View Source Evision.RGBD.DepthCleaner (Evision v0.1.34)
Summary
Functions
apply
Clears the algorithm state
create
create
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
getDefaultName
getDepth
getMethod
getWindowSize
initialize
Reads algorithm parameters from a file storage
save
setDepth
setMethod
setWindowSize
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.RGBD.DepthCleaner{ref: reference()}
Type that represents an RGBD.DepthCleaner
struct.
ref.
reference()
The underlying erlang resource variable.
Functions
@spec apply(t(), Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}
apply
Positional Arguments
self:
Evision.RGBD.DepthCleaner.t()
points:
Evision.Mat.t()
.a rows x cols x 3 matrix of CV_32F/CV64F or a rows x cols x 1 CV_U16S
Return
depth:
Evision.Mat.t()
.a rows x cols matrix of the cleaned up depth
Given a set of 3d points in a depth image, compute the normals at each point.
Python prototype (for reference only):
apply(points[, depth]) -> depth
@spec apply(t(), Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil) :: Evision.Mat.t() | {:error, String.t()}
apply
Positional Arguments
self:
Evision.RGBD.DepthCleaner.t()
points:
Evision.Mat.t()
.a rows x cols x 3 matrix of CV_32F/CV64F or a rows x cols x 1 CV_U16S
Return
depth:
Evision.Mat.t()
.a rows x cols matrix of the cleaned up depth
Given a set of 3d points in a depth image, compute the normals at each point.
Python prototype (for reference only):
apply(points[, depth]) -> depth
Clears the algorithm state
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Python prototype (for reference only):
clear() -> None
create
Positional Arguments
depth:
int
.the depth of the normals (only CV_32F or CV_64F)
Keyword Arguments
window_size:
int
.the window size to compute the normals: can only be 1,3,5 or 7
method:
int
.one of the methods to use: RGBD_NORMALS_METHOD_SRI, RGBD_NORMALS_METHOD_FALS
Return
- retval:
DepthCleaner
Constructor
Python prototype (for reference only):
create(depth[, window_size[, method]]) -> retval
create
Positional Arguments
depth:
int
.the depth of the normals (only CV_32F or CV_64F)
Keyword Arguments
window_size:
int
.the window size to compute the normals: can only be 1,3,5 or 7
method:
int
.one of the methods to use: RGBD_NORMALS_METHOD_SRI, RGBD_NORMALS_METHOD_FALS
Return
- retval:
DepthCleaner
Constructor
Python prototype (for reference only):
create(depth[, window_size[, method]]) -> retval
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Return
- retval:
bool
Python prototype (for reference only):
empty() -> retval
getDefaultName
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.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
getDepth
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Return
- retval:
int
Python prototype (for reference only):
getDepth() -> retval
getMethod
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Return
- retval:
int
Python prototype (for reference only):
getMethod() -> retval
getWindowSize
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Return
- retval:
int
Python prototype (for reference only):
getWindowSize() -> retval
initialize
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
Initializes some data that is cached for later computation If that function is not called, it will be called the first time normals are computed
Python prototype (for reference only):
initialize() -> None
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- fn_:
Evision.FileNode.t()
Python prototype (for reference only):
read(fn_) -> None
save
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.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
setDepth
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- val:
int
Python prototype (for reference only):
setDepth(val) -> None
setMethod
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- val:
int
Python prototype (for reference only):
setMethod(val) -> None
setWindowSize
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- val:
int
Python prototype (for reference only):
setWindowSize(val) -> None
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}
Stores algorithm parameters in a file storage
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- fs:
Evision.FileStorage.t()
Python prototype (for reference only):
write(fs) -> None
@spec write(t(), Evision.FileStorage.t(), binary()) :: t() | {:error, String.t()}
write
Positional Arguments
- self:
Evision.RGBD.DepthCleaner.t()
- fs:
Evision.FileStorage.t()
- name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None