Reader small image

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

Product typeBook
Published inApr 2023
Reading LevelBeginner
PublisherPackt
ISBN-139781800561625
Edition1st Edition
Languages
Tools
Right arrow
Author (1)
Van Vung Pham
Van Vung Pham
author image
Van Vung Pham

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.
Read more about Van Vung Pham

Right arrow

Annotation formats

Similar to labeling tools, many different annotation formats are available for annotating images for computer vision applications. The common standards include COCO JSON, Pascal VOC XML, and YOLO PyTorch TXT. There are many more formats (e.g., TensorFlow TFRecord, CreateML JSON, and so on). However, this section covers only the previously listed three most common annotation standards due to space limitations. Furthermore, this section uses two images and labels extracted from the test set of the brain tumor object detection dataset available from Kaggle (https://www.kaggle.com/datasets/davidbroberts/brain-tumor-object-detection-datasets) to illustrate these data formats and demonstrate their differences, as shown in Figure 3.4. This section briefly discusses the key points of each annotation format, and interested readers can refer to the GitHub page of this chapter to inspect this same dataset in different formats in further detail.

Figure 3.4: Two images and tumor labels used to illustrate different annotation formats

Figure...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Hands-On Computer Vision with Detectron2
Published in: Apr 2023Publisher: PacktISBN-13: 9781800561625

Author (1)

author image
Van Vung Pham

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.
Read more about Van Vung Pham