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

Performs images matching.

Positional Arguments

• self: Evision.Detail.BestOf2NearestMatcher.t()

• features: [Evision.Detail.ImageFeatures].

  Features of the source images

Keyword Arguments

• mask: Evision.Mat.t().

  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(t(), [Evision.Detail.ImageFeatures.t()], [{atom(), term()}, ...] | nil) ::
  [Evision.Detail.MatchesInfo.t()] | {:error, String.t()}

Performs images matching.

Positional Arguments

• self: Evision.Detail.BestOf2NearestMatcher.t()

• features: [Evision.Detail.ImageFeatures].

  Features of the source images

Keyword Arguments

• mask: Evision.Mat.t().

  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(t(), Evision.Detail.ImageFeatures.t(), Evision.Detail.ImageFeatures.t()) ::
  Evision.Detail.MatchesInfo.t() | {:error, String.t()}

apply

Positional Arguments

• self: Evision.Detail.BestOf2NearestMatcher.t()

• features1: Evision.Detail.ImageFeatures.t().

  First image features

• features2: Evision.Detail.ImageFeatures.t().

  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 bestOf2NearestMatcher() :: t() | {:error, String.t()}

Constructs a "best of 2 nearest" matcher.

Keyword Arguments

• try_use_gpu: bool.

  Should try to use GPU or not

• match_conf: float.

  Match distances ration threshold

• num_matches_thresh1: int.

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

• num_matches_thresh2: int.

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

• matches_confindece_thresh: double.

  Matching confidence threshold to take the match into account. The threshold was determined experimentally and set to 3 by default.

Return

• self: Evision.Detail.BestOf2NearestMatcher.t()

Python prototype (for reference only):

BestOf2NearestMatcher([, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]]) -> <detail_BestOf2NearestMatcher object>

@spec bestOf2NearestMatcher([{atom(), term()}, ...] | nil) ::
  t() | {:error, String.t()}

Constructs a "best of 2 nearest" matcher.

Keyword Arguments

• try_use_gpu: bool.

  Should try to use GPU or not

• match_conf: float.

  Match distances ration threshold

• num_matches_thresh1: int.

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

• num_matches_thresh2: int.

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

• matches_confindece_thresh: double.

  Matching confidence threshold to take the match into account. The threshold was determined experimentally and set to 3 by default.

Return

• self: Evision.Detail.BestOf2NearestMatcher.t()

Python prototype (for reference only):

BestOf2NearestMatcher([, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]]) -> <detail_BestOf2NearestMatcher object>

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

collectGarbage

Positional Arguments

• self: Evision.Detail.BestOf2NearestMatcher.t()

Python prototype (for reference only):

collectGarbage() -> None

@spec create() :: t() | {:error, String.t()}

create

Keyword Arguments

• try_use_gpu: bool.
• match_conf: float.
• num_matches_thresh1: int.
• num_matches_thresh2: int.
• matches_confindece_thresh: double.

Return

• retval: Evision.Detail.BestOf2NearestMatcher.t()

Python prototype (for reference only):

create([, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]]) -> retval

@spec create([{atom(), term()}, ...] | nil) :: t() | {:error, String.t()}

create

Keyword Arguments

• try_use_gpu: bool.
• match_conf: float.
• num_matches_thresh1: int.
• num_matches_thresh2: int.
• matches_confindece_thresh: double.

Return

• retval: Evision.Detail.BestOf2NearestMatcher.t()

Python prototype (for reference only):

create([, try_use_gpu[, match_conf[, num_matches_thresh1[, num_matches_thresh2[, matches_confindece_thresh]]]]]) -> retval

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

isThreadSafe

Positional Arguments

• self: Evision.Detail.BestOf2NearestMatcher.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