Planeat food Instance Segmentation Computer Vision Project
Here are a few use cases for this project:
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Smart Menu Selection: A mobile application that recommends personalized meal options at a restaurant or cafeteria by identifying foods on display, considering user preferences, dietary restrictions, or nutritional goals.
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Fitness and Nutrition Tracking: An app that uses instance segmentation to automatically log food consumed for easy tracking and estimation of nutritional information, aiding in maintaining a balanced diet and achieving fitness goals.
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Inventory Management in Grocery Stores: A system to monitor food stock levels by identifying and counting food items in real-time, helping store managers maintain adequate inventory and reduce food waste.
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Automated Meal Planning for Catering Services: By identifying and analyzing different food items and their quantity, catering companies can create balanced and diverse menus, considering clients' preferences and potential dietary restrictions.
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Cooking Assistance and Recipe Selection: A smart kitchen assistant that recommends recipes based on available ingredients, by identifying and measuring the identified food items to help users make the most out of their pantry ingredients.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
planeat-food-instance-segmentation_dataset,
title = { Planeat food Instance Segmentation Dataset },
type = { Open Source Dataset },
author = { tirocinio },
howpublished = { \url{ https://universe.roboflow.com/tirocinio-oylk4/planeat-food-instance-segmentation } },
url = { https://universe.roboflow.com/tirocinio-oylk4/planeat-food-instance-segmentation },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { feb },
note = { visited on 2024-05-06 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Planeat food Instance Segmentation project in your project.