summaryrefslogtreecommitdiff
path: root/libs/vamp-pyin/YinVamp.cpp
diff options
context:
space:
mode:
authorRobin Gareus <robin@gareus.org>2019-09-02 03:12:22 +0200
committerRobin Gareus <robin@gareus.org>2019-09-02 03:12:22 +0200
commit63994f3b820c8f0754ff59d0d09585405d87ae0e (patch)
tree4138d2f4b5d7e7c4ab0f371c08615b5d8fcc7538 /libs/vamp-pyin/YinVamp.cpp
parent1c8b6e1b4296b4fbabc258f9f94635390a319522 (diff)
Include vamp-pyin
In preparation for captainMorgan's pitch analysis script.
Diffstat (limited to 'libs/vamp-pyin/YinVamp.cpp')
-rw-r--r--libs/vamp-pyin/YinVamp.cpp367
1 files changed, 367 insertions, 0 deletions
diff --git a/libs/vamp-pyin/YinVamp.cpp b/libs/vamp-pyin/YinVamp.cpp
new file mode 100644
index 0000000000..bc1e010e26
--- /dev/null
+++ b/libs/vamp-pyin/YinVamp.cpp
@@ -0,0 +1,367 @@
+/* -*- 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;
+}