How to Train YOLOv5 on a Custom Dataset
YOLOv5 is the evolution in the YOLO family of object detection models. It's the first YOLO implementation native to PyTorch (rather than Darknet) and emphasizes ease of use and quickness of training and inference. This YOLOv5 tutorial shows you how to train the model on your own dataset in Python.
You will also learn how to install YoloV5 , Download a custom dataset , discover the data and the class , Train an object detection model based on YoloV5 and test the result on a new and fresh image
Code for the tutorial : https://ko-fi.com/s/5982955852
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
00:39 Installation
05:39 Download the dataset / Data discovery
13:45 Train
20:26 Test the model
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#EranFeit #objectdetection #yolo
~~~~~~~~~~~~~~ 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...