Search Results for "image segmentation tools"
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Showing 1107 open source projects for "image segmentation tools"
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Segmentation Models
Segmentation models with pretrained backbones. PyTorch
Segmentation models with pre trained backbones. High-level API (just two lines to create a neural network) 9 models architectures for binary and multi class segmentation (including legendary Unet) 124 available encoders (and 500+ encoders from timm) All encoders have pre-trained weights for faster and better convergence. Popular metrics and losses for training routines. -
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labelme Image Polygonal Annotation
Image polygonal annotation with Python
Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Image annotation for polygon, rectangle, circle, line and point. Image flag annotation for classification and cleaning. Video annotation. (video annotation). GUI customization (predefined labels / flags, auto-saving, label validation, etc). Exporting VOC-format dataset for semantic/instance segmentation. -
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MatImage
Image Processing library for Matlab
matImage is an open-source MATLAB library for image processing and analysis. It provides a variety of tools for image enhancement, segmentation, and feature extraction. It’s especially useful for users working on biomedical images or those needing detailed image analysis in MATLAB. -
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Qwen-Image
Qwen-Image is a powerful image generation foundation model
...The model excels not only in text rendering but also in a wide range of artistic styles, including photorealistic, impressionist, anime, and minimalist aesthetics. Qwen-Image supports sophisticated editing tasks such as style transfer, object insertion and removal, detail enhancement, and even human pose manipulation, making it suitable for both professional and casual users. It also includes advanced image understanding capabilities like object detection, semantic segmentation, depth and edge estimation, and novel view synthesis. -
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SimpleITK
A layer built on top of the Insight Toolkit (ITK)
SimpleITK is an image analysis toolkit with a large number of components supporting general filtering operations, image segmentation and registration. It is built on top of the Insight Segmentation and Registration Toolkit ITK with the intent of providing a simplified interface to ITK. SimpleITK itself is written in C++ but is available for a large number of programming languages. -
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ComfyUI Essentials
Essential nodes that are weirdly missing from ComfyUI core
ComfyUI_essentials is a ComfyUI custom node collection that adds practical nodes the author considers missing from the ComfyUI core. The project focuses on useful workflow building blocks rather than generic duplicates, with nodes for image handling, mask processing, sampling, segmentation, conditioning, text, and miscellaneous operations. Its image tools include functions for batching, cropping, flipping, resizing, compositing, background removal, color matching, LUT application, sharpening, tiling, and latent previewing. Its mask tools include blur, smoothing, fixing, flipping, color-based masks, segmentation masks, bounding boxes, transition masks, and batch utilities. ... -
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ITK-SNAP is a tool for segmenting anatomical structures in medical images. It provides an automatic active contour segmentation pipeline, along with supporting manual segmentation toolbox. ITK-SNAP has a full-featured UI aimed at clinical researchers.
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Medical Img Segmentation Suite
A software providing easy ways to segment structures in medical images
- 15 segmentation tools (FloodFill Strict, Adaptive Gaussian Threshold, Manual Brush (Freehand Lasso), Polygon Lasso (Click Points), Manual Bounding Box, Auto Bounding Box, Local Otsu Auto-Threshold, K-Means Clustering, Watershed, GrabCut AI, Canny Edge + Morphological Close, Morphologic Active Contours, Interactive Heatmap, Topographical Relief Map, Segment Anything AI) - Hybrid Layout (1 window with editor tools or Split-View with a preview window) - Intelligent file management (once a folder is loaded, the system recognizes which files already have masks and leaves them in the background) - Real-time filter application (CLAHE, Global Histogram Equalization, Top-Hat, Bottom-Hat, Multi-Scale Retinex, Homomorphic Filter, Sharpness Control) - Three mask and label options (conventional masks in - Lesion shape, lesion region bounding boxes, and heatmap to outline the lesion and its secondary components) - Brush/cursor sensitivity control... -
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Segment Anything
Provides code for running inference with the SegmentAnything Model
Segment Anything (SAM) is a foundation model for image segmentation that’s designed to work “out of the box” on a wide variety of images without task-specific fine-tuning. It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. ... -
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image-optimizer
Easily optimize images using PHP
Spatie Image Optimizer is a PHP package that automatically optimizes images by compressing them without losing quality. It works with various image formats, including JPEG, PNG, GIF, and SVG, by using underlying optimization tools. The package is lightweight and can be easily integrated into web applications to reduce image file sizes, enhancing loading speed and performance. -
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GeoAI
GeoAI: Artificial Intelligence for Geospatial Data
GeoAI is a comprehensive open-source Python package designed to integrate artificial intelligence techniques with geospatial data analysis, enabling users to perform advanced geographic modeling and visualization tasks with ease. It provides a unified framework that combines machine learning libraries such as PyTorch and Transformers with geospatial tools, allowing users to process satellite imagery, aerial photos, and vector datasets in a streamlined workflow. The platform supports a wide range of tasks including image classification, object detection, segmentation, and change detection, making it suitable for applications in environmental monitoring, urban planning, and disaster response. ... -
