Awesome GitHub RepositoriesProcessing APIs

Rembg is a machine learning-based toolkit designed for automated image background removal and subject segmentation. It functions as a versatile engine that identifies and extracts subjects from images, supporting diverse input methods including individual files, directory-based batch processing, and live binary data streams. The project distinguishes itself through its flexible integration options, offering a command-line interface for local automation, a library for programmatic access, and an HTTP service for remote requests. It utilizes deep learning architectures to classify pixels and ge

Background Removal JS is a client-side neural matting library that runs a lightweight AI model directly in the browser to compute alpha mattes, removing image backgrounds without uploading any data to a server. It functions as a browser-based image background removal SDK and client-side image matting library, keeping all processing on the user's device to eliminate server costs and preserve privacy. The project provides a cross-platform creative editing engine that produces identical image and video output across web, mobile, desktop, and server environments from a single codebase. It offers

SD.Next is an all-in-one web interface and multi-backend inference engine for generating, editing, and processing images and videos using diffusion models. It functions as a comprehensive tool for diffusion model management and an automated image processing pipeline for bulk operations. The project is distinguished by its hardware-backend abstraction layer, which provides automatic detection and acceleration for NVIDIA CUDA, AMD ROCm, Intel OpenVINO, and DirectML. It features a headless generative API and a programmatic command interface, allowing users to trigger tasks via REST API or CLI wi

A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷

Imaginary is a self-hosted HTTP server for image processing that applies transformations like resizing, cropping, rotating, and format conversion through URL parameters. It operates as a stateless request-response pipeline, processing images fetched from remote URLs or served from a local directory without requiring client-side dependencies. The server distinguishes itself through its security and access control capabilities, offering optional API key validation, HMAC-signed URL verification, and remote origin whitelisting to restrict which image sources are permitted. It also provides a heal

Clarity-upscaler est un outil d'upscaling et d'amélioration d'image par IA utilisant des modèles de deep learning pour augmenter la résolution et restaurer les détails visuels. Il fonctionne comme un moteur d'inférence de super-résolution qui emploie des réseaux de neurones pour prédire les pixels manquants et synthétiser des détails haute fréquence à partir de sources basse résolution. Le projet est fourni sous forme d'API programmable, permettant l'intégration du traitement automatisé et de l'accentuation d'images haute résolution dans des applications et workflows externes. Cette interface permet l'upscaling programmatique d'images pour créer des assets haute résolution. Le système offre des capacités d'amélioration d'image automatisée, supprimant le bruit et améliorant la clarté pour produire des versions plus nettes d'images de basse qualité. Il gère ces tâches via une architecture client-serveur découplée qui gère la nature intensive en calcul de l'inférence par machine learning.