CarbonDiet

CarbonDiet

Object Detection

CarbonDiet Computer Vision Project

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Here are a few use cases for this project:

  1. Personalized Meal Planning: CarbonDiet can be used by individuals to plan meals according to their dietary preferences, budget constraints, and nutritional requirements. Users can search for recipes using keywords related to the recipe title or category, find price estimations, and view ingredient quantities, all of which will help them plan a balanced meal plan within their budget.

  2. Restaurant Menu Optimization: CarbonDiet can help restaurant owners and chefs in categorizing and optimizing their menus based on recipe ingredients, item descriptions, and prices. The model can also be utilized to identify the most popular and profitable menu items in a specific category, assisting in the decision-making process when updating or revising menus.

  3. Inventory Management: Grocery retailers can benefit from CarbonDiet in managing their inventory by identifying popular recipe ingredients and their corresponding quantities. This data can help them forecast item demand, allowing them to stock shelves with the right items and reduce waste due to spoilage or low demand.

  4. Nutritional Analysis: Nutritionists and dieticians can use CarbonDiet to analyze the nutritional content of a wide range of recipes, determining the caloric values, macronutrient distribution, and micronutrient content. This enables them to provide tailored recommendations to their clients and educate them on making healthier meal choices.

  5. Cooking App Development: Developers building cooking and recipe apps can integrate CarbonDiet as a robust search and categorization tool for users. This will allow users to easily browse, find, and organize recipes based on criteria such as recipe title, category, ingredients, price, and restaurant name, enhancing the user experience and making their app stand out in a competitive market.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            carbondiet_dataset,
                            title = { CarbonDiet Dataset },
                            type = { Open Source Dataset },
                            author = { CarbonDiet },
                            howpublished = { \url{ https://universe.roboflow.com/carbondiet/carbondiet } },
                            url = { https://universe.roboflow.com/carbondiet/carbondiet },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-03-29 },
                            }
                        

Connect Your Model With Program Logic

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

Source

CarbonDiet

Last Updated

8 months ago

Project Type

Object Detection

Subject

recipes

Views: 121

Views in previous 30 days: 5

Downloads: 7

Downloads in previous 30 days: 0

License

CC BY 4.0

Classes

Price Quantities Recipe Recipe ingredients Recipe title Section Section title category item item_description price restaurant_name