private static Image DrawSonogram(BaseSonogram sonogram, double[,] hits, List <Plot> scores, List <Track> tracks)
{
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage());
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
foreach (Plot plot in scores)
{
// assumes data normalized in 0,1
image.AddTrack(ImageTrack.GetNamedScoreTrack(plot.data, 0.0, 1.0, plot.threshold, plot.title));
}
}
if (tracks != null)
{
image.AddTracks(tracks, sonogram.FramesPerSecond, sonogram.FBinWidth);
}
if (hits != null)
{
image.OverlayRedMatrix(hits, 1.0);
}
return(image.GetImage());
}
static Image DrawSonogram(BaseSonogram sonogram, double[,] hits, double[] scores, List <AcousticEvent> predictedEvents, double eventThreshold)
{
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage());
//System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
//img.Save(@"C:\SensorNetworks\temp\testimage1.png", System.Drawing.Imaging.ImageFormat.Png);
//Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
image.AddTrack(ImageTrack.GetScoreTrack(scores, 0.0, 0.5, eventThreshold));
}
//if (hits != null) image.OverlayRedTransparency(hits);
if (hits != null)
{
image.OverlayRainbowTransparency(hits);
}
if (predictedEvents.Count > 0)
{
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
return(image.GetImage());
} //DrawSonogram()
public static Image DrawSonogram(BaseSonogram sonogram, IEnumerable <EventCommon> events)
{
var image = new Image_MultiTrack(sonogram.GetImage(false, true, doMelScale: false));
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
////image.AddTrack(ImageTrack.GetWavEnvelopeTrack(sonogram, image.sonogramImage.Width));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
//############################################################################################ TODO TODO
//convert blob events to acoustic events for drawing purposes
var aeEvents = new List <AcousticEvent>();
foreach (var be in events)
{
aeEvents.Add(EventConverters.ConvertSpectralEventToAcousticEvent((SpectralEvent)be));
}
image.AddEvents(
aeEvents,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
return(image.GetImage());
}
public static Image DisplayDebugImage(BaseSonogram sonogram, List <AcousticEvent> events, List <Plot> scores, double[,] hits)
{
bool doHighlightSubband = false;
bool add1kHzLines = true;
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines, doMelScale: false));
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
if (scores != null)
{
foreach (Plot plot in scores)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(plot.data, 0.0, 1.0, plot.threshold, plot.title)); //assumes data normalised in 0,1
}
}
if (hits != null)
{
image.OverlayRainbowTransparency(hits);
}
if (events.Count > 0)
{
foreach (AcousticEvent ev in events) // set colour for the events
{
ev.BorderColour = AcousticEvent.DefaultBorderColor;
ev.ScoreColour = AcousticEvent.DefaultScoreColor;
}
image.AddEvents(events, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
return(image.GetImage());
}
}//end DetectGratingEvents()
static Image DrawSonogram(BaseSonogram sonogram, double[,] hits, double[] scores, List <AcousticEvent> predictedEvents, double eventThreshold)
{
//Log.WriteLine("# Start to draw image of sonogram.");
bool doHighlightSubband = false; bool add1kHzLines = true;
double maxScore = 32.0; //assume max period = 64.
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines));
//System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
//img.Save(@"C:\SensorNetworks\temp\testimage1.png", System.Drawing.Imaging.ImageFormat.Png);
//Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
image.AddTrack(ImageTrack.GetScoreTrack(scores, 0.0, 1.0, eventThreshold));
}
if (hits != null)
{
image.OverlayRedMatrix(hits, maxScore);
}
if (predictedEvents.Count > 0)
{
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
return(image.GetImage());
} //DrawSonogram()
} // CreateScorePlots()
static Image DrawSonogram(BaseSonogram sonogram, double[,] hits, List <Plot> plots, List <AcousticEvent> predictedEvents)
{
bool doHighlightSubband = false; bool add1kHzLines = false;
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines));
//System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
//img.Save(@"C:\SensorNetworks\temp\testimage1.png", System.Drawing.Imaging.ImageFormat.Png);
//Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (plots != null)
{
foreach (Plot plot in plots)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(plot.data, 0.0, 1.0, plot.threshold, plot.title));
}
}
//if (hits != null) image.OverlayRedTransparency(hits);
if (hits != null)
{
image.OverlayRedMatrix(hits, 1.0);
}
if (predictedEvents.Count > 0)
{
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
return(image.GetImage());
} //DrawSonogram()
/// <summary>
/// draw the spectrogram with red marks indicating the local spectral peaks.
