The OCR process runs in parallel and is CPU intensive. It takes 3 minutes on my dual-core laptop to extract a 20 seconds video. You may want more cores for longer videos.
The language of the subtitles. You can extract subtitles in almost any language. All language codes on [this page](https://github.com/tesseract-ocr/tesseract/wiki/Data-Files#data-files-for-version-400-november-29-2016) (e.g. `'eng'` for English) and all script names in [this repository](https://github.com/tesseract-ocr/tessdata_fast/tree/master/script) (e.g. `'HanS'` for simplified Chinese) are supported.
Note that you can use more than one language. For example, `'hin+eng'` means using Hindi and English together for recognition. More details are available in the [Tesseract documentation](https://github.com/tesseract-ocr/tesseract/wiki/Command-Line-Usage#using-multiple-languages).
Language data files will be automatically downloaded to your `$HOME/tessdata` directory when necessary. You can read more about Tesseract language data files on their [wiki page](https://github.com/tesseract-ocr/tesseract/wiki/Data-Files).
Extract subtitles from only a part of the video. The subtitle timestamps are still calculated according to the full video length.
-`conf_threshold`
Confidence threshold for word predictions. Words with lower confidence than this threshold are discarded. The default value is fine for most cases.
Make it closer to 0 if you get too few words from the predictions, or make it closer to 100 if you get too many excess words.
-`sim_threshold`
Similarity threshold for subtitle lines. Neighbouring subtitles with larger [Levenshtein](https://en.wikipedia.org/wiki/Levenshtein_distance) ratios than this threshold will be merged together. The default value is fine for most cases.
By default, only the bottom half of each frame is used for OCR. You can explicitly use the full frame if your subtitles are not within the bottom half of each frame.