public static void DrawSonogram(BaseSonogram sonogram, string path, double[] array1, double[] array2, List <double[]> scores)
{
Log.WriteLine("# Draw image of sonogram.");
bool doHighlightSubband = false; bool add1kHzLines = true;
//sonogram.FramesPerSecond = 1 / sonogram.FrameOffset;
int length = sonogram.FrameCount;
int maxIndex1 = DataTools.GetMaxIndex(array1);
int maxIndex2 = DataTools.GetMaxIndex(array2);
using (System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines))
using (Image_MultiTrack image = new Image_MultiTrack(img))
{
//img.Save(@"C:\SensorNetworks\WavFiles\temp1\testimage1.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetScoreTrack(DataTools.ScaleArray(array1, length), 0.0, array1[maxIndex1], 5));
image.AddTrack(ImageTrack.GetScoreTrack(DataTools.ScaleArray(array2, length), 0.0, array2[maxIndex2], 0.5));
for (int i = 0; i < scores.Count; i++)
{
int maxIndex = DataTools.GetMaxIndex(scores[i]);
double max = scores[i][maxIndex];
if (max <= 0.0)
{
max = 1.0;
}
image.AddTrack(ImageTrack.GetScoreTrack(DataTools.ScaleArray(scores[i], length), 0.0, max, 0.1));
}
image.Save(path);
}// using
}
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()
} // 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()
public static void DrawSonogram(BaseSonogram sonogram, FileInfo path, List <AcousticEvent> predictedEvents, List <double> thresholdList, List <double[]> scoresList)
{
Log.WriteLine("# Start to draw image of sonogram.");
bool doHighlightSubband = false; bool add1kHzLines = true;
// DO NOT NEED FOLLOWING TWO LINES BECAUSE HAVE CHANGED CODE TO ENSURE THAT ALL TEMPLATES USE THE SAME FRAME OVERLAP
// AND THEREFORE ALL SCORE ARRAYS ARE OF THE SAME LENGTH FOR GIVEN RECORDING
//Log.WriteLine("# Convert score arrays to correct length for display = {0}.", sonogram.FrameCount);
//scoresList = ConvertScoreArrayLengths(scoresList, sonogram.FrameCount);
// DO NOT NEED FOLLOWING LINES BECAUSE HAVE CHANGED CODE TO ENSURE THAT ALL TEMPLATES USE THE SAME FRAME OVERLAP
// AND THEREFORE ALL SCORE ARRAYS ARE OF THE SAME LENGTH FOR GIVEN RECORDING
// Edit the events because they will not necessarily correspond to the timescale of the display image
//Log.WriteLine("# Convert time scale of events.");
//foreach (AcousticEvent ae in predictedEvents)
//{
// Log.WriteLine("# Event frame= {0} to {1}.", ae.oblong.RowTop, ae.oblong.RowBottom);
// ae.FrameOffset = sonogram.FrameOffset;
// ae.FramesPerSecond = sonogram.FramesPerSecond;
// ae.oblong = AcousticEvent.ConvertEvent2Oblong(ae);
// Log.WriteLine("# Event time = {0:f2} to {1:f2}.", ae.StartTime, ae.EndTime);
// Log.WriteLine("# Event frame= {0} to {1}.", ae.oblong.RowTop, ae.oblong.RowBottom);
//}
using (System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines))
using (Image_MultiTrack image = new Image_MultiTrack(img))
{
//img.Save(@"C:\SensorNetworks\WavFiles\temp1\testimage1.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
// Add in score tracks
for (int s = 0; s < scoresList.Count; s++)
{
if (scoresList[s] == null)
{
continue;
}
double[] scores = scoresList[s];
double normMax = thresholdList[s] * 4; //so normalised eventThreshold = 0.25
for (int i = 0; i < scores.Length; i++)
{
scores[i] /= normMax;
if (scores[i] > 1.0)
{
scores[i] = 1.0;
}
if (scores[i] < 0.0)
{
scores[i] = 0.0;
}
}
image.AddTrack(ImageTrack.GetScoreTrack(scores, 0.0, 1.0, 0.25));
} //end adding in score tracks
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
image.Save(path.FullName);