/// </summary>
public static Image DrawSonogram(BaseSonogram sonogram, double[,] hits)
{
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage());
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (hits != null)
{
image.OverlayRedMatrix(hits, 1.0);
}
return(image.GetImage());
}
public void WriteDebugImage(string recordingFileName, DirectoryInfo outputDirectory, BaseSonogram sonogram, List <AcousticEvent> events, List <Plot> scores, double[,] hits)
{
//DEBUG IMAGE this recognizer only. MUST set false for deployment.
bool displayDebugImage = MainEntry.InDEBUG;
if (displayDebugImage)
{
bool doHighlightSubband = false;
bool add1kHzLines = true;
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines, doMelScale: false));
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
if (scores != null)
{
foreach (Plot plot in scores)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(plot.data, 0.0, 1.0, plot.threshold, plot.title));
}
//assumes data normalised in 0,1
}
if (hits != null)
{
image.OverlayRainbowTransparency(hits);
}
if (events.Count > 0)
{
foreach (AcousticEvent ev in events) // set colour for the events
{
ev.BorderColour = AcousticEvent.DefaultBorderColor;
ev.ScoreColour = AcousticEvent.DefaultScoreColor;
}
image.AddEvents(
events,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
}
var debugImage = image.GetImage();
var debugPath = outputDirectory.Combine(FilenameHelpers.AnalysisResultName(Path.GetFileNameWithoutExtension(recordingFileName), this.Identifier, "png", "DebugSpectrogram"));
debugImage.Save(debugPath.FullName);
}
}
public static Image DrawSonogram(BaseSonogram sonogram, IEnumerable <AcousticEvent> events)
{
var image = new Image_MultiTrack(sonogram.GetImage(false, true, doMelScale: false));
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
////image.AddTrack(ImageTrack.GetWavEnvelopeTrack(sonogram, image.sonogramImage.Width));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
image.AddEvents(
events,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
return(image.GetImage());
}
protected virtual Image DrawSonogram(
BaseSonogram sonogram,
double[,] hits,
List <Plot> scores,
List <AcousticEvent> predictedEvents,
double eventThreshold)
{
const bool doHighlightSubband = false;
const bool add1KHzLines = true;
var image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1KHzLines, doMelScale: false));
////System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
////img.Save(@"C:\SensorNetworks\temp\testimage1.png", System.Drawing.Imaging.ImageFormat.Png);
////Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
foreach (var plot in scores)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(plot.data, 0.0, 1.0, plot.threshold, plot.title));
}
}
if (hits != null)
{
image.OverlayRedTransparency(hits);
}
if (predictedEvents != null && predictedEvents.Count > 0)
{
image.AddEvents(
predictedEvents,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
}
var result = image.GetImage();
return(result);
}
/// <summary>
/// draw the spectrogram with spectral tracks.
/// </summary>
public static Image DrawTracks(BaseSonogram sonogram, double[,] hits, List <SpectralTrack> tracks)
{
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage());
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (tracks != null)
{
image.AddTracks(tracks, sonogram.FramesPerSecond, sonogram.FBinWidth);
}
if (hits != null)
{
image.OverlayRedMatrix(hits, 1.0);
}
return(image.GetImage());
}
/// <summary>
/// Overlays the spectral cluster IDs on a spectrogram from which the clusters derived.
