Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/botbahlul/whisper_autosrt

A python script COMMAND LINE utility to AUTO GENERATE SUBTITLE FILE (using faster_whisper module which is a reimplementation of OpenAI Whisper module) and TRANSLATED SUBTITLE FILE (using unofficial online Google Translate API) for any video or audio file
https://github.com/botbahlul/whisper_autosrt

auto-caption auto-subtitle caption faster-whisper ffmpeg google-translate-api openai openai-whisper python speech-recognition speechrecognition subtitle voice-recognition voicerecognition whisper

Last synced: about 1 month ago
JSON representation

A python script COMMAND LINE utility to AUTO GENERATE SUBTITLE FILE (using faster_whisper module which is a reimplementation of OpenAI Whisper module) and TRANSLATED SUBTITLE FILE (using unofficial online Google Translate API) for any video or audio file

Awesome Lists containing this project

README 

        
# whisper_autosrt 

  

### Auto generate subtitle and translated subtitles files for any video / audio files

whisper_autosrt is a simple command line tool made with python to auto generate subtitle/closed caption for any video or audio files using faster_whisper module https://github.com/guillaumekln/faster-whisper which is a reimplementation of OpenAI's Whisper module and translate it automatically for free using a simple unofficial online Google Translate API.



### Installation

If you don't have python on your Windows system you can try the compiled version from this git release assets

https://github.com/botbahlul/whisper_autosrt/releases



If it doesn't run well then you need to install python on your Windows system.



Just extract those ffmpeg.exe, ffprobe.exe, and whisper_autosrt.exe into a folder that has been added to PATH ENVIRONMENT for example in C:\Windows\system32 so you can execute them from any folder.



You can get latest version of ffmpeg from https://www.ffmpeg.org/



In Linux you have to install this script with python (version minimal 3.8.12) and install ffmpeg with your linux package manager, for example in debian based linux distribution you can type :



```

sudo apt update

sudo apt install -y ffmpeg

```



To install this whisper_autosrt, just type :

```

pip install --upgrade whisper_autosrt

```



You can try to compile that whisper_autosrt.py script in win/linux folder into a single executable file with pyinstaller by typing these :

```

pip install pyinstaller

pyinstaller --onefile whisper_autosrt.py

```



The executable compiled file will be placed by pyinstaller into dist subfolder of your current working folder, so you can just rename and put that compiled file into a folder that has been added to your PATH ENVIRONMENT so you can execute it from anywhere. 

Beware that on Linux system the compiled file could be very large (about 2.2GB) because pyinstaller will include all nvidia cuda driver on it.



I was succesfuly compiled it on Windows 10 with pyinstaller-5.1 and Pyhton-3.10.4, and python-3.8.12 on Debian 9.



Another alternative way to install this script with python is by cloning this git (or downloading this git as zip then extract it into a folder), and then just type :



```

pip install wheel

python setup.py bdist_wheel

```



Then check the name of the whl file created in dist folder. In case the filename is whisper_autosrt-0.0.3-py2.py3-none-any.whl then you can install that whl file with pip :

```

cd dist

pip install whisper_autosrt-0.0.3-py2.py3-none-any.whl

```



You can also install this script (or any pip package) in ANDROID DEVICES via PYTHON package in TERMUX APP.



https://github.com/termux/termux-app/releases/tag/v0.118.0



Choose the right apk for your device, install it, then open it



Type these commands to get python, pip, this whisper_autosrt, (and any other pip packages) :



```

termux-setup-storage

pkg update -y

pkg install -y python

pkg install -y ffmpeg

pip install whisper_autosrt

```



### Simple usage example 



```

whisper_autosrt --list-src-languages

whisper_autosrt --list-dst-languages

whisper_autosrt -S zh -D en "Episode 1.mp4"

```



If you don't know exactly what language spoken on the video/audio file, you can try to use \'-S auto\', so this app will try to auto detect the language.

```

whisper_autosrt -S auto -D en ""Episode 1.mp4""

```



For multiple video/audio files you can use wildcard e.g:

```

whisper_autosrt -S zh -D en C:\Movies\*.mp4

```



or separate them with space character e.g:

```

whisper_autosrt -S zh -D en "Episode 1.mp4" "Episode 2.mp4"

```



If you don't need translations just type :

```

whisper_autosrt -S auto "Episode 1.mp4"

```



### Usage



```

usage: whisper_autosrt [-h] [-m MODEL_NAME] [-lm] [-d DEVICE] [-ld] [-ct COMPUTE_TYPE] [-lct] [-t CPU_THREADS] [-nw NUM_WORKERS]

                       [-S SRC_LANGUAGE] [-D DST_LANGUAGE] [-lS] [-lD] [-F FORMAT] [-lF] [-c CONCURRENCY] [-es EMBED_SRC]

                       [-ed EMBED_DST] [-fr FORCE_RECOGNIZE] [-v]

                       [source_path ...]



positional arguments:

  source_path           Path to the video or audio files to generate subtitles files (use wildcard for multiple files or separate

                        them with a space character e.g. "file 1.mp4" "file 2.mp4")



options:

  -h, --help            show this help message and exit

  -m MODEL_NAME, --model-name MODEL_NAME

                        name of whisper model to use

  -lm, --list-models    List of whisper models name

  -d DEVICE, --device DEVICE

                        name of the device to use

  -ld, --list-devices   List of supported devices

  -ct COMPUTE_TYPE, --compute-type COMPUTE_TYPE

                        name of the compute type (quantization) to use

  -lct, --list-compute-types

                        List of supported compute types

  -t CPU_THREADS, --cpu-threads CPU_THREADS

                        Number of threads to use when running on CPU

  -nw NUM_WORKERS, --num-workers NUM_WORKERS

                        Number of concurrent calls when running whisper model

  -S SRC_LANGUAGE, --src-language SRC_LANGUAGE

                        Language code of the audio language spoken in video/audio source_path

  -D DST_LANGUAGE, --dst-language DST_LANGUAGE

                        Desired translation language code for the subtitles

  -lS, --list-src-languages

                        List all available src_languages (whisper supported languages)

  -lD, --list-dst-languages

                        List all available dst_languages (google translate supported languages)

  -F FORMAT, --format FORMAT

                        Desired subtitles format

  -lF, --list-formats   List all supported subtitles formats

  -c CONCURRENCY, --concurrency CONCURRENCY

                        Number of concurrent calls for Google Translate API

  -es EMBED_SRC, --embed-src EMBED_SRC

                        Boolean value (True or False) for embedding original language subtitles file into video file

  -ed EMBED_DST, --embed-dst EMBED_DST

                        Boolean value (True or False) for embedding translated subtitles file into video file

  -fr FORCE_RECOGNIZE, --force-recognize FORCE_RECOGNIZE

                        Boolean value (True or False) for re-recognize media file event if it's already has subtitles stream

  -v, --version         show program's version number and exit

```



### License



MIT



Check my other SPEECH RECOGNITIION + TRANSLATE PROJECTS https://github.com/botbahlul?tab=repositories



Buy me coffee : https://sociabuzz.com/botbahlul/tribe