def blend(pose1, pose2, alpha=0.5):
assert 0.0 <= alpha <= 1.0
pose_new = copy.deepcopy(pose1)
for j in range(pose1.skel.num_joints()):
R0, p0 = conversions.T2Rp(pose1.get_transform(j, local=True))
R1, p1 = conversions.T2Rp(pose2.get_transform(j, local=True))
R, p = math.slerp(R0, R1, alpha), math.lerp(p0, p1, alpha)
pose_new.set_transform(j, conversions.Rp2T(R, p), local=True)
return pose_new
def interpolate(cls, v1, v2, alpha):
"""Returns interpolated velocity object between two velocity objects.
Typically, each velocity object is associated with a frame.
`interpolate` could be used to calculated interpolated angular and
linear velocity for any frame between them.
Args:
v1, v2: Velocity objects associated with frame between which
interpolated velocity is calculated
alpha: Value between 0 and 1 denoting the blending ratio. alpha=0
returns v1, and alpha=1 returns v2
"""
data_local = math.lerp(v1.data_local, v2.data_local, alpha)
data_global = math.lerp(v1.data_global, v2.data_global, alpha)
v = cls()
v.set_skel(v1.skel)
v.set_data_local(data_local)
v.set_data_global(data_global)
return v
def interpolate(cls, pose1, pose2, alpha):
skel = pose1.skel
data = []
for j in skel.joints:
R1, p1 = conversions.T2Rp(pose1.get_transform(j, local=True))
R2, p2 = conversions.T2Rp(pose2.get_transform(j, local=True))
R, p = (
math.slerp(R1, R2, alpha),
math.lerp(p1, p2, alpha),
)
data.append(conversions.Rp2T(R, p))
return Pose(pose1.skel, data)
