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14 dépôts

Awesome GitHub RepositoriesBatch Image Processors

Tools for automating repetitive image processing tasks.

Distinguishing note: Focuses on batch automation workflows.

Explore 14 awesome GitHub repositories matching development tools & productivity · Batch Image Processors. Refine with filters or upvote what's useful.

Awesome Batch Image Processors GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • aseprite/asepriteAvatar de aseprite

    aseprite/aseprite

    37,521Voir sur GitHub↗

    Aseprite is a specialized graphics editor and animation suite designed for the creation of pixel-based artwork. It provides a comprehensive environment for managing multi-layered animation sequences, offering tools for frame-by-frame design, onion skinning, and real-time motion previews. The application is built to handle both indexed color palettes and full-color RGB editing, allowing users to maintain precise control over pixel data and transparency. What distinguishes Aseprite is its focus on programmable workflows and game asset production. It features a scriptable command architecture th

    Executes command-line scripts to batch convert, resize, or export large volumes of files.

    C++animated-spritesanimationaseprite
    Voir sur GitHub↗37,521
  • danielgatis/rembgAvatar de danielgatis

    danielgatis/rembg

    21,911Voir sur GitHub↗

    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

    Automates background removal across directories and watch folders for high-volume image processing.

    Pythonbackground-removalimage-processingpython
    Voir sur GitHub↗21,911
  • mikubill/sd-webui-controlnetAvatar de Mikubill

    Mikubill/sd-webui-controlnet

    17,853Voir sur GitHub↗

    This project is an extension for Stable Diffusion that provides an image-to-image control framework. It serves as a multi-control constraint manager and structural data preprocessor, allowing users to guide the layout and composition of generated images through spatial maps and structural constraints. The system enables multi-constraint image generation by combining several different control inputs to enforce multiple stylistic or spatial rules within a single generation pass. It provides tools for visual image referencing and precise geometric or anatomical templating to ensure generated ima

    Automates the execution of sequential control tasks across directories of image files for batch generation.

    Python
    Voir sur GitHub↗17,853
  • imagemagick/imagemagickAvatar de ImageMagick

    ImageMagick/ImageMagick

    15,742Voir sur GitHub↗

    ImageMagick is a comprehensive software suite for the creation, editing, composition, and conversion of digital images. It functions as both a command-line utility for batch processing and automation, and as a programming library that allows developers to integrate advanced image manipulation capabilities into external applications. The project is distinguished by its modular architecture, which supports hundreds of image formats through a pluggable coder system and external delegate libraries. It is designed for high-performance environments, utilizing memory-mapped pixel caching, stream-ori

    Provides a scriptable engine for automating complex, high-volume image workflows at scale.

    Ccommand-line-image-tooldigital-image-editingimage-conversion
    Voir sur GitHub↗15,742
  • guofei9987/blind_watermarkAvatar de guofei9987

    guofei9987/blind_watermark

    13,405Voir sur GitHub↗

    This is a blind image watermarking and steganography tool designed to embed and extract hidden data from images without requiring the original source file. It functions as a framework for concealing text or bit arrays within images using mathematical transforms to ensure the marks remain invisible to the viewer. The system is designed for robust watermark extraction, allowing hidden information to be recovered even after images have undergone rotations, cropping, resizing, noise injection, or brightness changes. It utilizes a blind extraction mechanism that retrieves data using a shared passw

    Applies invisible marks to large volumes of images using parallel processing for efficiency.

    Pythonblind-watermarkimage-processingwatermark
    Voir sur GitHub↗13,405
  • t8rin/imagetoolboxAvatar de T8RIN

    T8RIN/ImageToolbox

    11,746Voir sur GitHub↗

    ImageToolbox is an open-source Android application designed for comprehensive image manipulation and batch processing. It provides a toolkit for performing advanced visual edits, including background removal, geometric transformations, and the application of complex filter chains to prepare image assets. The application distinguishes itself through a modular, pipeline-based architecture that allows for the integration of new processing algorithms as isolated plugins. It leverages native hardware acceleration to handle intensive pixel manipulation tasks and supports asynchronous execution to m

    Streamlines repetitive tasks by applying complex editing operations and filter chains to multiple files simultaneously.

    Kotlinaiandroidbackground-removal
    Voir sur GitHub↗11,746
  • vladmandic/sdnextAvatar de vladmandic

    vladmandic/sdnext

    7,139Voir sur GitHub↗

    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

    Provides batch image processing to apply generation or editing operations to multiple files simultaneously.

    Pythonai-artcaptiondiffusers
    Voir sur GitHub↗7,139
  • lymphatus/caesium-image-compressorAvatar de Lymphatus

    Lymphatus/caesium-image-compressor

    6,039Voir sur GitHub↗

    Caesium is an image compression tool that reduces file sizes for JPG, PNG, WebP, and TIFF images while preserving visual quality and metadata. It operates as a cross-platform desktop application with a graphical interface, a command-line tool for scripting and automation, and a web-based interface for browser uploads, all supporting batch processing of multiple images at once. The tool distinguishes itself by offering multiple interaction modes — desktop, terminal, and web — each capable of handling the same core compression tasks. It preserves folder structure when saving compressed images,

    Compresses multiple images at once, maintaining folder structure and supporting automated workflows.

