Source Code for Module timeside.analyzer.yaafe

  1  # -*- coding: utf-8 -*- 
  2  # 
  3  # Copyright (c) 2013 Thomas Fillon <thomas@parisson.com> 
  4   
  5  # This file is part of TimeSide. 
  6   
  7  # TimeSide is free software: you can redistribute it and/or modify 
  8  # it under the terms of the GNU General Public License as published by 
  9  # the Free Software Foundation, either version 2 of the License, or 
 10  # (at your option) any later version. 
 11   
 12  # TimeSide is distributed in the hope that it will be useful, 
 13  # but WITHOUT ANY WARRANTY; without even the implied warranty of 
 14  # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the 
 15  # GNU General Public License for more details. 
 16   
 17  # You should have received a copy of the GNU General Public License 
 18  # along with TimeSide.  If not, see <http://www.gnu.org/licenses/>. 
 19   
 20  # Author : Thomas Fillon <thomas@parisson.com> 
 21  """ 
 22  Module Yaafe Analyzer 
 23  Created on Thu Jun 13 16:05:02 2013 
 24   
 25  @author: Thomas Fillon 
 26  """ 
 27  from timeside.core import implements, interfacedoc 
 28  from timeside.analyzer.core import Analyzer 
 29  from timeside.api import IAnalyzer 
 30  from yaafelib import * 
 31  import numpy 
 32   
 33   
 34 -class Yaafe(Analyzer): 
 35      implements(IAnalyzer) 
 36   
 37 -    def __init__(self, yaafeSpecification=None): 
 38          super(Yaafe,self).__init__() 
 39   
 40          # Check arguments 
 41          if yaafeSpecification is None: 
 42              yaafeSpecification = FeaturePlan(sample_rate=32000) 
 43              # add feature definitions manually 
 44              yaafeSpecification.addFeature('mfcc: MFCC blockSize=512 stepSize=256') 
 45   
 46          if isinstance(yaafeSpecification, DataFlow): 
 47              self.dataFlow = yaafeSpecification 
 48          elif isinstance(yaafeSpecification, FeaturePlan): 
 49              self.featurePlan = yaafeSpecification 
 50              self.dataFlow = self.featurePlan.getDataFlow() 
 51          else: 
 52              raise TypeError("'%s' Type must be either '%s' or '%s'" % 
 53                              (str(yaafeSpecification), 
 54                               str(DataFlow), 
 55                               str(FeaturePlan))) 
 56          self.yaafe_engine = None 
 57   
 58   
 59      @interfacedoc 
 60 -    def setup(self, channels=None, samplerate=None, 
 61                blocksize=None, totalframes=None): 
 62          super(Yaafe, self).setup(channels, samplerate, blocksize, totalframes) 
 63          # Configure a YAAFE engine 
 64          self.yaafe_engine = Engine() 
 65          self.yaafe_engine.load(self.dataFlow) 
 66          self.yaafe_engine.reset() 
 67          self.input_samplerate = samplerate 
 68          self.input_blocksize = blocksize 
 69   
 70      @staticmethod 
 71      @interfacedoc 
 72 -    def id(): 
 73          return "yaafe" 
 74   
 75      @staticmethod 
 76      @interfacedoc 
 77 -    def name(): 
 78          return "Yaafe Descriptor" 
 79   
 80      @staticmethod 
 81      @interfacedoc 
 82 -    def unit(): 
 83          return '' 
 84   
 85 -    def process(self, frames, eod=False): 
 86          # do process things... 
 87          # Downmixing to mono and convert to float64 for compatibility with 
 88          # Yaafe 
 89          yaafe_frames = frames.sum( 
 90              axis=-1, dtype=numpy.float64) / frames.shape[-1] 
 91          # Reshape for compatibility with Yaafe input format 
 92          yaafe_frames.shape = (1, yaafe_frames.shape[0]) 
 93          # write audio array on 'audio' input 
 94          self.yaafe_engine.writeInput('audio', yaafe_frames) 
 95          # process available data 
 96          self.yaafe_engine.process() 
 97          if eod: 
 98              # flush yaafe engine to process remaining data 
 99              self.yaafe_engine.flush() 
100   
101          return frames, eod 
102   
103 -    def post_process(self): 
104          # Get feature extraction results from yaafe 
105          featNames = self.yaafe_engine.getOutputs().keys() 
106          if len(featNames) == 0: 
107              raise KeyError('Yaafe engine did not return any feature') 
108          for featName in featNames: 
109   
110              result = self.new_result(data_mode='value', time_mode='framewise') 
111              result.id_metadata.id += '.' + featName 
112              result.id_metadata.name += ' ' + featName 
113              # Read Yaafe Results 
114              result.data_object.value = self.yaafe_engine.readOutput(featName) 
115              # Store results in Container 
116              if len(result.data_object.value): 
117                  self.process_pipe.results.add(result) 
118