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livetrax/libs/vamp-pyin/YinVamp.cpp
Robin Gareus 63994f3b82
Include vamp-pyin
In preparation for captainMorgan's pitch analysis script.
2019-09-02 03:12:22 +02:00

368 lines
8.0 KiB
C++

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
/*
pYIN - A fundamental frequency estimator for monophonic audio
Centre for Digital Music, Queen Mary, University of London.
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License as
published by the Free Software Foundation; either version 2 of the
License, or (at your option) any later version. See the file
COPYING included with this distribution for more information.
*/
#include "YinVamp.h"
#include "MonoNote.h"
#include "vamp-sdk/FFT.h"
#include <vector>
#include <algorithm>
#include <cstdio>
#include <cmath>
#include <complex>
using std::string;
using std::vector;
using Vamp::RealTime;
YinVamp::YinVamp(float inputSampleRate) :
Plugin(inputSampleRate),
m_channels(0),
m_stepSize(256),
m_blockSize(2048),
m_fmin(40),
m_fmax(1600),
m_yin(2048, inputSampleRate, 0.0),
m_outNoF0(0),
m_outNoPeriodicity(0),
m_outNoRms(0),
m_outNoSalience(0),
m_yinParameter(0.15f),
m_outputUnvoiced(2.0f)
{
}
YinVamp::~YinVamp()
{
}
string
YinVamp::getIdentifier() const
{
return "yin";
}
string
YinVamp::getName() const
{
return "Yin";
}
string
YinVamp::getDescription() const
{
return "A vamp implementation of the Yin algorithm for monophonic frequency estimation.";
}
string
YinVamp::getMaker() const
{
return "Matthias Mauch";
}
int
YinVamp::getPluginVersion() const
{
// Increment this each time you release a version that behaves
// differently from the previous one
return 2;
}
string
YinVamp::getCopyright() const
{
return "GPL";
}
YinVamp::InputDomain
YinVamp::getInputDomain() const
{
return TimeDomain;
}
size_t
YinVamp::getPreferredBlockSize() const
{
return 2048;
}
size_t
YinVamp::getPreferredStepSize() const
{
return 256;
}
size_t
YinVamp::getMinChannelCount() const
{
return 1;
}
size_t
YinVamp::getMaxChannelCount() const
{
return 1;
}
YinVamp::ParameterList
YinVamp::getParameterDescriptors() const
{
ParameterList list;
ParameterDescriptor d;
d.identifier = "yinThreshold";
d.name = "Yin threshold";
d.description = "The greedy Yin search for a low value difference function is done once a dip lower than this threshold is reached.";
d.unit = "";
d.minValue = 0.025f;
d.maxValue = 1.0f;
d.defaultValue = 0.15f;
d.isQuantized = true;
d.quantizeStep = 0.025f;
list.push_back(d);
d.identifier = "outputunvoiced";
d.valueNames.clear();
d.name = "Output estimates classified as unvoiced?";
d.description = ".";
d.unit = "";
d.minValue = 0.0f;
d.maxValue = 2.0f;
d.defaultValue = 2.0f;
d.isQuantized = true;
d.quantizeStep = 1.0f;
d.valueNames.push_back("No");
d.valueNames.push_back("Yes");
d.valueNames.push_back("Yes, as negative frequencies");
list.push_back(d);
return list;
}
float
YinVamp::getParameter(string identifier) const
{
if (identifier == "yinThreshold") {
return m_yinParameter;
}
if (identifier == "outputunvoiced") {
return m_outputUnvoiced;
}
return 0.f;
}
void
YinVamp::setParameter(string identifier, float value)
{
if (identifier == "yinThreshold")
{
m_yinParameter = value;
}
if (identifier == "outputunvoiced")
{
m_outputUnvoiced = value;
}
}
YinVamp::ProgramList
YinVamp::getPrograms() const
{
ProgramList list;
return list;
}
string
YinVamp::getCurrentProgram() const
{
return ""; // no programs
}
void
YinVamp::selectProgram(string name)
{
}
YinVamp::OutputList
YinVamp::getOutputDescriptors() const
{
OutputList outputs;
OutputDescriptor d;
int outputNumber = 0;
d.identifier = "f0";
d.name = "Estimated f0";
