Credo Health

Food Recognition

Object Detection

Food Recognition Computer Vision Project


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Here are a few use cases for this project:

  1. Smart Nutrition Tracker: Based on images of food items clicked or uploaded by users, the model can estimate the nutritional content and provide diet plans or advice.

  2. Automated Restaurant Ordering: The model can be used in a visual-based food ordering system where patrons can simply point their camera at food items on the menu to understand what the dish is, its ingredients etc.

  3. Recipe Recommendation System: The model can identify food classes and suggest relevant recipes to users wishing to recreate certain dishes at home.

  4. Food Quality Control: In the food and beverage industry, companies can integrate the model into their quality control process to ensure consistency of food products or dishes.

  5. Supermarket Self-checkout Systems: The computer vision model can be used at supermarket self-checkout lanes. Customers just need to place the food items in front of a camera, and the system will recognize and automatically ring up the items.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

                            title = { Food Recognition  Dataset },
                            type = { Open Source Dataset },
                            author = { Credo Health },
                            howpublished = { \url{ } },
                            url = { },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-03-02 },

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Food Recognition project in your project.


Credo Health

Last Updated

7 months ago

Project Type

Object Detection




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