Cupscale is a graphical user interface for AI-powered image upscaling, primarily leveraging ESRGAN models. It targets users needing to enhance image resolution for various purposes, offering a user-friendly experience with advanced features like model chaining and batch processing.

How It Works

Cupscale supports multiple AI backends: NVIDIA CUDA (recommended), Vulkan (via ncnn-vulkan for broader GPU compatibility, though slower), and CPU-only. It integrates with ESRGAN and Real-ESRGAN, allowing on-the-fly model interpolation and chaining for complex upscaling workflows. Automatic image tiling prevents VRAM limitations during processing.

Quick Start & Requirements

• Install: Download the single executable from the releases page.
• Prerequisites: NVIDIA GPU with CUDA recommended for best performance. Vulkan or CPU are alternatives.
• Setup: Portable application, no complex installation. Temporary files are stored in the executable's directory.
• Docs: https://github.com/n00mkrad/cupscale

Highlighted Details

• Supports CUDA, Vulkan (ncnn), and CPU backends.
• Features on-the-fly model interpolation and model chaining.
• Includes batch upscaling, automatic image tiling, and pre/post-processing options.
• Supports various image formats and clipboard input, with comparison export options (GIF/MP4).

Maintenance & Community

The project is based on forks and frameworks from xinntao, Joey, BlueAmulet, and nihui. Further community or maintenance details are not specified in the README.

Licensing & Compatibility

The README does not explicitly state a license. Compatibility for commercial or closed-source use is not specified.

Limitations & Caveats

Vulkan backend performance is noted as slower with a longer startup time compared to CUDA. CPU processing is described as "very slow." The application should not be installed in protected system locations due to temporary file storage.