opencv/modules/ocl/perf/perf_ml.cpp

/*M///////////////////////////////////////////////////////////////////////////////////////
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//                           License Agreement
//                For Open Source Computer Vision Library
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
//    Jin Ma, jin@multicorewareinc.com
//    Xiaopeng Fu, fuxiaopeng2222@163.com
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
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#include "perf_precomp.hpp"
using namespace perf;
using namespace std;
using namespace cv::ocl;
using namespace cv;
using std::tr1::tuple;
using std::tr1::get;
////////////////////////////////// K-NEAREST NEIGHBOR ////////////////////////////////////
static void genData(Mat& trainData, Size size, Mat& trainLabel = Mat().setTo(Scalar::all(0)), int nClasses = 0)
{
    trainData.create(size, CV_32FC1);
    randu(trainData, 1.0, 100.0);

    if(nClasses != 0)
    {
        trainLabel.create(size.height, 1, CV_8UC1);
        randu(trainLabel, 0, nClasses - 1);
        trainLabel.convertTo(trainLabel, CV_32FC1);
    }
}

typedef tuple<int> KNNParamType;
typedef TestBaseWithParam<KNNParamType> KNNFixture;

PERF_TEST_P(KNNFixture, KNN,
            testing::Values(1000, 2000, 4000))
{
    KNNParamType params = GetParam();
    const int rows = get<0>(params);
    int columns = 100;
    int k = rows/250;

    Mat trainData, trainLabels;
    Size size(columns, rows);
    genData(trainData, size, trainLabels, 3);

    Mat testData;
    genData(testData, size);
    Mat best_label;

    if(RUN_PLAIN_IMPL)
    {
        TEST_CYCLE()
        {
            CvKNearest knn_cpu;
            knn_cpu.train(trainData, trainLabels);
            knn_cpu.find_nearest(testData, k, &best_label);
        }
    }else if(RUN_OCL_IMPL)
    {
        cv::ocl::oclMat best_label_ocl;
        cv::ocl::oclMat testdata;
        testdata.upload(testData);

        OCL_TEST_CYCLE()
        {
            cv::ocl::KNearestNeighbour knn_ocl;
            knn_ocl.train(trainData, trainLabels);
            knn_ocl.find_nearest(testdata, k, best_label_ocl);
        }
        best_label_ocl.download(best_label);
    }else
        OCL_PERF_ELSE
    SANITY_CHECK(best_label);
}