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Open Source Computer Vision Library
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253 lines
8.0 KiB
253 lines
8.0 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
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// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// Intel License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved. |
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// @Authors |
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// Wenju He, wenju@multicorewareinc.com |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of Intel Corporation may not be used to endorse or promote products |
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// derived from this software without specific prior written permission. |
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// |
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// This software is provided by the copyright holders and contributors "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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//M*/ |
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#include "precomp.hpp" |
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#include "opencv2/core/core.hpp" |
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using namespace std; |
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#ifdef HAVE_OPENCL |
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extern string workdir; |
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PARAM_TEST_CASE(HOG, cv::Size, int) |
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{ |
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cv::Size winSize; |
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int type; |
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virtual void SetUp() |
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{ |
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winSize = GET_PARAM(0); |
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type = GET_PARAM(1); |
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} |
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}; |
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TEST_P(HOG, GetDescriptors) |
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{ |
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// Load image |
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cv::Mat img_rgb = readImage(workdir + "lena.jpg"); |
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ASSERT_FALSE(img_rgb.empty()); |
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// Convert image |
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cv::Mat img; |
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switch (type) |
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{ |
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case CV_8UC1: |
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cv::cvtColor(img_rgb, img, CV_BGR2GRAY); |
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break; |
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case CV_8UC4: |
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default: |
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cv::cvtColor(img_rgb, img, CV_BGR2BGRA); |
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break; |
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} |
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cv::ocl::oclMat d_img(img); |
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// HOGs |
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cv::ocl::HOGDescriptor ocl_hog; |
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ocl_hog.gamma_correction = true; |
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cv::HOGDescriptor hog; |
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hog.gammaCorrection = true; |
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// Compute descriptor |
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cv::ocl::oclMat d_descriptors; |
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ocl_hog.getDescriptors(d_img, ocl_hog.win_size, d_descriptors, ocl_hog.DESCR_FORMAT_COL_BY_COL); |
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cv::Mat down_descriptors; |
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d_descriptors.download(down_descriptors); |
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down_descriptors = down_descriptors.reshape(0, down_descriptors.cols * down_descriptors.rows); |
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hog.setSVMDetector(hog.getDefaultPeopleDetector()); |
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std::vector<float> descriptors; |
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switch (type) |
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{ |
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case CV_8UC1: |
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hog.compute(img, descriptors, ocl_hog.win_size); |
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break; |
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case CV_8UC4: |
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default: |
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hog.compute(img_rgb, descriptors, ocl_hog.win_size); |
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break; |
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} |
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cv::Mat cpu_descriptors(descriptors); |
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EXPECT_MAT_SIMILAR(down_descriptors, cpu_descriptors, 1e-2); |
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} |
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bool match_rect(cv::Rect r1, cv::Rect r2, int threshold) |
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{ |
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return ((abs(r1.x - r2.x) < threshold) && (abs(r1.y - r2.y) < threshold) && |
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(abs(r1.width - r2.width) < threshold) && (abs(r1.height - r2.height) < threshold)); |
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} |
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TEST_P(HOG, Detect) |
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{ |
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// Load image |
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cv::Mat img_rgb = readImage(workdir + "lena.jpg"); |
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ASSERT_FALSE(img_rgb.empty()); |
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// Convert image |
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cv::Mat img; |
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switch (type) |
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{ |
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case CV_8UC1: |
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cv::cvtColor(img_rgb, img, CV_BGR2GRAY); |
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break; |
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case CV_8UC4: |
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default: |
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cv::cvtColor(img_rgb, img, CV_BGR2BGRA); |
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break; |
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} |
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cv::ocl::oclMat d_img(img); |
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// HOGs |
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if ((winSize != cv::Size(48, 96)) && (winSize != cv::Size(64, 128))) |
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winSize = cv::Size(64, 128); |
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cv::ocl::HOGDescriptor ocl_hog(winSize); |
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ocl_hog.gamma_correction = true; |
