Added PriorBox layer implementation

modules/dnn/src/layers/prior_box_layer.cpp

+/*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) 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:
+//
+//   * 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"
+#include "layers_common.hpp"
+#include "prior_box_layer.hpp"
+#include <float.h>
+#include <algorithm>
+#include <cmath>
+
+namespace cv
+{
+namespace dnn
+{
+
+void PriorBoxLayer::checkParameter(const LayerParams &params, const string &parameterName)
+{
+    if (!params.has(parameterName))
+    {
+        CV_Error(Error::StsBadArg, "PriorBox layer parameter does not contain " + parameterName + " index.");
+    }
+}
+
+PriorBoxLayer::PriorBoxLayer(LayerParams &params) : Layer(params)
+{
+    checkParameter(params, "min_size");
+
+    _minSize = params.min_size();
+    CV_Assert(_minSize > 0);
+
+    _aspectRatios.clear();
+    _aspectRatios.push_back(1.);
+
+    _flip = params.flip();
+
+    for (int i = 0; i < params.aspect_ratio_size(); ++i)
+    {
+        float aspectRatio = params.aspect_ratio(i);
+        bool already_exist = false;
+
+        for (int j = 0; j < _aspectRatios.size(); ++j)
+        {
+            if (fabs(aspectRatio - _aspectRatios[j]) < 1e-6)
+            {
+                already_exist = true;
+                break;
+            }
+        }
+        if (!already_exist)
+        {
+            _aspectRatios.push_back(aspectRatio);
+            if (_flip)
+            {
+                _aspectRatios.push_back(1./aspectRatio);
+            }
+        }
+    }
+
+    _numPriors = _aspectRatios.size();
+
+    _maxSize = -1;
+    if (params.has(max_size))
+    {
+        _maxSize = params.max_size();
+        CV_Assert(_maxSize > _minSize);
+
+        _numPriors += 1;
+    }
+
+    _clip = params.clip();
+
+    int varianceSize = params.variance_size();
+    if (varianceSize > 1)
+    {
+        // Must and only provide 4 variance.
+        CV_Assert(varianceSize == 4);
+
+        for (int i = 0; i < varianceSize; ++i)
+        {
+            float variance = params.variance(i);
+            CV_Assert(variance > 0);
+            _variance.push_back(variance);
+        }
+    }
+    else
+    {
+        if (varianceSize == 1)
+        {
+            float variance = params.variance(0);
+            CV_Assert(variance > 0);
+            _variance.push_back(variance);
+        }
+        else
+        {
+            // Set default to 0.1.
+            _variance.push_back(0.1);
+        }
+    }
+}
+
+void PriorBoxLayer::allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs)
+{
+    CV_Assert(inputs.size() == 2);
+
+    _layerWidth = inputs[0]->width();
+    _layerHeight = inputs[0]->height();
+
+    _imageWidth = inputs[1]->width();
+    _imageHeight = inputs[1]->height();
+
+    _stepX = static_cast<float>(_imageWidth) / _layerWidth;
+    _stepY = static_cast<float>(_imageHeight) / _layerHeight;
+
+    // Since all images in a batch has same height and width, we only need to
+    // generate one set of priors which can be shared across all images.
+    size_t outNum = 1;
+    // 2 channels. First channel stores the mean of each prior coordinate.
+    // Second channel stores the variance of each prior coordinate.
+    size_t outChannels = 2;
+    size_t outHeight = _layerHeight;
+    size_t outWidth = _layerWidth * _numPriors * 4;
+
+    _outChannelSize = _layerHeight * _layerWidth * _numPriors * 4;
+
+    outputs[0].create(BlobShape(outNum, outChannels, outHeight, outWidth));
+}
+
+void PriorBoxLayer::forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs)
+{
+    float* outputPtr = outputs[0].ptrf();
+
+    // first prior: aspect_ratio = 1, size = min_size
+    _boxWidth = _boxHeight = _minSize;
+
+    int idx = 0;
+    for (int h = 0; h < _layerHeight; ++h)
+    {
+        for (int w = 0; w < _layerWidth; ++w)
+        {
+            float center_x = (w + 0.5) * _stepX;
+            float center_y = (h + 0.5) * _stepY;
+            // xmin
