/*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 "mvn_layer.hpp" namespace cv { namespace dnn { MVNLayer::MVNLayer(LayerParams ¶ms) : Layer(params) { eps = params.get<double>("eps", 1e-9); acrossChannels = params.get<bool>("across_channels", false); normalizeVariance = params.get<bool>("normalize_variance", true); } void MVNLayer::allocate(const std::vector<Blob *> &inputs, std::vector<Blob> &outputs) { outputs.resize(inputs.size()); for (size_t i = 0; i < inputs.size(); i++) { CV_Assert(!acrossChannels || inputs[i]->dims() >= 2); outputs[i].create(inputs[i]->shape(), inputs[i]->type()); } } void MVNLayer::forward(std::vector<Blob *> &inputs, std::vector<Blob> &outputs) { for (size_t inpIdx = 0; inpIdx < inputs.size(); inpIdx++) { Blob &inpBlob = *inputs[inpIdx]; Blob &outBlob = outputs[inpIdx]; int workSize[2]; int splitDim = (acrossChannels) ? 1 : 2; workSize[0] = (int)inpBlob.total(0, splitDim); workSize[1] = (int)inpBlob.total(splitDim); Mat inpMat = inpBlob.matRef().reshape(1, 2, workSize); Mat outMat = outBlob.matRef().reshape(1, 2, workSize); Scalar mean, dev; for (int i = 0; i < workSize[0]; i++) { Mat inpRow = inpMat.row(i); Mat outRow = outMat.row(i); cv::meanStdDev(inpRow, mean, (normalizeVariance) ? dev : noArray()); double alpha = (normalizeVariance) ? 1/(eps + dev[0]) : 1; inpRow.convertTo(outRow, outRow.type(), alpha, -mean[0] * alpha); } } } } }