def create(self):
project_dir = self._config['project_dir']
ref_motion_db = self._config['character'].get('ref_motion_db')
ref_motion_scale = self._config['character'].get('ref_motion_scale')
ref_motion_file = []
for i, mdb in enumerate(ref_motion_db):
motions = []
if mdb.get('cluster_info'):
''' Read reference motions based on the cluster labels '''
assert mdb.get('data') is None, \
'This should not be specified when cluster_info is used'
dir = mdb['cluster_info'].get('dir')
label_file = mdb['cluster_info'].get('label_file')
sample_id = mdb['cluster_info'].get('sample_id')
labels = {}
assert label_file
if project_dir:
label_file = os.path.join(project_dir, label_file)
with open(label_file, 'r') as file:
for line in file:
l = re.split('[\t|\n|,|:| ]+', line)
id, rank, score, filename = int(l[0]), int(
l[1]), float(l[2]), str(l[3])
if id not in labels.keys(): labels[id] = []
labels[id].append({
'rank': rank,
'socre': score,
'filename': filename
})
num_cluster = len(labels.keys())
for j in range(num_cluster):
if sample_id and j != sample_id:
continue
for label in labels[j]:
if project_dir:
file = os.path.join(project_dir, dir,
label['filename'])
motions.append(file)
else:
''' Read reference motions from the specified list of files and dirs '''
ref_motion_data = mdb.get('data')
motions = []
if ref_motion_data.get('file'):
motions += ref_motion_data.get('file')
if ref_motion_data.get('dir'):
for d in ref_motion_data.get('dir'):
if project_dir:
d = os.path.join(project_dir, d)
motions += utils.files_in_dir(d, ext=".bvh", sort=True)
if project_dir:
for j in range(len(motions)):
motions[j] = os.path.join(project_dir, motions[j])
'''
If num_sample is specified, we use only num_sample motions
from the entire reference motions.
'random' chooses randomly, 'top' chooses the first num_sample
'''
num_sample = mdb.get('num_sample')
if num_sample:
sample_method = mdb.get('sample_method')
if sample_method == 'random':
motions = random.choices(motions, k=num_sample)
elif sample_method == 'top':
motions = motions[:num_sample]
else:
raise NotImplementedError
ref_motion_file.append(motions)
''' Load Reference Motion '''
self._ref_motion_all = []
self._ref_motion_file_names = []
for i in range(self._num_agent):
ref_motion_all, ref_motion_file_names = \
load_motions(ref_motion_file[i],
self._base_motion[i].skel,
self._sim_agent[i]._char_info,
self._verbose)
self._ref_motion_all.append(ref_motion_all)
self._ref_motion_file_names.append(ref_motion_file_names)
''' Should call reset after all setups are done '''
self.reset({'add_noise': False})
self._initialized = True
if self._verbose:
print('----- Humanoid Imitation Environment Created -----')
for i in range(self._num_agent):
print('[Agent%d]: state(%d) and action(%d)' \
%(i, len(self.state(i)), self._action_space[i].dim))
print('-------------------------------')
help="Window stride for test and validation, in frames. This is also"
" used as training window size",
)
args = parser.parse_args()
train_files = read_content(
os.path.join(args.split_dir, "training_fnames.txt"))
validation_files = read_content(
os.path.join(args.split_dir, "validation_fnames.txt"))
test_files = read_content(os.path.join(args.split_dir, "test_fnames.txt"))
train_ftuples = []
test_ftuples = []
validation_ftuples = []
for filepath in fairmotion_utils.files_in_dir(args.input_dir, ext="pkl"):
db_name = os.path.split(os.path.dirname(filepath))[1]
db_name = ("_".join(db_name.split("_")[1:])
if "AMASS" in db_name else db_name.split("_")[0])
f = os.path.basename(filepath)
file_id = "{}/{}".format(db_name, f)
if file_id in train_files:
train_ftuples.append((filepath, file_id))
elif file_id in validation_files:
validation_ftuples.append((filepath, file_id))
elif file_id in test_files:
test_ftuples.append((filepath, file_id))
else:
pass
parser.add_argument("--diff-threshold", type=float, default=5.0)
parser.add_argument("--w-joint-pos", type=float, default=8.0)
parser.add_argument("--w-joint-vel", type=float, default=2.0)
parser.add_argument("--w-root-pos", type=float, default=0.5)
parser.add_argument("--w-root-vel", type=float, default=1.5)
parser.add_argument("--w-ee-pos", type=float, default=3.0)
parser.add_argument("--w-ee-vel", type=float, default=1.0)
parser.add_argument("--w-trajectory", type=float, default=1.0)
parser.add_argument("--num-workers", type=int, default=10)
args = parser.parse_args()
# Load motions
motion_files = args.motion_files if args.motion_files else []
motion_files = (motion_files +
utils.files_in_dir(args.motion_folder, ext="bvh")
if args.motion_folder else motion_files)
motions = bvh.load_parallel(
motion_files,
scale=args.scale,
v_up_skel=utils.str_to_axis(args.v_up_skel),
v_face_skel=utils.str_to_axis(args.v_face_skel),
v_up_env=utils.str_to_axis(args.v_up_env),
)
skel = motions[0].skel
motions_with_velocity = []
for motion in motions:
motion.set_skeleton(skel)
motions_with_velocity.append(