From: Li Peng Date: Tue, 5 Dec 2017 15:17:34 +0000 (+0800) Subject: prior box layer ocl implementation X-Git-Tag: accepted/tizen/6.0/unified/20201030.111113~269^2~2 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=910d7dab1f056ccd6531c8615e4f50e0c1c1c76d;p=platform%2Fupstream%2Fopencv.git prior box layer ocl implementation Signed-off-by: Li Peng --- diff --git a/modules/dnn/src/layers/prior_box_layer.cpp b/modules/dnn/src/layers/prior_box_layer.cpp index 5fc852a..575ac5e 100644 --- a/modules/dnn/src/layers/prior_box_layer.cpp +++ b/modules/dnn/src/layers/prior_box_layer.cpp @@ -45,6 +45,7 @@ #include #include #include +#include "opencl_kernels_dnn.hpp" namespace cv { @@ -270,11 +271,108 @@ public: return false; } +#ifdef HAVE_OPENCL + bool forward_ocl(InputArrayOfArrays inps, OutputArrayOfArrays outs, OutputArrayOfArrays internals) + { + std::vector inputs; + std::vector outputs; + + inps.getUMatVector(inputs); + outs.getUMatVector(outputs); + + int _layerWidth = inputs[0].size[3]; + int _layerHeight = inputs[0].size[2]; + + int _imageWidth = inputs[1].size[3]; + int _imageHeight = inputs[1].size[2]; + + float stepX, stepY; + if (_stepX == 0 || _stepY == 0) + { + stepX = static_cast(_imageWidth) / _layerWidth; + stepY = static_cast(_imageHeight) / _layerHeight; + } else { + stepX = _stepX; + stepY = _stepY; + } + + if (umat_offsetsX.empty()) + { + Mat offsetsX(1, _offsetsX.size(), CV_32FC1, &_offsetsX[0]); + Mat offsetsY(1, _offsetsX.size(), CV_32FC1, &_offsetsY[0]); + Mat aspectRatios(1, _aspectRatios.size(), CV_32FC1, &_aspectRatios[0]); + Mat variance(1, _variance.size(), CV_32FC1, &_variance[0]); + + offsetsX.copyTo(umat_offsetsX); + offsetsY.copyTo(umat_offsetsY); + aspectRatios.copyTo(umat_aspectRatios); + variance.copyTo(umat_variance); + + int real_numPriors = _numPriors / pow(2, _offsetsX.size() - 1); + umat_scales = UMat(1, &real_numPriors, CV_32F, 1.0f); + } + + size_t nthreads = _layerHeight * _layerWidth; + + ocl::Kernel kernel("prior_box", ocl::dnn::prior_box_oclsrc); + kernel.set(0, (int)nthreads); + kernel.set(1, (float)stepX); + kernel.set(2, (float)stepY); + kernel.set(3, (float)_minSize); + kernel.set(4, (float)_maxSize); + kernel.set(5, ocl::KernelArg::PtrReadOnly(umat_offsetsX)); + kernel.set(6, ocl::KernelArg::PtrReadOnly(umat_offsetsY)); + kernel.set(7, (int)_offsetsX.size()); + kernel.set(8, ocl::KernelArg::PtrReadOnly(umat_aspectRatios)); + kernel.set(9, (int)_aspectRatios.size()); + kernel.set(10, ocl::KernelArg::PtrReadOnly(umat_scales)); + kernel.set(11, ocl::KernelArg::PtrWriteOnly(outputs[0])); + kernel.set(12, (int)_layerHeight); + kernel.set(13, (int)_layerWidth); + kernel.set(14, (int)_imageHeight); + kernel.set(15, (int)_imageWidth); + kernel.run(1, &nthreads, NULL, false); + + // clip the prior's coordidate such that it is within [0, 1] + if (_clip) + { + Mat mat = outputs[0].getMat(ACCESS_READ); + int aspect_count = (_maxSize > 0) ? 1 : 0; + int offset = nthreads * 4 * _offsetsX.size() * (1 + aspect_count + _aspectRatios.size()); + float* outputPtr = mat.ptr() + offset; + int _outChannelSize = _layerHeight * _layerWidth * _numPriors * 4; + for (size_t d = 0; d < _outChannelSize; ++d) + { + outputPtr[d] = std::min(std::max(outputPtr[d], 0.), 1.); + } + } + + // set the variance. + { + ocl::Kernel kernel("set_variance", ocl::dnn::prior_box_oclsrc); + int offset = total(shape(outputs[0]), 2); + size_t nthreads = _layerHeight * _layerWidth * _numPriors; + kernel.set(0, (int)nthreads); + kernel.set(1, (int)offset); + kernel.set(2, (int)_variance.size()); + kernel.set(3, ocl::KernelArg::PtrReadOnly(umat_variance)); + kernel.set(4, ocl::KernelArg::PtrWriteOnly(outputs[0])); + if (!kernel.run(1, &nthreads, NULL, false)) + return false; + } + return true; + } +#endif + void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays