Image Classification Using YoloV8 Model on Custom dataset | Agricultural Pests

Explore the power of YoloV8 with PyTorch Hub integration. Unlock its potential for image classification tasks using custom datasets, and dive into comprehensive tutorials on training YoloV8 models from scratch with PyTorch. Harness the ultralytics YoloV8 library to build robust image classification solutions.

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/abfa3b40fd

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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https://www.youtube.com/watch?v=--FPMF49Dpg