{"url":"/dataset/food-image-classification-dataset","name":"Food Image Classification Dataset","full_name":null,"description_markdown":"About Dataset\r\nThe file contains 24K unique figure obtained from various Google resources\r\nMeticulously curated figure ensuring diversity and representativeness\r\nProvides a solid foundation for developing robust and precise figure allocation algorithms\r\nEncourages exploration in the fascinating field of feed figure allocation\r\n\r\nUnparalleled Diversity\r\nDive into a vast collection spanning culinary landscapes worldwide.\r\nImmerse yourself in a diverse array of cuisines, from Italian pasta to Japanese sushi.\r\nExplore a rich tapestry of food imagery, meticulously curated for accuracy and breadth.\r\nPrecision Labeling\r\nBenefit from meticulous labeling, ensuring each image is tagged with precision.\r\nAccess detailed metadata for seamless integration into your machine learning projects.\r\nEmpower your algorithms with the clarity they need to excel in food recognition tasks.\r\n Endless Applications\r\nFuel advancements in machine learning and computer vision with this comprehensive dataset.\r\nRevolutionize food industry automation, from inventory management to quality control.\r\nEnable innovative applications in health monitoring and dietary analysis for a healthier tomorrow.\r\n Seamless Integration\r\nSeamlessly integrate our dataset into your projects with user-friendly access and documentation.\r\nEnjoy high-resolution images optimized for compatibility with a range of AI frameworks.\r\nAccess support and resources to maximize the potential of our dataset for your specific needs.\r\n \r\nConclusion\r\nEmbark on a culinary journey through the lens of artificial intelligence and unlock the potential of feed figure allocation with our SEO-optimized file. Elevate your research, elevate your projects, and elevate the way we perceive and interact with food in the digital age. Dive in today and savor the possibilities!\r\n\r\nThis dataset is sourced from Kaggle.","description_withheld":null,"homepage":"https://gts.ai/dataset-download/food-image-classification-dataset/","introduced_date":"2025-02-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/food-ingredients-recognition-through-multi","title":"Food Ingredients Recognition through Multi-label Learning","first_author":"Marc Bolaños","url":null},"license":{"name":"CC0: Public Domain","url":null},"modalities":[],"tasks":[{"name":"Food Recognition","url":"/task/food-recognition","datasets_with_task":"/datasets/task/food-recognition"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Food Image Classification Dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}