View Source Evision.CUDA.ORB (Evision v0.1.28)

Link to this section Summary

Types

t()

Type that represents an CUDA.ORB struct.

Functions

Variant 1:

Computes the descriptors for a set of keypoints detected in an image.

Variant 1:

Computes the descriptors for a set of keypoints detected in an image.

Variant 1:

convert

create

create

defaultNorm

descriptorSize

descriptorType

Variant 1:

detect

Variant 1:

detect

Variant 1:

detectAndComputeAsync

Variant 1:

detectAndComputeAsync

Variant 1:

Detects keypoints in an image.

Variant 1:

Detects keypoints in an image.

empty

getBlurForDescriptor

getDefaultName

getEdgeThreshold

getFastThreshold

getFirstLevel

getMaxFeatures

getNLevels

getPatchSize

getScaleFactor

getScoreType

getWTA_K

Variant 1:

read

Link to this section Types

@type t() :: %Evision.CUDA.ORB{ref: reference()}

Type that represents an CUDA.ORB struct.

  • ref. reference()

    The underlying erlang resource variable.

Link to this section Functions

Link to this function

compute(self, images, keypoints)

View Source

Variant 1:

compute

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • images: [Evision.Mat].

    Image set.

Return
  • keypoints: [[Evision.KeyPoint]].

    Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).

  • descriptors: [Evision.Mat].

    Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

Has overloading in C++

Python prototype (for reference only):

compute(images, keypoints[, descriptors]) -> keypoints, descriptors

Variant 2:

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Return
  • keypoints: [Evision.KeyPoint].

    Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).

  • descriptors: Evision.Mat.t().

    Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

Python prototype (for reference only):

compute(image, keypoints[, descriptors]) -> keypoints, descriptors
Link to this function

compute(self, images, keypoints, opts)

View Source
@spec compute(
  Evision.ORB.t(),
  [Evision.Mat.maybe_mat_in()],
  [[Evision.KeyPoint.t()]],
  [{atom(), term()}, ...] | nil
) :: {[[Evision.KeyPoint.t()]], [Evision.Mat.t()]} | {:error, String.t()}
@spec compute(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  [Evision.KeyPoint.t()],
  [{atom(), term()}, ...] | nil
) :: {[Evision.KeyPoint.t()], Evision.Mat.t()} | {:error, String.t()}

Variant 1:

compute

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • images: [Evision.Mat].

    Image set.

Return
  • keypoints: [[Evision.KeyPoint]].

    Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).

  • descriptors: [Evision.Mat].

    Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

Has overloading in C++

Python prototype (for reference only):

compute(images, keypoints[, descriptors]) -> keypoints, descriptors

Variant 2:

Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Return
  • keypoints: [Evision.KeyPoint].

    Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation).

  • descriptors: Evision.Mat.t().

    Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint.

Python prototype (for reference only):

compute(image, keypoints[, descriptors]) -> keypoints, descriptors
Link to this function

computeAsync(self, image)

View Source
@spec computeAsync(Evision.ORB.t(), Evision.Mat.maybe_mat_in()) ::
  {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec computeAsync(Evision.ORB.t(), Evision.CUDA.GpuMat.t()) ::
  {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}

Variant 1:

Computes the descriptors for a set of keypoints detected in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.Mat.t().

    Input collection of keypoints.

  • descriptors: Evision.Mat.t().

    Computed descriptors. Row j is the descriptor for j-th keypoint.

Python prototype (for reference only):

computeAsync(image[, keypoints[, descriptors[, stream]]]) -> keypoints, descriptors

Variant 2:

Computes the descriptors for a set of keypoints detected in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.CUDA.GpuMat.t().

    Image.

Keyword Arguments
  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.CUDA.GpuMat.t().

    Input collection of keypoints.

  • descriptors: Evision.CUDA.GpuMat.t().

    Computed descriptors. Row j is the descriptor for j-th keypoint.

Python prototype (for reference only):

computeAsync(image[, keypoints[, descriptors[, stream]]]) -> keypoints, descriptors
Link to this function

computeAsync(self, image, opts)

View Source
@spec computeAsync(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) ::
  {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec computeAsync(
  Evision.ORB.t(),
  Evision.CUDA.GpuMat.t(),
  [{atom(), term()}, ...] | nil
) ::
  {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}

Variant 1:

Computes the descriptors for a set of keypoints detected in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.Mat.t().