/// </summary>
public static Image DrawClusterSpectrogram(BaseSonogram sonogram, ClusterInfo clusterInfo, TrainingDataInfo data, int lowerBinBound)
{
using (var img = sonogram.GetImage(doHighlightSubband: false, add1KHzLines: true, doMelScale: false))
using (var image = new Image_MultiTrack(img))
{
//image.AddTrack(ImageTrack.GetScoreTrack(DataTools.Bool2Binary(clusterInfo.selectedFrames),0.0, 1.0, 0.0));
//add time scale
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
// add cluster track, show ID of cluster of each frame
string label = string.Format(clusterInfo.ClusterCount + " Clusters");
var scores = new Plot(label, DataTools.normalise(clusterInfo.ClusterHits2), 0.0); // location of cluster hits
image.AddTrack(ImageTrack.GetNamedScoreTrack(scores.data, 0.0, 1.0, scores.threshold, scores.title));
// overlay cluster hits on spectrogram
int[,] hits = AssembleClusterSpectrogram(sonogram.Data, lowerBinBound, clusterInfo, data);
image.OverlayDiscreteColorMatrix(hits);
return(image.GetImage());
}// using
}
} // Analysis()
private static Image DrawSonogram(
BaseSonogram sonogram,
double[,] hits,
Plot scores,
List <AcousticEvent> predictedEvents,
double eventThreshold)
{
const bool DoHighlightSubband = false;
const bool Add1KHzLines = true;
var image = new Image_MultiTrack(sonogram.GetImage(DoHighlightSubband, Add1KHzLines));
////System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
////img.Save(@"C:\SensorNetworks\temp\testimage1.png", System.Drawing.Imaging.ImageFormat.Png);
////Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(scores.data, 0.0, 1.0, scores.threshold, scores.title));
}
if (hits != null)
{
image.OverlayRedTransparency(hits);
}
if ((predictedEvents != null) && (predictedEvents.Count > 0))
{
image.AddEvents(
predictedEvents,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
}
return(image.GetImage());
}
private static Image DrawSonogram(
BaseSonogram sonogram,
double[,] hits,
Plot scores,
List <AcousticEvent> predictedEvents,
double eventThreshold)
{
var image = new Image_MultiTrack(sonogram.GetImage());
////System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines);
////Image_MultiTrack image = new Image_MultiTrack(img);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(scores.data, 0.0, 1.0, scores.threshold, scores.title));
}
////if (hits != null) image.OverlayRedTransparency(hits);
if (hits != null)
{
image.OverlayRainbowTransparency(hits);
}
if (predictedEvents != null && predictedEvents.Count > 0)
{
image.AddEvents(
predictedEvents,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FramesPerSecond);
}
return(image.GetImage());
}
public static Image DrawSonogram(BaseSonogram sonogram, Plot scores, List <AcousticEvent> poi, double eventThreshold, double[,] overlay)
{
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband: false, add1KHzLines: false, doMelScale: false));
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
if (scores != null)
{
image.AddTrack(ImageTrack.GetNamedScoreTrack(scores.data, 0.0, 1.0, scores.threshold, scores.title));
}
if (poi != null && poi.Count > 0)
{
image.AddEvents(poi, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
if (overlay != null)
{
var m = MatrixTools.ThresholdMatrix2Binary(overlay, 0.5);
image.OverlayDiscreteColorMatrix(m);
}
return(image.GetImage());
}
static Image DrawSonogram(BaseSonogram sonogram, double[,] hits, List <double[]> scores, List <AcousticEvent> predictedEvents, double eventThreshold)
{
bool doHighlightSubband = false; bool add1kHzLines = true;
int maxFreq = sonogram.NyquistFrequency / 2;
Image_MultiTrack image = new Image_MultiTrack(sonogram.GetImage(maxFreq, 1, doHighlightSubband, add1kHzLines));
image.AddTrack(Image_Track.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
if (scores != null)
{
foreach (double[] array in scores)
{
image.AddTrack(Image_Track.GetScoreTrack(array, 0.0, 1.0, eventThreshold));
}
}
if (hits != null)
{
image.OverlayRainbowTransparency(hits);
}
if (predictedEvents.Count > 0)
{
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
}
return(image.GetImage());
} //DrawSonogram()
public static void Main(Arguments arguments)
{
//1. set up the necessary files
//DirectoryInfo diSource = arguments.Source.Directory;
FileInfo fiSourceRecording = arguments.Source;
FileInfo fiConfig = arguments.Config.ToFileInfo();
FileInfo fiImage = arguments.Output.ToFileInfo();
fiImage.CreateParentDirectories();
string title = "# CREATE FOUR (4) SONOGRAMS FROM AUDIO RECORDING";
string date = "# DATE AND TIME: " + DateTime.Now;
LoggedConsole.WriteLine(title);
LoggedConsole.WriteLine(date);
LoggedConsole.WriteLine("# Input audio file: " + fiSourceRecording.Name);
LoggedConsole.WriteLine("# Output image file: " + fiImage);
//2. get the config dictionary
Config configuration = ConfigFile.Deserialize(fiConfig);
//below three lines are examples of retrieving info from Config config
//string analysisIdentifier = configuration[AnalysisKeys.AnalysisName];
//bool saveIntermediateWavFiles = (bool?)configuration[AnalysisKeys.SaveIntermediateWavFiles] ?? false;
//scoreThreshold = (double?)configuration[AnalysisKeys.EventThreshold] ?? scoreThreshold;
//3 transfer conogram parameters to a dictionary to be passed around
var configDict = new Dictionary <string, string>();
// #Resample rate must be 2 X the desired Nyquist. Default is that of recording.