}// using
} // DrawSonogram()
public static void DrawSonogram(BaseSonogram sonogram, string path, List <AcousticEvent> predictedEvents, double threshold, double[] scores)
{
Log.WriteLine("# Start to draw image of sonogram.");
bool doHighlightSubband = false; bool add1kHzLines = true;
using (System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines))
using (Image_MultiTrack image = new Image_MultiTrack(img))
{
//img.Save(@"C:\SensorNetworks\WavFiles\temp1\testimage1.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
image.AddTrack(Image_Track.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
if (scores != null)
{
double normMax = threshold * 4; //so normalised eventThreshold = 0.25
for (int i = 0; i < scores.Length; i++)
{
scores[i] /= normMax;
if (scores[i] > 1.0)
{
scores[i] = 1.0;
}
if (scores[i] < 0.0)
{
scores[i] = 0.0;
}
}
image.AddTrack(Image_Track.GetScoreTrack(scores, 0.0, 1.0, 0.25));
}
image.AddEvents(predictedEvents);
image.Save(path);
}
}
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());
}
}//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()
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 void Execute(Arguments arguments)
{
MainEntry.WarnIfDeveloperEntryUsed();
if (arguments == null)
{
throw new NoDeveloperMethodException();
}
// READ PARAMETER VALUES FROM INI FILE
var config = ConfigFile.Deserialize(arguments.Config);
var aedConfig = Aed.GetAedParametersFromConfigFileOrDefaults(config);
var input = arguments.Source;
Tuple <BaseSonogram, List <AcousticEvent> > result = Detect(input, aedConfig, Default.eprNormalisedMinScore, TimeSpan.Zero);
List <AcousticEvent> eprEvents = result.Item2;
eprEvents.Sort((ae1, ae2) => ae1.TimeStart.CompareTo(ae2.TimeStart));
LoggedConsole.WriteLine();
foreach (AcousticEvent ae in eprEvents)
{
LoggedConsole.WriteLine(ae.TimeStart + "," + ae.EventDurationSeconds + "," + ae.LowFrequencyHertz + "," + ae.HighFrequencyHertz);
}
LoggedConsole.WriteLine();
string outputFolder = arguments.Config.ToFileInfo().DirectoryName;
string wavFilePath = input.FullName;
BaseSonogram sonogram = result.Item1;
string imagePath = Path.Combine(outputFolder, Path.GetFileNameWithoutExtension(wavFilePath) + ".png");
var image = Aed.DrawSonogram(sonogram, eprEvents.ConvertAcousticEventsToSpectralEvents());
image.Save(imagePath);
}
}//end CaneToadRecogniser
public static void DrawSonogram(BaseSonogram sonogram, string path, double[,] hits, double[] scores,
List <AcousticEvent> predictedEvents, double eventThreshold, double[] intensity)
{
Log.WriteLine("# Start to draw image of sonogram.");
bool doHighlightSubband = false;
bool add1kHzLines = true;
//double maxScore = 50.0; //assumed max posisble oscillations per second
using (System.Drawing.Image img = sonogram.GetImage(doHighlightSubband, add1kHzLines, doMelScale: false))
using (Image_MultiTrack image = new Image_MultiTrack(img))
{
//img.Save(@"C:\SensorNetworks\WavFiles\temp1\testimage1.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
image.AddTrack(ImageTrack.GetTimeTrack(sonogram.Duration, sonogram.FramesPerSecond));
image.AddTrack(ImageTrack.GetSegmentationTrack(sonogram));
image.AddTrack(ImageTrack.GetScoreTrack(scores, 0.0, 1.0, eventThreshold));
//double maxScore = 100.0;
//image.AddSuperimposedMatrix(hits, maxScore);
if (intensity != null)
{
double min, max;
DataTools.MinMax(intensity, out min, out max);
double threshold_norm = eventThreshold / max; //min = 0.0;
intensity = DataTools.normalise(intensity);
