@spec compute(t(), [Evision.Mat.maybe_mat_in()], [[Evision.KeyPoint.t()]]) ::
  {[[Evision.KeyPoint.t()]], [Evision.Mat.t()]} | {:error, String.t()}

@spec compute(t(), Evision.Mat.maybe_mat_in(), [Evision.KeyPoint.t()]) ::
  {[Evision.KeyPoint.t()], Evision.Mat.t()} | {:error, String.t()}

Variant 1:

compute

Positional Arguments

• self: Evision.GFTTDetector.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.GFTTDetector.t()

• image: Evision.Mat.

  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

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

@spec compute(
  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.GFTTDetector.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.GFTTDetector.t()

• image: Evision.Mat.

  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

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

create

Keyword Arguments

• maxCorners: integer().
• qualityLevel: double.
• minDistance: double.
• blockSize: integer().
• useHarrisDetector: bool.
• k: double.

Return

• retval: Evision.GFTTDetector.t()

Python prototype (for reference only):

create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval

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

@spec create(
  [
    blockSize: term(),
    k: term(),
    maxCorners: term(),
    minDistance: term(),
    qualityLevel: term(),
    useHarrisDetector: term()
  ]
  | nil
) :: t() | {:error, String.t()}

create

Keyword Arguments

• maxCorners: integer().
• qualityLevel: double.
• minDistance: double.
• blockSize: integer().
• useHarrisDetector: bool.
• k: double.

Return

• retval: Evision.GFTTDetector.t()

Python prototype (for reference only):

create([, maxCorners[, qualityLevel[, minDistance[, blockSize[, useHarrisDetector[, k]]]]]]) -> retval

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

create

Positional Arguments

• maxCorners: integer()
• qualityLevel: double
• minDistance: double
• blockSize: integer()
• gradiantSize: integer()

Keyword Arguments

• useHarrisDetector: bool.
• k: double.

Return

• retval: Evision.GFTTDetector.t()

Python prototype (for reference only):

create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval

@spec create(
  integer(),
  number(),
  number(),
  integer(),
  integer(),
  [k: term(), useHarrisDetector: term()] | nil
) :: t() | {:error, String.t()}

create

Positional Arguments

• maxCorners: integer()
• qualityLevel: double
• minDistance: double
• blockSize: integer()
• gradiantSize: integer()

Keyword Arguments

• useHarrisDetector: bool.
• k: double.

Return

• retval: Evision.GFTTDetector.t()

Python prototype (for reference only):

create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval

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

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

defaultNorm

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

defaultNorm() -> retval

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

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

descriptorSize

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

descriptorSize() -> retval

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

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

descriptorType

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

descriptorType() -> retval

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

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

Variant 1:

detect

Positional Arguments

• self: Evision.GFTTDetector.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.GFTTDetector.t()

• image: Evision.Mat.

  Image.

Keyword Arguments

• mask: Evision.Mat.

  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

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

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

Variant 1:

detect

Positional Arguments

• self: Evision.GFTTDetector.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.GFTTDetector.t()

• image: Evision.Mat.

  Image.

Keyword Arguments

• mask: Evision.Mat.

  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

@spec detectAndCompute(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.GFTTDetector.t()
• image: Evision.Mat
• mask: Evision.Mat

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

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

detectAndCompute

Positional Arguments

• self: Evision.GFTTDetector.t()
• image: Evision.Mat
• mask: Evision.Mat

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

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

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

empty

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: bool

Python prototype (for reference only):

empty() -> retval

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

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

getBlockSize

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

getBlockSize() -> retval

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

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

getDefaultName

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: String

Python prototype (for reference only):

getDefaultName() -> retval

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

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

getGradientSize

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

getGradientSize() -> retval

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

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

getHarrisDetector

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: bool

Python prototype (for reference only):

getHarrisDetector() -> retval

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

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

getK

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: double

Python prototype (for reference only):

getK() -> retval

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

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

getMaxFeatures

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: integer()

Python prototype (for reference only):

getMaxFeatures() -> retval

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

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

getMinDistance

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: double

Python prototype (for reference only):

getMinDistance() -> retval

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

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

getQualityLevel

Positional Arguments

• self: Evision.GFTTDetector.t()

Return

• retval: double

Python prototype (for reference only):

getQualityLevel() -> retval

@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}

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

Variant 1:

read

Positional Arguments

• self: Evision.GFTTDetector.t()
• arg1: Evision.FileNode

Python prototype (for reference only):

read(arg1) -> None

Variant 2:

read

Positional Arguments

• self: Evision.GFTTDetector.t()
• fileName: String

Python prototype (for reference only):

read(fileName) -> None

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

setBlockSize

Positional Arguments

• self: Evision.GFTTDetector.t()
• blockSize: integer()

Python prototype (for reference only):

setBlockSize(blockSize) -> None

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

setGradientSize

Positional Arguments

• self: Evision.GFTTDetector.t()
• gradientSize_: integer()

Python prototype (for reference only):

setGradientSize(gradientSize_) -> None

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

setHarrisDetector

Positional Arguments

• self: Evision.GFTTDetector.t()
• val: bool

Python prototype (for reference only):

setHarrisDetector(val) -> None

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

setK

Positional Arguments

• self: Evision.GFTTDetector.t()
• k: double

Python prototype (for reference only):

setK(k) -> None

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

setMaxFeatures

Positional Arguments

• self: Evision.GFTTDetector.t()
• maxFeatures: integer()

Python prototype (for reference only):

setMaxFeatures(maxFeatures) -> None

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

setMinDistance

Positional Arguments

• self: Evision.GFTTDetector.t()
• minDistance: double

Python prototype (for reference only):

setMinDistance(minDistance) -> None

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

setQualityLevel

Positional Arguments

• self: Evision.GFTTDetector.t()
• qlevel: double

Python prototype (for reference only):

setQualityLevel(qlevel) -> None

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

write

Positional Arguments

• self: Evision.GFTTDetector.t()
• fileName: String

Python prototype (for reference only):

write(fileName) -> None

@spec write(t(), Evision.FileStorage.t(), binary()) :: t() | {:error, String.t()}

write

Positional Arguments

• self: Evision.GFTTDetector.t()
• fs: Evision.FileStorage
• name: String

Python prototype (for reference only):

write(fs, name) -> None