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https://github.com/shruti23-ui/calories-advisor

Calories Advisor App uses Google’s Gemini 1.5 Pro to analyze food images and estimate nutritional content. Upload an image, enter portion size, and get insights on calories, ingredients, and nutrient breakdown. Built with Streamlit for easy access to dietary advice and tips
https://github.com/shruti23-ui/calories-advisor

generative-ai google-gemini-pro python streamlit-application

Last synced: 14 days ago
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Calories Advisor App uses Google’s Gemini 1.5 Pro to analyze food images and estimate nutritional content. Upload an image, enter portion size, and get insights on calories, ingredients, and nutrient breakdown. Built with Streamlit for easy access to dietary advice and tips

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README

        

# Calories Advisor App

**Calories Advisor App** uses Google's Gemini 1.5 Pro to analyze food images and estimate nutritional content. This app helps users understand the calorie content and nutritional value of their food based on uploaded images. It provides insights into ingredients, calorie estimates, and general dietary advice.

## Features

- **Image Analysis**: Upload food images to get insights on calorie content.
- **Nutritional Breakdown**: Receive details on calories, possible ingredients, and nutrient distribution (carbohydrates, fats, vitamins, etc.).
- **Portion Size Input**: Specify the portion size for more accurate estimates.
- **Dietary Advice**: Get tips on achieving a balanced diet and improving overall health.

## Technologies Used

- **Streamlit**: For building the user interface.
- **Google Gemini 1.5 Pro**: For analyzing and generating content from images.
- **Pillow (PIL)**: For image processing.
- **Python Libraries**: `dotenv`, `os`, `io`, `base64`.

## Installation

1. Clone the repository:
```bash
git clone https://github.com/shruti23-ui/Calories-Advisor-App.git
```
2. Navigate to the project directory:
```bash
cd Calories-Advisor-App
```
3. Set up a virtual environment:
```bash
python -m venv venv
```
4. Activate the virtual environment:
```bash
venv\Scripts\activate
```
5. Install the required packages:
```bash
pip install -r requirements.txt
```

## Usage

1. Make sure you have a `.env` file with your `GOOGLE_API_KEY` set.
2. Run the Streamlit app:
```bash
streamlit run app.py
```
3. Open the provided URL in your browser.
4. Upload a food image and enter the portion size to get nutritional insights.

## Contribution

Feel free to contribute by opening issues or submitting pull requests.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

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