image.AddTrack(ImageTrack.GetScoreTrack(intensity, 0.0, 1.0, eventThreshold));
}
image.AddEvents(predictedEvents, sonogram.NyquistFrequency, sonogram.Configuration.FreqBinCount, sonogram.FramesPerSecond);
image.Save(path);
}
}
/// <summary>
/// Performs Spectral Peak Tracking on a recording
/// Returns a matrix derived from the sonogram
/// </summary>
/// <param name="sonogram">the sonogram</param>
/// <param name="intensityThreshold">Intensity threshold in decibels above backgorund</param>
/// <param name="smallLengthThreshold">remove event swhose length is less than this threshold</param>
/// <returns></returns>
public static Tuple <double[, ]> doSPT(BaseSonogram sonogram, double intensityThreshold, int smallLengthThreshold)
{
// Sonograms in Matlab (which F# AED was modelled on) are orientated the opposite way
var m = MatrixModule.transpose(MatrixModule.ofArray2D(sonogram.Data));
//Log.WriteLine("Wiener filter start");
var w = Matlab.wiener2(7, m);
//Log.WriteLine("Wiener filter end");
//Log.WriteLine("Remove subband mode intensities start");
var s = AcousticEventDetection.removeSubbandModeIntensities(w);
//Log.WriteLine("Remove subband mode intensities end");
Log.WriteLine("SPT start");
int nh = 3;
var p = SpectralPeakTrack.spt(s, intensityThreshold, nh, smallLengthThreshold);
Log.WriteLine("SPT finished");
var r = MatrixModule.toArray2D(MatrixModule.transpose(p));
return(Tuple.Create(r));
}
/// <summary>
/// AN EXPERIMENTAL SPECTROGRAM - A FALSE-COLOR VERSION OF A standard scale SPECTROGRAM.
/// </summary>
/// <param name="dbSpectrogramData">The original data for decibel spectrogram.</param>
/// <param name="nrSpectrogram">The noise-reduced spectrogram.</param>
/// <param name="sourceRecordingName">Name of the source file. Required only to add label to spectrogram.</param>
/// <returns>Image of spectrogram.</returns>
public static Image <Rgb24> GetDecibelSpectrogram_Ridges(
double[,] dbSpectrogramData,
SpectrogramStandard nrSpectrogram,
string sourceRecordingName)
{
// ########################### SOBEL ridge detection
var ridgeThreshold = 3.5;
var matrix = ImageTools.WienerFilter(dbSpectrogramData, 3);
var hits = RidgeDetection.Sobel5X5RidgeDetectionExperiment(matrix, ridgeThreshold);
// ########################### EIGEN ridge detection
//double ridgeThreshold = 6.0;
//double dominanceThreshold = 0.7;
//var rotatedData = MatrixTools.MatrixRotate90Anticlockwise(dbSpectrogramData);
//byte[,] hits = RidgeDetection.StructureTensorRidgeDetection(rotatedData, ridgeThreshold, dominanceThreshold);
//hits = MatrixTools.MatrixRotate90Clockwise(hits);
// ########################### EIGEN ridge detection
var frameStep = nrSpectrogram.Configuration.WindowStep;
var sampleRate = nrSpectrogram.SampleRate;
var image = SpectrogramTools.CreateFalseColourDecibelSpectrogram(dbSpectrogramData, nrSpectrogram.Data, hits);
image = BaseSonogram.GetImageAnnotatedWithLinearHertzScale(
image,
sampleRate,
frameStep,
$"AN EXPERIMENTAL DECIBEL SPECTROGRAM with ridges ({sourceRecordingName})",
ImageTags[Experimental]);
//var image = decibelSpectrogram.GetImageFullyAnnotated("DECIBEL SPECTROGRAM - with ridges");
return(image);
}
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());
}
/// <summary>
/// Only call this method for short recordings.
/// If accumulating data for long recordings then call the method for long recordings - i.e.
/// double[] spectralIndex = GenerateOscillationDataAndImages(FileInfo audioSegment, Dictionary configDict, false, false).
