forked from pradana.aumars/videocr
105 lines
3.7 KiB
Markdown
105 lines
3.7 KiB
Markdown
# videocr
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Extract hardcoded subtitles from videos using the [Tesseract](https://github.com/tesseract-ocr/tesseract) OCR engine with Python.
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Input a video with hardcoded subtitles:
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<p float="left">
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<img width="430" alt="screenshot" src="https://user-images.githubusercontent.com/10210967/56873658-3b76dd00-6a34-11e9-95c6-cd6edc721f58.png">
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<img width="430" alt="screenshot" src="https://user-images.githubusercontent.com/10210967/56873659-3b76dd00-6a34-11e9-97aa-2c3e96fe3a97.png">
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</p>
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```python
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import videocr
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print(videocr.get_subtitles('video.avi', lang='chi_sim+eng', sim_threshold=70))
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```
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Output:
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```
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0
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00:00:01,042 --> 00:00:02,877
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喝 点 什么 ?
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What can I get you?
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1
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00:00:03,044 --> 00:00:05,463
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我 不 知道
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Um, I'm not sure.
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2
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00:00:08,091 --> 00:00:10,635
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休闲 时 光 …
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For relaxing times, make it...
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3
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00:00:10,677 --> 00:00:12,595
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三 得 利 时 光
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Bartender, Bob Suntory time.
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4
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00:00:14,472 --> 00:00:17,142
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我 要 一 杯 伏特 加
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Un, I'll have a vodka tonic.
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5
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00:00:18,059 --> 00:00:19,019
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谢谢
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Laughs Thanks.
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```
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## Performance
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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.
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## API
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```python
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videocr.get_subtitles(
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video_path: str, lang='eng', time_start='0:00', time_end='',
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conf_threshold=65, sim_threshold=90, use_fullframe=False)
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```
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Return the subtitles string in SRT format.
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```python
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videocr.save_subtitles_to_file(
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video_path: str, file_path='subtitle.srt', lang='eng', time_start='0:00',
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time_end='', conf_threshold=65, sim_threshold=90, use_fullframe=False)
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```
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Write subtitles to `file_path`. If the file does not exist, it will be created automatically.
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### Parameters
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- `lang`
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The language of the subtitles in the video. 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.
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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).
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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).
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- `time_start` and `time_end`
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Extract subtitles from only a part of the video. The subtitle timestamps are still calculated according to the full video length.
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- `conf_threshold`
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Confidence threshold for word predictions. Words with lower confidence than this threshold are discarded. The default value is fine for most cases.
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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.
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- `sim_threshold`
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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.
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Make it closer to 0 if you get too many duplicated subtitle lines, or make it closer to 100 if you get too few subtitle lines.
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- `use_fullframe`
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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.
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