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!7

cmodule LearnDogsVsCats > DynSingleFunctionWithPrintLog {
  /*switchable*/ transient File dir = userDir("dev/dogs-vs-cats/train");
  LPair<RGBImage, Rect> scaledImages;

  void doIt {
    // load scaled down test images
    
    LPair<File, Rect> data = gatherMarkedThingInImages(listImageFiles(dir), "eye");
    pnlStruct(data);
    if (empty(data)) ret with print("No marked images found in " + dir);
    
    int gridSize = 4;
    scaledImages = scaleDownTestImagesWithRect(gridSize, data);
    
    // make "random & vary" module
    
    RandomAndVary_Record<CloseToColorPredicate> rav = new(CloseToColorPredicate, 
      color := new RandomAndVary_RGBInt,
      maxDistance := new RandomAndVary_Double);
      
    // optimize
      
    CloseToColorPredicate e = pairA(racerOptimize(rav, func(CloseToColorPredicate e) -> double { scoreColorPredicateByRect(e, scaledImages) }, minRuntimeUnless100 := 10.0));
    
    print(e);
    showImage(renderColorPredicateOnTestImages(e, pairsA(scaledImages));
    
    // use centroid to detect rects
    
    for (Pair<RGBImage, Rect> p : scaledImages) {
      DoublePt pt = centroidForColorPredicate(e, p.a);
      if (pt == null) continue with print("No result");
      double dist = ptDistance(pt, centerOfRect(p.b));
      print(pt + " / " + centerOfRect(p.b));
      print("Error: " + percentRatio(dist, hypotenuse(p.a.getWidth(), p.a.getHeight())) + "%");
    }
  }
}