srecord noeq RecursiveImageSplitter(
  IProbabilisticScheduler scheduler,
  URecognizer recognizer) {
  
  replace Cell with URecognizer.Cell.
  
  Node root;
  int minPixelSize = 64; // don't dive below this (for the splitting)
  
  // actual class for leaves, base class for split nodes
  class Node > Pair<Node> { // funky type
    Cell cell;
    int color;
    
    // known error (distance to image). will go up as image is
    // scanned in more detail.
    double error;
    
    *() {}
    *(Cell *cell) {
      color = cell.intColor();
    }
    
    // availability - how important are we? (our percentage of total area)
    double availability() { ret recognizer.relativeArea(position); }
    
    double splitPossibility() {
      ret zeroOrOne(diameter(position) < minPixelSize);
    }
    
    Rect position() { ret cell.rectInImage(); }
    
    void scheduleSplits {
      var p = availability() * splitProbability();
      scheduler.at(p, r splitHorizontally);
      scheduler.at(p, r splitVertically);
    }
    
    void splitHorizontally {
      
    }
    
    void splitVertically { /* TODO */ }
  }

  class Split > Node {
    int splitDimension;
    int splitPoint;
  }

  run {
    // make single color root from top cell.
    // let the node schedule its possible splits.
    root = Node(recognizer.cell());
    root.scheduleSplits();
  }
}