Generate LRC files for your music using openai's whisper
Project description
AutoLRC
AutoLRC is a command-line that generates lyric files (.lrc) for your music locally using OpenAI's Whisper model.
Installation
Install AutoLRC with pip
pip install auto-lrc
AutoLRC depends on FFmpeg to be installed
Usage
CLI
AutoLRC --help
Note: the CLI may be slow to start as it has to import big packages.
Options
--music-dir: Path to the directory containing your music files.--model: Whisper model to use for transcription (default:turbo).--device: Device to run the transcription on (cpu,cuda, or default:auto).
Example
AutoLRC --music-dir "M:\Music" --model "large-v3-turbo" --device "cuda"
GPU Support
- Currently GPU support is only available Nvidia GPUs.
- CUDA 12.6 installed. (Other versions may work fine)
Development
AutoLRC is built with UV
- Clone the repository:
git clone https://github.com/HeavyLvy/auto-lrc
- Setup project:
uv sync
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file auto_lrc-3.0.0.tar.gz.
File metadata
- Download URL: auto_lrc-3.0.0.tar.gz
- Upload date:
- Size: 1.2 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
aebf95408f1b907df00c5ac13a1dce2baf7e4caf2e29716a441230c4497efd42
|
|
| MD5 |
ed66f28663cccfc7d1e104238f830b4c
|
|
| BLAKE2b-256 |
3179b6403a941b3cc5b2ca3250d193046d9efe532ee50fa47ff9d9b2ba467e88
|
File details
Details for the file auto_lrc-3.0.0-py3-none-any.whl.
File metadata
- Download URL: auto_lrc-3.0.0-py3-none-any.whl
- Upload date:
- Size: 6.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e9cbd3644a2b04aec2b3819e7b9bf58c21a6fb6779831710126074ee1e979935
|
|
| MD5 |
033cb249dc920cb11267b21074543cf7
|
|
| BLAKE2b-256 |
0199e58fef0f7fe1b1b3086d085014442f2e5cf36dccb2996607ba85aeb32025
|