    Input collection of keypoints.

  • descriptors: Evision.Mat.t().

    Computed descriptors. Row j is the descriptor for j-th keypoint.

Python prototype (for reference only):

computeAsync(image[, keypoints[, descriptors[, stream]]]) -> keypoints, descriptors

Variant 2:

Computes the descriptors for a set of keypoints detected in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.CUDA.GpuMat.t().

    Image.

Keyword Arguments
  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.CUDA.GpuMat.t().

    Input collection of keypoints.

  • descriptors: Evision.CUDA.GpuMat.t().

    Computed descriptors. Row j is the descriptor for j-th keypoint.

Python prototype (for reference only):

computeAsync(image[, keypoints[, descriptors[, stream]]]) -> keypoints, descriptors
Link to this function

convert(self, gpu_keypoints)

View Source
@spec convert(Evision.ORB.t(), Evision.Mat.maybe_mat_in()) ::
  [Evision.KeyPoint.t()] | {:error, String.t()}
@spec convert(Evision.ORB.t(), Evision.CUDA.GpuMat.t()) ::
  [Evision.KeyPoint.t()] | {:error, String.t()}

Variant 1:

convert

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • gpu_keypoints: Evision.Mat.t()
Return
  • keypoints: [Evision.KeyPoint]

Converts keypoints array from internal representation to standard vector.

Python prototype (for reference only):

convert(gpu_keypoints) -> keypoints

Variant 2:

convert

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • gpu_keypoints: Evision.CUDA.GpuMat.t()
Return
  • keypoints: [Evision.KeyPoint]

Converts keypoints array from internal representation to standard vector.

Python prototype (for reference only):

convert(gpu_keypoints) -> keypoints
@spec create() :: t() | {:error, String.t()}

create

Keyword Arguments
  • nfeatures: int.
  • scaleFactor: float.
  • nlevels: int.
  • edgeThreshold: int.
  • firstLevel: int.
  • wTA_K: int.
  • scoreType: int.
  • patchSize: int.
  • fastThreshold: int.
  • blurForDescriptor: bool.
Return
  • retval: Evision.CUDA.ORB.t()

Python prototype (for reference only):

create([, nfeatures[, scaleFactor[, nlevels[, edgeThreshold[, firstLevel[, WTA_K[, scoreType[, patchSize[, fastThreshold[, blurForDescriptor]]]]]]]]]]) -> retval
@spec create([{atom(), term()}, ...] | nil) :: t() | {:error, String.t()}

create

Keyword Arguments
  • nfeatures: int.
  • scaleFactor: float.
  • nlevels: int.
  • edgeThreshold: int.
  • firstLevel: int.
  • wTA_K: int.
  • scoreType: int.
  • patchSize: int.
  • fastThreshold: int.
  • blurForDescriptor: bool.
Return
  • retval: Evision.CUDA.ORB.t()

Python prototype (for reference only):

create([, nfeatures[, scaleFactor[, nlevels[, edgeThreshold[, firstLevel[, WTA_K[, scoreType[, patchSize[, fastThreshold[, blurForDescriptor]]]]]]]]]]) -> retval
@spec defaultNorm(Evision.ORB.t()) :: integer() | {:error, String.t()}

defaultNorm

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

defaultNorm() -> retval
@spec descriptorSize(Evision.ORB.t()) :: integer() | {:error, String.t()}

descriptorSize

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

descriptorSize() -> retval
@spec descriptorType(Evision.ORB.t()) :: integer() | {:error, String.t()}

descriptorType

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

descriptorType() -> retval
@spec detect(Evision.ORB.t(), [Evision.Mat.maybe_mat_in()]) ::
  [[Evision.KeyPoint.t()]] | {:error, String.t()}
@spec detect(Evision.ORB.t(), Evision.Mat.maybe_mat_in()) ::
  [Evision.KeyPoint.t()] | {:error, String.t()}

Variant 1:

detect

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • images: [Evision.Mat].

    Image set.

Keyword Arguments
  • masks: [Evision.Mat].

    Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].

Return
  • keypoints: [[Evision.KeyPoint]].

    The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .

Has overloading in C++

Python prototype (for reference only):

detect(images[, masks]) -> keypoints

Variant 2:

Detects keypoints in an image (first variant) or image set (second variant).

