public void BhattacharyyaTest2()
{
double[] x = { 2, 0, 0 };
double[] y = { 1, 0, 0 };
double[,] covX =
{
{ 2, 3, 0 },
{ 3, 0, 0 },
{ 0, 0, 0 }
};
double[,] covY =
{
{ 2, 1, 0 },
{ 1, 0, 0 },
{ 0, 0, 0 }
};
// Run actual test
double expected = 0.1438410362258904;
double actual = new Bhattacharyya().Distance(x, covX, y, covY);
Assert.AreEqual(expected, actual, 1e-6);
Assert.IsFalse(Double.IsNaN(actual));
}
public void IndexFiles(FileInfo[] imageFiles, BackgroundWorker IndexBgWorker, object argument = null)
{
List <BhattacharyyaRecord> listOfRecords = new List <BhattacharyyaRecord>();
Double[,] normalizedHistogram = new double[16, 16];
int totalFileCount = imageFiles.Length;
for (int i = 0; i < totalFileCount; i++)
{
var fi = imageFiles[i];
using (Image img = Image.FromFile(fi.FullName))
{
normalizedHistogram = Bhattacharyya.CalculateNormalizedHistogram(img);
}
BhattacharyyaRecord record = new BhattacharyyaRecord
{
Id = i,
ImageName = fi.Name,
ImagePath = fi.FullName,
NormalizedHistogram = MultiToSingle(normalizedHistogram)
};
listOfRecords.Add(record);
IndexBgWorker.ReportProgress(i);
}
BinaryAlgoRepository <List <BhattacharyyaRecord> > repo = new BinaryAlgoRepository <List <BhattacharyyaRecord> >();
repo.Save(listOfRecords);
}
public void BhattacharyyaTest1()
{
double[] histogram1 = { 0.1, 0.5, 0.4 };
double[] histogram2 = { 0.7, 0.2, 0.1 };
double expected = 0.468184902444219;
double actual = new Bhattacharyya().Distance(histogram1, histogram2);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
public void BhattacharyyaTest1()
{
double[] histogram1 = { 0.1, 0.5, 0.4 };
double[] histogram2 = { 0.7, 0.2, 0.1 };
double expected = 0.468184902444219;
double actual = new Bhattacharyya().Distance(histogram1, histogram2);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
public void BhattacharyyaTest4()
{
double[,] X =
{
{ 0.20, 0.52 },
{ 1.52, 2.53 },
{ 7.21, 0.92 },
};
double expected = 0.0;
double actual = new Bhattacharyya().Distance(X, X);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
private void btnImageCompare_Click(object sender, EventArgs e)
{
string orgImagePath = lblImage1Path.Text;
string dupImagePath = lblImage2Path.Text;
bool isFirstImageEmpty = string.IsNullOrWhiteSpace(orgImagePath);
bool isSecondImageEmpty = string.IsNullOrWhiteSpace(dupImagePath);
if (isFirstImageEmpty || isSecondImageEmpty)
{
MessageBox.Show("Please select images before compare");
}
bool ispHashSelected = cbCompareAlgorithm.Text == "pHash";
bool isBhattacharyyaSelected = cbCompareAlgorithm.Text == "Bhattacharyya";
if (ispHashSelected)
{
var percentage = ImageHashing.Similarity(orgImagePath, dupImagePath);
percentage = Math.Round(percentage, 3);
txtPerDiff.Text = percentage.ToString();
}
else if (isBhattacharyyaSelected)
{
Image img1 = Image.FromFile(orgImagePath);
Image img2 = Image.FromFile(dupImagePath);
var percentage = Bhattacharyya.BhattacharyyaDifference(img1, img2);
percentage = percentage * 100;
percentage = Math.Round(percentage, 3);
txtPerDiff.Text = percentage.ToString();
}
else
{
int imageAlgoIndex = cbCompareAlgorithm.SelectedIndex;
ErrorMetric imageAlgo = (ErrorMetric)imageAlgoIndex;
MagickImage orgImage = new MagickImage(orgImagePath);
MagickImage dupImage = new MagickImage(dupImagePath);
var percentage = orgImage.Compare(dupImage, imageAlgo);
txtPerDiff.Text = percentage.ToString();
orgImage.Dispose();
dupImage.Dispose();
}
}
public void IndexFilesAsync(FileInfo[] imageFiles, BackgroundWorker IndexBgWorker, object argument = null)
{
ConcurrentBag <BhattacharyyaRecord> listOfRecords = new ConcurrentBag <BhattacharyyaRecord>();
Double[,] normalizedHistogram = new double[16, 16];
int totalFileCount = imageFiles.Length;
int i = 0; long nextSequence;
//In the class scope:
Object lockMe = new Object();
Parallel.ForEach(imageFiles, currentImageFile =>
{
var fi = currentImageFile;
using (Image img = Image.FromFile(fi.FullName))
{
normalizedHistogram = Bhattacharyya.CalculateNormalizedHistogram(img);
}
lock (lockMe)
{
nextSequence = i++;
}
BhattacharyyaRecord record = new BhattacharyyaRecord
{
Id = nextSequence,
ImageName = fi.Name,
ImagePath = fi.FullName,
