Cross validation plus oversampling?
Adding to what Himanshu Rai said, you should be careful not to oversample before the StratifiedKFold, once you risk to put the same sample in both the training and testing folds check this, (where you took your image from) and that doesn't really evaluate your model's capacity to data that it never saw. What i did was to use StratifiedKFold, and then oversample or SMOTE (or whatever you want) all the training folds separately, by only looking at that fold's training data. Then use all those folds to validate your models.