RVC CreateFeatureFiles

_CreateFeatureFiles.md

RVCの特徴量ファイル（total_fea.npyとadded～.index）を指定したフォルダにモデル名で書き出すスクリプト。

• CreateFeatureFiles.bat の VENV_DIR
• CreateFeatureFiles.py の model_path output_path

を設定する。
batとpyを同じフォルダに置いて、batを実行すると設定したvenvでpyを実行する。モデル名を訊いてくるので入力。
output_path に 「モデル名.npy」「モデル名.index」が書き出される。

CreateFeatureFiles.bat

@echo off
set PYTHON=
set GIT=
@REM venvのパスを指定
set VENV_DIR=G:\venv\RVC\.venv
set COMMANDLINE_ARGS=

if not defined PYTHON (set PYTHON=python)
set ERROR_REPORTING=FALSE

:start_venv
if ["%VENV_DIR%"] == ["-"] goto :launch

:activate_venv
set PYTHON="%VENV_DIR%\Scripts\Python.exe"
echo venv %PYTHON%

:launch
%PYTHON% CreateFeatureFiles.py %*
pause
exit /b

:show_stdout_stderr

echo.
echo exit code: %errorlevel%

pause

CreateFeatureFiles.py

import os
import faiss
import numpy as np

#トレーニングフォルダ
model_path = r"G:\venv\RVC\rvc-webui\models\training\models"
#書き出すフォルダ
output_path = r"G:\venv\RVC\subdata"

def make(training_dir, output_path, model_name):
    feature_dir = os.path.join(training_dir, "3_feature256")
    npys = []
    listdir_res = list(os.listdir(feature_dir))
    for name in sorted(listdir_res):
        phone = np.load(os.path.join(feature_dir, name))
        npys.append(phone)
    big_npy = np.concatenate(npys, 0)
    # np.save(os.path.join(training_dir, "total_fea.npy"), big_npy)
    np.save(os.path.join(output_path, model_name + ".npy"), big_npy)
    n_ivf = big_npy.shape[0] // 39
    index = faiss.index_factory(256, f"IVF{n_ivf},Flat")
    index_ivf = faiss.extract_index_ivf(index)
    index_ivf.nprobe = int(np.power(n_ivf, 0.3))
    index.train(big_npy)
    index.add(big_npy)
    faiss.write_index(
        index,
        # os.path.join(training_dir, f"added_IVF{n_ivf}_Flat_nprobe_{index_ivf.nprobe}.index"),
        os.path.join(output_path, model_name + ".index"),
    )

print("CreateFeatureFiles.py")
model_name = input("target model name:")
print(model_name)
training_dir = os.path.join(model_path, model_name)
if os.path.exists(training_dir):
    make(training_dir, output_path, model_name)
    print("done")
else:
    print("error: model dir not found")