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https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2025-04-06 03:57:44 +08:00
Update inference_webui.py
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RVC-Boss
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@ -1,4 +1,5 @@
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import os, re, logging
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logging.getLogger("markdown_it").setLevel(logging.ERROR)
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logging.getLogger("urllib3").setLevel(logging.ERROR)
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logging.getLogger("httpcore").setLevel(logging.ERROR)
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@ -46,6 +47,7 @@ from transformers import AutoModelForMaskedLM, AutoTokenizer
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import numpy as np
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import librosa, torch
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from feature_extractor import cnhubert
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cnhubert.cnhubert_base_path = cnhubert_base_path
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from module.models import SynthesizerTrn
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@ -56,6 +58,7 @@ from time import time as ttime
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from module.mel_processing import spectrogram_torch
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from my_utils import load_audio
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from tools.i18n.i18n import I18nAuto
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i18n = I18nAuto()
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os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 确保直接启动推理UI时也能够设置。
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@ -74,6 +77,7 @@ if is_half == True:
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else:
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bert_model = bert_model.to(device)
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def get_bert_feature(text, word2ph):
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with torch.no_grad():
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inputs = tokenizer(text, return_tensors="pt")
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@ -89,6 +93,7 @@ def get_bert_feature(text, word2ph):
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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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class DictToAttrRecursive(dict):
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def __init__(self, input_dict):
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super().__init__(input_dict)
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@ -123,6 +128,7 @@ if is_half == True:
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else:
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ssl_model = ssl_model.to(device)
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def change_sovits_weights(sovits_path):
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global vq_model, hps
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dict_s2 = torch.load(sovits_path, map_location="cpu")
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@ -143,9 +149,13 @@ def change_sovits_weights(sovits_path):
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vq_model = vq_model.to(device)
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vq_model.eval()
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print(vq_model.load_state_dict(dict_s2["weight"], strict=False))
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with open("./sweight.txt","w",encoding="utf-8")as f:f.write(sovits_path)
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with open("./sweight.txt", "w", encoding="utf-8") as f:
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f.write(sovits_path)
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change_sovits_weights(sovits_path)
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def change_gpt_weights(gpt_path):
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global hz, max_sec, t2s_model, config
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hz = 50
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@ -161,8 +171,11 @@ def change_gpt_weights(gpt_path):
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total = sum([param.nelement() for param in t2s_model.parameters()])
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print("Number of parameter: %.2fM" % (total / 1e6))
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with open("./gweight.txt", "w", encoding="utf-8") as f: f.write(gpt_path)
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change_gpt_weights(gpt_path)
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def get_spepc(hps, filename):
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audio = load_audio(filename, int(hps.data.sampling_rate))
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audio = torch.FloatTensor(audio)
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@ -262,12 +275,16 @@ def nonen_get_bert_inf(text, language):
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return bert
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splits = {"，", "。", "？", "！", ",", ".", "?", "!", "~", ":", "：", "—", "…", }
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def get_first(text):
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pattern = "[" + "".join(re.escape(sep) for sep in splits) + "]"
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text = re.split(pattern, text)[0].strip()
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return text
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def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language, how_to_cut=i18n("不切")):
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t0 = ttime()
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prompt_text = prompt_text.strip("\n")
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@ -307,10 +324,16 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
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phones1, word2ph1, norm_text1 = clean_text_inf(prompt_text, prompt_language)
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else:
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phones1, word2ph1, norm_text1 = nonen_clean_text_inf(prompt_text, prompt_language)
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if(how_to_cut==i18n("凑四句一切")):text=cut1(text)
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elif(how_to_cut==i18n("凑50字一切")):text=cut2(text)
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elif(how_to_cut==i18n("按中文句号。切")):text=cut3(text)
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elif(how_to_cut==i18n("按英文句号.切")):text=cut4(text)
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if (how_to_cut == i18n("凑四句一切")):
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text = cut1(text)
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elif (how_to_cut == i18n("凑50字一切")):
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text = cut2(text)
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elif (how_to_cut == i18n("按中文句号。切")):
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text = cut3(text)
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elif (how_to_cut == i18n("按英文句号.切")):
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text = cut4(text)
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elif (how_to_cut == i18n("按标点符号切")):
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text = cut5(text)
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text = text.replace("\n\n", "\n").replace("\n\n", "\n").replace("\n\n", "\n")
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print(i18n("实际输入的目标文本(切句后):"), text)
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texts = text.split("\n")
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@ -380,6 +403,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language,
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np.int16
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)
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def split(todo_text):
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todo_text = todo_text.replace("……", "。").replace("——", "，")
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if todo_text[-1] not in splits:
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@ -440,10 +464,25 @@ def cut2(inp):
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def cut3(inp):
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inp = inp.strip("\n")
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return "\n".join(["%s" % item for item in inp.strip("。").split("。")])
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def cut4(inp):
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inp = inp.strip("\n")
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return "\n".join(["%s" % item for item in inp.strip(".").split(".")])
