videocr

Extract hardcoded (burned-in) subtitles from videos using the PaddleOCR OCR engine with Python. A Colab notebook for installing and running this library is included for convenience:

# 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:

0
00:07:10,000 --> 00:07:10,083
商城......现在没什么东西

1
00:07:10,416 --> 00:07:12,000
这边是战斗辅助系统

2
00:07:13,083 --> 00:07:14,500
要进去才能了解了

3
00:07:15,083 --> 00:07:15,916
没问题了吧

4
00:07:16,333 --> 00:07:17,166
我们准备登录

5
00:07:18,416 --> 00:07:21,083
啊对了， 登录没有服务器的选择么

6
00:07:21,333 --> 00:07:25,000
没有本游戏所有玩家， 都在个服务器内

7
00:07:25,833 --> 00:07:28,833
刺激了， 这么多玩家居然都不分流的么

8
00:07:29,500 --> 00:07:31,083
那......现在登录吗？

9
00:07:31,166 --> 00:07:32,416
好，登录吧！

Install prerequisites

Python 3.7 - 3.10

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

API

1. Return subtitle string in SRT format

   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

   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 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 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
• [ ] handle multiple lines of text in the same frame
• [ ] publish to pypi
• [ ] commandline interface
• [ ] user-friendly application for non-devs