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Metadata-Version: 2.1 | |
Name: videocr | |
Version: 0.1.6 | |
Summary: Extract hardcoded subtitles from videos using machine learning | |
Home-page: https://github.com/apm1467/videocr | |
Author: Yi Ge | |
Author-email: me@yige.ch | |
License: MIT | |
Download-URL: https://github.com/apm1467/videocr/archive/v0.1.6.tar.gz | |
Description: # videocr | |
Extract hardcoded (burned-in) subtitles from videos using the [Tesseract](https://github.com/tesseract-ocr/tesseract) OCR engine with Python. | |
Input a video with hardcoded subtitles: | |
<p float="left"> | |
<img width="430" alt="screenshot" src="https://user-images.githubusercontent.com/10210967/56873658-3b76dd00-6a34-11e9-95c6-cd6edc721f58.png"> | |
<img width="430" alt="screenshot" src="https://user-images.githubusercontent.com/10210967/56873659-3b76dd00-6a34-11e9-97aa-2c3e96fe3a97.png"> | |
</p> | |
```python | |
# example.py | |
from videocr import get_subtitles | |
if __name__ == '__main__': # This check is mandatory for Windows. | |
print(get_subtitles('video.mp4', lang='chi_sim+eng', sim_threshold=70, conf_threshold=65)) | |
``` | |
`$ python3 example.py` | |
Output: | |
``` | |
0 | |
00:00:01,042 --> 00:00:02,877 | |
喝 点 什么 ? | |
What can I get you? | |
1 | |
00:00:03,044 --> 00:00:05,463 | |
我 不 知道 | |
Um, I'm not sure. | |
2 | |
00:00:08,091 --> 00:00:10,635 | |
休闲 时 光 … | |
For relaxing times, make it... | |
3 | |
00:00:10,677 --> 00:00:12,595 | |
三 得 利 时 光 | |
Bartender, Bob Suntory time. | |
4 | |
00:00:14,472 --> 00:00:17,142 | |
我 要 一 杯 伏特 加 | |
Un, I'll have a vodka tonic. | |
5 | |
00:00:18,059 --> 00:00:19,019 | |
谢谢 | |
Laughs Thanks. | |
``` | |
## Performance | |
The OCR process is CPU intensive. It takes 3 minutes on my dual-core laptop to extract a 20 seconds video. More CPU cores will make it faster. | |
## Installation | |
1. Install [Tesseract](https://github.com/tesseract-ocr/tesseract/wiki) and make sure it is in your `$PATH` | |
2. `$ pip install videocr` | |
## API | |
1. Return subtitle string in SRT format | |
```python | |
get_subtitles( | |
video_path: str, lang='eng', time_start='0:00', time_end='', | |
conf_threshold=65, sim_threshold=90, use_fullframe=False) | |
``` | |
2. Write subtitles to `file_path` | |
```python | |
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) | |
``` | |
### Parameters | |
- `lang` | |
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, e.g. `lang='hin+eng'` for Hindi and English together. | |
Language files will be automatically downloaded to your `~/tessdata`. You can read more about Tesseract language data files on their [wiki page](https://github.com/tesseract-ocr/tesseract/wiki/Data-Files). | |
- `conf_threshold` | |
Confidence threshold for word predictions. Words with lower confidence than this value will be discarded. The default value `65` is fine for most cases. | |
Make it closer to 0 if you get too few words in each line, or make it closer to 100 if there are too many excess words in each line. | |
- `sim_threshold` | |
Similarity threshold for subtitle lines. Subtitle lines with larger [Levenshtein](https://en.wikipedia.org/wiki/Levenshtein_distance) ratios than this threshold will be merged together. The default value `90` is fine for most cases. | |
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. | |
- `time_start` and `time_end` | |
Extract subtitles from only a clip of the video. The subtitle timestamps are still calculated according to the full video length. | |
- `use_fullframe` | |
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. | |
Platform: UNKNOWN | |
Classifier: Development Status :: 3 - Alpha | |
Classifier: Intended Audience :: Developers | |
Classifier: License :: OSI Approved :: MIT License | |
Classifier: Programming Language :: Python :: 3 | |
Classifier: Programming Language :: Python :: 3.7 | |
Description-Content-Type: text/markdown | |