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#include "test_precomp.hpp"
#include <fstream>

using namespace std;
using namespace cv;
using namespace cvtest;
using namespace optflow;

static string getDataDir() { return TS::ptr()->get_data_path(); }

static string getRubberWhaleFrame1() { return getDataDir() + "optflow/RubberWhale1.png"; }

static string getRubberWhaleFrame2() { return getDataDir() + "optflow/RubberWhale2.png"; }

static string getRubberWhaleGroundTruth() { return getDataDir() + "optflow/RubberWhale.flo"; }

static bool isFlowCorrect(float u) { return !cvIsNaN(u) && (fabs(u) < 1e9); }

static bool isFlowCorrect(double u) { return !cvIsNaN(u) && (fabs(u) < 1e9); }

static float calcRMSE(Mat flow1, Mat flow2)
{
    float sum = 0;
    int counter = 0;
    const int rows = flow1.rows;
    const int cols = flow1.cols;

    for (int y = 0; y < rows; ++y)
    {
        for (int x = 0; x < cols; ++x)
        {
            Vec2f flow1_at_point = flow1.at<Vec2f>(y, x);
            Vec2f flow2_at_point = flow2.at<Vec2f>(y, x);

            float u1 = flow1_at_point[0];
            float v1 = flow1_at_point[1];
            float u2 = flow2_at_point[0];
            float v2 = flow2_at_point[1];

            if (isFlowCorrect(u1) && isFlowCorrect(u2) && isFlowCorrect(v1) && isFlowCorrect(v2))
            {
                sum += (u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2);
                counter++;
            }
        }
    }
    return (float)sqrt(sum / (1e-9 + counter));
}

static float calcAvgEPE(vector< pair<Point2i, Point2i> > corr, Mat flow)
{
    double sum = 0;
    int counter = 0;

    for (size_t i = 0; i < corr.size(); ++i)
    {
        Vec2f flow1_at_point = Point2f(corr[i].second - corr[i].first);
        Vec2f flow2_at_point = flow.at<Vec2f>(corr[i].first.y, corr[i].first.x);

        double u1 = (double)flow1_at_point[0];
        double v1 = (double)flow1_at_point[1];
        double u2 = (double)flow2_at_point[0];
        double v2 = (double)flow2_at_point[1];

        if (isFlowCorrect(u1) && isFlowCorrect(u2) && isFlowCorrect(v1) && isFlowCorrect(v2))
        {
            sum += sqrt((u1 - u2) * (u1 - u2) + (v1 - v2) * (v1 - v2));
            counter++;
        }
    }

    return (float)(sum / counter);
}

bool readRubberWhale(Mat &dst_frame_1, Mat &dst_frame_2, Mat &dst_GT)
{
    const string frame1_path = getRubberWhaleFrame1();
    const string frame2_path = getRubberWhaleFrame2();
    const string gt_flow_path = getRubberWhaleGroundTruth();

    dst_frame_1 = imread(frame1_path);
    dst_frame_2 = imread(frame2_path);
    dst_GT = readOpticalFlow(gt_flow_path);

    if (dst_frame_1.empty() || dst_frame_2.empty() || dst_GT.empty())
        return false;
    else
        return true;
}

TEST(DenseOpticalFlow_SimpleFlow, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    float target_RMSE = 0.37f;

    Mat flow;
    Ptr<DenseOpticalFlow> algo;
    algo = createOptFlow_SimpleFlow();
    algo->calc(frame1, frame2, flow);
    ASSERT_EQ(GT.rows, flow.rows);
    ASSERT_EQ(GT.cols, flow.cols);
    EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}

TEST(DenseOpticalFlow_DeepFlow, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    float target_RMSE = 0.35f;
    cvtColor(frame1, frame1, COLOR_BGR2GRAY);
    cvtColor(frame2, frame2, COLOR_BGR2GRAY);

    Mat flow;
    Ptr<DenseOpticalFlow> algo;
    algo = createOptFlow_DeepFlow();
    algo->calc(frame1, frame2, flow);
    ASSERT_EQ(GT.rows, flow.rows);
    ASSERT_EQ(GT.cols, flow.cols);
    EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}

TEST(DenseOpticalFlow_SparseToDenseFlow, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    float target_RMSE = 0.52f;

