---
title: Food Label Analyzer
emoji: 💻
colorFrom: green
colorTo: purple
sdk: streamlit
sdk_version: 1.38.0
app_file: app.py
pinned: false
license: apache-2.0
---
# LabelWise: An AI-powered Food Label Analyzer

[Visit the live app here!](https://deadshot2003-food-label-analyzer.hf.space)

**LabelWise** is an intelligent tool that helps users make informed food choices by analyzing product labels based on their individual health profiles. By using cutting-edge AI, the app evaluates the nutritional content of products and provides users with a personalized health rating, helping them align their food consumption with their health goals.

## Features

- **User Registration and Profile Setup**: 
  - Register by providing your name, email, password, age, height, weight (BMI auto-calculated), health conditions, allergies, activity level, food preferences, and health goals.
  - Edit your profile anytime to ensure recommendations are always relevant.

- **Login and Personal Dashboard**: 
  - Secure login with email and password. Access your personalized dashboard with options to edit your profile, analyze products, and more.

- **AI-Powered Label Analysis**: 
  - Upload the back label of any product, and our AI model analyzes it against your health profile.
  - Get instant feedback including a health rating based on nutritional data and your individual preferences.

- **Database Recognition**: 
  - If the product is already in our database, get instant access to its details.
  - If it's new, answer two simple questions: product type and consumption frequency.

- **Multilingual Support**: 
  - Translate AI analysis into any world language and most Indian regional languages for easy comprehension.

- **Health Ratings**: 
  - Receive a personalized health rating for each product based on your profile and its nutritional content.

- **Logout**: 
  - Easily logout and secure your information when done.

give the whole thing is a .md file format like install dependencies then enviorment setup, running the application


 # LabelWise: Getting Started Guide



## 1. Clone the Repository

To get started, clone the LabelWise repository to your local machine:

```sh
git clone https://github.com/yourusername/LabelWise.git
cd LabelWise
```
##2. Install Dependencies
Ensure you have Python installed on your system. Then, install the required Python packages using pip:
```sh
pip install -r requirements.txt
```
3. Environment Setup
LabelWise requires some environment variables to be set up for MongoDB Atlas and other API keys.

Create a .env file in the root directory of your project. Add your MongoDB connection string and any other necessary secret keys to the .env file.

Example .env file contents:

```sh
MONGODB_URI=your_mongodb_uri
SECRET_KEY=your_secret_key
```
4. Running the Application
Once you've completed the setup and installed all required dependencies, you can run the LabelWise application using Streamlit:

```sh
streamlit run app.py
```
This command will start the application and open it in your default web browser.

Feel free to reach out if you have any questions or need further assistance.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference