comparison plugins/BeatTrack.cpp @ 27:3256bfa04ed8

* split out tempo/beat/onset plugin into tempo/beat and onset

+/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
+
+/*
+    QM Vamp Plugin Set
+
+    Centre for Digital Music, Queen Mary, University of London.
+    All rights reserved.
+*/
+
+#include "BeatTrack.h"
+
+#include <dsp/onsets/DetectionFunction.h>
+#include <dsp/onsets/PeakPicking.h>
+#include <dsp/tempotracking/TempoTrack.h>
+
+using std::string;
+using std::vector;
+using std::cerr;
+using std::endl;
+
+float BeatTracker::m_stepSecs = 0.01161;
+
+class BeatTrackerData
+{
+public:
+    BeatTrackerData(const DFConfig &config) : dfConfig(config) {
+	df = new DetectionFunction(config);
+    }
+    ~BeatTrackerData() {
+	delete df;
+    }
+    void reset() {
+	delete df;
+	df = new DetectionFunction(dfConfig);
+	dfOutput.clear();
+    }
+
+    DFConfig dfConfig;
+    DetectionFunction *df;
+    vector<double> dfOutput;
+};
+    
+
+BeatTracker::BeatTracker(float inputSampleRate) :
+    Vamp::Plugin(inputSampleRate),
+    m_d(0),
+    m_dfType(DF_COMPLEXSD)
+{
+}
+
+BeatTracker::~BeatTracker()
+{
+    delete m_d;
+}
+
+string
+BeatTracker::getIdentifier() const
+{
+    return "qm-tempotracker";
+}
+
+string
+BeatTracker::getName() const
+{
+    return "Tempo and Beat Tracker";
+}
+
+string
+BeatTracker::getDescription() const
+{
+    return "Estimate beat locations and tempo";
+}
+
+string
+BeatTracker::getMaker() const
+{
+    return "Christian Landone and Matthew Davies, Queen Mary, University of London";
+}
+
+int
+BeatTracker::getPluginVersion() const
+{
+    return 3;
+}
+
+string
+BeatTracker::getCopyright() const
+{
+    return "Copyright (c) 2006-2007 - All Rights Reserved";
+}
+
+BeatTracker::ParameterList
+BeatTracker::getParameterDescriptors() const
+{
+    ParameterList list;
+
+    ParameterDescriptor desc;
+    desc.identifier = "dftype";
+    desc.name = "Onset Detection Function Type";
+    desc.description = "Method used to calculate the onset detection function";
+    desc.minValue = 0;
+    desc.maxValue = 3;
+    desc.defaultValue = 3;
+    desc.isQuantized = true;
+    desc.quantizeStep = 1;
+    desc.valueNames.push_back("High-Frequency Content");
+    desc.valueNames.push_back("Spectral Difference");
+    desc.valueNames.push_back("Phase Deviation");
+    desc.valueNames.push_back("Complex Domain");
+    desc.valueNames.push_back("Broadband Energy Rise");
+    list.push_back(desc);
+
+    return list;
+}
+
+float
+BeatTracker::getParameter(std::string name) const
+{
+    if (name == "dftype") {
+        switch (m_dfType) {
+        case DF_HFC: return 0;
+        case DF_SPECDIFF: return 1;
+        case DF_PHASEDEV: return 2;
+        default: case DF_COMPLEXSD: return 3;
+        case DF_BROADBAND: return 4;
+        }
+    }
+    return 0.0;
+}
+
+void
+BeatTracker::setParameter(std::string name, float value)
+{
+    if (name == "dftype") {
+        switch (lrintf(value)) {
+        case 0: m_dfType = DF_HFC; break;
+        case 1: m_dfType = DF_SPECDIFF; break;
+        case 2: m_dfType = DF_PHASEDEV; break;
+        default: case 3: m_dfType = DF_COMPLEXSD; break;
+        case 4: m_dfType = DF_BROADBAND; break;
+        }
+    }
+}
+
+bool
