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