Update app.py

app.py

@@ -15,10 +15,9 @@ warnings.filterwarnings("ignore", category=UserWarning)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 print(f"Using device: {device}")
 
-# Load the LangSAM model and move it to the selected device
-model = LangSAM()
-model.to(device)
-model.eval()  # Set model to evaluation mode
+# Load the LangSAM model
+model = LangSAM()  # Use the default model or specify custom checkpoint if necessary
+# Note: Removed model.to(device) since LangSAM does not support it
 
 def extract_masks(image_pil, prompts):
     """
@@ -35,7 +34,7 @@ def extract_masks(image_pil, prompts):
     masks_dict = {}
     with torch.no_grad():  # Disable gradient computation for inference
         for prompt in prompts_list:
-            # Ensure the model uses the correct device
+            # Ensure the model uses the correct device internally
             masks, boxes, phrases, logits = model.predict(image_pil, prompt)
             if masks is not None and len(masks) > 0:
                 # Move masks to CPU and convert to numpy