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GPT_SoVITS/inference_webui.py
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@ -17,6 +17,8 @@ logging.getLogger("charset_normalizer").setLevel(logging.ERROR)
logging.getLogger("torchaudio._extension").setLevel(logging.ERROR)
import pdb
import torch
import shutil
from scipy.io import wavfile
if os.path.exists("./gweight.txt"):
with open("./gweight.txt", 'r', encoding="utf-8") as file:
@ -312,7 +314,7 @@ def merge_short_text_in_array(texts, threshold):
result[len(result) - 1] += text
return result
def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切"), top_k=20, top_p=0.6, temperature=0.6, ref_free = False):
def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切"), top_k=20, top_p=0.6, temperature=0.6, interval=0.3, ref_free = False):
if prompt_text is None or len(prompt_text) == 0:
ref_free = True
t0 = ttime()
@ -328,7 +330,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
print(i18n("实际输入的目标文本:"), text)
zero_wav = np.zeros(
int(hps.data.sampling_rate * 0.3),
int(hps.data.sampling_rate * interval),
dtype=np.float16 if is_half == True else np.float32,
)
if not ref_free:
@ -436,7 +438,17 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
yield hps.data.sampling_rate, (np.concatenate(audio_opt, 0) * 32768).astype(
np.int16
)
# 指定保存音频的文件路径
file_path = 'moys/temp/audio.wav'
# 调用保存音频的函数
save_audio(hps.data.sampling_rate, np.concatenate(audio_opt, 0), file_path)
# 保存音频数据到文件
def save_audio(sampling_rate, audio_data, file_path):
# 确保音频数据是16位PCM格式
audio_data = np.int16(audio_data / np.max(np.abs(audio_data)) * 32767)
wavfile.write(file_path, sampling_rate, audio_data)
def split(todo_text):
todo_text = todo_text.replace("……", "。").replace("——", "，")
@ -584,6 +596,135 @@ def get_weights_names():
return SoVITS_names, GPT_names
def save_model_config(GPT_dropdown, SoVITS_dropdown, inp_ref, prompt_text, prompt_language):
config_dir = "moys"
config_dir1 = r"moys\audio"
if not os.path.exists(config_dir):
os.makedirs(config_dir)
# 复制参考音频文件到配置目录
copy_ref_audio_path = os.path.join(config_dir1, os.path.basename(inp_ref))
shutil.copy(inp_ref, copy_ref_audio_path)
gpt_model_name = os.path.basename(GPT_dropdown).split('-')[0]
config_file_path = os.path.join(config_dir, f"{gpt_model_name}.txt")
with open(config_file_path, 'w', encoding='utf-8') as f:
f.write(f"GPT_model_path={GPT_dropdown}\n")
f.write(f"SoVITS_model_path={SoVITS_dropdown}\n")
f.write(f"ref_audio_path={copy_ref_audio_path}\n") # 修改写入的路径为复制文件的路径
f.write(f"ref_text={prompt_text}\n")
f.write(f"ref_audio_language={prompt_language}\n")
return f"Configuration saved to {config_file_path}"
def load_model_config(config_file_name):
config_dir = "moys"
# 因为 config_file_name 现在是字符串，我们直接使用它来构造文件路径
config_file_path = os.path.join(config_dir, config_file_name)
with open(config_file_path, 'r', encoding='utf-8') as f:
lines = f.readlines()
config = {}
for line in lines:
key, value = line.strip().split('=')
config[key] = value
# 返回一个包含所有组件期望值的字典
return (
config["GPT_model_path"],
config["SoVITS_model_path"],
config["ref_audio_path"],
config["ref_text"],
config["ref_audio_language"]
)
def refresh_config_files():
# 获取最新的配置文件列表
config_files = get_config_files()
# 创建一个新的文件名列表，只包含文件名
config_file_names = [os.path.basename(path) for path in config_files]
# 返回一个更新的配置，告诉 Gradio 更新下拉菜单的选项
return {"choices": config_file_names, "__type__": "update"}
# 辅助函数，用于处理 load_model_config 函数的输出
def handle_load_model_config(config_file_name, GPT_dropdown, SoVITS_dropdown, inp_ref, prompt_text, prompt_language):
# 调用原始函数获取配置
config = load_model_config(config_file_name)
# 更新组件的值
GPT_dropdown.update(value=config.get("GPT_model_path"))
SoVITS_dropdown.update(value=config.get("SoVITS_model_path"))
inp_ref.update(value=config.get("ref_audio_path"))
prompt_text.update(value=config.get("ref_text"))
prompt_language.update(value=config.get("ref_audio_language"))
def get_config_files():
config_dir = "moys"
if not os.path.exists(config_dir):
return []
return [os.path.join(config_dir, f) for f in os.listdir(config_dir) if f.endswith('.txt')]
def echo(input_text):
# 直接返回输入的文本
return input_text
def find_latest_wav(source_dir, dest_dir):
# 确保目标文件夹存在
if not os.path.exists(dest_dir):
os.makedirs(dest_dir)
# 初始化找到的wav文件路径
wav_file_path = None
# 遍历源文件夹
for root, dirs, files in os.walk(source_dir):
for file in files:
if file.lower().endswith('.wav'):
wav_file_path = os.path.join(root, file)
# 找到第一个wav文件就退出循环
break
if wav_file_path:
break # 确保找到文件后不再继续遍历
# 如果找到了wav文件，复制到目标文件夹
if wav_file_path:
base_name = os.path.basename(wav_file_path)
file_name, file_ext = os.path.splitext(base_name)
dest_file_path = os.path.join(dest_dir, base_name)
# 检查目标文件夹中是否存在同名文件，并添加后缀以避免覆盖
counter = 1
while os.path.exists(dest_file_path):
new_name = f"{file_name}({counter}){file_ext}"
dest_file_path = os.path.join(dest_dir, new_name)
counter += 1
# 复制文件
shutil.copy2(wav_file_path, dest_file_path)
print(f"Copied WAV file to {dest_file_path}")
return dest_file_path # 返回复制的文件路径
else:
print("No WAV files found.")
