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Hands-On Computer Vision with Detectron2

You're reading from  Hands-On Computer Vision with Detectron2

Product type Book
Published in Apr 2023
Publisher Packt
ISBN-13 9781800561625
Pages 318 pages
Edition 1st Edition
Languages
Author (1):
Van Vung Pham Van Vung Pham
Profile icon Van Vung Pham

Table of Contents (20) Chapters

Preface Part 1: Introduction to Detectron2
Chapter 1: An Introduction to Detectron2 and Computer Vision Tasks Chapter 2: Developing Computer Vision Applications Using Existing Detectron2 Models Part 2: Developing Custom Object Detection Models
Chapter 3: Data Preparation for Object Detection Applications Chapter 4: The Architecture of the Object Detection Model in Detectron2 Chapter 5: Training Custom Object Detection Models Chapter 6: Inspecting Training Results and Fine-Tuning Detectron2’s Solvers Chapter 7: Fine-Tuning Object Detection Models Chapter 8: Image Data Augmentation Techniques Chapter 9: Applying Train-Time and Test-Time Image Augmentations Part 3: Developing a Custom Detectron2 Model for Instance Segmentation Tasks
Chapter 10: Training Instance Segmentation Models Chapter 11: Fine-Tuning Instance Segmentation Models Part 4: Deploying Detectron2 Models into Production
Chapter 12: Deploying Detectron2 Models into Server Environments Chapter 13: Deploying Detectron2 Models into Browsers and Mobile Environments Index Other Books You May Enjoy

Summary

This chapter discussed the popular data sources for the computer vision community. These data sources often have pre-trained models that help you quickly build computer vision applications. We also learned about the common places to download computer vision datasets. If no datasets exist for a specific computer vision task, this chapter also helped you get images by downloading them from the internet and select a tool for labeling the downloaded images. Furthermore, the computer vision field is developing rapidly, and many different annotation formats are available. Therefore, this chapter also covered popular data formats and the steps to convert these formats into the format supported by Detectron2.

By this time, you should have your dataset ready. The next chapter discusses the architecture of Detectron2 with details regarding the backbone networks and how to select one for an object detection task before training an object detection model using Detectron2.

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