sclass CheesyRecognizer {
  BWIntegralImage inputImage;
  
  new L<Prototype> prototypes;
  new Map<Int, ScaledInputImage> scaledInputImages; // key = width
  
  class Prototype {
    BWIntegralImage image;
    new Map<Int, ScaledPrototype> scaledPrototypes; // key = width
    
    ScaledPrototype scaledPrototype(int width) {
      ret mapGetOrCreate(scaledPrototypes, width,
        () -> new ScaledPrototype(this, scaleDownUsingIntegralImageBW(image, width)));
    }
  }
  
  class ScaledInputImage {
    BWImage image;
    
    *(BWImage *image) {}
  }
  
  class ScaledPrototype {
    Prototype prototype;
    BWImage image;
    
    *(Prototype *prototype, BWImage *image) {}
  }
  
  *(BWImage inputImage) { this.inputImage = bwIntegralImage(inputImage); }
  *(BufferedImage inputImage) { this(BWImage(inputImage)); }
  
  void fullScan(ScaledInputImage img, ScaledPrototype proto, float minSimilarity, IVF2<Rect, Double> onFound) {
    bwImageSearch_onFound(img.image, proto.image, minSimilarity, onFound);
  }

  // compare scaled prototype to scaled image at some location
  Pair<Rect, Double> singleCheck(ScaledInputImage img, ScaledPrototype prototype, int x, int y, float minSimilarity) {
    BWImage proto = prototype.image, image = img.image;
    int wp = proto.getWidth(), hp = proto.getHeight();

    float maxError = (1f-minSimilarity)*wp*hp;
    float diff = bwImageSectionsSimilarity(image, proto, x, y, maxError);
    ret diff > maxError ? null : pair(new Rect(x, y, wp, hp), (1-(double) diff)/(wp*hp));
  }
  
  ScaledInputImage scaledInputImage(int width) {
    ret mapGetOrCreate(scaledInputImages, width,
      () -> new ScaledInputImage(scaleDownUsingIntegralImageBW(inputImage, width)));
  }
}