+BeatTracker::initialise(size_t channels, size_t stepSize, size_t blockSize)
+{
+    if (m_d) {
+	delete m_d;
+	m_d = 0;
+    }
+
+    if (channels < getMinChannelCount() ||
+	channels > getMaxChannelCount()) {
+        std::cerr << "BeatTracker::initialise: Unsupported channel count: "
+                  << channels << std::endl;
+        return false;
+    }
+
+    if (blockSize != getPreferredStepSize() * 2) {
+        std::cerr << "BeatTracker::initialise: Unsupported block size for this sample rate: "
+                  << blockSize << " (wanted " << (getPreferredStepSize() * 2) << ")" << std::endl;
+        return false;
+    }
+
+    if (stepSize != getPreferredStepSize()) {
+        std::cerr << "BeatTracker::initialise: Unsupported step size for this sample rate: "
+                  << stepSize << " (wanted " << (getPreferredStepSize()) << ")" << std::endl;
+        return false;
+    }
+
+    DFConfig dfConfig;
+    dfConfig.DFType = m_dfType;
+    dfConfig.stepSecs = float(stepSize) / m_inputSampleRate;
+    dfConfig.stepSize = stepSize;
+    dfConfig.frameLength = blockSize;
+    dfConfig.dbRise = 3;
+    
+    m_d = new BeatTrackerData(dfConfig);
+    return true;
+}
+
+void
+BeatTracker::reset()
+{
+    if (m_d) m_d->reset();
+}
+
+size_t
+BeatTracker::getPreferredStepSize() const
+{
+    size_t step = size_t(m_inputSampleRate * m_stepSecs + 0.0001);
+//    std::cerr << "BeatTracker::getPreferredStepSize: input sample rate is " << m_inputSampleRate << ", step size is " << step << std::endl;
+    return step;
+}
+
+size_t
+BeatTracker::getPreferredBlockSize() const
+{
+    return getPreferredStepSize() * 2;
+}
+
+BeatTracker::OutputList
+BeatTracker::getOutputDescriptors() const
+{
+    OutputList list;
+
+    OutputDescriptor beat;
+    beat.identifier = "beats";
+    beat.name = "Beats";
+    beat.description = "Estimated metrical beat locations";
+    beat.unit = "";
+    beat.hasFixedBinCount = true;
+    beat.binCount = 0;
+    beat.sampleType = OutputDescriptor::VariableSampleRate;
+    beat.sampleRate = 1.0 / m_stepSecs;
+
+    OutputDescriptor df;
+    df.identifier = "detection_fn";
+    df.name = "Onset Detection Function";
+    df.description = "Probability function of note onset likelihood";
+    df.unit = "";
+    df.hasFixedBinCount = true;
+    df.binCount = 1;
+    df.hasKnownExtents = false;
+    df.isQuantized = false;
+    df.sampleType = OutputDescriptor::OneSamplePerStep;
+
+    OutputDescriptor tempo;
+    tempo.identifier = "tempo";
+    tempo.name = "Tempo";
+    tempo.description = "Locked tempo estimates";
+    tempo.unit = "bpm";
+    tempo.hasFixedBinCount = true;
+    tempo.binCount = 1;
+    tempo.sampleType = OutputDescriptor::VariableSampleRate;
+    tempo.sampleRate = 1.0 / m_stepSecs;
+
+    list.push_back(beat);
+    list.push_back(df);
+    list.push_back(tempo);
+
+    return list;
+}
+
+BeatTracker::FeatureSet
+BeatTracker::process(const float *const *inputBuffers,
+                     Vamp::RealTime /* timestamp */)
+{
+    if (!m_d) {
+	cerr << "ERROR: BeatTracker::process: "
+	     << "BeatTracker has not been initialised"
+	     << endl;
+	return FeatureSet();
+    }
+
+    size_t len = m_d->dfConfig.frameLength / 2;
+
+    double *magnitudes = new double[len];
