VisionSR
The facts below are what the maker publishes about VisionSR, checked and dated. Our editors have not written about it yet.
The facts
Each one read from VisionSR's own pages, with the date it was checked.
What it does
- API
- The HTTP API includes image analysis, enhancement jobs, live progress events over SSE, and job results.checked 12 Oct 2026
- API access
- Yeschecked 22 Sep 2026
- Automatic routing
- It analyzes image content and damage, then automatically selects a suitable model and tile size based on available VRAM.checked 12 Oct 2026
- Batch processing
- Yeschecked 22 Sep 2026
- Desktop features
- The desktop app includes a watched hot folder and native open and save, and starts its own engine process.checked 12 Oct 2026
- Hardware
- The README describes tiled inference designed for a 4 GB GPU; GPU installation requires an NVIDIA card, while the packaged ONNX Runtime and DirectML app is described as supporting DX12 GPUs from NVIDIA, AMD, or Intel.checked 12 Oct 2026
- Hardware requirements
- The project requires Python 3.11 or later, and an NVIDIA card for GPU use; tiled inference is designed to work from 4 GB VRAM.checked 12 Oct 2026
- Image tools
- Listed capabilities include super resolution, face restoration, and background removal.checked 12 Oct 2026
- Image workflows
- Features include batch folder processing, face restoration, background removal, image analysis, and model inspection.checked 12 Oct 2026
- Integrations
- The README documents PyTorch, ONNX Runtime, DirectML, and OpenVINO as supported inference backends.checked 12 Oct 2026
- Intended users
- The project describes a 4 GB laptop GPU as its design target and includes model paths for photographs, portraits, scans, and line art.checked 12 Oct 2026
- Interfaces
- It provides a CLI, Python interface, HTTP API, web UI, and Electron desktop app.checked 12 Oct 2026
- License
- The project is licensed under Apache-2.0, and the README says model weights have their own licenses and are downloaded rather than redistributed.checked 12 Oct 2026
- Limits
- The README says the training pipeline and cloud or multi-tenant layer are not built.checked 12 Oct 2026
- Local processing
- The project says images are processed locally, with no upload, per-image cost, or queue.checked 12 Oct 2026
- Maximum scale
- 4xchecked 22 Sep 2026
- Models
- The README lists nine models for super resolution, anime and illustration upscaling, face restoration, background removal, and face detection.checked 12 Oct 2026
- Model selection
- Its content classification and model selection use inspectable heuristic rules and image statistics rather than a learned classifier.checked 12 Oct 2026
- Notable limits
- The README says the training pipeline and cloud or multi-tenant layer are not built.checked 12 Oct 2026
- Purpose
- VisionSR is an AI super-resolution engine for image upscaling, restoration, face recovery, and detail reconstruction.checked 12 Oct 2026
- Runtime options
- The documented backends include PyTorch, ONNX Runtime, DirectML, and OpenVINO; the README says the shipped desktop runtime uses ONNX and can run through DirectML on DX12 GPUs.checked 12 Oct 2026
- Security
- The repository README lists CI security workflows for CVEs, CodeQL, secrets, and filesystem checks.checked 12 Oct 2026
- Security checks
- The repository README lists CI security workflows for CVEs, CodeQL, secrets, and filesystem checks.checked 12 Oct 2026
Where it runs
- Desktop app
- Yeschecked 22 Sep 2026
Alternatives to VisionSR
- 1
Cutout.Pro
Free planAndroidiOSWebAPI8.5From $5 a month - 2
Krea Enhancer
Free planiOSWebAPISelf-hosted8.4Free plan - 3
Bigjpg
Free planAndroidiOSWebAPI8.4$6 one-time - 4
Phot.AI
Free planAndroidiOSWebAPI8.4From $9 a month - 5
Pixelcut
Free planAndroidiOSWebAPI8.4From $8 a month - 6
Upscal
Free planiOSmacOSWindows8.3Free plan