configDict["ResampleRate"] = (configuration.GetIntOrNull(AnalysisKeys.ResampleRate) ?? 17640).ToString();
configDict["FrameLength"] = configuration[AnalysisKeys.FrameLength] ?? "512";
int frameSize = configuration.GetIntOrNull(AnalysisKeys.FrameLength) ?? 512;
// #Frame Overlap as fraction: default=0.0
configDict["FrameOverlap"] = configuration[AnalysisKeys.FrameOverlap] ?? "0.0";
double windowOverlap = configuration.GetDoubleOrNull(AnalysisKeys.FrameOverlap) ?? 0.0;
// #MinHz: 500
// #MaxHz: 3500
// #NOISE REDUCTION PARAMETERS
configDict["DoNoiseReduction"] = configuration["DoNoiseReduction"] ?? "true";
configDict["BgNoiseThreshold"] = configuration["BgNoiseThreshold"] ?? "3.0";
configDict["ADD_AXES"] = configuration["ADD_AXES"] ?? "true";
configDict["AddSegmentationTrack"] = configuration["AddSegmentationTrack"] ?? "true";
// 3: GET RECORDING
var startOffsetMins = TimeSpan.Zero;
var endOffsetMins = TimeSpan.Zero;
FileInfo fiOutputSegment = fiSourceRecording;
if (!(startOffsetMins == TimeSpan.Zero && endOffsetMins == TimeSpan.Zero))
{
var buffer = new TimeSpan(0, 0, 0);
fiOutputSegment = new FileInfo(Path.Combine(fiImage.DirectoryName, "tempWavFile.wav"));
//This method extracts segment and saves to disk at the location fiOutputSegment.
var resampleRate = configuration.GetIntOrNull(AnalysisKeys.ResampleRate) ?? AppConfigHelper.DefaultTargetSampleRate;
AudioRecording.ExtractSegment(fiSourceRecording, startOffsetMins, endOffsetMins, buffer, resampleRate, fiOutputSegment);
}
var recording = new AudioRecording(fiOutputSegment.FullName);
// EXTRACT ENVELOPE and SPECTROGRAM
var dspOutput = DSP_Frames.ExtractEnvelopeAndFfts(recording, frameSize, windowOverlap);
// average absolute value over the minute recording
////double[] avAbsolute = dspOutput.Average;
// (A) ################################## EXTRACT INDICES FROM THE SIGNAL WAVEFORM ##################################
// var wavDuration = TimeSpan.FromSeconds(recording.WavReader.Time.TotalSeconds);
// double totalSeconds = wavDuration.TotalSeconds;
// double[] signalEnvelope = dspOutput.Envelope;
// double avSignalEnvelope = signalEnvelope.Average();
// double[] frameEnergy = dspOutput.FrameEnergy;
// double highAmplIndex = dspOutput.HighAmplitudeCount / totalSeconds;
// double binWidth = dspOutput.BinWidth;
// int nyquistBin = dspOutput.NyquistBin;
// dspOutput.WindowPower,
// dspOutput.FreqBinWidth
int nyquistFreq = dspOutput.NyquistFreq;
double epsilon = recording.Epsilon;
// i: prepare amplitude spectrogram
double[,] amplitudeSpectrogramData = dspOutput.AmplitudeSpectrogram; // get amplitude spectrogram.
var image1 = ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(amplitudeSpectrogramData));
// ii: prepare decibel spectrogram prior to noise removal
double[,] decibelSpectrogramdata = MFCCStuff.DecibelSpectra(dspOutput.AmplitudeSpectrogram, dspOutput.WindowPower, recording.SampleRate, epsilon);
decibelSpectrogramdata = MatrixTools.NormaliseMatrixValues(decibelSpectrogramdata);
var image2 = ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(decibelSpectrogramdata));
// iii: Calculate background noise spectrum in decibels
// Calculate noise value for each freq bin.
