Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#include <string>
using namespace std;
/* ///////////////////// simpleflow_test ///////////////////////// */
class CV_SimpleFlowTest : public cvtest::BaseTest
{
public:
CV_SimpleFlowTest();
protected:
void run(int);
};
CV_SimpleFlowTest::CV_SimpleFlowTest() {}
static bool readOpticalFlowFromFile(FILE* file, cv::Mat& flow) {
char header[5];
if (fread(header, 1, 4, file) < 4 && (string)header != "PIEH") {
return false;
}
int cols, rows;
if (fread(&cols, sizeof(int), 1, file) != 1||
fread(&rows, sizeof(int), 1, file) != 1) {
return false;
}
flow = cv::Mat::zeros(rows, cols, CV_32FC2);
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
cv::Vec2f flow_at_point;
if (fread(&(flow_at_point[0]), sizeof(float), 1, file) != 1 ||
fread(&(flow_at_point[1]), sizeof(float), 1, file) != 1) {
return false;
}
flow.at<cv::Vec2f>(i, j) = flow_at_point;
}
}
return true;
}
static bool isFlowCorrect(float u) {
return !cvIsNaN(u) && (fabs(u) < 1e9);
}
static float calc_rmse(cv::Mat flow1, cv::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) {
cv::Vec2f flow1_at_point = flow1.at<cv::Vec2f>(y, x);
cv::Vec2f flow2_at_point = flow2.at<cv::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));
}
void CV_SimpleFlowTest::run(int) {
const float MAX_RMSE = 0.6f;
const string frame1_path = ts->get_data_path() + "optflow/RubberWhale1.png";
const string frame2_path = ts->get_data_path() + "optflow/RubberWhale2.png";
const string gt_flow_path = ts->get_data_path() + "optflow/RubberWhale.flo";
cv::Mat frame1 = cv::imread(frame1_path);
cv::Mat frame2 = cv::imread(frame2_path);
if (frame1.empty()) {
ts->printf(cvtest::TS::LOG, "could not read image %s\n", frame2_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
if (frame2.empty()) {
ts->printf(cvtest::TS::LOG, "could not read image %s\n", frame2_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
if (frame1.rows != frame2.rows && frame1.cols != frame2.cols) {
ts->printf(cvtest::TS::LOG, "images should be of equal sizes (%s and %s)",
frame1_path.c_str(), frame2_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
if (frame1.type() != 16 || frame2.type() != 16) {
ts->printf(cvtest::TS::LOG, "images should be of equal type CV_8UC3 (%s and %s)",
frame1_path.c_str(), frame2_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
cv::Mat flow_gt;
FILE* gt_flow_file = fopen(gt_flow_path.c_str(), "rb");
if (gt_flow_file == NULL) {
ts->printf(cvtest::TS::LOG, "could not read ground-thuth flow from file %s",
gt_flow_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
if (!readOpticalFlowFromFile(gt_flow_file, flow_gt)) {
ts->printf(cvtest::TS::LOG, "error while reading flow data from file %s",
gt_flow_path.c_str());
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
return;
}
fclose(gt_flow_file);
cv::Mat flow;
cv::calcOpticalFlowSF(frame1, frame2, flow, 3, 2, 4);
float rmse = calc_rmse(flow_gt, flow);
ts->printf(cvtest::TS::LOG, "Optical flow estimation RMSE for SimpleFlow algorithm : %lf\n",
rmse);
if (rmse > MAX_RMSE) {
ts->printf( cvtest::TS::LOG,
"Too big rmse error : %lf ( >= %lf )\n", rmse, MAX_RMSE);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
return;
}
}
TEST(Video_OpticalFlowSimpleFlow, accuracy) { CV_SimpleFlowTest test; test.safe_run(); }
/* End of file. */