Upscayl is a cross-platform desktop application for AI-powered image upscaling, built with Electron and Next.js. It uses Real-ESRGAN models via the ncnn inference engine (Vulkan backend) to upscale images by 2x-4x. The application provides a rich UI with model selection, batch processing, double upscaling, custom model support, and extensive settings (GPU selection, tile size, TTA mode, metadata preservation). It also includes a cloud API (Upscayl Cloud) for server-side upscaling, documented via OpenAPI. The codebase is well-structured with clear separation between Electron main process and Next.js renderer, using Jotai for state management, Radix UI primitives, and a comprehensive localization system supporting 17 languages. While primarily an application, it contains pre-trained neural network model files (.param, .bin) that are research artifacts, giving it a hybrid character.
This is a ComfyUI custom node pack providing advanced tile-based image upscaling, inpainting, and detail enhancement via a 'Smart Tile 2.0' system. It enables variable-size, object-aware tiling using SAM3/QwenVL3 for automatic detection and per-tile prompt generation, with an interactive canvas editor in the browser for manual control. The pack also includes video generation helpers: LTX-Video first/last frame conditioning, a TeaCache sampler for HunyuanVideo acceleration, and various conditioning/coordinate nodes. The codebase is predominantly a set of ComfyUI node implementations in Python with a significant frontend JavaScript component for the interactive tile editor. While it functions as a library for ComfyUI workflows, its core tile data structures and layout algorithms could be extracted for use in other image processing pipelines. The repository is actively maintained, with example workflows demonstrating real production usage for high-resolution Flux and HunyuanVideo generation.
waifu2x-caffe is a Windows desktop application for image upscaling and denoising using pre-trained convolutional neural networks (Caffe). It provides three interfaces: a graphical user interface (GUI) built with Win32 dialogs, a command-line interface (CLI) using a forked TCLAP parser, and a dynamic-link library (DLL) for integration into other software. The core processing pipeline is implemented in the `common/` directory, with classes `Waifu2x` orchestrating model loading and inference, `cNet` wrapping Caffe's `Net` for forward passes, and `stImage` handling image I/O, preprocessing (padding, alpha channel), and tiled processing for large images. The application supports multiple model architectures (VGG-7, upconv_7, upresnet10, cunet) and modes (noise removal, scaling, both), with bundled pre-trained models in prototxt format. It also includes a localization system with JSON language files and a lightweight Win32 dialog framework. While primarily an inference tool, the repository contains appendix Python scripts for converting Chainer models to Caffe format, adding a minor research component. The codebase is heavily Windows-specific, relying on Visual Studio 2015, CUDA 11.0, cuDNN, Boost, OpenCV, and Caffe, which introduces significant technical drift due to the unmaintained status of Caffe and the aging toolchain.