View Source Evision.XImgProc.SuperpixelSLIC (Evision v0.2.9)
Summary
Functions
Clears the algorithm state
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
Enforce label connectivity.
Enforce label connectivity.
getDefaultName
Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
Returns the segmentation labeling of the image.
Returns the segmentation labeling of the image.
Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelSLIC object.
Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.
Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.
Reads algorithm parameters from a file storage
save
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.XImgProc.SuperpixelSLIC{ref: reference()}
Type that represents an XImgProc.SuperpixelSLIC
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.XImgProc.SuperpixelSLIC.t()
Python prototype (for reference only):
clear() -> None
@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.XImgProc.SuperpixelSLIC.t()
Return
- retval:
bool
Python prototype (for reference only):
empty() -> retval
@spec enforceLabelConnectivity(Keyword.t()) :: any() | {:error, String.t()}
@spec enforceLabelConnectivity(t()) :: t() | {:error, String.t()}
Enforce label connectivity.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
min_element_size:
integer()
.The minimum element size in percents that should be absorbed into a bigger superpixel. Given resulted average superpixel size valid value should be in 0-100 range, 25 means that less then a quarter sized superpixel should be absorbed, this is default.
The function merge component that is too small, assigning the previously found adjacent label to this component. Calling this function may change the final number of superpixels.
Python prototype (for reference only):
enforceLabelConnectivity([, min_element_size]) -> None
@spec enforceLabelConnectivity(t(), [{:min_element_size, term()}] | nil) :: t() | {:error, String.t()}
Enforce label connectivity.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
min_element_size:
integer()
.The minimum element size in percents that should be absorbed into a bigger superpixel. Given resulted average superpixel size valid value should be in 0-100 range, 25 means that less then a quarter sized superpixel should be absorbed, this is default.
The function merge component that is too small, assigning the previously found adjacent label to this component. Calling this function may change the final number of superpixels.
Python prototype (for reference only):
enforceLabelConnectivity([, min_element_size]) -> None
@spec getDefaultName(Keyword.t()) :: any() | {:error, String.t()}
@spec getDefaultName(t()) :: binary() | {:error, String.t()}
getDefaultName
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.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 getLabelContourMask(Keyword.t()) :: any() | {:error, String.t()}
@spec getLabelContourMask(t()) :: Evision.Mat.t() | {:error, String.t()}
Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
thick_line:
bool
.If false, the border is only one pixel wide, otherwise all pixels at the border are masked.
Return
image:
Evision.Mat.t()
.Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border, and 0 otherwise.
The function return the boundaries of the superpixel segmentation.
Python prototype (for reference only):
getLabelContourMask([, image[, thick_line]]) -> image
@spec getLabelContourMask(t(), [{:thick_line, term()}] | nil) :: Evision.Mat.t() | {:error, String.t()}
Returns the mask of the superpixel segmentation stored in SuperpixelSLIC object.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
thick_line:
bool
.If false, the border is only one pixel wide, otherwise all pixels at the border are masked.
Return
image:
Evision.Mat.t()
.Return: CV_8U1 image mask where -1 indicates that the pixel is a superpixel border, and 0 otherwise.
The function return the boundaries of the superpixel segmentation.
Python prototype (for reference only):
getLabelContourMask([, image[, thick_line]]) -> image
@spec getLabels(Keyword.t()) :: any() | {:error, String.t()}
@spec getLabels(t()) :: Evision.Mat.t() | {:error, String.t()}
Returns the segmentation labeling of the image.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Return
labels_out:
Evision.Mat.t()
.Return: A CV_32SC1 integer array containing the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].
Each label represents a superpixel, and each pixel is assigned to one superpixel label.
The function returns an image with the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].
Python prototype (for reference only):
getLabels([, labels_out]) -> labels_out
@spec getLabels(t(), [{atom(), term()}, ...] | nil) :: Evision.Mat.t() | {:error, String.t()}
Returns the segmentation labeling of the image.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Return
labels_out:
Evision.Mat.t()
.Return: A CV_32SC1 integer array containing the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].
Each label represents a superpixel, and each pixel is assigned to one superpixel label.
The function returns an image with the labels of the superpixel segmentation. The labels are in the range [0, getNumberOfSuperpixels()].
Python prototype (for reference only):
getLabels([, labels_out]) -> labels_out
@spec getNumberOfSuperpixels(Keyword.t()) :: any() | {:error, String.t()}
@spec getNumberOfSuperpixels(t()) :: integer() | {:error, String.t()}
Calculates the actual amount of superpixels on a given segmentation computed and stored in SuperpixelSLIC object.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Return
- retval:
integer()
Python prototype (for reference only):
getNumberOfSuperpixels() -> retval
@spec iterate(Keyword.t()) :: any() | {:error, String.t()}
@spec iterate(t()) :: t() | {:error, String.t()}
Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
num_iterations:
integer()
.Number of iterations. Higher number improves the result.
This function can be called again without the need of initializing the algorithm with createSuperpixelSLIC(). This save the computational cost of allocating memory for all the structures of the algorithm.
The function computes the superpixels segmentation of an image with the parameters initialized with the function createSuperpixelSLIC(). The algorithms starts from a grid of superpixels and then refines the boundaries by proposing updates of edges boundaries.
Python prototype (for reference only):
iterate([, num_iterations]) -> None
Calculates the superpixel segmentation on a given image with the initialized parameters in the SuperpixelSLIC object.
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
Keyword Arguments
num_iterations:
integer()
.Number of iterations. Higher number improves the result.
This function can be called again without the need of initializing the algorithm with createSuperpixelSLIC(). This save the computational cost of allocating memory for all the structures of the algorithm.
The function computes the superpixels segmentation of an image with the parameters initialized with the function createSuperpixelSLIC(). The algorithms starts from a grid of superpixels and then refines the boundaries by proposing updates of edges boundaries.
Python prototype (for reference only):
iterate([, num_iterations]) -> None
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.t()
- func:
Evision.FileNode
Python prototype (for reference only):
read(fn) -> None
save
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.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
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}
Stores algorithm parameters in a file storage
Positional Arguments
- self:
Evision.XImgProc.SuperpixelSLIC.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.XImgProc.SuperpixelSLIC.t()
- fs:
Evision.FileStorage
- name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None