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//                For Open Source Computer Vision Library
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//    Matthias Bady aegirxx ==> gmail.com
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#include "test_precomp.hpp"

using namespace std;
using namespace cv;
using namespace ocl;

#ifdef HAVE_OPENCL

namespace
{
IMPLEMENT_PARAM_CLASS( BRIEF_Bytes, int )
}

PARAM_TEST_CASE( BRIEF, BRIEF_Bytes )
{
    int bytes;

    virtual void SetUp( )
    {
        bytes = GET_PARAM( 0 );
    }
};

OCL_TEST_P( BRIEF, Accuracy )
{
    Mat img = readImage( "gpu/opticalflow/rubberwhale1.png", IMREAD_GRAYSCALE );
    ASSERT_TRUE( !img.empty( ) ) << "no input image";

    FastFeatureDetector fast( 20 );
    std::vector<KeyPoint> keypoints;
    fast.detect( img, keypoints, Mat( ) );

    Mat descriptorsGold;
    BriefDescriptorExtractor brief( bytes );
    brief.compute( img, keypoints, descriptorsGold );

    Mat kpMat( 2, int( keypoints.size() ), CV_32FC1 );
    for ( int i = 0, size = (int)keypoints.size( ); i < size; ++i )
    {
        kpMat.col( i ).row( 0 ) = int( keypoints[i].pt.x );
        kpMat.col( i ).row( 1 ) = int( keypoints[i].pt.y );
    }
    oclMat imgOcl( img ), keypointsOcl( kpMat ), descriptorsOcl, maskOcl;

    BRIEF_OCL briefOcl( bytes );
    briefOcl.compute( imgOcl, keypointsOcl, maskOcl, descriptorsOcl );
    Mat mask, descriptors;
    maskOcl.download( mask );
    descriptorsOcl.download( descriptors );

    const int numDesc = cv::countNonZero( mask );
    if ( numDesc != descriptors.cols )
    {
        int idx = 0;
        Mat tmp( numDesc, bytes, CV_8UC1 );
        for ( int i = 0; i < descriptors.rows; ++i )
        {
            if ( mask.at<uchar>(i) )
            {
                descriptors.row( i ).copyTo( tmp.row( idx++ ) );
            }
        }
        descriptors = tmp;
    }
    ASSERT_TRUE( descriptors.size( ) == descriptorsGold.size( ) ) << "Different number of descriptors";
    ASSERT_TRUE( 0 == norm( descriptors, descriptorsGold, NORM_HAMMING ) ) << "Descriptors different";
}

INSTANTIATE_TEST_CASE_P( OCL_Features2D, BRIEF, testing::Values( 16, 32, 64 ) );
#endif