Displaying 1 to 20 from 55 results

FaceTracker - Real time deformable face tracking in C++ with OpenCV 3.

  •    C++

FaceTracker is a library for deformable face tracking written in C++ using OpenCV 2, authored by Jason Saragih and maintained by Kyle McDonald. It is available free for non-commercial use, and may be redistributed under these conditions. Please see license.md for complete details. For commercial use, request a quote.

opencv - Open Source Computer Vision Library

  •    C++

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

openFrameworks - openFrameworks is a community-developed cross platform toolkit for creative coding in C++

  •    C++

docs has some documentation around OF usage, per platform things to consider, etc. You should definitely take a look in there; for example, if you are on OSX, read the osx.md. apps and examples are where projects go -- examples contains a variety of projects that show you how to use OF, and apps is where your own projects will go. libs contains the libraries that OF uses, including the openframeworks core itself. addons are for additional functionality that's not part of the core. export is for DLLs and dylibs that need to be put in each compiled project. The scripts folder has the templates and small scripts for automating OF per platform. project generator is a GUI based tool for making new projects - this folder is only there in packaged releases. One idea that's important is that OF releases are designed to be self-contained. You can put them anywhere on your hard drive, but it's not possible to mix different releases of OF together, so please keep each release (0.8.0, 0.8.1) separate. Projects may generally work from release to release, but this is not guaranteed. Because OF is self-contained, there's extensive use of local file paths (ie, ../../../) throughout OF. It's important to be aware of how directories are structured. A common error is to take a project and move it so that it's a level below or above where it used to be compared to the root of OF. This means that links such as ../../../libs will break.

opentrack - Head tracking software for MS Windows, Linux, and Apple OSX

  •    C++

opentrack project home at <http://github.com/opentrack/opentrack>. Please first refer to <https://github.com/opentrack/opentrack/wiki> for new user guide, frequent answers, specific tracker/filter documentation. See also the gameplay video with opentrack set up.




bgslibrary - A background subtraction library

  •    C++

The BGSLibrary was developed early 2012 by Andrews Sobral to provide an easy-to-use C++ framework for foreground-background separation in videos based on OpenCV. The bgslibrary is compatible with OpenCV 2.x and 3.x, and compiles under Windows, Linux, and Mac OS X. Currently the library contains 43 algorithms. The source code is available under GNU GPLv3 license, the library is available free of charge to all users, academic and commercial.

openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation

  •    C++

OpenPose represents the first real-time multi-person system to jointly detect human body, hand, and facial keypoints (in total 135 keypoints) on single images. For further details, check all released features and release notes.

OpenCV3-Intro-Book-Src - :blue_book:《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code

  •    C++

:blue_book:《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code

opencv4nodejs - Asynchronous OpenCV 3

  •    C++

By its nature, JavaScript lacks the performance to implement Computer Vision tasks efficiently. Therefore this package brings the performance of the native OpenCV library to your Node.js application. This project targets OpenCV 3 and provides an asynchronous as well as an synchronous API. The ultimate goal of this project is to provide a comprehensive collection of Node.js bindings to the API of OpenCV and the OpenCV-contrib modules. An overview of available bindings can be found in the API Documentation. Furthermore, contribution is highly appreciated. If you want to get involved you can have a look at the contribution guide.


eyeLike - A webcam based pupil tracking implementation.

  •    C++

An OpenCV based webcam gaze tracker based on a simple image gradient-based eye center algorithm by Fabian Timm.This does not track gaze yet. It is basically just a developer reference implementation of Fabian Timm's algorithm that shows some debugging windows with points on your pupils.

ofxCv - Alternative approach to interfacing with OpenCv from openFrameworks.

  •    C++

ofxCv represents an alternative approach to wrapping OpenCV for openFrameworks. Or download the source from GitHub here, unzip the folder, rename it from ofxCv-master to ofxCv and place it in your openFrameworks/addons folder.

opencv - OpenCV projects: Face Recognition, Machine Learning, Colormaps, Local Binary Patterns, Examples

  •    C++

This repository contains OpenCV code and documents. More (maybe) here: https://www.bytefish.de.

captcha-break - captcha break based on opencv2, tesseract-ocr and some machine learning algorithm.

  •    C++

captcha break based on opencv2, tesseract-ocr and some machine learning algorithm. The simplest captcha breaking.

grid_map - Universal grid map library for mobile robotic mapping

  •    C++

This is a C++ library with ROS interface to manage two-dimensional grid maps with multiple data layers. It is designed for mobile robotic mapping to store data such as elevation, variance, color, friction coefficient, foothold quality, surface normal, traversability etc. It is used in the Robot-Centric Elevation Mapping package designed for rough terrain navigation. The grid map package has been tested with ROS Indigo, Jade (under Ubuntu 14.04) and Kinetic (under Ubuntu 16.04). This is research code, expect that it changes often and any fitness for a particular purpose is disclaimed.

simple_vehicle_counting - Vehicle Detection, Tracking and Counting

  •    C++

Note: the procedure is similar for OpenCV 2.4.x and Visual Studio 2013. Go to Windows console.

vehicle_detection_haarcascades - Vehicle Detection by Haar Cascades with OpenCV

  •    C++

Hello everyone, An easy way to perform vehicle detection is by using Haar Cascades. Currently, I don't have a detailed tutorial about it, but you can get some extra information in the OpenCV homepage, see Cascade Classifier page. See also Cascade Classifier Training for training your own cascade classifier. The haar-cascade cars.xml was trained using 526 images of cars from the rear (360 x 240 pixels, no scale). The images were extracted from the Car dataset proposed by Brad Philip and Paul Updike taken of the freeways of southern California.

flow-io-opencv - Fork and OpenCV wrapper of the optical flow I/O and visualization code provided as part of the Sintel dataset [1]

  •    C++

lib/README-FlowIO: the original README shipped with the Sintel dataset.lib/imageLib/README: the original README of imageLib shipped with the Sintel dataset.

hierarchical-graph-based-video-segmentation - Implementation of the hierarchical graph-based video segmentation algorithm proposed by Grundmann et al

  •    C++

This is an implementation of the hierarchical graph-based video segmentation algorithm proposed by Grundmann et al. [1] based on the graph-based image segmentation algorithm by Felzenswalb and Huttenlocher [2].Further, evaluation metrics based on the Precision-Recall Framework for videos [3,4], Undersegmentation Error [4,5] and Achievable Segmentation Accuracy [3] are provided.

seeds-revised - Implementation of the superpixel algorithm called SEEDS [1].

  •    C++

Update: SEEDS Revised is also part of davidstutz/superpixel-benchmark.Update: SEEDS Revised is also available as part of Superpixels Revisited, a library providing command line tools for seven state-of-the-art superpixel algorithms.

superpixel-benchmark - An extensive evaluation and comparison of 28 state-of-the-art superpixel algorithms on 5 datasets

  •    C++

This repository contains the source code used for evaluation in [1], a large-scale comparison of state-of-the-art superpixel algorithms.This repository subsumes earlier work on comparing superpixel algorithms: davidstutz/gcpr2015-superpixels, davidstutz/superpixels-revisited.