IndianFoodNet-30

About IndianFoodNet-30

IndianFoodNet-30 is created by Ritu Agarwal, Nikunj Bansal, Tanupriya Choudhury, Tanmay Sarkar & Neelu Jyothi Ahuja with a goal of building an Indian Food detection model. It contains more than 5500 images of 30 popular Indian food items.

Data collection

We used search engines (Google and Bing) to crawl and look for suitable images using JavaScript queries for each food item from the list created. The images with incomplete RGB channels were removed, and the images collected from different search engines were compiled. When downloading images from search engines, many images were irrelevant to the purpose, especially the ones with a lot of text in them. We deployed the EAST text detector to segregate such images. Finally, a comprehensive manual inspection was conducted to ensure the relevancy of images in the dataset.

Fair use

This dataset contains some copyrighted material whose use has not been specifically authorized by the copyright owners. In an effort to advance scientific research, we make this material available for academic research. If you wish to use copyrighted material in our dataset for purposes of your own that go beyond non-commercial research and academic purposes, you must obtain permission directly from the copyright owner. We believe this constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the US Copyright Law. In accordance with Title 17 U.S.C. Section 107, the material on this site is distributed without profit to those who have expressed a prior interest in receiving the included information for non-commercial research and educational purposes.(adapted from Christopher Thomas).

Citation

If you find our dataset useful, please cite us as:

@dataset{dataset,
author = {Agarwal, Ritu and Bansal, Nikunj and Choudhury, Tanupriya and Sarkar, Tanmay and J.Ahuja, Neelu},
year = {2023},
title = {IndianFoodNet-30 Dataset},
publisher = {Roboflow Universe},
url = {https://universe.roboflow.com/indianfoodnet/indianfoodnet},
}