I'd be keen on doing or learning about a mapping from spatial tree to 2d raster and have the inverse (dual) mapped back to a spatial tree via a deep learning mo

I'd be keen on doing or learning about a mapping from spatial tree to 2d raster and have the inverse (dual) mapped back to a spatial tree via a deep learning model, though I'm not sure how you'd represent the shapes and transform matrices. Maybe some sort of matrix stream like char2vec? A nice property of such an experiment, you could generate your training data via permutations of the spatial trees. You may have to accept multiple valid answers, since one could correctly say, the ball is to the left of the car, or the car is to the right of the ball.