How do I use data generators in Keras?

How do I use data generators in Keras?

Data generators in Keras are used to efficiently load and preprocess data in batches. They are especially useful for large datasets.

Can you show me an example of how to create a data generator?

Sure! You can create a data generator using the ImageDataGenerator class. Here's a simple example:

from keras.preprocessing.image import ImageDataGenerator

generator = ImageDataGenerator(rescale=1./255)
train_generator = generator.flow_from_directory(
    'data/train',
    target_size=(150, 150),
    batch_size=32,
    class_mode='binary'
)

What are the benefits of using data generators?

Data generators help in reducing memory usage by loading data in batches, and they can also perform real-time data augmentation.

Can I use data generators for text data as well?

Yes, you can create custom data generators for text data by subclassing Sequence or using fit_generator with your own data loading logic.