FoodSeg103 is a large-scale benchmark for food image segmentation. It contains 103 food categories and 7118 images with ingredient level pixel-wise annotations. The dataset is a curated sample from Recipe1M and annotated and refined by human annotators. The dataset is split into 2 subsets: training set, validation set. The training set contains 4983 images and the validation set contains 2135 images.
Supported Tasks… See the full description on the dataset page: https://huggingface.co/datasets/EduardoPacheco/FoodSeg103.