/// </summary>
public static FreqVsOscillationsResult GetFreqVsOscillationsDataAndImage(BaseSonogram sonogram, string algorithmName)
{
double sensitivity = DefaultSensitivityThreshold;
int sampleLength = DefaultSampleLength;
var freqOscilMatrix = GetFrequencyByOscillationsMatrix(sonogram.Data, sensitivity, sampleLength, algorithmName);
var image = GetFreqVsOscillationsImage(freqOscilMatrix, sonogram.FramesPerSecond, sonogram.FBinWidth, sampleLength, algorithmName);
var sourceName = Path.GetFileNameWithoutExtension(sonogram.Configuration.SourceFName);
// get the OSC spectral index
// var spectralIndex = ConvertMatrix2SpectralIndexBySummingFreqColumns(freqOscilMatrix, skipNRows: 1);
var spectralIndex = MatrixTools.GetMaximumColumnValues(freqOscilMatrix);
if (spectralIndex == null)
{
throw new ArgumentNullException(nameof(spectralIndex));
}
// DEBUGGING
// Add spectralIndex into the matrix because want to add it to image.
// This is for debugging only and can comment this line
int rowCount = freqOscilMatrix.GetLength(0);
MatrixTools.SetRow(freqOscilMatrix, rowCount - 2, spectralIndex);
var result = new FreqVsOscillationsResult
{
SourceFileName = sourceName,
FreqOscillationImage = image,
FreqOscillationData = freqOscilMatrix,
OscillationSpectralIndex = spectralIndex,
};
return(result);
}
private void WriteDebugImage(
AudioRecording recording,
DirectoryInfo outputDirectory,
BaseSonogram sonogram,
List <AcousticEvent> acousticEvents,
List <Plot> plots,
double[,] hits)
{
//DEBUG IMAGE this recogniser only. MUST set false for deployment.
bool displayDebugImage = MainEntry.InDEBUG;
if (displayDebugImage)
{
Image debugImage1 = SpectrogramTools.GetSonogramPlusCharts(sonogram, acousticEvents, plots, hits);
var debugPath1 = outputDirectory.Combine(FilenameHelpers.AnalysisResultName(Path.GetFileNameWithoutExtension(recording.BaseName), this.Identifier, "png", "DebugSpectrogram1"));
debugImage1.Save(debugPath1.FullName);
// save new image with longer frame
var sonoConfig2 = new SonogramConfig
{
SourceFName = recording.BaseName,
WindowSize = 1024,
WindowOverlap = 0,
//NoiseReductionType = NoiseReductionType.NONE,
NoiseReductionType = NoiseReductionType.Standard,
NoiseReductionParameter = 0.1,
};
BaseSonogram sonogram2 = new SpectrogramStandard(sonoConfig2, recording.WavReader);
var debugPath2 = outputDirectory.Combine(FilenameHelpers.AnalysisResultName(Path.GetFileNameWithoutExtension(recording.BaseName), this.Identifier, "png", "DebugSpectrogram2"));
Image debugImage2 = SpectrogramTools.GetSonogramPlusCharts(sonogram2, acousticEvents, plots, null);
debugImage2.Save(debugPath2.FullName);
}
}
public static List <AcousticEvent> ReadGroundParrotTemplateAsList(BaseSonogram sonogram)
{
var timeScale = sonogram.FrameStep;
var hzScale = (int)sonogram.FBinWidth;
int rows = GroundParrotTemplate1.GetLength(0);
int cols = GroundParrotTemplate1.GetLength(1);
double timeOffset = GroundParrotTemplate1[0, 0];
var gpTemplate = new List <AcousticEvent>();
for (int r = 0; r < rows; r++)
{
int t1 = (int)Math.Round((GroundParrotTemplate1[r, 0] - timeOffset) / timeScale);
int t2 = (int)Math.Round((GroundParrotTemplate1[r, 1] - timeOffset) / timeScale);
int f2 = (int)Math.Round(GroundParrotTemplate1[r, 2] / hzScale);
int f1 = (int)Math.Round(GroundParrotTemplate1[r, 3] / hzScale);
Oblong o = new Oblong(t1, f1, t2, f2);
gpTemplate.Add(
new AcousticEvent(
