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https://github.com/RVC-Boss/GPT-SoVITS.git
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chores (#1528)
* chores * ... * Add files via upload * ... * remove gradio warnings * Update inference_webui.py Fix inference_cli issue
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@ -182,6 +182,11 @@ class TTS_Config:
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def _load_configs(self, configs_path: str)->dict:
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def _load_configs(self, configs_path: str)->dict:
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if os.path.exists(configs_path):
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...
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else:
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print(i18n("路径不存在,使用默认配置"))
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self.save_configs(configs_path)
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with open(configs_path, 'r') as f:
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with open(configs_path, 'r') as f:
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configs = yaml.load(f, Loader=yaml.FullLoader)
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configs = yaml.load(f, Loader=yaml.FullLoader)
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@ -748,7 +753,8 @@ class TTS:
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phones, bert_features, norm_text = \
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phones, bert_features, norm_text = \
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self.text_preprocessor.segment_and_extract_feature_for_text(
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self.text_preprocessor.segment_and_extract_feature_for_text(
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prompt_text,
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prompt_text,
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prompt_lang)
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prompt_lang,
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self.configs.version)
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self.prompt_cache["phones"] = phones
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self.prompt_cache["phones"] = phones
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self.prompt_cache["bert_features"] = bert_features
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self.prompt_cache["bert_features"] = bert_features
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self.prompt_cache["norm_text"] = norm_text
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self.prompt_cache["norm_text"] = norm_text
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@ -760,7 +766,7 @@ class TTS:
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t1 = ttime()
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t1 = ttime()
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data:list = None
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data:list = None
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if not return_fragment:
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if not return_fragment:
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data = self.text_preprocessor.preprocess(text, text_lang, text_split_method)
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data = self.text_preprocessor.preprocess(text, text_lang, text_split_method, self.configs.version)
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if len(data) == 0:
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if len(data) == 0:
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yield self.configs.sampling_rate, np.zeros(int(self.configs.sampling_rate),
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yield self.configs.sampling_rate, np.zeros(int(self.configs.sampling_rate),
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dtype=np.int16)
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dtype=np.int16)
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@ -55,9 +55,9 @@ class TextPreprocessor:
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self.tokenizer = tokenizer
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self.tokenizer = tokenizer
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self.device = device
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self.device = device
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def preprocess(self, text:str, lang:str, text_split_method:str, version:str="v1")->List[Dict]:
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def preprocess(self, text:str, lang:str, text_split_method:str, version:str="v2")->List[Dict]:
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print(i18n("############ 切分文本 ############"))
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print(i18n("############ 切分文本 ############"))
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text = self.replace_consecutive_punctuation(text) # 变量命名应该是写错了
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text = self.replace_consecutive_punctuation(text)
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texts = self.pre_seg_text(text, lang, text_split_method)
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texts = self.pre_seg_text(text, lang, text_split_method)
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result = []
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result = []
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print(i18n("############ 提取文本Bert特征 ############"))
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print(i18n("############ 提取文本Bert特征 ############"))
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@ -204,7 +204,7 @@ class TextPreprocessor:
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phone_level_feature = torch.cat(phone_level_feature, dim=0)
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phone_level_feature = torch.cat(phone_level_feature, dim=0)
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return phone_level_feature.T
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return phone_level_feature.T
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def clean_text_inf(self, text:str, language:str, version:str="v1"):
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def clean_text_inf(self, text:str, language:str, version:str="v2"):
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phones, word2ph, norm_text = clean_text(text, language, version)
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phones, word2ph, norm_text = clean_text(text, language, version)
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phones = cleaned_text_to_sequence(phones, version)
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phones = cleaned_text_to_sequence(phones, version)
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return phones, word2ph, norm_text
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return phones, word2ph, norm_text
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1
GPT_SoVITS/configs/.gitignore
vendored
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1
GPT_SoVITS/configs/.gitignore
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@ -0,0 +1 @@
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*.yaml
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@ -21,6 +21,11 @@ import LangSegment, os, re, sys, json
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import pdb
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import pdb
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import torch
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import torch
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try:
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import gradio.analytics as analytics
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analytics.version_check = lambda:None
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except:...
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version=os.environ.get("version","v2")
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version=os.environ.get("version","v2")
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pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"]
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pretrained_sovits_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth", "GPT_SoVITS/pretrained_models/s2G488k.pth"]
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pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"]
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pretrained_gpt_name=["GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"]
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@ -392,7 +397,8 @@ def merge_short_text_in_array(texts, threshold):
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##ref_wav_path+prompt_text+prompt_language+text(单个)+text_language+top_k+top_p+temperature
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##ref_wav_path+prompt_text+prompt_language+text(单个)+text_language+top_k+top_p+temperature
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# cache_tokens={}#暂未实现清理机制
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# cache_tokens={}#暂未实现清理机制
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cache= {}
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cache= {}
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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,speed=1,if_freeze=False,inp_refs=123):
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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
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=False,speed=1,if_freeze=False,inp_refs=None):
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global cache
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global cache
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if ref_wav_path:pass
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if ref_wav_path:pass
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else:gr.Warning(i18n('请上传参考音频'))
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else:gr.Warning(i18n('请上传参考音频'))
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@ -23,6 +23,11 @@ logging.getLogger("torchaudio._extension").setLevel(logging.ERROR)
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import pdb
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import pdb
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import torch
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import torch
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try:
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import gradio.analytics as analytics
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analytics.version_check = lambda:None
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except:...
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infer_ttswebui = os.environ.get("infer_ttswebui", 9872)
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infer_ttswebui = os.environ.get("infer_ttswebui", 9872)
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infer_ttswebui = int(infer_ttswebui)
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infer_ttswebui = int(infer_ttswebui)
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@ -4,6 +4,11 @@ import json
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import os
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import os
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import uuid
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import uuid
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try:
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import gradio.analytics as analytics
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analytics.version_check = lambda:None
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except:...
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import librosa
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import librosa
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import gradio as gr
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import gradio as gr
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import numpy as np
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import numpy as np
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@ -14,6 +14,11 @@ from mdxnet import MDXNetDereverb
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from vr import AudioPre, AudioPreDeEcho
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from vr import AudioPre, AudioPreDeEcho
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from bsroformer import BsRoformer_Loader
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from bsroformer import BsRoformer_Loader
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try:
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import gradio.analytics as analytics
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analytics.version_check = lambda:None
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except:...
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weight_uvr5_root = "tools/uvr5/uvr5_weights"
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weight_uvr5_root = "tools/uvr5/uvr5_weights"
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uvr5_names = []
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uvr5_names = []
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for name in os.listdir(weight_uvr5_root):
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for name in os.listdir(weight_uvr5_root):
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