OpenCVopencv/opencv
OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
72 libraries, 30 updated this year
Libraries that read images and video. OpenCV is the foundation almost everything else builds on, with bindings for C++, Python, Java, .NET (Emgu CV), Go (GoCV) and MATLAB (mexopencv). For deep learning models, Ultralytics YOLO handles real-time object detection, detectron2 covers detection and segmentation research, and timm collects hundreds of pretrained image backbones.
72 libraries
OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
Ultralytics' YOLOv8 implementation with C++ support for real-time object detection and tracking, optimized for edge devices.
Face recognition library that recognizes and manipulates faces from Python or from the command line.
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more.
FAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.
A real-time multi-person keypoint detection library for body, face, hands, and foot estimation
MLX is an array framework for machine learning on Apple silicon, developed by Apple machine learning research.
FAIR's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN. It is written in Python and powered by the Caffe2 deep learning framework.
A lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for Python covering cutting-edge models such as VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, Dlib and ArcFace.
Free and open source face recognition with deep neural networks.
А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.
DLib has C++ and Python interfaces for face detection and training general object detectors.
A PyTorch-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.
Machine learning from Apple. Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.
AutoML for Image, Text, Tabular, Time-Series, and MultiModal Data.
Fastest unstructured dataset management for TensorFlow/PyTorch. Stream & version-control data. Store even petabyte-scale data in a single numpy-like array on the cloud accessible on any machine. Visit activeloop.ai for more info.
Face recognition system that can be easily integrated into any system without prior machine learning skills. CompreFace provides REST API for face recognition, face verification, face detection, face mask detection, landmark detection, age, and gender recognition and is easily deployed with docker.
Serpent.AI is a game agent framework that allows you to turn any video game you own into a sandbox to develop AI and machine learning experiments. For both researchers and hobbyists.
Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm, Artificial Fish Swarm Algorithm in Python)
A collection of algorithms for image processing in Python.
Python-tesseract is an optical character recognition (OCR) tool for python. That is, it will recognize and "read" the text embedded in images. Python-tesseract is a wrapper for Google's Tesseract-OCR Engine.
Highly optimized artificial intelligence and machine learning library written in Swift.
A TensorFlow Keras-based toolkit that offers pre-trained segmentation models for computer vision tasks. It simplifies the development of image segmentation applications by providing a collection of popular architecture implementations, such as UNet and PSPNet, along with pre-trained weights, making it easier for researchers and developers to achieve high-quality pixel-level object segmentation in images.
A library containing Convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.
A PyTorch implementation of CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
Lightly is a computer vision framework for self-supervised learning.
High-level utils for PyTorch DL & RL research. It was developed with a focus on reproducibility, fast experimentation and code/ideas reusing. Being able to research/develop something new, rather than write another regular train loop.
As known as L0CV, is a new generation of computer vision open source online learning media, a cross-platform interactive learning framework integrating graphics, source code and HTML. the L0CV ecosystem — Notebook, Datasets, Source Code, and from Diving-in to Advanced — as well as the L0CV Hub.
An open source computer vision framework that gives access to several high-powered computer vision libraries, such as OpenCV. Written on Python and runs on Mac, Windows, and Ubuntu Linux.
A machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.
Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.
Deep learning based cutting-edge facial detector for Python coming with facial landmarks
A C++ edge video AI engine for RTSP ingestion, CV/VLM inference, visual pipeline orchestration, alarms, and event delivery on Sophon and Rockchip NPUs.
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Pretrain computer vision models on unlabeled data for industrial applications
A PyTorch-based framework to train and validate the models producing high-quality embeddings.
TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs).
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library designed for real-time gesture recognition.
A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).
Collection and a development kit of MATLAB mex functions for OpenCV library.
Train and run a computer vision model with 5-10 lines of code.
VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.
Generative AI Image Toolset with GANs and Diffusion for Real-World Applications.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.