SmartReceiptParser

It extracts text from an image of a store receipt and converts it into a structured JSON object using OCR (Tesseract), OpenCV, and Gemini AI.

Requirements

• Python 3.x
• OpenCV
• pytesseract
• openai-agents
• Tesseract-OCR (must be installed separately and added to your system PATH)

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Install the required Python packages:

   pip install -r requirements.txt

3. Install Tesseract-OCR (separately):

   • Download and install from Tesseract at UB Mannheim.
   • Add the Tesseract install directory (e.g., C:\Program Files\Tesseract-OCR) to your system PATH.
   • Test installation with:

     tesseract --version

4. Set up your Gemini API key:

   • Create a .env file in the project root:

     GEMINI_API_KEY=your_gemini_api_key_here
     

Usage

1. Add a receipt image
   Place your receipt image (e.g., receipt2.png) in the raw_receipts folder.

2. Run the script:

   python main.py

3. Output:

   • The extracted text will be printed to the console.
   • The structured JSON will be saved to json_receipt/receipt.json (full path will be shown after running).

Project Structure

• main.py: Main script for image processing, OCR, and AI extraction.
• llm_setup.py: Gemini AI model setup and configuration.
• raw_receipts/: Place your input receipt images here.
• json_receipt/: Output folder for generated JSON files.
• requirements.txt: Python dependencies.
• readme.md: Project documentation.

Troubleshooting

• Tesseract not found:
  Ensure Tesseract-OCR is installed and its path is added to your system PATH. Test with tesseract --version in your terminal.
• No internet connection:
  Gemini AI requires an active internet connection.
• API key errors:
  Make sure your .env file is present and contains a valid GEMINI_API_KEY.