123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252 |
- /*
- By downloading, copying, installing or using the software you agree to this
- license. If you do not agree to this license, do not download, install,
- copy or use the software.
- License Agreement
- For Open Source Computer Vision Library
- (3-clause BSD License)
- Copyright (C) 2013, OpenCV Foundation, all rights reserved.
- Third party copyrights are property of their respective owners.
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
- * Redistributions of source code must retain the above copyright notice,
- this list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
- this list of conditions and the following disclaimer in the documentation
- and/or other materials provided with the distribution.
- * Neither the names of the copyright holders nor the names of the contributors
- may be used to endorse or promote products derived from this software
- without specific prior written permission.
- This software is provided by the copyright holders and contributors "as is" and
- any express or implied warranties, including, but not limited to, the implied
- warranties of merchantability and fitness for a particular purpose are
- disclaimed. In no event shall copyright holders or contributors be liable for
- any direct, indirect, incidental, special, exemplary, or consequential damages
- (including, but not limited to, procurement of substitute goods or services;
- loss of use, data, or profits; or business interruption) however caused
- and on any theory of liability, whether in contract, strict liability,
- or tort (including negligence or otherwise) arising in any way out of
- the use of this software, even if advised of the possibility of such damage.
- */
- #ifndef __OPENCV_XIMGPROC_SEGMENTATION_HPP__
- #define __OPENCV_XIMGPROC_SEGMENTATION_HPP__
- #include <opencv2/core.hpp>
- namespace cv {
- namespace ximgproc {
- namespace segmentation {
- //! @addtogroup ximgproc_segmentation
- //! @{
- /** @brief Graph Based Segmentation Algorithm.
- The class implements the algorithm described in @cite PFF2004 .
- */
- class CV_EXPORTS_W GraphSegmentation : public Algorithm {
- public:
- /** @brief Segment an image and store output in dst
- @param src The input image. Any number of channel (1 (Eg: Gray), 3 (Eg: RGB), 4 (Eg: RGB-D)) can be provided
- @param dst The output segmentation. It's a CV_32SC1 Mat with the same number of cols and rows as input image, with an unique, sequential, id for each pixel.
- */
- CV_WRAP virtual void processImage(InputArray src, OutputArray dst) = 0;
- CV_WRAP virtual void setSigma(double sigma) = 0;
- CV_WRAP virtual double getSigma() = 0;
- CV_WRAP virtual void setK(float k) = 0;
- CV_WRAP virtual float getK() = 0;
- CV_WRAP virtual void setMinSize(int min_size) = 0;
- CV_WRAP virtual int getMinSize() = 0;
- };
- /** @brief Creates a graph based segmentor
- @param sigma The sigma parameter, used to smooth image
- @param k The k parameter of the algorythm
- @param min_size The minimum size of segments
- */
- CV_EXPORTS_W Ptr<GraphSegmentation> createGraphSegmentation(double sigma=0.5, float k=300, int min_size=100);
- /** @brief Strategie for the selective search segmentation algorithm
- The class implements a generic stragery for the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategy : public Algorithm {
- public:
- /** @brief Set a initial image, with a segementation.
- @param img The input image. Any number of channel can be provided
- @param regions A segementation of the image. The parameter must be the same size of img.
- @param sizes The sizes of different regions
- @param 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.
- */
- CV_WRAP virtual void setImage(InputArray img, InputArray regions, InputArray sizes, int image_id = -1) = 0;
- /** @brief Return the score between two regions (between 0 and 1)
- @param r1 The first region
- @param r2 The second region
- */
- CV_WRAP virtual float get(int r1, int r2) = 0;
- /** @brief Inform the strategy that two regions will be merged
- @param r1 The first region
- @param r2 The second region
- */
- CV_WRAP virtual void merge(int r1, int r2) = 0;
- };
- /** @brief Color-based strategy for the selective search segmentation algorithm
- The class is implemented from the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategyColor : public SelectiveSearchSegmentationStrategy {
- };
- /** @brief Create a new color-based strategy */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyColor> createSelectiveSearchSegmentationStrategyColor();
- /** @brief Size-based strategy for the selective search segmentation algorithm
- The class is implemented from the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategySize : public SelectiveSearchSegmentationStrategy {
- };
- /** @brief Create a new size-based strategy */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategySize> createSelectiveSearchSegmentationStrategySize();
- /** @brief Texture-based strategy for the selective search segmentation algorithm
- The class is implemented from the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategyTexture : public SelectiveSearchSegmentationStrategy {
- };
- /** @brief Create a new size-based strategy */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyTexture> createSelectiveSearchSegmentationStrategyTexture();
- /** @brief Fill-based strategy for the selective search segmentation algorithm
