How to Train Ultralytics YOLOv8 models on Your Custom Dataset | 196 classes | Image classification
Eran Feit
Want to unlock the secrets of image classification with YOLOv8? This tutorial dives into PyTorch Hub for easy model access, guides you through training on custom datasets using Python, and empowers you to become an object recognition master!
Explore the exciting world of YOLOv8 for image classification! In this comprehensive guide, you'll learn how to leverage PyTorch Hub, train YOLOv8 from scratch on your own custom datasets with Python code examples, and discover best practices for image classification using YOLOv8 and Ultralytics.
This tutorial composed of several parts :
🐍Create Conda enviroment and all the relevant Python libraries .
🔍 Download and prepare the data : We'll start by downloading the images, and preparing the dataset for the train
🛠️ Training : Run the train over our dataset
📊 Testing the Model: Once the model is trained, we'll show you how to test the model using a new and fresh image
You can download the code here : https://ko-fi.com/s/9ea87857d9
More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4aCcCN4ioFpdLVAGZ_dFeFr
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
00:12 Installation
02:41 Download the dataset
03:39 Train the model
08:30 Test the model
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~
Music by Vincent Rubinetti
Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify: https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u
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