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Data Augmentation with Python

You're reading from   Data Augmentation with Python Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246451
Length 394 pages
Edition 1st Edition
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Author (1):
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Duc Haba Duc Haba
Author Profile Icon Duc Haba
Duc Haba
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Data Augmentation
2. Chapter 1: Data Augmentation Made Easy FREE CHAPTER 3. Chapter 2: Biases in Data Augmentation 4. Part 2: Image Augmentation
5. Chapter 3: Image Augmentation for Classification 6. Chapter 4: Image Augmentation for Segmentation 7. Part 3: Text Augmentation
8. Chapter 5: Text Augmentation 9. Chapter 6: Text Augmentation with Machine Learning 10. Part 4: Audio Data Augmentation
11. Chapter 7: Audio Data Augmentation 12. Chapter 8: Audio Data Augmentation with Spectrogram 13. Part 5: Tabular Data Augmentation
14. Chapter 9: Tabular Data Augmentation 15. Index 16. Other Books You May Enjoy

Reinforcing your learning

The same concepts for classification image transformations apply to segmentation image transformations. Here, Pluto reuses or slightly hacks the wrapper functions in Chapter 3. In particular, Pluto hacks the following methods for segmentation:

  • Horizontal flip
  • Vertical flip
  • Rotating
  • Random resizing and cropping
  • Transpose
  • Lighting
  • FancyPCA

Fun fact

You can’t complete or understand this chapter unless you have read Chapter 3. This is because Pluto reuses or slightly modifies the existing image augmentation wrapper functions.

Pluto chose these filters because the Albumentations library marked them as safe for segmentation. So, let’s start with horizontal flip.

Horizontal flip

Pluto demonstrated horizontal flip using the PIL library in Chapter 3 because the code is easy to understand. Thus, he will hack draw_image_flip_pil() into the draw_image_flip_pil_segmen() function. The transformation code is...

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