public static Image GetFreqVsOscillationsImage(double[,] freqOscilMatrix, double framesPerSecond, double freqBinWidth, int sampleLength, string algorithmName)
{
// remove the high cycles/sec end of the matrix because nothing really happens here.
freqOscilMatrix = MatrixTools.Submatrix(freqOscilMatrix, 0, 0, 30, freqOscilMatrix.GetLength(1) - 1);
// get the OSC spectral index
// double[] spectralIndex = ConvertMatrix2SpectralIndexBySummingFreqColumns(freqOscilMatrix, skipNrows: 0);
var spectralIndex = MatrixTools.GetMaximumColumnValues(freqOscilMatrix);
// Convert spectrum index to oscillations per second
double oscillationBinWidth = framesPerSecond / sampleLength;
//draw an image
freqOscilMatrix = MatrixTools.MatrixRotate90Anticlockwise(freqOscilMatrix);
int xscale = 5;
int yscale = 5;
var image1 = ImageTools.DrawMatrixInColour(freqOscilMatrix, xPixelsPerCell: xscale, yPixelsPerCell: yscale);
var image2 = ImageTools.DrawVectorInColour(DataTools.reverseArray(spectralIndex), cellWidth: xscale);
var image = ImageTools.CombineImagesInLine(new[] { image1, image2 });
// a tic every 5cpsec.
double cycleInterval = 5.0;
double xTicInterval = cycleInterval / oscillationBinWidth * xscale;
// a tic every 1000 Hz.
int herzInterval = 1000;
double yTicInterval = herzInterval / freqBinWidth * yscale;
int xOffset = xscale / 2;
int yOffset = yscale / 2;
image = ImageTools.DrawXandYaxes(image, 18, cycleInterval, xTicInterval, xOffset, herzInterval, yTicInterval, yOffset);
var titleBar = DrawTitleBarOfOscillationSpectrogram(algorithmName, image.Width);
var imageList = new List <Image> {
titleBar, image
};
var compositeBmp = (Bitmap)ImageTools.CombineImagesVertically(imageList);
return(compositeBmp);
}
public static Dictionary <string, double[, ]> GetSpectralIndexFilesAndConcatenate(
DirectoryInfo[] dirs,
string analysisType,
string[] keys,
IndexGenerationData indexGenerationData,
bool verbose = false)
{
TimeSpan indexCalcTimeSpan = indexGenerationData.IndexCalculationDuration;
Dictionary <string, double[, ]> spectrogramMatrices = new Dictionary <string, double[, ]>();
foreach (string key in keys)
{
//DateTime now1 = DateTime.Now;
string pattern = "*__" + analysisType + "." + key + ".csv";
var files = GetFilesInDirectories(dirs, pattern);
if (files.Length == 0)
{
LoggedConsole.WriteWarnLine($"{key} WARNING: No csv files found for KEY=" + key);
continue;
}
List <double[, ]> matrices = ConcatenateSpectralIndexFilesWithTimeCheck(files, indexCalcTimeSpan, key);
double[,] m = MatrixTools.ConcatenateMatrixRows(matrices);
//Dictionary<string, double[,]> dict = spectralIndexValues.ToTwoDimensionalArray(SpectralIndexValues.CachedSelectors, TwoDimensionalArray.Rotate90ClockWise);
m = MatrixTools.MatrixRotate90Anticlockwise(m);
spectrogramMatrices.Add(key, m);
//var now2 = DateTime.Now;
//var et = now2 - now1;
//if (verbose)
//{
// LoggedConsole.WriteLine($"\t\tTime to read <{key}> spectral index files = {et.TotalSeconds:f2} seconds");
//}
}
return(spectrogramMatrices);
}
public override AnalysisResult2 Analyze <T>(AnalysisSettings analysisSettings, SegmentSettings <T> segmentSettings)
{
var configuration = (StandardizedFeatureExtractionConfig)analysisSettings.Configuration;
var audioFile = segmentSettings.SegmentAudioFile;
var recording = new AudioRecording(audioFile.FullName);
// Configurations non-specific for bands
TimeSpan indexCalculationDuration = configuration.IndexCalculationDurationTimeSpan;
TimeSpan bgNoiseNeighbourhood = configuration.BgNoiseBuffer;
// Bands
List <StandardizedFeatureExtractionConfig.BandsProperties> bandsList = configuration.Bands;
// Check if there are identical bands
CheckForIdenticalBands(bandsList);
// Estimate total number of subsegments
double segmentDurationSeconds = segmentSettings.AnalysisIdealSegmentDuration.TotalSeconds;
double subsegmentDuration = indexCalculationDuration.TotalSeconds;
int subsegmentCount = (int)Math.Round(segmentDurationSeconds / subsegmentDuration);
int totalSubsegmentCount = subsegmentCount * bandsList.Count;
// Store results of all subsegments
var analysisResults = new AnalysisResult2(analysisSettings, segmentSettings, recording.Duration);
analysisResults.AnalysisIdentifier = this.Identifier;
var trackScores = new List <Plot>(totalSubsegmentCount);
var tracks = new List <SpectralTrack>(totalSubsegmentCount);
analysisResults.SummaryIndices = new SummaryIndexBase[totalSubsegmentCount];
analysisResults.SpectralIndices = new SpectralIndexBase[totalSubsegmentCount];
// Create list to store images, one for each band. They are later combined into one image.
