private List <byte[]> get_palette(List <byte[]> samples1)
{
//def get_palette(samples, options, return_mask= False, kmeans_iter= 40):
//'''Extract the palette for the set of sampled RGB values. The first
//palette entry is always the background color; the rest are determined
//from foreground pixels by running K - means clustering.Returns the
//palette, as well as a mask corresponding to the foreground pixels.
var bg_color = get_bg_color(samples1, 6);
var fg_mask = get_fg_mask(bg_color, samples1);
//var kmeans_iter = 40; // Can't specify this at run time. 44 iterations are run versus 40 in python.
var kmeans = new Accord.MachineLearning.KMeans(num_colors - 1);
//Convert List of Byte[] to double[][] for Accord KMeans
var doubleSamples = new double[samples1.Count][];
for (int i = 0; i < samples1.Count; i++)
{
doubleSamples[i] = new double[] { samples1[i][0], samples1[i][1], samples1[i][2] }
}
;
// Filter samples to only true items
var countOfTrue = fg_mask.Where(x => x == true).Count();
var filteredSamples = new double[countOfTrue][];
var c = 0;
for (int i = 0; i < fg_mask.Count; i++)
{
if (fg_mask[i])
{
filteredSamples[c] = new double[] { doubleSamples[i][0], doubleSamples[i][1], doubleSamples[i][2] };
c++;
}
}
// Accord KMeans returns different values than scipy kmeans.
var clusters = kmeans.Learn(filteredSamples);
var palette1 = clusters.Centroids.ToList();
palette1.Insert(0, new double[] { bg_color.R, bg_color.G, bg_color.B });
var bytePal = new List <byte[]>();
for (int i = 0; i < palette1.Count; i++)
{
bytePal.Add(new byte[] { (byte)palette1[i][0], (byte)palette1[i][1], (byte)palette1[i][2] });
}
return(bytePal);
}
/// <summary>
/// Get the palette of an image
/// </summary>
/// <param name="image"></param>
public static List <Color> GetPalette(Image image, int paletteSize)
{
PaletteManager.PaletteSize = paletteSize;
// Get data for kmeans clustering
KMeansData data = GetKMeansData(image.Pixels.Select(p => p.Color).ToList());
// Format color data for KMeans (using Lab color space)
double[][] formattedData = FormatData(data.means);
double[][] centroids = FormatData(data.centroids);
// Perform KMeans w/additional black datapoint
Accord.MachineLearning.KMeans kMeans = new Accord.MachineLearning.KMeans(PaletteSize + 1);
kMeans.Centroids = centroids;
var clusters = kMeans.Learn(formattedData);
int[] labels = clusters.Decide(formattedData);
// Get palette values
double[][] doublePalette = kMeans.Centroids;
List <Color> Palette = new List <Color>();
foreach (double[] lab in doublePalette)
{
Palette.Add(new Color(L: lab[0], a: lab[1], b: lab[2]));
}
// Sort palette by luminance
Palette = Palette.OrderBy(p => p.L).ToList();
// Take all actual palette members
Palette = Palette.TakeLast(PaletteSize).ToList();
return(Palette);
}
private void openToolStripMenuItem_Click(object sender, EventArgs e)
{
string outputFileName = "";
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "Wave File (*.wav) | *.wav|MP3 Files (*.mp3) | *.mp3|All Files (*.*) | *.*";
openFileDialog.FilterIndex = 1;
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
outputFileName = openFileDialog.FileName;
}
else
{
return;
}
if (openFileDialog.FileName.Contains(".mp3"))
{
outputFileName = outputFileName.Substring(0, outputFileName.Length - 3) + "wav";
Mp3ToWav(openFileDialog.FileName, outputFileName);
}
//OpenFileDialog open = new OpenFileDialog();
//open.Filter = "Wave File (*.wav) | *.wav";
//if (open.ShowDialog() != DialogResult.OK) return;
waveViewer1.WaveStream = new NAudio.Wave.WaveFileReader(outputFileName);
waveViewer1.GetTotal = true;
waveViewer1.Refresh();
var datalow = waveViewer1.Datax;
var datahigh = waveViewer1.Datay;
//take the data and look for patterns in the frame of 8 secs
var peaks = detectpeak(200, datahigh, true);
var trough = detectpeak(200, datahigh, false);
peaks = filterpeak(20, peaks);
trough = filterpeak(20, trough);
waveViewer1.peaks = peaks;
waveViewer1.trough = trough;
double[][] highamp = new double[peaks.Count][];
for (int a = 0; a < peaks.Count - 1; a++)
{
highamp[a] = new double[2];
highamp[a][0] = peaks[a + 1] - peaks[a];
highamp[a][1] = datahigh[peaks[a]];
}
highamp[peaks.Count - 1] = new double[2];
highamp[peaks.Count - 1][0] = 0; highamp[peaks.Count - 1][1] = 0;
