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