NormalizedHistogram = MultiToSingle(normalizedHistogram)
};
listOfRecords.Add(record);
IndexBgWorker.ReportProgress(i);
});
BinaryAlgoRepository <List <BhattacharyyaRecord> > repo = new BinaryAlgoRepository <List <BhattacharyyaRecord> >();
repo.Save(listOfRecords.ToList());
}
public void BhattacharyyaTest()
{
double[,] X =
{
{ 0.20, 0.52 },
{ 1.52, 2.53 },
{ 7.21, 0.92 },
};
double[,] Y =
{
{ 9.42, 5.21 },
{ 1.12, 3.14 },
{ 5.21, 2.12 },
};
double expected = 0.45095821066601938;
double actual = new Bhattacharyya().Distance(X, Y);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
public void BhattacharyyaTest()
{
double[,] X =
{
{ 0.20, 0.52 },
{ 1.52, 2.53 },
{ 7.21, 0.92 },
};
double[,] Y =
{
{ 9.42, 5.21 },
{ 1.12, 3.14 },
{ 5.21, 2.12 },
};
double expected = 0.45095821066601938;
double actual = new Bhattacharyya().Distance(X, Y);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
private void ComputeDistances(FlowProfile profile1, FlowProfile profile2)
{
var measuresTable = new DataTable();
measuresTable.Columns.Add("Target", typeof(string));
measuresTable.Columns.Add("Count 1", typeof(double));
measuresTable.Columns.Add("Count 2", typeof(double));
measuresTable.Columns.Add("Distance", typeof(double));
foreach (var m1 in profile1)
{
if (profile2.TryGetValue(m1.Key, out var m2))
{
var b = new Bhattacharyya();
var dist = b.Distance(m1.Value.Samples.ToArray(), m2.Samples.ToArray());
measuresTable.Rows.Add(m1.Key, m1.Value.Samples.Count, m2.Samples.Count, dist);
}
}
Console.WriteLine("Distances:");
ConsoleTableBuilder.From(measuresTable)
.WithFormat(ConsoleTableBuilderFormat.MarkDown)
.ExportAndWriteLine();
}
public void BhattacharyyaTest2()
{
double[] x = { 2, 0, 0 };
double[] y = { 1, 0, 0 };
double[,] covX =
{
{ 2, 3, 0 },
{ 3, 0, 0 },
{ 0, 0, 0 }
};
double[,] covY =
{
{ 2, 1, 0 },
{ 1, 0, 0 },
{ 0, 0, 0 }
};
// Run actual test
double expected = 0.1438410362258904;
double actual = new Bhattacharyya().Distance(x, covX, y, covY);
Assert.AreEqual(expected, actual, 1e-6);
Assert.IsFalse(Double.IsNaN(actual));
}
public void BhattacharyyaTest4()
{
double[,] X =
{
{ 0.20, 0.52 },
{ 1.52, 2.53 },
{ 7.21, 0.92 },
};
double expected = 0.0;
double actual = new Bhattacharyya().Distance(X, X);
Assert.AreEqual(expected, actual, 1e-10);
Assert.IsFalse(Double.IsNaN(actual));
}
private void btnImageCompare_Click(object sender, EventArgs e)
{
string pictureDirectory = DirectoryHelper.PictureDirectory;
if (string.IsNullOrWhiteSpace(pictureDirectory))
{
MessageBox.Show("Can't find picture directory, this form can't work!");
return;
}
string OrginalFile = Path.Combine(pictureDirectory, "Original.jpg");
MagickImage orgImage = null;
MagickImage dupImage = null;
DirectoryInfo di = new DirectoryInfo(pictureDirectory);
Dictionary <string, double> imageCompareData = new Dictionary <string, double>();
foreach (FileInfo fi in di.EnumerateFiles())
{
string filePath = fi.FullName;
string fileName = fi.Name;
if (filePath == OrginalFile)
{
continue;
}
bool ispHashSelected = cbCompareAlgorithm.Text == "pHash";
bool isBhattacharyyaSelected = cbCompareAlgorithm.Text == "Bhattacharyya";
if (ispHashSelected)
{
var percentage = ImageHashing.Similarity(OrginalFile, filePath);
percentage = Math.Round(percentage, 3);
imageCompareData.Add(fileName, percentage);
}
else if (isBhattacharyyaSelected)
{
Image img1 = Image.FromFile(OrginalFile);
Image img2 = Image.FromFile(filePath);
var percentage = Bhattacharyya.BhattacharyyaDifference(img1, img2);
percentage = (1 - percentage) * 100;
percentage = Math.Round(percentage, 3);
imageCompareData.Add(fileName, percentage);
}
else
{
orgImage = new MagickImage(OrginalFile);
int imageAlgoIndex = cbCompareAlgorithm.SelectedIndex;
ErrorMetric imageAlgo = (ErrorMetric)imageAlgoIndex;
dupImage = new MagickImage(filePath);
var percentage = orgImage.Compare(dupImage, imageAlgo);
percentage = Math.Round(percentage, 3);
imageCompareData.Add(fileName, percentage);
}
}
var bl = new DictionaryBindingList <string, double>(imageCompareData);
dataGridView1.DataSource = bl;
if (orgImage != null)
{
orgImage.Dispose();
}
if (dupImage != null)
{
dupImage.Dispose();
}
}
