update dev branch

GPT_SoVITS/download.py

@@ -1,5 +1,5 @@
 import os, sys
 now_dir = os.getcwd()
 sys.path.insert(0, now_dir)
-from .text.g2pw import G2PWPinyin
+from text.g2pw import G2PWPinyin
 g2pw = G2PWPinyin(model_dir="GPT_SoVITS/text/G2PWModel",model_source="GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large",v_to_u=False, neutral_tone_with_five=True)

quick_inference.py

@@ -1,6 +1,7 @@
 import os, re, logging
 import LangSegment
 import pdb
+import json
 import torch
 import gradio as gr
 from transformers import AutoModelForMaskedLM, AutoTokenizer
@@ -21,7 +22,8 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 i18n = I18nAuto()
 
-dict_language = {
+version = os.environ.get("version", "v2")
+dict_language_v1 = {
     i18n("中文"): "all_zh",  # 全部按中文识别
     i18n("英文"): "en",  # 全部按英文识别#######不变
     i18n("日文"): "all_ja",  # 全部按日文识别
@@ -29,6 +31,20 @@ dict_language = {
     i18n("日英混合"): "ja",  # 按日英混合识别####不变
     i18n("多语种混合"): "auto",  # 多语种启动切分识别语种
 }
+dict_language_v2 = {
+    i18n("中文"): "all_zh",  # 全部按中文识别
+    i18n("英文"): "en",  # 全部按英文识别#######不变
+    i18n("日文"): "all_ja",  # 全部按日文识别
+    i18n("粤语"): "all_yue",  # 全部按中文识别
+    i18n("韩文"): "all_ko",  # 全部按韩文识别
+    i18n("中英混合"): "zh",  # 按中英混合识别####不变
+    i18n("日英混合"): "ja",  # 按日英混合识别####不变
+    i18n("粤英混合"): "yue",  # 按粤英混合识别####不变
+    i18n("韩英混合"): "ko",  # 按韩英混合识别####不变
+    i18n("多语种混合"): "auto",  # 多语种启动切分识别语种
+    i18n("多语种混合(粤语)"): "auto_yue",  # 多语种启动切分识别语种
+}
+dict_language = dict_language_v1 if version == 'v1' else dict_language_v2
 
 is_share = os.environ.get("is_share", "False")
 is_share = eval(is_share)
@@ -283,12 +299,18 @@ def set_gpt_weights(gpt_path):
     with open("./gweight.txt", "w", encoding="utf-8") as f: f.write(gpt_path)
 
 
-def set_sovits_weights(sovits_path):
-    global vq_model, hps
+def set_sovits_weights(sovits_path, prompt_language=None, text_language=None):
+    global vq_model, hps, version, dict_language
     dict_s2 = torch.load(sovits_path, map_location="cpu")
     hps = dict_s2["config"]
     hps = DictToAttrRecursive(hps)
     hps.model.semantic_frame_rate = "25hz"
+    if dict_s2['weight']['enc_p.text_embedding.weight'].shape[0] == 322:
+        hps.model.version = "v1"
+    else:
+        hps.model.version = "v2"
+    version = hps.model.version
+    print("sovits版本:", hps.model.version)
     vq_model = SynthesizerTrn(
         hps.data.filter_length // 2 + 1,
         hps.train.segment_size // hps.data.hop_length,
@@ -303,8 +325,26 @@ def set_sovits_weights(sovits_path):
         vq_model = vq_model.to(device)
     vq_model.eval()
     print(vq_model.load_state_dict(dict_s2["weight"], strict=False))
-    with open("./sweight.txt", "w", encoding="utf-8") as f:
-        f.write(sovits_path)
+    dict_language = dict_language_v1 if version == 'v1' else dict_language_v2
+    with open("./weight.json") as f:
+        data = f.read()
+        data = json.loads(data)
+        data["SoVITS"][version] = sovits_path
+    with open("./weight.json", "w") as f:
+        f.write(json.dumps(data))
+    if prompt_language is not None and text_language is not None:
+        if prompt_language in list(dict_language.keys()):
+            prompt_text_update, prompt_language_update = {'__type__': 'update'}, {'__type__': 'update', 'value': prompt_language}
+        else:
+            prompt_text_update = {'__type__': 'update', 'value': ''}
+            prompt_language_update = {'__type__': 'update', 'value': i18n("中文")}
+        if text_language in list(dict_language.keys()):
+            text_update, text_language_update = {'__type__': 'update'}, {'__type__': 'update', 'value': text_language}
+        else:
+            text_update = {'__type__': 'update', 'value': ''}
+            text_language_update = {'__type__': 'update', 'value': i18n("中文")}
+        return {'__type__': 'update', 'choices': list(dict_language.keys())}, {'__type__': 'update', 'choices': list(
+            dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update
 
 
 def gen_audio(ref_wav_path, prompt_text, text_to_speak, output_file, top_k=20, top_p=0.6, temperature=0.6, ref_free=False):
@@ -454,12 +494,12 @@ else:
 
 
 def speak(text_to_speak):
-    sovits_path = "SoVITS_weights/阿贝多_e12_s2748.pth"
+    sovits_path = "SoVITS_weights/迪希雅_e15_s1050.pth"
     set_sovits_weights(sovits_path)
-    gpt_path = "GPT_weights/阿贝多-e10.ckpt"
+    gpt_path = "GPT_weights/迪希雅-e10.ckpt"
     set_gpt_weights(gpt_path)
-    ref_wav_path = "audio/首先，先看看这不明来源的元素力，究竟是如何对外流动的.wav"
-    prompt_text = "首先，先看看这不明来源的元素力，究竟是如何对外流动的。"
+    ref_wav_path = "audio/呼玛伊家也还会招工，报酬优厚，我和兄弟们自然没有拒绝的理由.wav"
+    prompt_text = "呼玛伊家也还会招工，报酬优厚，我和兄弟们自然没有拒绝的理由。"
     # text_to_speak = "我...我...我不知道你在说什么，我们之间没有秘密呀。可能你弄错了，我们平时关系很好的，请不要误会。"
     # 创建一个时间戳的文件名
     output_file = "outputs/" + str(int(ttime())) + ".wav"
@@ -468,7 +508,7 @@ def speak(text_to_speak):
 
 
 def main():
-    speak("放学了，我该回家了，你叫我留下来干什么？")
+    speak("你就是没用！")
 
 
 if __name__ == '__main__':