Add application file

app.py

@@ -13,6 +13,8 @@ device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
 
 class Detection:
+
+    @spaces.GPU
     def __init__(self):
         # Set the model path and confidence threshold
         yolov8_model_path = "./model/best.pt"  # Update to your model path
@@ -25,7 +27,6 @@ class Detection:
             device=device  # Change to 'cuda:0' if you are using a GPU
         )
 
-    @spaces.GPU
     def detect_from_image(self, image):
         # Perform sliced prediction with SAHI
         results = get_sliced_prediction(
@@ -39,7 +40,6 @@ class Detection:
             postprocess_match_metric='IOU',
             postprocess_match_threshold=0.1,
             postprocess_class_agnostic=True,
-            device=device
         )
 
         # Retrieve COCO annotations