Package org.opencv.bgsegm
Class BackgroundSubtractorCNT
- java.lang.Object
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- org.opencv.core.Algorithm
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- org.opencv.video.BackgroundSubtractor
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- org.opencv.bgsegm.BackgroundSubtractorCNT
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public class BackgroundSubtractorCNT extends BackgroundSubtractor
Background subtraction based on counting. About as fast as MOG2 on a high end system. More than twice faster than MOG2 on cheap hardware (benchmarked on Raspberry Pi3). %Algorithm by Sagi Zeevi ( https://github.com/sagi-z/BackgroundSubtractorCNT )
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Constructor Summary
Constructors Modifier Constructor Description protected
BackgroundSubtractorCNT(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static BackgroundSubtractorCNT
__fromPtr__(long addr)
void
apply(Mat image, Mat fgmask)
Computes a foreground mask.void
apply(Mat image, Mat fgmask, double learningRate)
Computes a foreground mask.protected void
finalize()
void
getBackgroundImage(Mat backgroundImage)
Computes a background image.boolean
getIsParallel()
Returns if we're parallelizing the algorithm.int
getMaxPixelStability()
Returns maximum allowed credit for a pixel in history.int
getMinPixelStability()
Returns number of frames with same pixel color to consider stable.boolean
getUseHistory()
Returns if we're giving a pixel credit for being stable for a long time.void
setIsParallel(boolean value)
Sets if we're parallelizing the algorithm.void
setMaxPixelStability(int value)
Sets the maximum allowed credit for a pixel in history.void
setMinPixelStability(int value)
Sets the number of frames with same pixel color to consider stable.void
setUseHistory(boolean value)
Sets if we're giving a pixel credit for being stable for a long time.-
Methods inherited from class org.opencv.core.Algorithm
clear, empty, getDefaultName, getNativeObjAddr, save
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Method Detail
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__fromPtr__
public static BackgroundSubtractorCNT __fromPtr__(long addr)
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apply
public void apply(Mat image, Mat fgmask, double learningRate)
Description copied from class:BackgroundSubtractor
Computes a foreground mask.- Overrides:
apply
in classBackgroundSubtractor
- Parameters:
image
- Next video frame.fgmask
- The output foreground mask as an 8-bit binary image.learningRate
- 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.
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apply
public void apply(Mat image, Mat fgmask)
Description copied from class:BackgroundSubtractor
Computes a foreground mask.- Overrides:
apply
in classBackgroundSubtractor
- Parameters:
image
- Next video frame.fgmask
- The output foreground mask as an 8-bit binary image. 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.
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getBackgroundImage
public void getBackgroundImage(Mat backgroundImage)
Description copied from class:BackgroundSubtractor
Computes a background image.- Overrides:
getBackgroundImage
in classBackgroundSubtractor
- Parameters:
backgroundImage
- The output background image. Note: Sometimes the background image can be very blurry, as it contain the average background statistics.
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getMinPixelStability
public int getMinPixelStability()
Returns number of frames with same pixel color to consider stable.- Returns:
- automatically generated
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setMinPixelStability
public void setMinPixelStability(int value)
Sets the number of frames with same pixel color to consider stable.- Parameters:
value
- automatically generated
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getMaxPixelStability
public int getMaxPixelStability()
Returns maximum allowed credit for a pixel in history.- Returns:
- automatically generated
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setMaxPixelStability
public void setMaxPixelStability(int value)
Sets the maximum allowed credit for a pixel in history.- Parameters:
value
- automatically generated
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getUseHistory
public boolean getUseHistory()
Returns if we're giving a pixel credit for being stable for a long time.- Returns:
- automatically generated
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setUseHistory
public void setUseHistory(boolean value)
Sets if we're giving a pixel credit for being stable for a long time.- Parameters:
value
- automatically generated
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getIsParallel
public boolean getIsParallel()
Returns if we're parallelizing the algorithm.- Returns:
- automatically generated
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setIsParallel
public void setIsParallel(boolean value)
Sets if we're parallelizing the algorithm.- Parameters:
value
- automatically generated
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finalize
protected void finalize() throws java.lang.Throwable
- Overrides:
finalize
in classBackgroundSubtractor
- Throws:
java.lang.Throwable
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