+    double *phases = new double[len];
+
+    // We only support a single input channel
+
+    for (size_t i = 0; i < len; ++i) {
+
+        magnitudes[i] = sqrt(inputBuffers[0][i*2  ] * inputBuffers[0][i*2  ] +
+                             inputBuffers[0][i*2+1] * inputBuffers[0][i*2+1]);
+
+	phases[i] = atan2(-inputBuffers[0][i*2+1], inputBuffers[0][i*2]);
+    }
+
+    double output = m_d->df->process(magnitudes, phases);
+
+    delete[] magnitudes;
+    delete[] phases;
+
+    m_d->dfOutput.push_back(output);
+
+    FeatureSet returnFeatures;
+
+    Feature feature;
+    feature.hasTimestamp = false;
+    feature.values.push_back(output);
+
+    returnFeatures[1].push_back(feature); // detection function is output 1
+    return returnFeatures;
+}
+
+BeatTracker::FeatureSet
+BeatTracker::getRemainingFeatures()
+{
+    if (!m_d) {
+	cerr << "ERROR: BeatTracker::getRemainingFeatures: "
+	     << "BeatTracker has not been initialised"
+	     << endl;
+	return FeatureSet();
+    }
+
+    double aCoeffs[] = { 1.0000, -0.5949, 0.2348 };
+    double bCoeffs[] = { 0.1600,  0.3200, 0.1600 };
+
+    TTParams ttParams;
+    ttParams.winLength = 512;
+    ttParams.lagLength = 128;
+    ttParams.LPOrd = 2;
+    ttParams.LPACoeffs = aCoeffs;
+    ttParams.LPBCoeffs = bCoeffs;
+    ttParams.alpha = 9;
+    ttParams.WinT.post = 8;
+    ttParams.WinT.pre = 7;
+
+    TempoTrack tempoTracker(ttParams);
+
+    vector<double> tempos;
+    vector<int> beats = tempoTracker.process(m_d->dfOutput, &tempos);
+
+    FeatureSet returnFeatures;
+
+    char label[100];
+
+    for (size_t i = 0; i < beats.size(); ++i) {
+
+	size_t frame = beats[i] * m_d->dfConfig.stepSize;
+
+	Feature feature;
+	feature.hasTimestamp = true;
+	feature.timestamp = Vamp::RealTime::frame2RealTime
+	    (frame, lrintf(m_inputSampleRate));
+
+	float bpm = 0.0;
+	int frameIncrement = 0;
+
+	if (i < beats.size() - 1) {
+
+	    frameIncrement = (beats[i+1] - beats[i]) * m_d->dfConfig.stepSize;
+
+	    // one beat is frameIncrement frames, so there are
+	    // samplerate/frameIncrement bps, so
+	    // 60*samplerate/frameIncrement bpm
+
+	    if (frameIncrement > 0) {
+		bpm = (60.0 * m_inputSampleRate) / frameIncrement;
+		bpm = int(bpm * 100.0 + 0.5) / 100.0;
+                sprintf(label, "%.2f bpm", bpm);
+                feature.label = label;
+	    }
+	}
+
+	returnFeatures[0].push_back(feature); // beats are output 0
+    }
+
+    double prevTempo = 0.0;
+
+    for (size_t i = 0; i < tempos.size(); ++i) {
+
+        size_t frame = i * m_d->dfConfig.stepSize * ttParams.lagLength;
+
+//        std::cerr << "unit " << i << ", step size " << m_d->dfConfig.stepSize << ", hop " << ttParams.lagLength << ", frame = " << frame << std::endl;
+        
+        if (tempos[i] > 1 && int(tempos[i] * 100) != int(prevTempo * 100)) {
+            Feature feature;
+            feature.hasTimestamp = true;
+            feature.timestamp = Vamp::RealTime::frame2RealTime
+                (frame, lrintf(m_inputSampleRate));
+            feature.values.push_back(tempos[i]);
+            sprintf(label, "%.2f bpm", tempos[i]);
+            feature.label = label;
+            returnFeatures[2].push_back(feature); // tempo is output 2
+        }
+    }
+
+    return returnFeatures;
+}
+