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1 classdef MTTMixedFeatureGenreRandom < MTTAudioFeature & handle
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2 % ---
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3 %
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4 % The usual worklow for these features constist of three steps
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5 % 1. extract: extracts the basic single-file dependent features
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6 % 2. define_global_transform: calculates the global feature
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7 % transformation parameters
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8 % 3. finalise: applies the common transformations to a specific feature
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9 % ---
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10
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11 properties(Constant = true)
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12
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13 % svn hook
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14 my_revision = str2double(substr('$Rev: 455 $', 5, -1));
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15 end
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16
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17 properties
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18 % ---
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19 % Set default parameters
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20 % ---
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21 my_params = MTTAudioFeature.inherited_params(...
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22 'MTTTagFeatureGenreBasic', ...
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23 ... % ---
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24 ... % following are Random parameters
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25 ... % ---
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26 'nrandoms', 100 ...
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27 );
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28 end
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29
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30 % ---
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31 % member functions
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32 % ---
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33 methods
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34
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35 % ---
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36 % constructor: pointer to feature in database
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37 % ---
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38 function feature = MTTMixedFeatureGenreRandom(varargin)
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39
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40 feature = feature@MTTAudioFeature(varargin{:});
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41 end
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42
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43 % ---
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44 % extract feature data by combining genre adn basicsm features
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45 % ---
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46 function data = extract(feature, clip)
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47
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48 % ---
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49 % get MTTMixedFeatureGenreBasicSm this includes possible
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50 % local normalisations
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51 % ---
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52 data.tags = clip.features('MTTTagFeatureGenreBasic',feature.my_params);
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53
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54 % ---
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55 % get genre tag features
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56 % ---
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57
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58 data.random = clip.features('MTTRandomFeature',feature.my_params);
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59
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60
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61 % prepare field for final features
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62 data.final.vector = [];
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63 data.final.vector_info = struct();
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64 data.final.dim = 0;
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65
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66 % save info data
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67 data.info.type = class(feature);
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68 data.info.owner_id = clip.id;
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69 data.info.creatorrev = feature.my_revision;
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70
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71 % save parameters
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72 data.info.params = feature.my_params;
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73 end
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74
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75 function define_global_transform(features)
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76 % calculate and set normalization factors from the group of
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77 % input features. These features will be set for the full database
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78
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79 if numel(features) == 1
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80 error ('Insert feature array for this method');
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81 end
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82
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83 % ---
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84 % We collect all the relevant tag
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85 % features and get the transform on this basis.
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86 % ---
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87 for i = 1:numel(features)
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88 tags(i) = features(i).data.tags;
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89 end
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90
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91 % call the features own transsform function
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92 tags.define_global_transform();
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93
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94 % ---
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95 % Random features have no global transform
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96 % ---
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97
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98 % ---
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99 % set common feature values for mixed features
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100 % ---
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101 features(1).my_db.set_common([1]); %trivial common
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102 end
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103
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104
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105 function finalise(feature)
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106 % applies a final transformation and collects the
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107 % information of this feature within a single vector
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108 % see info for types in specific dimensions
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109
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110 for i = 1:numel(feature)
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111
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112 % check for neccesary parameters
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113 if isempty(feature(i).my_db.commondb)
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114
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115 error('Define the global transformation first');
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116 end
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117
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118 % ---
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119 % final data assembly
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120 % ---
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121 % concatenate vectors
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122 feature(i).data.final.vector = ...
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123 [feature(i).data.tags.vector() ;...
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124 feature(i).data.random.vector()];
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125
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126 % add up feature dimensions
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127 feature(i).data.final.dim = feature(i).data.tags.dim...
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128 + feature(i).data.random.dim;
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129
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130 % concatenate labels
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131 lbl1 = feature(i).data.tags.labels();
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132 lbl2 = feature(i).data.random.labels();
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133 feature(i).data.final.vector_info.labels = ...
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134 {lbl1{:}, lbl2{:}};
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135 end
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136 end
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137
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138 % ---
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139 % destructor: do we really want to remove this
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140 % from the database? No, but
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141 % TODO: create marker for unused objects in db, and a cleanup
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142 % function
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143 % ---
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144 function delete(feature)
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145
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146 end
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147 end
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148 end |
