Download Installer
Installers and releases are published for Windows (64-bit).
Interface Previews
Quality Comparison
Side-by-side samples and short demo videos demonstrating restoration and upscaling results.
Key Features
- AI Upscaling & Restoration – Utilize Real-ESRGAN, BSRGAN, and IRCNN models for denoising, super-resolution, and detail recovery.
- Face Restoration (GFPGAN) – Recover facial details from low-resolution or blurry images and video frames.
- Frame Interpolation (RIFE) – Smooth motion or generate slow-motion content with 2×, 4×, or 8× interpolation.
- Advanced Hardware Acceleration – Intelligent provider selection prioritizes CUDA, falls back to DirectML, and finally CPU for maximum compatibility and performance.
- Batch Processing – Process multiple media files simultaneously, saving time and effort.
- Custom Workflows – Fine-grained control over models, resolution, output formats, and quality parameters.
- Open-Source & Extensible – Fully MIT licensed, for contributors and developers.
System Requirements
- OS: Windows 11 or higher (64-bit)
- RAM: 8GB+ recommended
- GPU: NVIDIA (for CUDA), AMD, or Intel GPU with up-to-date drivers recommended
- Storage: Sufficient free space for input and processed media
Model Comparison
Common models bundled or supported by Warlock-Studio and their typical use cases.
| Model File | Use Case | Speed | Quality | Notes |
|---|---|---|---|---|
| GFPGANv1.4 | Face restoration | High | High | Optimal for portraits |
| BSRGANx2 | 2× upscale + denoising | Medium | Very High | Suitable for lightly degraded media |
| BSRGANx4 | 4× upscale + denoising | Low | Very High | For heavily degraded content |
| RIFE | Frame interpolation | High | High | Smooth motion, slow-motion support |
| RIFE-Lite | Lightweight interpolation | Very High | Medium | Faster, lower resource usage |
| RealESRGANx4 | General 4× upscaling | Medium | High | Balanced performance |
| RealESRNetx4 | Subtle restoration | Medium | High | Preserves natural image texture |
| RealSRx4_Anime | Anime / line-art enhancement | Medium | High | Sharp edges for 2D art |
| IRCNN_L | Light denoising | High | Medium | Mild artifact removal |
| IRCNN_M | Medium denoising | High | Medium | Stronger artifact cleanup |
Contributions
We welcome contributions from the community:
- Fork the repository on GitHub.
- Create a branch for your feature or bug fix.
- Submit a Pull Request with a detailed description and testing notes.
Contact: negroayub97@gmail.com
License & Technologies
Integrated Technologies & Licenses
| Technology | License | Author / Maintainer | Source |
|---|---|---|---|
| QualityScaler | MIT | Djdefrag | GitHub |
| FluidFrames | MIT | Djdefrag | GitHub |
| Real-ESRGAN | BSD 3-Clause / Apache | Xintao Wang | GitHub |
| GFPGAN | Apache 2.0 | TencentARC / Xintao Wang | GitHub |
| RIFE | Apache 2.0 | hzwer | GitHub |
| BSRGAN | Apache 2.0 | Kai Zhang | GitHub |
| IRCNN | BSD / Mixed | Kai Zhang | GitHub |
| ONNX Runtime | MIT | Microsoft | GitHub |
| FFmpeg | LGPL / GPL | FFmpeg Team |