Open Source C++ Computer Vision Libraries
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C++ Computer Vision Libraries
View 200 business solutionsBrowse free open source C++ Computer Vision Libraries and projects below. Use the toggles on the left to filter open source C++ Computer Vision Libraries by OS, license, language, programming language, and project status.
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OpenCV
Open Source Computer Vision Library
The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: https://arma.sourceforge.net/download.html * Documentation: https://arma.sourceforge.net/docs.html * Bug reports: https://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/armadillo-lib/armadillo-code -
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COLMAP
Structure-from-Motion and Multi-View Stereo
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. -
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OpenVINO
OpenVINO™ Toolkit repository
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi. -
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reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a platform for AI research to experiment with deep learning, computer vision and reinforcement learning algorithms for autonomous vehicles. For this purpose, AirSim also exposes APIs to retrieve data and control vehicles in a platform independent way. AirSim is fully enabled for multiple vehicles. This capability allows you to create multiple vehicles easily and use APIs to control them. -
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AWS IoT FleetWise Edge
AWS IoT FleetWise Edge Agent
Easily collect, transform, and transfer vehicle data to the cloud in near-real-time. AWS IoT FleetWise makes it easy and cost-effective for automakers to collect, transform, and transfer vehicle data to the cloud in near-real-time and use it to build applications with analytics and machine learning that improve vehicle quality, safety, and autonomy. Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles. Improve electric vehicle (EV) battery range estimates with crowdsourced environmental data, such as weather and driving conditions, from nearby vehicles. Collect select data from nearby vehicles and use it to notify drivers of changing road conditions, such as lane closures or construction. Use near real-time data to proactively detect and mitigate fleet-wide quality issues. -
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GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even better GoogleTest. GoogleTest features an xUnit test framework, a rich set of assertions, user-defined assertions, death tests, among many others. It's been used on a variety of platforms, including Cygwin, Symbian, MinGW and PlatformIO. -
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OculiX
Visual Automation IDE — automate anything you see on screen
OculiX is the evolution of SikuliX, actively maintained with the full agreement of its original creator RaiMan. Automate any desktop application using image recognition (OpenCV) and OCR (Tesseract + PaddleOCR). No access to source code or DOM required — if you can see it, you can automate it. Key features: - Guided step-by-step recorder with live code preview - Image recognition via OpenCV 4.10 - Dual OCR: Tesseract (built-in) + PaddleOCR (neural, high precision) - Local and remote automation via integrated VNC - SSH tunnels via embedded JSch - Cross-platform: Windows, macOS (Apple Silicon M1-M4), Linux - Scripting: Jython, JRuby, Java, PowerShell, AppleScript - Java 17 recommended (Java 8+ supported) - Full CI/CD with automated builds for all platforms Used worldwide for test automation, RPA, and visual regression testing. MIT License. Maintained by oculix-org. -
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OpenPose
Real-time multi-person keypoint detection library for body, face, etc.
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. We would also like to thank all the people who has helped OpenPose in any way. 15, 18 or 25-keypoint body/foot keypoint estimation, including 6 foot keypoints. Runtime invariant to number of detected people. 2x21-keypoint hand keypoint estimation. Runtime depends on number of detected people. 70-keypoint face keypoint estimation. Runtime depends on number of detected people. Input: Image, video, webcam, Flir/Point Grey, IP camera, and support to add your own custom input source (e.g., depth camera). -
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Mobile Robot Programming Toolkit (MRPT)
**MOVED TO GITHUB** ==> https://github.com/MRPT/mrpt
**MOVED TO GITHUB** ==> https://github.com/MRPT/mrpt The Mobile Robot Programming Toolkit (MRPT) is an extensive, cross-platform, and open source C++ library aimed for robotics researchers to design and implement algorithms about Localization, SLAM, Navigation, computer vision. http://www.mrpt.org/ -
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Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train your own DNN models onboard Jetson with PyTorch. Ready to dive into deep learning? It only takes two days. We’ll provide you with all the tools you need, including easy to follow guides, software samples such as TensorRT code, and even pre-trained network models including ImageNet and DetectNet examples. Follow these directions to integrate deep learning into your platform of choice and quickly develop a proof-of-concept design. -
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The Integrating Vision Toolkit (IVT) is a powerful and fast C++ computer vision library with an easy-to-use object-oriented architecture. It offers its own multi-platform GUI toolkit. OpenCV is integrated optionally. Website: http://ivt.sourceforge.net
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cv.jit is a collection of max/msp/jitter externals, abstractions and help files for computer vision applications.
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i3D-converter creates a 3D representation from a couple of images (or a pair of stereo images). This program also performs other Computer Vision operations such as, edge and corner detection, image filtering, getting geometric shapes,...
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Fish4Knowledge Project
Analysis of undersea fish videos
The Fish4knowledge project investigated: information abstraction and storage methods for analyzing undersea video data (from 10E+15 pixels to 10E+12 units of information), machine and human vocabularies for detecting & describing fish, flexible process architectures to process the data and scientific queries and effective specialised user query interfaces. A combination of computer vision, database storage, workflow and human computer interaction methods were used to achieve this. The project used live video feeds from 10 underwater cameras as a testbed for investigating more generally applicable methods for capture, storage, analysis and querying of multiple video streams. We collated a public database from 3 years containing video summaries of the observed fish and associated descriptors. Expert web-based interfaces were developed for use by marine researchers, allowing unprecedented access to live and previously stored videos, or previously extracted information. -
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OpenPR stands for Open Pattern Recognition project and is intended to be an open source library for algorithms of image processing, computer vision, natural language processing, pattern recognition, machine learning and the related fields.
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SITPLUS is a free software framework whose main goal is to provide recreational activities for people with multiple disabilities. It offers new forms of interaction based on computer vision, voice and other peripherals.
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A Computer vision tracking filter for Avisynth. Allows cropping to follow Object of interest. You can watch a small demo at http://www.youtube.com/watch?v=SQ-JtJs7US0
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VideoMan Library
C++ library for image acquisition and visualization
Library for capturing video from cameras, 3d sensors, frame-grabbers, video files and image sequences. It can also display multiple images using OpenGL with different layouts. Easy integration with OpenCV, CUDA... Perfect for computer vision. Keywords: video capture, computer vision, machine vision, opencv, opengl, cameras, video input devices, firewire, usb, gige -
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IPA library is a platform developed for image processing and analysis. It composed by a lot of class of algorithms and functions with loose coupling, which can help users to develop professional applications of image processing or computer vision rapidly
