feat:Added batch tts option

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！"
+    }
 }

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

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)
+tokenizer = AutoTokenizer.from_pretrained(str(merge_dir_txt2(ROOT_DIR,bert_path)))
-bert_model = AutoModelForMaskedLM.from_pretrained(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],

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")
+sys.path.append(f"{str(Path(os.path.dirname(os.path.abspath(__file__))).parent)}/GPT_SoVITS/eres2net")
-sv_path = "GPT_SoVITS/pretrained_models/sv/pretrained_eres2netv2w24s4ep4.ckpt"
+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