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

Computes a foreground mask.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.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.BackgroundSubtractorGMG.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.BackgroundSubtractorGMG.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.BackgroundSubtractorGMG.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.BackgroundSubtractorGMG.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.BackgroundSubtractorGMG.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 getBackgroundPrior(Keyword.t()) :: any() | {:error, String.t()}

@spec getBackgroundPrior(t()) :: number() | {:error, String.t()}

Returns the prior probability that each individual pixel is a background pixel.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: double

Python prototype (for reference only):

getBackgroundPrior() -> retval

@spec getDecisionThreshold(Keyword.t()) :: any() | {:error, String.t()}

@spec getDecisionThreshold(t()) :: number() | {:error, String.t()}

Returns the value of decision threshold.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: double

Decision value is the value above which pixel is determined to be FG.

Python prototype (for reference only):

getDecisionThreshold() -> retval

@spec getDefaultLearningRate(Keyword.t()) :: any() | {:error, String.t()}

@spec getDefaultLearningRate(t()) :: number() | {:error, String.t()}

Returns the learning rate of the algorithm.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: double

It lies between 0.0 and 1.0. It determines how quickly features are "forgotten" from histograms.

Python prototype (for reference only):

getDefaultLearningRate() -> retval

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

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

getDefaultName

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.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 getMaxFeatures(Keyword.t()) :: any() | {:error, String.t()}

@spec getMaxFeatures(t()) :: integer() | {:error, String.t()}

Returns total number of distinct colors to maintain in histogram.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: integer()

Python prototype (for reference only):

getMaxFeatures() -> retval

@spec getMaxVal(Keyword.t()) :: any() | {:error, String.t()}

@spec getMaxVal(t()) :: number() | {:error, String.t()}

Returns the maximum value taken on by pixels in image sequence. e.g. 1.0 or 255.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: double

Python prototype (for reference only):

getMaxVal() -> retval

@spec getMinVal(Keyword.t()) :: any() | {:error, String.t()}

@spec getMinVal(t()) :: number() | {:error, String.t()}

Returns the minimum value taken on by pixels in image sequence. Usually 0.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: double

Python prototype (for reference only):

getMinVal() -> retval

@spec getNumFrames(Keyword.t()) :: any() | {:error, String.t()}

@spec getNumFrames(t()) :: integer() | {:error, String.t()}

Returns the number of frames used to initialize background model.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: integer()

Python prototype (for reference only):

getNumFrames() -> retval

@spec getQuantizationLevels(Keyword.t()) :: any() | {:error, String.t()}

@spec getQuantizationLevels(t()) :: integer() | {:error, String.t()}

Returns the parameter used for quantization of color-space.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: integer()

It is the number of discrete levels in each channel to be used in histograms.

Python prototype (for reference only):

getQuantizationLevels() -> retval

@spec getSmoothingRadius(Keyword.t()) :: any() | {:error, String.t()}

@spec getSmoothingRadius(t()) :: integer() | {:error, String.t()}

Returns the kernel radius used for morphological operations

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: integer()

Python prototype (for reference only):

getSmoothingRadius() -> retval

@spec getUpdateBackgroundModel(Keyword.t()) :: any() | {:error, String.t()}

@spec getUpdateBackgroundModel(t()) :: boolean() | {:error, String.t()}

Returns the status of background model update

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()

Return

• retval: bool

Python prototype (for reference only):

getUpdateBackgroundModel() -> retval

@spec read(t(), Evision.FileNode.t()) :: t() | {:error, String.t()}

Reads algorithm parameters from a file storage

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.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.BgSegm.BackgroundSubtractorGMG.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 setBackgroundPrior(t(), number()) :: t() | {:error, String.t()}

Sets the prior probability that each individual pixel is a background pixel.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• bgprior: double

Python prototype (for reference only):

setBackgroundPrior(bgprior) -> None

@spec setDecisionThreshold(t(), number()) :: t() | {:error, String.t()}

Sets the value of decision threshold.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• thresh: double

Python prototype (for reference only):

setDecisionThreshold(thresh) -> None

@spec setDefaultLearningRate(t(), number()) :: t() | {:error, String.t()}

Sets the learning rate of the algorithm.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• lr: double

Python prototype (for reference only):

setDefaultLearningRate(lr) -> None

@spec setMaxFeatures(t(), integer()) :: t() | {:error, String.t()}

Sets total number of distinct colors to maintain in histogram.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• maxFeatures: integer()

Python prototype (for reference only):

setMaxFeatures(maxFeatures) -> None

@spec setMaxVal(t(), number()) :: t() | {:error, String.t()}

Sets the maximum value taken on by pixels in image sequence.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• val: double

Python prototype (for reference only):

setMaxVal(val) -> None

@spec setMinVal(t(), number()) :: t() | {:error, String.t()}

Sets the minimum value taken on by pixels in image sequence.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• val: double

Python prototype (for reference only):

setMinVal(val) -> None

@spec setNumFrames(t(), integer()) :: t() | {:error, String.t()}

Sets the number of frames used to initialize background model.

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• nframes: integer()

Python prototype (for reference only):

setNumFrames(nframes) -> None

@spec setQuantizationLevels(t(), integer()) :: t() | {:error, String.t()}

Sets the parameter used for quantization of color-space

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• nlevels: integer()

Python prototype (for reference only):

setQuantizationLevels(nlevels) -> None

@spec setSmoothingRadius(t(), integer()) :: t() | {:error, String.t()}

Sets the kernel radius used for morphological operations

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• radius: integer()

Python prototype (for reference only):

setSmoothingRadius(radius) -> None

@spec setUpdateBackgroundModel(t(), boolean()) :: t() | {:error, String.t()}

Sets the status of background model update

Positional Arguments

• self: Evision.BgSegm.BackgroundSubtractorGMG.t()
• update: bool

Python prototype (for reference only):

setUpdateBackgroundModel(update) -> None

@spec write(t(), Evision.FileStorage.t()) :: t() | {:error, String.t()}

Stores algorithm parameters in a file storage

Positional Arguments

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

Has overloading in C++

Python prototype (for reference only):

write(fs, name) -> None