@spec apply2(Evision.Detail.Detail.LightGlueFeaturesMatcher.t(), [
  Evision.Detail.ImageFeatures.t()
]) ::
  [Evision.Detail.MatchesInfo.t()] | {:error, String.t()}

Performs images matching.

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()

• features: [Evision.Detail.ImageFeatures].

  Features of the source images

Keyword Arguments

• mask: Evision.Mat.

  Mask indicating which image pairs must be matched

Return

• pairwise_matches: [Evision.Detail.MatchesInfo].

  Found pairwise matches

The function is parallelized with the TBB library. @sa detail::MatchesInfo

Python prototype (for reference only):

apply2(features[, mask]) -> pairwise_matches

@spec apply2(
  Evision.Detail.Detail.LightGlueFeaturesMatcher.t(),
  [Evision.Detail.ImageFeatures.t()],
  [{:mask, term()}] | nil
) :: [Evision.Detail.MatchesInfo.t()] | {:error, String.t()}

Performs images matching.

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()

• features: [Evision.Detail.ImageFeatures].

  Features of the source images

Keyword Arguments

• mask: Evision.Mat.

  Mask indicating which image pairs must be matched

Return

• pairwise_matches: [Evision.Detail.MatchesInfo].

  Found pairwise matches

The function is parallelized with the TBB library. @sa detail::MatchesInfo

Python prototype (for reference only):

apply2(features[, mask]) -> pairwise_matches

@spec apply(
  Evision.Detail.Detail.LightGlueFeaturesMatcher.t(),
  Evision.Detail.ImageFeatures.t(),
  Evision.Detail.ImageFeatures.t()
) :: Evision.Detail.MatchesInfo.t() | {:error, String.t()}

apply

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()

• features1: Evision.Detail.ImageFeatures.

  First image features

• features2: Evision.Detail.ImageFeatures.

  Second image features

Return

• matches_info: Evision.Detail.MatchesInfo.t().

  Found matches

Has overloading in C++

Python prototype (for reference only):

apply(features1, features2) -> matches_info

@spec collectGarbage(Keyword.t()) :: any() | {:error, String.t()}

@spec collectGarbage(Evision.Detail.Detail.LightGlueFeaturesMatcher.t()) ::
  Evision.Detail.Detail.LightGlueFeaturesMatcher.t() | {:error, String.t()}

Frees unused memory allocated before if there is any.

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()

Python prototype (for reference only):

collectGarbage() -> None

@spec isThreadSafe(Keyword.t()) :: any() | {:error, String.t()}

@spec isThreadSafe(Evision.Detail.Detail.LightGlueFeaturesMatcher.t()) ::
  boolean() | {:error, String.t()}

isThreadSafe

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()

Return

• retval: bool

@return True, if it's possible to use the same matcher instance in parallel, false otherwise

Python prototype (for reference only):

isThreadSafe() -> retval

@spec lightGlueFeaturesMatcher(Keyword.t()) :: any() | {:error, String.t()}

@spec lightGlueFeaturesMatcher(Evision.LightGlueMatcher.t()) ::
  t() | {:error, String.t()}

Constructs a LightGlue features matcher.

Positional Arguments

• lgMatcher: Evision.LightGlueMatcher.

  LightGlueMatcher instance for DNN-based matching

Keyword Arguments

• num_matches_thresh1: integer().

  Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step

• num_matches_thresh2: integer().

  Minimum number of matches required for the 2D projective transform re-estimation on inliers

• matches_confidence_thresh: double.

  Matching confidence threshold to take the match into account.

Return

• self: LightGlueFeaturesMatcher

Python prototype (for reference only):

LightGlueFeaturesMatcher(lgMatcher[, num_matches_thresh1[, num_matches_thresh2[, matches_confidence_thresh]]]) -> <detail_LightGlueFeaturesMatcher object>

@spec lightGlueFeaturesMatcher(
  Evision.LightGlueMatcher.t(),
  [
    matches_confidence_thresh: term(),
    num_matches_thresh1: term(),
    num_matches_thresh2: term()
  ]
  | nil
) :: t() | {:error, String.t()}

Constructs a LightGlue features matcher.

Positional Arguments

• lgMatcher: Evision.LightGlueMatcher.

  LightGlueMatcher instance for DNN-based matching

Keyword Arguments

• num_matches_thresh1: integer().

  Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step

• num_matches_thresh2: integer().

  Minimum number of matches required for the 2D projective transform re-estimation on inliers

• matches_confidence_thresh: double.

  Matching confidence threshold to take the match into account.

Return

• self: LightGlueFeaturesMatcher

Python prototype (for reference only):

LightGlueFeaturesMatcher(lgMatcher[, num_matches_thresh1[, num_matches_thresh2[, matches_confidence_thresh]]]) -> <detail_LightGlueFeaturesMatcher object>

@spec setScoreThreshold(Evision.Detail.Detail.LightGlueFeaturesMatcher.t(), number()) ::
  Evision.Detail.Detail.LightGlueFeaturesMatcher.t() | {:error, String.t()}

Sets the LightGlue confidence threshold for filtering matches.

Positional Arguments

• self: Evision.Detail.LightGlueFeaturesMatcher.t()
• thresh: float

Python prototype (for reference only):

setScoreThreshold(thresh) -> None