📊 Snapsheet - Attendance Sheet Image to SpreadSheet Converter

This project allows users to upload an image containing a table, extract the data using Google's Gemini AI, and download the extracted data as an Excel file. It consists of a Flutter frontend for image selection and file download, and a Node.js backend for processing the image and generating the Excel file.

✨ Features

• 📷 Image Upload: Select an image from your device.
• 🤖 AI-Powered Data Extraction: Use Google's Gemini AI to extract table data from the image.
• 👥 Excel Download: Download the extracted data as an Excel file.
• ⚠️ Error Handling: Robust error handling for invalid inputs and API failures.

🛠️ Tech Stack

Frontend (Flutter)

• 📱 Flutter: For building the cross-platform mobile app.
• 🌐 http: For making API requests to the backend.
• 🖼️ image_picker: For selecting images from the device.
• 💾 file_saver: For saving the Excel file to the device.

Backend (Node.js)

• ✨ Express.js: For handling HTTP requests.
• 🤓 Google Generative AI: For extracting table data from images.
• 📚 ExcelJS: For generating Excel files.
• 🔒 dotenv: For managing environment variables.
• 🌍 cors: For enabling cross-origin requests.

⚙️ Setup Instructions

Prerequisites

• Flutter SDK: Install Flutter from flutter.dev.
• Node.js: Install Node.js from nodejs.org.
• Google Gemini API Key: Obtain an API key from Google AI Studio.

Backend Setup

1. Clone the repository:

   git clone https://github.com/your-repo/table-data-extractor.git
   cd table-data-extractor/backend

2. Install dependencies:

   npm install

3. Create a .env file in the backend directory and add your Gemini API key:

   GEMINI_API_KEY=your_api_key_here
   PORT=3000

4. Start the backend server:

   npm start

   The backend will run at http://localhost:3000.

Frontend Setup

1. Navigate to the frontend directory:

   cd ../frontend

2. Install dependencies:

   flutter pub get

3. Update the backend URL in lib/home_page.dart:

   final url = Uri.parse('http://localhost:3000/extract_data');

4. Run the Flutter app:

   flutter run

📰 API Endpoints

POST /extract_data

• Description: Extracts table data from an image and returns an Excel file.
• Request Body:

  {
    "image": "base64_encoded_image"
  }

• Response:
  • Success: Excel file (application/vnd.openxmlformats-officedocument.spreadsheetml.sheet).
  • Error: JSON with error message.

💪 Contributing

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Commit your changes:

   git commit -m "Add your feature"

4. Push to the branch:

   git push origin feature/your-feature-name

5. Open a pull request.

❓ Support

For issues or questions, please open an issue on the GitHub repository.

Enjoy extracting table data with ease! 🚀

📧 Contact & Support

For questions, feel free to open an issue or contact me at chinmayjoshi003@gmail.com 📩

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