Awesome GitHub RepositoriesImage Processing Pipelines

GFPGAN is a generative face restoration model and Python-based image processing tool designed to restore low-resolution facial images. It utilizes generative adversarial networks to recover fine details and increase the clarity of degraded portraits. The system employs a generative facial prior to map degraded images to a high-quality manifold, enabling blind-face restoration without requiring knowledge of the specific degradation process. It utilizes a multi-stage workflow that includes face detection, alignment, and region-specific masking to separate facial areas from the background. Beyo

This project is a collection of pre-trained machine learning models and conversion pipelines designed for running inference directly in the browser using TensorFlow.js. It provides a library of ready-to-use models for computer vision, audio classification, and natural language processing tasks. The suite includes specialized tools for transforming Python-based Keras models into JSON formats compatible with web environments. It enables the deployment of these models by fetching architectures and weight shards via HTTP for client-side execution. The project covers a broad range of capabilities

Jimp is a zero-dependency JavaScript image processing library and programmatic editor designed for manipulating, resizing, and filtering images in Node.js. It functions as a multi-format image encoder and extensible pipeline that operates entirely in JavaScript to ensure portable deployment across different environments without requiring native system dependencies. The engine features a modular architecture that allows for custom image processor builds and the registration of custom processing plugins. This extensibility enables the addition of specific visual effects and custom file-type enc

Jimp is a JavaScript image processing library and Node.js manipulation tool designed to perform image transformations and edits entirely within a JavaScript environment. It is a zero-dependency image library that operates without requiring native binaries or external system software dependencies. The project provides a programmatic interface for automated image transformations, including resizing, cropping, and filtering. It supports the creation of custom image pipelines and server-side image editing by processing data without relying on native system tools.

Neural Enhance is a deep learning image upscaler and restoration tool designed to increase image resolution and remove blur. It functions as a neural image restoration utility for eliminating noise and JPEG artifacts, and includes a framework for training and tuning custom neural network models against image datasets. The system utilizes a containerized environment to offload tensor calculations to GPU cores, speeding up neural network inference. It features a batch processing pipeline that queues multiple image files in sequence to maximize hardware throughput. Capabilities include domain-s

This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow. It provides a comprehensive guide for building, training, and deploying neural networks, combining theoretical fundamentals with practical implementation examples. The repository distinguishes itself by covering the end-to-end machine learning workflow, from low-level tensor mathematics and linear algebra to the creation of complex model architectures. It includes specific guidance on developing data pipelines for diverse data types, such as images, text, and time-series seque

This is a Glide image transformation library for Android that provides a collection of image processing filters and shapes. It functions as a suite of hardware-accelerated tools for image cropping, artistic filtering, and transformation pipeline management. The project distinguishes itself through an image filter pipeline that allows for sequential transformation chaining, enabling multiple visual effects and color modifications to be applied in a single pass. It utilizes GPU acceleration to implement artistic effects such as pixelation, sketching, and blur. The library covers a broad range

This repository is a comprehensive collection of reference implementations and sample libraries for the Universal Windows Platform. It provides practical examples of how to use Windows Runtime APIs to build cross-device applications, including detailed guidance on XAML-based declarative user interfaces and DirectX-integrated rendering. The project distinguishes itself by providing a wide array of hardware integration suites, covering low-level communication with USB, Serial, I2C, SPI, and GPIO peripherals. It includes specialized implementations for mixed reality holographic rendering, advanc

Paperclip is an ActiveRecord file attachment manager that links database models to files stored on local disks or cloud storage. It functions as a system for managing file attachments, a fingerprinting system for detecting duplicates and verifying integrity, and a MIME type validator to ensure uploaded files match allowed formats. The project features an image processing pipeline that uses command-line utilities to automatically generate thumbnails and scaled versions of images based on predefined dimensions. It also provides S3 compatible file storage for managing attachments in Amazon S3 an

CarrierWave is a Ruby file upload library used to manage the uploading, storing, and retrieval of files within web frameworks such as Rails and Sinatra. It functions as an Active Record file manager that associates uploaded assets with database records. The project includes an image processing pipeline for generating thumbnails and derivative versions of uploaded images. It also features a file validation engine to restrict uploads based on allowlists or denylists of extensions and content types, and provides cloud storage integration to manage assets on remote providers. The library covers

