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//                For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// @Authors
//    Peng Xiao, pengxiao@multicorewareinc.com
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#include "precomp.hpp"

#ifdef HAVE_OPENCL
////////////////////////////////////////////////////////////////////////////////
// MatchTemplate
#define ALL_TEMPLATE_METHODS testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR), TemplateMethod(cv::TM_CCOEFF), TemplateMethod(cv::TM_SQDIFF_NORMED), TemplateMethod(cv::TM_CCORR_NORMED), TemplateMethod(cv::TM_CCOEFF_NORMED))

IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size);

const char *TEMPLATE_METHOD_NAMES[6] = {"TM_SQDIFF", "TM_SQDIFF_NORMED", "TM_CCORR", "TM_CCORR_NORMED", "TM_CCOEFF", "TM_CCOEFF_NORMED"};

#define MTEMP_SIZES testing::Values(cv::Size(128, 256), cv::Size(1024, 768))

PARAM_TEST_CASE(MatchTemplate8U, cv::Size, TemplateSize, Channels, TemplateMethod)
{
    cv::Size size;
    cv::Size templ_size;
    int cn;
    int method;
    //std::vector<cv::ocl::Info> oclinfo;

    virtual void SetUp()
    {
        size = GET_PARAM(0);
        templ_size = GET_PARAM(1);
        cn = GET_PARAM(2);
        method = GET_PARAM(3);
        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
    }
};

TEST_P(MatchTemplate8U, Accuracy)
{

    std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
    std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
    std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")" << std::endl;
    std::cout << "Channels: " << cn << std::endl;

    cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn));
    cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_8U, cn));

    cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ);
    cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);

    cv::Mat dst_gold;
    cv::matchTemplate(image, templ, dst_gold, method);

    char sss [100] = "";

    cv::Mat mat_dst;
    dst.download(mat_dst);

    EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
}

PARAM_TEST_CASE(MatchTemplate32F, cv::Size, TemplateSize, Channels, TemplateMethod)
{
    cv::Size size;
    cv::Size templ_size;
    int cn;
    int method;
    //std::vector<cv::ocl::Info> oclinfo;

    virtual void SetUp()
    {
        size = GET_PARAM(0);
        templ_size = GET_PARAM(1);
        cn = GET_PARAM(2);
        method = GET_PARAM(3);
        //int devnums = getDevice(oclinfo, OPENCV_DEFAULT_OPENCL_DEVICE);
        //CV_Assert(devnums > 0);
    }
};

TEST_P(MatchTemplate32F, Accuracy)
{
    cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn));
    cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn));

    cv::ocl::oclMat dst, ocl_image(image), ocl_templ(templ);
    cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);

    cv::Mat dst_gold;
    cv::matchTemplate(image, templ, dst_gold, method);

    char sss [100] = "";

    cv::Mat mat_dst;
    dst.download(mat_dst);

    EXPECT_MAT_NEAR(dst_gold, mat_dst, templ_size.area() * 1e-1, sss);
}

INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U,
                        testing::Combine(
                            MTEMP_SIZES,
                            testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
                            testing::Values(Channels(1), Channels(3), Channels(4)),
                            ALL_TEMPLATE_METHODS
                        )
                       );

INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
                            MTEMP_SIZES,
                            testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
                            testing::Values(Channels(1), Channels(3), Channels(4)),
                            testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));
#endif