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https://github.com/antiboredom/videogrep

automatic video supercuts with python
https://github.com/antiboredom/videogrep

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automatic video supercuts with python

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Videogrep

=========



Videogrep is a command line tool that searches through dialog in video or audio files and makes supercuts based on what it finds. It will recognize `.srt` or `.vtt` subtitle tracks, or transcriptions that can be generated with vosk, pocketsphinx, and other tools.



#### Examples



* [The Meta Experience](https://www.youtube.com/watch?v=nGHbOckpifw)

* [All the instances of the phrase "time" in the movie "In Time"](https://www.youtube.com/watch?v=PQMzOUeprlk)

* [All the one to two second silences in "Total Recall"](https://www.youtube.com/watch?v=qEtEbXVbYJQ)

* [A former press secretary telling us what he can tell us](https://www.youtube.com/watch?v=D7pymdCU5NQ)



#### Tutorial



See my blog for a short [tutorial on videogrep and yt-dlp](https://lav.io/notes/videogrep-tutorial/), and part 2, on [videogrep and natural language processing](https://lav.io/notes/videogrep-and-spacy/).



----



## Installation



Videogrep is compatible with Python versions 3.6 to 3.10.



To install:



```

pip install videogrep

```



If you want to transcribe video or audio, you also need to install [vosk](https://alphacephei.com/vosk/):



```

pip install vosk

```



Note: the previous version of videogrep supported pocketsphinx for speech-to-text. Vosk seems *much* better so I've added support for it and will likely be phasing out support for pocketsphinx.



## Usage



The most basic use:



```

videogrep --input path/to/video.mp4 --search 'search phrase'

```



It works with audio too:

```

videogrep --input path/to/audio.mp3 --search 'search phrase'

```



You can put any regular expression in the search phrase.



**NOTE: videogrep requires a matching subtitle track with each video you want to use. The video/audio file and subtitle file need to have the exact same name, up to the extension.** For example, `my_movie.mp4` and `my_movie.srt` will work, and `my_movie.mp4` and `my_movie_subtitle.srt` will *not* work.



Videogrep will search for matching `srt` and `vtt` subtitles, as well as `json` transcript files that can be generated with the `--transcribe` argument.



### Options



#### `--input [filename(s)] / -i [filename(s)]`



File or files to use as input. Most video or audio formats should work. If you mix audio and video input files, the resulting output will only be audio.



#### `--output [filename] / -o [filename]`



Name of the file to generate. By default this is `supercut.mp4`. Any standard video or audio extension will also work. (If you're using audio input or mixed audio and video input and you keep the default `supercut.mp4` as the output filename, videogrep will automatically change the output to `supercut.mp3`)



Videogrep will also recognize the following extensions for saving files:

  * `.mpv.edl`: generates an edl file playable by [mpv](https://mpv.io/) (useful for previews)

  * `.m3u`: media playlist

  * `.xml`: Final Cut Pro timeline, compatible with Adobe Premiere and Davinci Resolve



```

videogrep --input path/to/video --search 'search phrase' --output coolvid.mp4

```



#### `--search [query] / -s [query]`



Search term, as a regular expression. You can add as many of these as you want. For example:



```

videogrep --input path/to/video --search 'search phrase' --search 'another search' --search 'a third search' --output coolvid.mp4

```



#### `--search-type [type] / -st [type]`



Type of search you want to perform. There are two options:



* `sentence`: (default): Generates clips containing the full sentences of your search query.

* `fragment`: Generates clips containing the exact word or phrase of your search query.



Both options take regular expressions. You may only use the `fragment` search if your transcript has word-level timestamps, which will be the case for youtube `.vtt` files, or if you generated a transcript using Videogrep itself.



```

videogrep --input path/to/video --search 'experience' --search-type fragment

```



#### `--max-clips [num] / -m [num]`



Maximum number of clips to use for the supercut.



#### `--demo / -d`



Show the search results without making the supercut.



#### `--preview / -pr`



Preview the supercut in mpv (requires [mpv to be installed](https://mpv.io/))



#### `--randomize / -r`



Randomize the order of the clips.



#### `--padding [seconds] / -p [seconds]`



Padding in seconds to add to the start and end of each clip.



#### `--resyncsubs [seconds] / -rs [seconds]`



Time in seconds to shift the shift the subtitles forwards or backwards.



#### `--transcribe / -tr`



Transcribe the video/audio using [vosk](https://alphacephei.com/vosk/). This will generate a `.json` file in the same folder as the video. By default this uses vosk's small english model.



**NOTE:** Because of some compatibility issues, vosk must be installed separately with `pip install vosk`.



```

videogrep -i vid.mp4 --transcribe

```



#### `--model [modelpath] / -mo [modelpath]`



In combination with the `--transcribe` option, allows you to specify the path to a vosk model folder to use. Vosk models are [available here](https://alphacephei.com/vosk/models) in a variety of languages.



```

videogrep -i vid.mp4 --transcribe --model path/to/model/

```



#### `--export-clips / -ec`



Exports clips as individual files rather than as a supercut.



```

videogrep -i vid.mp4 --search 'whatever' --export-clips

```



#### `--export-vtt / -ev`



Exports the transcript of the supercut as a WebVTT file next to the video.



```

videogrep -i vid.mp4 --search 'whatever' --export-vtt

```



#### `--ngrams [num] / -n [num]`



Shows common words and phrases from the video or audio file.



```

videogrep -i vid.mp4 --ngrams 1

```



----



## Use it as a module



```

from videogrep import videogrep



videogrep('path/to/your/files','output_file_name.mp4', 'search_term', 'search_type')

```

The videogrep module accepts the same parameters as the command line script. To see the usage check out the source.



### Example Scripts



Also see the examples folder for:

* [silence extraction](https://github.com/antiboredom/videogrep/blob/master/examples/only_silence.py)

* [automatically creating supercuts](https://github.com/antiboredom/videogrep/blob/master/examples/auto_supercut.py)

* [creating supercuts based on youtube searches](https://github.com/antiboredom/videogrep/blob/master/examples/auto_youtube.py)

* [creating supercuts from specific parts of speech](https://github.com/antiboredom/videogrep/blob/master/examples/parts_of_speech.py)

* [creating supercuts from spacy pattern matching](https://github.com/antiboredom/videogrep/blob/master/examples/pattern_matcher.py)



----



## Credits



Videogrep is maintained by [Sam Lavigne](https://lav.io), and built using [MoviePy](https://zulko.github.io/moviepy/) and [Vosk](https://alphacephei.com/vosk/). A big thanks goes out to all those who have [contributed](https://github.com/antiboredom/videogrep/graphs/contributors), particuarly to [Charlie Macquarie](https://charliemacquarie.com) for his efforts in getting the project to work with audio-only media.



Videogrep has received financial support from the [Department of Digital Humanities, King’s College London](https://www.kcl.ac.uk/ddh) and from the [Clinic for Open Source Arts](https://clinicopensourcearts.org/).