FastImageCache is an iOS image caching library that provides a persistent disk-based image store. It utilizes a persistent bitmap cache to store images in uncompressed formats and incorporates an image pre-processing pipeline to optimize assets before they are committed to storage. The library optimizes rendering performance by using memory-mapped image tables for constant-time retrieval and byte-aligned data layouts to prevent memory copies. It organizes images of identical dimensions into shared tables and manages disk space through a least-recently-used cache eviction system. The project

Final2x is an AI image super-resolution tool and neural network inference engine designed to increase image resolution and reconstruct missing details while reducing noise. It functions as a cross-platform image upscaler that executes consistent super-resolution logic across different operating systems. The project serves as a custom model inference engine and upscaling interface, allowing for the import and application of user-defined super-resolution weights and architectures to tailor the visual output of enlarged images. The system utilizes hardware-accelerated processing to offload comp

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

Lychee is a self-hosted photo management system and PHP web application designed for organizing, browsing, and sharing personal photo collections. It functions as a dockerized media server that provides a web interface for uploading and managing images independently of commercial cloud services. The system features an integrated image processing pipeline that automatically generates responsive thumbnails and applies watermarks during the upload process. It supports remote media migration through integration with the Dropbox API and allows for the synchronization of existing server directories

yolotf es un framework de detección de objetos que proporciona herramientas para convertir configuraciones y pesos de modelos de Darknet a grafos de TensorFlow. Incluye un entrenador de modelos de TensorFlow para entrenar nuevos modelos de detección o ajustar pesos existentes utilizando datasets personalizados. El proyecto cuenta con un exportador de modelos móviles que serializa definiciones de grafos y metadatos en archivos protobuf para su despliegue en dispositivos móviles. El framework soporta inferencia de detección de objetos en imágenes y video para identificar objetos y exportar coordenadas de cajas delimitadoras. Gestiona el estado del modelo mediante la traducción de mapeo de pesos y entrenamiento basado en puntos de control para permitir la restauración de pesos y estados del optimizador.

Darkflow es un framework de detección de objetos y pipeline de visión artificial que proporciona una interfaz programática para realizar análisis de imágenes y detección de objetos en tiempo real. Funciona como una herramienta para cargar pesos, ajustar modelos y ejecutar inferencia tanto en imágenes estáticas como en feeds de video. El proyecto sirve como un convertidor que traduce configuraciones y pesos de Darknet a grafos de TensorFlow para permitir el reentrenamiento y el despliegue. Incluye un exportador de modelos que guarda los grafos entrenados en archivos protobuf portátiles para su uso en dispositivos móviles y nativos. El sistema cubre capacidades para entrenar y ajustar modelos de detección en datasets personalizados, con puntos de control de progreso para la recuperación del entrenamiento. También proporciona herramientas para la traducción de mapeo de pesos y el procesamiento de datos de imagen crudos a través de operaciones de tensores para producir cajas delimitadoras y puntuaciones de confianza.

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

chaiNNer is a GPU-accelerated AI image upscaling application that uses a visual node-based interface for constructing image processing pipelines. At its core, it provides a node-based visual programming environment where users connect processing nodes in a directed acyclic graph, with a graph execution scheduler that traverses the pipeline in topological order. The application includes an iterator-based batch processing system that automatically applies the same pipeline to multiple files, and a model format conversion pipeline that transforms neural network models between PyTorch, ONNX, and N

vtracer is a raster to SVG converter and image vectorization pipeline. It transforms high-resolution scans and pixel-based images into scalable vector graphics by tracing shapes and colors. The tool includes a specialized pixel art vectorizer that converts low-resolution raster graphics into vector shapes while preserving a pixelated aesthetic. It also functions as a Bezier curve fitting tool to simplify dense point sets into smooth curves, reducing the complexity of vector paths. The project covers large scale image vectorization for gigapixel-scale data, color clustering and patch segmenta