Sebastian Raschka • 1/29/2023

Comparing Different Automatic Image Augmentation Methods in PyTorch

Read Original

This article provides a detailed comparison of four automatic image augmentation techniques available in PyTorch: AutoAugment, RandAugment, AugMix, and TrivialAugment. It explains how these methods help reduce overfitting by generating variations of training data and includes performance benchmarks using a ResNet-18 model on a simple dataset, with executable code provided on GitHub.

0 comments
#Pytorch #Image Augmentation #Autoaugment
Comparing Different Automatic Image Augmentation Methods in PyTorch

Comments

No comments yet

Be the first to share your thoughts!

Browser Extension

Get instant access to AllDevBlogs from your browser

Top of the Week

1
React vs Browser APIs (Mental Model)
Jivbcoop • 3 votes
2
React, useEffect, and Stale Closures: How to Avoid Them with Dependencies and useRef
Jivbcoop • 2 votes
3
Building Type-Safe Compound Components
TkDodo Dominik Dorfmeister • 2 votes
4
Using Browser Apis In React Practical Guide
Jivbcoop • 1 votes
5
Better react-hook-form Smart Form Components
Maarten Hus • 1 votes