double[][] lowamp = new double[trough.Count][];
for (int a = 0; a < trough.Count - 1; a++)
{
lowamp[a] = new double[2];
lowamp[a][0] = trough[a + 1] - trough[a];
lowamp[a][1] = datahigh[trough[a]];
}
lowamp[trough.Count - 1] = new double[2];
lowamp[trough.Count - 1][0] = 0; lowamp[trough.Count - 1][1] = 0;
//cluster both
Accord.MachineLearning.KMeans gm = new Accord.MachineLearning.KMeans(5);
Accord.MachineLearning.KMeans gml = new Accord.MachineLearning.KMeans(5);
var ans = gm.Compute(highamp);
var lans = gml.Compute(lowamp);
var fclus = filtercluster(ans, peaks);
cluspos = MixerControls.ToDict(fclus);
var flans = filtercluster(lans, trough);//ignore bot
waveViewer1.peakclus = ans;
waveViewer1.troughclus = lans;
IWavePlayer play;
play = new NAudio.Wave.WaveOut();
audio = new AudioFileReader(outputFileName);
play.Init(audio);
play.Play();
Application.Idle += Application_Idle;
timer1.Interval = 20;
timer1.Enabled = true;
timer1.Start();
Rectangle workingArea = Screen.GetWorkingArea(this);
this.Location = new Point(workingArea.Right - Size.Width - 20,
workingArea.Bottom - Size.Height - 20);
//this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.None;
this.TopMost = true;
this.Opacity = .8;
openToolStripMenuItem.Visible = false;
menuStrip1.Visible = false;
this.pictureBox1.Image = Image.FromFile("D:\\AllVSProject232015\\AudioMix\\AudioMix\\Hypnoctivity-Logo.png");
}
private void openToolStripMenuItem_Click(object sender, EventArgs e)
{
string outputFileName = "";
OpenFileDialog openFileDialog = new OpenFileDialog();
openFileDialog.Filter = "Wave File (*.wav) | *.wav|MP3 Files (*.mp3) | *.mp3|All Files (*.*) | *.*";
openFileDialog.FilterIndex = 1;
if (openFileDialog.ShowDialog() == DialogResult.OK)
{
outputFileName = openFileDialog.FileName;
}
else
return;
if (openFileDialog.FileName.Contains(".mp3"))
{
outputFileName = outputFileName.Substring(0, outputFileName.Length - 3) + "wav";
Mp3ToWav(openFileDialog.FileName, outputFileName);
}
//OpenFileDialog open = new OpenFileDialog();
//open.Filter = "Wave File (*.wav) | *.wav";
//if (open.ShowDialog() != DialogResult.OK) return;
waveViewer1.WaveStream = new NAudio.Wave.WaveFileReader(outputFileName);
waveViewer1.GetTotal = true;
waveViewer1.Refresh();
var datalow = waveViewer1.Datax;
var datahigh = waveViewer1.Datay;
//take the data and look for patterns in the frame of 8 secs
var peaks = detectpeak(200, datahigh, true);
var trough = detectpeak(200, datahigh, false);
peaks = filterpeak(20, peaks);
trough = filterpeak(20, trough);
waveViewer1.peaks = peaks;
waveViewer1.trough = trough;
double[][] highamp = new double[peaks.Count][];
for(int a = 0; a < peaks.Count-1; a++)
{
highamp[a] = new double[2];
highamp[a][0] = peaks[a+1] - peaks[a];
highamp[a][1] = datahigh[peaks[a]];
}
highamp[peaks.Count - 1] = new double[2];
highamp[peaks.Count - 1][0] = 0; highamp[peaks.Count - 1][1] = 0;
double[][] lowamp = new double[trough.Count][];
for (int a = 0; a < trough.Count-1; a++)
{
lowamp[a] = new double[2];
lowamp[a][0] = trough[a+1] - trough[a];
lowamp[a][1] = datahigh[trough[a]];
}
lowamp[trough.Count - 1] = new double[2];
lowamp[trough.Count - 1][0] = 0; lowamp[trough.Count - 1][1] = 0;
//cluster both
Accord.MachineLearning.KMeans gm = new Accord.MachineLearning.KMeans(5);
Accord.MachineLearning.KMeans gml = new Accord.MachineLearning.KMeans(5);
var ans = gm.Compute(highamp);
var lans = gml.Compute(lowamp);
var fclus = filtercluster(ans, peaks);
cluspos = MixerControls.ToDict(fclus);
var flans = filtercluster(lans, trough);//ignore bot
waveViewer1.peakclus = ans;
waveViewer1.troughclus = lans;
IWavePlayer play;
play = new NAudio.Wave.WaveOut();
audio = new AudioFileReader(outputFileName);
play.Init(audio);
play.Play();
Application.Idle += Application_Idle;
timer1.Interval = 20;
timer1.Enabled = true;
timer1.Start();
Rectangle workingArea = Screen.GetWorkingArea(this);
this.Location = new Point(workingArea.Right - Size.Width-20,
workingArea.Bottom - Size.Height - 20);
//this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.None;
this.TopMost = true;
this.Opacity = .8;
openToolStripMenuItem.Visible = false;
menuStrip1.Visible = false;
this.pictureBox1.Image = Image.FromFile("D:\\AllVSProject232015\\AudioMix\\AudioMix\\Hypnoctivity-Logo.png");
}
