sync ms

README.md

@@ -4,7 +4,7 @@ emoji: 🪕🎶
 colorFrom: yellow
 colorTo: blue
 sdk: gradio
-sdk_version: 5.22.0
+sdk_version: 6.3.0
 app_file: app.py
 pinned: true
 license: mit

app.py

@@ -394,12 +394,9 @@ if __name__ == "__main__":
                 gr.Dropdown(choices=models, label=_L("选择模型"), value=models[0]),
             ],
             outputs=[
-                gr.Textbox(label=_L("状态栏"), show_copy_button=True),
-                gr.Textbox(label=_L("音频文件名"), show_copy_button=True),
-                gr.Textbox(
-                    label=_L("中国乐器识别"),
-                    show_copy_button=True,
-                ),
+                gr.Textbox(label=_L("状态栏"), buttons=["copy"]),
+                gr.Textbox(label=_L("音频文件名"), buttons=["copy"]),
+                gr.Textbox(label=_L("中国乐器识别"), buttons=["copy"]),
             ],
             examples=examples,
             cache_examples=False,
@@ -426,4 +423,4 @@ if __name__ == "__main__":
             ```"""
         )
 
-    demo.launch()
+    demo.launch(css="#gradio-share-link-button-0 { display: none; }")

model.py

@@ -1,8 +1,6 @@
 import torch
 import torch.nn as nn
 import torchvision.models as models
-from modelscope.msdatasets import MsDataset
-from datasets import load_dataset
 from utils import MODEL_DIR, EN_US
 
 
@@ -39,11 +37,16 @@ class EvalNet:
         return backbone_list[0]
 
     def _model_info(self, m_ver: str):
-        backbone_list = (
-            load_dataset("monetjoe/cv_backbones", split="train")
-            if EN_US
-            else MsDataset.load("monetjoe/cv_backbones", split="train")
-        )
+        if EN_US:
+            from datasets import load_dataset
+
+            backbone_list = load_dataset("monetjoe/cv_backbones", split="train")
+
+        else:
+            from modelscope.msdatasets import MsDataset
+
+            backbone_list = MsDataset.load("monetjoe/cv_backbones", split="train")
+
         backbone = self._get_backbone(m_ver, backbone_list)
         m_type = str(backbone["type"])
         input_size = int(backbone["input_size"])

requirements.txt

@@ -1,5 +1,4 @@
 librosa
 matplotlib
-modelscope[framework]
 torch
 torchvision

utils.py

@@ -1,8 +1,6 @@
 import os
 import torch
 import torchvision.transforms as transforms
-import huggingface_hub
-import modelscope
 from PIL import Image
 
 EN_US = os.getenv("LANG") != "zh_CN.UTF-8"
@@ -17,17 +15,21 @@ ZH2EN = {
     "引用": "Cite",
 }
 
-MODEL_DIR = (
-    huggingface_hub.snapshot_download(
+if EN_US:
+    import huggingface_hub
+
+    MODEL_DIR = huggingface_hub.snapshot_download(
         "ccmusic-database/CTIS",
         cache_dir="./__pycache__",
     )
-    if EN_US
-    else modelscope.snapshot_download(
+
+else:
+    import modelscope
+
+    MODEL_DIR = modelscope.snapshot_download(
         "ccmusic-database/CTIS",
         cache_dir="./__pycache__",
     )
-)
 
 
 def _L(zh_txt: str):