https://github.com/calcoloergosum/video-watching-acceleration

https://github.com/calcoloergosum/video-watching-acceleration

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/calcoloergosum/video-watching-acceleration
• Owner: calcoloergosum
• Created: 2022-12-18T04:54:05.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2022-12-19T18:31:46.000Z (almost 2 years ago)
• Last Synced: 2024-05-29T23:18:32.110Z (4 months ago)
• Language: Python
• Size: 4.24 MB
• Stars: 8
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Video Watching Acceleration

Better experience for watching videos where people talk.

This script was intended to watch small scale math lectures/seminars, usually hours long.

## Sample

Before: 28 seconds (Click to play):

[![original](assets/original.png)](assets/original.mp4)

After: 20 seconds (Click to play):

[![processed](assets/processed.png)](assets/processed.mp4)

## Motivation

I watch videos fast-forward, usually x1.25. Faster than that I cannot fully comprehend the utterances anymore.

But when presented together with subtitles, I can comfortably follow the argument of the speaker with playback speed of x1.5 or more (depends on the speaker of course).

Also, I usually skip the pauses by pressing right-arrow button on the keyboard with VLC. But it is easier to pause when I can't follow the video, than skipping when I can fully follow the video.

Personal result is:

- Speed up by subtitles: about 25%

- Speed up by long pause skip: about 60%

- Overall speed-up: about 200%

## Methodology

1. Prepare subtitle

    [Whisper by OpenAI](https://github.com/openai/whisper)(MIT license) was used.

    To better adjust timestamps, [stable-ts](https://github.com/jianfch/stable-ts) was used.

2. Clip long pauses

    [Silero-VAD](https://github.com/snakers4/silero-vad)(MIT License) was used.

3. When watching, fast-forward according to your preference

    Any media player with playback speed control will do; e.g. VLC.

## How to use

After installing requirements by `pip install -r requirements.txt`,

Start with a directory that contains videos.

```

data_src/

    - lecture01.mp4

    - lecture02.mp4

    - ...

```

Run ```python -m video_watching_acceleration.transcribe mp4 data_src data_src --whisper-model small```

```

data_src/

    - lecture01.mp4

    - lecture01.srt

    - lecture02.mp4

    - ...

```

Run ```python -m video_watching_acceleration.vad mp4 data_src data_src```

```

data_src/

    - lecture01.mp4

    - lecture01.srt

    - lecture01_vad.csv

    - lecture02.mp4

    - ...

```

Finally, run ```python -m video_watching_acceleration.edit mp4 data_src data_dst```

```

data_src/

    - lecture01.mp4

    - lecture01.srt

    - lecture01_vad.csv

    - lecture02.mp4

    - ...

data_dst/

    - lecture01.mp4

    - lecture01.srt

    - lecture02.mp4

    ...

```

Enjoy!