Iván Eduardo Chavez Ayub
9.5 KiB
Warlock-Studio is a unified, high-performance platform for upscaling, restoration, denoising, and frame interpolation.
Inspired by Djdefrag tools such as QualityScaler and FluidFrames.
📥 Download Installer
This installer was built using PyInstaller and Inno Setup.
By default, it includes DirectML support to ensure maximum compatibility with any graphics card (NVIDIA/AMD/INTEL).
Select your preferred option to download the latest version (Direct Release/Mirror):
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✨ What is New in v5.0
The v5.0 release represents a foundational transformation of the application:
- 🧩 Modular Architecture: The core has been re-engineered into specialized components (
core,preferences,console,drag_drop) for superior stability and fault isolation. - 🧠 NEO Engine: A new diagnostic subsystem that scans CPU topology, RAM, and GPU VRAM to automatically recommend optimal tiling and thread settings.
- 🖥️ Integrated Debug Console: A real-time GUI terminal that intercepts
stdoutandstderrwith syntax highlighting, allowing users to diagnose FFmpeg or ONNX issues instantly. - ⚡ Native CUDA & Failover: The backend now strictly prioritizes CUDA (NVIDIA Optimized) > DirectML > CPU, with corrected integer typing for device IDs.
- 💎 Lossless Pipeline: Deprecated
.jpgusage in favor of.pngfor intermediate frames to prevent compression artifacts (blurriness).
🖼️ Interface Previews
⚙️ Preferences
🔍 Quality Comparison
✨ Key Features
- AI Upscaling & Restoration – Utilize Real-ESRGAN, BSRGAN, RealESRNet, RealESR_Animex4, 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.
- 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
| Component | Minimum Specification | Recommended Specification |
|---|---|---|
| OS | Windows 10 (64-bit) | Windows 11 (64-bit) |
| RAM | 8 GB | 16 GB+ (Recommended for 4K Video) |
| GPU | DirectX 12 Compatible | NVIDIA RTX 2060 / AMD RX 6700 XT |
| VRAM | 4 GB | 8 GB+ (NEO Engine auto-tunes limits) |
| Storage | HDD Space | NVMe SSD (Highly recommended for RIFE) |
🚀 What's Next?
We are working on a fundamental transformation of how users create, manage, and execute pipelines within Warlock-Studio. The next major update introduces the Visual Nodes system, a powerful tool that will drastically improve the user experience and the complexity of the projects you can handle.
🖼️ New Module: WSNodes (Visual Node Editor)
The WSNodes module is an advanced visual node editor, built on PyQt5, that will allow users to:
- Design Pipelines Intuitively: Instead of directly editing JSON files, you will be able to drag, connect, and configure modules as if you were drawing a flowchart.
- Simplified Visual Complexity: Build complex, multi-step, and branching workflows in a clear and visual manner.
- Reusability and Modularity: Each node will encapsulate a specific function, allowing for easy reuse and simpler code maintenance.
- Compilation and Execution: Once designed, the editor will automatically compile the visual diagram into the internal pipeline format that Warlock-Studio already uses for execution.
This represents a significant leap in Warlock-Studio's usability and capability, moving it towards a more flexible and visually powerful project development environment.
🤝 Contributions
We welcome contributions from the community:
- Fork the repository.
- 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 & Credits
© 2025 Iván Eduardo Chavez Ayub
Licensed under MIT. Additional terms and attributions are provided in NOTICE.md.
📊 Integrated Technologies & Licenses
| Technology / Model | License | Author / Maintainer | Source |
|---|---|---|---|
| Real-ESRGAN | BSD 3-Clause | Xintao Wang | GitHub |
| • RealESRGANx4 | BSD 3-Clause | Xintao Wang | Same as above |
| • RealESRNetx4 | BSD 3-Clause | Xintao Wang | Same as above |
| • RealESR_Gx4 (Custom Variant) | BSD 3-Clause | Xintao / Community | Same as above |
| • RealESR_Animex4 (Anime Model) | BSD 3-Clause | Community | Same as above |
| BSRGAN | Apache 2.0 | Kai Zhang | GitHub |
| • BSRGANx4 | Apache 2.0 | Kai Zhang | Same as above |
| • BSRGANx2 | Apache 2.0 | Kai Zhang | Same as above |
| IRCNN | BSD / Mixed | Kai Zhang | GitHub |
| • IRCNN_Mx1 | BSD / Mixed | Kai Zhang | Same as above |
| • IRCNN_Lx1 | BSD / Mixed | Kai Zhang | Same as above |
| GFPGAN | Apache 2.0 | TencentARC | GitHub |
| RIFE | Apache 2.0 | hzwer | GitHub |
| QualityScaler | MIT | Djdefrag | GitHub |
| FluidFrames | MIT | Djdefrag | GitHub |
| ONNX Runtime | MIT | Microsoft | GitHub |
| FFmpeg | LGPL / GPL | FFmpeg Team | Official Site |
| ExifTool | Artistic | Phil Harvey | Official Site |
| Python | PSF License | Python Software Foundation | Official Site |
| PyInstaller | GPLv2+ | PyInstaller Team | GitHub |
| Inno Setup | Custom | Jordan Russell | Official Site |