def process_observation(self, n_avg=5): """ Store an observation of ar_marker and hydras. """ raw_input(colorize("Press return when ready to capture transforms.", "green", True)) ar_avg_tfm = [] hydra_avg_tfm = [] for j in xrange(n_avg): print colorize('\tGetting averaging transform : %d of %d ...'%(j,n_avg-1), "blue", True) ar_transforms = gmt.get_ar_markers_from_cameras(self.cameras, cams = [self.calib_camera], markers = [self.ar_marker]) hydra_transforms = gmt.get_hydra_transforms('hydra_base', [self.calib_hydra]) ar_avg_tfm.append(ar_transforms[self.ar_marker]) hydra_avg_tfm.append(hydra_transforms[self.ar_marker][self.calib_hydra]) self.ar_transforms.append(utils.avg_transform(ar_avg_tfm)) self.hydra_transforms.append(utils.avg_transform(hydra_avg_tfm))
def process_observation (self, n_avg=5): self.iterations += 1 raw_input(colorize("Iteration %d: Press return when ready to capture transforms."%self.iterations, "red", True)) avg_tfms = {} for j in xrange(n_avg): print colorize('\tGetting averaging transform : %d of %d ...'%(j,n_avg-1), "blue", True) tfms = {} tfms.update(gmt.get_ar_markers_from_cameras(self.cameras, parent_frame=self.parent_frame, markers=self.ar_markers)) tfms.update(gmt.get_hydra_transforms(parent_frame=parent_frame, hydras = self.hydras)) pot_angle = gmt.get_pot_angle() for marker in tfms: if marker not in avg_tfms: avg_tfms[marker] = [] avg_tfms[marker].append(tfms[marker]) for marker in avg_tfms: avg_tfms[marker] = utils.avg_transform(avg_tfms[marker]) update_groups_from_observations(self.masterGraph, avg_tfms, pot_angle)