@spec apply(t(), Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}

Computes a foreground mask.

Positional Arguments

• self: Evision.BackgroundSubtractor.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.BackgroundSubtractor.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.BackgroundSubtractor.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.BackgroundSubtractor.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.BackgroundSubtractor.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.BackgroundSubtractor.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 getDefaultName(Keyword.t()) :: any() | {:error, String.t()}

@spec getDefaultName(t()) :: binary() | {:error, String.t()}

getDefaultName

Positional Arguments

• self: Evision.BackgroundSubtractor.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.BackgroundSubtractor.t()
• func: Evision.FileNode

Python prototype (for reference only):

read(fn) -> None

@spec save(t(), binary()) :: t() | {:error, String.t()}

save

Positional Arguments

• self: Evision.BackgroundSubtractor.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.BackgroundSubtractor.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.BackgroundSubtractor.t()
• fs: Evision.FileStorage
• name: String

Has overloading in C++

Python prototype (for reference only):

write(fs, name) -> None