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • mask: Evision.Mat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

Return
  • keypoints: [Evision.KeyPoint].

    The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .

Python prototype (for reference only):

detect(image[, mask]) -> keypoints
Link to this function

detect(self, images, opts)

View Source
@spec detect(
  Evision.ORB.t(),
  [Evision.Mat.maybe_mat_in()],
  [{atom(), term()}, ...] | nil
) ::
  [[Evision.KeyPoint.t()]] | {:error, String.t()}
@spec detect(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) ::
  [Evision.KeyPoint.t()] | {:error, String.t()}

Variant 1:

detect

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • images: [Evision.Mat].

    Image set.

Keyword Arguments
  • masks: [Evision.Mat].

    Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i].

Return
  • keypoints: [[Evision.KeyPoint]].

    The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .

Has overloading in C++

Python prototype (for reference only):

detect(images[, masks]) -> keypoints

Variant 2:

Detects keypoints in an image (first variant) or image set (second variant).

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • mask: Evision.Mat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

Return
  • keypoints: [Evision.KeyPoint].

    The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] .

Python prototype (for reference only):

detect(image[, mask]) -> keypoints
Link to this function

detectAndCompute(self, image, mask)

View Source
@spec detectAndCompute(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in()
) ::
  {[Evision.KeyPoint.t()], Evision.Mat.t()} | {:error, String.t()}

detectAndCompute

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.Mat.t()
  • mask: Evision.Mat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
Return
  • keypoints: [Evision.KeyPoint]
  • descriptors: Evision.Mat.t().

Detects keypoints and computes the descriptors

Python prototype (for reference only):

detectAndCompute(image, mask[, descriptors[, useProvidedKeypoints]]) -> keypoints, descriptors
Link to this function

detectAndCompute(self, image, mask, opts)

View Source
@spec detectAndCompute(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) :: {[Evision.KeyPoint.t()], Evision.Mat.t()} | {:error, String.t()}

detectAndCompute

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.Mat.t()
  • mask: Evision.Mat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
Return
  • keypoints: [Evision.KeyPoint]
  • descriptors: Evision.Mat.t().

Detects keypoints and computes the descriptors

Python prototype (for reference only):

detectAndCompute(image, mask[, descriptors[, useProvidedKeypoints]]) -> keypoints, descriptors
Link to this function

detectAndComputeAsync(self, image, mask)

View Source
@spec detectAndComputeAsync(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in()
) ::
  {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec detectAndComputeAsync(
  Evision.ORB.t(),
  Evision.CUDA.GpuMat.t(),
  Evision.CUDA.GpuMat.t()
) ::
  {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}

Variant 1:

detectAndComputeAsync

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.Mat.t()
  • mask: Evision.Mat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
  • stream: Evision.CUDA.Stream.t().
Return
  • keypoints: Evision.Mat.t().
  • descriptors: Evision.Mat.t().

Detects keypoints and computes the descriptors.

Python prototype (for reference only):

detectAndComputeAsync(image, mask[, keypoints[, descriptors[, useProvidedKeypoints[, stream]]]]) -> keypoints, descriptors

Variant 2:

detectAndComputeAsync

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.CUDA.GpuMat.t()
  • mask: Evision.CUDA.GpuMat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
  • stream: Evision.CUDA.Stream.t().
Return
  • keypoints: Evision.CUDA.GpuMat.t().
  • descriptors: Evision.CUDA.GpuMat.t().

Detects keypoints and computes the descriptors.

Python prototype (for reference only):

detectAndComputeAsync(image, mask[, keypoints[, descriptors[, useProvidedKeypoints[, stream]]]]) -> keypoints, descriptors
Link to this function

detectAndComputeAsync(self, image, mask, opts)

View Source
@spec detectAndComputeAsync(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) :: {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec detectAndComputeAsync(
  Evision.ORB.t(),
  Evision.CUDA.GpuMat.t(),
  Evision.CUDA.GpuMat.t(),
  [{atom(), term()}, ...] | nil
) :: {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}

Variant 1:

detectAndComputeAsync

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.Mat.t()
  • mask: Evision.Mat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
  • stream: Evision.CUDA.Stream.t().
Return
  • keypoints: Evision.Mat.t().
  • descriptors: Evision.Mat.t().