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# contributed by https://github.com/AI-Hobbyist/GPT-SoVITS/blob/main/GPT_SoVITS/inference_webui.py
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def cut5(inp):
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# if not re.search(r'[^\w\s]', inp[-1]):
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# inp += '。'
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inp = inp.strip("\n")
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punds = r'[,.;?!、，。？！;：]'
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items = re.split(f'({punds})', inp)
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items = ["".join(group) for group in zip(items[::2], items[1::2])]
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opt = "\n".join(items)
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return opt
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def custom_sort_key(s):
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# 使用正则表达式提取字符串中的数字部分和非数字部分
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parts = re.split('(\d+)', s)
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@ -451,16 +490,20 @@ def custom_sort_key(s):
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parts = [int(part) if part.isdigit() else part for part in parts]
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return parts
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def change_choices():
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SoVITS_names, GPT_names = get_weights_names()
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return {"choices": sorted(SoVITS_names, key=custom_sort_key), "__type__": "update"}, {"choices": sorted(GPT_names, key=custom_sort_key), "__type__": "update"}
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pretrained_sovits_name = "GPT_SoVITS/pretrained_models/s2G488k.pth"
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pretrained_gpt_name = "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
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SoVITS_weight_root = "SoVITS_weights"
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GPT_weight_root = "GPT_weights"
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os.makedirs(SoVITS_weight_root, exist_ok=True)
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os.makedirs(GPT_weight_root, exist_ok=True)
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def get_weights_names():
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SoVITS_names = [pretrained_sovits_name]
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for name in os.listdir(SoVITS_weight_root):
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@ -469,6 +512,8 @@ def get_weights_names():
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for name in os.listdir(GPT_weight_root):
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if name.endswith(".ckpt"): GPT_names.append("%s/%s" % (GPT_weight_root, name))
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return SoVITS_names, GPT_names
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SoVITS_names, GPT_names = get_weights_names()
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with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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@ -499,8 +544,8 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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)
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how_to_cut = gr.Radio(
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label=i18n("怎么切"),
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choices=[i18n("不切"),i18n("凑四句一切"),i18n("凑50字一切"),i18n("按中文句号。切"),i18n("按英文句号.切"),],
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value=i18n("凑50字一切"),
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choices=[i18n("不切"), i18n("凑四句一切"), i18n("凑50字一切"), i18n("按中文句号。切"), i18n("按英文句号.切"), i18n("按标点符号切"), ],
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value=i18n("凑四句一切"),
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interactive=True,
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)
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inference_button = gr.Button(i18n("合成语音"), variant="primary")
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@ -519,11 +564,13 @@ with gr.Blocks(title="GPT-SoVITS WebUI") as app:
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button2 = gr.Button(i18n("凑50字一切"), variant="primary")
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button3 = gr.Button(i18n("按中文句号。切"), variant="primary")
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button4 = gr.Button(i18n("按英文句号.切"), variant="primary")
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button5 = gr.Button(i18n("按标点符号切"), variant="primary")
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text_opt = gr.Textbox(label=i18n("切分后文本"), value="")
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button1.click(cut1, [text_inp], [text_opt])
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button2.click(cut2, [text_inp], [text_opt])
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button3.click(cut3, [text_inp], [text_opt])
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button4.click(cut4, [text_inp], [text_opt])
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button5.click(cut5, [text_inp], [text_opt])
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gr.Markdown(value=i18n("后续将支持混合语种编码文本输入。"))
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app.queue(concurrency_count=511, max_size=1022).launch(
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