https://github.com/devmaxxing/videocr-PaddleOCR
Extract hardcoded subtitles from videos using machine learning
https://github.com/devmaxxing/videocr-PaddleOCR
machine-learning ocr paddleocr paddlepaddle subtitles
Last synced: 11 months ago
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Extract hardcoded subtitles from videos using machine learning
- Host: GitHub
- URL: https://github.com/devmaxxing/videocr-PaddleOCR
- Owner: devmaxxing
- License: mit
- Fork: true (apm1467/videocr)
- Created: 2021-07-16T18:59:01.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2024-07-02T01:17:40.000Z (almost 2 years ago)
- Last Synced: 2024-08-05T09:13:02.102Z (almost 2 years ago)
- Topics: machine-learning, ocr, paddleocr, paddlepaddle, subtitles
- Language: Jupyter Notebook
- Homepage:
- Size: 3.29 MB
- Stars: 127
- Watchers: 4
- Forks: 18
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# videocr
Extract hardcoded (burned-in) subtitles from videos using the [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) OCR engine with Python. A Colab notebook for installing and running this library is included for convenience:
[](https://colab.research.google.com/github/oliverfei/videocr-PaddleOCR/blob/master/videocr_PaddleOCR.ipynb)
## GUI Applications
For user friendly applications that make use of this library, see:
- https://github.com/timminator/VideOCR
## Usage
```python
# example.py
from videocr import save_subtitles_to_file
if __name__ == '__main__':
save_subtitles_to_file('example_cropped.mp4', 'example.srt', lang='ch', time_start='7:10', time_end='7:34',
sim_threshold=80, conf_threshold=75, use_fullframe=True,
brightness_threshold=210, similar_image_threshold=1000, frames_to_skip=1)
```
`$ python3 example.py`
example.srt:
```
1
00:07:10,000 --> 00:07:10,083
商城......现在没什么东西
2
00:07:10,416 --> 00:07:12,000
这边是战斗辅助系统
3
00:07:13,083 --> 00:07:14,500
要进去才能了解了
4
00:07:15,083 --> 00:07:15,916
没问题了吧
5
00:07:16,333 --> 00:07:17,166
我们准备登录
6
00:07:18,416 --> 00:07:21,083
啊对了， 登录没有服务器的选择么
7
00:07:21,333 --> 00:07:25,000
没有本游戏所有玩家， 都在个服务器内
8
00:07:25,833 --> 00:07:28,833
刺激了， 这么多玩家居然都不分流的么
9
00:07:29,500 --> 00:07:31,083
那......现在登录吗？
10
00:07:31,166 --> 00:07:32,416
好，登录吧！
```
## Install prerequisites
Python 3.8 - 3.12
paddlepaddle or paddlepaddle-gpu See https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/en/install/pip/linux-pip_en.html
## Installation
`pip install git+https://github.com/oliverfei/videocr-PaddleOCR.git`
Alternatively for development:
1. Clone this repo
2. From the root directory of this repository run `python -m pip install .`
## Performance
The OCR process can be very slow on CPU. Running with `paddlepaddle-gpu` is recommended if you have a CUDA GPU.
## Tips
To shorten the amount of time it takes to perform OCR on each frame, you can use the `crop_x`, `crop_y`, `crop_width`, `crop_height` params to crop out only the areas of the videos where the subtitles appear. When cropping, leave a bit of buffer space above and below the text to ensure accurate readings.
### Quick Configuration Cheatsheet
|| More Speed | More Accuracy | Notes
-|------------|---------------|--------
Input Video Quality | Use lower quality | Use higher quality | Performance impact of using higher resolution video can be reduced with cropping
`frames_to_skip` | Higher number | Lower number |
`brightness_threshold` | Higher threshold | N/A | A brightness threshold can help speed up the OCR process by filtering out dark frames. In certain circumstances such as when subtitles are white and against a bright background, it may also help with accuracy.
## API
1. Return subtitle string in SRT format
```python
get_subtitles(
video_path: str, lang='ch', time_start='0:00', time_end='',
conf_threshold=75, sim_threshold=80, use_fullframe=False,
det_model_dir=None, rec_model_dir=None, use_gpu=False,
brightness_threshold=None, similar_image_threshold=100, similar_pixel_threshold=25, frames_to_skip=1,
crop_x=None, crop_y=None, crop_width=None, crop_height=None)
```
2. Write subtitles to `file_path`
```python
save_subtitles_to_file(
video_path: str, file_path='subtitle.srt', lang='ch', time_start='0:00', time_end='',
conf_threshold=75, sim_threshold=80, use_fullframe=False,
det_model_dir=None, rec_model_dir=None, use_gpu=False,
brightness_threshold=None, similar_image_threshold=100, similar_pixel_threshold=25, frames_to_skip=1,
crop_x=None, crop_y=None, crop_width=None, crop_height=None)
```
### Parameters
- `lang`
The language of the subtitles. See [PaddleOCR docs](https://github.com/PaddlePaddle/PaddleOCR/blob/release/2.6/doc/doc_en/multi_languages_en.md#5-support-languages-and-abbreviations) for list of supported languages and their abbreviations
- `conf_threshold`
Confidence threshold for word predictions. Words with lower confidence than this value will be discarded. The default value `75` 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 `80` 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, the specified cropped area is used for OCR or if a crop is not specified, then the bottom third of the frame will be used. By setting this value to `True` the entire frame will be used.
- `crop_x`, `crop_y`, `crop_width`, `crop_height`
Specifies the bounding area in pixels for the portion of the frame that will be used for OCR. See image below for example:
- `det_model_dir`
the text detection inference model folder. There are two ways to transfer parameters, 1. None: Automatically download the built-in model to ~/.paddleocr/det; 2. The path of a specific inference model, the model and params files must be included in the model path.
See PaddleOCR repo for list of prebuilt models: https://github.com/PaddlePaddle/PaddleOCR/.
- `rec_model_dir`
the text recognition inference model folder. There are two ways to transfer parameters, 1. None: Automatically download the built-in model to ~/.paddleocr/rec; 2. The path of a specific inference model, the model and params files must be included in the model path.
See PaddleOCR repo for list of prebuilt models: https://github.com/PaddlePaddle/PaddleOCR/.
- `use_gpu`
Set to `True` if performing ocr with gpu (requires the `paddlepaddle-gpu` python package to be installed)
- `brightness_threshold`
If set, pixels whose brightness are less than the threshold will be blackened out. Valid brightness values range from 0 (black) to 255 (white). This can help improve accuracy when performing OCR on videos with white subtitles.
- `similar_image_threshold`
The number of non-similar pixels there can be before the program considers 2 consecutive frames to be different. If a frame is not different from the previous frame, then the OCR result from the previous frame will be used (which can save a lot of time depending on how fast each OCR inference takes).
- `similar_pixel_threshold`
Brightness threshold from 0-255 used with the `similar_image_threshold` to determine if 2 consecutive frames are different. If the difference between 2 pixels exceeds the threshold, then they will be considered non-similar.
- `frames_to_skip`
The number of frames to skip before sampling a frame for OCR. Keep in mind the fps of the input video before increasing.
## TODO
- [ ] parallel processing
- [ ] publish to pypi
- [ ] commandline interface
- [ ] user-friendly application for non-devs