I am using automl from google using a custom dataset. The dataset consists of images collected by me. However, manually labelling the image take some time, so I would like to enlarge the dataset by image augmentation, such as rotation and blurring. Does automl perform augmentation behind the screen automatically?
AutoML does few types of data augmentation. This is implementation detail and may change in the future without notice, basic augmentations that are used are:
- random resizes / crops
- random flip left right
- random color and brightness distortions
- more may be used / added in the future
If doing data augmentation on your side please follow best practices:
- if you augment image - please put all augmentations of the same image in the same part of the dataset (TRAIN, VALIDATION, TEST) - otherwise the model can overfit without noticing (if almost the same image is in TRAIN and VALIDATION set)
- do transformations that are meaningful in your context - for example rotations - if in typical use-case you don't get rotated images or objects that are rotated - then training model to detect rotated images may not help your application (for example if you never see people who are upside down in your real application - than training with people who are upside down may not benefit your end model).