var list = new List <Image <Rgb24> >();
string imagePath = segmentSettings.SegmentImageFile.FullName;
int maxImageWidth = 0;
int bandCount = 0;
foreach (var band in bandsList)
{
Log.DebugFormat("Starting band {0}/{1}", bandCount + 1, bandsList.Count);
// Calculate spectral indices
// get a fresh copy of the ICC config
var config = (IndexCalculateConfig)((ICloneable)configuration).Clone();
// Add values specific for band from custom configuration file to config
config.MinBandWidth = band.Bandwidth.Min;
config.MaxBandWidth = band.Bandwidth.Max;
config.FrameLength = band.FftWindow;
if (band.MelScale != 0)
{
config.FrequencyScale = FreqScaleType.Mel;
config.MelScale = band.MelScale;
}
else
{
config.FrequencyScale = FreqScaleType.Linear;
}
// Calculate indices for each subsegment and for each band
IndexCalculateResult[] subsegmentResults = AcousticIndices.CalculateIndicesInSubsegments(
recording,
segmentSettings.SegmentStartOffset,
segmentSettings.AnalysisIdealSegmentDuration,
indexCalculationDuration,
config.IndexProperties,
segmentSettings.Segment.SourceMetadata.SampleRate,
config);
int columnsAmplitudeSpectrogram = subsegmentResults[0].AmplitudeSpectrogram.GetLength(1);
double[,] amplitudeSpectrogramSegment = new double[0, columnsAmplitudeSpectrogram];
for (int i = 0; i < subsegmentResults.Length; i++)
{
var indexCalculateResult = subsegmentResults[i];
indexCalculateResult.SummaryIndexValues.FileName = segmentSettings.Segment.SourceMetadata.Identifier;
indexCalculateResult.SpectralIndexValues.FileName = segmentSettings.Segment.SourceMetadata.Identifier;
analysisResults.SummaryIndices[bandCount + (i * bandsList.Count)] = indexCalculateResult.SummaryIndexValues;
analysisResults.SpectralIndices[bandCount + (i * bandsList.Count)] = indexCalculateResult.SpectralIndexValues;
trackScores.AddRange(indexCalculateResult.TrackScores);
if (indexCalculateResult.Tracks != null)
{
tracks.AddRange(indexCalculateResult.Tracks);
}
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave())
{
// Add amplitude spectrograms of each subsegment together to get amplitude spectrogram of one segment
double[,] amplitudeSpectrogramSubsegment = indexCalculateResult.AmplitudeSpectrogram;
amplitudeSpectrogramSegment = MatrixTools.ConcatenateMatrixRows(
amplitudeSpectrogramSegment,
amplitudeSpectrogramSubsegment);
}
}
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave())
{
// Create image of amplitude spectrogram
var image = ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(amplitudeSpectrogramSegment));
// Label information
string minBandWidth = band.Bandwidth.Min.ToString();
string maxBandWidth = band.Bandwidth.Max.ToString();
string fftWindow = band.FftWindow.ToString();
string mel;
string melScale;
if (band.MelScale != 0)
{
mel = "Mel";
melScale = band.MelScale.ToString();
}
else
{
mel = "Standard";
melScale = 0.ToString();
}
// Create label
string segmentSeparator = "_";
string[] segments = { minBandWidth, maxBandWidth, fftWindow, mel, melScale };
string labelText = segments.Aggregate(string.Empty, (aggregate, item) => aggregate + segmentSeparator + item);
var stringFont = Drawing.Arial14;
int width = 250;
int height = image.Height;
var label = new Image <Rgb24>(width, height);
label.Mutate(g1 =>
{
g1.Clear(Color.Gray);
g1.DrawText(labelText, stringFont, Color.Black, new PointF(4, 30));