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cv::HOGDescriptor hog; |
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hog.winSize = winSize; |
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hog.gammaCorrection = true; |
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if (winSize.width == 48 && winSize.height == 96) |
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{ |
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// daimler's base |
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ocl_hog.setSVMDetector(ocl_hog.getPeopleDetector48x96()); |
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hog.setSVMDetector(hog.getDaimlerPeopleDetector()); |
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} |
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else if (winSize.width == 64 && winSize.height == 128) |
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{ |
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ocl_hog.setSVMDetector(ocl_hog.getPeopleDetector64x128()); |
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hog.setSVMDetector(hog.getDefaultPeopleDetector()); |
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} |
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else |
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{ |
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ocl_hog.setSVMDetector(ocl_hog.getDefaultPeopleDetector()); |
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hog.setSVMDetector(hog.getDefaultPeopleDetector()); |
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} |
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// OpenCL detection |
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std::vector<cv::Rect> d_found; |
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ocl_hog.detectMultiScale(d_img, d_found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2); |
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// CPU detection |
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std::vector<cv::Rect> found; |
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switch (type) |
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{ |
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case CV_8UC1: |
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hog.detectMultiScale(img, found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2); |
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break; |
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case CV_8UC4: |
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default: |
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hog.detectMultiScale(img_rgb, found, 0, cv::Size(8, 8), cv::Size(0, 0), 1.05, 2); |
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break; |
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} |
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// Ground-truth rectangular people window |
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cv::Rect win1_64x128(231, 190, 72, 144); |
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cv::Rect win2_64x128(621, 156, 97, 194); |
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cv::Rect win1_48x96(238, 198, 63, 126); |
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cv::Rect win2_48x96(619, 161, 92, 185); |
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cv::Rect win3_48x96(488, 136, 56, 112); |
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// Compare whether ground-truth windows are detected and compare the number of windows detected. |
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std::vector<int> d_comp(4); |
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std::vector<int> comp(4); |
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for(int i = 0; i < (int)d_comp.size(); i++) |
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{ |
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d_comp[i] = 0; |
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comp[i] = 0; |
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} |
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int threshold = 10; |
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int val = 32; |
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d_comp[0] = d_found.size(); |
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comp[0] = found.size(); |
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if (winSize == cv::Size(48, 96)) |
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{ |
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for(int i = 0; i < (int)d_found.size(); i++) |
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{ |
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if (match_rect(d_found[i], win1_48x96, threshold)) |
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d_comp[1] = val; |
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if (match_rect(d_found[i], win2_48x96, threshold)) |
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d_comp[2] = val; |
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if (match_rect(d_found[i], win3_48x96, threshold)) |
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d_comp[3] = val; |
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} |
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for(int i = 0; i < (int)found.size(); i++) |
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{ |
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if (match_rect(found[i], win1_48x96, threshold)) |
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comp[1] = val; |
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if (match_rect(found[i], win2_48x96, threshold)) |
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comp[2] = val; |
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if (match_rect(found[i], win3_48x96, threshold)) |
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comp[3] = val; |
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} |
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} |
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else if (winSize == cv::Size(64, 128)) |
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{ |
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for(int i = 0; i < (int)d_found.size(); i++) |
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{ |
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if (match_rect(d_found[i], win1_64x128, threshold)) |
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d_comp[1] = val; |
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if (match_rect(d_found[i], win2_64x128, threshold)) |
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d_comp[2] = val; |
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} |
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for(int i = 0; i < (int)found.size(); i++) |
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{ |
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if (match_rect(found[i], win1_64x128, threshold)) |
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comp[1] = val; |
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if (match_rect(found[i], win2_64x128, threshold)) |
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comp[2] = val; |
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} |
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} |
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char s[100] = {0}; |
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EXPECT_MAT_NEAR(cv::Mat(d_comp), cv::Mat(comp), 3, s); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, HOG, testing::Combine( |
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testing::Values(cv::Size(64, 128), cv::Size(48, 96)), |
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)))); |
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#endif //HAVE_OPENCL
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