How to Normalize, Center, and Standardize Image Pixels in Keras
Last Updated on July 5, 2019
The pixel values in images must be scaled prior to providing the images as input to a deep learning neural network model during the training or evaluation of the model.
Traditionally, the images would have to be scaled prior to the development of the model and stored in memory or on disk in the scaled format.
An alternative approach is to scale the images using a preferred scaling technique just-in-time during the training or model evaluation process. Keras supports this type of data preparation for image data via the ImageDataGenerator class and API.
In this tutorial, you will discover how to use the ImageDataGenerator class to scale pixel data just-in-time when fitting and evaluating deep learning neural network models.
After completing this tutorial, you will know:
- How to configure and a use the ImageDataGenerator class for train, validation, and test datasets of images.
- How to use the ImageDataGenerator to normalize pixel values when fitting and evaluating a convolutional neural network model.
- How to use the ImageDataGenerator to center and standardize pixel values when fitting and evaluating a convolutional neural network model.
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