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1 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
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2
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3 /*
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4 QM Vamp Plugin Set
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5
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6 Centre for Digital Music, Queen Mary, University of London.
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7 All rights reserved.
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8 */
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9
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10 #include "BarBeatTrack.h"
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11
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12 #include <dsp/onsets/DetectionFunction.h>
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13 #include <dsp/onsets/PeakPicking.h>
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14 #include <dsp/tempotracking/TempoTrackV2.h>
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15 #include <dsp/tempotracking/DownBeat.h>
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16 #include <maths/MathUtilities.h>
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17
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18 using std::string;
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19 using std::vector;
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20 using std::cerr;
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21 using std::endl;
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22
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23 #ifndef __GNUC__
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24 #include <alloca.h>
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25 #endif
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26
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27 float BarBeatTracker::m_stepSecs = 0.01161; // 512 samples at 44100
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28
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29 class BarBeatTrackerData
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30 {
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31 public:
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32 BarBeatTrackerData(float rate, const DFConfig &config) : dfConfig(config) {
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33 df = new DetectionFunction(config);
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34 // decimation factor aims at resampling to c. 3KHz; must be power of 2
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35 int factor = MathUtilities::nextPowerOfTwo(rate / 3000);
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36 // std::cerr << "BarBeatTrackerData: factor = " << factor << std::endl;
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37 downBeat = new DownBeat(rate, factor, config.stepSize);
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38 }
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39 ~BarBeatTrackerData() {
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40 delete df;
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41 delete downBeat;
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42 }
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43 void reset() {
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44 delete df;
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45 df = new DetectionFunction(dfConfig);
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46 dfOutput.clear();
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47 downBeat->resetAudioBuffer();
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48 origin = Vamp::RealTime::zeroTime;
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49 }
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50
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51 DFConfig dfConfig;
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52 DetectionFunction *df;
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53 DownBeat *downBeat;
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54 vector<double> dfOutput;
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55 Vamp::RealTime origin;
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56 };
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57
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58
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59 BarBeatTracker::BarBeatTracker(float inputSampleRate) :
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60 Vamp::Plugin(inputSampleRate),
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61 m_d(0),
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62 m_bpb(4)
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63 {
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64 }
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65
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66 BarBeatTracker::~BarBeatTracker()
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67 {
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68 delete m_d;
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69 }
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70
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71 string
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72 BarBeatTracker::getIdentifier() const
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73 {
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74 return "qm-barbeattracker";
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75 }
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76
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77 string
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78 BarBeatTracker::getName() const
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79 {
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80 return "Bar and Beat Tracker";
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81 }
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82
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83 string
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84 BarBeatTracker::getDescription() const
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85 {
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86 return "Estimate bar and beat locations";
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87 }
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88
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89 string
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90 BarBeatTracker::getMaker() const
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91 {
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92 return "Queen Mary, University of London";
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93 }
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94
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95 int
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96 BarBeatTracker::getPluginVersion() const
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97 {
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98 return 1;
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99 }
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100
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101 string
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102 BarBeatTracker::getCopyright() const
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103 {
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104 return "Plugin by Matthew Davies, Christian Landone and Chris Cannam. Copyright (c) 2006-2009 QMUL - All Rights Reserved";
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105 }
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106
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107 BarBeatTracker::ParameterList
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108 BarBeatTracker::getParameterDescriptors() const
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109 {
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110 ParameterList list;
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111
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112 ParameterDescriptor desc;
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113
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114 desc.identifier = "bpb";
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115 desc.name = "Beats per Bar";
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116 desc.description = "The number of beats in each bar";
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117 desc.minValue = 2;
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118 desc.maxValue = 16;
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119 desc.defaultValue = 4;
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120 desc.isQuantized = true;
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121 desc.quantizeStep = 1;
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122 list.push_back(desc);
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123
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124 return list;
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125 }
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126
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127 float
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128 BarBeatTracker::getParameter(std::string name) const
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129 {
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130 if (name == "bpb") return m_bpb;
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131 return 0.0;
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132 }
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133
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134 void
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135 BarBeatTracker::setParameter(std::string name, float value)
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136 {
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137 if (name == "bpb") m_bpb = lrintf(value);
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138 }
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139
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140 bool
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141 BarBeatTracker::initialise(size_t channels, size_t stepSize, size_t blockSize)
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142 {
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143 if (m_d) {
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144 delete m_d;
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145 m_d = 0;
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146 }
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147
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148 if (channels < getMinChannelCount() ||
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149 channels > getMaxChannelCount()) {
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150 std::cerr << "BarBeatTracker::initialise: Unsupported channel count: "
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151 << channels << std::endl;
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152 return false;
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153 }
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154
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155 if (stepSize != getPreferredStepSize()) {
