Best way to implement 10-fold cross validation for CNN model
In my point of view, it should be Option-I
 Primary logic is to test your Model on unseen data.
Reason for that is,
When you executed your K-Fold and let's say got a score ~87% and then you tweaked your Hyperparameters.
In this way, we actually leak the test data(K-Fold test set) information to the learning process, and eventually, the process will overfit to the test data too if this hit-try happens multiple times.
So, the Option-I score should be closer to the score on future new data.