Explore the Intersection over Union (IoU) similarity metric for assessing object recognition model performance in this 18-minute tutorial. Learn the theory behind IoU for bounding boxes and masks, starting with a comprehensive definition and formula breakdown. Discover how to modify segmentation masks and implement IoU using PyTorch for both boxes and masks. Follow along with code walkthroughs and gain practical insights into this essential computer vision technique. By the end of the tutorial, acquire a solid understanding of IoU and its applications in object detection and segmentation tasks.
Overview
Syllabus
- Introduction:
- Definition of IoU:
- Formula Breakdown:
- Segmentation Mask Modification:
- Pytorch Implementation of IoU - Box:
- Pytorch Implementation of IoU - Mask:
- Conclusion:
Taught by
Yacine Mahdid
Related Courses
-
Deep Learning for Images with PyTorch
-
Modern Computer Vision GPT, PyTorch, Keras, OpenCV4 in 2024!
-
Intersection Over Union Explained and PyTorch Implementation
-
Convolutional Neural Nets Explained and Implemented in Python - PyTorch
-
DenseNet Deep Neural Network Architecture Explained
-
Introduction to Computer Vision - Lecture 1
