sclass MultiLevelRecognizer3
  // how big do we think the prototype is in the whole image
  // (percentage by height)
  L<Double> assumedPrototypeHeightPercentages = ll(70.0, 70.0/sqrt(2), 35.0, 35.0/sqrt(2), 17.0);
  
  // widths to scale camera image to
  transient L<Int> widths = ll(32, 64, 128);
  
  BWIntegralImage integralInputImage;
  new Map<Int, BWIntegralImage> prototypeImages; // key = height
  new Map<Int, IBWIntegralImage> integralImages; // key = width
  new Map<Int, ByPrototype> byPrototypeMap;
  
  class ByPrototype {
  }
  
  // constructors, addPrototype functions
  
  *() {}
  *(File imgFile) {
    integralInputImage = loadBWIntegralImage(imgFile);
  }

  void addPrototype(BufferedImage img) {
    prototypeImages.add(bwIntegralImage(img));
  }

  void addPrototype(File imgFile) {
    addPrototype(loadImage2(imgFile));
  }
  
  void addPrototypes(Iterable l) {
    fOr (O o : l) call(this, 'addPrototype, img);
  }
  
  void search(assumedPrototypeHeightPercentage, IVF1<Rect> onGuess) {
    img16 = scaleImageToWidth(inputImage, 16);
    int assumedPrototypeHeight16 = calculate(percentage, img16);
    prototype16 = resizeImageToHeight(prototype, assumedPrototypeHeight16);
    img32 = scaleImageToWidth(inputImage, 32);
    etc.
    
    double minSimilarity = 0.5;
    L<Scored<Rect>> found16 = bwRawImageSearch(img16, prototype16, minSimilarity);
    sortScoredDesc_inPlace(found16);
    candidates16 = getVars(takeFirst(5, found16));
    for (Rect candidate16 : candidates16) {
      candidate32 = scaleRect(candidate16, 2);
    }
  }
}