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Fix nested audio files bug

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litagin02
2024-04-27 12:50:00 +09:00
parent 32145e18a3
commit 9df344b995
1 changed files with 15 additions and 9 deletions
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24
gradio_tabs/style_vectors.py
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@@ -1,6 +1,7 @@
import json import json
import os import os
import shutil import shutil
from pathlib import Path
import gradio as gr import gradio as gr
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
@@ -15,11 +16,10 @@ from config import config
from style_bert_vits2.constants import DEFAULT_STYLE, GRADIO_THEME from style_bert_vits2.constants import DEFAULT_STYLE, GRADIO_THEME
from style_bert_vits2.logging import logger from style_bert_vits2.logging import logger
# Get path settings # Get path settings
with open(os.path.join("configs", "paths.yml"), "r", encoding="utf-8") as f: with open(os.path.join("configs", "paths.yml"), "r", encoding="utf-8") as f:
path_config: dict[str, str] = yaml.safe_load(f.read()) path_config: dict[str, str] = yaml.safe_load(f.read())
dataset_root = path_config["dataset_root"] dataset_root = Path(path_config["dataset_root"])
# assets_root = path_config["assets_root"] # assets_root = path_config["assets_root"]
MAX_CLUSTER_NUM = 10 MAX_CLUSTER_NUM = 10
@@ -28,7 +28,7 @@ MAX_AUDIO_NUM = 10
tsne = TSNE(n_components=2, random_state=42, metric="cosine") tsne = TSNE(n_components=2, random_state=42, metric="cosine")
umap = UMAP(n_components=2, random_state=42, metric="cosine", n_jobs=1, min_dist=0.0) umap = UMAP(n_components=2, random_state=42, metric="cosine", n_jobs=1, min_dist=0.0)
wav_files = [] wav_files: list[Path] = []
x = np.array([]) x = np.array([])
x_reduced = None x_reduced = None
y_pred = np.array([]) y_pred = np.array([])
@@ -36,13 +36,17 @@ mean = np.array([])
centroids = [] centroids = []
def load(model_name, reduction_method): def load(model_name: str, reduction_method: str):
global wav_files, x, x_reduced, mean global wav_files, x, x_reduced, mean
wavs_dir = os.path.join(dataset_root, model_name, "wavs") # wavs_dir = os.path.join(dataset_root, model_name, "wavs")
style_vector_files = [ wavs_dir = dataset_root / model_name / "wavs"
os.path.join(wavs_dir, f) for f in os.listdir(wavs_dir) if f.endswith(".npy") # style_vector_files = [
] # os.path.join(wavs_dir, f) for f in os.listdir(wavs_dir) if f.endswith(".npy")
wav_files = [f.replace(".npy", "") for f in style_vector_files] # ]
style_vector_files = [f for f in wavs_dir.rglob("*.npy") if f.is_file()]
# foo.wav.npy -> foo.wav
wav_files = [f.with_suffix("") for f in style_vector_files]
logger.info(f"Found {len(style_vector_files)} style vectors in {wavs_dir}")
style_vectors = [np.load(f) for f in style_vector_files] style_vectors = [np.load(f) for f in style_vector_files]
x = np.array(style_vectors) x = np.array(style_vectors)
mean = np.mean(x, axis=0) mean = np.mean(x, axis=0)
@@ -201,6 +205,7 @@ def save_style_vectors_from_clustering(model_name, style_names_str: str):
logger.info(f"Backup {style_vector_path} to {style_vector_path}.bak") logger.info(f"Backup {style_vector_path} to {style_vector_path}.bak")
shutil.copy(style_vector_path, f"{style_vector_path}.bak") shutil.copy(style_vector_path, f"{style_vector_path}.bak")
np.save(style_vector_path, style_vectors) np.save(style_vector_path, style_vectors)
logger.success(f"Saved style vectors to {style_vector_path}")
# config.jsonの更新 # config.jsonの更新
config_path = os.path.join(result_dir, "config.json") config_path = os.path.join(result_dir, "config.json")
@@ -222,6 +227,7 @@ def save_style_vectors_from_clustering(model_name, style_names_str: str):
json_dict["data"]["style2id"] = style_dict json_dict["data"]["style2id"] = style_dict
with open(config_path, "w", encoding="utf-8") as f: with open(config_path, "w", encoding="utf-8") as f:
json.dump(json_dict, f, indent=2, ensure_ascii=False) json.dump(json_dict, f, indent=2, ensure_ascii=False)
logger.success(f"Updated {config_path}")
return f"成功!\n{style_vector_path}に保存し{config_path}を更新しました。" return f"成功!\n{style_vector_path}に保存し{config_path}を更新しました。"