Bonsai_Tutorials/transcriber/README.md

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# transcriber
[![Release](https://img.shields.io/github/v/release/dscoular/transcriber)](https://img.shields.io/github/v/release/dscoular/transcriber)
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[![License](https://img.shields.io/github/license/dscoular/transcriber)](https://img.shields.io/github/license/dscoular/transcriber)
A python script which uses whisper to transcribe videos and outputs SRT subtitle text files.
- **Github repository**: <https://github.com/dscoular/transcriber/>
- **Documentation** <https://dscoular.github.io/transcriber/>
# `UV` or `Docker` - that is the question.
Whether you choose to use `uv` or `docker` our `Makefile` will launch it to a series of interactive
questions with sensible defaults. It will use the second smallest language model `base.en` by
default, however I used the largest model `medium.en` for the SRT files I've commited to this repo.
To be honest there wasn't much difference that I could discern.
## Using python's `uv`
If you have `uv` in your `PATH` and `ffmpeg` installed in your operating system, you should
be able to do the following to install and use this package.
1. `make` - runs the default target of `make help` to show help on all the `make` targets.
2. `make install` - installs the virtual environment and pre-commit hooks.
3. `make check` - **optional**, runs the code quality tools.
4. `make test` - **optional**, runs unit tests.
5. `make docs-test` - **optional**, generate HTML documents in the `site` directory.
6. `make transcribe` - by default, this converts the videos in the directory above our `Makefile` to `.srt` subtitle text files.
## Using `Docker`
If you have `docker` installed on your system, you should
be able to do the following to install and use this package.
1. `make docker-build` - Download and build the `transcribe-app` container image.
2. `make docker-run` - Run the transcriber interactively, by default, this converts the videos in the directory above our `Makefile` to `.srt` subtitle text files.