Mercurial > hg > camir-aes2014

annotate core/magnatagatune/MTTMixedFeatureStober11Genre.m @ 0:e9a9cd732c1e tip

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
parents
children
rev   line source
wolffd@0 1 classdef MTTMixedFeatureStober11Genre < MTTAudioFeature & handle
wolffd@0 2 % ---
wolffd@0 3 %
wolffd@0 4 % The usual worklow for these features constist of three steps
wolffd@0 5 % 1. extract: extracts the basic single-file dependent features
wolffd@0 6 % 2. define_global_transform: calculates the global feature
wolffd@0 7 % transformation parameters
wolffd@0 8 % 3. finalise: applies the common transformations to a specific feature
wolffd@0 9 % ---
wolffd@0 10
wolffd@0 11 properties(Constant = true)
wolffd@0 12
wolffd@0 13 % svn hook
wolffd@0 14 my_revision = str2double(substr('$Rev$', 5, -1));
wolffd@0 15 end
wolffd@0 16
wolffd@0 17 properties
wolffd@0 18 % ---
wolffd@0 19 % Set default parameters
wolffd@0 20 % ---
wolffd@0 21 my_params = struct(...
wolffd@0 22 ... % ---
wolffd@0 23 ... % these are Stober11 parameters
wolffd@0 24 ... % ---
wolffd@0 25 'stob_lowaudio', 1, ...
wolffd@0 26 'stob_highaudio', 1, ... %
wolffd@0 27 'stob_tags', 1, ...
wolffd@0 28 'stob_norm', 1, ...
wolffd@0 29 ... % ---
wolffd@0 30 ... % following are GenreBasic parameters
wolffd@0 31 ... % ---
wolffd@0 32 'pct_genres', 1, ... % 1/100 percentile genre tags used
wolffd@0 33 'empty_genres', 1 ... % allow empty genres to persist
wolffd@0 34 );
wolffd@0 35 end
wolffd@0 36
wolffd@0 37 % ---
wolffd@0 38 % member functions
wolffd@0 39 % ---
wolffd@0 40 methods
wolffd@0 41
wolffd@0 42 % ---
wolffd@0 43 % constructor: pointer to feature in database
wolffd@0 44 % ---
wolffd@0 45 function feature = MTTMixedFeatureStober11Genre(varargin)
wolffd@0 46
wolffd@0 47 feature = feature@MTTAudioFeature(varargin{:});
wolffd@0 48 end
wolffd@0 49
wolffd@0 50 % ---
wolffd@0 51 % extract feature data by combining genre adn stob features
wolffd@0 52 % ---
wolffd@0 53 function data = extract(feature, clip)
wolffd@0 54
wolffd@0 55 % ---
wolffd@0 56 % get Basic Summary audio features. this includes possible
wolffd@0 57 % local normalisations
wolffd@0 58 % ---
wolffd@0 59 stob = clip.features('MTTMixedFeatureStober11',feature.my_params);
wolffd@0 60
wolffd@0 61 % ---
wolffd@0 62 % get genre tag features
wolffd@0 63 % ---
wolffd@0 64
wolffd@0 65 genrebasic = clip.genre_features_basic(feature.my_params);
wolffd@0 66
wolffd@0 67 % save to features data field
wolffd@0 68 data.stob = stob;
wolffd@0 69 data.tags = genrebasic;
wolffd@0 70
wolffd@0 71 % prepare field for final features
wolffd@0 72 data.final.vector = [];
wolffd@0 73 data.final.vector_info = struct();
wolffd@0 74 data.final.dim = 0;
wolffd@0 75
wolffd@0 76 % save info data
wolffd@0 77 data.info.type = 'MTTMixedFeatureStober11Genre';
wolffd@0 78 data.info.owner_id = clip.id;
wolffd@0 79 data.info.creatorrev = feature.my_revision;
wolffd@0 80
wolffd@0 81 % save parameters
wolffd@0 82 data.info.params = feature.my_params;
wolffd@0 83 end
wolffd@0 84
wolffd@0 85 function define_global_transform(features)
wolffd@0 86 % calculate and set normalization factors from the group of
wolffd@0 87 % input features. These features will be set for the full database
wolffd@0 88
wolffd@0 89 if numel(features) == 1
wolffd@0 90 error ('Insert feature array for this method');
wolffd@0 91 end
wolffd@0 92
wolffd@0 93 % ---
wolffd@0 94 % We collect all the relevant stob
wolffd@0 95 % features and get the transform on this basis.
