QualityScaler is a GUI application for upscaling images and videos using AI-powered super-resolution models.
The tool addresses the problem of low-resolution or compressed media by applying deep-learning-based upscaling. It uses ONNX Runtime for model inference, allowing it to leverage multiple hardware backends including NVIDIA GPUs, AMD GPUs, and Intel processors. The application handles both image and video inputs, with support for noise reduction and compression artifact removal as part of its processing pipeline.
QualityScaler is designed for Windows users who need a graphical interface for batch or individual upscaling tasks. It suits workflows involving anime and manga content upscaling alongside general photography and video enhancement. The tool's multi-platform GPU support means users can run it on various hardware configurations without rewriting code, though the specific performance characteristics across different accelerators would depend on the underlying ONNX Runtime implementations.
The project shows active development with regular updates to its codebase. Work spans across core upscaling functionality, GPU backend integration, and user interface refinement. The maintainer demonstrates responsiveness to implementation details, with commits addressing both feature additions and technical improvements in the processing pipeline.
