try lazy initialization for SAM2

app.py

@@ -101,13 +101,7 @@ if not os.path.exists("./checkpoints/sam2.1_hiera_large.pt"):
 SAM2_CHECKPOINT = "./checkpoints/sam2.1_hiera_large.pt"
 SAM2_CONFIG = "configs/sam2.1/sam2.1_hiera_l.yaml"
 
-sam2_model = build_sam2(
-    config_file=SAM2_CONFIG,
-    ckpt_path=SAM2_CHECKPOINT,
-    device='cpu'
-)
-sam2_predictor = SAM2ImagePredictor(sam2_model)
-# sam2_predictor = SAM2ImagePredictor.from_pretrained("facebook/sam2-hiera-large", device=torch.device("cpu"))
+sam2_predictor = None
 
 ############## 3D-Fixer model
 model_dir = 'HorizonRobotics/3D-Fixer'
@@ -231,6 +225,14 @@ def run_segmentation(
     rgb_image = image_prompts["image"].convert("RGB")
 
     global work_space
+    global sam2_predictor
+
+    if sam2_predictor is None:
+        sam2_model = build_sam2(
+            config_file=SAM2_CONFIG,
+            ckpt_path=SAM2_CHECKPOINT,
+        )
+        sam2_predictor = SAM2ImagePredictor(sam2_model)
 
     # pre-process the layers and get the xyxy boxes of each layer
     if len(image_prompts["points"]) == 0: