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