Main module headers are moved 1 level up
e.g. <opencv2/core/core.hpp> become <opencv2/core.hpp> Also renamed <opencv2/core/opengl_interop.hpp> to <opencv2/core/opengl.hpp>
This commit is contained in:
Andrey Kamaev
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modules/softcascade/include/opencv2/softcascade.hpp
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modules/softcascade/include/opencv2/softcascade.hpp
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// 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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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2008-2013, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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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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//
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// * Redistribution's 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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// * Redistribution's 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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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software 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 disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// 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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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_SOFTCASCADE_HPP__
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#define __OPENCV_SOFTCASCADE_HPP__
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#include "opencv2/core.hpp"
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namespace cv { namespace softcascade {
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// Representation of detectors result.
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struct CV_EXPORTS Detection
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{
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// Default object type.
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enum {PEDESTRIAN = 1};
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// Creates Detection from an object bounding box and confidence.
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// Param b is a bounding box
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// Param c is a confidence that object belongs to class k
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// Param k is an object class
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Detection(const cv::Rect& b, const float c, int k = PEDESTRIAN) : bb(b), confidence(c), kind(k) {}
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cv::Rect bb;
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float confidence;
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int kind;
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};
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class CV_EXPORTS Dataset
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{
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public:
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typedef enum {POSITIVE = 1, NEGATIVE = 2} SampleType;
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virtual cv::Mat get(SampleType type, int idx) const = 0;
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virtual int available(SampleType type) const = 0;
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virtual ~Dataset();
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};
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// ========================================================================== //
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// Public interface feature pool.
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// ========================================================================== //
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class CV_EXPORTS FeaturePool
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{
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public:
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virtual int size() const = 0;
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virtual float apply(int fi, int si, const Mat& channels) const = 0;
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virtual void write( cv::FileStorage& fs, int index) const = 0;
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virtual ~FeaturePool();
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static cv::Ptr<FeaturePool> create(const cv::Size& model, int nfeatures, int nchannels );
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};
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// ========================================================================== //
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// First order channel feature.
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// ========================================================================== //
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class CV_EXPORTS ChannelFeature
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{
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public:
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ChannelFeature(int x, int y, int w, int h, int ch);
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~ChannelFeature();
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bool operator ==(ChannelFeature b);
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bool operator !=(ChannelFeature b);
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float operator() (const cv::Mat& integrals, const cv::Size& model) const;
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friend void write(cv::FileStorage& fs, const std::string&, const ChannelFeature& f);
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friend std::ostream& operator<<(std::ostream& out, const ChannelFeature& f);
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private:
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cv::Rect bb;
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int channel;
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};
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void write(cv::FileStorage& fs, const std::string&, const ChannelFeature& f);
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std::ostream& operator<<(std::ostream& out, const ChannelFeature& m);
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// ========================================================================== //
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// Public Interface for Integral Channel Feature.
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// ========================================================================== //
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class CV_EXPORTS_W ChannelFeatureBuilder : public cv::Algorithm
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{
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public:
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virtual ~ChannelFeatureBuilder();
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// apply channels to source frame
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CV_WRAP_AS(compute) virtual void operator()(InputArray src, CV_OUT OutputArray channels, cv::Size channelsSize = cv::Size()) const = 0;
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CV_WRAP virtual int totalChannels() const = 0;
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virtual cv::AlgorithmInfo* info() const = 0;
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CV_WRAP static cv::Ptr<ChannelFeatureBuilder> create(const std::string& featureType);
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};
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// ========================================================================== //
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// Implementation of soft (stageless) cascaded detector.
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// ========================================================================== //
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class CV_EXPORTS_W Detector : public cv::Algorithm
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{
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public:
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enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
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// An empty cascade will be created.
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// Param minScale is a minimum scale relative to the original size of the image on which cascade will be applied.
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// Param minScale is a maximum scale relative to the original size of the image on which cascade will be applied.
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// Param scales is a number of scales from minScale to maxScale.
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// Param rejCriteria is used for NMS.
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CV_WRAP Detector(double minScale = 0.4, double maxScale = 5., int scales = 55, int rejCriteria = 1);
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CV_WRAP virtual ~Detector();
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cv::AlgorithmInfo* info() const;
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// Load soft cascade from FileNode.
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// Param fileNode is a root node for cascade.
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CV_WRAP virtual bool load(const FileNode& fileNode);
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// Load soft cascade config.
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CV_WRAP virtual void read(const FileNode& fileNode);
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// Return the vector of Detection objects.
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// Param image is a frame on which detector will be applied.
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// Param rois is a vector of regions of interest. Only the objects that fall into one of the regions will be returned.
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// Param objects is an output array of Detections
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virtual void detect(InputArray image, InputArray rois, std::vector<Detection>& objects) const;
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// Param rects is an output array of bounding rectangles for detected objects.
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// Param confs is an output array of confidence for detected objects. i-th bounding rectangle corresponds i-th confidence.
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CV_WRAP virtual void detect(InputArray image, InputArray rois, CV_OUT OutputArray rects, CV_OUT OutputArray confs) const;
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private:
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void detectNoRoi(const Mat& image, std::vector<Detection>& objects) const;
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struct Fields;
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Fields* fields;
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double minScale;
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double maxScale;
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int scales;
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int rejCriteria;
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};
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// ========================================================================== //
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// Public Interface for singe soft (stageless) cascade octave training.
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// ========================================================================== //
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class CV_EXPORTS Octave : public cv::Algorithm
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{
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public:
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enum
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{
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// Direct backward pruning. (Cha Zhang and Paul Viola)
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DBP = 1,
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// Multiple instance pruning. (Cha Zhang and Paul Viola)
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MIP = 2,
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// Originally proposed by L. Bourdev and J. Brandt
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HEURISTIC = 4
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};
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virtual ~Octave();
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static cv::Ptr<Octave> create(cv::Rect boundingBox, int npositives, int nnegatives,
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int logScale, int shrinkage, cv::Ptr<ChannelFeatureBuilder> builder);
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virtual bool train(const Dataset* dataset, const FeaturePool* pool, int weaks, int treeDepth) = 0;
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virtual void setRejectThresholds(OutputArray thresholds) = 0;
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virtual void write( cv::FileStorage &fs, const FeaturePool* pool, InputArray thresholds) const = 0;
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virtual void write( CvFileStorage* fs, std::string name) const = 0;
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};
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CV_EXPORTS bool initModule_softcascade(void);
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}} // namespace cv { namespace softcascade {
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#endif
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