Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in [277].
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#include <opencv2/ximgproc/segmentation.hpp>
Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in [277].
◆ get()
virtual float cv::ximgproc::segmentation::SelectiveSearchSegmentationStrategy::get |
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int |
r1, |
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int |
r2 |
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pure virtual |
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| cv.ximgproc.segmentation.SelectiveSearchSegmentationStrategy.get( | r1, r2 | ) -> | retval |
Return the score between two regions (between 0 and 1)
- Parameters
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r1 | The first region |
r2 | The second region |
◆ merge()
virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentationStrategy::merge |
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int |
r1, |
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int |
r2 |
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pure virtual |
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| cv.ximgproc.segmentation.SelectiveSearchSegmentationStrategy.merge( | r1, r2 | ) -> | None |
Inform the strategy that two regions will be merged.
- Parameters
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r1 | The first region |
r2 | The second region |
◆ setImage()
virtual void cv::ximgproc::segmentation::SelectiveSearchSegmentationStrategy::setImage |
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InputArray |
img, |
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InputArray |
regions, |
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InputArray |
sizes, |
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int |
image_id = -1 |
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) |
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pure virtual |
Python: |
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| cv.ximgproc.segmentation.SelectiveSearchSegmentationStrategy.setImage( | img, regions, sizes[, image_id] | ) -> | None |
Set a initial image, with a segmentation.
- Parameters
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img | The input image. Any number of channel can be provided |
regions | A segmentation of the image. The parameter must be the same size of img. |
sizes | The sizes of different regions |
image_id | If not set to -1, try to cache pre-computations. If the same set og (img, regions, size) is used, the image_id need to be the same. |
The documentation for this class was generated from the following file: