Open Source Computer Vision and Deep Learning Library
OpenCV, the Open Source Computer Vision Library includes state of the art computer vision and deep learning algorithms (including running deep networks) and apps. It is professionally coded and optimized. It can be used in C++, Python, javascipt, Cuda, OpenCL and Matlab. It runs on: Android, iOS, Windows, Linux and MacOS and many embedded implementations such as Raspberry Pi.
- Ideas Page
- Mailing List https://groups.google.com/d/forum/opencv-gsoc-2019
- Main web pages
- Nightly builds of the documentation are at: https://docs.opencv.org/master
- Code is at:
- OpenCV (the core data structures, optimized algorithms, sample and tutorial code): https://github.com/opencv/opencv
- opencv_contrib (new algorithms, applications and GSoC contributions and related tutorial and sample code): https://github.com/opencv/opencv_contrib.git
- opencv_extra (extra data and code samples):https://github.com/opencv/opencv_extra
- downloads for various OS and mobile devices: https://opencv.org/releases.html
It is also useful to look at the change log: https://github.com/opencv/opencv/wiki/ChangeLog and instructions to install on various platforms: https://docs.opencv.org/3.3.1/df/d65/tutorial_table_of_content_introduction.html
Please see our videos for the past several years of GSoC contributions: (2017: https://docs.opencv.org/master/da/d9d/tutorial_dnn_yolo.html) (2015: https://youtu.be/OUbUFn71S4s) (2014: https://youtu.be/3f76HCHJJRA) (2013: https://youtu.be/_TTtN4frMEA).
Many books on OpenCV, google: books opencv
OpenCV 2019 Projects
Allow the OpenCV's DNN module to work with GPUsThe development of GPUs for general purpose computing has revolutionized the field of deep learning. They are critical for training large deep neural...
Computer Vision based Alpha MattingThis project aims to integrate some of the computer vision based alpha matting algorithms into OpenCV. Alpha matting refers to the problem of softly...
Curating Deep Nets for the OpenCV DNN ModuleThe OpenCV's DNN Module allows us to run inference on a pre-trained Deep Neural Network in order to accomplish high end vision tasks with just a few...
Deep learning based super-resolution algorithms based on OpenCV DNNSuper Resolution is a subset of algorithms that aim to up-sample a lower quality image to a higher quality one. It’s goal is to create an up-sampled...
DynamicFusion ImplementationDynamicFusion is the first dense SLAM system capable of reconstructing non-rigidly deforming scenes in real time. It accomplishes this by extending...
Facial Landmark DetectorFacial feature detection and tracking is a high value area of computer vision since humans are interested in what humans are paying attention to,...
Learning-based Super ResolutionSuper resolution is the process of up-scaling and improving the details of an image. Currently the super resolution modules within OpenCV are based...