Super cool. I've always been a big fan of generating synthetic training data. As long as you can degrade/distort the data to match real world conditions, you can have your cake and eat it to: accurate inputs with perfect automated labels.
At my last job, we read the contents of receipts and parsed them for purchase information. I was really interested in working there, so I built a docker-based CGI receipt-generator[0] that mimicked real-world conditions of a receipt captured with a camera phone. After getting the job, I expanded it to provide the perfect labelled data of bounding box and character[1]. I then used this data to train custom TensorFlow models.