int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize = Size(), double scaleFactor = 1.1, int minNeighbors = 4);
};
+// ======================== GPU version for soft cascade ===================== //
+
+class CV_EXPORTS SoftCascade
+{
+public:
+ //! An empty cascade will be created.
+ SoftCascade();
+
+ //! Cascade will be created from file for scales from minScale to maxScale.
+ //! Param filename is a path to xml-serialized cascade.
+ //! Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed.
+ //! Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
+ SoftCascade( const string& filename, const float minScale = 0.4f, const float maxScale = 5.f);
+
+ //! cascade will be loaded from file "filename". The previous cascade will be destroyed.
+ //! Param filename is a path to xml-serialized cascade.
+ //! Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed.
+ //! Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
+ bool load( const string& filename, const float minScale = 0.4f, const float maxScale = 5.f);
+
+ virtual ~SoftCascade();
+
+ //! return vector of bounding boxes. Each box contains one detected object
+ virtual void detectMultiScale(const GpuMat& image, const GpuMat& rois, GpuMat& objects,
+ int rejectfactor = 1, Stream stream = Stream::Null()); // ToDo store objects in GPU mem
+
+protected:
+ enum { BOOST = 0 };
+ enum
+ {
+ FRAME_WIDTH = 640,
+ FRAME_HEIGHT = 480,
+ TOTAL_SCALES = 55,
+ CLASSIFIERS = 5,
+ ORIG_OBJECT_WIDTH = 64,
+ ORIG_OBJECT_HEIGHT = 128
+ };
+
+private:
+ struct Filds;
+ Filds* filds;
+};
+
////////////////////////////////// SURF //////////////////////////////////////////
class CV_EXPORTS SURF_GPU
--- /dev/null
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// 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
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2008-2012, Willow Garage Inc., 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:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's 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.
+//
+// * The name of the copyright holders may not 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 the Intel Corporation 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.
+//
+//M*/
+
+#include <precomp.hpp>
+
+#if !defined (HAVE_CUDA)
+
+cv::gpu::SoftCascade::SoftCascade() : filds(0) { throw_nogpu(); }
+
+cv::gpu::SoftCascade::SoftCascade( const string&, const float, const float) : filds(0) { throw_nogpu(); }
+
+cv::gpu::SoftCascade::~SoftCascade() { throw_nogpu(); }
+
+bool cv::gpu::SoftCascade::load( const string&, const float, const float) { throw_nogpu(); }
+
+void cv::gpu::SoftCascade::detectMultiScale(const GpuMat&, const GpuMat&, GpuMat&, const int, Stream) { throw_nogpu(); }
+
+#else
+
+struct cv::gpu::SoftCascade::Filds
+{
+ bool fill(const FileNode &root, const float mins, const float maxs){return true;}
+ void calcLevels(int frameW, int frameH, int scales) {}
+};
+
+cv::gpu::SoftCascade::SoftCascade() : filds(0) {}
+
+cv::gpu::SoftCascade::SoftCascade( const string& filename, const float minScale, const float maxScale) : filds(0)
+{
+ load(filename, minScale, maxScale);
+}
+
+cv::gpu::SoftCascade::~SoftCascade()
+{
+ delete filds;
+}
+
+bool cv::gpu::SoftCascade::load( const string& filename, const float minScale, const float maxScale)
+{
+ if (filds)
+ delete filds;
+ filds = 0;
+
+ cv::FileStorage fs(filename, FileStorage::READ);
+ if (!fs.isOpened()) return false;
+
+ filds = new Filds;
+ Filds& flds = *filds;
+ if (!flds.fill(fs.getFirstTopLevelNode(), minScale, maxScale)) return false;
+ flds.calcLevels(FRAME_WIDTH, FRAME_HEIGHT, TOTAL_SCALES);
+
+ return true;
+}
+
+void cv::gpu::SoftCascade::detectMultiScale(const GpuMat& /*image*/, const GpuMat& /*rois*/,
+ GpuMat& /*objects*/, const int /*rejectfactor*/, Stream /*stream*/)
+{
+ // empty
+}
+
+#endif