Use monkey patch to disable weights_only for ultralytics model loading

Amp-Thread-ID: https://ampcode.com/threads/T-22e83726-d77c-475f-b185-6d55f37c5979
Co-authored-by: Amp <amp@ampcode.com>

model.py

@@ -5,25 +5,33 @@ import yaml
 from huggingface_hub import hf_hub_download
 import os
 import torch
-from ultralytics.nn.tasks import DetectionModel
 
 class TrafficSignDetector:
     def __init__(self, config_path):
         with open(config_path, 'r') as f:
             config = yaml.safe_load(f)
 
-        # Download model from HF Hub if not local
-        model_path = config['model']['path']
-        if model_path.startswith('VietCat/GTSRB-Model/'):
-            # Extract repo and file path for GTSRB-Model
-            repo_id = 'VietCat/GTSRB-Model'
-            file_path = model_path.replace('VietCat/GTSRB-Model/', '')
-            local_model_path = hf_hub_download(repo_id=repo_id, filename=file_path)
-            # Allow safe loading of ultralytics model
-            with torch.serialization.safe_globals([torch.nn.Module, DetectionModel]):
+        # Monkey patch torch.load to disable weights_only for ultralytics
+        original_torch_load = torch.load
+        def patched_torch_load(*args, **kwargs):
+            kwargs['weights_only'] = False
+            return original_torch_load(*args, **kwargs)
+        torch.load = patched_torch_load
+
+        try:
+            # Download model from HF Hub if not local
+            model_path = config['model']['path']
+            if model_path.startswith('VietCat/GTSRB-Model/'):
+                # Extract repo and file path for GTSRB-Model
+                repo_id = 'VietCat/GTSRB-Model'
+                file_path = model_path.replace('VietCat/GTSRB-Model/', '')
+                local_model_path = hf_hub_download(repo_id=repo_id, filename=file_path)
                 self.model = YOLO(local_model_path)
-        else:
-            self.model = YOLO(model_path)
+            else:
+                self.model = YOLO(model_path)
+        finally:
+            # Restore original torch.load
+            torch.load = original_torch_load
 
         self.conf_threshold = config['model']['confidence_threshold']
         self.box_color = config['inference']['box_color']