mirror of
https://github.com/opencv/opencv.git
synced 2024-12-12 07:09:12 +08:00
93 lines
3.7 KiB
Python
93 lines
3.7 KiB
Python
|
#!/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 = -1L
|
||
|
|
||
|
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 = str(cvWaitKey( 100 ))
|
||
|
if( code != '-1'):
|
||
|
break
|
||
|
|
||
|
if( code == '\x1b' or code == 'q' or code == 'Q' ):
|
||
|
break
|
||
|
|
||
|
cvDestroyWindow("Kalman")
|