d.description = "Estimated fundamental frequency";
d.unit = "Hz";
d.hasFixedBinCount = true;
d.binCount = 1;
d.hasKnownExtents = true;
d.minValue = m_fmin;
d.maxValue = 500;
d.isQuantized = false;
d.sampleType = OutputDescriptor::FixedSampleRate;
d.sampleRate = (m_inputSampleRate / m_stepSize);
d.hasDuration = false;
outputs.push_back(d);
m_outNoF0 = outputNumber++;
d.identifier = "periodicity";
d.name = "Periodicity";
d.description = "by-product of Yin f0 estimation";
d.unit = "";
d.hasFixedBinCount = true;
d.binCount = 1;
d.hasKnownExtents = true;
d.minValue = 0;
d.maxValue = 1;
d.isQuantized = false;
d.sampleType = OutputDescriptor::FixedSampleRate;
d.sampleRate = (m_inputSampleRate / m_stepSize);
d.hasDuration = false;
outputs.push_back(d);
m_outNoPeriodicity = outputNumber++;
d.identifier = "rms";
d.name = "Root mean square";
d.description = "Root mean square of the waveform.";
d.unit = "";
d.hasFixedBinCount = true;
d.binCount = 1;
d.hasKnownExtents = true;
d.minValue = 0;
d.maxValue = 1;
d.isQuantized = false;
d.sampleType = OutputDescriptor::FixedSampleRate;
d.sampleRate = (m_inputSampleRate / m_stepSize);
d.hasDuration = false;
outputs.push_back(d);
m_outNoRms = outputNumber++;
d.identifier = "salience";
d.name = "Salience";
d.description = "Yin Salience";
d.hasFixedBinCount = true;
d.binCount = m_blockSize / 2;
d.hasKnownExtents = true;
d.minValue = 0;
d.maxValue = 1;
d.isQuantized = false;
d.sampleType = OutputDescriptor::FixedSampleRate;
d.sampleRate = (m_inputSampleRate / m_stepSize);
d.hasDuration = false;
outputs.push_back(d);
m_outNoSalience = outputNumber++;
return outputs;
}
bool
YinVamp::initialise(size_t channels, size_t stepSize, size_t blockSize)
{
if (channels < getMinChannelCount() ||
channels > getMaxChannelCount()) return false;
/*
std::cerr << "YinVamp::initialise: channels = " << channels
<< ", stepSize = " << stepSize << ", blockSize = " << blockSize
<< std::endl;
*/
m_channels = channels;
m_stepSize = stepSize;
m_blockSize = blockSize;
reset();
return true;
}
void
YinVamp::reset()
{
m_yin.setThreshold(m_yinParameter);
m_yin.setFrameSize(m_blockSize);
/*
std::cerr << "YinVamp::reset: yin threshold set to " << (m_yinParameter)
<< ", blockSize = " << m_blockSize
<< std::endl;
*/
}
YinVamp::FeatureSet
YinVamp::process(const float *const *inputBuffers, RealTime timestamp)
{
timestamp = timestamp + Vamp::RealTime::frame2RealTime(m_blockSize/2, lrintf(m_inputSampleRate));
FeatureSet fs;
double *dInputBuffers = new double[m_blockSize];
for (size_t i = 0; i < m_blockSize; ++i) dInputBuffers[i] = inputBuffers[0][i];
Yin::YinOutput yo = m_yin.process(dInputBuffers);
// std::cerr << "f0 in YinVamp: " << yo.f0 << std::endl;
Feature f;
f.hasTimestamp = true;
f.timestamp = timestamp;
if (m_outputUnvoiced == 0.0f)
{
// std::cerr << "f0 in YinVamp: " << yo.f0 << std::endl;
if (yo.f0 > 0 && yo.f0 < m_fmax && yo.f0 > m_fmin) {
f.values.push_back(yo.f0);
fs[m_outNoF0].push_back(f);
}
} else if (m_outputUnvoiced == 1.0f)
{
if (fabs(yo.f0) < m_fmax && fabs(yo.f0) > m_fmin) {
f.values.push_back(fabs(yo.f0));
fs[m_outNoF0].push_back(f);
}
} else
{
if (fabs(yo.f0) < m_fmax && fabs(yo.f0) > m_fmin) {
f.values.push_back(yo.f0);
fs[m_outNoF0].push_back(f);
}
}
f.values.clear();
f.values.push_back(yo.rms);
fs[m_outNoRms].push_back(f);
f.values.clear();
for (size_t iBin = 0; iBin < yo.salience.size(); ++iBin)
{
f.values.push_back(yo.salience[iBin]);
}
fs[m_outNoSalience].push_back(f);
f.values.clear();
// f.values[0] = yo.periodicity;
f.values.push_back(yo.periodicity);
fs[m_outNoPeriodicity].push_back(f);
delete [] dInputBuffers;
return fs;
}
YinVamp::FeatureSet
YinVamp::getRemainingFeatures()
{
FeatureSet fs;
return fs;
}