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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 Vamp
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5
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6 An API for audio analysis and feature extraction plugins.
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7
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8 Centre for Digital Music, Queen Mary, University of London.
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9 Copyright 2006 Chris Cannam.
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10
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11 Permission is hereby granted, free of charge, to any person
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12 obtaining a copy of this software and associated documentation
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13 files (the "Software"), to deal in the Software without
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14 restriction, including without limitation the rights to use, copy,
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15 modify, merge, publish, distribute, sublicense, and/or sell copies
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16 of the Software, and to permit persons to whom the Software is
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17 furnished to do so, subject to the following conditions:
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18
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19 The above copyright notice and this permission notice shall be
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20 included in all copies or substantial portions of the Software.
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21
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22 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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23 EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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24 MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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25 NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
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26 ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
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27 CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
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28 WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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29
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30 Except as contained in this notice, the names of the Centre for
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31 Digital Music; Queen Mary, University of London; and Chris Cannam
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32 shall not be used in advertising or otherwise to promote the sale,
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33 use or other dealings in this Software without prior written
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34 authorization.
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35 */
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36
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37 #include "SpectralCentroid.h"
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38
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39 using std::string;
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40 using std::vector;
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41 using std::cerr;
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42 using std::endl;
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43
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44 #include <math.h>
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45
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46 #ifdef WIN32
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47 #define isnan(x) false
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48 #define isinf(x) false
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49 #endif
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50
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51 SpectralCentroid::SpectralCentroid(float inputSampleRate) :
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52 Plugin(inputSampleRate),
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53 m_stepSize(0),
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54 m_blockSize(0)
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55 {
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56 }
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57
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58 SpectralCentroid::~SpectralCentroid()
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59 {
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60 }
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61
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62 string
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63 SpectralCentroid::getIdentifier() const
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64 {
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65 return "spectralcentroid";
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66 }
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67
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68 string
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69 SpectralCentroid::getName() const
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70 {
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71 return "Spectral Centroid";
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72 }
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73
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74 string
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75 SpectralCentroid::getDescription() const
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76 {
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77 return "Calculate the centroid frequency of the spectrum of the input signal";
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78 }
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79
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80 string
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81 SpectralCentroid::getMaker() const
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82 {
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83 return "Vamp SDK Example Plugins";
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84 }
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85
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86 int
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87 SpectralCentroid::getPluginVersion() const
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88 {
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89 return 2;
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90 }
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91
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92 string
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93 SpectralCentroid::getCopyright() const
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94 {
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95 return "Freely redistributable (BSD license)";
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96 }
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97
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98 bool
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99 SpectralCentroid::initialise(size_t channels, size_t stepSize, size_t blockSize)
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100 {
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101 if (channels < getMinChannelCount() ||
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102 channels > getMaxChannelCount()) return false;
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103
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104 m_stepSize = stepSize;
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105 m_blockSize = blockSize;
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106
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107 return true;
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108 }
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109
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110 void
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111 SpectralCentroid::reset()
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112 {
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113 }
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114
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115 SpectralCentroid::OutputList
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116 SpectralCentroid::getOutputDescriptors() const
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117 {
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118 OutputList list;
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119
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120 OutputDescriptor d;
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121 d.identifier = "logcentroid";
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122 d.name = "Log Frequency Centroid";
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123 d.description = "Centroid of the log weighted frequency spectrum";
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124 d.unit = "Hz";
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125 d.hasFixedBinCount = true;
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126 d.binCount = 1;
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127 d.hasKnownExtents = false;
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128 d.isQuantized = false;
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129 d.sampleType = OutputDescriptor::OneSamplePerStep;
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130 list.push_back(d);
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131
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132 d.identifier = "linearcentroid";
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133 d.name = "Linear Frequency Centroid";
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134 d.description = "Centroid of the linear frequency spectrum";
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135 list.push_back(d);
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136
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137 return list;
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138 }
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139
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140 //static int scount = 0;
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141
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142 SpectralCentroid::FeatureSet
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143 SpectralCentroid::process(const float *const *inputBuffers, Vamp::RealTime timestamp)
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144 {
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145 if (m_stepSize == 0) {
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146 cerr << "ERROR: SpectralCentroid::process: "
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147 << "SpectralCentroid has not been initialised"
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148 << endl;
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149 return FeatureSet();
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150 }
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151
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152 // std::cerr << "SpectralCentroid::process: count = " << scount++ << ", timestamp = " << timestamp << ", total power = ";
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153
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154 double numLin = 0.0, numLog = 0.0, denom = 0.0;
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155
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156 for (size_t i = 1; i <= m_blockSize/2; ++i) {
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157 double freq = (double(i) * m_inputSampleRate) / m_blockSize;
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158 double real = inputBuffers[0][i*2];
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159 double imag = inputBuffers[0][i*2 + 1];
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160 double power = sqrt(real * real + imag * imag) / (m_blockSize/2);
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161 numLin += freq * power;
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162 numLog += log10f(freq) * power;
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163 denom += power;
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164 }
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165
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166 // std::cerr << denom << std::endl;
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167
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168 FeatureSet returnFeatures;
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169
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170 if (denom != 0.0) {
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171 float centroidLin = float(numLin / denom);
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172 float centroidLog = powf(10, float(numLog / denom));
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173
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174 Feature feature;
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175 feature.hasTimestamp = false;
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176 if (!isnan(centroidLog) && !isinf(centroidLog)) {
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177 feature.values.push_back(centroidLog);
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178 }
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179 returnFeatures[0].push_back(feature);
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180
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181 feature.values.clear();
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182 if (!isnan(centroidLin) && !isinf(centroidLin)) {
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183 feature.values.push_back(centroidLin);
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184 }
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185 returnFeatures[1].push_back(feature);
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186 }
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187
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188 return returnFeatures;
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189 }
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190
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191 SpectralCentroid::FeatureSet
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192 SpectralCentroid::getRemainingFeatures()
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193 {
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194 return FeatureSet();
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195 }
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196
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