TimeSpan.Zero,
o,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FrameDuration,
sonogram.FrameStep,
sonogram.FrameCount));
}
return(gpTemplate);
}
public override AnalysisResult2 Analyze <T>(AnalysisSettings analysisSettings, SegmentSettings <T> segmentSettings)
{
FileInfo audioFile = segmentSettings.SegmentAudioFile;
var aedConfig = GetAedParametersFromConfigFileOrDefaults(analysisSettings.Configuration);
var results = Detect(audioFile, aedConfig, segmentSettings.SegmentStartOffset);
var analysisResults = new AnalysisResult2(analysisSettings, segmentSettings, results.Item2.Duration);
analysisResults.AnalysisIdentifier = this.Identifier;
analysisResults.Events = results.Item1;
BaseSonogram sonogram = results.Item3;
if (analysisSettings.AnalysisDataSaveBehavior)
{
this.WriteEventsFile(segmentSettings.SegmentEventsFile, analysisResults.Events);
analysisResults.EventsFile = segmentSettings.SegmentEventsFile;
}
if (analysisSettings.AnalysisDataSaveBehavior)
{
// noop
}
// save image of sonograms
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave(analysisResults.Events.Length))
{
Image image = DrawSonogram(sonogram, results.Item1);
image.Save(segmentSettings.SegmentImageFile.FullName);
analysisResults.ImageFile = segmentSettings.SegmentImageFile;
}
return(analysisResults);
}
} //Analysis()
//private static System.Tuple<string[], Type[], bool[]> InitOutputTableColumns()
//{
// HEADERS[0] = header_count; COL_TYPES[0] = typeof(int); DISPLAY_COLUMN[0] = false; COMBO_WEIGHTS[0] = 0.0;
// HEADERS[1] = header_startMin; COL_TYPES[1] = typeof(double); DISPLAY_COLUMN[1] = false; COMBO_WEIGHTS[1] = 0.0;
// HEADERS[2] = header_SecondsDuration; COL_TYPES[2] = typeof(double); DISPLAY_COLUMN[2] = false; COMBO_WEIGHTS[2] = 0.0;
// HEADERS[3] = header_avAmpdB; COL_TYPES[3] = typeof(double); DISPLAY_COLUMN[3] = true; COMBO_WEIGHTS[3] = 0.0;
// HEADERS[4] = header_snrdB; COL_TYPES[4] = typeof(double); DISPLAY_COLUMN[4] = true; COMBO_WEIGHTS[4] = 0.0;
// HEADERS[5] = header_bgdB; COL_TYPES[5] = typeof(double); DISPLAY_COLUMN[5] = true; COMBO_WEIGHTS[5] = 0.0;
// HEADERS[6] = header_activity; COL_TYPES[6] = typeof(double); DISPLAY_COLUMN[6] = true; COMBO_WEIGHTS[6] = 0.0;
// HEADERS[7] = header_hfCover; COL_TYPES[7] = typeof(double); DISPLAY_COLUMN[7] = true; COMBO_WEIGHTS[7] = 0.0;
// HEADERS[8] = header_mfCover; COL_TYPES[8] = typeof(double); DISPLAY_COLUMN[8] = true; COMBO_WEIGHTS[8] = 0.0;
// HEADERS[9] = header_lfCover; COL_TYPES[9] = typeof(double); DISPLAY_COLUMN[9] = true; COMBO_WEIGHTS[9] = 0.0;
// HEADERS[10] = header_HAmpl; COL_TYPES[10] = typeof(double); DISPLAY_COLUMN[10] = true; COMBO_WEIGHTS[10] = 0.0;
// HEADERS[11] = header_HAvSpectrum; COL_TYPES[11] = typeof(double); DISPLAY_COLUMN[11] = true; COMBO_WEIGHTS[11] = 0.4;
// //HEADERS[12] = header_HVarSpectrum; COL_TYPES[12] = typeof(double); DISPLAY_COLUMN[12] = false; COMBO_WEIGHTS[12] = 0.1;
// return Tuple.Create(HEADERS, COL_TYPES, DISPLAY_COLUMN);
//}
static Image DrawSonogram(BaseSonogram sonogram, List <Plot> scores)
{
Dictionary <string, string> configDict = new Dictionary <string, string>();
List <AcousticEvent> predictedEvents = null;
double eventThreshold = 0.0;
Image image = SpectrogramTools.Sonogram2Image(sonogram, configDict, null, scores, predictedEvents, eventThreshold);
return(image);
}
