perf test
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								modules/objdetect/perf/opencl/perf_hogdetect.cpp
									
									
									
									
									
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								modules/objdetect/perf/opencl/perf_hogdetect.cpp
									
									
									
									
									
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/*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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//                           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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//    Fangfang Bai, fangfang@multicorewareinc.com
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//    Jin Ma,       jin@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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//   * The name of the copyright holders 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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// This software is provided by the copyright holders and contributors as is and
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//M*/
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#include "perf_precomp.hpp"
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#include "opencv2/ts/ocl_perf.hpp"
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#ifdef HAVE_OPENCL
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namespace cvtest {
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namespace ocl {
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///////////// HOG////////////////////////
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struct RectLess :
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        public std::binary_function<cv::Rect, cv::Rect, bool>
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{
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    bool operator()(const cv::Rect& a,
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        const cv::Rect& b) const
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    {
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        if (a.x != b.x)
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            return a.x < b.x;
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        else if (a.y != b.y)
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            return a.y < b.y;
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        else if (a.width != b.width)
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            return a.width < b.width;
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        else
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            return a.height < b.height;
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    }
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};
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OCL_PERF_TEST(HOGFixture, HOG)
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{
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    UMat src;
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    imread(getDataPath("gpu/hog/road.png"), cv::IMREAD_GRAYSCALE).copyTo(src);
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    CV_Assert(!src.empty());
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    vector<cv::Rect> found_locations;
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    declare.in(src).time(5);
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    HOGDescriptor hog;
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    hog.setSVMDetector(hog.getDefaultPeopleDetector());
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    OCL_TEST_CYCLE() hog.detectMultiScale(src, found_locations);
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    std::sort(found_locations.begin(), found_locations.end(), RectLess());
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//    SANITY_CHECK(found_locations, 1 + DBL_EPSILON);
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}
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}
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}
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#endif
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@@ -1377,7 +1377,7 @@ void HOGDescriptor::compute(InputArray _img, std::vector<float>& descriptors,
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    padding.height = (int)alignSize(std::max(padding.height, 0), cacheStride.height);
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    Size paddedImgSize(imgSize.width + padding.width*2, imgSize.height + padding.height*2);
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    if(ocl::useOpenCL() && _img.dims() <= 2 && _img.type() == CV_8UC1 && _img.isUMat() && 
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    if(ocl::useOpenCL() && _img.dims() <= 2 && _img.type() == CV_8UC1 && _img.isUMat() &&
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        ocl_compute(_img, winStride, descriptors, DESCR_FORMAT_COL_BY_COL))
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        return;
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@@ -1713,7 +1713,7 @@ bool HOGDescriptor::ocl_detect(const UMat& img, std::vector<Point> &hits,
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        effect_size.width, block_hists, (float)L2HysThreshold)) return false;
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    size_t descriptor_size = getDescriptorSize();
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    float free_coef = free_coef = svmDetector.size() > descriptor_size ? svmDetector[descriptor_size] : 0;
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    float free_coef = svmDetector.size() > descriptor_size ? svmDetector[descriptor_size] : 0;
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    Size blocks_per_win = numPartsWithin(winSize, blockSize, blockStride);
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@@ -59,7 +59,7 @@ namespace cvtest {
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namespace ocl {
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///////////////////// HOG /////////////////////////////
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    PARAM_TEST_CASE(HOG, Size, MatType)
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PARAM_TEST_CASE(HOG, Size, MatType)
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{
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    Size winSize;
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    int type;
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@@ -69,7 +69,7 @@ namespace ocl {
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    {
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        winSize = GET_PARAM(0);
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        type = GET_PARAM(1);
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        img = readImage("C:/opencv_extra/testdata/gpu/hog/road.png", IMREAD_GRAYSCALE);
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        img = readImage("cascadeandhog/images/image_00000000_0.png", IMREAD_GRAYSCALE);
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        ASSERT_FALSE(img.empty());
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        img.copyTo(uimg);
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    }
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@@ -90,7 +90,7 @@ OCL_TEST_P(HOG, GetDescriptors)
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    Mat cpu_desc(cpu_descriptors), gpu_desc(gpu_descriptors);
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    EXPECT_MAT_SIMILAR(cpu_desc, gpu_desc, 1e-2);
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    EXPECT_MAT_SIMILAR(cpu_desc, gpu_desc, 1e-1);
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}
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OCL_TEST_P(HOG, Detect)
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@@ -110,6 +110,20 @@ OCL_TEST_P(HOG, Detect)
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    OCL_OFF(hog.detectMultiScale(img, cpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
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    OCL_ON(hog.detectMultiScale(uimg, gpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
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    for (size_t i = 0; i < cpu_found.size(); i++)
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    {
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        Rect r = cpu_found[i];
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        rectangle(img, r.tl(), r.br(), Scalar(0, 255, 0), 3);
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    }
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    imshow("cpu", img);
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    Mat imgs(img);
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    for (size_t i = 0; i < gpu_found.size(); i++)
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    {
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        Rect r = cpu_found[i];
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        rectangle(imgs, r.tl(), r.br(), Scalar(0, 255, 0), 3);
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    }
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    imshow("gpu", imgs);
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    waitKey(0);
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    EXPECT_LT(checkRectSimilarity(img.size(), cpu_found, gpu_found), 1.0);
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}
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