View Source Evision.CUDA.HoughSegmentDetector (Evision v0.2.9)

Summary

Types

t()

Type that represents an CUDA.HoughSegmentDetector struct.

Functions

Clears the algorithm state

Variant 1:

Finds line segments in a binary image using the probabilistic Hough transform.

Variant 1:

Finds line segments in a binary image using the probabilistic Hough transform.

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

getMinLineLength

Reads algorithm parameters from a file storage

Stores algorithm parameters in a file storage

Types

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

Type that represents an CUDA.HoughSegmentDetector struct.

  • ref. reference()

    The underlying erlang resource variable.

Functions

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

Clears the algorithm state

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

Python prototype (for reference only):

clear() -> None
@spec detect(Keyword.t()) :: any() | {:error, String.t()}
@spec detect(t(), Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}
@spec detect(t(), Evision.CUDA.GpuMat.t()) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Finds line segments in a binary image using the probabilistic Hough transform.

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

  • src: Evision.Mat.

    8-bit, single-channel binary source image.

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

    Stream for the asynchronous version.

Return
  • lines: Evision.Mat.t().

    Output vector of lines. Each line is represented by a 4-element vector \f$(x_1, y_1, x_2, y_2)\f$ , where \f$(x_1,y_1)\f$ and \f$(x_2, y_2)\f$ are the ending points of each detected line segment.

@sa HoughLinesP

Python prototype (for reference only):

detect(src[, lines[, stream]]) -> lines

Variant 2:

Finds line segments in a binary image using the probabilistic Hough transform.

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

  • src: Evision.CUDA.GpuMat.t().

    8-bit, single-channel binary source image.

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

    Stream for the asynchronous version.

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

    Output vector of lines. Each line is represented by a 4-element vector \f$(x_1, y_1, x_2, y_2)\f$ , where \f$(x_1,y_1)\f$ and \f$(x_2, y_2)\f$ are the ending points of each detected line segment.

@sa HoughLinesP

Python prototype (for reference only):

detect(src[, lines[, stream]]) -> lines
@spec detect(t(), Evision.Mat.maybe_mat_in(), [{:stream, term()}] | nil) ::
  Evision.Mat.t() | {:error, String.t()}
@spec detect(t(), Evision.CUDA.GpuMat.t(), [{:stream, term()}] | nil) ::
  Evision.CUDA.GpuMat.t() | {:error, String.t()}

Variant 1:

Finds line segments in a binary image using the probabilistic Hough transform.

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

  • src: Evision.Mat.

    8-bit, single-channel binary source image.

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

    Stream for the asynchronous version.

Return
  • lines: Evision.Mat.t().

    Output vector of lines. Each line is represented by a 4-element vector \f$(x_1, y_1, x_2, y_2)\f$ , where \f$(x_1,y_1)\f$ and \f$(x_2, y_2)\f$ are the ending points of each detected line segment.

@sa HoughLinesP

Python prototype (for reference only):

detect(src[, lines[, stream]]) -> lines

Variant 2:

Finds line segments in a binary image using the probabilistic Hough transform.

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

  • src: Evision.CUDA.GpuMat.t().

    8-bit, single-channel binary source image.

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

    Stream for the asynchronous version.

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

    Output vector of lines. Each line is represented by a 4-element vector \f$(x_1, y_1, x_2, y_2)\f$ , where \f$(x_1,y_1)\f$ and \f$(x_2, y_2)\f$ are the ending points of each detected line segment.

@sa HoughLinesP

Python prototype (for reference only):

detect(src[, lines[, stream]]) -> lines
@spec empty(Keyword.t()) :: any() | {:error, String.t()}
@spec empty(t()) :: boolean() | {:error, String.t()}

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

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

Python prototype (for reference only):

empty() -> retval
Link to this function

getDefaultName(named_args)

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

getDefaultName

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

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

Python prototype (for reference only):

getDefaultName() -> retval
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getMaxLineGap(named_args)

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

getMaxLineGap

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: integer()

Python prototype (for reference only):

getMaxLineGap() -> retval
@spec getMaxLines(Keyword.t()) :: any() | {:error, String.t()}
@spec getMaxLines(t()) :: integer() | {:error, String.t()}

getMaxLines

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: integer()

Python prototype (for reference only):

getMaxLines() -> retval
Link to this function

getMinLineLength(named_args)

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

getMinLineLength

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: integer()

Python prototype (for reference only):

getMinLineLength() -> retval
@spec getRho(Keyword.t()) :: any() | {:error, String.t()}
@spec getRho(t()) :: number() | {:error, String.t()}

getRho

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: float

Python prototype (for reference only):

getRho() -> retval
@spec getTheta(Keyword.t()) :: any() | {:error, String.t()}
@spec getTheta(t()) :: number() | {:error, String.t()}

getTheta

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: float

Python prototype (for reference only):

getTheta() -> retval
Link to this function

getThreshold(named_args)

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

getThreshold

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
Return
  • retval: integer()

Python prototype (for reference only):

getThreshold() -> retval
@spec read(Keyword.t()) :: any() | {:error, String.t()}
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}

Reads algorithm parameters from a file storage

Positional Arguments

Python prototype (for reference only):

read(fn) -> None
@spec save(Keyword.t()) :: any() | {:error, String.t()}
@spec save(t(), binary()) :: t() | {:error, String.t()}

save

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • filename: String

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

Python prototype (for reference only):

save(filename) -> None
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setMaxLineGap(named_args)

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@spec setMaxLineGap(Keyword.t()) :: any() | {:error, String.t()}
Link to this function

setMaxLineGap(self, maxLineGap)

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

setMaxLineGap

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • maxLineGap: integer()

Python prototype (for reference only):

setMaxLineGap(maxLineGap) -> None
@spec setMaxLines(Keyword.t()) :: any() | {:error, String.t()}
Link to this function

setMaxLines(self, maxLines)

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

setMaxLines

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • maxLines: integer()

Python prototype (for reference only):

setMaxLines(maxLines) -> None
Link to this function

setMinLineLength(named_args)

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@spec setMinLineLength(Keyword.t()) :: any() | {:error, String.t()}
Link to this function

setMinLineLength(self, minLineLength)

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

setMinLineLength

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • minLineLength: integer()

Python prototype (for reference only):

setMinLineLength(minLineLength) -> None
@spec setRho(Keyword.t()) :: any() | {:error, String.t()}
@spec setRho(t(), number()) :: t() | {:error, String.t()}

setRho

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • rho: float

Python prototype (for reference only):

setRho(rho) -> None
@spec setTheta(Keyword.t()) :: any() | {:error, String.t()}
@spec setTheta(t(), number()) :: t() | {:error, String.t()}

setTheta

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • theta: float

Python prototype (for reference only):

setTheta(theta) -> None
Link to this function

setThreshold(named_args)

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@spec setThreshold(Keyword.t()) :: any() | {:error, String.t()}
Link to this function

setThreshold(self, threshold)

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

setThreshold

Positional Arguments
  • self: Evision.CUDA.HoughSegmentDetector.t()
  • threshold: integer()

Python prototype (for reference only):

setThreshold(threshold) -> None
@spec write(Keyword.t()) :: any() | {:error, String.t()}
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}

Stores algorithm parameters in a file storage

Positional Arguments

Python prototype (for reference only):

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

write

Positional Arguments

Has overloading in C++

Python prototype (for reference only):

write(fs, name) -> None