Book Image

Hands-On Computer Vision with Detectron2

By : Van Vung Pham
5 (4)
Book Image

Hands-On Computer Vision with Detectron2

5 (4)
By: Van Vung Pham

Overview of this book

Computer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, Facebook's next-gen library providing cutting-edge detection and segmentation algorithms. It’s used in research and practical projects at Facebook to support computer vision tasks, and its models can be exported to TorchScript or ONNX for deployment. The book provides you with step-by-step guidance on using existing models in Detectron2 for computer vision tasks (object detection, instance segmentation, key-point detection, semantic detection, and panoptic segmentation). You’ll get to grips with the theories and visualizations of Detectron2’s architecture and learn how each module in Detectron2 works. As you advance, you’ll build your practical skills by working on two real-life projects (preparing data, training models, fine-tuning models, and deployments) for object detection and instance segmentation tasks using Detectron2. Finally, you’ll deploy Detectron2 models into production and develop Detectron2 applications for mobile devices. By the end of this deep learning book, you’ll have gained sound theoretical knowledge and useful hands-on skills to help you solve advanced computer vision tasks using Detectron2.
Table of Contents (20 chapters)
1
Part 1: Introduction to Detectron2
4
Part 2: Developing Custom Object Detection Models
12
Part 3: Developing a Custom Detectron2 Model for Instance Segmentation Tasks
15
Part 4: Deploying Detectron2 Models into Production

Part 1: Introduction to Detectron2

This first part introduces Detectron2, its architectures, and the computer vision tasks that Detectron2 can perform. In other words, it discusses why we need computer vision applications and what computer vision tasks Detectron2 can perform. Additionally, this part provides the steps to set up environments for developing computer vision applications using Detectron2 locally or on the cloud using Google Colab. Also, it guides you through the steps to build applications for computer vision tasks using state-of-the-art models in Detectron2. Specifically, it discusses the existing and pre-trained models in Detectron2’s Model Zoo and the steps to develop applications for object detection, instance segmentation, key-point detection, semantic segmentation, and panoptic segmentation using these models.

The first part covers the following chapters:

  • Chapter 1, An Introduction to Detectron2 and Computer Vision Tasks
  • Chapter 2, Developing...