class_docstr: Encapsulate the prompts inputs for a Model.
  
  Args:
      points: A tuple with the keypoints (coordinates x, y) and their respective labels. Shape :math:`(K, N, 2)` for
              the keypoints, and :math:`(K, N)`
      boxes: Batched box inputs, with shape :math:`(K, 4)`. Expected to be into xyxy format.
      masks: Batched mask prompts to the model with shape :math:`(K, 1, H, W)`
class_docstr_tok: ["Encapsulate","the","prompts","inputs","for","a","Model",".","Args",":","points",":","A","tuple","with","the","keypoints","(","coordinates","x",",","y",")","and","their","respective","labels",".","Shape",":","math",":","`","(","K",",","N",",","2",")","`","for","the","keypoints",",","and",":","math",":","`","(","K",",","N",")","`","boxes",":","Batched","box","inputs",",","with","shape",":","math",":","`","(","K",",","4",")","`",".","Expected","to","be","into","xyxy","format",".","masks",":","Batched","mask","prompts","to","the","model","with","shape",":","math",":","`","(","K",",","1",",","H",",","W",")","`"]
docstr: The keypoints from the `points`
docstr_tok: ["The","keypoints","from","the","`","points","`"]
code: def keypoints(self) -> Optional[Tensor]:
      """The keypoints from the `points`"""
      return self.points[0] if isinstance(self.points, tuple) else None
  
file_path: kornia/kornia/contrib/models/structures.py
imports: from __future__ import annotations
  from dataclasses import dataclass
  from typing import Optional
  from kornia.core import Tensor
  from kornia.core.check import KORNIA_CHECK
  from kornia.geometry.transform import resize
label_desc: Use image node_id 2 for calling the Prompts obj's underlying member method code with example usage: obj.keypoints() and returns: unknown