How to Detect Dogs using Deep learning
In this tutorial, we delve into the world of *computer vision* by creating a **YOLOv8-based dogs breed object detection ** using **Deep learning **.
What you'll learn:
How to import and utilize the YOLOv8 model from the Ultralytics library.
How to convert annotations from XML format to Yolo format
How to load and interpret annotation data from a YAML file.
How to train your YOLOv8 model with a dogs dataset.
How to make predictions and draw bounding boxes around detected dogs.
Code for the tutorial : https://ko-fi.com/s/3021f127ba
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
00:40 Installation
03:36 Download the dataset & Prepare the data
18:10 Convert all annotations
18:40 Predict a test image
32:54 Train
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#EranFeit #objectdetection #yolov8
~~~~~~~~~~~~~~ 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...