📊 Excel-It

Convert PDF documents to Excel spreadsheets with ease. Excel-It intelligently extracts tables and text from PDFs using advanced table detection and OCR capabilities.

✨ Features

• 🎯 Smart Table Detection - Automatically extracts tables from PDF documents
• 📄 Multi-Method Extraction - Uses camelot, pdfplumber, and OCR for maximum compatibility
• 🔄 Fallback Pipeline - Seamlessly switches between extraction methods if one fails
• 📊 Excel Export - Converts extracted tables to formatted Excel spreadsheets
• 🚀 Easy to Use - Simple API with minimal configuration required

🛠️ Tech Stack

• PDF Processing: Camelot, pdfplumber
• OCR: Tesseract, pytesseract
• Data Processing: Pandas
• Excel Export: openpyxl
• Image Processing: OpenCV, Pillow

📋 Requirements

Before installation, ensure you have:

• Python 3.8 or higher
• Tesseract OCR (for OCR functionality)

Installing Tesseract OCR

Windows

1. Download the installer from here
2. Run the installer and follow the setup wizard
3. Note the installation path (default: C:\Program Files\Tesseract-OCR)

macOS

brew install tesseract

Linux (Ubuntu/Debian)

sudo apt-get install tesseract-ocr

🚀 Installation

1. Clone the repository

   git clone https://github.com/rachit404/excel-it.git
   cd excel-it

2. Create a virtual environment (recommended)

   # On Windows
   python -m venv venv
   venv\Scripts\activate
   
   # On macOS/Linux
   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Configure Tesseract path (Windows only)

   If you installed Tesseract to a non-default location, edit main.py and add:

   import pytesseract
   pytesseract.pytesseract.pytesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

📖 Quick Start

Basic Usage

1. Place your PDF file in the input/ folder
2. Update the filename in main.py:

   PDF_FILE = "input/your_file.pdf"

3. Run the script:

   python main.py

4. Find your Excel file in the output/ folder

Example

from src.extract_tables import extract_tables
from src.export_excel import export_tables

# Extract tables from PDF
tables = extract_tables("input/document.pdf")

# Export to Excel
export_tables(tables, "output/result.xlsx")

📁 Project Structure

excel-it/
├── main.py                 # Entry point
├── requirements.txt        # Python dependencies
├── README.md              # This file
├── input/                 # Place PDF files here
├── output/                # Extracted Excel files saved here
└── src/
    ├── extract_tables.py   # Table extraction module
    ├── pdf_utils.py        # PDF utility functions
    ├── ocr_pipeline.py     # OCR processing pipeline
    └── export_excel.py     # Excel export functionality

🔍 How It Works

Excel-It uses a three-tier extraction pipeline:

1. Camelot-Based Detection - First attempts to extract tables using advanced table detection
2. Text-Based Extraction - Falls back to pdfplumber for text-based PDFs
3. OCR Processing - Uses Tesseract OCR as a final fallback for scanned documents

This ensures maximum compatibility with various PDF formats and quality.

⚙️ Troubleshooting

"pytesseract.TesseractNotFoundError"

• Windows: Verify Tesseract is installed and update the path in main.py
• macOS/Linux: Run which tesseract to verify installation

"No tables found"

• Ensure your PDF contains structured tables
• Check PDF file format and quality
• For scanned PDFs, OCR will be used automatically

Module import errors

• Verify virtual environment is activated
• Run pip install -r requirements.txt again

🤝 Contributing

Contributions are welcome! Feel free to:

• Report bugs
• Suggest features
• Submit pull requests

📝 License

This project is licensed under the MIT License - see LICENSE file for details.

📧 Support

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

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Made with ❤️ by rachit404