- The class is implemented from the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategyFill : public SelectiveSearchSegmentationStrategy {
- };
- /** @brief Create a new fill-based strategy */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyFill> createSelectiveSearchSegmentationStrategyFill();
- /** @brief Regroup multiple strategies for the selective search segmentation algorithm
- */
- class CV_EXPORTS_W SelectiveSearchSegmentationStrategyMultiple : public SelectiveSearchSegmentationStrategy {
- public:
- /** @brief Add a new sub-strategy
- @param g The strategy
- @param weight The weight of the strategy
- */
- CV_WRAP virtual void addStrategy(Ptr<SelectiveSearchSegmentationStrategy> g, float weight) = 0;
- /** @brief Remove all sub-strategies
- */
- CV_WRAP virtual void clearStrategies() = 0;
- };
- /** @brief Create a new multiple strategy */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyMultiple> createSelectiveSearchSegmentationStrategyMultiple();
- /** @brief Create a new multiple strategy and set one subtrategy
- @param s1 The first strategy
- */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyMultiple> createSelectiveSearchSegmentationStrategyMultiple(Ptr<SelectiveSearchSegmentationStrategy> s1);
- /** @brief Create a new multiple strategy and set two subtrategies, with equal weights
- @param s1 The first strategy
- @param s2 The second strategy
- */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyMultiple> createSelectiveSearchSegmentationStrategyMultiple(Ptr<SelectiveSearchSegmentationStrategy> s1, Ptr<SelectiveSearchSegmentationStrategy> s2);
- /** @brief Create a new multiple strategy and set three subtrategies, with equal weights
- @param s1 The first strategy
- @param s2 The second strategy
- @param s3 The third strategy
- */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyMultiple> createSelectiveSearchSegmentationStrategyMultiple(Ptr<SelectiveSearchSegmentationStrategy> s1, Ptr<SelectiveSearchSegmentationStrategy> s2, Ptr<SelectiveSearchSegmentationStrategy> s3);
- /** @brief Create a new multiple strategy and set four subtrategies, with equal weights
- @param s1 The first strategy
- @param s2 The second strategy
- @param s3 The third strategy
- @param s4 The forth strategy
- */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentationStrategyMultiple> createSelectiveSearchSegmentationStrategyMultiple(Ptr<SelectiveSearchSegmentationStrategy> s1, Ptr<SelectiveSearchSegmentationStrategy> s2, Ptr<SelectiveSearchSegmentationStrategy> s3, Ptr<SelectiveSearchSegmentationStrategy> s4);
- /** @brief Selective search segmentation algorithm
- The class implements the algorithm described in @cite uijlings2013selective.
- */
- class CV_EXPORTS_W SelectiveSearchSegmentation : public Algorithm {
- public:
- /** @brief Set a image used by switch* functions to initialize the class
- @param img The image
- */
- CV_WRAP virtual void setBaseImage(InputArray img) = 0;
- /** @brief Initialize the class with the 'Single stragegy' parameters describled in @cite uijlings2013selective.
- @param k The k parameter for the graph segmentation
- @param sigma The sigma parameter for the graph segmentation
- */
- CV_WRAP virtual void switchToSingleStrategy(int k = 200, float sigma = 0.8f) = 0;
- /** @brief Initialize the class with the 'Selective search fast' parameters describled in @cite uijlings2013selective.
- @param base_k The k parameter for the first graph segmentation
- @param inc_k The increment of the k parameter for all graph segmentations
- @param sigma The sigma parameter for the graph segmentation
- */
- CV_WRAP virtual void switchToSelectiveSearchFast(int base_k = 150, int inc_k = 150, float sigma = 0.8f) = 0;
- /** @brief Initialize the class with the 'Selective search fast' parameters describled in @cite uijlings2013selective.
- @param base_k The k parameter for the first graph segmentation
- @param inc_k The increment of the k parameter for all graph segmentations
- @param sigma The sigma parameter for the graph segmentation
- */
- CV_WRAP virtual void switchToSelectiveSearchQuality(int base_k = 150, int inc_k = 150, float sigma = 0.8f) = 0;
- /** @brief Add a new image in the list of images to process.
- @param img The image
- */
- CV_WRAP virtual void addImage(InputArray img) = 0;
- /** @brief Clear the list of images to process
- */
- CV_WRAP virtual void clearImages() = 0;
- /** @brief Add a new graph segmentation in the list of graph segementations to process.
- @param g The graph segmentation
- */
- CV_WRAP virtual void addGraphSegmentation(Ptr<GraphSegmentation> g) = 0;
- /** @brief Clear the list of graph segmentations to process;
- */
- CV_WRAP virtual void clearGraphSegmentations() = 0;
- /** @brief Add a new strategy in the list of strategy to process.
- @param s The strategy
- */
- CV_WRAP virtual void addStrategy(Ptr<SelectiveSearchSegmentationStrategy> s) = 0;
- /** @brief Clear the list of strategy to process;
- */
- CV_WRAP virtual void clearStrategies() = 0;
- /** @brief Based on all images, graph segmentations and stragies, computes all possible rects and return them
- @param rects The list of rects. The first ones are more relevents than the lasts ones.
- */
- CV_WRAP virtual void process(CV_OUT std::vector<Rect>& rects) = 0;
- };
- /** @brief Create a new SelectiveSearchSegmentation class.
- */
- CV_EXPORTS_W Ptr<SelectiveSearchSegmentation> createSelectiveSearchSegmentation();
- //! @}
- }
- }
- }
- #endif
|