"ACETADA: Meal Images Enriched With Contextual Metadata"

"ACETADA is a public collection of 806 high-resolution \"before-meal\" images captured with consumer smartphones in free-living settings. This dataset is the first of its kind to pair these free-living images with dietitian-verified nutrition labels (kilocalories, grams of protein, carbohydrates, fat, and edible-portion mass) and enriched with \"contextual metadata\" in the form of precise GPS coordinates, timestamps, and fine-grained food-item annotations. Images are distributed as JPEG files; all annotations reside in a single CVS file that follows the Huggingface datasets schema for the possibility of one-line loading in Python. ACETADA enables controlled studies of nutrition and portion estimation, and metadata-aware prompting for Large Multimodal Models (LMM). The dataset is released under a CC-BY-4.0 licence for non-commercial use, with commercial licensing available upon request. ACETADA accompanies the manuscript \"Evaluating Large Multimodal Models for Nutrition Analysis: A Benchmark Enriched with Contextual Metadata\" (IEEE JBHI, 2025)."