Food Ingredients Image Detection_Team4 Object Detection Dataset and Pre-Trained Model by DSStudy

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Explore Dataset

Here are a few use cases for this project:

Meal Preparation: Users can leverages the "Food Ingredients Image Detection_Team4" model to facilitate their meal preparations, helping them identify specific ingredients on their kitchen counters or in their pantry. This can even be employed in cooking apps or chef assistants to verify if a user has the correct ingredients needed for a certain recipe.
Grocery Shopping: As part of a grocery shopping app, the AI model can help shoppers identify different ingredients in the store. In addition, it can assist users in finding replacements for items that aren't available or suggest alternatives based on dietary restrictions.
Dietary Tracking: Nutrition apps can use this model to help users identify and track the ingredients they're consuming. By scanning food items or meals, users can acquire a detailed understanding of their dietary habits, which can support weight loss goals or managing dietary restrictions.
School Cafeteria: Schools can implement this model to help in their cafeterias, identifying specific ingredients in meals to accommodate students with food allergies or dietary preferences.
Food Waste Management: By identifying perishable items like fruits and vegetables, this model can support food waste reduction strategies at home or in food-related businesses. It would alert users to consume items that are nearing their expiration date.

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-ingredients-image-detection_team4_dataset,
                            title = { Food Ingredients Image Detection_Team4 Dataset },
                            type = { Open Source Dataset },
                            author = { DSStudy },
                            howpublished = { \url{ https://universe.roboflow.com/dsstudy-h0rzy/food-ingredients-image-detection_team4 } },
                            url = { https://universe.roboflow.com/dsstudy-h0rzy/food-ingredients-image-detection_team4 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-28 },
                            }