    Mat flow;
    Ptr<DenseOpticalFlow> algo;
    algo = createOptFlow_SparseToDense();
    algo->calc(frame1, frame2, flow);
    ASSERT_EQ(GT.rows, flow.rows);
    ASSERT_EQ(GT.cols, flow.cols);
    EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}

TEST(DenseOpticalFlow_DIS, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    int presets[] = {DISOpticalFlow::PRESET_ULTRAFAST, DISOpticalFlow::PRESET_FAST, DISOpticalFlow::PRESET_MEDIUM};
    float target_RMSE[] = {0.86f, 0.74f, 0.49f};
    cvtColor(frame1, frame1, COLOR_BGR2GRAY);
    cvtColor(frame2, frame2, COLOR_BGR2GRAY);

    Ptr<DenseOpticalFlow> algo;

    // iterate over presets:
    for (int i = 0; i < 3; i++)
    {
        Mat flow;
        algo = createOptFlow_DIS(presets[i]);
        algo->calc(frame1, frame2, flow);
        ASSERT_EQ(GT.rows, flow.rows);
        ASSERT_EQ(GT.cols, flow.cols);
        EXPECT_LE(calcRMSE(GT, flow), target_RMSE[i]);
    }
}

TEST(DenseOpticalFlow_VariationalRefinement, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    float target_RMSE = 0.86f;
    cvtColor(frame1, frame1, COLOR_BGR2GRAY);
    cvtColor(frame2, frame2, COLOR_BGR2GRAY);

    Ptr<VariationalRefinement> var_ref;
    var_ref = createVariationalFlowRefinement();
    var_ref->setAlpha(20.0f);
    var_ref->setDelta(5.0f);
    var_ref->setGamma(10.0f);
    var_ref->setSorIterations(25);
    var_ref->setFixedPointIterations(25);
    Mat flow(frame1.size(), CV_32FC2);
    flow.setTo(0.0f);
    var_ref->calc(frame1, frame2, flow);
    ASSERT_EQ(GT.rows, flow.rows);
    ASSERT_EQ(GT.cols, flow.cols);
    EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}

TEST(DenseOpticalFlow_PCAFlow, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
    const float target_RMSE = 0.55f;

    Mat flow;
    Ptr<DenseOpticalFlow> algo = createOptFlow_PCAFlow();
    algo->calc(frame1, frame2, flow);
    ASSERT_EQ(GT.rows, flow.rows);
    ASSERT_EQ(GT.cols, flow.cols);
    EXPECT_LE(calcRMSE(GT, flow), target_RMSE);
}

TEST(DenseOpticalFlow_GlobalPatchColliderDCT, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));

    const Size sz = frame1.size() / 2;
    frame1 = frame1(Rect(0, 0, sz.width, sz.height));
    frame2 = frame2(Rect(0, 0, sz.width, sz.height));
    GT = GT(Rect(0, 0, sz.width, sz.height));

    vector<Mat> img1, img2, gt;
    vector< pair<Point2i, Point2i> > corr;
    img1.push_back(frame1);
    img2.push_back(frame2);
    gt.push_back(GT);

    Ptr< GPCForest<5> > forest = GPCForest<5>::create();
    forest->train(img1, img2, gt, GPCTrainingParams(8, 3, GPC_DESCRIPTOR_DCT, false));
    forest->findCorrespondences(frame1, frame2, corr);

    ASSERT_LE(7500U, corr.size());
    ASSERT_LE(calcAvgEPE(corr, GT), 0.5f);
}

TEST(DenseOpticalFlow_GlobalPatchColliderWHT, ReferenceAccuracy)
{
    Mat frame1, frame2, GT;
    ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));

    const Size sz = frame1.size() / 2;
    frame1 = frame1(Rect(0, 0, sz.width, sz.height));
    frame2 = frame2(Rect(0, 0, sz.width, sz.height));
    GT = GT(Rect(0, 0, sz.width, sz.height));

    vector<Mat> img1, img2, gt;
    vector< pair<Point2i, Point2i> > corr;
    img1.push_back(frame1);
    img2.push_back(frame2);
    gt.push_back(GT);

    Ptr< GPCForest<5> > forest = GPCForest<5>::create();
    forest->train(img1, img2, gt, GPCTrainingParams(8, 3, GPC_DESCRIPTOR_WHT, false));
    forest->findCorrespondences(frame1, frame2, corr);

    ASSERT_LE(7000U, corr.size());
    ASSERT_LE(calcAvgEPE(corr, GT), 0.5f);
}
