View Source Evision.BackgroundSubtractor (Evision v0.1.21)

Link to this section Summary

Types

t()

Type that represents an Evision.BackgroundSubtractor struct.

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.

getDefaultName

Reads algorithm parameters from a file storage

simplified API for language bindings

simplified API for language bindings

Link to this section Types

@type t() :: %Evision.BackgroundSubtractor{ref: reference()}

Type that represents an Evision.BackgroundSubtractor struct.

  • ref. reference()

    The underlying erlang resource variable.

Link to this section Functions

@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.

    The output foreground mask as an 8-bit binary image.

Python prototype (for reference only):

apply(image[, fgmask[, learningRate]]) -> fgmask
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apply(self, image, opts)

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@spec apply(t(), Evision.Mat.maybe_mat_in(), [{atom(), 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.

    The output foreground mask as an 8-bit binary image.

Python prototype (for reference only):

apply(image[, fgmask[, learningRate]]) -> fgmask
@spec clear(t()) :: :ok | {:error, String.t()}

Clears the algorithm state

Positional Arguments
  • self: Evision.BackgroundSubtractor.t()

Python prototype (for reference only):

clear() -> None
@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
Link to this function

getBackgroundImage(self)

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

Computes a background image.

Positional Arguments
  • self: Evision.BackgroundSubtractor.t()
Return
  • backgroundImage: Evision.Mat.

    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
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getBackgroundImage(self, opts)

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@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.

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

getDefaultName

Positional Arguments
  • self: Evision.BackgroundSubtractor.t()
Return

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()) :: :ok | {:error, String.t()}

Reads algorithm parameters from a file storage

Positional Arguments

Python prototype (for reference only):

read(fn_) -> None
@spec save(t(), binary()) :: :ok | {: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()) :: :ok | {:error, String.t()}

simplified API for language bindings

Positional Arguments
Keyword Arguments

Has overloading in C++

Python prototype (for reference only):

write(fs[, name]) -> None
@spec write(t(), Evision.FileStorage.t(), [{atom(), term()}, ...] | nil) ::
  :ok | {:error, String.t()}

simplified API for language bindings

Positional Arguments
Keyword Arguments

Has overloading in C++

Python prototype (for reference only):

write(fs[, name]) -> None