优化

app.py

@@ -48,7 +48,7 @@ if not os.path.exists(os.path.join(DOWNLOAD_DIR,'config.json'):
     print('下载配置文件...')
     model_configfile = hf_hub_download(repo_id=MODEL_REPO,filename='config.json',local_dir=DOWNLOAD_DIR)
 if not os.path.exists(os.path.join('./pretrain/checkpoint_best_legacy_500.pt'):
-    print('下载预训练模型文件...)
+    print('下载预训练模型文件...')
     checkpoint_pt = hf_hub_download(repo_id=CHECKPOINT_REPO,filename='checkpoint_best_legacy_500.pt',local_dir='./pretrain')
 class HParams():
     def __init__(self, **kwargs):

app.py.bak

@@ -23,6 +23,7 @@ import soundfile
 from inference import infer_tool
 from inference import slicer
 from inference.infer_tool import Svc
+from huggingface_hub import hf_hub_download
 
 logging.getLogger('numba').setLevel(logging.WARNING)
 chunks_dict = infer_tool.read_temp("inference/chunks_temp.json")
@@ -36,8 +37,19 @@ logging.getLogger('multipart').setLevel(logging.WARNING)
 model = None
 spk = None
 debug = False
-
-
+MODEL_REPO = 'Asankilp/gochiusa-sovits4.0'
+MODEL_NAME = 'G_240000.pth'
+DOWNLOAD_DIR = './downloaded'
+CHECKPOINT_REPO = 'WitchHuntTV/checkpoint_best_legacy_500.pt'
+if not os.path.exists(os.path.join(DOWNLOAD_DIR,MODEL_NAME):
+    print('下载模型文件...')
+    model_pth = hf_hub_download(repo_id=MODEL_REPO,filename=MODEL_NAME,local_dir=DOWNLOAD_DIR)
+if not os.path.exists(os.path.join(DOWNLOAD_DIR,'config.json'):
+    print('下载配置文件...')
+    model_configfile = hf_hub_download(repo_id=MODEL_REPO,filename='config.json',local_dir=DOWNLOAD_DIR)
+if not os.path.exists(os.path.join('./pretrain/checkpoint_best_legacy_500.pt'):
+    print('下载预训练模型文件...)
+    checkpoint_pt = hf_hub_download(repo_id=CHECKPOINT_REPO,filename='checkpoint_best_legacy_500.pt',local_dir='./pretrain')
 class HParams():
     def __init__(self, **kwargs):
         for k, v in kwargs.items():
@@ -174,10 +186,11 @@ def vc_fn2(sid, input_audio, vc_transform, auto_f0, cluster_ratio, slice_db, noi
 models_info = [
     {
         "description": """
-                      gochiusa test
+                      请问你今天要来点so-vits-svc 4.0模型吗？\n\n
+                      * 模型尚处于半成品（
                        """,
-        "model_path": "./G_240000.pth",
-        "config_path": "./config.json",
+        "model_path": os.path.join(DOWNLOAD_DIR,MODEL_NAME),
+        "config_path": os.path.join(DOWNLOAD_DIR,'config.json'),
     }
 ]
 
@@ -240,11 +253,7 @@ if __name__ == "__main__":
     parser.add_argument('-ft', '--f0_filter_threshold', type=float, default=0.05,
                         help='F0过滤阈值，只有使用crepe时有效. 数值范围从0-1. 降低该值可减少跑调概率，但会增加哑音')
     args = parser.parse_args()
-    categories = ["Blue Archive"]
-    others = {
-        "PCR vits-fast-fineturning": "https://huggingface.co/spaces/FrankZxShen/vits-fast-finetuning-pcr",
-        "Blue Archive vits-fast-fineturning": "https://huggingface.co/spaces/FrankZxShen/vits-fast-fineturning-models-ba",
-    }
+    categories = ['Gochiusa']
     for info in models_info:
         config_path = info['config_path']
         model_path = info['model_path']
@@ -339,24 +348,6 @@ if __name__ == "__main__":
                                         cl_num, lg_num, lgr_num, f0_predictor, enhancer_adaptive_key, cr_threshold], [vc_output1, vc_output2])
                 vc_submit2.click(vc_fn2, [sid, vc_input3, vc_transform, auto_f0, cluster_ratio, slice_db, noise_scale, pad_seconds, cl_num,
                                           lg_num, lgr_num, text2tts, tts_rate, tts_voice, f0_predictor, enhancer_adaptive_key, cr_threshold], [vc_output1, vc_output2])
-                # gr.Examples(
-                #     examples=example,
-                #     inputs=[textbox, char_dropdown, language_dropdown,
-                #             duration_slider, symbol_input],
-                #     outputs=[text_output, audio_output],
-                #     fn=tts_fn
-                # )
-            for category, link in others.items():
-                with gr.TabItem(category):
-                    gr.Markdown(
-                        f'''
-                        <center>
-                          <h2>Click to Go</h2>
-                          <a href="{link}">
-                            <img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-xl-dark.svg"
-                          </a>
-                        </center>
-                        '''
-                    )
+                
 
     app.queue(concurrency_count=3).launch(show_api=False, share=args.share)