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Sleeping
| import numpy as np | |
| SMPL_BODY_BONES = [-0.0018, -0.2233, 0.0282, 0.0695, -0.0914, -0.0068, -0.0677, -0.0905, -0.0043, | |
| -0.0025, 0.1090, -0.0267, 0.0343, -0.3752, -0.0045, -0.0383, -0.3826, -0.0089, | |
| 0.0055, 0.1352, 0.0011, -0.0136, -0.3980, -0.0437, 0.0158, -0.3984, -0.0423, | |
| 0.0015, 0.0529, 0.0254, 0.0264, -0.0558, 0.1193, -0.0254, -0.0481, 0.1233, | |
| -0.0028, 0.2139, -0.0429, 0.0788, 0.1217, -0.0341, -0.0818, 0.1188, -0.0386, | |
| 0.0052, 0.0650, 0.0513, 0.0910, 0.0305, -0.0089, -0.0960, 0.0326, -0.0091, | |
| 0.2596, -0.0128, -0.0275, -0.2537, -0.0133, -0.0214, 0.2492, 0.0090, -0.0012, | |
| -0.2553, 0.0078, -0.0056, 0.0840, -0.0082, -0.0149, -0.0846, -0.0061, -0.0103] | |
| class HybrIKJointsToRotmat: | |
| def __init__(self): | |
| self.naive_hybrik = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, | |
| 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0] | |
| self.num_nodes = 22 | |
| self.parents = [0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 9, 12, 13, 14, 16, 17, 18, 19] | |
| self.child = [-1, 4, 5, 6, 7, 8, 9, 10, 11, -1, -2, -2, 15, | |
| 16, 17, -2, 18, 19, 20, 21, -2, -2] | |
| self.bones = np.reshape(np.array(SMPL_BODY_BONES), [24, 3])[:self.num_nodes] | |
| def multi_child_rot(self, t, p, | |
| pose_global_parent): | |
| """ | |
| t: B x 3 x child_num | |
| p: B x 3 x child_num | |
| pose_global_parent: B x 3 x 3 | |
| """ | |
| m = np.matmul(t, np.transpose(np.matmul(np.linalg.inv(pose_global_parent), p), [0, 2, 1])) | |
| u, s, vt = np.linalg.svd(m) | |
| r = np.matmul(np.transpose(vt, [0, 2, 1]), np.transpose(u, [0, 2, 1])) | |
| err_det_mask = (np.linalg.det(r) < 0.0).reshape(-1, 1, 1) | |
| id_fix = np.reshape(np.array([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, -1.0]]), | |
| [1, 3, 3]) | |
| r_fix = np.matmul(np.transpose(vt, [0, 2, 1]), | |
| np.matmul(id_fix, | |
| np.transpose(u, [0, 2, 1]))) | |
| r = r * (1.0 - err_det_mask) + r_fix * err_det_mask | |
| return r, np.matmul(pose_global_parent, r) | |
| def single_child_rot(self, t, p, pose_global_parent, twist=None): | |
| """ | |
| t: B x 3 x 1 | |
| p: B x 3 x 1 | |
| pose_global_parent: B x 3 x 3 | |
| twist: B x 2 if given, default to None | |
| """ | |
| p_rot = np.matmul(np.linalg.inv(pose_global_parent), p) | |
| cross = np.cross(t, p_rot, axisa=1, axisb=1, axisc=1) | |
| sina = np.linalg.norm(cross, axis=1, keepdims=True) / (np.linalg.norm(t, axis=1, keepdims=True) * | |
| np.linalg.norm(p_rot, axis=1, keepdims=True)) | |
| cross = cross / np.linalg.norm(cross, axis=1, keepdims=True) | |
| cosa = np.sum(t * p_rot, axis=1, keepdims=True) / (np.linalg.norm(t, axis=1, keepdims=True) * | |
