def __init__(self, data_path):
Dataset.__init__(self)
bvh = BVH()
bvh.load(data_path)
self.bvh = bvh
self.phases = np.loadtxt(data_path.replace('bvh', 'phase'))
self.root_motions = bvh.motions[:, :num_of_root_infos]
self.phase_deltas = self.phases[1:] - self.phases[:-1]
self.phase_deltas *= phase_scale
print(self.phase_deltas[200:300])
def __init__(self,
data_root,
transform=None):
"""TODO: to be defined.
:data_root: TODO
:transform: TODO
"""
Dataset.__init__(self)
assert isinstance(data_root, str)
assert Path(data_root).resolve().exists()
self._data_root = Path(data_root).resolve()
assert transform is not None
self._transform = transform
def __init__(self, data_path):
Dataset.__init__(self)
bvh = BVH()
bvh.load(data_path)
self.bvh = bvh
self.phases = np.loadtxt(data_path.replace('bvh',
'phase'))[start_index:]
self.phase_deltas = (self.phases[1:] - self.phases[:-1])
self.phase_deltas[self.phase_deltas < 0] += 1
self.phase_deltas_mean = np.mean(self.phase_deltas, axis=0)
self.phase_deltas_std = np.std(self.phase_deltas, axis=0)
self.phase_deltas = (self.phase_deltas -
self.phase_deltas_mean) / self.phase_deltas_std
self.phase_deltas *= phase_scale
self.root_motions = bvh.motions[start_index:, :num_of_root_infos]
self.trajectories = self.root_motions[:, [0, 2, 4]]
self.trajectories = self.trajectories[1:] - self.trajectories[:-1]
print(self.root_motions[:-1, [4]].shape)
self.trajectories = np.concatenate(
[self.trajectories, self.root_motions[:-1, [4]]], axis=1)
self.trajectory_mean = np.mean(self.trajectories, axis=0)
self.trajectory_std = np.std(self.trajectories, axis=0)
self.trajectories = (self.trajectories -
self.trajectory_mean) / self.trajectory_std
self.trajectories *= trajectory_scale
self.angles = self.bvh.motion_angles[start_index:]
self.angles_mean = np.mean(self.angles, axis=0)
self.angles_std = np.std(self.angles, axis=0)
# print(self.angles_mean.shape)
# print(self.angles_std)
# print(self.angles)
print(self.angles.shape)
self.angles_delta = self.angles[1:] - self.angles[:-1]
self.angles_delta_mean = np.mean(self.angles_delta, axis=0)
self.angles_delta_std = np.std(self.angles_delta, axis=0)
self.angles = (self.angles-self.angles_mean) / \
(self.angles_std+(self.angles_std == 0))
self.angles_delta = (self.angles_delta-self.angles_delta_mean) / \
(self.angles_delta_std+(self.angles_delta_std == 0))
self.angles *= angles_scale
self.angles_delta *= angles_scale
def __init__(self, data_path):
Dataset.__init__(self)
bvh = BVH()
bvh.load(data_path)
self.bvh = bvh
self.phases = np.loadtxt(data_path.replace('bvh', 'phase'))
print(self.phases.shape)
root_motions = bvh.motions[:, :num_of_root_infos]
self.root_deltas = root_motions[1:] - root_motions[:-1]
print(self.root_deltas.shape)
self.root_deltas[:, 0] *= delta_scale
self.root_deltas[:, 2] *= delta_scale
for i in range(6):
items = self.root_deltas[:, i]
print(np.max(items), np.min(items), np.mean(items))
self.phase_deltas = self.phases[1:] - self.phases[:-1]
self.phase_deltas *= phase_scale
items = self.phase_deltas
print(np.max(items), np.min(items), np.mean(items))
def __init__(self, files_source, transforms=None):
Dataset.__init__(self)
self.transforms = transforms
# get number of classes
self.classes = sorted(os.listdir(files_source))
self.name_to_id = {
self.classes[i]: i
for i in range(len(self.classes))
}
if len(self.classes) != 1000:
raise ValueError(
"There should be 1000 classes, only {} exist".format(
len(self.classes)))
# get files list
if isinstance(files_source, str) and os.path.isdir(files_source):
self.files = glob.glob(os.path.join(files_source, "*/*.npz"))
else:
raise ValueError(
"You should provide either dir_path or paths_list!")
def __init__(self, bvh, num_of_frames):
Dataset.__init__(self)
self.bvh = bvh
self.motions = bvh.motions
self.num_of_frames = num_of_frames