Hands-On Computer Vision with Detectron2
Develop object detection and segmentation models with a code and visualization approach
1st Edition
Published on 21. May 2024
318 pages
978-1-80056-660-6 (ISBN)
Description
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Persons
Pham Van Vung :
Van Vung Pham is a passionate research scientist in machine learning, deep learning, data science, and data visualization. He has years of experience and numerous publications in these areas. He is currently working on projects that use deep learning to predict road damage from pictures or videos taken from roads. One of the projects uses Detectron2 and Faster R-CNN to predict and classify road damage and achieve state-of-the-art results for this task. Dr. Pham obtained his PhD from the Computer Science Department, at Texas Tech University, Lubbock, Texas, USA. He is currently an assistant professor at the Computer Science Department, Sam Houston State University, Huntsville, Texas, USA.
Van Vung Pham is a passionate research scientist in machine learning, deep learning, data science, and data visualization. He has years of experience and numerous publications in these areas. He is currently working on projects that use deep learning to predict road damage from pictures or videos taken from roads. One of the projects uses Detectron2 and Faster R-CNN to predict and classify road damage and achieve state-of-the-art results for this task. Dr. Pham obtained his PhD from the Computer Science Department, at Texas Tech University, Lubbock, Texas, USA. He is currently an assistant professor at the Computer Science Department, Sam Houston State University, Huntsville, Texas, USA.
Content
Table of Contents - An Introduction to Detectron2 and Computer Vision Tasks
- Developing Computer Vision Applications Using Existing Detectron2 Models
- Data Preparation for Object Detection Applications
- The Architecture of the Object Detection Model in Detectron2
- Training Custom Object Detection Models
- Inspecting Training Results and Fine-Tuning Detectron2's Solver
- Fine-Tuning Object Detection Models
- Image Data Augmentation Techniques
- Applying Train-Time and Test-Time Image Augmentations
- Training Instance Segmentation Models
- Fine-Tuning Instance Segmentation Models
- Deploying Detectron2 Models into Server Environments
- Deploying Detectron2 models into Browsers and Mobile Environments
- Developing Computer Vision Applications Using Existing Detectron2 Models
- Data Preparation for Object Detection Applications
- The Architecture of the Object Detection Model in Detectron2
- Training Custom Object Detection Models
- Inspecting Training Results and Fine-Tuning Detectron2's Solver
- Fine-Tuning Object Detection Models
- Image Data Augmentation Techniques
- Applying Train-Time and Test-Time Image Augmentations
- Training Instance Segmentation Models
- Fine-Tuning Instance Segmentation Models
- Deploying Detectron2 Models into Server Environments
- Deploying Detectron2 models into Browsers and Mobile Environments