private static Image DrawSonogram(double[,] data, TimeSpan xInterval, TimeSpan xAxisPixelDuration, int nyquist, int herzInterval, string title)
{
var image = ImageTools.GetMatrixImage(data);
var titleBar = BaseSonogram.DrawTitleBarOfGrayScaleSpectrogram(title, image.Width);
var minuteOffset = TimeSpan.Zero;
var labelInterval = TimeSpan.FromSeconds(5);
image = BaseSonogram.FrameSonogram(image, titleBar, minuteOffset, xInterval, xAxisPixelDuration, labelInterval, nyquist, herzInterval);
return(image);
}
protected virtual Image DrawSonogram(
BaseSonogram sonogram,
double[,] hits,
List <Plot> scores,
List <AcousticEvent> predictedEvents,
double eventThreshold)
{
var image = SpectrogramTools.GetSonogramPlusCharts(sonogram, predictedEvents, scores, hits);
return(image);
}
public static EventCommon[] CallAed(BaseSonogram sonogram, AedConfiguration aedConfiguration, TimeSpan segmentStartOffset, TimeSpan segmentDuration)
{
Log.Info("AED start");
var aedOptions = new AedOptions(sonogram.Configuration.NyquistFreq)
{
IntensityThreshold = aedConfiguration.IntensityThreshold,
SmallAreaThreshold = aedConfiguration.SmallAreaThreshold,
DoNoiseRemoval = aedConfiguration.NoiseReductionType == NoiseReductionType.None,
};
if (aedConfiguration.BandpassMinimum.HasValue && aedConfiguration.BandpassMaximum.HasValue)
{
var bandPassFilter =
Tuple.Create(
(double)aedConfiguration.BandpassMinimum.Value,
(double)aedConfiguration.BandpassMaximum.Value);
aedOptions.BandPassFilter = new FSharpOption <Tuple <double, double> >(bandPassFilter);
}
IEnumerable <Oblong> oblongs = AcousticEventDetection.detectEvents(aedOptions, sonogram.Data);
Log.Info("AED finished");
var unitConverters = new UnitConverters(
segmentStartOffset.TotalSeconds,
sonogram.SampleRate,
sonogram.Configuration.WindowSize,
sonogram.Configuration.WindowOverlap);
var events = oblongs.Select(
o =>
{
var blob = new BlobEvent()
{
SegmentDurationSeconds = segmentDuration.TotalSeconds,
Name = "AED Event",
};
unitConverters.SetBounds(blob, o);
if (aedConfiguration.IncludeHitElementsInOutput)
{
o.HitElements
.Select(p => unitConverters.ConvertPointToSpectralPoint(p, 1.0))
.ForEach(sp => blob.Points.Add(sp));
}
return(blob);
});
return(events.ToArray());
}
public void CropTrack(BaseSonogram sonogram, double threshold)
{
//int length = sonogram.FrameCount;
int binID = (int)this.AverageBin;
double[] freqBin = MatrixTools.GetColumn(sonogram.Data, binID);
double[] subArray = DataTools.Subarray(freqBin, this.StartFrame, this.Length);
int[] bounds = DataTools.Peaks_CropLowAmplitude(subArray, threshold);
this.EndFrame = this.StartFrame + bounds[1];
this.StartFrame += bounds[0];
}
public override AnalysisResult2 Analyze <T>(AnalysisSettings analysisSettings, SegmentSettings <T> segmentSettings)
{
FileInfo audioFile = segmentSettings.SegmentAudioFile;
/* ###################################################################### */
Dictionary <string, string> configuration = analysisSettings.Configuration.ToDictionary();
KoalaMaleResults results = Analysis(audioFile, configuration, segmentSettings.SegmentStartOffset);
/* ###################################################################### */
BaseSonogram sonogram = results.Sonogram;
double[,] hits = results.Hits;
Plot scores = results.Plot;
var analysisResults = new AnalysisResult2(analysisSettings, segmentSettings, results.RecordingtDuration)
{
AnalysisIdentifier = this.Identifier,
};
analysisResults.Events = results.Events.ToArray();
