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motion_utils.py
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motion_utils.py
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import os
import pickle
import gzip
import re
import random
from fairmotion.core.motion import Motion
from fairmotion.core.velocity import MotionWithVelocity
from fairmotion.data import bvh,asfamc
from fairmotion.utils import utils
def load_motions(motion_files, skel, char_info, verbose):
assert motion_files is not None
motion_all = []
motion_file_names = []
motion_file_asf_names = []
amc = False
for names in motion_files:
if type(names) is list:
asf_head,asf_tail = os.path.split(names[0])
motion_head,motion_tail = os.path.split(names[1])
motion_file_asf_names.append(asf_tail)
motion_file_names.append(motion_tail)
amc = True
else:
head, tail = os.path.split(names)
motion_file_names.append(tail)
if len(motion_files) > 0:
if isinstance(motion_files[0], str) or isinstance(motion_files[0], list):
motion_dict = {}
for i, file in enumerate(motion_files):
''' If the same file is already loaded, do not load again for efficiency'''
if amc:
asf_file = file[0]
file = file[1]
if file in motion_dict:
m = motion_dict[file]
else:
if file.endswith('bvh'):
if skel is not None:
m = bvh.load(motion=Motion(name=file, skel=skel),
file=file,
scale=1.0,
load_skel=False,
v_up_skel=char_info.v_up,
v_face_skel=char_info.v_face,
v_up_env=char_info.v_up_env)
else:
m = bvh.load(file=file,
scale=1.0,
v_up_skel=char_info.v_up,
v_face_skel=char_info.v_face,
v_up_env=char_info.v_up_env)
m = MotionWithVelocity.from_motion(m)
elif file.endswith('amc'):
m = asfamc.load(
file=asf_file,
motion= file,
scale=1.0,
v_up_skel=char_info.v_up,
v_face_skel=char_info.v_face,
v_up_env=char_info.v_up_env)
m = MotionWithVelocity.from_motion(m)
elif file.endswith('bin'):
m = pickle.load(open(file, "rb"))
elif file.endswith('gzip') or file.endswith('gz'):
with gzip.open(file, "rb") as f:
m = pickle.load(f)
else:
raise Exception('Unknown Motion File Type')
if verbose:
print('Loaded: %s'%file)
motion_all.append(m)
elif isinstance(motion_files[0], MotionWithVelocity):
motion_all = motion_files
else:
raise Exception('Unknown Type for Reference Motion')
return motion_all, motion_file_names, motion_file_asf_names
def collect_motion_files(project_dir, ref_motion_db):
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)):
if type(motions[j]) is list:
motions[j][0] = os.path.join(project_dir, motions[j][0])
motions[j][1] = os.path.join(project_dir, motions[j][1])
else:
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)
return ref_motion_file
# for i, ref_motion in enumerate(self._ref_motion_all):
# for j, m in enumerate(ref_motion):
# _, p = conversions.T2Rp(m.get_pose_by_frame(0).get_root_transform())
# v = np.zeros(3)
# if i==0:
# v[1] = -p[1] - 2.0
# R = conversions.Az2R(-0.5*np.pi)
# else:
# v[1] = -p[1] + 2.0
# R = conversions.Az2R(0.5*np.pi)
# T = conversions.Rp2T(R, v)
# motion.transform(m, T, 0)
# bvh.save(m, "data/temp/"+self._ref_motion_file_names[i][j]+"_edited.bvh", verbose=True)
# exit(0)