View Source Evision.BackgroundSubtractor (Evision v0.1.7)

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cv

Computes a foreground mask.

Computes a foreground mask.

Computes a background image.

Link to this section cv

Computes a foreground mask.

Positional Arguments
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):

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

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Computes a foreground mask.

Positional Arguments
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):

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

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Computes a background image.

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):

getBackgroundImage([, backgroundImage]) -> backgroundImage

Link to this section Functions

Raising version of apply/2.

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apply!(self, image, opts)

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Raising version of apply/3.

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getBackgroundImage!(self)

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Raising version of getBackgroundImage/1.