Extract Hardsub From Video

This script assumes you have a basic understanding of Python and access to FFmpeg.

Extracting (text burned directly into the video frames) requires Optical Character Recognition (OCR) because the text isn't stored as a separate data track. Best Tools for Hardsub Extraction

A simple Python script using pytesseract can loop through the saved images, extract the text, and format it into a text document or basic SRT structure. Tips for Maximizing OCR Accuracy extract hardsub from video

Load your video into VideoSubFinder. Run the "Search Text" feature. The software will create a folder full of images containing only the cleaned-up subtitle text with completely black backgrounds.

Since hardsubs are burned into the video frames (not a separate stream), you can’t just extract them like soft subtitles. Instead, you need . This script assumes you have a basic understanding

Many open-source developers have created wrappers for this exact workflow, such as or scikit-video scripts found on GitHub. The underlying technical process follows these phases:

Replace w:h:x:y with the width, height, and coordinate positions of the subtitle box. Tips for Maximizing OCR Accuracy Load your video

For those comfortable with the command line, you can build a custom pipeline using (to extract frames) and Tesseract (to perform OCR). This gives you maximum control.

With the tools and techniques in this guide, you can now tackle almost any hardsubbed video and free its text from the pixels.

To extract hardsubs, software must perform two distinct tasks: