Simple test time augmentation (TTA) for keras python library.
So far the wrapper flips the images horizontally and vertically and averages the predictions of all flipped images.
The intuition behind this is that even if the test image is not too easy to make a prediction, the transformations change it such that the model has higher chances of capturing the target shape and predicting accordingly.
tta_model = TTA_ModelWrapper(model)
predictions = tta_model.predict(X_test)