Multiple coords + Multiple boxes + Multiple labels solution - Need suggest

i implemented in my code

```predictor = SamPredictor(self.sam)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
predictor.set_image(image)

input_boxes = np.array(boxes) if len(boxes) > 0 else None
input_boxes = torch.tensor(input_boxes, device=predictor.device)
transformed_boxes = predictor.transform.apply_boxes_torch(input_boxes, image.shape[:2])

masks, scores, logits = predictor.predict_torch(
point_coords=None,
point_labels=None,
boxes=transformed_boxes,
multimask_output=False,
)
```

how can i use multiple coord and labels ? What format it is ?
Thanks for help.

Start with the SamPredictor usage shown in the issue, especially predict_torch and its point_coords and point_labels parameters, then compare the repository’s example notebooks. Document the accepted format for multiple coordinates and labels alongside the existing boxes example, and verify that the example explains how the inputs correspond to the returned masks.

Written by the indexing model from the issue text.