double sdCount = 0.0; // number of SDs above the mean for noise removal
var decibelProfile = NoiseProfile.CalculateModalNoiseProfile(decibelSpectrogramdata, sdCount);
// DataTools.writeBarGraph(dBProfile.NoiseMode);
// iv: Prepare noise reduced spectrogram
decibelSpectrogramdata = SNR.TruncateBgNoiseFromSpectrogram(decibelSpectrogramdata, decibelProfile.NoiseThresholds);
//double dBThreshold = 1.0; // SPECTRAL dB THRESHOLD for smoothing background
//decibelSpectrogramdata = SNR.RemoveNeighbourhoodBackgroundNoise(decibelSpectrogramdata, dBThreshold);
var image3 = ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(decibelSpectrogramdata));
// prepare new sonogram config and draw second image going down different code pathway
var config = new SonogramConfig
{
MinFreqBand = 0,
MaxFreqBand = 10000,
NoiseReductionType = SNR.KeyToNoiseReductionType("Standard"),
NoiseReductionParameter = 1.0,
WindowSize = frameSize,
WindowOverlap = windowOverlap,
};
//var mfccConfig = new MfccConfiguration(config);
int bandCount = config.mfccConfig.FilterbankCount;
bool doMelScale = config.mfccConfig.DoMelScale;
int ccCount = config.mfccConfig.CcCount;
int fftBins = config.FreqBinCount; //number of Hz bands = 2^N +1 because includes the DC band
int minHz = config.MinFreqBand ?? 0;
int maxHz = config.MaxFreqBand ?? nyquistFreq;
var standardSonogram = new SpectrogramStandard(config, recording.WavReader);
var image4 = standardSonogram.GetImage();
// TODO next line crashes - does not produce cepstral sonogram.
//SpectrogramCepstral cepSng = new SpectrogramCepstral(config, recording.WavReader);
//Image image5 = cepSng.GetImage();
//var mti = SpectrogramTools.Sonogram2MultiTrackImage(sonogram, configDict);
//var image = mti.GetImage();
//Image image = SpectrogramTools.Matrix2SonogramImage(deciBelSpectrogram, config);
//Image image = SpectrogramTools.Audio2SonogramImage(FileInfo fiAudio, Dictionary<string, string> configDict);
//prepare sonogram images
var protoImage6 = new Image_MultiTrack(standardSonogram.GetImage(doHighlightSubband: false, add1KHzLines: true, doMelScale: false));
protoImage6.AddTrack(ImageTrack.GetTimeTrack(standardSonogram.Duration, standardSonogram.FramesPerSecond));
protoImage6.AddTrack(ImageTrack.GetWavEnvelopeTrack(recording, protoImage6.SonogramImage.Width));
protoImage6.AddTrack(ImageTrack.GetSegmentationTrack(standardSonogram));
var image6 = protoImage6.GetImage();
var list = new List <Image <Rgb24> >();
list.Add(image1); // amplitude spectrogram
list.Add(image2); // decibel spectrogram before noise removal
list.Add(image3); // decibel spectrogram after noise removal
list.Add(image4); // second version of noise reduced spectrogram
//list.Add(image5); // ceptral sonogram
list.Add(image6.CloneAs <Rgb24>()); // multitrack image
Image finalImage = ImageTools.CombineImagesVertically(list);
finalImage.Save(fiImage.FullName);
////2: NOISE REMOVAL
//double[,] originalSg = sonogram.Data;
//double[,] mnr = sonogram.Data;
//mnr = ImageTools.WienerFilter(mnr, 3);
//double backgroundThreshold = 4.0; //SETS MIN DECIBEL BOUND
//var output = SNR.NoiseReduce(mnr, NoiseReductionType.STANDARD, backgroundThreshold);
//double ConfigRange = 70; //sets the the max dB
//mnr = SNR.SetConfigRange(output.Item1, 0.0, ConfigRange);
////3: Spectral tracks sonogram
//byte[,] binary = MatrixTools.IdentifySpectralRidges(mnr);
//binary = MatrixTools.ThresholdBinarySpectrum(binary, mnr, 10);
//binary = MatrixTools.RemoveOrphanOnesInBinaryMatrix(binary);
////binary = MatrixTools.PickOutLines(binary); //syntactic approach
//sonogram.SetBinarySpectrum(binary);
////sonogram.Data = SNR.SpectralRidges2Intensity(binary, originalSg);
//image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, false));
//image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
