Training a CNN to convert ellipses into circles
Use your generated images to train an encoder-decoder that attempts to rebuild the input image. We'll call these pieces the input encoder and ellipse decoder. In parallel, train a second decoder that takes the input encoder (i.e. embedding representation) as input and attempts to rebuild the original circle image. The input encoder + circle decoder can then be used together for scoring out-of-sample observations.