def __init__(self, params, **args):
self.vg_pub = VoxelgridPublisher()
self.selection_sub = None
self.model_runner = None
self.dataset_supervisor = None
self.params = params
self.train_or_test = args[
'train_or_test'] if 'train_or_test' in args else 'train'
if args['dataset']:
self.load_dataset(args['dataset'])
if args['trial']:
self.load_model(lookup_trial(args['trial']))
def make_live_cheezit_video_1():
scene = get_scene('live_cheezit')
trial = lookup_trial('YCB')
with WindowRecorder([
"live_shape_completion.rviz* - RViz",
"live_shape_completion.rviz - RViz"
],
frame_rate=30.0,
name_suffix="rviz",
save_dir=rviz_capture_path):
with CameraRecorder(filename=f'{rviz_capture_path}/live_cheezit.mp4'):
contact_shape_completer = ContactShapeCompleter(
scene, trial, store_request=False)
contact_shape_completer.get_visible_vg()
contact_shape_completer.compute_known_occ()
print("Up and running")
rospy.spin()
def make_aab_video_1():
# tf.random.set_seed(20210108) # Okay, but initial free space measurement does not affect any particles
tf.random.set_seed(20210111)
scene = get_scene('cheezit_01')
trial = lookup_trial('AAB')
with WindowRecorder([
"live_shape_completion.rviz* - RViz",
"live_shape_completion.rviz - RViz"
],
frame_rate=30.0,
name_suffix="rviz",
save_dir=rviz_capture_path):
contact_shape_completer = ContactShapeCompleter(scene,
trial,
store_request=False,
completion_density=1)
contact_shape_completer.get_visible_vg()
contact_shape_completer.compute_known_occ()
print("Up and running")
rospy.spin()
def generate_evaluation(details):
tf.random.set_seed(20210108)
scene = details.scene_type()
contact_shape_completer = ContactShapeCompleter(scene,
lookup_trial(
details.network),
completion_density=1,
method=details.method)
contact_shape_completer.get_visible_vg(load=True)
columns = [
'request number', 'chs count', 'particle num', 'scene', 'method',
'chamfer distance', 'projection succeeded?'
]
df = pd.DataFrame(columns=columns)
gt = scene.get_gt(density_factor=1)
point_pub = ros_helpers.get_connected_publisher('/pointcloud',
PointCloud2,
queue_size=1)
point_pub.publish(gt)
files = sorted([f for f in scene.get_save_path().glob('req_*')])
for req_number, file in enumerate(files):
print(f"{Fore.CYAN}Loading stored request{file}{Fore.RESET}")
completion_req = CompleteShapeRequest()
with file.open('rb') as f:
completion_req.deserialize(f.read())
completion_req.num_samples = NUM_PARTICLES_IN_TRIAL
resp = contact_shape_completer.complete_shape_srv(completion_req)
dists = []
for particle_num, completion_pts_msg in enumerate(
resp.sampled_completions):
total_dist = 0
for view in contact_shape_completer.robot_views:
dist = vg_chamfer_distance(
contact_shape_completer.transform_from_gpuvoxels(
view, completion_pts_msg),
contact_shape_completer.transform_from_gpuvoxels(view, gt),
scale=view.scale).numpy()
print(f"Errors w.r.t. gt: {dist}")
total_dist += dist
dists.append(total_dist)
df = df.append(pd.Series([
req_number,
float(len(completion_req.chss)), particle_num, scene.name,
details.method, dist, True
],
index=columns),
ignore_index=True)
if len(dists) == 0:
continue
print(f"Closest particle has error {np.min(dists)}")
print(f"Average particle has error {np.mean(dists)}")
display_sorted_particles(resp.sampled_completions, dists)
df.to_csv(get_evaluation_path(details))
print(df)
contact_shape_completer.unsubscribe()
"""
default_dataset_params = default_params.get_default_params()
def parse_command_line_args():
parser = argparse.ArgumentParser(
description='Publish shape data to RViz for viewing')
parser.add_argument('--trial', required=True)
parser.add_argument('--scene', required=True)
parser.add_argument('--store', action='store_true')
return parser.parse_args()
if __name__ == "__main__":
ARGS = parse_command_line_args()
rospy.init_node('contact_shape_completer_service')
rospy.loginfo("Data Publisher")
scene = get_scene(ARGS.scene)
contact_shape_completer = ContactShapeCompleter(scene,
lookup_trial(ARGS.trial),
store_request=ARGS.store)
contact_shape_completer.get_visible_vg()
contact_shape_completer.compute_known_occ()
print("Up and running")
rospy.spin()