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salient-image

v1.0.2

Published

Image signature: highlighting sparse salient regions

Downloads

5

Readme

salient-image

Simple salient processing on top of node-opencv

H. Xiaodi, H. Jonathan, C. Koch, Image signature: highlighting sparse salient regions, IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (1) (2012) 194–200.

pre-requisites

  • opencv

installation

npm install salient-image

examples

Examples

Images

| assets/input.jpg | assets/output.png | assets/output_with_options.png | |---|---|---| | | | |

Code

var salient = require("salient-image");
var cv = require("opencv");

// Without any options
salient("assets/mona.png", function(err, saliency){
  // saliency is an node-opencv floating-point Matrix
  // maximum is 1, minium is 1
  var width = saliency.width(), height =  saliency.height();
  var imgOutput = new cv.Matrix(width, height, cv.Constants.CV_8U);

  // convert floating point to grey scale Matrix
  saliency.convertTo(imgOutput, cv.Constants.CV_8U, 255);
  imgOutput.save("assets/output.png");
  console.log('Image saved to ./assets/output.png');
});

Example with options

var cv = require("node-opencv");

// With options
salient("assets/mona.png", {
    resize : [200, 200], // the resize size
    sigma : 0.045, // the sigma of the gaussian kernel
    gaussianKernel : [11, 11] // the size of the gaussian kernel
  }, function(err, saliency){
    // saliency is an node-opencv floating-point Matrix
    // maximum is 1, minium is 1
    var width = saliency.width(), height =  saliency.height();
    var imgOutput = new cv.Matrix(width, height, cv.Constants.CV_8U);

    // convert floating point to grey scale Matrix
    saliency.convertTo(imgOutput, cv.Constants.CV_8U, 255);
    imgOutput.save("assets/output_with_options.png");
    console.log('Image saved to ./assets/output_with_options.png');
});

With existing opencv image as input

var img = new cv.Matrix(<...>);

salient({
    image : img,
    resize : [200, 200], // the resize size
    sigma : 0.045, // the sigma of the gaussian kernel
    gaussianKernel : [11, 11] // the size of the gaussian kernel
  }, function(err, saliency){ ... });