up -d --buildOpen http://YOUR_SERVER_IP:5000 to see the Web UI.
- Open Jellyfin Dashboard โ Plugins โ Repositories โ Add
- Enter URL:
https://raw.githubusercontent.com/Kuschel-code/JellyfinUpscalerPlugin/main/manifest.json - Go to Catalog, find "AI Upscaler", install v1.5.0.0
- Restart Jellyfin
- In Plugin Settings: Set AI Service URL to
http://YOUR_SERVER_IP:5000
- Docker Microservice: AI runs isolated in a container (no DLL conflicts!)
- Multiple AI Models: FSRCNN, ESPCN, LapSRN, EDSR (2x, 3x, 4x upscaling)
- Web UI: Manage models at http://YOUR_SERVER_IP:5000
- Hardware Detection: Automatic GPU/CPU detection
- Dashboard: Job monitoring in Jellyfin sidebar
- FFmpeg Integration: Automatic filter injection
After installation, find settings under Dashboard โ Plugins โ AI Upscaler Plugin.
| Setting | Description |
|---|---|
| AI Service URL | URL to Docker container (e.g., http://nas:5000) |
| Enable Plugin | Global switch |
| Scaling Factor | 2x, 3x, or 4x |
| Quality Level | low / medium / high |
- ๐ง Fixed #34: Plugin initialization error (HardwareBenchmarkService DI)
- ๐ง Fixed #33: Checksum mismatch during installation
- ๐ท Added #32: Intel GPU/iGPU support via OpenVINO (Dockerfile.intel)
- ๐ณ Docker Microservice Architecture: AI processing in separate container
- ๐ฆ ~1.6 MB instead of 417 MB: No more native DLLs in plugin
- ๐ง OpenCV DNN Models: FSRCNN, ESPCN, LapSRN, EDSR from public sources
- ๐ Web UI: Model management at http://localhost:5000
- โ Fixed version format: 4-part version for Jellyfin compatibility
- Settings Page Fix
- Cross-Platform Support
- Complete DI Registration
- Make sure you uninstalled old versions (1.4.9.x)
- Delete old plugin folder from Jellyfin plugins directory
- Restart Jellyfin
- Install v1.5.0.0 fresh from repository
# Check Docker container
docker ps --filter name=jellyfin-ai-upscaler
# View logs
docker logs jellyfin-ai-upscaler- Check if Docker is running:
curl http://YOUR_IP:5000/status - Check Plugin Settings: AI Service URL correct?
- Check if model is loaded: http://YOUR_IP:5000 โ Web UI
MIT License - See LICENSE for details.