- 1 min

Table of Contents:

E-RotaNet is a Computer Vision pipeline, which can rotate images in proportion to human-level vision.

What is ‘E’ in E-Rotanet?

‘E’ stands for the Efficientnet backbone used to learn the features and the context of the images.

EfficientNets are a family of image classification models which use compound scaling, and achieve state-of-the-art accuracy, yet being an order-of-magnitude smaller and faster than previous models.

About the dataset

The released models are trained on Google Street View dataset, which contains ~62k images which contain mostly human-perception viewing angles of streets and buildings.


Documentation can be found at GitHub.


The bare source code can rotate images and generate a plot like this: E-RotaNet_Figure_1

However, the repository also contains a deployed Flask application, such that it attains following proof of concept:

E-RotaNet_Screenshot_1 E-RotaNet_Screenshot_2

Demo GIF


Aitik Gupta

I go by @aitikgupta throughout the web! \o/

rss facebook twitter github gitlab gitlab youtube mail spotify lastfm instagram linkedin google google-plus pinterest medium vimeo telegram stackoverflow reddit quora quora key download slideshare speakerdeck googlescholar researchgate mendeley orcid impactstory figshare pubmed