    C++caesiumcompressioncross-platform
    Voir sur GitHub↗6,039
  • chainner-org/chainnerAvatar de chaiNNer-org

    chaiNNer-org/chaiNNer

    5,855Voir sur GitHub↗

    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

    Processes multiple files through a visual pipeline using iterator nodes for uniform operations.

    Python
    Voir sur GitHub↗5,855
  • kornelski/pngquantAvatar de kornelski

    kornelski/pngquant

    5,671Voir sur GitHub↗

    Compresses multiple PNG files in a single command with recursive directory traversal and shell script integration.

    Ccconversionimage-optimization
    Voir sur GitHub↗5,671
  • coobird/thumbnailatorAvatar de coobird

    coobird/thumbnailator

    5,420Voir sur GitHub↗

    Thumbnailator est une bibliothèque Java de création de vignettes d'images conçue pour générer des images redimensionnées avec préservation du ratio d'aspect et un redimensionnement de haute qualité. Elle sert de boîte à outils pour faire pivoter, recadrer et ajuster l'opacité des images au sein des applications Java. La bibliothèque se distingue par sa capacité à fonctionner comme un processeur d'images conscient des données Exif, faisant automatiquement pivoter les vignettes en fonction des métadonnées d'orientation intégrées. Elle fournit également des utilitaires spécialisés pour le tatouage numérique (watermarking), permettant aux images secondaires et aux marqueurs de marque d'être superposés avec une transparence ajustable. Les capacités principales couvrent un large éventail de tâches de traitement d'image, incluant le recadrage sur point focal, le redimensionnement des dimensions et l'ajout de bordures d'image. Le projet gère également l'exportation des images traitées vers des fichiers ou des flux en utilisant des schémas de nommage et des paramètres de compression configurables.

    Enables automated programmatic workflows for applying rotations, borders, and opacity changes to collections of images.

    Javafluent-interfaceimage-processingimage-resizer
    Voir sur GitHub↗5,420
  • zuruoke/watermark-removalAvatar de zuruoke

    zuruoke/watermark-removal

    4,616Voir sur GitHub↗

    Ce logiciel est un système de suppression de filigrane (watermark) qui utilise l'apprentissage automatique et l'inpainting d'image pour supprimer les textes ou logos indésirables des images. Il reconstruit les pixels manquants pour correspondre à l'arrière-plan original, assurant une cohérence visuelle grâce à des modèles pré-entraînés. Le projet inclut un utilitaire de masquage pour isoler des régions spécifiques pour le remplacement de contenu en utilisant des masques binaires, des boîtes englobantes ou des traits de pinceau. Il dispose également d'un processeur par lots qui applique ces tâches de nettoyage à de grands ensembles d'images via une liste de fichiers prédéfinie. Le système gère la préparation des images en normalisant les dimensions et les rapports d'aspect en tenseurs pour aligner les images avec leurs masques correspondants pour le traitement par réseau neuronal.

    Provides a system to automate the removal of designated areas across multiple images.

    Pythondeep-learningmachine-learningpython
    Voir sur GitHub↗4,616
  • thejoefin/text-grabAvatar de TheJoeFin

    TheJoeFin/Text-Grab

    4,610Voir sur GitHub↗

    Text-Grab is a desktop utility that captures text from screen regions, images, PDFs, and native user interface elements using on-device optical character recognition (OCR) and Windows UI Automation. It processes text entirely locally without sending data to external services, and extracts text directly from UI controls with perfect accuracy by reading the accessibility tree. The application also includes a persistent snippet dictionary for instant retrieval of frequently used text via a configurable system-wide hotkey. The tool supports building reusable extraction workflows by saving capture

    Applies saved capture regions and pattern rules to automatically extract text from entire folders of images or PDFs.

    C#dotnetlocal-aimsix
    Voir sur GitHub↗4,610
  • imazen/imageflowAvatar de imazen

    imazen/imageflow

    4,402Voir sur GitHub↗

    Imageflow is a high-performance image manipulation library and composition engine available as a C-compatible library, a command-line image processor, and a dynamic image processing server. It provides the means to decode, encode, and apply complex visual transformations to images through programmatic interfaces, JSON job files, or on-the-fly URL query strings. The system distinguishes itself through a graph-based processing pipeline that allows for single-pass multi-format encoding, generating multiple image sizes and formats from a single decode to reduce overhead. It further features a res

    Ships a command-line tool for automating batch image processing using JSON job files and operation graphs.

    Rustimage-compressionimage-manipulationimage-server
    Voir sur GitHub↗4,402
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  3. Batch Image Processors

Explorer les sous-tags

  • OCR Batch ProcessorsTools that apply OCR to entire folders of images or PDFs using saved configurations and pattern rules. **Distinct from Batch Image Processors:** Distinct from Batch Image Processors: focuses on OCR text extraction with reusable rules, not general image manipulation.