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Data Labeling in Machine Learning with Python

You're reading from   Data Labeling in Machine Learning with Python Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781804610541
Length 398 pages
Edition 1st Edition
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Author (1):
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Vijaya Kumar Suda Vijaya Kumar Suda
Author Profile Icon Vijaya Kumar Suda
Vijaya Kumar Suda
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Labeling Tabular Data
2. Chapter 1: Exploring Data for Machine Learning FREE CHAPTER 3. Chapter 2: Labeling Data for Classification 4. Chapter 3: Labeling Data for Regression 5. Part 2: Labeling Image Data
6. Chapter 4: Exploring Image Data 7. Chapter 5: Labeling Image Data Using Rules 8. Chapter 6: Labeling Image Data Using Data Augmentation 9. Part 3: Labeling Text, Audio, and Video Data
10. Chapter 7: Labeling Text Data 11. Chapter 8: Exploring Video Data 12. Chapter 9: Labeling Video Data 13. Chapter 10: Exploring Audio Data 14. Chapter 11: Labeling Audio Data 15. Chapter 12: Hands-On Exploring Data Labeling Tools 16. Index 17. Other Books You May Enjoy

pyOpenAnnotate

pyOpenAnnotate is an open source Python-based annotation tool that automates the image annotation pipeline using OpenCV. It is particularly well-suited for annotating simple datasets, such as images with plain backgrounds or infrared images. pyOpenAnnotate is a single-class automated annotation tool that can help you label and annotate images and videos using computer vision techniques. It is built by harnessing the power of OpenCV. You can check out the Python library documentation to understand how pyOpenAnnotate has been designed: https://pypi.org/project/pyOpenAnnotate/.

You can load your images in a directory and then run the following command to start labeling the bounding boxes for your images:

!annotate --img /path/to/directory/Images

The following image is available in the book’s GitHub path for this chapter.

You can replace the directory path with your own dataset path. This will prompt the tool to label the objects in your image and you can...

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