Upload app.py

app.py

@@ -62,8 +62,8 @@ from modelscope.utils.audio.audio_utils import TtsTrainType
 
 pretrained_model_id = 'damo/speech_personal_sambert-hifigan_nsf_tts_zh-cn_pretrain_16k'
 
-dataset_id = "/home/yiho/Personal-TTS-v3/output_training_data/"
-pretrain_work_dir = "/home/yiho/Personal-TTS-v3/pretrain_work_dir/"
+dataset_id = "/home/user/app/output_training_data/"
+pretrain_work_dir = "/home/user/app/pretrain_work_dir/"
 
 
 def auto_label(Voicetoclone, VoiceMicrophone):
@@ -73,9 +73,9 @@ def auto_label(Voicetoclone, VoiceMicrophone):
         audio = Voicetoclone
         
     try:
-        split_long_audio(whisper_model, audio, "/home/yiho/Personal-TTS-v3/test_wavs/")
-        input_wav = "/home/yiho/Personal-TTS-v3/test_wavs/"
-        output_data = "/home/yiho/Personal-TTS-v3/output_training_data/"
+        split_long_audio(whisper_model, audio, "/home/user/app/test_wavs/")
+        input_wav = "/home/user/app/test_wavs/"
+        output_data = "/home/user/app/output_training_data/"
         ret, report = run_auto_label(input_wav=input_wav, work_dir=output_data, resource_revision="v1.0.7")
     
     except Exception as e:
@@ -122,8 +122,8 @@ import shutil
 import datetime
 
 def save_model(worked_dir,dest_dir):
-    worked_dir = "/home/yiho/Personal-TTS-v3/pretrain_work_dir"
-    dest_dir = "/home/yiho/Personal-TTS-v3/trained_model"
+    worked_dir = "/home/user/app/pretrain_work_dir"
+    dest_dir = "/home/user/app/trained_model"
     # worked_dir: 临时工作目录
     # dest_dir: 目标存储目录
     # 检查 worked_dir 路径内是否有文件
@@ -137,13 +137,13 @@ def save_model(worked_dir,dest_dir):
         # 复制临时工作目录到目标文件夹
         shutil.copytree(worked_dir, dest_folder)
         # 清除训练缓存
-        shutil.rmtree("/home/yiho/Personal-TTS-v3/output_training_data")
-        shutil.rmtree("/home/yiho/Personal-TTS-v3/pretrain_work_dir")
-        shutil.rmtree("/home/yiho/Personal-TTS-v3/test_wavs")
+        shutil.rmtree("/home/user/app/output_training_data")
+        shutil.rmtree("/home/user/app/pretrain_work_dir")
+        shutil.rmtree("/home/user/app/test_wavs")
         # 重新创建一个同名的空目录
-        os.mkdir("/home/yiho/Personal-TTS-v3/output_training_data")
-        os.mkdir("/home/yiho/Personal-TTS-v3/pretrain_work_dir")
-        os.mkdir("/home/yiho/Personal-TTS-v3/test_wavs")
+        os.mkdir("/home/user/app/output_training_data")
+        os.mkdir("/home/user/app/pretrain_work_dir")
+        os.mkdir("/home/user/app/test_wavs")
         # 返回模型已成功保存为模型的名称
         return f"模型已成功保存为 {date_str}"
     else: # 如果 worked_dir 为空
@@ -157,7 +157,7 @@ import random
 
 def infer(text):
 
-  model_dir = "/home/yiho/Personal-TTS-v3/pretrain_work_dir/"
+  model_dir = "/home/user/app/pretrain_work_dir/"
 
   test_infer_abs = {
       'voice_name':
@@ -221,7 +221,7 @@ def infer(text):
 
 def infer_custom(model_name, text, noise_level): 
 
-  custom_model_dir = os.path.join("/home/yiho/Personal-TTS-v3/trained_model/", model_name) # 修改模型目录为用户指定的目录
+  custom_model_dir = os.path.join("/home/user/app/trained_model/", model_name) # 修改模型目录为用户指定的目录
 
   custom_infer_abs = {
       'voice_name':
@@ -283,7 +283,7 @@ def infer_custom(model_name, text, noise_level):
 
 
 # 已训练模型的路径trained_model
-trained_model = "/home/yiho/Personal-TTS-v3/trained_model/"
+trained_model = "/home/user/app/trained_model/"
 
 
 # 刷新模型列表下拉菜单
@@ -311,13 +311,13 @@ def rename_model(old_name, new_name):
 # 清除训练缓存
 def clear_cache(a):
     # 删除目录及其所有内容
-    shutil.rmtree("/home/yiho/Personal-TTS-v3/output_training_data")
-    shutil.rmtree("/home/yiho/Personal-TTS-v3/pretrain_work_dir")
-    shutil.rmtree("/home/yiho/Personal-TTS-v3/test_wavs")
+    shutil.rmtree("/home/user/app/output_training_data")
+    shutil.rmtree("/home/user/app/pretrain_work_dir")
+    shutil.rmtree("/home/user/app/test_wavs")
     # 重新创建一个同名的空目录
-    os.mkdir("/home/yiho/Personal-TTS-v3/output_training_data")
-    os.mkdir("/home/yiho/Personal-TTS-v3/pretrain_work_dir")
-    os.mkdir("/home/yiho/Personal-TTS-v3/test_wavs")
+    os.mkdir("/home/user/app/output_training_data")
+    os.mkdir("/home/user/app/pretrain_work_dir")
+    os.mkdir("/home/user/app/test_wavs")
     return "已清除缓存，请返回训练页面重新训练"
 
 
@@ -335,7 +335,7 @@ def FRCRN_De_Noise(noise_wav, noisemic_wav):
     
   ans = pipeline(
     Tasks.acoustic_noise_suppression,
-    model='/home/yiho/Personal-TTS-v3/damo/speech_frcrn_ans_cirm_16k')
+    model='/home/user/app/damo/speech_frcrn_ans_cirm_16k')
 
   # 生成文件名
   now = datetime.datetime.now()