def get_bvh_offsets_and_animation(file_name, frame_number):
with open(file_name) as f:
mocap = Bvh(f.read())
mocap_joint_names = mocap.get_joints_names()
mocap_joint_prefix = mocap_joint_names[0].split('Hips')[0]
rotation_matrices = np.empty((1, 3, 3), dtype=float)
offsets = np.empty((1, 3), dtype=float)
root_position = mocap.frame_joint_channels(
frame_number, mocap_joint_names[0],
['Xposition', 'Yposition', 'Zposition'])
for name in joint_names: # predefined joint_names
mocap_joint_name = mocap_joint_prefix + name
euler = mocap.frame_joint_channels(
frame_number, mocap_joint_name,
['Xrotation', 'Yrotation', 'Zrotation'])
# print(name, euler)
# rot = R.from_euler('xyz', euler, degrees=False) # Previous models are trained for wrong rotations
rot = R.from_euler('XYZ', euler,
degrees=True) # should we use 'XYZ', degrees=True?
rot = np.array(rot.as_matrix())
rot = rot.reshape(1, 3, 3)
rotation_matrices = np.append(rotation_matrices, rot, axis=0)
offset = np.array(mocap.joint_offset(mocap_joint_name))
offsets = np.append(offsets, offset.reshape(1, 3), axis=0)
# print('{}:\nRotationMatrix:\n'.format(name), rot[0], '\nOffset: ', offset.reshape(3, ))
offsets = np.delete(offsets, [0, 0], axis=0)
rotation_matrices = np.delete(rotation_matrices, [0, 0, 0], axis=0)
return offsets, rotation_matrices, root_position #[3], [J, 3], [J, 3]
def load_from_bvh(self, fname, exclude_bones=None, spec_channels=None):
if exclude_bones is None:
exclude_bones = {}
if spec_channels is None:
spec_channels = dict()
with open(fname) as f:
mocap = Bvh(f.read())
joint_names = list(
filter(lambda x: all([t not in x for t in exclude_bones]),
mocap.get_joints_names()))
dof_ind = {'x': 0, 'y': 1, 'z': 2}
self.len_scale = 0.0254
self.root = Bone()
self.root.id = 0
self.root.name = joint_names[0]
self.root.channels = mocap.joint_channels(self.root.name)
self.name2bone[self.root.name] = self.root
self.bones.append(self.root)
for i, joint in enumerate(joint_names[1:]):
bone = Bone()
bone.id = i + 1
bone.name = joint
bone.channels = spec_channels[joint] if joint in spec_channels.keys(
) else mocap.joint_channels(joint)
bone.dof_index = [dof_ind[x[0].lower()] for x in bone.channels]
bone.offset = np.array(mocap.joint_offset(joint)) * self.len_scale
bone.lb = [-180.0] * 3
bone.ub = [180.0] * 3
self.bones.append(bone)
self.name2bone[joint] = bone
for bone in self.bones[1:]:
parent_name = mocap.joint_parent(bone.name).name
if parent_name in self.name2bone.keys():
bone_p = self.name2bone[parent_name]
bone_p.child.append(bone)
bone.parent = bone_p
self.forward_bvh(self.root)
for bone in self.bones:
if len(bone.child) == 0:
bone.end = bone.pos + np.array([
float(x)
for x in mocap.get_joint(bone.name).children[-1]['OFFSET']
]) * self.len_scale
else:
bone.end = sum([bone_c.pos
for bone_c in bone.child]) / len(bone.child)
def test_unknown_joint(self):
with open('tests/test_mocapbank.bvh') as f:
mocap = Bvh(f.read())
with self.assertRaises(LookupError):
mocap.joint_offset('FooBar')
def test_joint_offset(self):
with open('tests/test_mocapbank.bvh') as f:
mocap = Bvh(f.read())
self.assertEqual(mocap.joint_offset('RightElbow'), (-2.6865, -25.0857, 1.2959))
with open('../Data/BVH/Vasso_Miserable_0.bvh') as data:
mocap = Bvh(data.read())
#Get Mocap Tree
tree = [str(item) for item in mocap.root]
#['HIERARCHY', 'ROOT Hips', 'MOTION', 'Frames: 1068', 'Frame Time: 0.0333333']
#Get ROOT OFFSET
root = next(mocap.root.filter('ROOT'))['OFFSET']
#['3.93885', '96.9818', '-23.2913']
#Get all JOINT names
joints = mocap.get_joints_names() #54
mocap.get_joints_names()[17] #All Names
mocap.joint_offset('Head') #Offset
mocap.joint_channels('Neck') #Channels
mocap.get_joint_channels_index('Spine')
#
mocap.joint_parent_index('Neck') #Parent Index
mocap.joint_parent('Head').name # Parent Name
#mocap.joint_direct_children('Hips') #Direct Children
#Get Frames
mocap.nframes
mocap.frame_time
mocap.frame_joint_channel(22, 'Spine', 'Xrotation')
#SEARCH
[str(node) for node in mocap.search('JOINT', 'LeftShoulder')] #Single Item
[str(node) for node in mocap.search('JOINT')] #All Items
