Merge branch 'main' into patch-4

GPT_SoVITS/inference_webui.py

@@ -4,12 +4,30 @@ logging.getLogger("urllib3").setLevel(logging.ERROR)
 logging.getLogger("httpcore").setLevel(logging.ERROR)
 logging.getLogger("httpx").setLevel(logging.ERROR)
 logging.getLogger("asyncio").setLevel(logging.ERROR)
+
+logging.getLogger("charset_normalizer").setLevel(logging.ERROR)
+logging.getLogger("torchaudio._extension").setLevel(logging.ERROR)
 import pdb
 
-gpt_path = os.environ.get(
-    "gpt_path", "pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
-)
-sovits_path = os.environ.get("sovits_path", "pretrained_models/s2G488k.pth")
+if os.path.exists("./gweight.txt"):
+    with open("./gweight.txt", 'r',encoding="utf-8") as file:
+        gweight_data = file.read()
+        gpt_path = os.environ.get(
+    "gpt_path", gweight_data)
+else:
+    gpt_path = os.environ.get(
+    "gpt_path", "GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt")
+
+if os.path.exists("./sweight.txt"):
+    with open("./sweight.txt", 'r',encoding="utf-8") as file:
+        sweight_data = file.read()
+        sovits_path = os.environ.get("sovits_path", sweight_data)
+else:
+    sovits_path = os.environ.get("sovits_path", "GPT_SoVITS/pretrained_models/s2G488k.pth")
+# gpt_path = os.environ.get(
+#     "gpt_path", "pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt"
+# )
+# sovits_path = os.environ.get("sovits_path", "pretrained_models/s2G488k.pth")
 cnhubert_base_path = os.environ.get(
     "cnhubert_base_path", "pretrained_models/chinese-hubert-base"
 )
@@ -60,7 +78,7 @@ def get_bert_feature(text, word2ph):
     with torch.no_grad():
         inputs = tokenizer(text, return_tensors="pt")
         for i in inputs:
-            inputs[i] = inputs[i].to(device)  #####输入是long不用管精度问题，精度随bert_model
+            inputs[i] = inputs[i].to(device)
         res = bert_model(**inputs, output_hidden_states=True)
         res = torch.cat(res["hidden_states"][-3:-2], -1)[0].cpu()[1:-1]
     assert len(word2ph) == len(text)
@@ -124,6 +142,7 @@ def change_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)
 change_sovits_weights(sovits_path)
 
 def change_gpt_weights(gpt_path):
@@ -140,6 +159,7 @@ def change_gpt_weights(gpt_path):
     t2s_model.eval()
     total = sum([param.nelement() for param in t2s_model.parameters()])
     print("Number of parameter: %.2fM" % (total / 1e6))
+    with open("./gweight.txt","w",encoding="utf-8")as f:f.write(gpt_path)
 change_gpt_weights(gpt_path)
 
 def get_spepc(hps, filename):
@@ -213,7 +233,7 @@ def nonen_clean_text_inf(text, language):
         lang = langlist[i]
         phones, word2ph, norm_text = clean_text_inf(textlist[i], lang)
         phones_list.append(phones)
-        if lang=="en" or "ja":
+        if lang == "en" or "ja":
             pass
         else:
             word2ph_list.append(word2ph)
@@ -271,6 +291,7 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
     t1 = ttime()
     prompt_language = dict_language[prompt_language]
     text_language = dict_language[text_language]
+
     if prompt_language == "en":
         phones1, word2ph1, norm_text1 = clean_text_inf(prompt_text, prompt_language)
     else:
@@ -281,11 +302,11 @@ def get_tts_wav(ref_wav_path, prompt_text, prompt_language, text, text_language)
         bert1 = get_bert_inf(phones1, word2ph1, norm_text1, prompt_language)
     else:
         bert1 = nonen_get_bert_inf(prompt_text, prompt_language)
+    
     for text in texts:
         # 解决输入目标文本的空行导致报错的问题
         if (len(text.strip()) == 0):
             continue
-            
         if text_language == "en":
             phones2, word2ph2, norm_text2 = clean_text_inf(text, text_language)
         else:

tools/uvr5/webui.py

@@ -52,7 +52,8 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
             paths = [path.name for path in paths]
         for path in paths:
             inp_path = os.path.join(inp_root, path)
-            need_reformat = 1
+            if(os.path.isfile(inp_path)==False):continue
+            try:
                 done = 0
                 try:
                     y, sr = librosa.load(inp_path, sr=None)
@@ -97,6 +98,9 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
                             "%s->%s" % (os.path.basename(inp_path), traceback.format_exc())
                         )
                         yield "\n".join(infos)
+            except:
+                infos.append("Oh my god. %s->%s"%(os.path.basename(inp_path), traceback.format_exc()))
+                yield "\n".join(infos)
     except:
         infos.append(traceback.format_exc())
         yield "\n".join(infos)