Heat Maps | Yolov5 object detection
EigenCAM is a visualization technique designed to enhance the interpretability of deep learning models, specifically those used for object detection like YOLOv5. It stands for Eigen Class Activation Map, and its purpose is to highlight the regions of an input image that are most influential for the model's predictions.
In this video, we delve into the world of computer vision and explore EigenCAM, a powerful visualization tool for YOLOv5, one of the most popular object detection algorithms. EigenCAM, short for Eigen Class Activation Map, helps us understand and interpret the decisions made by deep learning models. By generating heatmaps that highlight the most influential regions of an input image, EigenCAM provides insights into how YOLOv5 identifies and classifies objects within a scene.
Code for the tutorial : https://ko-fi.com/s/538fc343b8
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
00:34 Installation
07:50 Let's start coding ...
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#EranFeit #objectdetection #yolo
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~
Music by Vincent Rubinetti
Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/a...
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