PDF-to-Word-Conversion

Description

The PDF-to-Word-Conversion project is designed to convert pages of a PDF document into separate pages of a Microsoft Word document while adhering to specific technical requirements. The project employs two main processing strategies: using the Google Cloud Vision API for text extraction and local processing with PyMuPDF and Tesseract.

Tech Stack

• Google Cloud Vision API: For extracting text from images.
• PyMuPDF: For working with PDF documents.
• Tesseract OCR: For recognizing text in images.
• pdf2image: For converting PDF pages into images.
• Pillow: For image processing.
• python-docx: For creating and editing Word documents.
• tqdm: For displaying progress.
• Flake8: For linting.
• Pytest: For tests.

Installation

1. Clone the repository:

   git clone https://github.com/AlexTkDev/PDF-to-Word-Conversion.git
   cd PDF-to-Word-Conversion

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # For Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

   Note: Ensure that Google Cloud SDK and Tesseract OCR are installed and configured.

4. Set up Google Cloud Vision API:

   • Obtain a Google Cloud credentials file (JSON format).
   • Set the path to this file in the environment variable GOOGLE_APPLICATION_CREDENTIALS.

5. Setting up Tesseract OCR:

   • For Windows:

     • Download the Tesseract OCR installer from the official repository or source.
     • Run the installer and follow the instructions.
     • Add the path to Tesseract in the PATH environment variable (e.g., C:\Program Files\Tesseract-OCR).

   • For macOS:

     • Use Homebrew to install Tesseract. Open a terminal and run:

       brew install tesseract

   • For Linux:

     • Install Tesseract using a package manager. For example, on Ubuntu:

       sudo apt-get update
       sudo apt-get install tesseract-ocr

   • Installing Language Packages:

     • To add additional language packages, follow the instructions for your operating system.

   • Using in Python:

     • Install the pytesseract library:

       pip install pytesseract

     • Ensure that pytesseract knows where Tesseract is installed:

     import pytesseract
         # Specify the path to Tesseract if it's not in PATH
      pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
         # for Windows

6. Run the scripts:

   • To process PDF using Google Cloud Vision API:

     python PDF_processing_with_Google_Cloud_Vision_API.py

   • To process PDF locally using PyMuPDF and Tesseract:

     python processing_PDF_locally.py

Running tests

• To run tests, use the command:

 pytest tests/

Linting

• To check your code for standards compliance, use Flake8. Run the command:

flake8 PDF_processing_with_Google_Cloud_Vision_API.py processing_PDF_locally.py --show-source --statistics
flake8 PDF_processing_with_Google_Cloud_Vision_API.py processing_PDF_locally.py --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics

Notes

• In the script PDF_processing_with_Google_Cloud_Vision_API.py, replace 'path_to_your_google_credentials.json' with the path to your Google Cloud credentials file.
• In the script processing_PDF_locally.py, replace 'Open Project 100 images.pdf' with the path to your PDF document.

Project Structure

• PDF_processing_with_Google_Cloud_Vision_API.py: Script for extracting text from images using Google Cloud Vision API and creating a Word document.
• processing_PDF_locally.py: Script for extracting text from images using Tesseract and creating a Word document.

Contributing

• If you want to make changes to the project, fork the repository, make your changes, and create a Pull Request.

License

This project is licensed under the MIT License.