finds arbitrary template in the grayscale image using Generalized Hough Transform
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#include <opencv2/imgproc.hpp>
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virtual void | detect (InputArray edges, InputArray dx, InputArray dy, OutputArray positions, OutputArray votes=noArray())=0 |
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virtual void | detect (InputArray image, OutputArray positions, OutputArray votes=noArray())=0 |
| find template on image
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virtual int | getCannyHighThresh () const =0 |
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virtual int | getCannyLowThresh () const =0 |
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virtual double | getDp () const =0 |
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virtual int | getMaxBufferSize () const =0 |
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virtual double | getMinDist () const =0 |
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virtual void | setCannyHighThresh (int cannyHighThresh)=0 |
| Canny high threshold.
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virtual void | setCannyLowThresh (int cannyLowThresh)=0 |
| Canny low threshold.
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virtual void | setDp (double dp)=0 |
| Inverse ratio of the accumulator resolution to the image resolution.
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virtual void | setMaxBufferSize (int maxBufferSize)=0 |
| Maximal size of inner buffers.
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virtual void | setMinDist (double minDist)=0 |
| Minimum distance between the centers of the detected objects.
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virtual void | setTemplate (InputArray edges, InputArray dx, InputArray dy, Point templCenter=Point(-1, -1))=0 |
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virtual void | setTemplate (InputArray templ, Point templCenter=Point(-1, -1))=0 |
| set template to search
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state.
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virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage.
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virtual void | save (const String &filename) const |
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage.
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void | write (FileStorage &fs, const String &name) const |
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finds arbitrary template in the grayscale image using Generalized Hough Transform
◆ detect() [1/2]
Python: |
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| cv.GeneralizedHough.detect( | image[, positions[, votes]] | ) -> | positions, votes |
| cv.GeneralizedHough.detect( | edges, dx, dy[, positions[, votes]] | ) -> | positions, votes |
◆ detect() [2/2]
Python: |
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| cv.GeneralizedHough.detect( | image[, positions[, votes]] | ) -> | positions, votes |
| cv.GeneralizedHough.detect( | edges, dx, dy[, positions[, votes]] | ) -> | positions, votes |
◆ getCannyHighThresh()
virtual int cv::GeneralizedHough::getCannyHighThresh |
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const |
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pure virtual |
Python: |
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| cv.GeneralizedHough.getCannyHighThresh( | | ) -> | retval |
◆ getCannyLowThresh()
virtual int cv::GeneralizedHough::getCannyLowThresh |
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const |
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pure virtual |
Python: |
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| cv.GeneralizedHough.getCannyLowThresh( | | ) -> | retval |
◆ getDp()
virtual double cv::GeneralizedHough::getDp |
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const |
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pure virtual |
Python: |
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| cv.GeneralizedHough.getDp( | | ) -> | retval |
◆ getMaxBufferSize()
virtual int cv::GeneralizedHough::getMaxBufferSize |
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const |
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pure virtual |
Python: |
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| cv.GeneralizedHough.getMaxBufferSize( | | ) -> | retval |
◆ getMinDist()
virtual double cv::GeneralizedHough::getMinDist |
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const |
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pure virtual |
Python: |
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| cv.GeneralizedHough.getMinDist( | | ) -> | retval |
◆ setCannyHighThresh()
virtual void cv::GeneralizedHough::setCannyHighThresh |
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int |
cannyHighThresh | ) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setCannyHighThresh( | cannyHighThresh | ) -> | None |
◆ setCannyLowThresh()
virtual void cv::GeneralizedHough::setCannyLowThresh |
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int |
cannyLowThresh | ) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setCannyLowThresh( | cannyLowThresh | ) -> | None |
◆ setDp()
virtual void cv::GeneralizedHough::setDp |
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double |
dp | ) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setDp( | dp | ) -> | None |
Inverse ratio of the accumulator resolution to the image resolution.
◆ setMaxBufferSize()
virtual void cv::GeneralizedHough::setMaxBufferSize |
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int |
maxBufferSize | ) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setMaxBufferSize( | maxBufferSize | ) -> | None |
Maximal size of inner buffers.
◆ setMinDist()
virtual void cv::GeneralizedHough::setMinDist |
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double |
minDist | ) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setMinDist( | minDist | ) -> | None |
Minimum distance between the centers of the detected objects.
◆ setTemplate() [1/2]
Python: |
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| cv.GeneralizedHough.setTemplate( | templ[, templCenter] | ) -> | None |
| cv.GeneralizedHough.setTemplate( | edges, dx, dy[, templCenter] | ) -> | None |
◆ setTemplate() [2/2]
virtual void cv::GeneralizedHough::setTemplate |
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InputArray |
templ, |
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Point |
templCenter = Point(-1, -1) |
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) |
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pure virtual |
Python: |
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| cv.GeneralizedHough.setTemplate( | templ[, templCenter] | ) -> | None |
| cv.GeneralizedHough.setTemplate( | edges, dx, dy[, templCenter] | ) -> | None |
The documentation for this class was generated from the following file: