Awesome GitHub RepositoriesImage Sharpening

This project is an educational platform and technical reference for learning real-time graphics programming through the development of custom shaders. It provides a comprehensive guide to the programmable graphics pipeline, offering a collection of tutorials and interactive examples that demonstrate how to manipulate coordinate spaces, manage buffer data, and implement complex rendering techniques in 3D environments. The repository distinguishes itself as a versatile toolkit for both photorealistic and non-photorealistic rendering. It includes modular implementations for stylized aesthetics s

Proton GE Custom is a compatibility layer designed to execute Windows games on Linux by translating binary instructions and API calls. It focuses on improving game stability and performance through a Wine-based translation system. The project utilizes custom patches and per-game configuration overrides to resolve specific application crashes and glitches. It implements specialized media foundation patching to ensure stable playback of proprietary cinematic formats and adds support for High Dynamic Range output. The software covers a range of gaming optimizations, including raw input latency

Xenia is an emulator designed to run Xbox 360 games and applications on modern computer hardware. It enables the execution of console software from disc images, digital downloads, and extracted files, facilitating legacy software preservation on hardware that lacks native support. The project distinguishes itself through high-fidelity graphics enhancements, including the ability to increase internal rendering resolution and apply contrast-adaptive sharpening to restore image clarity. It implements specialized visual techniques such as blue noise dithering to reduce color banding and multisamp

BasicSR is a PyTorch-based image restoration toolbox and framework designed for training and deploying deep learning models to upscale, denoise, and deblur images and videos. It serves as a comprehensive system for image super-resolution and video quality restoration, providing the necessary infrastructure to recover fine visual details and increase pixel density. The project distinguishes itself through specialized toolkits for facial image enhancement and high-fidelity face synthesis, as well as a dedicated video quality restoration suite that utilizes deformable convolutions and generative

Imaging is a Go library for image processing that provides a set of functions for common image manipulation tasks. It offers capabilities for adjusting image colors, applying convolution filters, blurring, cropping, resizing, sharpening, and correcting orientation based on EXIF data. The library supports resizing images to exact dimensions or bounding boxes with aspect ratio preservation and configurable resampling filters. Color adjustments include gamma, contrast, brightness, and saturation controls, while blurring and sharpening use Gaussian-based algorithms with configurable sigma paramet

RapidRAW is a non-destructive RAW photo editor and digital asset manager designed for decoding manufacturer RAW formats and applying tonal and color adjustments. It functions as a professional image processor that ensures original source data remains unmodified by saving all edits, masks, and crops to sidecar files. The software features a specialized color grading suite using 3D LUTs, color wheels, and HSL mixers, alongside AI-powered utilities for subject isolation, automatic masking, and generative inpainting for object removal. It distinguishes itself with AI-assisted photo retouching and

Esta librería proporciona una colección de extensiones de procesamiento de imágenes para la clase nativa de imagen en iOS. Funciona como un kit de herramientas para aplicar filtros artísticos, ajustes de color y algoritmos de enfoque directamente a objetos de imagen dentro de aplicaciones móviles. El framework se distingue por integrarse con el pipeline nativo de imágenes para ejecutar operaciones a nivel de píxel en la GPU. Utiliza un enfoque declarativo para encadenar unidades de procesamiento modulares, permitiendo la construcción de efectos visuales complejos mientras mantiene transformaciones no destructivas mediante la generación de nuevos buffers de salida. El proyecto cubre un amplio rango de capacidades fotográficas, incluyendo gradación de color de nivel profesional mediante el ajuste de niveles, curvas y saturación. También incluye herramientas para mejorar la claridad de la imagen y aplicar estilos visuales predefinidos que simulan la estética de la fotografía clásica y digital.