CODEWITHSUNDEEP
tensorflowdeep-learningkeras
Wild Ox
Wild Ox

Reputation: 1

Split Image dataset for keras model.fit_generator

I have single directory, dataset, which contains sub-folders(labels/classes) of images.
Here's the Sub-folders of animal images in dataset:

I want to split the dataset into train and test set for model.fit_generotar().

How can I do that?

Upvotes: -1

Views: 949

Answers (1)

Jakub Bartczuk
Jakub Bartczuk

Reputation: 2378

Use glob to get file paths iterator.

You can then use scikit-learn's train-test split to get train and test data paths (use stratify parameter to get the same class distribution in test/train as in whole dataset).

The result would be two lists of paths, which you can write to appropriate test/train folders, and then you can apply generator's flow_from_directory method.

EDIT:

The second way would be to not use flow_from_directory, but load train/test sets (either load everything and use scikit-learn method or use what I've described before) and then use generator's flow method.

Also note that you might not want to use generators for test/validation data, since it would make comparing accuracy hard, since you won't have a fixed valid/test set.

Upvotes: 1

Related Questions