View Source Evision.GFTTDetector (Evision v0.1.21)

Link to this section Summary

Types

t()

Type that represents an Evision.GFTTDetector struct.

Link to this section Types

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

Type that represents an Evision.GFTTDetector struct.

  • ref. reference()

    The underlying erlang resource variable.

Link to this section Functions

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compute(self, images, keypoints)

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@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.

    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
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compute(self, images, keypoints, opts)

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@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.

    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: int.
  • qualityLevel: double.
  • minDistance: double.
  • blockSize: int.
  • useHarrisDetector: bool.
  • k: double.
Return

Python prototype (for reference only):

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

create

Keyword Arguments
  • maxCorners: int.
  • qualityLevel: double.
  • minDistance: double.
  • blockSize: int.
  • useHarrisDetector: bool.
  • k: double.
Return

Python prototype (for reference only):

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

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

create

Positional Arguments
  • maxCorners: int
  • qualityLevel: double
  • minDistance: double
  • blockSize: int
  • gradiantSize: int
Keyword Arguments
  • useHarrisDetector: bool.
  • k: double.
Return

Python prototype (for reference only):

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

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

create

Positional Arguments
  • maxCorners: int
  • qualityLevel: double
  • minDistance: double
  • blockSize: int
  • gradiantSize: int
Keyword Arguments
  • useHarrisDetector: bool.
  • k: double.
Return

Python prototype (for reference only):

create(maxCorners, qualityLevel, minDistance, blockSize, gradiantSize[, useHarrisDetector[, k]]) -> retval
@spec defaultNorm(t()) :: integer() | {:error, String.t()}

defaultNorm

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

Python prototype (for reference only):

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

descriptorSize

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

Python prototype (for reference only):

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

descriptorType

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

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
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detect(self, images, opts)

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@spec detect(t(), [Evision.Mat.maybe_mat_in()], [{atom(), term()}, ...] | nil) ::
  [[Evision.KeyPoint.t()]] | {:error, String.t()}
@spec detect(t(), Evision.Mat.maybe_mat_in(), [{atom(), 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
Link to this function

detectAndCompute(self, image, mask)

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@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
Keyword Arguments
  • useProvidedKeypoints: bool.
Return

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)

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@spec detectAndCompute(
  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
Keyword Arguments
  • useProvidedKeypoints: bool.
Return

Detects keypoints and computes the descriptors

Python prototype (for reference only):

detectAndCompute(image, mask[, descriptors[, useProvidedKeypoints]]) -> keypoints, descriptors
@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(t()) :: integer() | {:error, String.t()}

getBlockSize

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

Python prototype (for reference only):

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

getDefaultName

Positional Arguments
  • self: Evision.GFTTDetector.t()
Return

Python prototype (for reference only):

getDefaultName() -> retval
@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(t()) :: number() | {:error, String.t()}

getK

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

Python prototype (for reference only):

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

getMaxFeatures

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

Python prototype (for reference only):

getMaxFeatures() -> retval
@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(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()) :: :ok | {:error, String.t()}
@spec read(t(), binary()) :: :ok | {:error, String.t()}

Variant 1:

read

Positional Arguments

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
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setBlockSize(self, blockSize)

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

setBlockSize

Positional Arguments
  • self: Evision.GFTTDetector.t()
  • blockSize: int

Python prototype (for reference only):

setBlockSize(blockSize) -> None
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setHarrisDetector(self, val)

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

setHarrisDetector

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

Python prototype (for reference only):

setHarrisDetector(val) -> None
@spec setK(t(), number()) :: :ok | {:error, String.t()}

setK

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

Python prototype (for reference only):

setK(k) -> None
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setMaxFeatures(self, maxFeatures)

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

setMaxFeatures

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

Python prototype (for reference only):

setMaxFeatures(maxFeatures) -> None
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setMinDistance(self, minDistance)

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

setMinDistance

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

Python prototype (for reference only):

setMinDistance(minDistance) -> None
Link to this function

setQualityLevel(self, qlevel)

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

setQualityLevel

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

Python prototype (for reference only):

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

Variant 1:

write

Positional Arguments
Keyword Arguments

Python prototype (for reference only):

write(fs[, name]) -> None

Variant 2:

write

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

Python prototype (for reference only):

write(fileName) -> None
@spec write(t(), Evision.FileStorage.t(), [{atom(), term()}, ...] | nil) ::
  :ok | {:error, String.t()}

write

Positional Arguments
Keyword Arguments

Python prototype (for reference only):

write(fs[, name]) -> None