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OpenCV_4.2.0/opencv_contrib-4.2.0/modules/optflow/test/test_OF_accuracy.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// Intel License Agreement
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#include "test_precomp.hpp"
namespace opencv_test { namespace {
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 calcRMSE(vector<Point2f> prevPts, vector<Point2f> currPts, Mat flow)
{
vector<float> ee;
for (unsigned int n = 0; n < prevPts.size(); n++)
{
Point2f gtFlow = flow.at<Point2f>(prevPts[n]);
if (isFlowCorrect(gtFlow.x) && isFlowCorrect(gtFlow.y))
{
Point2f diffFlow = (currPts[n] - prevPts[n]) - gtFlow;
ee.push_back(sqrt(diffFlow.x * diffFlow.x + diffFlow.y * diffFlow.y));
}
}
return static_cast<float>(mean(ee).val[0]);
}
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)
{
string frame1_path = getRubberWhaleFrame1();
string frame2_path = getRubberWhaleFrame2();
string gt_flow_path = getRubberWhaleGroundTruth();
// removing space may be an issue on windows machines
frame1_path.erase(std::remove_if(frame1_path.begin(), frame1_path.end(), isspace), frame1_path.end());
frame2_path.erase(std::remove_if(frame2_path.begin(), frame2_path.end(), isspace), frame2_path.end());
gt_flow_path.erase(std::remove_if(gt_flow_path.begin(), gt_flow_path.end(), isspace), gt_flow_path.end());
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(SparseOpticalFlow, ReferenceAccuracy)
{
// with the following test each invoker class should be tested once
Mat frame1, frame2, GT;
ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
vector<Point2f> prevPts, currPts;
for (int r = 0; r < frame1.rows; r+=10)
{
for (int c = 0; c < frame1.cols; c+=10)
{
prevPts.push_back(Point2f(static_cast<float>(c), static_cast<float>(r)));
}
}
vector<uchar> status(prevPts.size());
vector<float> err(prevPts.size());
Ptr<SparseRLOFOpticalFlow> algo = SparseRLOFOpticalFlow::create();
algo->setForwardBackward(0.0f);
Ptr<RLOFOpticalFlowParameter> param = Ptr<RLOFOpticalFlowParameter>(new RLOFOpticalFlowParameter);
param->supportRegionType = SR_CROSS;
param->useIlluminationModel = true;
param->solverType = ST_BILINEAR;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.3f);
param->solverType = ST_STANDART;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.34f);
param->useIlluminationModel = false;
param->solverType = ST_BILINEAR;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.27f);
param->solverType = ST_STANDART;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.27f);
param->normSigma0 = numeric_limits<float>::max();
param->normSigma1 = numeric_limits<float>::max();
param->useIlluminationModel = true;
param->solverType = ST_BILINEAR;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.28f);
param->solverType = ST_STANDART;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.28f);
param->useIlluminationModel = false;
param->solverType = ST_BILINEAR;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.80f);
param->solverType = ST_STANDART;
algo->setRLOFOpticalFlowParameter(param);
algo->calc(frame1, frame2, prevPts, currPts, status, err);
EXPECT_LE(calcRMSE(prevPts, currPts, GT), 0.28f);
}
TEST(DenseOpticalFlow_RLOF, ReferenceAccuracy)
{
Mat frame1, frame2, GT;
ASSERT_TRUE(readRubberWhale(frame1, frame2, GT));
Mat flow;
Ptr<DenseRLOFOpticalFlow> algo = DenseRLOFOpticalFlow::create();
Ptr<RLOFOpticalFlowParameter> param = Ptr<RLOFOpticalFlowParameter>(new RLOFOpticalFlowParameter);
param->supportRegionType = SR_CROSS;
param->solverType = ST_BILINEAR;
algo->setRLOFOpticalFlowParameter(param);
algo->setForwardBackward(1.0f);
algo->setGridStep(cv::Size(4, 4));
algo->setInterpolation(INTERP_EPIC);
algo->calc(frame1, frame2, flow);
ASSERT_EQ(GT.rows, flow.rows);
ASSERT_EQ(GT.cols, flow.cols);
EXPECT_LE(calcRMSE(GT, flow), 0.46f);
algo->setInterpolation(INTERP_GEO);
algo->calc(frame1, frame2, flow);
ASSERT_EQ(GT.rows, flow.rows);
ASSERT_EQ(GT.cols, flow.cols);
EXPECT_LE(calcRMSE(GT, flow), 0.55f);
}
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_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);
}
}} // namespace
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