g1.DrawLine(new Pen(Color.Black, 1), 0, 0, width, 0); //draw upper boundary
g1.DrawLine(new Pen(Color.Black, 1), 0, 1, width, 1); //draw upper boundary
});
var labelledImage = ImageTools.CombineImagesInLine(label, image);
// Add labeled image to list
list.Add(labelledImage);
// Update maximal width of image
if (image.Width > maxImageWidth)
{
maxImageWidth = image.Width;
}
}
bandCount += 1;
Log.InfoFormat("Completed band {0}/{1}", bandCount, bandsList.Count);
}
if (analysisSettings.AnalysisDataSaveBehavior)
{
this.WriteSummaryIndicesFile(segmentSettings.SegmentSummaryIndicesFile, analysisResults.SummaryIndices);
analysisResults.SummaryIndicesFile = segmentSettings.SegmentSummaryIndicesFile;
analysisResults.SpectraIndicesFiles =
this.WriteSpectrumIndicesFiles(
segmentSettings.SegmentSpectrumIndicesDirectory,
Path.GetFileNameWithoutExtension(segmentSettings.SegmentAudioFile.Name),
analysisResults.SpectralIndices);
}
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave())
{
var finalImage = ImageTools.CombineImagesVertically(list, maxImageWidth);
finalImage.Save(imagePath);
analysisResults.ImageFile = new FileInfo(imagePath);
LoggedConsole.WriteLine("See {0} for spectrogram pictures", imagePath);
}
return(analysisResults);
}
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!");
}
public static AudioToSonogramResult GenerateSpectrogramImages(FileInfo sourceRecording, Dictionary <string, string> configDict, DirectoryInfo outputDirectory)
{
// the source name was set up in the Analyse() method. But it could also be obtained directly from recording.
string sourceName = configDict[ConfigKeys.Recording.Key_RecordingFileName];
sourceName = Path.GetFileNameWithoutExtension(sourceName);
var result = new AudioToSonogramResult();
// init the image stack
var list = new List <Image>();
// 1) draw amplitude spectrogram
var recordingSegment = new AudioRecording(sourceRecording.FullName);
// default values config except disable noise removal for first two spectrograms
SonogramConfig sonoConfig = new SonogramConfig(configDict)
{
NoiseReductionType = NoiseReductionType.None
};
BaseSonogram sonogram = new AmplitudeSonogram(sonoConfig, recordingSegment.WavReader);
// remove the DC bin
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.FrameCount - 1, sonogram.Configuration.FreqBinCount);
// save spectrogram data at this point - prior to noise reduction
double[,] spectrogramDataBeforeNoiseReduction = sonogram.Data;
const int lowPercentile = 20;
const double neighbourhoodSeconds = 0.25;
int neighbourhoodFrames = (int)(sonogram.FramesPerSecond * neighbourhoodSeconds);
const double lcnContrastLevel = 0.25;
////LoggedConsole.WriteLine("LCN: FramesPerSecond (Prior to LCN) = {0}", sonogram.FramesPerSecond);
////LoggedConsole.WriteLine("LCN: Neighbourhood of {0} seconds = {1} frames", neighbourhoodSeconds, neighbourhoodFrames);
sonogram.Data = NoiseRemoval_Briggs.NoiseReduction_ShortRecordings_SubtractAndLCN(sonogram.Data, lowPercentile, neighbourhoodFrames, lcnContrastLevel);
// draw amplitude spectrogram unannotated
FileInfo outputImage1 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".amplitd.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage1.FullName);
// draw amplitude spectrogram annotated
var image = sonogram.GetImageFullyAnnotated("AMPLITUDE SPECTROGRAM + Bin LCN (Local Contrast Normalisation)");
list.Add(image);
