Hi!

I've been playing around with this model locally following the instructions in the README and my results don't seem to be nearly as good as yours.. I'm following your instructions here #11 (comment) and then running the prepare.py in my fork

For instance even with different style prompts the model seems to generate very similar results for me
Real on left, Generated on right

IAM style 1

IAM style 2

and then secondly the CVL and the IAM models give very different results to each other. But also quite consistent results within the model itself for different styles

CVL style 1

CVL style2

Is there something stupid I'm missing or do I need to train it with these writers in the dataset to get better results? does the google drive contain the fully trained models that were used to generate the results in the paper?

Very cool project though - congrats!!