From e2feca85994c62db854643d87882c770a37aa5d3 Mon Sep 17 00:00:00 2001 From: Sting <loic.allegre@ensiie.fr> Date: Tue, 25 Jul 2023 16:35:17 +0200 Subject: [PATCH] Update README --- README.md | 51 ++++++++++++++++++++++++++++----------------------- 1 file changed, 28 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 5239f2f..291cd15 100644 --- a/README.md +++ b/README.md @@ -46,37 +46,42 @@ If we ever want to use an AI to identify syllables without a reference lyrics fi ## Requirements - MKVToolnix (at least the CLI utils) +- FFmpeg - Python >= 3.8 -Optional : -- PyTorch for custom model training : follow the instructions [here](https://pytorch.org/get-started/locally/) - All other python modules can be installed directly through pip, see further. -This project requires at least Python 3.8, and using a virtual environment is strongly recommended. -To install the dependencies, execute in the project directory : -```bash -$ python -m venv env # create the virtual environment, do it once -$ source env/bin/activate # use the virtual environement +## Install -# Install the required python modules -$ pip install -r requirements.txt +The simplest way to install Autokara is through PIP : +```bash +# Using HTTPS +$ pip install git+https://git.iiens.net/bakaclub/autokara.git -# To exit the virtual environment -$ deactivate +# Or SSH +$ pip install git+ssh://git@git.iiens.net:bakaclub/autokara.git ``` -Having a CUDA-capable GPU is optional, but can greatly reduce processing time in some situations. +Or you can clone the repo and use `pip install <repo_directory>` if you prefer. -To use the custom phonetic mapping for Japanese Romaji, you need to update manually (for now) the g2p DB (within the venv): +To use the custom phonetic mappings for Japanese Romaji and other non-English languages, you need to update manually (for now) the g2p DB (within the venv): ```bash -$ cp g2p/mappings/langs/rji/* env/lib/python3.11/site-packages/g2p/mappings/langs/rji/ +$ autokara-gen-lang +``` -#Then update : -$ g2p update + +If you plan on contributing to development, the use of a virtual environment is recommended : +```bash +$ python -m venv env # create the virtual environment, do it once +$ source env/bin/activate # use the virtual environement +$ pip install git+ssh://git@git.iiens.net:bakaclub/autokara.git # install autokara + +# To exit the virtual environment +$ deactivate ``` +Having a CUDA-capable GPU is optional, but can greatly reduce processing time in some situations. # Use @@ -89,22 +94,22 @@ To use Autokara, you need : To execute AutoKara on a MKV video file and an ASS file containing the lyrics (ASS will be overwritten): ```bash -$ python autokara.py video.mkv lyrics.ass +$ autokara video.mkv lyrics.ass ``` To output to a different file (and keep the original) : ```bash -$ python autokara.py video.mkv lyrics.ass -o output.ass +$ autokara video.mkv lyrics.ass -o output.ass ``` To execute AutoKara on a (pre-extracted) WAV (or OGG, MP3, ...) vocals file, pass the `--vocals` flag : ```bash -$ python autokara.py vocals.wav output.ass --vocals +$ autokara vocals.wav output.ass --vocals ``` To use a phonetic transcription optimized for a specific language, use `--lang` (or `-l`) : ```bash -$ python autokara.py vocals.wav output.ass --lang jp +$ autokara vocals.wav output.ass --lang jp ``` Available languages are : ``` @@ -114,7 +119,7 @@ en : English Full help for all options is available with : ```bash -$ python autokara.py -h +$ autokara -h ``` ## Useful scripts @@ -143,7 +148,7 @@ A visualization tool, mainly intended for debug. Does the same as autokara.py, but instead of writing to a file, plots a graphic with onset times, spectrogram, probability curves,... Does not work on video files, only separated vocals audio files ```bash -$ python plot_syls.py vocals.wav lyrics.ass +$ autokara-plot vocals.wav lyrics.ass ``` -- GitLab