Food/Non-food Image Classification
The data consists of 222430 training and 55096 testing images belonging to 2 classes. For the preparation of this dataset, we used images from the existing image datasets of UECFOOD256, Caltech 256, Instagram Images, Flickr Image Dataset, Food101, Malaysian Food Dataset(gathered and crawled by us), Indoor Scene recognition Dataset, 15 scene dataset.
Please only cite our work, for Food/Non-Food detection, in case of classification problems on the individual datasets, please cite and use them.
- FoodNonFoodDataset.zip (18.23 GB)
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