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from scipy.spatial.transform import Rotation as R
import numpy as np
def rot_mats_to_eulers(predicted_mats):
ident = np.eye(3, dtype=np.float32)
angle_axes = np.zeros((predicted_mats.shape[0],72))
for i,joints in enumerate(predicted_mats):
joints = joints[0]
trans = joints[216:]
joints = joints[:216].reshape(-1,9)
new_thing = np.zeros(72)
# new_thing[69:] = trans
for j,mat in enumerate(joints):
mat = mat.reshape(3,3) + ident
rot = R.from_matrix(mat)
rot = rot.as_rotvec()
new_thing[j*3:(j+1)*3] = rot
angle_axes[i] = new_thing
smpl_thing = {'smpl_loss':1.8,'smpl_poses':angle_axes,'smpl_trans':predicted_mats[:,0,216:], 'smpl_scaling': np.array([95])}
# pickle.dump(smpl_thing, open("analysis/aistplusplus_api/last.generated.test.pkl", "wb"))
return smpl_thing
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