diff --git a/README.md b/README.md index e116f2a..967ec80 100644 --- a/README.md +++ b/README.md @@ -1,16 +1,18 @@ # videocr -screenshot +Extract hardcoded subtitles from videos using the [Tesseract](https://github.com/tesseract-ocr/tesseract) OCR engine with Python. -screenshot +Input video with hardcoded subtitles: -screenshot +

+ screenshot + screenshot +

-``` +```python import videocr print(videocr.get_subtitles('video.avi', lang='HanS')) - ``` Output: @@ -46,3 +48,47 @@ Un, I'll have a vodka tonic. Laughs Thanks. ``` + +## API + +```python +videocr.get_subtitles( + video_path: str, lang='eng', time_start='0:00', time_end='', + conf_threshold=65, sim_threshold=90, use_fullframe=False) +``` +Return the subtitles string in SRT format. + + +```python + +videocr.save_subtitles_to_file( + video_path: str, file_path='subtitle.srt', lang='eng', time_start='0:00', + time_end='', conf_threshold=65, sim_threshold=90, use_fullframe=False) +``` +Write subtitles to `file_path`. If the file does not exist, it will be created automatically. + +## Adjustable Parameters + +- `lang` + + Language of the subtitles in the video. + +- `time_start` and `time_end` + + 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. + + Make it closer to 0 if you get too few subtitle lines, or make it closer to 100 if you get too many duplicated subtitles. + +- `use_fullframe` + + By default, only the bottom half of each frame is used for OCR in order to reduce errors. You can explicitly make the algorithm handle the full frame.