Multi Language Invoice Extractor

Multi-Language Invoice Extractor

Access the application here: Multi-Language Invoice Extractor

This project aims to extract and understand content from multi-language invoices using Google Generative AI (Gemini Model). This reduces the need for traditional OCR methods such as Tesseract and OpenCV.

Installation

Step 1: Clone the Repository

git clone https://github.com/yourusername/invoice-extractor.git
cd invoice-extractor

Step 2: Create the Conda Environment

Create a new Conda environment with Python 3.10.

conda create -p venv python==3.10 -y

Step 3: Activate the Environment

Activate the Conda environment.

conda activate "/Users/vallirajasekar/Desktop/gemini/Invoice Extractor/venv"

Step 4: Install Dependencies

Install the required dependencies.

pip install -r requirements.txt

Usage

1. Set Up API Key: Make sure to set up your Google Generative AI API key. You can store it in a .env file in the root directory of your project:

   GOOGLE_API_KEY=your_google_api_key
   

2. Run the Streamlit Application: Start the Streamlit application by running:

   streamlit run app.py

3. Upload an Invoice:

   • Open the Streamlit app in your web browser.
   • Input your prompt in the text box.
   • Upload an invoice image (supports .jpg, .jpeg, .png formats).
   • Click on the "Tell me about the Invoice" button to get the extracted information.

Description

The Multi-Language Invoice Extractor project is designed to simplify the extraction of information from invoices in various languages. Traditional methods like Tesseract OCR and OpenCV require extensive preprocessing and are limited by the quality of the image and language support. By leveraging the power of Google Generative AI (Gemini Model), this project aims to directly understand and extract information from invoice images.

Key Features:

• Multi-Language Support: Capable of understanding invoices in different languages.
• AI-Powered: Utilizes Google Generative AI to process the content, reducing the need for traditional OCR.
• Easy to Use: Simple web interface to upload images and get results.

How It Works:

1. Input Prompt: The user provides a prompt describing the task (e.g., "Extract invoice details").
2. Image Upload: The user uploads an image of the invoice.
3. AI Processing: The image and prompt are sent to the Google Generative AI model, which processes the image and returns the extracted content.

Acknowledgements

This project uses the following technologies:

• Streamlit: An open-source app framework for Machine Learning and Data Science.
• Google Generative AI: API for advanced AI models.

Notes

• Ensure you have the necessary API key from Google Cloud for accessing the Generative AI services.
• This project is intended for educational and experimental purposes.

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