Detecting Underwater Objects with YOLO-NAS Deep Learning

Learn how to implement underwater object detection using YOLO-NAS and Python in this comprehensive tutorial. Discover the process of importing and utilizing the YOLO-NAS model, training it with a custom underwater dataset, and making predictions with bounding boxes around detected objects. Gain hands-on experience with SuperGradients, a PyTorch-based computer vision library, and explore its compatibility with PyTorch Datasets and Dataloaders. Follow along as the instructor demonstrates each step, from installation to predicting test images, and acquire valuable skills in applying state-of-the-art object detection techniques to underwater imagery.

Introduction
Installation
Download the dataset
Train
Predict a test image