X-Git-Url: https://vcs.maemo.org/git/?a=blobdiff_plain;f=samples%2Fpython%2Fkalman.py;fp=samples%2Fpython%2Fkalman.py;h=0000000000000000000000000000000000000000;hb=e4c14cdbdf2fe805e79cd96ded236f57e7b89060;hp=fb68cfa4250f781bbada25bafd26fe400749741f;hpb=454138ff8a20f6edb9b65a910101403d8b520643;p=opencv

diff --git a/samples/python/kalman.py b/samples/python/kalman.py
deleted file mode 100755
index fb68cfa..0000000
--- a/samples/python/kalman.py
+++ /dev/null
@@ -1,92 +0,0 @@
-#!/usr/bin/python
-""" 
-   Tracking of rotating point.
-   Rotation speed is constant.
-   Both state and measurements vectors are 1D (a point angle),
-   Measurement is the real point angle + gaussian noise.
-   The real and the estimated points are connected with yellow line segment,
-   the real and the measured points are connected with red line segment.
-   (if Kalman filter works correctly,
-    the yellow segment should be shorter than the red one).
-   Pressing any key (except ESC) will reset the tracking with a different speed.
-   Pressing ESC will stop the program.
-"""
-from opencv.cv import *
-from opencv.highgui import *
-from math import cos, sin, sqrt
-
-if __name__ == "__main__":
-    A = [ [1, 1], [0, 1] ];
-    
-    img = cvCreateImage( cvSize(500,500), 8, 3 );
-    kalman = cvCreateKalman( 2, 1, 0 );
-    state = cvCreateMat( 2, 1, CV_32FC1 );  # (phi, delta_phi)
-    process_noise = cvCreateMat( 2, 1, CV_32FC1 );
-    measurement = cvCreateMat( 1, 1, CV_32FC1 );
-    rng = cvRNG(-1);
-    code = -1;
-
-    cvZero( measurement );
-    cvNamedWindow( "Kalman", 1 );
-
-    while True:
-        cvRandArr( rng, state, CV_RAND_NORMAL, cvRealScalar(0), cvRealScalar(0.1) );
-        
-        kalman.transition_matrix[:] = A;
-        cvSetIdentity( kalman.measurement_matrix, cvRealScalar(1) );
-        cvSetIdentity( kalman.process_noise_cov, cvRealScalar(1e-5) );
-        cvSetIdentity( kalman.measurement_noise_cov, cvRealScalar(1e-1) );
-        cvSetIdentity( kalman.error_cov_post, cvRealScalar(1));
-        cvRandArr( rng, kalman.state_post, CV_RAND_NORMAL, cvRealScalar(0), cvRealScalar(0.1) );
-        
-        while True:
-            def calc_point(angle):
-                return cvPoint( cvRound(img.width/2 + img.width/3*cos(angle)),
-                         cvRound(img.height/2 - img.width/3*sin(angle))) 
-
-            state_angle = state[0] 
-            state_pt = calc_point(state_angle);
-            
-            prediction = cvKalmanPredict( kalman );
-            predict_angle = prediction[0,0] 
-            predict_pt = calc_point(predict_angle);
-
-            cvRandArr( rng, measurement, CV_RAND_NORMAL, cvRealScalar(0),
-                       cvRealScalar(sqrt(kalman.measurement_noise_cov[0,0])) );
-
-            # generate measurement 
-            cvMatMulAdd( kalman.measurement_matrix, state, measurement, measurement );
-
-            measurement_angle = measurement[0,0];
-            measurement_pt = calc_point(measurement_angle);
-            
-            # plot points 
-            def draw_cross( center, color, d ):                                 
-                cvLine( img, cvPoint( center.x - d, center.y - d ),                
-                             cvPoint( center.x + d, center.y + d ), color, 1, CV_AA, 0); 
-                cvLine( img, cvPoint( center.x + d, center.y - d ),                
-                             cvPoint( center.x - d, center.y + d ), color, 1, CV_AA, 0 )
-
-            cvZero( img );
-            draw_cross( state_pt, CV_RGB(255,255,255), 3 );
-            draw_cross( measurement_pt, CV_RGB(255,0,0), 3 );
-            draw_cross( predict_pt, CV_RGB(0,255,0), 3 );
-            cvLine( img, state_pt, measurement_pt, CV_RGB(255,0,0), 3, CV_AA, 0 );
-            cvLine( img, state_pt, predict_pt, CV_RGB(255,255,0), 3, CV_AA, 0 );
-            
-            cvKalmanCorrect( kalman, measurement );
-
-            cvRandArr( rng, process_noise, CV_RAND_NORMAL, cvRealScalar(0),
-                       cvRealScalar(sqrt(kalman.process_noise_cov[0,0])));
-            cvMatMulAdd( kalman.transition_matrix, state, process_noise, state );
-
-            cvShowImage( "Kalman", img );
-            code = cvWaitKey( 100 );
-            
-            if( code > 0 ):
-                break;
-            
-        if( code == '\x1b' or code == 'q' or code == 'Q' ):
-            break;
-    
-    cvDestroyWindow("Kalman");