Is it cheating to stratified sample the whole dataset based on a previous evaluation result?
By having seen the results on the held-out test set, learning something and applying that to the model, you have essentially added some bias to your model. So if we are being strict, yes... You cheated a little bit  ;) 

Without having a solid (meaning unbiased) validation metric, you cannot objectively compare the two results. You used prior information to make an improved modelling decision, which is great :)   However, that information flowed directly from your test data, which introduced the bias. 

It can be difficult when you have limited data, I know. You could maybe look into data augmentation to synthetically increase your dataset. In your case, adding random rotations and mirrored images could help a great deal!