vobsubocr

vobsubocr is a blazingly fast and accurate DVD VobSub to SRT subtitle conversion tool.

Background

DVD subtitles are unfortunately encoded essentially as a series of images. This presents problems when needing a text representation of the subtitle, e.g. for language learning. vobsubocr can alleviate this problem by generating SRT subtitles from an input VobSub file, leveraging the power of Tesseract.

Installation

Install the latest release with cargo:

cargo install vobsubocr

Or alternatively, install the development version from git:

cargo install --git https://github.com/elizagamedev/vobsubocr

You will need to have Tesseract's development libraries installed; see the leptess readme for more details. If you use Nix, the provided shell.nix provides an environment with all of the necessary dependencies.

Usage

# Convert simplified Chinese vobsub subtitles and print them to stdout.
vobsubocr -l chi_sim shrek_chi.idx

# Convert English vobsub subtitles and write them to a file named "shrek_eng.srt".
vobsubocr -l eng -o shrek_eng.srt shrek_eng.idx

We can also specify more advanced configuration options for Tesseract with -c.

# Convert subtitles and blacklist the specified characters from being (mistakenly) recognized.
vobsubocr -l eng -c tessedit_char_blacklist='|\/`_~' shrek_eng.idx

How does it work/compare to similar tools?

The most comparable tool to vobsubocr is VobSub2SRT, but vobsubocr has significantly better output, especially for non-English languages, mainly because VobSub2SRT does not do much preprocessing of the image at all before sending it to Tesseract. For example, Tesseract 4.0 expects black text on a white background, which VobSub2SRT does not guarantee, but vobsubocr does. Additionally, vobsubocr splits each line into separate images to take advantage of page segmentation method 7, which greatly improves accuracy of non-English languages in particular.

Official documentation on how to improve accuracy of Tesseract output can be viewed here.

Miscellaneous Notes

From my understanding, the chi_sim and chi_tra Tesseract models work on both simplified and traditional Chinese text, but automatically convert said text to their respective forms.