class_docstr: Encapsulate the results obtained by the :py:class:`kornia.contrib.FaceDetector`.
  
  Args:
      data: the encoded results coming from the feature detector with shape :math:`(14,)`.
class_docstr_tok: ["Encapsulate","the","results","obtained","by","the",":","py",":","class",":","`","kornia.contrib.FaceDetector","`",".","Args",":","data",":","the","encoded","results","coming","from","the","feature","detector","with","shape",":","math",":","`","(","14",",",")","`","."]
docstr: The bounding box top-left x-coordinate.
docstr_tok: ["The","bounding","box","top-left","x-coordinate","."]
code: def xmin(self) -> torch.Tensor:
      """The bounding box top-left x-coordinate."""
      return self._data[..., 0]
  
imports: import math
  from enum import Enum
  from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.geometry.bbox import nms
  from kornia.utils.helpers import map_location_to_cpu
label_desc: Use image node_id 3 for calling the FaceDetectorResult obj's underlying member method code with example usage: obj.xmin() and returns: self