if 1:
skel = Skeleton(stereo_cam)
filename = "/wg/wgdata1/vol1/iros2009/mkplot_snap"
filename = "ABCDEFG"
skel.load(filename)
print "skel.nodes:", len(skel.nodes)
for e in skel.edges:
if e[0] in bad_vertices or e[1] in bad_vertices:
print "bad edge", e
skel.nodes = [ id for id in skel.nodes if not id in bad_vertices ]
print "skel.nodes:", len(skel.nodes)
print set(skel.labelization())
skel.optimize()
skel.optimize()
skel.save("iros2009/ABCDEF2")
pos,edges,_ = skel.localization()
f = open("deletion2.pickle", "w")
pickle.dump(pos, f)
pickle.dump(edges, f)
pickle.dump(skel.labelization(), f)
f.close()
res_views = []
res_newedges = []
res_view_nb = []
res_clusters_nb = []
op = open("1", "w")
for kappa in [2]: # [ 9999,7,5,4,3,2 ]:
print "There are", len(vo.tracks), "tracks"
print "There are", len([t for t in vo.tracks if t.alive]), "live tracks"
print "There are", len(set([t.p[-1] for t in vo.tracks if t.alive])), "unique endpoints on live tracks"
for vo in vos:
print vo.name()
print "distance from start:", vo.pose.distance()
vo.summarize_timers()
print vo.log_keyframes
print
skel.summarize_timers()
skel.dump_timers('skel_timers.pickle')
skel.trim()
print "Saving as mkplot_snap"
skel.save("mkplot_snap")
#skel.plot('blue', True)
#pylab.show()
sys.exit(0)
colors = [ 'red', 'black', 'magenta', 'cyan', 'orange', 'brown', 'purple', 'olive', 'gray' ]
for i in range(len(vos)):
vos[i].planarity = planar(numpy.array([x for (x,y,z) in trajectory[i]]), numpy.array([y for (x,y,z) in trajectory[i]]), numpy.array([z for (x,y,z) in trajectory[i]]))
print "planarity", vos[i].planarity
xs = numpy.array(vo_x[i])
ys = numpy.array(vo_y[i])
if 0:
xs -= 4.5 * 1e-3
f = -0.06
else:
f = 0.0
