OCR Document Processing System

A robust document processing system that handles various file formats including PDFs, images, emails, and office documents. The system extracts text content and converts documents to searchable PDFs.

Features

• Multi-format Support: Processes various document types:

  • PDF files
  • Images (PNG, JPG, TIFF, BMP, WEBP)
  • Email files (EML, MSG)
  • Office documents (DOC, DOCX, PPTX, XLSX)
  • Text files (TXT, RTF, JSON)
  • Media files (MP4, MP3, WAV, GIF)

• Advanced OCR Capabilities:

  • Automatic rotation correction
  • Image preprocessing for better OCR results
  • Support for partially OCRed documents
  • Text quality assessment

• Email Processing:

  • Full message body extraction
  • Attachment handling
  • Proper encoding support
  • HTML to text conversion

• Parallel Processing:

  • Multi-threaded document processing
  • Configurable number of workers
  • Progress tracking and logging

Requirements

• Python 3.8+
• Tesseract OCR
• Required Python packages (install via pip install -r requirements.txt):
  • pytesseract
  • opencv-python
  • pandas
  • python-docx
  • python-pptx
  • extract-msg
  • ocrmypdf
  • reportlab
  • beautifulsoup4
  • pywin32
  • pydub
  • SpeechRecognition

Installation

1. Install Tesseract OCR:

   • Windows: Download from Tesseract GitHub
   • Set path in config.py if different from default

2. Clone the repository:

   git clone https://github.com/way-wise/OCR.git
   cd OCR

3. Install dependencies:

   pip install -r requirements.txt

Configuration

Edit config.py to set:

• NUM_WORKERS: Number of parallel processing workers
• OUTPUT_DIR: Directory for processed files
• TESSERACT_PATH: Path to Tesseract OCR executable

Usage

1. Place documents to process in the input directory
2. Run the main script:

   python main.py

3. Processed files will be saved in the output directory
4. Results are logged in processing.log

Output

• Converted PDF files in the output directory
• CSV files containing:
  • output_mapping.csv: Mapping of original to converted files
  • processing_errors.csv: Any errors encountered during processing

Error Handling

• Comprehensive error logging
• Retry mechanism for file operations
• Alternative save locations for permission issues
• Detailed error reporting in CSV format

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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