Image to DOCX Converter

A web application that converts images of documents into editable .docx files using Azure Cognitive Services.

Table of Contents

• Introduction
• Features
• Prerequisites
• Installation
• Configuration
• Running the Application
• Accessing the Application
• Usage
• Security Considerations
• Troubleshooting
• License

Introduction

This application allows users to upload images of documents and converts them into editable Word documents (.docx) using Azure's Optical Character Recognition (OCR) technology.

Features

• Image Upload: Upload images in formats like PNG, JPG, JPEG, BMP, and GIF.
• OCR Processing: Extracts text from images using Azure Cognitive Services.
• DOCX Generation: Converts extracted text into a Word document.
• Responsive UI: Mobile-first design with modern aesthetics.
• Local Network Access: Accessible from other devices on your local network.

Prerequisites

• Python 3.6+
• Azure Account: An active Azure subscription with a Computer Vision resource.
• Azure Cognitive Services SDK: Installed via pip.

Installation

Step 1: Clone the Repository

git clone https://github.com/math-alpha/image-to-docx-converter.git
cd image-to-docx-converter

Step 2: Create and Activate a Virtual Environment (Recommended)

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

Step 3: Install Required Packages

pip install -r requirements.txt

Configuration

Step 1: Create a .env File

Create a .env file in the project root directory with the following content:

AZURE_ENDPOINT=https://your-computer-vision-endpoint.cognitiveservices.azure.com/
AZURE_SUBSCRIPTION_KEY=your_subscription_key
SECRET_KEY=your_secret_key

• Replace https://your-computer-vision-endpoint.cognitiveservices.azure.com/ with your Azure endpoint.
• Replace your_subscription_key with your Azure subscription key.
• Replace your_secret_key with a secure, random string.

Step 2: Create an uploads Directory

mkdir uploads

Running the Application

Using Waitress (Recommended for Windows Users)

python app.py

• This command starts the application using Waitress (if configured), binding it to all network interfaces on port 5000.

Alternative (Development Mode)

If you want to run the application in development mode (not recommended for production):

1. Ensure the app.run() section in app.py is active:

   if __name__ == '__main__':
       app.run(debug=True, host='0.0.0.0', port=5000)

2. Run the application:

   python app.py

Note for Unix-based Systems

If you're using a Unix-based system (like Linux or macOS), you can use Gunicorn:

gunicorn --bind 0.0.0.0:5000 app:app

• Ensure you have Gunicorn installed:

  pip install gunicorn

Accessing the Application

• Local Machine: Open your browser and navigate to http://localhost:5000 or http://127.0.0.1:5000.
• Other Devices on Local Network:
  • Find your local IP address (e.g., 192.168.1.x).
  • On another device connected to the same network, navigate to http://<your_local_ip>:5000.

Usage

1. Open the Application: Navigate to the application's URL.
2. Upload an Image: Click on "Choose Image" to select an image file.
3. Convert: Click on "Convert" to start the OCR process.
4. Download: After processing, the browser will prompt you to download the generated .docx file.

Security Considerations

• Secret Key: Keep your SECRET_KEY and Azure credentials secure. Do not expose them in public repositories.
• HTTPS: For production deployment, serve the application over HTTPS.
• File Handling: The application restricts allowed file types and securely handles uploads to prevent security risks.
• Production Server: Use a production-ready WSGI server (like Waitress or Gunicorn) instead of the Flask development server.

Troubleshooting

• Processing Hangs:
  • Ensure that you have the latest Azure SDK installed.

    pip install --upgrade azure-cognitiveservices-vision-computervision

  • Verify that your Azure credentials are correct in the .env file.
• Access Issues:
  • If you cannot access the app from other devices, check your firewall settings and ensure the server is bound to 0.0.0.0.
• Error Messages:
  • Check the console output for any exceptions or error logs.
  • Ensure all required Python packages are installed and up-to-date.
• Common Errors:
  • AttributeError: Ensure you are using the correct methods compatible with your SDK version.
  • ImportError: Verify that all necessary packages are installed.

License

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

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Testing the App on Local Network

To test the app on your local network:

1. Ensure the Server is Running

   python app.py

2. Find Your Local IP Address

   • Windows: Open Command Prompt and run ipconfig.
   • macOS/Linux: Open Terminal and run ifconfig or ip addr.

3. Access from Another Device

   • Connect your device (phone, tablet, another computer) to the same Wi-Fi/network.
   • Open a web browser and navigate to http://<your_local_ip>:5000.

4. Firewall Considerations

   • Ensure that your firewall allows incoming connections on port 5000.
   • On Windows, you may need to allow python.exe or waitress-serve through the firewall.
   • On macOS/Linux, adjust your firewall settings accordingly.

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Final Notes

• Deployment: For production deployment, consider using a more robust setup with a reverse proxy like Nginx and SSL certificates.
• Testing: Test the application thoroughly to ensure all features work as expected.
• Feedback: If you encounter any issues or have suggestions, feel free to contribute to the repository or open an issue.