//image.AddTrack(ImageTrack.GetWavEnvelopeTrack(recording, image.sonogramImage.Width));
//image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
//fn = outputFolder + wavFileName + "_tracks.png";
//image.Save(fn);
//LoggedConsole.WriteLine("Spectral tracks sonogram to file: " + fn);
//3: prepare image of spectral peaks sonogram
//sonogram.Data = SNR.NoiseReduce_Peaks(originalSg, dynamicRange);
//image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines));
//image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration));
//image.AddTrack(ImageTrack.GetWavEnvelopeTrack(recording, image.Image.Width));
//image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
//fn = outputFolder + wavFileName + "_peaks.png";
//image.Save(fn);
//LoggedConsole.WriteLine("Spectral peaks sonogram to file: " + fn);
//4: Sobel approach
//sonogram.Data = SNR.NoiseReduce_Sobel(originalSg, dynamicRange);
//image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines));
//image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration));
//image.AddTrack(ImageTrack.GetWavEnvelopeTrack(recording, image.Image.Width));
//image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
//fn = outputFolder + wavFileName + "_sobel.png";
//image.Save(fn);
//LoggedConsole.WriteLine("Sobel sonogram to file: " + fn);
// I1.txt contains the sonogram matrix produced by matlab
//string matlabFile = @"C:\SensorNetworks\Software\AudioAnalysis\AED\Test\matlab\GParrots_JB2_20090607-173000.wav_minute_3\I1.txt";
//double[,] matlabMatrix = Util.fileToMatrix(matlabFile, 256, 5166);
//LoggedConsole.WriteLine(matrix[0, 2] + " vs " + matlabMatrix[254, 0]);
//LoggedConsole.WriteLine(matrix[0, 3] + " vs " + matlabMatrix[253, 0]);
// TODO put this back once sonogram issues resolved
/*
* LoggedConsole.WriteLine("START: AED");
* IEnumerable<Oblong> oblongs = AcousticEventDetection.detectEvents(3.0, 100, matrix);
* LoggedConsole.WriteLine("END: AED");
*
*
* //set up static variables for init Acoustic events
* //AcousticEvent. doMelScale = config.DoMelScale;
* AcousticEvent.FreqBinCount = config.FreqBinCount;
* AcousticEvent.FreqBinWidth = config.FftConfig.NyquistFreq / (double)config.FreqBinCount;
* // int minF = (int)config.MinFreqBand;
* // int maxF = (int)config.MaxFreqBand;
* AcousticEvent.FrameDuration = config.GetFrameOffset();
*
*
* var events = new List<EventPatternRecog.Rectangle>();
* foreach (Oblong o in oblongs)
* {
* var e = new AcousticEvent(o);
* events.Add(new EventPatternRecog.Rectangle(e.StartTime, (double) e.MaxFreq, e.StartTime + e.Duration, (double)e.MinFreq));
* //LoggedConsole.WriteLine(e.StartTime + "," + e.Duration + "," + e.MinFreq + "," + e.MaxFreq);
* }
*
* LoggedConsole.WriteLine("# AED events: " + events.Count);
*
* LoggedConsole.WriteLine("START: EPR");
* IEnumerable<EventPatternRecog.Rectangle> eprRects = EventPatternRecog.detectGroundParrots(events);
* LoggedConsole.WriteLine("END: EPR");
*
* var eprEvents = new List<AcousticEvent>();
* foreach (EventPatternRecog.Rectangle r in eprRects)
* {
* var ae = new AcousticEvent(r.Left, r.Right - r.Left, r.Bottom, r.Top, false);
* LoggedConsole.WriteLine(ae.WriteProperties());
* eprEvents.Add(ae);
* }
*
* string imagePath = Path.Combine(outputFolder, "RESULTS_" + Path.GetFileNameWithoutExtension(recording.BaseName) + ".png");
*
* bool doHighlightSubband = false; bool add1kHzLines = true;
* var image = new Image_MultiTrack(sonogram.GetImage(doHighlightSubband, add1kHzLines));
* //image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration));
* //image.AddTrack(ImageTrack.GetWavEnvelopeTrack(recording, image.Image.Width));
* //image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
* image.AddEvents(eprEvents);
* image.Save(outputFolder + wavFileName + ".png");
*/
LoggedConsole.WriteLine("\nFINISHED!");
}