potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-30 15:53:03 +04:00
Code Packages Releases Wiki Activity

removed C API in the following modules: photo, video, imgcodecs, videoio (#13060)

Browse Source 
* removed C API in the following modules: photo, video, imgcodecs, videoio

* trying to fix various compile errors and warnings on Windows and Linux

* continue to fix compile errors and warnings

* continue to fix compile errors, warnings, as well as the test failures

* trying to resolve compile warnings on Android

* Update cap_dc1394_v2.cpp

fix warning from the new GCC
This commit is contained in:
Vadim Pisarevsky
2018-11-09 00:52:09 +03:00
committed by GitHub
parent 5087ff0814
commit 11eafca3e2
34 changed files with 389 additions and 1403 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/video/test/test_kalman.cpp
+22 -35
View File
@@ -40,7 +40,7 @@
//M*/
#include "test_precomp.hpp"
#include "opencv2/video/tracking_c.h"
#include "opencv2/video/tracking.hpp"
namespace opencv_test { namespace {
@@ -67,54 +67,41 @@ void CV_KalmanTest::run( int )
const double EPSILON = 1.000;
RNG& rng = ts->get_rng();
CvKalman* Kalm;
int i, j;
CvMat* Sample = cvCreateMat(Dim,1,CV_32F);
CvMat* Temp = cvCreateMat(Dim,1,CV_32F);
cv::Mat Sample(Dim,1,CV_32F);
cv::Mat Temp(Dim,1,CV_32F);
Kalm = cvCreateKalman(Dim, Dim);
CvMat Dyn = cvMat(Dim,Dim,CV_32F,Kalm->DynamMatr);
CvMat Mes = cvMat(Dim,Dim,CV_32F,Kalm->MeasurementMatr);
CvMat PNC = cvMat(Dim,Dim,CV_32F,Kalm->PNCovariance);
CvMat MNC = cvMat(Dim,Dim,CV_32F,Kalm->MNCovariance);
CvMat PriErr = cvMat(Dim,Dim,CV_32F,Kalm->PriorErrorCovariance);
CvMat PostErr = cvMat(Dim,Dim,CV_32F,Kalm->PosterErrorCovariance);
CvMat PriState = cvMat(Dim,1,CV_32F,Kalm->PriorState);
CvMat PostState = cvMat(Dim,1,CV_32F,Kalm->PosterState);
cvSetIdentity(&PNC);
cvSetIdentity(&PriErr);
cvSetIdentity(&PostErr);
cvSetZero(&MNC);
cvSetZero(&PriState);
cvSetZero(&PostState);
cvSetIdentity(&Mes);
cvSetIdentity(&Dyn);
Mat _Sample = cvarrToMat(Sample);
cvtest::randUni(rng, _Sample, cvScalarAll(-max_init), cvScalarAll(max_init));
cvKalmanCorrect(Kalm, Sample);
cv::KalmanFilter Kalm(Dim, Dim);
Kalm.transitionMatrix = cv::Mat::eye(Dim, Dim, CV_32F);
Kalm.measurementMatrix = cv::Mat::eye(Dim, Dim, CV_32F);
Kalm.processNoiseCov = cv::Mat::eye(Dim, Dim, CV_32F);
Kalm.errorCovPre = cv::Mat::eye(Dim, Dim, CV_32F);
Kalm.errorCovPost = cv::Mat::eye(Dim, Dim, CV_32F);
Kalm.measurementNoiseCov = cv::Mat::zeros(Dim, Dim, CV_32F);
Kalm.statePre = cv::Mat::zeros(Dim, 1, CV_32F);
Kalm.statePost = cv::Mat::zeros(Dim, 1, CV_32F);
cvtest::randUni(rng, Sample, Scalar::all(-max_init), Scalar::all(max_init));
Kalm.correct(Sample);
for(i = 0; i<Steps; i++)
{
cvKalmanPredict(Kalm);
Kalm.predict();
const Mat& Dyn = Kalm.transitionMatrix;
for(j = 0; j<Dim; j++)
{
float t = 0;
for(int k=0; k<Dim; k++)
{
t += Dyn.data.fl[j*Dim+k]*Sample->data.fl[k];
t += Dyn.at<float>(j,k)*Sample.at<float>(k);
}
Temp->data.fl[j]= (float)(t+(cvtest::randReal(rng)*2-1)*max_noise);
Temp.at<float>(j) = (float)(t+(cvtest::randReal(rng)*2-1)*max_noise);
}
cvCopy( Temp, Sample );
cvKalmanCorrect(Kalm,Temp);
Temp.copyTo(Sample);
Kalm.correct(Temp);
}
Mat _state_post = cvarrToMat(Kalm->state_post);
code = cvtest::cmpEps2( ts, _Sample, _state_post, EPSILON, false, "The final estimated state" );
cvReleaseMat(&Sample);
cvReleaseMat(&Temp);
cvReleaseKalman(&Kalm);
Mat _state_post = Kalm.statePost;
code = cvtest::cmpEps2( ts, Sample, _state_post, EPSILON, false, "The final estimated state" );
if( code < 0 )
ts->set_failed_test_info( code );