| Crates.io | vobsubocr |
| lib.rs | vobsubocr |
| version | 0.1.0 |
| created_at | 2022-07-06 01:59:54.703265+00 |
| updated_at | 2022-07-06 01:59:54.703265+00 |
| description | Converts DVD VOB subtitles to SRT subtitles with Tesseract OCR |
| homepage | https://github.com/elizagamedev/vobsubocr/ |
| repository | https://github.com/elizagamedev/vobsubocr/ |
| max_upload_size | |
| id | 620162 |
| size | 137,544 |
vobsubocr is a blazingly fast and accurate DVD VobSub to SRT subtitle conversion tool.
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.
This package is not on crates.io yet, so you will have to clone and build with
cargo. You will need to have Tesseract's development libraries installed; see
the leptess readme for more details.
# 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
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.
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.