nvision

nvision is a header-only C++ library for computer vision applications using the Eigen3 library.

nvision provides:

• image filters like gauss, box, laplace, sobel and scharr
• feature detectors like Harris, ShiTomasi, FAST and ORB
• feature descriptors like BRIEF and ORB
• optical flow estimation using LucasKanade and HornSchunck
• projective routines for triangulation and camera calibration
• handling files in pgm, ppm, png and jpgformat

Install

nvision uses the build2 build system. You can easily use it as dependency by adding it to your manifest file. It will also resolve all additional dependecies of nvision for you.

depends: libnvision ^1.0.0 # base library with CV algorithms
depends: libnvision-jpeg ^1.0.0 # for JPEG support
depends: libnvision-png ^1.0.0 # for PNG support

Otherwise you can simply copy the header files into your project and include them directly.

The core library and all algorithms only require Eigen3 as dependency. Make sure it can be found by your build system

For loading PNG and JPEG files you will need to link against libpng and libjpg-turbo additionally.

In Debian based systems you can simply install these dependencies using apt-get.

apt-get install libeigen3-dev libpng-dev libjpg-turbo-dev

Usage

nvision has many different modules and classes for filtering, feature or edge detection, optical flow and projective geometry.

Check the libnvision-exmaples/ directory for detailed examples and have a look at the docs for detailed information.

A simple getting started example with a gauss filter:

#include <iostream>
#include <nvision/filter.h>
#include <nvision/imageio.h>

int main(int argc, const char **argv)
{
    if(argc != 3)
    {
        std::cerr << "usage: simple_gauss <in-file> <out-file>" << std::endl;
        return -1;
    }

    // Each value per pixel and depth is representd by
    // a 8-Bit integer.
    nvision::Image<nvision::RGB> src;

    // Load the image from a file. The file type is determined by the extension
    // of the file.
    std::cout << "Load " << argv[1] << std::endl;
    nvision::imload(argv[1], src);

    // Create a Gauss filter object. The template parameter determines the
    // internal Scalar type, which is used for computations (e.g. Kernel and
    // Kernel application).
    nvision::GaussFilter<nvision::float32, 9> filter(8.0f);

    // Apply the filter to the source image and store it in dest.
    std::cout << "Apply filter" << std::endl;
    nvision::Image<nvision::RGB> dest = filter(src);

    // Save the image to a file. The file type is determined by the extension
    // of the file.
    std::cout << "Save " << argv[2] << std::endl;
    nvision::imsave(argv[2], dest);

    return 0;
}

A simple getting started example with FAST feature detection:

/* simple_fast.cpp
 *
 * Author: Fabian Meyer
 * Created On: 18 Jun 2019
 */

#include <iostream>
#include <nvision/feature.h>
#include <nvision/draw.h>
#include <nvision/imageio.h>

using namespace nvision;

int main(int argc, const char **argv)
{
    if(argc != 3)
    {
        std::cerr << "usage: simple_fast <in-file> <out-file>" << std::endl;
        return -1;
    }

    // Each value per pixel and depth is representd by
    // a 8-Bit integer.
    nvision::Image<nvision::RGBf> src;

    // Load the image from a file. The file type is determined by the extension
    // of the file.
    std::cout << "Load " << argv[1] << std::endl;
    nvision::imload(argv[1], src);

    std::cout << "Convert to gray scale" << std::endl;
    nvision::Image<nvision::Grayf> gray = nvision::image::convert<Grayf>(src);

    // Create a FAST feature detector object. The template parameter determines the
    // internal Scalar type, which is used for computations and feature point
    // representation.
    nvision::FASTFeature<nvision::float32> detector;

    // Extract feature points from the image.
    using FeatureMatrix = typename nvision::FASTFeature<nvision::float32>::FeatureMatrix;
    FeatureMatrix keypoints;
    std::cout << "Detect features" << std::endl;
    detector(gray, keypoints);

    std::cout << "Draw " << keypoints.cols() << " keypoints" << std::endl;
    nvision::image::draw(src, keypoints, nvision::Marker::Circle, nvision::color::red<RGBf>());

    // Save the image to a file. The file type is determined by the extension
    // of the file.
    std::cout << "Save " << argv[2] << std::endl;
    nvision::imsave(argv[2], src);

    return 0;

    return 0;
}

Compile

nvision can be compiled using the build2 build system.

bdep init -C @gcc-debug cc config.config.load=build-config/gcc.debug.build
b

This will resolve all dependencies of nvision and build all examples and unit tests with your default compiler. You can run the unit tests using build2 again.

bdep test