!7

cmodule PerceptronVAD1 > DynImageSurface {
  switchable int w = 5;
  switchable int h = 10;
  switchable int nMaxExamples = 2000;
  switchable S teacherModule; // an accurate VAD that we learn from
  new Perceptron perceptron;
  transient double[] parameters;
  transient ReliableSingleThread rstTrain = dm_rst(this, r train);
  
  afterVisualize {
    imageSurface_pixelated(imageSurface);
    setZoom(20);
  }
    
  start {
    dm_requireLiveAudioFFT();
    dm_audioInput_enableSendOutClonedData();

    dm_vmBus_onMessage_q newAudioFrequencyImageFromData(voidfunc(virtual BWImage _img, short[] fromData) {
      BWImage img = cast quickImport(_img);
      BWIntegralImage ii = new(img);
      BWImage bw = scaleDownUsingIntegralImageBW(ii, w, h);
      setImage(bw);
      parameters = concatDoubleArrays(
        bwImage_averageBrightnessPerRow(bw),
        bwImage_standardDeviationPerRow(bw));
        
      if (teacherModule != null) {
        Bool va = cast dm_call(teacherModule, 'hasVoiceActivity, fromData);
        // TODO: wait a bit while va == null
        print("va: " + va);
        if (va != null && l(perceptron.examples) < nMaxExamples) {
          perceptron.addExample(parameters, va);
          print("Have " + nExamples(perceptron.examples));
        }
        rstTrain.trigger();
      }
   });
  }
  
  void train enter {
    for ping (Double error : perceptron.trainingIterator())
      if (error != null) {
        perceptron.printWithWeights();
        change();
      }
  }
}