Food Allergy Detection Project Object Detection Dataset and Pre-Trained Model by FluxBlazeSU2022BatchC

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Explore Dataset

Here are a few use cases for this project:

Allergy Awareness Mobile Application: This model could be integrated into a mobile application to help users with food allergies identify potential allergens in their meals. By taking a picture of their food, the application would identify and notify the user of any potential allergens present.
Nutritional Education: For educators in the field of nutrition, this model could be used to create interactive games or quizzes, providing real-time feedback as students identify allergens in various food images.
Personalized Online Shopping Experience: In an e-commerce setting, this model can enhance the online grocery shopping experience. Users with food allergies can use it to scan product images and assess whether the product contains allergens, thereby aiding in making informed purchasing decisions.
Use in Restaurants/Bakeries: Restaurant staff or chefs could utilize this model to ensure their dishes don't contain specific allergens, thus ensuring proper meal preparation for customers with food allergies. Similarly, bakeries could use this to ensure that their nut-free or dairy-free claims are accurate.
Healthcare Application: The model could be used in healthcare or wellness settings where dietitians and nutritionists can quickly identify potential allergens in patients' meals, and customize diet plans more efficiently for individuals with food allergies.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            food-allergy-detection-project_dataset,
                            title = { Food Allergy Detection Project Dataset },
                            type = { Open Source Dataset },
                            author = { FluxBlazeSU2022BatchC },
                            howpublished = { \url{ https://universe.roboflow.com/fluxblazesu2022batchc/food-allergy-detection-project } },
                            url = { https://universe.roboflow.com/fluxblazesu2022batchc/food-allergy-detection-project },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { aug },
                            note = { visited on 2024-04-16 },
                            }