Food Recognition

Recipe1M+ is a dataset which contains one million structured cooking recipes with 13M associated images. Source: Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images Image Source: http://im2recipe.csail.mit.edu/

FoodX-251 is a dataset of 251 fine-grained classes with 118k training, 12k validation and 28k test images. Human verified labels are made available for the training and test images. The classes are fine-grained and visually similar, for example, different types of cakes, sandwiches, puddings, soups, and pastas. Source: FoodX-251: A Dataset for Fine-grained Food Classification Image Source: Kaur et al

Includes 500 categories from the list in the Wikipedia and 399,726 images, a more comprehensive food dataset that surpasses existing popular benchmark datasets by category coverage and data volume. Source: ISIA Food-500: A Dataset for Large-Scale Food Recognition via Stacked Global-Local Attention Network

ChineseFoodNet aims to automatically recognizing pictured Chinese dishes. Most of the existing food image datasets collected food images either from recipe pictures or selfie. In the dataset, images of each food category of the dataset consists of not only web recipe and menu pictures but photos taken from real dishes, recipe and menu as well. ChineseFoodNet contains over 180,000 food photos of 208 categories, with each category covering a large variations in presentations of same Chinese food. Source: ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition Image Source: https://sites.google.com/view/chinesefoodnet

The Kenyan Food Type Dataset (KenyanFood13) is an image classification dataset for Kenyan food. The images are categorized into 13 different labels. Source: https://github.com/monajalal/Kenyan-Food Image Source: https://github.com/monajalal/Kenyan-Food

Contains a dataset of 241 Chinese dishes with 191,811 images. There are 170843 images in the training set and 20943 images in the validation set. All images are resized to 600x600. As some of the images in the dataset are from ChineseFoodNet, they are not supported for commercial use.

CNFOOD-241 Contains a dataset of 241 Chinese dishes with 191,811 images. There are 170843 images in the training set and 20943 images in the validation set. All images are resized to 600x600. As some of the images in the dataset are from ChineseFoodNet, they are not supported for commercial use. CNFOOD-241-Chen is the CNFOOD-241 dataset spilt with the list introduced in the paper "Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning," which has random split as train, val, test three parts.

About Dataset The file contains 24K unique figure obtained from various Google resources Meticulously curated figure ensuring diversity and representativeness Provides a solid foundation for developing robust and precise figure allocation algorithms Encourages exploration in the fascinating field of feed figure allocation Unparalleled Diversity Dive into a vast collection spanning culinary landscapes worldwide. Immerse yourself in a diverse array of cuisines, from Italian pasta to Japanese sushi. Explore a rich tapestry of food imagery, meticulously curated for accuracy and breadth. Precision Labeling Benefit from meticulous labeling, ensuring each image is tagged with precision. Access detailed metadata for seamless integration into your machine learning projects. Empower your algorithms with the clarity they need to excel in food recognition tasks. Endless Applications Fuel advancements in machine learning and computer vision with this comprehensive dataset. Revolutionize food industry automation, from inventory management to quality control. Enable innovative applications in health monitoring and dietary analysis for a healthier tomorrow. Seamless Integration Seamlessly integrate our dataset into your projects with user-friendly access and documentation. Enjoy high-resolution images optimized for compatibility with a range of AI frameworks. Access support and resources to maximize the potential of our dataset for your specific needs. Conclusion Embark 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! This dataset is sourced from Kaggle.

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. ### Dataset Features - Dataset size : 5000+ - Captured by : Over 800+ crowdsource contributors - Resolution : 99% images HD and above (1920x1080 and above) - Location : Captured with 800+ cities accross India - Diversity : Various lighting conditions like day, night, varied distances, view points, dimlight etc. - Device used : Captured using mobile phones in 2020-2021 - Usage : Indian food classification, Dish classification, Food plate detection, etc. ### Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record To download full datasets or to submit a request for your dataset needs, please ping us at sales@datacluster.ai Visit www.datacluster.ai to know more. Note: All the images are manually captured and verified by a large contributor base on DataCluster platform