diff --git a/GPT_SoVITS/config.json b/GPT_SoVITS/config.json index 0965b480..73825583 100644 --- a/GPT_SoVITS/config.json +++ b/GPT_SoVITS/config.json @@ -1,3 +1,7 @@ { - "running_on" : "local" + "running_on" : "local", + "Default":{ + "GPT_Path": "不训练直接推v3底模！", + "SoVITS_Path": "不训练直接推v2ProPlus底模！" + } } \ No newline at end of file diff --git a/GPT_SoVITS/feature_extractor/cnhubert.py b/GPT_SoVITS/feature_extractor/cnhubert.py index f22b8d09..a81de48e 100644 --- a/GPT_SoVITS/feature_extractor/cnhubert.py +++ b/GPT_SoVITS/feature_extractor/cnhubert.py @@ -24,6 +24,7 @@ class CNHubert(nn.Module): super().__init__() if base_path is None: base_path = cnhubert_base_path + print(f"Loading CN-Hubert from \"{base_path}\"") if os.path.exists(base_path): ... else: @@ -69,6 +70,7 @@ class CNHubert(nn.Module): def get_model(): + print("cnhubert_base_path:", cnhubert_base_path) model = CNHubert() model.eval() return model diff --git a/GPT_SoVITS/inference_webui.py b/GPT_SoVITS/inference_webui.py index 709b5d56..ebc18c9a 100644 --- a/GPT_SoVITS/inference_webui.py +++ b/GPT_SoVITS/inference_webui.py @@ -12,6 +12,7 @@ import sys import json from pathlib import Path import uuid +from scipy.io.wavfile import write @@ -31,6 +32,7 @@ with open(merge_dir_txt2(get_my_dir(), "config.json"), "r", encoding="utf-8") as config_json = f.read() config_json = json.loads(config_json) running_on = config_json["running_on"] + Default = config_json["Default"] ROOT_DIR = str(get_parent_dir(get_my_dir())) sys.path.append(get_my_dir()) @@ -124,6 +126,7 @@ with open("./weight.json", "r", encoding="utf-8") as file: if isinstance(sovits_path, list): sovits_path = sovits_path[0] + # print(2333333) # print(os.environ["gpt_path"]) # print(gpt_path) @@ -150,7 +153,7 @@ import numpy as np from feature_extractor import cnhubert from transformers import AutoModelForMaskedLM, AutoTokenizer -cnhubert.cnhubert_base_path = cnhubert_base_path +cnhubert.cnhubert_base_path = merge_dir_txt2(ROOT_DIR, cnhubert_base_path) import random @@ -184,6 +187,12 @@ language = os.environ.get("language", "Auto") language = sys.argv[-1] if sys.argv[-1] in scan_language_list() else language i18n = I18nAuto(language=language) + +if gpt_path in [None, "",]: + gpt_path = str(merge_dir_txt2(ROOT_DIR, name2gpt_path[i18n(Default["GPT_Path"])])) +if sovits_path in [None, "",]: + sovits_path = str(merge_dir_txt2(ROOT_DIR, name2sovits_path[i18n(Default["SoVITS_Path"])])) + # os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1' # 确保直接启动推理UI时也能够设置。 if torch.cuda.is_available(): @@ -214,8 +223,8 @@ dict_language_v2 = { } dict_language = dict_language_v1 if version == "v1" else dict_language_v2 -tokenizer = AutoTokenizer.from_pretrained(bert_path) -bert_model = AutoModelForMaskedLM.from_pretrained(bert_path) +tokenizer = AutoTokenizer.from_pretrained(str(merge_dir_txt2(ROOT_DIR,bert_path))) +bert_model = AutoModelForMaskedLM.from_pretrained(str(merge_dir_txt2(ROOT_DIR,bert_path))) if is_half == True: bert_model = bert_model.half().to(device) else: @@ -428,6 +437,7 @@ except: def change_gpt_weights(gpt_path): + print("gpt_path:", gpt_path) if "！" in gpt_path or "!" in gpt_path: gpt_path = name2gpt_path[gpt_path] global hz, max_sec, t2s_model, config @@ -1205,7 +1215,204 @@ def get_tts_wav( else: return opt_sr, (audio_opt * 32767).astype(np.int16) +def batched_tts_wav( + ref_wav_path, + prompt_text, + prompt_language, + texts, + 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=None, + sample_steps=8, + if_sr=False, + pause_second=0.3, + SaveSvEmb=False, + SaveRefers=False, + SaveSvEmbName="sv_emb.voice", + SaveRefersName="refers.voice", + + SaveGE=False, + SaveGEName="ge.voice", + + InjectSvEmb=False, + InjectRefers=False, + InjectSvEmbName="sv_emb.voice", + InjectRefersName="refers.voice", + + EnableAudioLoad=True, + + SaveOutputAsUndecoded=False, + SaveOutputAsUndecodedName="output.voice", + AddRandomSaltToSaveOutputAsUndecodedName=False, + + ReturnWay = "yield", # "yield" or "return" +): + count = 0 + out = [] + SaveDir = merge_dir_txt2(ROOT_DIR,"output","tts_output",f"batch_{uuid.uuid4()}") + if not os.path.exists(SaveDir): + os.makedirs(SaveDir,exist_ok=True) + for text in texts: + if text in [None, " ", ""]: + gr.Warning(i18n(f"输入文本第{count}行中有空行，已跳过")) + continue + else: + unparsed = get_tts_wav( + ref_wav_path, + prompt_text, + prompt_language, + text, + text_language, + how_to_cut, + top_k, + top_p, + temperature, + ref_free, + speed, + if_freeze, + inp_refs, + sample_steps, + if_sr, + pause_second, + + SaveSvEmb, + SaveRefers, + SaveSvEmbName, + SaveRefersName, + + SaveGE, + SaveGEName, + + InjectSvEmb, + InjectRefers, + InjectSvEmbName, + InjectRefersName, + + EnableAudioLoad, + + SaveOutputAsUndecoded, + SaveOutputAsUndecodedName, + AddRandomSaltToSaveOutputAsUndecodedName, + "yield", + ) + unparsed = list(unparsed) + print(unparsed) + a = text.strip().replace(' ','_').replace('\n','_') + wav_path = os.path.join(SaveDir,f"tts_output_{a}_{str(uuid.uuid4())}.wav") + write(wav_path, unparsed[0][0], unparsed[0][1]) + out.append(wav_path) + count += 1 + if ReturnWay == "yield": + yield SaveDir + else: + return SaveDir + +def read_tts_batch_file(file_path): + ret = [] + with open(file_path, 'r', encoding='utf-8') as f: + lines = f.readlines() + for l in lines: + if l.strip() in [None, " ", ""]: + continue + else: + ret.append(l) + return ret + +def batch_tts( + ref_wav_path, + prompt_text, + prompt_language, + text_paths, + 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=None, + sample_steps=8, + if_sr=False, + pause_second=0.3, + + SaveSvEmb=False, + SaveRefers=False, + SaveSvEmbName="sv_emb.voice", + SaveRefersName="refers.voice", + + SaveGE=False, + SaveGEName="ge.voice", + + InjectSvEmb=False, + InjectRefers=False, + InjectSvEmbName="sv_emb.voice", + InjectRefersName="refers.voice", + + EnableAudioLoad=True, + + SaveOutputAsUndecoded=False, + SaveOutputAsUndecodedName="output.voice", + AddRandomSaltToSaveOutputAsUndecodedName=False, + + ReturnWay = "yield", # "yield" or "return" +): + print(text_paths) + text_list = [] + for i in text_paths: + text_list.extend(read_tts_batch_file(i)) + out = batched_tts_wav( + ref_wav_path, + prompt_text, + prompt_language, + text_list, + text_language, + how_to_cut, + top_k, + top_p, + temperature, + ref_free, + speed, + if_freeze, + inp_refs, + sample_steps, + if_sr, + pause_second, + + SaveSvEmb, + SaveRefers, + SaveSvEmbName, + SaveRefersName, + + SaveGE, + SaveGEName, + + InjectSvEmb, + InjectRefers, + InjectSvEmbName, + InjectRefersName, + + EnableAudioLoad, + + SaveOutputAsUndecoded, + SaveOutputAsUndecodedName, + AddRandomSaltToSaveOutputAsUndecodedName, + + "yield" + ) + out = list(out) + + if ReturnWay == "yield": + yield out + else: + return out def close_serv(): if running_on == "local": sys.exit(0) @@ -1540,6 +1747,25 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css show_label=True, visible=False if model_version != "v3" else True, ) + with gr.Row(): + gr.Markdown(html_center(i18n("批量语音合成参数"), "h3")) + with gr.Column(scale=13): + txt_paths = gr.File(label=i18n("批量语音合成文本文件，每行一个文本"), + file_types=[".txt"], + interactive=True, + file_count="multiple", + scale=13) + with gr.Column(scale=7): + out = gr.File(label=i18n("批量合成输出的语音文件"), + file_types=[".wav"], + file_count="directory",) + start_batch_btn = gr.Button(i18n("开始批量合成"), + variant="primary", + size="lg", + interactive=True, + scale=25) + + gr.Markdown(html_center(i18n("*请填写需要合成的目标文本和语种模式"), "h3")) with gr.Row(): with gr.Column(scale=13): @@ -1648,7 +1874,51 @@ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css ], [output], + api_name="get_tts_wav", ) + + start_batch_btn.click( + batch_tts, + [ + inp_ref, + prompt_text, + prompt_language, + txt_paths, + text_language, + how_to_cut, + top_k, + top_p, + temperature, + ref_text_free, + speed, + if_freeze, + inp_refs, + sample_steps, + if_sr_Checkbox, + pause_second_slider, + + SaveSvEmb, + SaveRefers, + SaveSvEmbName, + SaveRefersName, + SaveGE, + SaveGEName, + InjectSvEmb, + InjectRefers, + InjectSvEmbName, + InjectRefersName, + EnableAudioLoad, + + SaveOutputAsUndecoded, + SaveOutputAsUndecodedName, + AddRandomSaltToSaveOutputAsUndecodedName, + + ], + [out], + + api_name="batch_tts", + ) + SoVITS_dropdown.change( change_sovits_weights, [SoVITS_dropdown, prompt_language, text_language], diff --git a/GPT_SoVITS/sv.py b/GPT_SoVITS/sv.py index 22e70369..7fab06aa 100644 --- a/GPT_SoVITS/sv.py +++ b/GPT_SoVITS/sv.py @@ -1,9 +1,10 @@ import sys import os import torch +from pathlib import Path -sys.path.append(f"{os.getcwd()}/GPT_SoVITS/eres2net") -sv_path = "GPT_SoVITS/pretrained_models/sv/pretrained_eres2netv2w24s4ep4.ckpt" +sys.path.append(f"{str(Path(os.path.dirname(os.path.abspath(__file__))).parent)}/GPT_SoVITS/eres2net") +sv_path = f"{str(Path(os.path.dirname(os.path.abspath(__file__))).parent)}/GPT_SoVITS/pretrained_models/sv/pretrained_eres2netv2w24s4ep4.ckpt" from ERes2NetV2 import ERes2NetV2 import kaldi as Kaldi