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Applied Deep Learning with Keras

You're reading from   Applied Deep Learning with Keras Solve complex real-life problems with the simplicity of Keras

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Product type Paperback
Published in Apr 2019
Publisher
ISBN-13 9781838555078
Length 412 pages
Edition 1st Edition
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Authors (3):
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Matthew Moocarme Matthew Moocarme
Author Profile Icon Matthew Moocarme
Matthew Moocarme
Mahla Abdolahnejad Mahla Abdolahnejad
Author Profile Icon Mahla Abdolahnejad
Mahla Abdolahnejad
Ritesh Bhagwat Ritesh Bhagwat
Author Profile Icon Ritesh Bhagwat
Ritesh Bhagwat
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Toc

Image Augmentation


The word augmentation means the action or process of making or becoming greater in size or amount. Image or data augmentation works in a similar manner. Image/data augmentation creates many batches of our images. Then, it applies random transformations on random images inside the batches. Data transformation can be rotating images, shifting them, flipping them, and so on. By applying this transformation, we get more diverse images inside the batches, and we also have much more data than we had originally.

A cylinder can be rotated from different angles and seen differently. In the following figure, a single cylinder is seen from five different angles. So, we have effectively created five different images from a single image:

Figure 7.13: Image augmentation of a cylinder

The following is example code of image augmentation; here, the ImageDataGenerator class is used for processing. shear_range, zoom_range, and horizontal_flip are all used for the transformation of images:

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