Update README

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
 ```