return None # 没有找到 WAV 文件时返回 None
def on_download_click(textq_value):
source_directory = r'moys/temp' # 源文件夹路径
destination_directory = textq_value
# outputs.update_value(f"开始查找最新的WAV文件...")
result = find_latest_wav(source_directory, destination_directory) # 调用函数
# outputs.update_value(f"已保存到: {destination_directory}")
return f"{result}已保存到: {destination_directory}"
SoVITS_names, GPT_names = get_weights_names()
with gr.Blocks(title="GPT-SoVITS WebUI") as app:
@ -626,15 +767,69 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
top_k = gr.Slider(minimum=1,maximum=100,step=1,label=i18n("top_k"),value=5,interactive=True)
top_p = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("top_p"),value=1,interactive=True)
temperature = gr.Slider(minimum=0,maximum=1,step=0.05,label=i18n("temperature"),value=1,interactive=True)
interval = gr.Slider(minimum=0,maximum=5,step=0.02,label=i18n("interval"),value=0.3,interactive=True)
inference_button = gr.Button(i18n("合成语音"), variant="primary")
output = gr.Audio(label=i18n("输出的语音"))
inference_button.click(
get_tts_wav,
[inp_ref, prompt_text, prompt_language, text, text_language, how_to_cut, top_k, top_p, temperature, ref_text_free],
[output],
with gr.Row():
# 创建文本框和下载按钮
download_button = gr.Button("下载语音", variant="primary")
textq = gr.Textbox(label="保存的语音路径", value="")
outputs0 = gr.Textbox(label=i18n("保存状态"), value="", interactive=False)
# 将事件处理函数绑定到按钮的点击事件
download_button.click(
on_download_click,
inputs=[textq], # 这里确保 textq 是正确的组件引用
outputs=[outputs0] # 这里确保 outputs 是正确的组件引用
)
inference_button.click(
get_tts_wav,
[inp_ref, prompt_text, prompt_language, text, text_language, how_to_cut, top_k, top_p, temperature, interval, ref_text_free],
[output],
)
# Add new UI elements for saving and loading configurations
with gr.Row():
# 初始加载配置文件列表
config_files = get_config_files()
# 创建一个新的列表，只包含文件名
config_file_names = [os.path.basename(path) for path in config_files]
# 使用文件名列表作为 Dropdown 组件的选项
config_dropdown = gr.Dropdown(
label=i18n("加载模型配置"),
choices=config_file_names,
value=config_file_names[0] if config_file_names else None
)
# Output textbox for displaying save confirmation
save_output = gr.Textbox(label=i18n("保存配置状态"), value="", interactive=False)
# 绑定刷新按钮的点击事件
refresh_button = gr.Button(i18n("刷新配置文件列表"), variant="primary")
refresh_button.click(
fn=refresh_config_files, # 使用新创建的 refresh_config_files 函数
inputs=[], # 刷新按钮不需要输入
outputs=[config_dropdown] # 指定输出为 config_dropdown 组件，以更新其选项
)
# 绑定保存按钮的点击事件
save_button = gr.Button(i18n("保存模型配置"), variant="primary")
save_button.click(
fn=save_model_config,
inputs=[GPT_dropdown, SoVITS_dropdown, inp_ref, prompt_text, prompt_language],
outputs=[save_output]
)
# 绑定加载按钮的点击事件
load_button = gr.Button(i18n("加载模型配置"), variant="primary")
load_button.click(
fn=load_model_config, # 直接使用 load_model_config 函数
inputs=[config_dropdown], # config_dropdown 组件本身作为输入
outputs=[GPT_dropdown, SoVITS_dropdown, inp_ref, prompt_text, prompt_language] # 期望更新的组件列表
)
gr.Markdown(value=i18n("文本切分工具。太长的文本合成出来效果不一定好，所以太长建议先切。合成会根据文本的换行分开合成再拼起来。"))
with gr.Row():
text_inp = gr.Textbox(label=i18n("需要合成的切分前文本"), value="")
@ -643,12 +838,14 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
button3 = gr.Button(i18n("按中文句号。切"), variant="primary")
button4 = gr.Button(i18n("按英文句号.切"), variant="primary")
button5 = gr.Button(i18n("按标点符号切"), variant="primary")
button6 = gr.Button(i18n("推送"), variant="primary")
text_opt = gr.Textbox(label=i18n("切分后文本"), value="")
button1.click(cut1, [text_inp], [text_opt])
button2.click(cut2, [text_inp], [text_opt])
button3.click(cut3, [text_inp], [text_opt])
button4.click(cut4, [text_inp], [text_opt])
button5.click(cut5, [text_inp], [text_opt])
button6.click(echo, [text_opt], [text])
gr.Markdown(value=i18n("后续将支持转音素、手工修改音素、语音合成分步执行。"))
if __name__ == '__main__':