food Object Detection Dataset and Pre-Trained Model by yolostudy

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Explore Dataset

Here are a few use cases for this project:

Nutrient Content Analyzer: The model could be used in a mobile app that analyzes the nutrient content of a meal by identifying distinct food items, which could benefit diet-conscious individuals or those with specific dietary needs.
Cooking Assistant Application: An application could use this model to assist users in identifying and categorizing ingredients for a recipe. The user would take a photo of their ingredients, and the app would recognize and list them, making recipe preparation more convenient and streamlined.
Inventory Management: Grocery stores or restaurants could utilize the model to automatically track and manage inventory by recognizing specific food items.
Food Waste Management: This model could be useful for creating a system that tracks the rate at which different types of food are thrown away in households, restaurants, or grocery stores, helping to gain insights into food waste patterns.
Allergen Alert System: Those with food allergies could use an app that uses this model to identify potential allergens in prepared meals by recognizing specific food items. The app could alert the user if their allergen is detected, providing an additional safety layer.

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-k3oqt_dataset,
                            title = { food Dataset },
                            type = { Open Source Dataset },
                            author = { yolostudy },
                            howpublished = { \url{ https://universe.roboflow.com/yolostudy-lxjtn/food-k3oqt } },
                            url = { https://universe.roboflow.com/yolostudy-lxjtn/food-k3oqt },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-29 },
                            }