def test_sizes_of_parsed_data(self):
# Instantiate the humanoid environment.
env = humanoid_CMU.stand()
# Parse and convert specified clip.
converted = parse_amc.convert(_TEST_AMC_PATH, env.physics,
env.control_timestep())
self.assertEqual(converted.qpos.shape[0], 63)
self.assertEqual(converted.qvel.shape[0], 62)
self.assertEqual(converted.time.shape[0], converted.qpos.shape[1])
self.assertEqual(converted.qpos.shape[1], converted.qvel.shape[1] + 1)
# Parse and convert specified clip -- WITH SMALLER TIMESTEP
converted2 = parse_amc.convert(_TEST_AMC_PATH, env.physics,
0.5 * env.control_timestep())
self.assertEqual(converted2.qpos.shape[0], 63)
self.assertEqual(converted2.qvel.shape[0], 62)
self.assertEqual(converted2.time.shape[0], converted2.qpos.shape[1])
self.assertEqual(converted.qpos.shape[1], converted.qvel.shape[1] + 1)
# Compare sizes of parsed objects for different timesteps
self.assertEqual(converted.qpos.shape[1] * 2, converted2.qpos.shape[1])
def main(unused_argv):
env = humanoid_CMU.stand()
# Parse and convert specified clip.
converted = parse_amc.convert(FLAGS.filename,
env.physics, env.control_timestep())
max_frame = min(FLAGS.max_num_frames, converted.qpos.shape[1] - 1)
width = 480
height = 480
video = np.zeros((max_frame, height, 2 * width, 3), dtype=np.uint8)
for i in range(max_frame):
p_i = converted.qpos[:, i]
with env.physics.reset_context():
env.physics.data.qpos[:] = p_i
video[i] = np.hstack([env.physics.render(height, width, camera_id=0),
env.physics.render(height, width, camera_id=1)])
tic = time.time()
for i in range(max_frame):
if i == 0:
img = plt.imshow(video[i])
else:
img.set_data(video[i])
toc = time.time()
clock_dt = toc - tic
tic = time.time()
# Real-time playback not always possible as clock_dt > .03
plt.pause(max(0.01, 0.03 - clock_dt)) # Need min display time > 0.0.
plt.draw()
plt.waitforbuttonpress()
def getNumFrames(filename): env = humanoid_CMU.stand() # Parse and convert specified clip. converted = parse_amc.convert(filename, env.physics, env.control_timestep()) frame_num = converted.qpos.shape[1] - 1 return frame_num
def main(filename):
env = humanoid_CMU.run()
# Parse and convert specified clip.
converted = parse_amc.convert(filename, env.physics,
env.control_timestep())
max_frame = (converted.qvel.shape[1])
trajectory = []
reward = []
#pos = []
width = 480
height = 480
video = np.zeros((max_frame, height, 2 * width, 3), dtype=np.uint8)
print(converted.qpos.shape)
print(converted.qvel.shape)
for i in range(max_frame):
#print('we are at frame %d' %i)
p_i = converted.qpos[:, i]
v_i = converted.qvel[:, i]
with env.physics.reset_context():
env.physics.data.qpos[:] = p_i
env.physics.data.qvel[:] = v_i
trajectory.append(obs['observations'])
trajectory = np.array([traj for traj in trajectory])
return trajectory, converted.qpos[:, 0:max_frame], converted.qvel, np.sum(
reward)
def load_state_dataset(data_dir_path, env, control_timestep):
from dm_control.suite.utils import parse_amc
converted_data = []
files = os.listdir(data_dir_path)
for file in files:
if (file.endswith(".amc")):
file_path = data_dir_path + file
converted = parse_amc.convert(file_path, env.physics, control_timestep) # 0.01 --> env.control_timestep()
file_save_path = "/home/jmj/Download/subjects_08/" + file_path.split(".")[0] + ".npy"
# np.save(file_save_path, converted.qpos)
converted_data.append({"qpos": converted.qpos, "qvel": converted.qvel})
state_dataset = Dset(converted_data)
return state_dataset
def load_state_dataset(data_dir_path, env, control_timestep):
from dm_control.suite.utils import parse_amc
converted_data = []
files = os.listdir(data_dir_path)
for file in files:
if (file.endswith(".amc")):
file_path = data_dir_path + file
converted = parse_amc.convert(
file_path, env.physics,
control_timestep) # 0.01 --> env.control_timestep()
converted_data.append({
"qpos": converted.qpos,
"qvel": converted.qvel
})
state_dataset = Dset(converted_data)
return state_dataset
def load_mocap_expert_trajectory(env,
traj_data_dir,
only_preprocess=False,
force_repreprocess=False):
""" @brief:
load the mocap data from amc files. If the amc has been
preprocessed, load the npy file that contains the qpos and qvel data
"""
from dm_control.suite.utils import parse_amc
# get all the file names
if traj_data_dir.endswith('.amc'):
file_names = [traj_data_dir]
else:
assert os.path.exists(traj_data_dir)
file_names = glob.glob(traj_data_dir + '/*.amc')
mocap_data = []
for i_amc in file_names:
i_npy = i_amc.replace('.amc', '.npy')
if os.path.exists(i_npy) and (not force_repreprocess):
# if the npy files has been processed
i_mocap_data = np.load(i_npy, encoding="latin1").item()
else:
# if the npy has not been processed
converted_data = \
parse_amc.convert(i_amc, env.physics, env.control_timestep())
qvel = converted_data.qvel.transpose()
qpos = converted_data.qpos.transpose()
assert qpos.shape[0] == qvel.shape[0] + 1
num_qpos = len(qpos) - 1
observation = []
# get the other observation info
for i_id in range(num_qpos):
with env.physics.reset_context():
env.physics.data.qpos[:] = qpos[i_id]
env.physics.data.qvel[:] = qvel[i_id]
env.physics.after_reset()
i_observation_dict = env.task.get_observation(env.physics)
i_observation = np.concatenate([
env.physics.data.qpos[:7],
env_util.vectorize_ob(i_observation_dict),
np.ones(1) * i_id,
env.physics.center_of_mass_position()
])
observation.append(i_observation)
# the center of mass
i_mocap_data = {
'qvel': qvel,
'qpos': qpos,
'num_qpos': num_qpos,
'observation': np.array(observation)
}
np.save(i_npy, i_mocap_data) # save the data
mocap_data.append(i_mocap_data)
return mocap_data, file_names
