Background subtraction based on counting.
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#include <opencv2/bgsegm.hpp>
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 )
◆ apply()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::apply |
( |
InputArray |
image, |
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|
OutputArray |
fgmask, |
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double |
learningRate = -1 |
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) |
| |
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pure virtual |
| Python: |
|---|
| fgmask | = | cv.bgsegm_BackgroundSubtractorCNT.apply( | image[, fgmask[, learningRate]] | ) |
Computes a foreground mask.
- 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. |
Implements cv::BackgroundSubtractor.
◆ getBackgroundImage()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::getBackgroundImage |
( |
OutputArray |
backgroundImage | ) |
const |
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pure virtual |
| Python: |
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| backgroundImage | = | cv.bgsegm_BackgroundSubtractorCNT.getBackgroundImage( | [, backgroundImage] | ) |
Computes a background image.
- Parameters
-
| backgroundImage | The output background image. |
- Note
- Sometimes the background image can be very blurry, as it contain the average background statistics.
Implements cv::BackgroundSubtractor.
◆ getIsParallel()
| virtual bool cv::bgsegm::BackgroundSubtractorCNT::getIsParallel |
( |
| ) |
const |
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pure virtual |
| Python: |
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| retval | = | cv.bgsegm_BackgroundSubtractorCNT.getIsParallel( | | ) |
Returns if we're parallelizing the algorithm.
◆ getMaxPixelStability()
| virtual int cv::bgsegm::BackgroundSubtractorCNT::getMaxPixelStability |
( |
| ) |
const |
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pure virtual |
| Python: |
|---|
| retval | = | cv.bgsegm_BackgroundSubtractorCNT.getMaxPixelStability( | | ) |
Returns maximum allowed credit for a pixel in history.
◆ getMinPixelStability()
| virtual int cv::bgsegm::BackgroundSubtractorCNT::getMinPixelStability |
( |
| ) |
const |
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pure virtual |
| Python: |
|---|
| retval | = | cv.bgsegm_BackgroundSubtractorCNT.getMinPixelStability( | | ) |
Returns number of frames with same pixel color to consider stable.
◆ getUseHistory()
| virtual bool cv::bgsegm::BackgroundSubtractorCNT::getUseHistory |
( |
| ) |
const |
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pure virtual |
| Python: |
|---|
| retval | = | cv.bgsegm_BackgroundSubtractorCNT.getUseHistory( | | ) |
Returns if we're giving a pixel credit for being stable for a long time.
◆ setIsParallel()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::setIsParallel |
( |
bool |
value | ) |
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pure virtual |
| Python: |
|---|
| None | = | cv.bgsegm_BackgroundSubtractorCNT.setIsParallel( | value | ) |
Sets if we're parallelizing the algorithm.
◆ setMaxPixelStability()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::setMaxPixelStability |
( |
int |
value | ) |
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pure virtual |
| Python: |
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| None | = | cv.bgsegm_BackgroundSubtractorCNT.setMaxPixelStability( | value | ) |
Sets the maximum allowed credit for a pixel in history.
◆ setMinPixelStability()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::setMinPixelStability |
( |
int |
value | ) |
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pure virtual |
| Python: |
|---|
| None | = | cv.bgsegm_BackgroundSubtractorCNT.setMinPixelStability( | value | ) |
Sets the number of frames with same pixel color to consider stable.
◆ setUseHistory()
| virtual void cv::bgsegm::BackgroundSubtractorCNT::setUseHistory |
( |
bool |
value | ) |
|
|
pure virtual |
| Python: |
|---|
| None | = | cv.bgsegm_BackgroundSubtractorCNT.setUseHistory( | value | ) |
Sets if we're giving a pixel credit for being stable for a long time.
The documentation for this class was generated from the following file:
Public Member Functions inherited from cv::Algorithm
1.8.13