public List <String> perceptualSim(String imgPath)
{
Console.WriteLine("doing perceptual..");
var stopwatch = new Stopwatch();
stopwatch.Start();
double threshold = 1.5;
Dictionary <String, double> tempResults = new Dictionary <string, double>();
PerceptualSimilarity ps = new PerceptualSimilarity();
Bitmap img = new Bitmap(imgPath);
ComputeHistogram ch = new ComputeHistogram();
Dictionary <LUVClass, float> luv = ch.convertToLuv(ch.getRGBValues(img));
Dictionary <int, float> queryHistogram = ch.quantizeColors(luv, 0);
foreach (String path in fileEntries)
{
Bitmap dImg = new Bitmap(path);
Dictionary <LUVClass, float> luv2 = ch.convertToLuv(ch.getRGBValues(dImg));
Dictionary <int, float> dHistogram = ch.quantizeColors(luv2, 0);
Dictionary <int, float> qHist = new Dictionary <int, float>();
Dictionary <int, float> dHist = new Dictionary <int, float>();
//normalize
foreach (KeyValuePair <int, float> k in queryHistogram)
{
qHist[k.Key] = queryHistogram[k.Key] / (img.Width * img.Height);
}
foreach (KeyValuePair <int, float> k in dHistogram)
{
dHist[k.Key] = dHistogram[k.Key] / (dImg.Width * dImg.Height);
}
double similarity = ps.getSimilarity(qHist, dHist);
if (similarity > threshold)
{
tempResults[path] = similarity;
}
}
stopwatch.Stop();
Console.WriteLine("Done! Time: " + stopwatch.ElapsedMilliseconds);
//printDictionary(tempResults);
return(reversedOrderList(tempResults));
}
