/Video-to-pdf-converter

A solution capable of capturing frames from a video source, performing optical flow analysis to track and visualize the page flipping movements within the document and apply image processing techniques to extract and create the pdf document

Primary LanguagePython

Video to PDF Converter

Overview

This project focuses on extracting pages from a video where a book's pages are flipped one by one. The captured frames with visible pages are then used to create a PDF containing all the book pages.

Project Workflow

  1. Video Input: Provide a video file (*.mp4) where a book's pages are being flipped. The video can have some hand motion and camera movements.

  2. Page Capture:

    • Detect significant changes between consecutive frames to identify page flips.
    • Capture frames when a page flip is detected and when the page is stable for better visibility.

  3. Page Extraction:

    • Use computer vision techniques to extract the page from the captured frames.
    • Remove background noise and distortion to isolate the page.

  4. PDF Generation:

    • Save the extracted pages as images.
    • Create a PDF containing all the extracted pages.

Usage

  1. Clone this repository to your local machine:

    git clone https://github.com/yourusername/book-page-extraction.git

  2. Install the required libraries:

    pip install opencv-python-headless reportlab numpy Pillow

  3. Place your video file (*.mp4) in the project directory.

  4. Modify the video_path variable in main.py to point to your video file.

  5. Run the script: pyton video_to_pdf.py

  6. Once the script finishes, you will find the extracted pages in the project directory as JPEG images (saved_frame_*.jpg) and a PDF file (content_pdf_1.pdf) containing all the pages

Dependencies

  • OpenCV: For computer vision tasks such as frame extraction and page detection.
  • ReportLab: For generating PDF files.
  • NumPy: For numerical operations.
  • Pillow: For image processing.

Notes

  • Adjust the threshold values and parameters in the code according to the specific characteristics of your video.
  • Ensure proper lighting and stable camera setup for better results.
  • For detailed explanations and optimizations of the code, refer to the video_to_pdf.py file.