View Source Evision.BgSegm.BackgroundSubtractorCNT (Evision v0.2.16)
Summary
Functions
apply
Variant 1:
Computes a foreground mask with known foreground mask input.
Computes a foreground mask with known foreground mask input.
Clears the algorithm state
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
getBackgroundImage
getBackgroundImage
getDefaultName
Returns if we're parallelizing the algorithm.
Returns maximum allowed credit for a pixel in history.
Returns number of frames with same pixel color to consider stable.
Returns if we're giving a pixel credit for being stable for a long time.
Reads algorithm parameters from a file storage
save
Sets if we're parallelizing the algorithm.
Sets the maximum allowed credit for a pixel in history.
Sets the number of frames with same pixel color to consider stable.
Sets if we're giving a pixel credit for being stable for a long time.
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.BgSegm.BackgroundSubtractorCNT{ref: reference()}
Type that represents an BgSegm.BackgroundSubtractorCNT 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.BgSegm.BackgroundSubtractorCNT.t() - image:
Evision.Mat
Keyword Arguments
- learningRate:
double.
Return
- fgmask:
Evision.Mat.t().
Python prototype (for reference only):
apply(image[, fgmask[, learningRate]]) -> fgmask
@spec apply(t(), Evision.Mat.maybe_mat_in(), [{:learningRate, term()}] | nil) :: Evision.Mat.t() | {:error, String.t()}
@spec apply(t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}
Variant 1:
Computes a foreground mask with known foreground mask input.
Positional Arguments
self:
Evision.BgSegm.BackgroundSubtractorCNT.t()image:
Evision.Mat.Next video frame.
knownForegroundMask:
Evision.Mat.The mask for inputting already known foreground.
Keyword Arguments
learningRate:
double.The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
Return
fgmask:
Evision.Mat.t().The output foreground mask as an 8-bit binary image.
Note: This method has a default virtual implementation that throws a "not impemented" error. Foreground masking may not be supported by all background subtractors.
Python prototype (for reference only):
apply(image, knownForegroundMask[, fgmask[, learningRate]]) -> fgmaskVariant 2:
apply
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - image:
Evision.Mat
Keyword Arguments
- learningRate:
double.
Return
- fgmask:
Evision.Mat.t().
Python prototype (for reference only):
apply(image[, fgmask[, learningRate]]) -> fgmask
@spec apply( t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), [{:learningRate, term()}] | nil ) :: Evision.Mat.t() | {:error, String.t()}
Computes a foreground mask with known foreground mask input.
Positional Arguments
self:
Evision.BgSegm.BackgroundSubtractorCNT.t()image:
Evision.Mat.Next video frame.
knownForegroundMask:
Evision.Mat.The mask for inputting already known foreground.
Keyword Arguments
learningRate:
double.The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
Return
fgmask:
Evision.Mat.t().The output foreground mask as an 8-bit binary image.
Note: This method has a default virtual implementation that throws a "not impemented" error. Foreground masking may not be supported by all background subtractors.
Python prototype (for reference only):
apply(image, knownForegroundMask[, fgmask[, learningRate]]) -> fgmask
@spec clear(Keyword.t()) :: any() | {:error, String.t()}
@spec clear(t()) :: t() | {:error, String.t()}
Clears the algorithm state
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.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.BgSegm.BackgroundSubtractorCNT.t()
Return
- retval:
bool
Python prototype (for reference only):
empty() -> retval
@spec getBackgroundImage(Keyword.t()) :: any() | {:error, String.t()}
@spec getBackgroundImage(t()) :: Evision.Mat.t() | {:error, String.t()}
getBackgroundImage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- backgroundImage:
Evision.Mat.t().
Python prototype (for reference only):
getBackgroundImage([, backgroundImage]) -> backgroundImage
@spec getBackgroundImage(t(), [{atom(), term()}, ...] | nil) :: Evision.Mat.t() | {:error, String.t()}
getBackgroundImage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- backgroundImage:
Evision.Mat.t().
Python prototype (for reference only):
getBackgroundImage([, backgroundImage]) -> backgroundImage
@spec getDefaultName(Keyword.t()) :: any() | {:error, String.t()}
@spec getDefaultName(t()) :: binary() | {:error, String.t()}
getDefaultName
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.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 getIsParallel(Keyword.t()) :: any() | {:error, String.t()}
@spec getIsParallel(t()) :: boolean() | {:error, String.t()}
Returns if we're parallelizing the algorithm.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- retval:
bool
Python prototype (for reference only):
getIsParallel() -> retval
@spec getMaxPixelStability(Keyword.t()) :: any() | {:error, String.t()}
@spec getMaxPixelStability(t()) :: integer() | {:error, String.t()}
Returns maximum allowed credit for a pixel in history.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- retval:
integer()
Python prototype (for reference only):
getMaxPixelStability() -> retval
@spec getMinPixelStability(Keyword.t()) :: any() | {:error, String.t()}
@spec getMinPixelStability(t()) :: integer() | {:error, String.t()}
Returns number of frames with same pixel color to consider stable.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- retval:
integer()
Python prototype (for reference only):
getMinPixelStability() -> retval
@spec getUseHistory(Keyword.t()) :: any() | {:error, String.t()}
@spec getUseHistory(t()) :: boolean() | {:error, String.t()}
Returns if we're giving a pixel credit for being stable for a long time.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Return
- retval:
bool
Python prototype (for reference only):
getUseHistory() -> retval
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - func:
Evision.FileNode
Python prototype (for reference only):
read(fn) -> None
save
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.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
Sets if we're parallelizing the algorithm.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - value:
bool
Python prototype (for reference only):
setIsParallel(value) -> None
Sets the maximum allowed credit for a pixel in history.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - value:
integer()
Python prototype (for reference only):
setMaxPixelStability(value) -> None
Sets the number of frames with same pixel color to consider stable.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - value:
integer()
Python prototype (for reference only):
setMinPixelStability(value) -> None
Sets if we're giving a pixel credit for being stable for a long time.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.t() - value:
bool
Python prototype (for reference only):
setUseHistory(value) -> None
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}
Stores algorithm parameters in a file storage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorCNT.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.BgSegm.BackgroundSubtractorCNT.t() - fs:
Evision.FileStorage - name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None