Update app.py

app.py

@@ -87,7 +87,7 @@ def foward_pass(image_input: np.ndarray, points: List[List[int]]) -> np.ndarray:
     print('SAM-Segmentation-started------->')
     global cache_data
     image_input = Image.fromarray(image_input)
-    inputs = processor(image_input, input_boxes=np.array(points), return_tensors="pt").to(device)
+    inputs = processor(image_input, input_boxes=points, return_tensors="pt").to(device)
     if not cache_data or not torch.equal(inputs['pixel_values'],cache_data[0]):
         embedding = model.get_image_embeddings(inputs["pixel_values"])
         pixels = inputs["pixel_values"]