Combines the power of language and vision processing for food detection and nutritional estimation. With the help of LLaVa, it takes an image of food and optional textual hints as input and generates a comprehensive menu name, description, and nutritional information. The estimations are not realiable and the model halluciates a lot. Just for fun.
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Language Integration: By providing optional textual hints about the food image, users can guide the model's predictions, ensuring even more precise results.
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Menu Generation: Goes beyond basic food identification. It creates descriptive menu names and descriptions.
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Nutritional Estimation: Estimate the nutritional content of the identified foods. This includes calorie count, macronutrient distribution, and other relevant dietary details.
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User-Friendly Interface: The user interface is designed to be intuitive and easy to navigate, allowing users to upload images, provide hints, and receive detailed food information effortlessly. Lightning Apps.
- Python 3.7 or higher
- torch (tested 2.0)
- torchvision
- 7875MiB VRAM (4bit)
git clone https://github.com/luca-medeiros/food-info && cd food-info
pip install -r requirements.txt
To run the Lightning AI APP:
lightning run app app.py
This project is based on the following repositories:
This project is licensed under the Apache 2.0 License