a

app.py

@@ -14,7 +14,6 @@ from sam2.sam2_image_predictor import SAM2ImagePredictor
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 SAM_MODEL = "facebook/sam2.1-hiera-large"
-PREDICTOR = SAM2ImagePredictor.from_pretrained(SAM_MODEL, device=DEVICE)
 
 MODELS = {
     "RealVisXL V5.0 Lightning": "SG161222/RealVisXL_V5.0_Lightning",
@@ -66,7 +65,8 @@ def load_default_pipeline():
 @spaces.GPU()
 def predict_masks(image, points):
     """Predict a single mask from the image based on selected points."""
-    
+    PREDICTOR = SAM2ImagePredictor.from_pretrained(SAM_MODEL, device=DEVICE)
+
     image_np = np.array(image)
     points_list = [[point["x"], point["y"]] for point in points]
     input_labels = [1] * len(points_list)