Accord.NET - Machine learning, Computer vision, Statistics and general scientific computing for .NET

•    CSharp

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The Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.

machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpeg

sod - An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)

•    C

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SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.

computer-vision library deep-learning image-processing object-detection cpu real-time convolutional-neural-networks recurrent-neural-networks face-detection facial-landmarks machine-learning-algorithms image-recognition image-analysis vision-framework embedded detection iot-device iot

OpenCV - Open Source Computer Vision

•    C++

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OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision. The library has more than 500 optimized algorithms. It is used to interactive art, to mine inspection, stitching maps on the web on through advanced robotics.

image-processing visualization library 3d-image-processing 3d image-analysis

LiBLaB

•    CSharp

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LibLab is a C# Library, Networking, Camera, Image Processing, Audio Processing, Video Processing and Computer Vision

audio-processing camera computer-vision image-processing networking video-processing

visionworkbench - The NASA Vision Workbench is a general purpose image processing and computer vision library developed by the Autonomous Systems and Robotics (ASR) Area in the Intelligent Systems Division at the NASA Ames Research Center

•    C++

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The NASA Vision Workbench is a general purpose image processing and computer vision library developed by the Autonomous Systems and Robotics (ASR) Area in the Intelligent Systems Division at the NASA Ames Research Center.

PyCNN - Image Processing with Cellular Neural Networks in Python

•    Python

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Cellular Neural Networks (CNN) [wikipedia] [paper] are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors. This python library is the implementation of CNN for the application of Image Processing.

cellular neural-network cnn image-processing cnn-processors paper edge-detection corner-detection library cross-platform feedback computer-vision computer-science control

FILTER

•    Javascript

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This is a library for processing images/video in pure JavaScript using HTML5 features like Canvas, WebWorkers, WebGL and SVG (in progress) or analogs in Node.js. Some filters code has been adapted from open source libraries (mostly c, java and flash, plus a couple from javascript libraries), see the comments in the code for details.

image-processing video-processing computer-vision machine-learning framework

cvat - Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms

•    Javascript

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CVAT is completely re-designed and re-implemented version of Video Annotation Tool from Irvine, California tool. It is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team. Code released under the MIT License.

video-annotation computer-vision computer-vision-annotation deep-learning image-annotation annotation-tool annotation labeling labeling-tool image-labeling image-labelling-tool bounding-boxes boundingbox image-classification annotations imagenet detection recognition tensorflow

ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

•    Python

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A python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. Built with simplicity in mind, ImageAI supports a list of state-of-the-art Machine Learning algorithms for image prediction, custom image prediction, object detection, video detection, video object tracking and image predictions trainings. ImageAI currently supports image prediction and training using 4 different Machine Learning algorithms trained on the ImageNet-1000 dataset. ImageAI also supports object detection, video detection and object tracking using RetinaNet, YOLOv3 and TinyYOLOv3 trained on COCO dataset. Eventually, ImageAI will provide support for a wider and more specialized aspects of Computer Vision including and not limited to image recognition in special environments and special fields.

artificial-intelligence machine-learning prediction image-prediction python3 offline-capable imageai artificial-neural-networks algorithm image-recognition object-detection squeezenet densenet video inceptionv3 detection gpu ai-practice-recommendations

friday - Fast image IO and transformations.

•    Haskell

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friday is an image processing framework for Haskell. It has been designed to build fast, generic and type-safe image processing algorithms. friday also provide some simple computer vision features such as edge detection or histogram processing.

CoreAR - AR(Augmented reality) framework for iOS, based on a visual code like ARToolKit

•    C

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CoreAR.framework is open source AR framework. You can make an AR application using visual code like ARToolKit using this framework. CoreAR.framework does not depend on the other computer vision library like OpenCV. Considered portability, this framework is written only C or C++. The pixel array of an image is passed to CoreAR.framework and then visual code's identification number, rotation and translation matrix are obtained from the image including a visual code. Image processing speed of this framework is about 15 fps on iPhone4. Take notice that CoreAR.framework depends on Quartz Help Library and Real time image processing framework for iOS. You have to download these libraries and put on them at the path where CoreAR.framework has been installed.

Amazon-Forest-Computer-Vision - Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

•    Jupyter

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Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

pytorch data-augmentation kaggle-competition kaggle deep-learning computer-vision keras neural-networks neural-network-example transfer-learning

QVision: Computer Vision Library for Qt

•    C++

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Computer vision and image processing library for Qt.

LTI-Lib (C++ Computer Vision Library)

•    Java

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LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...

opencv - Open Source Computer Vision Library

•    C++

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Please read the contribution guidelines before starting work on a pull request.

opencv c-plus-plus computer-vision deep-learning image-processing

BoofCV - Fast computer vision library written entirely in Java.

•    Java

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BoofCV is an open source real-time computer vision library written entirely in Java and released under the Apache License 2.0. Functionality includes low-level image processing, camera calibration, feature detection/tracking, structure-from-motion, classification, and recognition. The bleeding edge source code can be obtained by cloning the git repository.

javacv - Java interface to OpenCV, FFmpeg, and more

•    Java

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JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, PGR FlyCapture, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, and flandmark), and provides utility classes to make their functionality easier to use on the Java platform, including Android.

opencv ffmpeg computer-vision image-processing

SerpentAI - Game Agent Framework. Helping you create AIs / Bots to play any game you own!

•    Jupyter

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The framework features a large assortment of supporting modules that provide solutions to commonly encountered scenarios when using video games as environments as well as CLI tools to accelerate development. It provides some useful conventions but is absolutely NOT opiniated about what you put in your agents: Want to use the latest, cutting-edge deep reinforcement learning algorithm? ALLOWED. Want to use computer vision techniques, image processing and trigonometry? ALLOWED. Want to randomly press the Left or Right buttons? sigh ALLOWED. To top it all off, Serpent.AI was designed to be entirely plugin-based (for both game support and game agents) so your experiments are actually portable and distributable to your peers and random strangers on the Internet. You'll also be glad to hear that all 3 major OSes are supported: Linux, Windows & macOS.

video-games artificial-intelligence machine-learning computer-vision framework

CloudCV - Large-Scale Distributed Computer Vision As A Cloud Service

•    NodeJS

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An example of using OpenCV library in server environment using Node.js. Here you will see that it's really simple to perform CPU-intense image processing routines in the cloud. A Node.js server handle client requests and calls C++ back-end.

image-processing image classification cloud cloudcv

free-vision

•    Java

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The free-vision project aims at creating a library for computer vision related functions, including camera capture interface, stereo, image processing, camera calibration and so on.