How to Detect Under the Sea classes using Deep learning | Yolo-Nas
YOLO-NAS delivers state-of-the-art (SOTA) performance with the unparalleled accuracy-speed performance, outperforming other models such as YOLOv5, YOLOv6, YOLOv7 and YOLOv8.
Training with SuperGradients, PyTorch-based computer vision library. SuperGradients is fully compatible with PyTorch Datasets and Dataloaders, so you can use your dataloaders as is.
In this video, we demonstrate how to implement Object Detection using YOLOv-NAS and Python, specifically for Detecting under the sea images
What you'll learn:
How to import and utilize the Yolo-Nas model .
How to train Yolo-Nas model with a custom under the sea dataset.
How to make predictions and draw bounding boxes around detected teeth.
Code for the tutorial : https://ko-fi.com/s/297688e915
You can find more computer vision tutorials in my blog page : https://eranfeit.net/blog/
You can find more projects and tutorials in this playlist : • Best Object Detection models
~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~
A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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00:00 Introduction
02:26 Installation
05:02 Download the dataset
10:14 Train
18:40 Predict a test image
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#EranFeit #objectdetection #yolo-nas
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~
Music by Vincent Rubinetti
Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/a...
Stream the music on Spotify: https://open.spotify.com/album/1dVyjw...