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https://github.com/marquesafonso/multilang-asr-captioner

A multilingual automatic speech recognition and video captioning tool using faster whisper. Supports real-time translation to english. Runs on consumer grade cpu.
https://github.com/marquesafonso/multilang-asr-captioner

automatic-speech-recognition captioning-videos faster-whisper whisper

Last synced: 2 months ago
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A multilingual automatic speech recognition and video captioning tool using faster whisper. Supports real-time translation to english. Runs on consumer grade cpu.

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## Multilang ASR Captioner

A multilingual automatic speech recognition and video captioning tool using faster whisper.

Supports real-time translation to english. Runs on consumer grade cpu.

## Requirements and Instalations

### Docker (preferred)

You'll need to install [docker](https://www.docker.com/products/docker-desktop/).

Then, follow the steps below.

1. clone the repo
```{bash}
git clone [email protected]:marquesafonso/multilang-asr-captioner.git
```
2. Build and run the container using docker-compose
```{bash}
docker compose up
```

Check the [landing page](http://127.0.0.1:8000).

From there you will see the [submit_video endpoint](http://127.0.0.1:8000/submit_video/) and the [documentation](http://127.0.0.1:8000/docs/)

**Tip**: on Linux or Mac localhost will resolve directly to 0.0.0.0 but on windows you will need to change it to 127.0.0.1 or localhost

### Local

To run this tool locally on your computer you will need the following sofware installed:
+ [ImageMagick](https://imagemagick.org/script/download.php)
+ [Python (3.11)](https://www.python.org/downloads/release/python-3116/)

Once you are at your desired working directory, run the following commands on your terminal:

```{bash}
git clone [email protected]:marquesafonso/multilang-asr-captioner.git

pip install pipenv

pipenv install
```

Note that this assumes a proper Git installation and ssh key configuration.

## Quick start (local)

### API

A FastAPI API is available. To start the API locally, run:

```
pipenv run python main.py
```

Then check the [landing page](http://127.0.0.1:8000).

From there you will see the [submit_video endpoint](http://127.0.0.1:8000/submit_video/) and the [documentation](http://127.0.0.1:8000/docs/)

**Tip**: on Linux or Mac localhost will resolve directly to 0.0.0.0 but on windows you will need to change it to 127.0.0.1 or localhost