class_docstr: LightGlue-based matcher in kornia API.
  
  This is based on the original code from paper "LightGlue: Local Feature Matching at Light Speed".
  See :cite:`LightGlue2023` for more details.
  
  Args:
      feature_name: type of feature for matching, can be `disk` or `superpoint`.
      params: LightGlue params.
class_docstr_tok: ["LightGlue-based","matcher","in","kornia","API",".","This","is","based","on","the","original","code","from","paper","``","LightGlue",":","Local","Feature","Matching","at","Light","Speed","''",".","See",":","cite",":","`","LightGlue2023","`","for","more","details",".","Args",":","feature_name",":","type","of","feature","for","matching",",","can","be","`","disk","`","or","`","superpoint","`",".","params",":","LightGlue","params","."]
code: def __init__(self, feature_name: str = "disk", params: Dict = {}) -> None:  # type: ignore
      feature_name_: str = feature_name.lower()
      super().__init__(feature_name_)
      self.feature_name = feature_name_
      self.params = params
      self.matcher = LightGlue(self.feature_name, **params)
  
imports: import warnings
  from typing import ClassVar, Dict, List, Optional, Tuple
  import torch
  from kornia.color import rgb_to_grayscale
  from kornia.constants import pi
  from kornia.core import Device, Module, Tensor, concatenate, deg2rad
  from kornia.core.check import KORNIA_CHECK_LAF
  from kornia.geometry.subpix import ConvQuadInterp3d
  from kornia.geometry.transform import ScalePyramid
  from .affine_shape import LAFAffNetShapeEstimator
  from .hardnet import HardNet
  from .keynet import KeyNetDetector
  from .laf import extract_patches_from_pyramid, get_laf_center, get_laf_orientation, get_laf_scale, scale_laf
  from .lightglue import LightGlue
  from .matching import GeometryAwareDescriptorMatcher, _no_match
  from .orientation import LAFOrienter, OriNet, PassLAF
  from .responses import BlobDoG, BlobDoGSingle, BlobHessian, CornerGFTT
  from .scale_space_detector import Detector_config, MultiResolutionDetector, ScaleSpaceDetector, get_default_detector_config
  from .siftdesc import SIFTDescriptor
label_desc: Use image node_id 1 to create a new LightGlueMatcher object from inherited base classes: GeometryAwareDescriptorMatcher with example: obj = LightGlueMatcher(feature_name, params)