Displaying 1 to 11 from 11 results

javacv - Java interface to OpenCV, FFmpeg, and more

  •    Java

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.

OpenLabeling - Open Source labeling tool to generate the training data in the format YOLO requires.

  •    Python

Bounding box labeler tool to generate the training data in the format YOLO v2 requires. The idea is to use OpenCV so that later it uses SIFT and Tracking algorithms to make labeling easier.

cylon-opencv - Cylon adaptor and driver for OpenCV

  •    Javascript

Cylon.js (http://cylonjs.com) is a JavaScript framework for robotics, physical computing, and the Internet of Things (IoT).Want to use the Go programming language to power your robots? Check out our sister project Gobot (http://gobot.io).




gocv - Go package for computer vision using OpenCV 3.3+

  •    Go

The GoCV package provides Go language bindings for the OpenCV 3 computer vision library.GoCV supports the latest release of OpenCV (v3.3) on Linux, OS X, and (soon) Windows.

go-cv - Computer Vision package in pure Go taking advantage of SIMD acceleration

  •    Go

go-cv is a computer vision and image processing library for Go using Golang assembly. It is a works-in-progress wrapper around the Simd library. For now most work has been done on the SSE2 version. See the underlying package go-cv for more information.

ImShow-Java-OpenCV - an alternative to imshow() in C++ OpenCV for Java OpenCV

  •    Java

An alternative to imshow() in C++ OpenCV for Java OpenCV. Basically helps to display the Mat images or Video in the Java - Opencv which lacks imshow like API from C++ Opencv interface. For ways to customise the GUI Frame or Window see the example.

powerai-counting-cars - Run a Jupyter Notebook to detect, track, and count cars in a video using PowerAI Vision and OpenCV

  •    Jupyter

Whether you are counting cars on a road or products on a conveyer belt, there are many use cases for computer vision with video. With video as input, automatic labeling can be used to create a better classifier with less manual effort. This Code Pattern shows you how to create and use a classifier to identify objects in motion and then track the objects and count them as they enter designated regions of interest. In this Code Pattern, we will create a video car counter using PowerAI Vision Video Data Platform, OpenCV and a Jupyter Notebook. We'll use a little manual labeling and a lot of automatic labeling to train an object classifier to recognize cars on a highway. We'll load another car video into a Jupyter Notebook where we'll process the individual frames and annotate the video.


OpenCVSharp-Samples - A collection of samples about using OpenCV in .NET applications.

  •    CSharp

A collection of samples about using OpenCV in .NET applications.

gocv-alpine - GoCV-compatible OpenCV 3.4 Alpine 3.7 Docker image

  •    Shell

This is a build image for the multi-stage image provisioning as well as runtime image to work with gocv-based binaries. Sample Docker file you can find here.