internals_arr) { CV_TRACE_FUNCTION(); CV_TRACE_ARG_VALUE(name, "name", name.c_str()); + CV_OCL_RUN((preferableTarget == DNN_TARGET_OPENCL) && + OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel()), + forward_ocl(inputs_arr, outputs_arr, internals_arr)) + Layer::forward_fallback(inputs_arr, outputs_arr, internals_arr); } @@ -441,6 +539,14 @@ private: std::vector _offsetsX; std::vector _offsetsY; +#ifdef HAVE_OPENCL + UMat umat_offsetsX; + UMat umat_offsetsY; + UMat umat_aspectRatios; + UMat umat_scales; + UMat umat_variance; +#endif + bool _flip; bool _clip; bool _explicitSizes; diff --git a/modules/dnn/src/opencl/prior_box.cl b/modules/dnn/src/opencl/prior_box.cl new file mode 100644 index 0000000..660ccb6 --- /dev/null +++ b/modules/dnn/src/opencl/prior_box.cl @@ -0,0 +1,148 @@ +/*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) 2016-2017 Fabian David Tschopp, 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*/ + +#define Dtype float +#define Dtype4 float4 + +__kernel void prior_box(const int nthreads, + const Dtype stepX, + const Dtype stepY, + const Dtype _minSize, + const Dtype _maxSize, + __global const Dtype* _offsetsX, + __global const Dtype* _offsetsY, + const int offsetsX_size, + __global const Dtype* _aspectRatios, + const int aspectRatios_size, + __global const Dtype* scales, + __global Dtype* dst, + const int _layerHeight, + const int _layerWidth, + const int imgHeight, + const int imgWidth) +{ + for (int index = get_global_id(0); index < nthreads; index += get_global_size(0)) + { + int w = index % _layerWidth; + int h = index / _layerWidth; + __global Dtype* outputPtr; + int aspect_count = (_maxSize > 0) ? 1 : 0; + outputPtr = dst + index * 4 * offsetsX_size * (1 + aspect_count + aspectRatios_size); + + Dtype _boxWidth, _boxHeight; + Dtype4 vec; + _boxWidth = _boxHeight = _minSize * scales[0]; + for (int i = 0; i < offsetsX_size; ++i) + { + float center_x = (w + _offsetsX[i]) * stepX; + float center_y = (h + _offsetsY[i]) * stepY; + + vec.x = (center_x - _boxWidth * 0.5f) / imgWidth; // xmin + vec.y = (center_y - _boxHeight * 0.5f) / imgHeight; // ymin + vec.z = (center_x + _boxWidth * 0.5f) / imgWidth; // xmax + vec.w = (center_y + _boxHeight * 0.5f) / imgHeight; // ymax + vstore4(vec, 0, outputPtr); + + outputPtr += 4; + } + + if (_maxSize > 0) + { + _boxWidth = _boxHeight = native_sqrt(_minSize * _maxSize) * scales[1]; + + for (int i = 0; i < offsetsX_size; ++i) + { + float center_x = (w + _offsetsX[i]) * stepX; + float center_y = (h + _offsetsY[i]) * stepY; + + vec.x = (center_x - _boxWidth * 0.5f) / imgWidth; // xmin + vec.y = (center_y - _boxHeight * 0.5f) / imgHeight; // ymin + vec.z = (center_x + _boxWidth * 0.5f) / imgWidth; // xmax + vec.w = (center_y + _boxHeight * 0.5f) / imgHeight; // ymax + vstore4(vec, 0, outputPtr); + + outputPtr += 4; + } + } + + for (int r = 0; r < aspectRatios_size; ++r) + { + float ar = native_sqrt(_aspectRatios[r]); + float scale = scales[(_maxSize > 0 ? 2 : 1) + r]; + + _boxWidth = _minSize * ar * scale; + _boxHeight = _minSize / ar * scale; + + for (int i = 0; i < offsetsX_size; ++i) + { + float center_x = (w + _offsetsX[i]) * stepX; + float center_y = (h + _offsetsY[i]) * stepY; + + vec.x = (center_x - _boxWidth * 0.5f) / imgWidth; // xmin + vec.y = (center_y - _boxHeight * 0.5f) / imgHeight; // ymin + vec.z = (center_x + _boxWidth * 0.5f) / imgWidth; // xmax + vec.w = (center_y + _boxHeight * 0.5f) / imgHeight; // ymax + vstore4(vec, 0, outputPtr); + + outputPtr += 4; + } + } + } +} + +__kernel void set_variance(const int nthreads, + const int offset, + const int variance_size, + __global const Dtype* variance, + __global Dtype* dst) +{ + for (int index = get_global_id(0); index < nthreads; index += get_global_size(0)) + { + Dtype4 var_vec; + + if (variance_size == 1) + var_vec = (Dtype4)(variance[0]); + else + var_vec = vload4(0, variance); + + vstore4(var_vec, 0, dst + offset + index * 4); + } +}