AI Media Enhancement Suite

Transform your media with cutting-edge AI technology

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Warlock-Studio is an open-source desktop application for Windows, designed to integrate state-of-the-art AI models for image and video enhancement. Inspired by Djdefrag tools such as QualityScaler and FluidFrames, Warlock-Studio provides a unified, high-performance platform for upscaling, restoration, denoising, and frame interpolation.

Version 4.2 introduces a full offline installer, an advanced ONNX Runtime engine with CUDA support, and significant packaging optimizations, ensuring the most reliable and performant experience yet.

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📥 Download Installer (v4.2)

Get the latest stable release from:

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✨ 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.

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🆕 What’s New in v4.2

• 📦 Full Offline Installer: The application is now distributed as a single, self-contained offline installer. All AI models are included, eliminating the need for an internet connection during setup and ensuring a reliable installation.
• 🚀 Advanced ONNX Runtime Engine: The model loading architecture was re-engineered to intelligently prioritize hardware acceleration providers (CUDA > DirectML > CPU), maximizing performance on capable hardware and ensuring stability via a robust fallback mechanism.
• ⚙️ Aggressive Packaging Optimization: The final application size has been drastically reduced by aggressively pruning unnecessary dependencies from the PyInstaller build, resulting in a lighter and more efficient package.
• 🐛 Enhanced Runtime Stability: Added crucial hidden imports to the build process, preventing ModuleNotFoundError crashes and ensuring all components of onnxruntime and other libraries load correctly.
• 🖥️ Improved Debugging Experience: The application now runs with an attached console window, providing real-time logs and error messages for easier troubleshooting.
• ✨ Professional Splash Screen: A new startup splash screen provides immediate visual feedback while the application initializes, improving the user experience.

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🖼️ Interface Previews

Main Window

Console

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🚀 How to Use

1. Run Warlock-Studio as Administrator (recommended for full GPU access).
2. Load Media – Import images or videos.
3. Configure Processing Settings:
   • Select AI model (Real-ESRGAN, GFPGAN, etc.)
   • Set resolution, format, frame interpolation, and quality.
4. Start Processing using "Make Magic".
5. Retrieve the processed results from the designated output folder.

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🖼️ Quality Comparison

Enhanced image using BSRGANx2:

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📊 Model Comparison

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

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⚙️ Installation

1. Download the Full Offline Installer (see links above).
2. Run the setup wizard and follow the prompts.
3. Launch via Start Menu or Desktop shortcut.

Warlock-Studio is packaged using PyInstaller and deployed with Inno Setup for a seamless, self-contained installation experience.

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🖥️ 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

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📌 Development Status (v4.2)

Component	Status	Notes
ONNX Runtime Engine	🟢 Enhanced	Prioritizes CUDA > DirectML > CPU with automatic fallback.
Installer & Packaging	🟢 Overhauled	Full offline installer; heavily optimized package size.
Upscaling Models	🟢 Stable	Includes VRAM recovery integration.
Face Restoration (GFPGAN)	🟢 Stable	High-quality face reconstruction.
Frame Interpolation (RIFE)	🟢 Stable	Smooth motion and slow-motion support.
Batch Processing	🟢 Stable	Improved error handling and logging.
User Interface (UI/UX)	🟢 Refined	Clean, modern design with splash screen.
Code Quality	🟢 Improved	Refactored, modular, and more maintainable.

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📂 Project Structure

Warlock-Studio/
├── AI-onnx/                          # Pre-trained ONNX models for AI processing
│   ├── BSRGANx2_fp16.onnx
│   ├── BSRGANx4_fp16.onnx
│   ├── GFPGANv1.4.fp16.onnx
│   ├── IRCNN_Lx1_fp16.onnx
│   ├── IRCNN_Mx1_fp16.onnx
│   ├── RealESR_Animex4_fp16.onnx
│   ├── RealESR_Gx4_fp16.onnx
│   ├── RealESRGANx4_fp16.onnx
│   ├── RealESRNetx4_fp16.onnx
│   ├── RealSRx4_Anime_fp16.onnx
│   ├── RIFE_fp32.onnx
│   └── RIFE_Lite_fp32.onnx
│
├── Assets/                           # Application assets and third-party binaries
│   ├── banner.png
│   ├── clear_icon.png
│   ├── exiftool.exe
│   ├── ffmpeg.exe
│   ├── info_icon.png
│   ├── logo.ico
│   ├── logo.png
│   ├── stop_icon.png
│   ├── upscale_icon.png
│   ├── wizard-image.bmp
│   └── wizard-small.bmp
│
├── rsc/                              # UI previews, workflows, and branding resources
│   ├── itch.io.png
│   ├── Capture.png
│   ├── CaptureRIFE.png
│   ├── GitHub_Logo_WS.png
│   ├── WorkflowBSRGAN.png
│   ├── WorkflowIRCNN.png
│   ├── WorkflowRealESRGAN.png
│   ├── WorkflowRIFE.png
│   ├── Installation_window.png
│   ├── Installation_window2.png
│   └── Installation_window3.png
│
├── Manual/                           # LaTeX sources and generated manuals
│   ├── Manual_EN.tex
│   ├── Manual_ES.tex
│   ├── v4.1_User_Manual_EN.pdf
│   └── v4.1_User_Manual_ES.pdf
│
├── Warlock-Studio.py                 # Main application script
├── Warlock-Studio.spec               # PyInstaller specification file
├── Setup.iss                         # Inno Setup installer script
├── README.md                         # Project overview
├── requirements.txt                  # Python dependencies
├── CHANGELOG.md                      # Version history and updates
├── LICENSE                           # MIT License information
├── NOTICE.md                         # Legal notices and attributions
├── CODE_OF_CONDUCT.md                # Contributor guidelines
├── CONTRIBUTING.md                   # Contribution guide
└── SECURITY.md                       # Security reporting policies

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📊 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	Official Site
ExifTool	Artistic License	Phil Harvey	Official Site
Python	PSF License	Python Software Foundation	Official Site
PyInstaller	GPLv2+	PyInstaller Team	GitHub
Inno Setup	Custom	Jordan Russell	Official Site

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🤝 Contributions

We welcome contributions from the community:

1. Fork the repository.
2. Create a branch for your feature or bug fix.
3. Submit a Pull Request with a detailed description and testing notes.

📧 Contact: negroayub97@gmail.com

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📜 License

© 2025 Iván Eduardo Chavez Ayub Licensed under MIT. Additional terms and attributions are provided in NOTICE.md.