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https://github.com/opencv/opencv.git
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5df77a841e
remove as much warnings as possible use enum instead of MACRO for ocl.hpp add command line parser in accuracy test and perf test some bug fix for arthim functions
254 lines
8.0 KiB
C++
254 lines
8.0 KiB
C++
/*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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