+            outputPtr[idx++] = (center_x - _boxWidth / 2.) / _imageWidth;
+            // ymin
+            outputPtr[idx++] = (center_y - _boxHeight / 2.) / _imageHeight;
+            // xmax
+            outputPtr[idx++] = (center_x + _boxWidth / 2.) / _imageWidth;
+            // ymax
+            outputPtr[idx++] = (center_y + _boxHeight / 2.) / _imageHeight;
+
+            if (_maxSize > 0)
+            {
+                // second prior: aspect_ratio = 1, size = sqrt(min_size * max_size)
+                _boxWidth = _boxHeight = sqrt(_minSize * _maxSize);
+                // xmin
+                outputPtr[idx++] = (center_x - _boxWidth / 2.) / _imageWidth;
+                // ymin
+                outputPtr[idx++] = (center_y - _boxHeight / 2.) / _imageHeight;
+                // xmax
+                outputPtr[idx++] = (center_x + _boxWidth / 2.) / _imageWidth;
+                // ymax
+                outputPtr[idx++] = (center_y + _boxHeight / 2.) / _imageHeight;
+            }
+
+            // rest of priors
+            for (int r = 0; r < _aspectRatios.size(); ++r)
+            {
+                float ar = _aspectRatios[r];
+                if (fabs(ar - 1.) < 1e-6)
+                {
+                    continue;
+                }
+                _boxWidth = _minSize * sqrt(ar);
+                _boxHeight = _minSize / sqrt(ar);
+                // xmin
+                outputPtr[idx++] = (center_x - _boxWidth / 2.) / _imageWidth;
+                // ymin
+                outputPtr[idx++] = (center_y - _boxHeight / 2.) / _imageHeight;
+                // xmax
+                outputPtr[idx++] = (center_x + _boxWidth / 2.) / _imageWidth;
+                // ymax
+                outputPtr[idx++] = (center_y + _boxHeight / 2.) / _imageHeight;
+            }
+        }
+    }
+    // clip the prior's coordidate such that it is within [0, 1]
+    if (_clip)
+    {
+        for (int d = 0; d < _outChannelSize; ++d)
+        {
+            outputPtr[d] = std::min<float>(std::max<float>(outputPtr[d], 0.), 1.);
+        }
+    }
+    // set the variance.
+    outputPtr = outputs[0].ptrf(0, 1);
+    if(_variance.size() == 1)
+    {
+        Mat secondChannel(outputs[0].height(), outputs[0].width(), CV_32F, outputPtr);
+        secondChannel.setTo(Scalar(_variance[0]));
+    }
+    else
+    {
+        int count = 0;
+        for (int h = 0; h < _layerHeight; ++h)
+        {
+            for (int w = 0; w < _layerWidth; ++w)
+            {
+                for (int i = 0; i < _numPriors; ++i)
+                {
+                    for (int j = 0; j < 4; ++j)
+                    {
+                        outputPtr[count] = _variance[j];
+                        ++count;
+                    }
+                }
+            }
+        }
+    }
+}
+}
+}

modules/dnn/src/layers/prior_box_layer.hpp

+/*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) 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:
+//
+//   * 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*/
+
+#ifndef __OPENCV_DNN_LAYERS_PRIOR_BOX_LAYER_HPP__
+#define __OPENCV_DNN_LAYERS_PRIOR_BOX_LAYER_HPP__
+#include "../precomp.hpp"
+
+namespace cv
+{
+namespace dnn
+{
+class PriorBoxLayer : public Layer
+{
+    size_t _layerWidth;
+    size_t _layerHeight;
+
+    size_t _imageWidth;
+    size_t _imageHeight;
+
+    size_t _outChannelSize;
+
+    float _stepX;
+    float _stepY;
+
+    float _minSize;
+    float _maxSize;
+
+    float _boxWidth;
+    float _boxHeight;
+
+    std::vector<float> _aspectRatios;
+    std::vector<float> _variance;
+
+    bool _flip;
+    bool _clip;
+
+    size_t _numPriors;
+
+    static const size_t _numAxes = 4;
+
+public:
+    PriorBoxLayer(LayerParams &params);
+    void allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
+    void forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
+    void checkParameter(const LayerParams &params, const std::string &parameterName);
+};
+}
+}
+#endif