/*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. // Copyright (C) 2017, Intel Corporation, 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 namespace cv { namespace dnn { class SliceLayerImpl : public SliceLayer { public: SliceLayerImpl(const LayerParams& params) { setParamsFrom(params); axis = params.get("axis", 1); if (params.has("slice_point")) { CV_Assert(!params.has("begin") && !params.has("size")); const DictValue &indicesValue = params.get("slice_point"); sliceRanges.resize(indicesValue.size() + 1, std::vector(axis + 1, Range::all())); int prevSlice = 0; for (int i = 0; i < indicesValue.size(); ++i) { sliceRanges[i][axis].start = prevSlice; sliceRanges[i][axis].end = indicesValue.get(i); prevSlice = sliceRanges[i][axis].end; } sliceRanges.back()[axis].start = prevSlice; } else if (params.has("begin") && params.has("size")) { const DictValue &begins = params.get("begin"); const DictValue &sizes = params.get("size"); CV_Assert(begins.size() == sizes.size()); sliceRanges.resize(1); sliceRanges[0].resize(begins.size(), Range::all()); for (int i = 0; i < begins.size(); ++i) { int start = begins.get(i); int size = sizes.get(i); CV_Assert(start >= 0); CV_Assert(size == -1 || size > 0); // -1 value means range [start, axis_size). sliceRanges[0][i].start = start; if (size > 0) sliceRanges[0][i].end = start + size; } } } bool getMemoryShapes(const std::vector &inputs, const int requiredOutputs, std::vector &outputs, std::vector &internals) const { CV_Assert(inputs.size() == 1); MatShape inpShape = inputs[0]; if (!sliceRanges.empty()) { outputs.resize(sliceRanges.size(), inpShape); for (int i = 0; i < outputs.size(); ++i) { CV_Assert(sliceRanges[i].size() <= inpShape.size()); for (int j = 0; j < sliceRanges[i].size(); ++j) { outputs[i][j] = std::min(sliceRanges[i][j].end, inpShape[j]) - std::max(sliceRanges[i][j].start, 0); } } } else // Divide input blob on equal parts by axis. { CV_Assert(0 < axis && axis < inpShape.size()); CV_Assert(requiredOutputs > 0 && inpShape[axis] % requiredOutputs == 0); inpShape[axis] /= requiredOutputs; outputs.resize(requiredOutputs, inpShape); } return false; } void finalize(const std::vector &inputs, std::vector &outputs) { CV_Assert(inputs.size() == 1); const MatSize& inpShape = inputs[0]->size; if (sliceRanges.empty()) { // Divide input blob on equal parts by axis. int outAxisSize = inpShape[axis] / outputs.size(); sliceRanges.resize(outputs.size(), std::vector(axis + 1, Range::all())); int prevSlice = 0; for (int i = 0; i < outputs.size(); ++i) { sliceRanges[i][axis].start = prevSlice; sliceRanges[i][axis].end = sliceRanges[i][axis].start + outAxisSize; prevSlice = sliceRanges[i][axis].end; } } else CV_Assert(outputs.size() == sliceRanges.size()); for (int i = 0; i < outputs.size(); ++i) { CV_Assert(sliceRanges[i].size() <= inpShape[-1]); // Clamp. for (int j = 0; j < sliceRanges[i].size(); ++j) { sliceRanges[i][j].start = std::max(0, sliceRanges[i][j].start); sliceRanges[i][j].end = std::min(sliceRanges[i][j].end, inpShape[j]); } // Fill the rest of ranges. for (int j = sliceRanges[i].size(); j < inpShape[-1]; ++j) { sliceRanges[i].push_back(Range::all()); } } } void forward(std::vector &inputs, std::vector &outputs, std::vector &internals) { CV_TRACE_FUNCTION(); CV_TRACE_ARG_VALUE(name, "name", name.c_str()); const Mat& inpMat = *inputs[0]; CV_Assert(outputs.size() == sliceRanges.size()); for (size_t i = 0; i < outputs.size(); i++) { inpMat(sliceRanges[i]).copyTo(outputs[i]); } } }; Ptr SliceLayer::create(const LayerParams& params) { return Ptr(new SliceLayerImpl(params)); } } }