View Source Evision.CUDA.HoughLinesDetector (Evision v0.2.9)
Summary
Functions
Clears the algorithm state
Variant 1:
Finds lines in a binary image using the classical Hough transform.
Variant 1:
Finds lines in a binary image using the classical Hough transform.
Variant 1:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Variant 1:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
getDefaultName
getDoSort
getMaxLines
getRho
getTheta
getThreshold
Reads algorithm parameters from a file storage
save
setDoSort
setMaxLines
setRho
setTheta
setThreshold
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.CUDA.HoughLinesDetector{ref: reference()}
Type that represents an CUDA.HoughLinesDetector
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.HoughLinesDetector.t()
Python prototype (for reference only):
clear() -> None
@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 lines in a binary image using the classical Hough transform.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.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 two-element vector \f$(\rho, \theta)\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of the image). \f$\theta\f$ is the line rotation angle in radians ( \f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ).
@sa HoughLines
Python prototype (for reference only):
detect(src[, lines[, stream]]) -> lines
Variant 2:
Finds lines in a binary image using the classical Hough transform.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.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 two-element vector \f$(\rho, \theta)\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of the image). \f$\theta\f$ is the line rotation angle in radians ( \f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ).
@sa HoughLines
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 lines in a binary image using the classical Hough transform.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.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 two-element vector \f$(\rho, \theta)\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of the image). \f$\theta\f$ is the line rotation angle in radians ( \f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ).
@sa HoughLines
Python prototype (for reference only):
detect(src[, lines[, stream]]) -> lines
Variant 2:
Finds lines in a binary image using the classical Hough transform.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.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 two-element vector \f$(\rho, \theta)\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of the image). \f$\theta\f$ is the line rotation angle in radians ( \f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ).
@sa HoughLines
Python prototype (for reference only):
detect(src[, lines[, stream]]) -> lines
@spec downloadResults(t(), Evision.Mat.maybe_mat_in()) :: {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec downloadResults(t(), Evision.CUDA.GpuMat.t()) :: {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}
Variant 1:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.t()
d_lines:
Evision.Mat
.Result of cuda::HoughLinesDetector::detect .
Keyword Arguments
stream:
Evision.CUDA.Stream.t()
.Stream for the asynchronous version.
Return
h_lines:
Evision.Mat.t()
.Output host array.
h_votes:
Evision.Mat.t()
.Optional output array for line's votes.
Python prototype (for reference only):
downloadResults(d_lines[, h_lines[, h_votes[, stream]]]) -> h_lines, h_votes
Variant 2:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.t()
d_lines:
Evision.CUDA.GpuMat.t()
.Result of cuda::HoughLinesDetector::detect .
Keyword Arguments
stream:
Evision.CUDA.Stream.t()
.Stream for the asynchronous version.
Return
h_lines:
Evision.CUDA.GpuMat.t()
.Output host array.
h_votes:
Evision.CUDA.GpuMat.t()
.Optional output array for line's votes.
Python prototype (for reference only):
downloadResults(d_lines[, h_lines[, h_votes[, stream]]]) -> h_lines, h_votes
@spec downloadResults(t(), Evision.Mat.maybe_mat_in(), [{:stream, term()}] | nil) :: {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
@spec downloadResults(t(), Evision.CUDA.GpuMat.t(), [{:stream, term()}] | nil) :: {Evision.CUDA.GpuMat.t(), Evision.CUDA.GpuMat.t()} | {:error, String.t()}
Variant 1:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.t()
d_lines:
Evision.Mat
.Result of cuda::HoughLinesDetector::detect .
Keyword Arguments
stream:
Evision.CUDA.Stream.t()
.Stream for the asynchronous version.
Return
h_lines:
Evision.Mat.t()
.Output host array.
h_votes:
Evision.Mat.t()
.Optional output array for line's votes.
Python prototype (for reference only):
downloadResults(d_lines[, h_lines[, h_votes[, stream]]]) -> h_lines, h_votes
Variant 2:
Downloads results from cuda::HoughLinesDetector::detect to host memory.
Positional Arguments
self:
Evision.CUDA.HoughLinesDetector.t()
d_lines:
Evision.CUDA.GpuMat.t()
.Result of cuda::HoughLinesDetector::detect .
Keyword Arguments
stream:
Evision.CUDA.Stream.t()
.Stream for the asynchronous version.
Return
h_lines:
Evision.CUDA.GpuMat.t()
.Output host array.
h_votes:
Evision.CUDA.GpuMat.t()
.Optional output array for line's votes.
Python prototype (for reference only):
downloadResults(d_lines[, h_lines[, h_votes[, stream]]]) -> h_lines, h_votes
@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.HoughLinesDetector.t()
Return
- retval:
bool
Python prototype (for reference only):
empty() -> retval
@spec getDefaultName(Keyword.t()) :: any() | {:error, String.t()}
@spec getDefaultName(t()) :: binary() | {:error, String.t()}
getDefaultName
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
Return
- retval:
String
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
@spec getDoSort(Keyword.t()) :: any() | {:error, String.t()}
@spec getDoSort(t()) :: boolean() | {:error, String.t()}
getDoSort
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
Return
- retval:
bool
Python prototype (for reference only):
getDoSort() -> retval
@spec getMaxLines(Keyword.t()) :: any() | {:error, String.t()}
@spec getMaxLines(t()) :: integer() | {:error, String.t()}
getMaxLines
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
Return
- retval:
integer()
Python prototype (for reference only):
getMaxLines() -> retval
@spec getRho(Keyword.t()) :: any() | {:error, String.t()}
@spec getRho(t()) :: number() | {:error, String.t()}
getRho
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.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.HoughLinesDetector.t()
Return
- retval:
float
Python prototype (for reference only):
getTheta() -> retval
@spec getThreshold(Keyword.t()) :: any() | {:error, String.t()}
@spec getThreshold(t()) :: integer() | {:error, String.t()}
getThreshold
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
Return
- retval:
integer()
Python prototype (for reference only):
getThreshold() -> retval
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- func:
Evision.FileNode
Python prototype (for reference only):
read(fn) -> None
save
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.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
setDoSort
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- doSort:
bool
Python prototype (for reference only):
setDoSort(doSort) -> None
setMaxLines
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- maxLines:
integer()
Python prototype (for reference only):
setMaxLines(maxLines) -> None
setRho
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- rho:
float
Python prototype (for reference only):
setRho(rho) -> None
setTheta
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- theta:
float
Python prototype (for reference only):
setTheta(theta) -> None
setThreshold
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- threshold:
integer()
Python prototype (for reference only):
setThreshold(threshold) -> None
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}
Stores algorithm parameters in a file storage
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- fs:
Evision.FileStorage
Python prototype (for reference only):
write(fs) -> None
@spec write(t(), Evision.FileStorage.t(), binary()) :: t() | {:error, String.t()}
write
Positional Arguments
- self:
Evision.CUDA.HoughLinesDetector.t()
- fs:
Evision.FileStorage
- name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None