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();

  }

}