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156 std::cerr << "ERROR: BarBeatTracker::initialise: Unsupported step size for this sample rate: "
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157 << stepSize << " (wanted " << (getPreferredStepSize()) << ")" << std::endl;
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158 return false;
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159 }
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160
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161 if (blockSize != getPreferredBlockSize()) {
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162 std::cerr << "WARNING: BarBeatTracker::initialise: Sub-optimal block size for this sample rate: "
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163 << blockSize << " (wanted " << getPreferredBlockSize() << ")" << std::endl;
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164 // return false;
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165 }
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166
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167 DFConfig dfConfig;
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168 dfConfig.DFType = DF_COMPLEXSD;
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169 dfConfig.stepSize = stepSize;
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170 dfConfig.frameLength = blockSize;
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171 dfConfig.dbRise = 3;
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172 dfConfig.adaptiveWhitening = false;
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173 dfConfig.whiteningRelaxCoeff = -1;
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174 dfConfig.whiteningFloor = -1;
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175
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176 m_d = new BarBeatTrackerData(m_inputSampleRate, dfConfig);
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177 m_d->downBeat->setBeatsPerBar(m_bpb);
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178 return true;
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179 }
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180
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181 void
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182 BarBeatTracker::reset()
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183 {
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184 if (m_d) m_d->reset();
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185 }
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186
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187 size_t
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188 BarBeatTracker::getPreferredStepSize() const
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189 {
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190 size_t step = size_t(m_inputSampleRate * m_stepSecs + 0.0001);
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191 if (step < 1) step = 1;
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192 // std::cerr << "BarBeatTracker::getPreferredStepSize: input sample rate is " << m_inputSampleRate << ", step size is " << step << std::endl;
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193 return step;
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194 }
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195
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196 size_t
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197 BarBeatTracker::getPreferredBlockSize() const
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198 {
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199 size_t theoretical = getPreferredStepSize() * 2;
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200
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201 // I think this is not necessarily going to be a power of two, and
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202 // the host might have a problem with that, but I'm not sure we
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203 // can do much about it here
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204 return theoretical;
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205 }
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206
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207 BarBeatTracker::OutputList
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208 BarBeatTracker::getOutputDescriptors() const
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209 {
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210 OutputList list;
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211
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212 OutputDescriptor beat;
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213 beat.identifier = "beats";
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214 beat.name = "Beats";
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215 beat.description = "Beat locations labelled with metrical position";
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216 beat.unit = "";
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217 beat.hasFixedBinCount = true;
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218 beat.binCount = 0;
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219 beat.sampleType = OutputDescriptor::VariableSampleRate;
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220 beat.sampleRate = 1.0 / m_stepSecs;
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221
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222 OutputDescriptor bars;
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223 bars.identifier = "bars";
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224 bars.name = "Bars";
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225 bars.description = "Bar locations";
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226 bars.unit = "";
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227 bars.hasFixedBinCount = true;
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228 bars.binCount = 0;
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229 bars.sampleType = OutputDescriptor::VariableSampleRate;
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230 bars.sampleRate = 1.0 / m_stepSecs;
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231
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232 OutputDescriptor beatcounts;
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233 beatcounts.identifier = "beatcounts";
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234 beatcounts.name = "Beat Count";
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235 beatcounts.description = "Beat counter function";
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236 beatcounts.unit = "";
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237 beatcounts.hasFixedBinCount = true;
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238 beatcounts.binCount = 1;
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239 beatcounts.sampleType = OutputDescriptor::VariableSampleRate;
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240 beatcounts.sampleRate = 1.0 / m_stepSecs;
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241
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242 OutputDescriptor beatsd;
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243 beatsd.identifier = "beatsd";
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244 beatsd.name = "Beat Spectral Difference";
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245 beatsd.description = "Beat spectral difference function used for bar-line detection";
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246 beatsd.unit = "";
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247 beatsd.hasFixedBinCount = true;
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248 beatsd.binCount = 1;
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249 beatsd.sampleType = OutputDescriptor::VariableSampleRate;
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250 beatsd.sampleRate = 1.0 / m_stepSecs;
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251
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252 list.push_back(beat);
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253 list.push_back(bars);
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254 list.push_back(beatcounts);
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255 list.push_back(beatsd);
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256
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257 return list;
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258 }
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259
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260 BarBeatTracker::FeatureSet
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261 BarBeatTracker::process(const float *const *inputBuffers,
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262 Vamp::RealTime timestamp)
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263 {
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264 if (!m_d) {
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265 cerr << "ERROR: BarBeatTracker::process: "
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266 << "BarBeatTracker has not been initialised"
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267 << endl;
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268 return FeatureSet();
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269 }
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270
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271 // We use time domain input, because DownBeat requires it -- so we
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272 // use the time-domain version of DetectionFunction::process which
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273 // does its own FFT. It requires doubles as input, so we need to
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274 // make a temporary copy
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275
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276 // We only support a single input channel
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277
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278 const int fl = m_d->dfConfig.frameLength;
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279 #ifndef __GNUC__
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280 double *dfinput = (double *)alloca(fl * sizeof(double));
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281 #else
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282 double dfinput[fl];
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283 #endif
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284 for (int i = 0; i < fl; ++i) dfinput[i] = inputBuffers[0][i];
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285
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286 double output = m_d->df->process(dfinput);
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287
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288 if (m_d->dfOutput.empty()) m_d->origin = timestamp;
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289
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290 // std::cerr << "df[" << m_d->dfOutput.size() << "] is " << output << std::endl;
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291 m_d->dfOutput.push_back(output);
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292
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293 // Downsample and store the incoming audio block.
