View Source Evision.BgSegm.BackgroundSubtractorMOG (Evision v0.2.9)
Summary
Functions
Computes a foreground mask.
Computes a foreground mask.
Clears the algorithm state
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read
Computes a background image.
Computes a background image.
getBackgroundRatio
getDefaultName
getHistory
getNMixtures
getNoiseSigma
Reads algorithm parameters from a file storage
save
setBackgroundRatio
setHistory
setNMixtures
setNoiseSigma
Stores algorithm parameters in a file storage
write
Types
@type t() :: %Evision.BgSegm.BackgroundSubtractorMOG{ref: reference()}
Type that represents an BgSegm.BackgroundSubtractorMOG
struct.
ref.
reference()
The underlying erlang resource variable.
Functions
@spec apply(t(), Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}
Computes a foreground mask.
Positional Arguments
self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
image:
Evision.Mat
.Next video frame.
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.
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()}
Computes a foreground mask.
Positional Arguments
self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
image:
Evision.Mat
.Next video frame.
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.
Python prototype (for reference only):
apply(image[, 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.BackgroundSubtractorMOG.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.BackgroundSubtractorMOG.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()}
Computes a background image.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
backgroundImage:
Evision.Mat.t()
.The output background image.
Note: Sometimes the background image can be very blurry, as it contain the average background statistics.
Python prototype (for reference only):
getBackgroundImage([, backgroundImage]) -> backgroundImage
@spec getBackgroundImage(t(), [{atom(), term()}, ...] | nil) :: Evision.Mat.t() | {:error, String.t()}
Computes a background image.
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
backgroundImage:
Evision.Mat.t()
.The output background image.
Note: Sometimes the background image can be very blurry, as it contain the average background statistics.
Python prototype (for reference only):
getBackgroundImage([, backgroundImage]) -> backgroundImage
@spec getBackgroundRatio(Keyword.t()) :: any() | {:error, String.t()}
@spec getBackgroundRatio(t()) :: number() | {:error, String.t()}
getBackgroundRatio
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
- retval:
double
Python prototype (for reference only):
getBackgroundRatio() -> retval
@spec getDefaultName(Keyword.t()) :: any() | {:error, String.t()}
@spec getDefaultName(t()) :: binary() | {:error, String.t()}
getDefaultName
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.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 getHistory(Keyword.t()) :: any() | {:error, String.t()}
@spec getHistory(t()) :: integer() | {:error, String.t()}
getHistory
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
- retval:
integer()
Python prototype (for reference only):
getHistory() -> retval
@spec getNMixtures(Keyword.t()) :: any() | {:error, String.t()}
@spec getNMixtures(t()) :: integer() | {:error, String.t()}
getNMixtures
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
- retval:
integer()
Python prototype (for reference only):
getNMixtures() -> retval
@spec getNoiseSigma(Keyword.t()) :: any() | {:error, String.t()}
@spec getNoiseSigma(t()) :: number() | {:error, String.t()}
getNoiseSigma
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Return
- retval:
double
Python prototype (for reference only):
getNoiseSigma() -> retval
@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}
Reads algorithm parameters from a file storage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
- func:
Evision.FileNode
Python prototype (for reference only):
read(fn) -> None
save
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.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
setBackgroundRatio
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
- backgroundRatio:
double
Python prototype (for reference only):
setBackgroundRatio(backgroundRatio) -> None
setHistory
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
- nframes:
integer()
Python prototype (for reference only):
setHistory(nframes) -> None
setNMixtures
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
- nmix:
integer()
Python prototype (for reference only):
setNMixtures(nmix) -> None
setNoiseSigma
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.t()
- noiseSigma:
double
Python prototype (for reference only):
setNoiseSigma(noiseSigma) -> None
@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}
Stores algorithm parameters in a file storage
Positional Arguments
- self:
Evision.BgSegm.BackgroundSubtractorMOG.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.BackgroundSubtractorMOG.t()
- fs:
Evision.FileStorage
- name:
String
Has overloading in C++
Python prototype (for reference only):
write(fs, name) -> None