wolffd@0 96 % ---
wolffd@0 97 for i = 1:numel(features)
wolffd@0 98 stob(i) = features(i).data.stob;
wolffd@0 99 end
wolffd@0 100
wolffd@0 101 % call the features own transsform function
wolffd@0 102 stob.define_global_transform();
wolffd@0 103
wolffd@0 104 % ---
wolffd@0 105 % We collect all the relevant genretag
wolffd@0 106 % features and get the transform on this basis.
wolffd@0 107 % ---
wolffd@0 108 for i = 1:numel(features)
wolffd@0 109 genrebasic(i) = features(i).data.tags;
wolffd@0 110 end
wolffd@0 111
wolffd@0 112 % call the features own transsform function
wolffd@0 113 genrebasic.define_global_transform();
wolffd@0 114
wolffd@0 115 % ---
wolffd@0 116 % set common feature values for mixed features
wolffd@0 117 % ---
wolffd@0 118 features(1).my_db.set_common([1]); %trivial common
wolffd@0 119 end
wolffd@0 120
wolffd@0 121
wolffd@0 122 function finalise(feature)
wolffd@0 123 % applies a final transformation and collects the
wolffd@0 124 % information of this feature within a single vector
wolffd@0 125 % see info for types in specific dimensions
wolffd@0 126
wolffd@0 127 for i = 1:numel(feature)
wolffd@0 128
wolffd@0 129 % check for neccesary parameters
wolffd@0 130 if isempty(feature(i).my_db.commondb)
wolffd@0 131
wolffd@0 132 error('Define the global transformation first');
wolffd@0 133 end
wolffd@0 134
wolffd@0 135 % ---
wolffd@0 136 % finalise audio feature and get vector
wolffd@0 137 % ---
wolffd@0 138 stob = feature(i).data.stob;
wolffd@0 139 stob.finalise();
wolffd@0 140
wolffd@0 141 % finalise tag features
wolffd@0 142 genrebasic = feature(i).data.tags;
wolffd@0 143 genrebasic.finalise;
wolffd@0 144
wolffd@0 145 % ---
wolffd@0 146 % final data assembly
wolffd@0 147 % ---
wolffd@0 148
wolffd@0 149 % concatenate vectors
wolffd@0 150 feature(i).data.final.vector = ...
wolffd@0 151 [stob.vector() ; genrebasic.vector()];
wolffd@0 152
wolffd@0 153 % add feature dimensions
wolffd@0 154 feature(i).data.final.dim = stob.dim + genrebasic.dim;
wolffd@0 155
wolffd@0 156 % concatenate labels
wolffd@0 157 feature(i).data.final.vector_info.labels = ...
wolffd@0 158 {stob.data.final.vector_info.labels{:}, ...
wolffd@0 159 genrebasic.data.final.vector_info.labels{:}};
wolffd@0 160 end
wolffd@0 161 end
wolffd@0 162
wolffd@0 163 % ---
wolffd@0 164 % destructor: do we really want to remove this
wolffd@0 165 % from the database? No, but
wolffd@0 166 % TODO: create marker for unused objects in db, and a cleanup
wolffd@0 167 % function
wolffd@0 168 % ---
wolffd@0 169 function delete(feature)
wolffd@0 170
wolffd@0 171 end
wolffd@0 172
wolffd@0 173 function visualise(feature)
wolffd@0 174 % ---
wolffd@0 175 % plots the different data types collected in this feature
wolffd@0 176 % ---
wolffd@0 177 for i = 1:numel(feature)
wolffd@0 178 clip = MTTClip(feature(i).owner_id());
wolffd@0 179 end
wolffd@0 180 end
wolffd@0 181 end
wolffd@0 182 end