if (analysisSettings.AnalysisDataSaveBehavior)
{
this.WriteEventsFile(segmentSettings.SegmentEventsFile, analysisResults.Events);
analysisResults.EventsFile = segmentSettings.SegmentEventsFile;
}
if (analysisSettings.AnalysisDataSaveBehavior)
{
TimeSpan unitTime = TimeSpan.FromMinutes(1.0);
analysisResults.SummaryIndices = this.ConvertEventsToSummaryIndices(
analysisResults.Events,
unitTime,
analysisResults.SegmentAudioDuration,
0);
this.WriteSummaryIndicesFile(segmentSettings.SegmentSummaryIndicesFile, analysisResults.SummaryIndices);
}
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave(analysisResults.Events.Length))
{
string imagePath = segmentSettings.SegmentImageFile.FullName;
const double EventThreshold = 0.1;
Image image = DrawSonogram(sonogram, hits, scores, results.Events, EventThreshold);
image.Save(imagePath, ImageFormat.Png);
analysisResults.ImageFile = segmentSettings.SegmentImageFile;
}
return(analysisResults);
}
/// <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 Setup()
{
this.outputDirectory = PathHelper.GetTempDir();
this.audioRecording = new AudioRecording(PathHelper.ResolveAsset("Recordings", "20190115_Bellingen_Feeding_minute6_OneChannel22050.wav"));
var sonoConfig = new SonogramConfig
{
WindowSize = 512,
NoiseReductionType = NoiseReductionType.Standard,
NoiseReductionParameter = 3.0,
WindowOverlap = 0.0,
};
this.sonogram = new SpectrogramStandard(sonoConfig, this.audioRecording.WavReader);
}
public static AcousticEvent[] CallAed(BaseSonogram sonogram, AedConfiguration aedConfiguration, TimeSpan segmentStartOffset, TimeSpan segmentDuration)
{
Log.Info("AED start");
var aedOptions = new AedOptions(sonogram.Configuration.NyquistFreq)
{
IntensityThreshold = aedConfiguration.IntensityThreshold,
SmallAreaThreshold = aedConfiguration.SmallAreaThreshold,
DoNoiseRemoval = aedConfiguration.NoiseReductionType == NoiseReductionType.None,
};
if (aedConfiguration.BandpassMinimum.HasValue && aedConfiguration.BandpassMaximum.HasValue)
{
var bandPassFilter =
Tuple.Create(
(double)aedConfiguration.BandpassMinimum.Value,
(double)aedConfiguration.BandpassMaximum.Value);
aedOptions.BandPassFilter = new FSharpOption <Tuple <double, double> >(bandPassFilter);
}
IEnumerable <Oblong> oblongs = AcousticEventDetection.detectEvents(aedOptions, sonogram.Data);
Log.Info("AED finished");
var events = oblongs.Select(
o =>
{
if (!aedConfiguration.IncludeHitElementsInOutput)
{
o.HitElements = null;
}
return(new AcousticEvent(
segmentStartOffset,
o,
sonogram.NyquistFrequency,
sonogram.Configuration.FreqBinCount,
sonogram.FrameDuration,
sonogram.FrameStep,
sonogram.FrameCount)
{
BorderColour = aedConfiguration.AedEventColor,
HitColour = aedConfiguration.AedHitColor,
SegmentDurationSeconds = segmentDuration.TotalSeconds,
});
}).ToArray();
return(events);
}
public static double[] DetectEPR(List <AcousticEvent> template, BaseSonogram sonogram, double[] odScores, double odThreshold)
{
int length = sonogram.FrameCount;
double[] eprScores = new double[length];
Oblong ob1 = template[0].Oblong; // the first chirp in template
Oblong obZ = template[template.Count - 1].Oblong; // the last chirp in template
int templateLength = obZ.RowBottom;
for (int frame = 0; frame < length - templateLength; frame++)
{
if (odScores[frame] < odThreshold)
{
continue;
}
// get best freq band and max score for the first rectangle.
