View Source Evision.Detail.BlocksCompensator (Evision v0.1.21)

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Types

t()

Type that represents an Evision.Detail.BlocksCompensator struct.

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

Type that represents an Evision.Detail.BlocksCompensator struct.

  • ref. reference()

    The underlying erlang resource variable.

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apply(self, index, corner, image, mask)

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@spec apply(
  t(),
  integer(),
  {number(), number()},
  Evision.Mat.maybe_mat_in(),
  Evision.Mat.maybe_mat_in()
) :: Evision.Mat.t() | {:error, String.t()}

apply

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • index: int
  • corner: Point
  • mask: Evision.Mat
Return

Python prototype (for reference only):

apply(index, corner, image, mask) -> image
@spec getBlockSize(t()) :: {number(), number()} | {:error, String.t()}

getBlockSize

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
Return
  • retval: Size

Python prototype (for reference only):

getBlockSize() -> retval
@spec getMatGains(t()) :: [Evision.Mat.t()] | {:error, String.t()}

getMatGains

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
Return
  • umv: [Evision.Mat].

Python prototype (for reference only):

getMatGains([, umv]) -> umv
@spec getMatGains(t(), [{atom(), term()}, ...] | nil) ::
  [Evision.Mat.t()] | {:error, String.t()}

getMatGains

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
Return
  • umv: [Evision.Mat].

Python prototype (for reference only):

getMatGains([, umv]) -> umv
@spec getNrFeeds(t()) :: integer() | {:error, String.t()}

getNrFeeds

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

Python prototype (for reference only):

getNrFeeds() -> retval
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getNrGainsFilteringIterations(self)

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

getNrGainsFilteringIterations

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

Python prototype (for reference only):

getNrGainsFilteringIterations() -> retval
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getSimilarityThreshold(self)

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

getSimilarityThreshold

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

Python prototype (for reference only):

getSimilarityThreshold() -> retval
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setBlockSize(self, size)

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

setBlockSize

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • size: Size

Python prototype (for reference only):

setBlockSize(size) -> None
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setBlockSize(self, width, height)

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

setBlockSize

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • width: int
  • height: int

Python prototype (for reference only):

setBlockSize(width, height) -> None
@spec setMatGains(t(), [Evision.Mat.maybe_mat_in()]) :: :ok | {:error, String.t()}

setMatGains

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • umv: [Evision.Mat]

Python prototype (for reference only):

setMatGains(umv) -> None
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setNrFeeds(self, nr_feeds)

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

setNrFeeds

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • nr_feeds: int

Python prototype (for reference only):

setNrFeeds(nr_feeds) -> None
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setNrGainsFilteringIterations(self, nr_iterations)

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

setNrGainsFilteringIterations

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • nr_iterations: int

Python prototype (for reference only):

setNrGainsFilteringIterations(nr_iterations) -> None
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setSimilarityThreshold(self, similarity_threshold)

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

setSimilarityThreshold

Positional Arguments
  • self: Evision.Detail.BlocksCompensator.t()
  • similarity_threshold: double

Python prototype (for reference only):

setSimilarityThreshold(similarity_threshold) -> None