Exemplo n.º 1
0
def main(args):
    assert args.path_to_video is not None
    KFilter = KalmanFilter(args.Q, args.R)
    MAnly = MotionAnalyzer(args.path_to_video)
    Vcorr = VideoCorrector(args.path_to_video)

    Tx, Ty, _ = MAnly.process()
    res_x, res_y = KFilter.filter(Tx), KFilter.filter(Ty)
    delta_x = np.array(Tx) - np.array(res_x)
    delta_y = np.array(Ty) - np.array(res_x)
    Vcorr.correct(zip(delta_x, delta_y))
Exemplo n.º 2
0
from MotionAnalyser import MotionAnalyzer
from utils import plot_Tx_Ty_Rot, plot_Tx_Ty
import numpy as np
from KalmanFilter import KalmanFilter
from VideoProcessor import VideoCorrector

KFilter = KalmanFilter()
MAnly = MotionAnalyzer('./output/IMG_1432_filted.mp4')
Vcorr = VideoCorrector('./output/IMG_1432_filted.mp4')

Tx, Ty, _ = MAnly.process()
# MAnly.save()
plot_Tx_Ty(Tx, Ty)
res_x, res_y = KFilter.filter(Tx), KFilter.filter(Ty)
plot_Tx_Ty(res_x, res_y)
delta_x = np.array(Tx) - np.array(res_x)
delta_y = np.array(Ty) - np.array(res_y)
Vcorr.correct(zip(delta_x, delta_y))

print('finish')
Exemplo n.º 3
0
        #print z_mw
        #print("all valid: %d" % (z_all_valid))
        #print z_all

        #if not z_lw_valid and not z_mw_valid:
        #    print "Warning: invalid Z"
        #print('z')
        #print lw_z, mw_z

        #break

        #print xpred
        #print Ppost
        #print lw_z
        xhat_lw[:,idx], Ppost_lw = \
                kalman.filter(xpred_lw, Ppost_lw, z_lw, z_lw_valid)
        xpred_lw = xhat_lw[:, idx]

        xhat_mw[:,idx], Ppost_mw = \
                kalman.filter(xpred_mw, Ppost_mw, z_mw, z_mw_valid)
        xpred_mw = xhat_mw[:, idx]

        xhat_all[:,idx], Ppost_all = \
                kalman.filter(xpred_all, Ppost_all, z_all, z_all_valid)
        xpred_all = xhat_all[:, idx]
        #print xhat_lw[:,idx], xhat_mw[:,idx]

        #rect = ((xpred[0] - xpred[4]*0.5, xpred[2] - xpred[5]*0.5), (xpred[4], xpred[5]), 0.0)
        rect = ((xpred_all[0], xpred_all[2]), (xpred_all[4], xpred_all[5]),
                0.0)
        box = np.int0(cv2.boxPoints(rect))