sync ms

README.md

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

app.py

@@ -183,8 +183,8 @@ 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("状态栏"), buttons=["copy"]),
+                gr.Textbox(label=_L("音频文件名"), buttons=["copy"]),
                 gr.Dataframe(label=_L("古筝演奏技法逐帧检测")),
             ],
             examples=examples,
@@ -212,4 +212,4 @@ if __name__ == "__main__":
             ```"""
         )
 
-    demo.launch()
+    demo.launch(css="#gradio-share-link-button-0 { display: none; }")

model.py

@@ -3,8 +3,6 @@ import torch.nn as nn
 import torch.nn.functional as F
 import torchvision.models as models
 import numpy as np
-from modelscope.msdatasets import MsDataset
-from datasets import load_dataset
 from utils import EN_US
 
 
@@ -81,11 +79,16 @@ class EvalNet:
         raise ValueError("[Backbone not found] Please check if --model is correct!")
 
     def _model_info(self, backbone: 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_info = self._get_backbone(backbone, backbone_list)
         return (
             str(backbone_info["type"]),
@@ -234,11 +237,16 @@ class t_EvalNet:
         raise ValueError("[Backbone not found] Please check if --model is correct!")
 
     def _model_info(self, backbone: str):
-        backbone_list = (
-            load_dataset("monetjoe/cv_backbones", split="train")
-            if EN_US
-            else MsDataset.load("monetjoe/cv_backbones", split="v1")
-        )
+        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="v1")
+
         backbone_info = self._get_backbone(backbone, backbone_list)
         return (
             str(backbone_info["type"]),

requirements.txt

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

utils.py

@@ -1,7 +1,5 @@
 import os
 import torch
-import modelscope
-import huggingface_hub
 import numpy as np
 from torchvision.transforms import Compose, Resize, Normalize
 
@@ -26,17 +24,21 @@ ZH2EN = {
     "技法": "Tech",
 }
 
-MODEL_DIR = (
-    huggingface_hub.snapshot_download(
+if EN_US:
+    import huggingface_hub
+
+    MODEL_DIR = huggingface_hub.snapshot_download(
         "ccmusic-database/Guzheng_Tech99",
         cache_dir="./__pycache__",
     )
-    if EN_US
-    else modelscope.snapshot_download(
+
+else:
+    import modelscope
+
+    MODEL_DIR = modelscope.snapshot_download(
         "ccmusic-database/Guzheng_Tech99",
         cache_dir="./__pycache__",
     )
-)
 
 
 def _L(zh_txt: str):