A realistic, diverse, and challenging dataset for object detection on images. The data was recorded at a beer tent in Germany and consists of 15 different categories of food and drink items.
2 PAPERS • 1 BENCHMARK
It contains data from two different realities: Food.com, a well-known American recipe site, and Planeat, an Italian site that allows you to plan recipes to save food waste. The dataset is divided into two parts: embeddings, which can be used directly to execute the work and receive suggestions, and raw data, which must first be processed into embeddings.
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This dataset is an extremely challenging set of over 5000+ original India food images captured and crowdsourced from over 800+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.
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