Image-to-Editable-PDF Converter

A robust, professionally structured Python-based web application (Flask) that performs asynchronous Optical Character Recognition (OCR) on uploaded documents, allows text editing, and converts the final content into a secure, downloadable, multi-page PDF.

Author

Marjory D. Marquez

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Project Image

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Key Features and Improvements

The project has been significantly enhanced for better document handling:

Core Functionality

• Asynchronous OCR: Uses Python Threading to handle long-running OCR tasks in the background, ensuring the web interface remains responsive and can be polled for job status.
• Language Detection & Correction: Automatically detects the source document's language and applies Spell Checking to the OCR output for superior accuracy.
• Robust Document Scanning: Supports single-page images (PNG, JPG) and multi-page documents (PDF, TIFF).
• Reliable OCR: Uses the powerful Tesseract engine for accurate text extraction.
• Zero-Dependency PDF/TIFF Rendering: Uses PyMuPDF (fitz) to reliably process multi-page PDF and TIFF files without requiring external dependencies like Ghostscript.

Security & Project Structure

• Secure File Handling: Implemented in security.py to prevent directory traversal attacks and sanitize all filenames.
• Rate Limiting: Protects the resource-intensive /upload endpoint using Flask-Limiter to prevent abuse.
• Modular Architecture: Code is professionally organized into dedicated modules (utils.py, security.py) and uses a robust, environment-aware Configuration Class (config.py).
• Automatic Cleanup: Files in the uploads directory are automatically deleted after a set time (default: 1 hour) to manage disk space.
• Unit Testing & CI: Includes a comprehensive test_ocr.py file and a GitHub Actions workflow for Continuous Integration.

Output & Testing

• Multi-Page PDF Generation: Converts the final, edited text, preserving page breaks, into a clean PDF using fpdf.

Prerequisites

• Python 3.8+

• Tesseract OCR: Must be installed on your system and accessible via the command line.

• Installation: Follow the instructions for your OS (e.g., sudo apt install tesseract-ocr on Debian/Ubuntu).

  • Configuration: If Tesseract is not in your system PATH, you may need to set the TESSERACT_CMD environment variable.

Required Python Libraries

All necessary Python libraries can be installed using pip from the project's requirements.txt file:

pip install -r requirements.txt


## Setup and Run

1. Clone the Repository

Bash

git clone https://github.com/YourUsername/ImageToPDF_App.git cd ImageToPDF_App

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2. Configure Environment

Create a file named .env in the root directory and set the following variables.

Crucial: Use a strong, random key for FLASK_SECRET_KEY in any non-development environment.

The FLASK_ENV controls which configuration settings (Development, Testing, or Production) are loaded via config.py.

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Code snippet

.env file content

FLASK_ENV="development" FLASK_SECRET_KEY="A_VERY_LONG_RANDOM_KEY_HERE"

Optional: Path to Tesseract if not in system PATH

TESSERACT_CMD="/usr/bin/tesseract"

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3. Install Dependencies

Ensure your virtual environment is active, then install the required Python packages: Bash

pip install -r requirements.txt

4. Access the App

Open your web browser and navigate to:

http://127.0.0.1:5000

Running Tests

Verify the project's integrity by running the unit tests: Bash

python test_ocr.py -v