////string path2 = @"C:\SensorNetworks\Output\Sonograms\dataInput2.png";
////Histogram.DrawDistributionsAndSaveImage(sonogram.Data, path2);
// 2) A FALSE-COLOUR VERSION OF AMPLITUDE SPECTROGRAM
double ridgeThreshold = 0.20;
double[,] matrix = ImageTools.WienerFilter(sonogram.Data, 3);
byte[,] hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
hits = RidgeDetection.JoinDisconnectedRidgesInMatrix(hits, matrix, ridgeThreshold);
image = SpectrogramTools.CreateFalseColourAmplitudeSpectrogram(spectrogramDataBeforeNoiseReduction, null, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "AMPLITUDE SPECTROGRAM + LCN + ridge detection");
list.Add(image);
Image envelopeImage = ImageTrack.DrawWaveEnvelopeTrack(recordingSegment, image.Width);
list.Add(envelopeImage);
// 3) now draw the standard decibel spectrogram
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
// remove the DC bin
sonogram.Data = MatrixTools.Submatrix(sonogram.Data, 0, 1, sonogram.FrameCount - 1, sonogram.Configuration.FreqBinCount);
// draw decibel spectrogram unannotated
FileInfo outputImage2 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".deciBel.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage2.FullName);
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM");
list.Add(image);
Image segmentationImage = ImageTrack.DrawSegmentationTrack(
sonogram,
EndpointDetectionConfiguration.K1Threshold,
EndpointDetectionConfiguration.K2Threshold,
image.Width);
list.Add(segmentationImage);
// keep the sonogram data (NOT noise reduced) for later use
double[,] dbSpectrogramData = (double[, ])sonogram.Data.Clone();
// 4) now draw the noise reduced decibel spectrogram
sonoConfig.NoiseReductionType = NoiseReductionType.Standard;
sonoConfig.NoiseReductionParameter = 3;
////sonoConfig.NoiseReductionType = NoiseReductionType.SHORT_RECORDING;
////sonoConfig.NoiseReductionParameter = 50;
sonogram = new SpectrogramStandard(sonoConfig, recordingSegment.WavReader);
// draw decibel spectrogram unannotated
FileInfo outputImage3 = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".noNoise_dB.bmp"));
ImageTools.DrawReversedMatrix(MatrixTools.MatrixRotate90Anticlockwise(sonogram.Data), outputImage3.FullName);
image = sonogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM + Lamel noise subtraction");
list.Add(image);
// keep the sonogram data for later use
double[,] nrSpectrogramData = sonogram.Data;
// 5) A FALSE-COLOUR VERSION OF DECIBEL SPECTROGRAM
ridgeThreshold = 2.5;
matrix = ImageTools.WienerFilter(dbSpectrogramData, 3);
hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
image = SpectrogramTools.CreateFalseColourDecibelSpectrogram(dbSpectrogramData, nrSpectrogramData, hits);
image = sonogram.GetImageAnnotatedWithLinearHerzScale(image, "DECIBEL SPECTROGRAM - Colour annotated");
list.Add(image);
// 6) COMBINE THE SPECTROGRAM IMAGES
Image compositeImage = ImageTools.CombineImagesVertically(list);
FileInfo outputImage = new FileInfo(Path.Combine(outputDirectory.FullName, sourceName + ".5spectro.png"));
compositeImage.Save(outputImage.FullName, ImageFormat.Png);
result.SpectrogramFile = outputImage;
// 7) Generate the FREQUENCY x OSCILLATIONS Graphs and csv data
////bool saveData = true;
////bool saveImage = true;
////double[] oscillationsSpectrum = Oscillations2014.GenerateOscillationDataAndImages(sourceRecording, configDict, saveData, saveImage);
return(result);
}