Detects keypoints and computes the descriptors.

Python prototype (for reference only):

detectAndComputeAsync(image, mask[, keypoints[, descriptors[, useProvidedKeypoints[, stream]]]]) -> keypoints, descriptors

Variant 2:

detectAndComputeAsync

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • image: Evision.CUDA.GpuMat.t()
  • mask: Evision.CUDA.GpuMat.t()
Keyword Arguments
  • useProvidedKeypoints: bool.
  • stream: Evision.CUDA.Stream.t().
Return
  • keypoints: Evision.CUDA.GpuMat.t().
  • descriptors: Evision.CUDA.GpuMat.t().

Detects keypoints and computes the descriptors.

Python prototype (for reference only):

detectAndComputeAsync(image, mask[, keypoints[, descriptors[, useProvidedKeypoints[, stream]]]]) -> keypoints, descriptors
Link to this function

detectAsync(self, image)

View Source
@spec detectAsync(Evision.ORB.t(), Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}
@spec detectAsync(Evision.ORB.t(), Evision.CUDA.GpuMat.t()) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Detects keypoints in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • mask: Evision.Mat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.Mat.t().

    The detected keypoints.

Python prototype (for reference only):

detectAsync(image[, keypoints[, mask[, stream]]]) -> keypoints

Variant 2:

Detects keypoints in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.CUDA.GpuMat.t().

    Image.

Keyword Arguments
  • mask: Evision.CUDA.GpuMat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.CUDA.GpuMat.t().

    The detected keypoints.

Python prototype (for reference only):

detectAsync(image[, keypoints[, mask[, stream]]]) -> keypoints
Link to this function

detectAsync(self, image, opts)

View Source
@spec detectAsync(
  Evision.ORB.t(),
  Evision.Mat.maybe_mat_in(),
  [{atom(), term()}, ...] | nil
) ::
  Evision.Mat.t() | {:error, String.t()}
@spec detectAsync(
  Evision.ORB.t(),
  Evision.CUDA.GpuMat.t(),
  [{atom(), term()}, ...] | nil
) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Detects keypoints in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.Mat.t().

    Image.

Keyword Arguments
  • mask: Evision.Mat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.Mat.t().

    The detected keypoints.

Python prototype (for reference only):

detectAsync(image[, keypoints[, mask[, stream]]]) -> keypoints

Variant 2:

Detects keypoints in an image.

Positional Arguments
  • self: Evision.CUDA.ORB.t()

  • image: Evision.CUDA.GpuMat.t().

    Image.

Keyword Arguments
  • mask: Evision.CUDA.GpuMat.t().

    Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest.

  • stream: Evision.CUDA.Stream.t().

    CUDA stream.

Return
  • keypoints: Evision.CUDA.GpuMat.t().

    The detected keypoints.

Python prototype (for reference only):

detectAsync(image[, keypoints[, mask[, stream]]]) -> keypoints
@spec empty(Evision.ORB.t()) :: boolean() | {:error, String.t()}

empty

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: bool

Python prototype (for reference only):

empty() -> retval
Link to this function

getBlurForDescriptor(self)

View Source
@spec getBlurForDescriptor(Evision.ORB.t()) :: boolean() | {:error, String.t()}

getBlurForDescriptor

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: bool

Python prototype (for reference only):

getBlurForDescriptor() -> retval
@spec getDefaultName(Evision.ORB.t()) :: binary() | {:error, String.t()}

getDefaultName

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return

Python prototype (for reference only):

getDefaultName() -> retval
@spec getEdgeThreshold(Evision.ORB.t()) :: integer() | {:error, String.t()}

getEdgeThreshold

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getEdgeThreshold() -> retval
@spec getFastThreshold(Evision.ORB.t()) :: integer() | {:error, String.t()}

getFastThreshold

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getFastThreshold() -> retval
@spec getFirstLevel(Evision.ORB.t()) :: integer() | {:error, String.t()}

getFirstLevel

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getFirstLevel() -> retval
@spec getMaxFeatures(Evision.ORB.t()) :: integer() | {:error, String.t()}

getMaxFeatures

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getMaxFeatures() -> retval
@spec getNLevels(Evision.ORB.t()) :: integer() | {:error, String.t()}

getNLevels

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getNLevels() -> retval
@spec getPatchSize(Evision.ORB.t()) :: integer() | {:error, String.t()}