double maxScore = -double.MaxValue;
int freqBinOffset = 0;
for (int bin = -5; bin < 15; bin++)
{
Oblong ob = new Oblong(ob1.RowTop + frame, ob1.ColumnLeft + bin, ob1.RowBottom + frame, ob1.ColumnRight + bin);
double score = GetLocationScore(sonogram, ob);
if (score > maxScore)
{
maxScore = score;
freqBinOffset = bin;
}
}
//if location score exceeds threshold of 6 dB then get remaining scores.
if (maxScore < 6.0)
{
continue;
}
foreach (AcousticEvent ae in template)
{
Oblong ob = new Oblong(ae.Oblong.RowTop + frame, ae.Oblong.ColumnLeft + freqBinOffset, ae.Oblong.RowBottom + frame, ae.Oblong.ColumnRight + freqBinOffset);
double score = GetLocationScore(sonogram, ob);
eprScores[frame] += score;
}
eprScores[frame] /= template.Count;
}
return(eprScores);
}
public override AnalysisResult2 Analyze <T>(AnalysisSettings analysisSettings, SegmentSettings <T> segmentSettings)
{
FileInfo audioFile = segmentSettings.SegmentAudioFile;
// execute actual analysis
dynamic configuration = analysisSettings.Configuration;
var recording = new AudioRecording(audioFile.FullName);
Log.Debug("Canetoad sample rate:" + recording.SampleRate);
RecognizerResults results = Analysis(recording, configuration, segmentSettings.SegmentStartOffset, segmentSettings.SegmentOutputDirectory);
var analysisResults = new AnalysisResult2(analysisSettings, segmentSettings, recording.Duration);
BaseSonogram sonogram = results.Sonogram;
double[,] hits = results.Hits;
Plot scores = results.Plots.First();
List <AcousticEvent> predictedEvents = results.Events;
analysisResults.Events = predictedEvents.ToArray();
if (analysisSettings.AnalysisDataSaveBehavior)
{
this.WriteEventsFile(segmentSettings.SegmentEventsFile, analysisResults.Events);
analysisResults.EventsFile = segmentSettings.SegmentEventsFile;
}
if (analysisSettings.AnalysisDataSaveBehavior)
{
var unitTime = TimeSpan.FromMinutes(1.0);
analysisResults.SummaryIndices = this.ConvertEventsToSummaryIndices(analysisResults.Events, unitTime, analysisResults.SegmentAudioDuration, 0);
analysisResults.SummaryIndicesFile = segmentSettings.SegmentSummaryIndicesFile;
this.WriteSummaryIndicesFile(segmentSettings.SegmentSummaryIndicesFile, analysisResults.SummaryIndices);
}
if (analysisSettings.AnalysisImageSaveBehavior.ShouldSave(analysisResults.Events.Length))
{
string imagePath = segmentSettings.SegmentImageFile.FullName;
const double EventThreshold = 0.1;
Image image = DrawSonogram(sonogram, hits, scores, predictedEvents, EventThreshold);
image.Save(imagePath, ImageFormat.Png);
analysisResults.ImageFile = segmentSettings.SegmentImageFile;
}
return(analysisResults);
}
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());
}
public static Image GetCepstralSpectrogram(SonogramConfig sonoConfig, AudioRecording recording, string sourceRecordingName)
{
// TODO at present noise reduction type must be set = Standard.
sonoConfig.NoiseReductionType = NoiseReductionType.Standard;
sonoConfig.NoiseReductionParameter = 3.0;
var cepgram = new SpectrogramCepstral(sonoConfig, recording.WavReader);
var image = cepgram.GetImage();
var titleBar = BaseSonogram.DrawTitleBarOfGrayScaleSpectrogram("CEPSTRO-GRAM " + sourceRecordingName, image.Width);
var startTime = TimeSpan.Zero;
var xAxisTicInterval = TimeSpan.FromSeconds(1);
TimeSpan xAxisPixelDuration = TimeSpan.FromSeconds(sonoConfig.WindowStep / (double)sonoConfig.SampleRate);
var labelInterval = TimeSpan.FromSeconds(5);
image = BaseSonogram.FrameSonogram(image, titleBar, startTime, xAxisTicInterval, xAxisPixelDuration, labelInterval);
return(image);
}