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SAM 2
The repository provides code for running inference with SAM 2
...SAM2 comes with pretrained weights and easy-to-use APIs, enabling developers and researchers to integrate promptable segmentation into annotation tools, vision pipelines, or downstream tasks. The project also includes scripts and notebooks to compare SAM2 against SAM on edge cases, benchmarks showing improvements, and evaluation suites to measure mask quality metrics like IoU and boundary error. -
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LISA
LISA: Reasoning Segmentation via Large Language Model
LISA is an open-source multimodal AI system designed to enable language models to perform pixel-level reasoning and segmentation tasks on images. The project introduces a framework where a large language model can interpret natural language instructions and produce segmentation masks that highlight relevant regions in an image. Instead of relying solely on predefined object categories, the model is capable of reasoning about complex textual queries and translating them into visual segmentation outputs. ... -
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image-blaster
An image-to-world skillset for Claude
...It can generate dynamic object models, static environment captures, ambient loops, and object-specific physics sounds. The resulting assets can be used in game engines, 3D tools, and web-based graphics projects. image-blaster is best understood as an experimental agent workflow for quickly jumpstarting interactive worlds rather than a full 3D authoring suite. -
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Re-image the Windows
These scripts to configure a ready-to-use Windows environment
Reimage-Windows is a repo for automating and documenting the process of reinstalling or “reimaging” Windows, turning what is normally a manual, error-prone chore into a repeatable pipeline. It bundles scripts, configuration, and notes so that after a clean Windows install you can run one or two commands to get your environment back. The project is aimed at people who rebuild machines often, maintain several PCs, or just want a disaster-recovery style setup for Windows. It encourages treating... -
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HivisionIDPhoto
HivisionIDPhotos: a lightweight and efficient AI ID photos tools
...It also allows the generation of layout sheets such as six-inch photo arrangements for printing multiple ID photos on a single page. The project focuses on building a practical pipeline for automated ID photo production using AI-based segmentation and image processing techniques. -
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Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about... -
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Advanced AI explainability for PyTorch
Advanced AI Explainability for computer vision
pytorch-grad-cam is an open-source library that provides advanced explainable AI techniques for interpreting the predictions of deep learning models used in computer vision. The project implements Grad-CAM and several related visualization methods that highlight the regions of an image that most strongly influence a neural network’s decision. These visualization techniques allow developers and researchers to better understand how convolutional neural networks and transformer-based vision models make predictions. The library supports a wide variety of tasks including image classification, object detection, semantic segmentation, and similarity analysis. ... -
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Qwen-MM-Plugins
Make any agent harness multimodal-native
Qwen-MM-Plugins is a collection of native multimodal capabilities that can extend Qwen-powered agent harnesses beyond text-only workflows. Each capability combines an instructional skill with an optional MCP server that exposes specialized tools. The core package can inspect images, videos, documents, and 3D models while providing OCR, grounding, segmentation, transcription, and visual question answering. Additional modules support long-video memory, audio-video analysis, media generation, video editing, Blender, FreeCAD, and educational content creation. Dynamic-resolution processing automatically adjusts visual inputs according to the detail required by the model. ... -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. ... -
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SAM 3
Code for running inference and finetuning with SAM 3 model
SAM 3 (Segment Anything Model 3) is a unified foundation model for promptable segmentation in both images and videos, capable of detecting, segmenting, and tracking objects. It accepts both text prompts (open-vocabulary concepts like “red car” or “goalkeeper in white”) and visual prompts (points, boxes, masks) and returns high-quality masks, boxes, and scores for the requested concepts. Compared with SAM 2, SAM 3 introduces the ability to exhaustively segment all instances of an... -
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Transformers
State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX
...Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments. -
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Static Analysis Tools for PHP
Docker image that provides static analysis tools for PHP
Docker image providing static analysis tools for PHP. The list of available tools and the installer is actually managed in the jakzal/toolbox repository. Docker image with quality analysis tools for PHP. To run the selected tool inside the container, you'll need to mount the project directory on the container with -v "$(pwd):/project". Some tools like to write to the /tmp directory (like PHPStan, or Behat in some cases), therefore it's often useful to share it between docker runs, i.e. with -v "$(pwd)/tmp-phpqa:/tmp". ... -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. ... -
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Depth Anything 3
Recovering the Visual Space from Any Views
...The model can be applied to photography, AR/VR content creation, robotics perception, and 3D reconstruction workflows, making it versatile across industries and research domains. It includes support for high-resolution inputs and post-processing tools that refine depth predictions, helping downstream tasks like segmentation, bounding volume estimation, and mixed reality layering.
