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revert dct example

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This commit is contained in:
Pierre Colle 2016-11-12 17:34:06 +01:00
parent 430976cb1a
commit aeb2618a34
1 changed files with 9 additions and 107 deletions
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116
examples/mat-dct.js
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@ -1,120 +1,22 @@
var cv = require('../lib/opencv');
var createGaussianKernel = function(sigma){
var cst = 1;
var denom = (2*sigma*sigma);
var factor = 100;
return {
get : function(i,j){
//console.log(cst, denom, ((i/10)*(i/10)+(j/10)*(j/10)), denom, Math.exp((i*i+j*j)/denom))
return cst*Math.exp(-1*(i*i+j*j)/denom);
}
}
};
var convolve = function(m1, m2){
var nCols = m1.width();
var nRows = m1.height();
var max = 0;
var res = new cv.Matrix(nRows, nCols, cv.Constants.CV_32FC1);
for(var i = 0; i < nCols; i++){
for(var j = 0; j < nRows; j++){
sum = 0;
for(var i2 = i-nCols+1; i2 <= i; i2++){
for(var j2 = j-nRows+1; j2 <= j; j2++){
sum += m1.get(i-i2,j-j2)*m2.get(i2,j2)
if(isNaN(sum)){
console.log(m1.get(i-i2,j-j2),m2.get(i2,j2), i-i2,i2,j-j2,j2)
throw("sum is NaN")
}
}
}
//console.log(sum)
if(sum > max){
max = sum
}
res.set(i,j, sum);
}
}
//console.log(max);
for(var i = 0; i < nCols; i++){
for(var j = 0; j < nRows; j++){
res.set(i,j, res.get(i,j)/max);
}
}
return res;
};
var getSalient = function(channel){
var floatInputMatrix = new cv.Matrix();
channel.convertTo(floatInputMatrix, cv.Constants.CV_32F);
var floatAfterDct = floatInputMatrix.dct();
var nCols = channel.width();
var nRows = channel.height();
var signs = new cv.Matrix(nRows, nCols, cv.Constants.CV_32FC1);
var arr = [];
for(var i = 0; i < nCols; i++){
var row = [];
for(var j = 0; j < nRows; j++){
if(floatAfterDct.get(i,j) < 0){
signs.set(i, j, -1);
} else if(floatAfterDct.get(i,j) == 0){
signs.set(i, j, 0);
} else {
signs.set(i, j, 1);
}
}
arr.push(row)
}
// for inverse dct, set argument to "true"
var afterDoubleDct = signs.idct();
//console.log(afterDoubleDct.getData())
var squaredFloat = new cv.Matrix(nRows, nCols, cv.Constants.CV_32FC1);
for(var i = 0; i < nCols; i++){
for(var j = 0; j < nRows; j++){
var v = afterDoubleDct.get(i,j)
squaredFloat.set(i,j, v * v)
}
}
var sigma = 0.3;
var res = convolve(squaredFloat, createGaussianKernel(sigma))
var outChannel = new cv.Matrix(nRows, nCols, cv.Constants.CV_8U);
res.convertTo(outChannel, cv.Constants.CV_8U, 255);
return outChannel;
};
cv.readImage("./files/mona.png", function(err, orig) {
if (err) throw err;
orig.resize(64, 64);
var chan1 = orig.split()[0];
var channels = orig.split();
var outChannels = [];
var floatInputMatrix = new cv.Matrix();
chan1.convertTo(floatInputMatrix, cv.Constants.CV_32F)
for(var chanIdx = 0; chanIdx < channels.length; chanIdx++){
outChannels.push(getSalient(channels[chanIdx]));
}
var foatAfterDct = floatInputMatrix.dct();
var outImg = new cv.Matrix()
// for inverse dct, set argument to "true"
var afterDoubleDct = foatAfterDct.dct(true);
outImg.merge(outChannels)
var intOutImage = new cv.Matrix();
outImg.save("./tmp/dct.png");
afterDoubleDct.convertTo(intOutImage, cv.Constants.CV_8U);
intOutImage.save("./tmp/dct.png");
console.log('Image saved to ./tmp/dct.png');
});