Image Processing Layers
Explore key Keras preprocessing layers for image data including Rescaling for normalization, Resizing to adjust image dimensions, and CenterCrop to focus on image centers. Understand how these layers integrate into deep learning models to handle raw image inputs during training, facilitating efficient dataset preprocessing and augmentation.
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The Keras preprocessing layers API allows us to build data processing pipelines. The layers provided by this API preprocess data during neural network training. These layers become part of a Keras DL model. Keras preprocessing layers make the DL model accept raw unprocessed data/images as input and preprocess the data during the model training process. Keras provides preprocessing layers for numerous tasks that include:
Image preprocessing: Rescale, resize, and center-crop images.
Image data augmentation: Randomly translate, rotate, crop, flip, zoom in/out, and change the image contrast.
Feature preprocessing:
Numerical feature preprocessing: Normalization and discretization.
Categorical feature preprocessing: Feature encoding and hashing. ... ...