Remove icf app, add xobjdetect module

modules/xobjdetect/include/opencv2/xobjdetect.hpp

@@ -0,0 +1,9 @@
+#ifndef __OPENCV_XOBJDETECT_XOBJDETECT_HPP__
+#define __OPENCV_XOBJDETECT_XOBJDETECT_HPP__
+
+#include "xobjdetect/stump.hpp"
+#include "xobjdetect/waldboost.hpp"
+#include "xobjdetect/acffeature.hpp"
+#include "xobjdetect/icfdetector.hpp"
+
+#endif /* __OPENCV_XOBJDETECT_XOBJDETECT_HPP__ */

modules/xobjdetect/include/opencv2/xobjdetect/acffeature.hpp

@@ -0,0 +1,108 @@
+/*
+
+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_ADAS_ACFFEATURE_HPP__
+#define __OPENCV_ADAS_ACFFEATURE_HPP__
+
+#include <opencv2/core.hpp>
+#include <vector>
+
+namespace cv
+{
+namespace adas
+{
+
+/* Compute channel pyramid for acf features
+
+    image — image, for which channels should be computed
+
+    channels — output array for computed channels
+
+*/
+void computeChannels(InputArray image, OutputArrayOfArrays channels);
+
+class CV_EXPORTS ACFFeatureEvaluator
+{
+public:
+    /* Construct evaluator, set features to evaluate */
+    ACFFeatureEvaluator(const std::vector<Point3i>& features);
+
+    /* Set channels for feature evaluation */
+    void setChannels(InputArrayOfArrays channels);
+
+    /* Set window position */
+    void setPosition(Size position);
+
+    /* Evaluate feature with given index for current channels
+        and window position */
+    int evaluate(size_t feature_ind) const;
+
+    /* Evaluate all features for current channels and window position
+
+    Returns matrix-column of features
+    */
+    void evaluateAll(OutputArray feature_values) const;
+
+private:
+    /* Features to evaluate */
+    std::vector<Point3i> features_;
+    /* Channels for feature evaluation */
+    std::vector<Mat> channels_;
+    /* Channels window position */
+    Size position_;
+};
+
+/* Generate acf features
+
+    window_size — size of window in which features should be evaluated
+
+    count — number of features to generate.
+    Max number of features is min(count, # possible distinct features)
+
+Returns vector of distinct acf features
+*/
+std::vector<Point3i>
+generateFeatures(Size window_size, int count = INT_MAX);
+
+} /* namespace adas */
+} /* namespace cv */
+
+#endif /* __OPENCV_ADAS_ACFFEATURE_HPP__ */

modules/xobjdetect/include/opencv2/xobjdetect/icfdetector.hpp

@@ -0,0 +1,85 @@
+/*
+
+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_ADAS_ICFDETECTOR_HPP__
+#define __OPENCV_ADAS_ICFDETECTOR_HPP__
+
+#include <string>
+#include <vector>
+
+#include <opencv2/core.hpp>
+
+namespace cv
+{
+namespace adas
+{
+
+struct CV_EXPORTS ICFDetectorParams
+{
+    int feature_count;
+    int weak_count;
+    int model_n_rows;
+    int model_n_cols;
+    double overlap;
+};
+
+class CV_EXPORTS ICFDetector
+{
+public:
+    /* Train detector
+
+        image_filenames — filenames of images for training
+
+        labelling — vector of object bounding boxes per every image
+
+        params — parameters for detector training
+    */
+    void train(const std::vector<std::string>& image_filenames,
+               const std::vector<std::vector<cv::Rect> >& labelling,
+               ICFDetectorParams params = ICFDetectorParams());
+
+    /* Save detector in file, return true on success, false otherwise */
+    bool save(const std::string& filename);
+};
+
+} /* namespace adas */
+} /* namespace cv */
+#endif /* __OPENCV_ADAS_ICFDETECTOR_HPP__ */

modules/xobjdetect/include/opencv2/xobjdetect/stump.hpp

@@ -0,0 +1,58 @@
+#ifndef __OPENCV_ADAS_STUMP_HPP__
+#define __OPENCV_ADAS_STUMP_HPP__
+
+#include <opencv2/core.hpp>
+
+namespace cv
+{
+namespace adas
+{
+
+class CV_EXPORTS Stump
+{
+public:
+
+    /* Initialize zero stump */
+    Stump(): threshold_(0), polarity_(1), pos_value_(1), neg_value_(-1) {}
+
+    /* Initialize stump with given threshold, polarity
+        and classification values */
+    Stump(int threshold, int polarity, float pos_value, float neg_value):
+        threshold_(threshold), polarity_(polarity),
+        pos_value_(pos_value), neg_value_(neg_value) {}
+
+    /* Train stump for given data
+
+        data — matrix of feature values, size M x N, one feature per row
+
+        labels — matrix of sample class labels, size 1 x N. Labels can be from
+            {-1, +1}
+
+        weights — matrix of sample weights, size 1 x N
+
+    Returns chosen feature index. Feature enumeration starts from 0
+    */
+    int train(const Mat& data, const Mat& labels, const Mat& weights);
+
+    /* Predict object class given
+
+        value — feature value. Feature must be the same as was chosen
+        during training stump
+
+    Returns real value, sign(value) means class
+    */
+    float predict(int value);
+
+private:
+    /* Stump decision threshold */
+    int threshold_;
+    /* Stump polarity, can be from {-1, +1} */
+    int polarity_;
+    /* Classification values for positive and negative classes  */
+    float pos_value_, neg_value_;
+};
+
+} /* namespace adas */
+} /* namespace cv */
+
+#endif /* __OPENCV_ADAS_STUMP_HPP__ */

modules/xobjdetect/include/opencv2/xobjdetect/waldboost.hpp

@@ -0,0 +1,101 @@
+/*
+
+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_ADAS_WALDBOOST_HPP__
+#define __OPENCV_ADAS_WALDBOOST_HPP__
+
+#include <opencv2/core.hpp>
+
+#include <opencv2/xobjdetect/acffeature.hpp>
+#include <opencv2/xobjdetect/stump.hpp>
+
+namespace cv
+{
+namespace adas
+{
+
+struct CV_EXPORTS WaldBoostParams
+{
+    int weak_count;
+    float alpha;
+};
+
+class CV_EXPORTS WaldBoost
+{
+public:
+    /* Initialize WaldBoost cascade with default of specified parameters */
+    WaldBoost(const WaldBoostParams& params);
+
+    /* Train WaldBoost cascade for given data
+
+        data — matrix of feature values, size M x N, one feature per row
+
+        labels — matrix of sample class labels, size 1 x N. Labels can be from
+            {-1, +1}
+
+    Returns feature indices chosen for cascade.
+    Feature enumeration starts from 0
+    */
+    std::vector<int> train(const Mat& data,
+                           const Mat& labels);
+
+    /* Predict object class given object that can compute object features
+
+       feature_evaluator — object that can compute features by demand
+
+    Returns confidence_value — measure of confidense that object
+    is from class +1
+    */
+    float predict(const Ptr<ACFFeatureEvaluator>& feature_evaluator);
+
+private:
+    /* Parameters for cascade training */
+    WaldBoostParams params_;
+    /* Stumps in cascade */
+    std::vector<Stump> stumps_;
+    /* Rejection thresholds for linear combination at every stump evaluation */
+    std::vector<float> thresholds_;
+};
+
+} /* namespace adas */
+} /* namespace cv */
+
+#endif /* __OPENCV_ADAS_WALDBOOST_HPP__ */