View Source Evision.SparseOpticalFlow (Evision v0.2.9)
Summary
Functions
Calculates a sparse optical flow.
Calculates a sparse optical flow.
Clears the algorithm state
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
getDefaultName
Reads algorithm parameters from a file storage
save
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.SparseOpticalFlow{ref: reference()}
Type that represents an SparseOpticalFlow
struct.
ref.
reference()
The underlying erlang resource variable.
Functions
@spec calc( t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in() ) :: {Evision.Mat.t(), Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
Calculates a sparse optical flow.
Positional Arguments
self:
Evision.SparseOpticalFlow.t()
prevImg:
Evision.Mat
.First input image.
nextImg:
Evision.Mat
.Second input image of the same size and the same type as prevImg.
prevPts:
Evision.Mat
.Vector of 2D points for which the flow needs to be found.
Return
nextPts:
Evision.Mat.t()
.Output vector of 2D points containing the calculated new positions of input features in the second image.
status:
Evision.Mat.t()
.Output status vector. Each element of the vector is set to 1 if the flow for the corresponding features has been found. Otherwise, it is set to 0.
err:
Evision.Mat.t()
.Optional output vector that contains error response for each point (inverse confidence).
Python prototype (for reference only):
calc(prevImg, nextImg, prevPts, nextPts[, status[, err]]) -> nextPts, status, err
@spec calc( t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil ) :: {Evision.Mat.t(), Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
Calculates a sparse optical flow.
Positional Arguments
self:
Evision.SparseOpticalFlow.t()
prevImg:
Evision.Mat
.First input image.
nextImg:
Evision.Mat
.Second input image of the same size and the same type as prevImg.
prevPts:
Evision.Mat
.Vector of 2D points for which the flow needs to be found.
Return
nextPts:
Evision.Mat.t()
.Output vector of 2D points containing the calculated new positions of input features in the second image.
status:
Evision.Mat.t()
.Output status vector. Each element of the vector is set to 1 if the flow for the corresponding features has been found. Otherwise, it is set to 0.
err:
Evision.Mat.t()
.Optional output vector that contains error response for each point (inverse confidence).
Python prototype (for reference only):
calc(prevImg, nextImg, prevPts, nextPts[, status[, err]]) -> nextPts, status, err
@spec clear(Keyword.t()) :: any() | {:error, String.t()}
@spec clear(t()) :: t() | {:error, String.t()}
Clears the algorithm state
Positional Arguments
- self:
Evision.SparseOpticalFlow.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.SparseOpticalFlow.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.SparseOpticalFlow.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 read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.SparseOpticalFlow.t()
- func:
Evision.FileNode
Python prototype (for reference only):
read(fn) -> None
save
Positional Arguments
- self:
Evision.SparseOpticalFlow.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.SparseOpticalFlow.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.SparseOpticalFlow.t()
- fs:
Evision.FileStorage
- name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None