The Food and Food Categories (FFoCat) Dataset

The Food and Food Categories (FFoCat) Dataset

The Food and Food Categories (FFoCat) Dataset contains 58.962 images of food annotated with the food label and the food categories of the Mediterranean Diet. It is one of the most complete datasets regarding the Mediterranean Diet as it is aligned with the standard AGROVOC and HeLiS ontologies and allows to study multitask learning problems in Computer Vision for food recognition and diet recommendation.

The dataset is already divided into the train and test folder. The file label.tsv contains the food labels, the file food_food_category_map.tsv contains the food labels with the corresponding food category labels. The following table compares the FFoCat dataset with previous datasets for food recognition.

This dataset has been published at the International Conference on Image Analysis and Processing (ICIAP - 2019). The source code for reproducing the experiments together with other information about the dataset is available here.

AGROVOC Alignment of Food Categories

The AGROVOC_alignment.tsv file contains the alignment of the food categories in the FFoCat dataset with AGROVOC, the standard ontology of the Food and Agriculture Organization (FAO) of the United Nations. This allows interoperability and linked open data navigation. Such alignment can be derived by querying HeLis, here we propose a shortcut.

Citing FFoCat

If you use FFoCat in your research, please use the following BibTeX entry.

@inproceedings{DonadelloD19Ontology,
author = {Ivan Donadello and Mauro Dragoni},
title = {Ontology-Driven Food Category Classification in Images},
booktitle = {{ICIAP} {(2)}},
series = {Lecture Notes in Computer Science},
volume = {11752},
pages = {607--617},
publisher = {Springer},
year = {2019}
}