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294 // We have an overlap on the incoming audio stream (step size is
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295 // half block size) -- this function is configured to take only a
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296 // step size's worth, so effectively ignoring the overlap. Note
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297 // however that this means we omit the last blocksize - stepsize
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298 // samples completely for the purposes of barline detection
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299 // (hopefully not a problem)
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300 m_d->downBeat->pushAudioBlock(inputBuffers[0]);
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301
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302 return FeatureSet();
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303 }
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304
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305 BarBeatTracker::FeatureSet
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306 BarBeatTracker::getRemainingFeatures()
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307 {
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308 if (!m_d) {
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309 cerr << "ERROR: BarBeatTracker::getRemainingFeatures: "
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310 << "BarBeatTracker has not been initialised"
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311 << endl;
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312 return FeatureSet();
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313 }
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314
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315 return barBeatTrack();
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316 }
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317
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318 BarBeatTracker::FeatureSet
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319 BarBeatTracker::barBeatTrack()
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320 {
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321 vector<double> df;
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322 vector<double> beatPeriod;
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323 vector<double> tempi;
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324
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325 for (size_t i = 2; i < m_d->dfOutput.size(); ++i) { // discard first two elts
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326 df.push_back(m_d->dfOutput[i]);
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327 beatPeriod.push_back(0.0);
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328 }
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329 if (df.empty()) return FeatureSet();
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330
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331 TempoTrackV2 tt(m_inputSampleRate, m_d->dfConfig.stepSize);
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332 tt.calculateBeatPeriod(df, beatPeriod, tempi);
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333
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334 vector<double> beats;
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335 tt.calculateBeats(df, beatPeriod, beats);
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336
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337 vector<int> downbeats;
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338 size_t downLength = 0;
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339 const float *downsampled = m_d->downBeat->getBufferedAudio(downLength);
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340 m_d->downBeat->findDownBeats(downsampled, downLength, beats, downbeats);
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341
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342 vector<double> beatsd;
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343 m_d->downBeat->getBeatSD(beatsd);
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344
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345 // std::cerr << "BarBeatTracker: found downbeats at: ";
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346 // for (int i = 0; i < downbeats.size(); ++i) std::cerr << downbeats[i] << " " << std::endl;
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347
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348 FeatureSet returnFeatures;
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349
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350 char label[20];
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351
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352 int dbi = 0;
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353 int beat = 0;
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354 int bar = 0;
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355
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356 if (!downbeats.empty()) {
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357 // get the right number for the first beat; this will be
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358 // incremented before use (at top of the following loop)
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359 int firstDown = downbeats[0];
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360 beat = m_bpb - firstDown - 1;
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361 if (beat == m_bpb) beat = 0;
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362 }
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363
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364 for (size_t i = 0; i < beats.size(); ++i) {
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365
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366 size_t frame = beats[i] * m_d->dfConfig.stepSize;
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367
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368 if (dbi < downbeats.size() && i == downbeats[dbi]) {
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369 beat = 0;
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370 ++bar;
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371 ++dbi;
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372 } else {
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373 ++beat;
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374 }
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375
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376 // outputs are:
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377 //
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378 // 0 -> beats
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379 // 1 -> bars
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380 // 2 -> beat counter function
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381
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382 Feature feature;
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383 feature.hasTimestamp = true;
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384 feature.timestamp = m_d->origin + Vamp::RealTime::frame2RealTime
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385 (frame, lrintf(m_inputSampleRate));
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386
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387 sprintf(label, "%d", beat + 1);
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388 feature.label = label;
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389 returnFeatures[0].push_back(feature); // labelled beats
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390
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c@89
|
391 feature.values.push_back(beat + 1);
|
c@89
|
392 returnFeatures[2].push_back(feature); // beat function
|
c@89
|
393
|
c@90
|
394 if (i > 0 && i <= beatsd.size()) {
|
c@90
|
395 feature.values.clear();
|
c@90
|
396 feature.values.push_back(beatsd[i-1]);
|
c@90
|
397 feature.label = "";
|
c@90
|
398 returnFeatures[3].push_back(feature); // beat spectral difference
|
c@90
|
399 }
|
c@90
|
400
|
c@89
|
401 if (beat == 0) {
|
c@89
|
402 feature.values.clear();
|
c@89
|
403 sprintf(label, "%d", bar);
|
c@89
|
404 feature.label = label;
|
c@89
|
405 returnFeatures[1].push_back(feature); // bars
|
c@89
|
406 }
|
c@89
|
407 }
|
c@89
|
408
|
c@89
|
409 return returnFeatures;
|
c@89
|
410 }
|
c@89
|
411
|