getPatchSize

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getPatchSize() -> retval
@spec getScaleFactor(Evision.ORB.t()) :: number() | {:error, String.t()}

getScaleFactor

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: double

Python prototype (for reference only):

getScaleFactor() -> retval
@spec getScoreType(Evision.ORB.t()) :: integer() | {:error, String.t()}

getScoreType

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getScoreType() -> retval
@spec getWTA_K(Evision.ORB.t()) :: integer() | {:error, String.t()}

getWTA_K

Positional Arguments
  • self: Evision.CUDA.ORB.t()
Return
  • retval: int

Python prototype (for reference only):

getWTA_K() -> retval
@spec read(Evision.ORB.t(), Evision.FileNode.t()) ::
  Evision.ORB.t() | {:error, String.t()}
@spec read(Evision.ORB.t(), binary()) :: Evision.ORB.t() | {:error, String.t()}

Variant 1:

read

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • arg1: Evision.FileNode.t()

Python prototype (for reference only):

read(arg1) -> None

Variant 2:

read

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • fileName: String

Python prototype (for reference only):

read(fileName) -> None
Link to this function

setBlurForDescriptor(self, blurForDescriptor)

View Source
@spec setBlurForDescriptor(Evision.ORB.t(), boolean()) ::
  Evision.ORB.t() | {:error, String.t()}

setBlurForDescriptor

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • blurForDescriptor: bool

Python prototype (for reference only):

setBlurForDescriptor(blurForDescriptor) -> None
Link to this function

setEdgeThreshold(self, edgeThreshold)

View Source
@spec setEdgeThreshold(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setEdgeThreshold

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • edgeThreshold: int

Python prototype (for reference only):

setEdgeThreshold(edgeThreshold) -> None
Link to this function

setFastThreshold(self, fastThreshold)

View Source
@spec setFastThreshold(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setFastThreshold

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • fastThreshold: int

Python prototype (for reference only):

setFastThreshold(fastThreshold) -> None
Link to this function

setFirstLevel(self, firstLevel)

View Source
@spec setFirstLevel(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setFirstLevel

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • firstLevel: int

Python prototype (for reference only):

setFirstLevel(firstLevel) -> None
Link to this function

setMaxFeatures(self, maxFeatures)

View Source
@spec setMaxFeatures(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setMaxFeatures

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • maxFeatures: int

Python prototype (for reference only):

setMaxFeatures(maxFeatures) -> None
Link to this function

setNLevels(self, nlevels)

View Source
@spec setNLevels(Evision.ORB.t(), integer()) :: Evision.ORB.t() | {:error, String.t()}

setNLevels

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • nlevels: int

Python prototype (for reference only):

setNLevels(nlevels) -> None
Link to this function

setPatchSize(self, patchSize)

View Source
@spec setPatchSize(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setPatchSize

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • patchSize: int

Python prototype (for reference only):

setPatchSize(patchSize) -> None
Link to this function

setScaleFactor(self, scaleFactor)

View Source
@spec setScaleFactor(Evision.ORB.t(), number()) ::
  Evision.ORB.t() | {:error, String.t()}

setScaleFactor

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • scaleFactor: double

Python prototype (for reference only):

setScaleFactor(scaleFactor) -> None
Link to this function

setScoreType(self, scoreType)

View Source
@spec setScoreType(Evision.ORB.t(), integer()) ::
  Evision.ORB.t() | {:error, String.t()}

setScoreType

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • scoreType: int

Python prototype (for reference only):

setScoreType(scoreType) -> None
@spec setWTA_K(Evision.ORB.t(), integer()) :: Evision.ORB.t() | {:error, String.t()}

setWTA_K

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • wta_k: int

Python prototype (for reference only):

setWTA_K(wta_k) -> None
@spec write(Evision.ORB.t(), binary()) :: Evision.ORB.t() | {:error, String.t()}

write

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • fileName: String

Python prototype (for reference only):

write(fileName) -> None
@spec write(Evision.ORB.t(), Evision.FileStorage.t(), binary()) ::
  Evision.ORB.t() | {:error, String.t()}

write

Positional Arguments
  • self: Evision.CUDA.ORB.t()
  • fs: Evision.FileStorage.t()
  • name: String

Python prototype (for reference only):

write(fs, name) -> None