2 hf

README.md

@@ -9,9 +9,4 @@ app_file: app.py
 pinned: false
 license: mit
 short_description: Music Genre Classifier
----
-
-## Maintenance
-```bash
-GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:spaces/ccmusic-database/music-genre
-```
+---

model.py

@@ -1,7 +1,7 @@
 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
 
 
@@ -39,11 +39,7 @@ class EvalNet:
         return backbone_list[0]
 
     def _model_info(self, m_ver):
-        backbone_list = MsDataset.load(
-            "monetjoe/cv_backbones",
-            split="v1",
-            trust_remote_code=True,
-        )
+        backbone_list = load_dataset("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

@@ -2,5 +2,4 @@ torch
 pillow
 librosa
 matplotlib
-torchvision
-modelscope==1.15
+torchvision

utils.py

@@ -1,12 +1,9 @@
 import os
 import torch
 import requests
-from modelscope import snapshot_download
+from huggingface_hub import snapshot_download
 
-MODEL_DIR = snapshot_download(
-    "ccmusic-database/music_genre",
-    cache_dir="./__pycache__",
-)
+MODEL_DIR = snapshot_download("ccmusic-database/music_genre", cache_dir="./__pycache__")
 
 
 def toCUDA(x):
@@ -31,6 +28,7 @@ def find_mp3_files(folder_path=f"{MODEL_DIR}/examples"):
 def get_modelist(model_dir=MODEL_DIR, assign_model=""):
     try:
         entries = os.listdir(model_dir)
+
     except OSError as e:
         print(f"Cannot access {model_dir}: {e}")
         return
@@ -61,5 +59,6 @@ def download(url: str):
                 f.write(chunk)
 
         print(f"The file has been downloaded to {os.getcwd()}/{filename}")
+
     else:
         print(f"Failed to download, status code: {response.status_code}")