| np.linalg.norm(p_rot, axis=1, keepdims=True)) | |
| sina = np.reshape(sina, [-1, 1, 1]) | |
| cosa = np.reshape(cosa, [-1, 1, 1]) | |
| skew_sym_t = np.stack([0.0 * cross[:, 0], -cross[:, 2], cross[:, 1], | |
| cross[:, 2], 0.0 * cross[:, 0], -cross[:, 0], | |
| -cross[:, 1], cross[:, 0], 0.0 * cross[:, 0]], 1) | |
| skew_sym_t = np.reshape(skew_sym_t, [-1, 3, 3]) | |
| dsw_rotmat = np.reshape(np.eye(3), [1, 3, 3] | |
| ) + sina * skew_sym_t + (1.0 - cosa) * np.matmul(skew_sym_t, | |
| skew_sym_t) | |
| if twist is not None: | |
| skew_sym_t = np.stack([0.0 * t[:, 0], -t[:, 2], t[:, 1], | |
| t[:, 2], 0.0 * t[:, 0], -t[:, 0], | |
| -t[:, 1], t[:, 0], 0.0 * t[:, 0]], 1) | |
| skew_sym_t = np.reshape(skew_sym_t, [-1, 3, 3]) | |
| sina = np.reshape(twist[:, 1], [-1, 1, 1]) | |
| cosa = np.reshape(twist[:, 0], [-1, 1, 1]) | |
| dtw_rotmat = np.reshape(np.eye(3), [1, 3, 3] | |
| ) + sina * skew_sym_t + (1.0 - cosa) * np.matmul(skew_sym_t, | |
| skew_sym_t) | |
| dsw_rotmat = np.matmul(dsw_rotmat, dtw_rotmat) | |
| return dsw_rotmat, np.matmul(pose_global_parent, dsw_rotmat) | |
| def __call__(self, joints, twist=None): | |
| """ | |
| joints: B x N x 3 | |
| twist: B x N x 2 if given, default to None | |
| """ | |
| expand_dim = False | |
| if len(joints.shape) == 2: | |
| expand_dim = True | |
| joints = np.expand_dims(joints, 0) | |
| if twist is not None: | |
| twist = np.expand_dims(twist, 0) | |
| assert (len(joints.shape) == 3) | |
| batch_size = np.shape(joints)[0] | |
| joints_rel = joints - joints[:, self.parents] | |
| joints_hybrik = 0.0 * joints_rel | |
| pose_global = np.zeros([batch_size, self.num_nodes, 3, 3]) | |
| pose = np.zeros([batch_size, self.num_nodes, 3, 3]) | |
| for i in range(self.num_nodes): | |
| if i == 0: | |
| joints_hybrik[:, 0] = joints[:, 0] | |
| else: | |
| joints_hybrik[:, i] = np.matmul(pose_global[:, self.parents[i]], | |
| np.reshape(self.bones[i], [1, 3, 1])).reshape(-1, 3) + \ | |
| joints_hybrik[:, self.parents[i]] | |
| if self.child[i] == -2: | |
| pose[:, i] = pose[:, i] + np.eye(3).reshape(1, 3, 3) | |
| pose_global[:, i] = pose_global[:, self.parents[i]] | |
| continue | |
| if i == 0: | |
| r, rg = self.multi_child_rot(np.transpose(self.bones[[1, 2, 3]].reshape(1, 3, 3), [0, 2, 1]), | |
| np.transpose(joints_rel[:, [1, 2, 3]], [0, 2, 1]), | |
| np.eye(3).reshape(1, 3, 3)) | |
| elif i == 9: | |
| r, rg = self.multi_child_rot(np.transpose(self.bones[[12, 13, 14]].reshape(1, 3, 3), [0, 2, 1]), | |
| np.transpose(joints_rel[:, [12, 13, 14]], [0, 2, 1]), | |
| pose_global[:, self.parents[9]]) | |
| else: | |
| p = joints_rel[:, self.child[i]] | |
| if self.naive_hybrik[i] == 0: | |
| p = joints[:, self.child[i]] - joints_hybrik[:, i] | |
| twi = None | |
| if twist is not None: | |
| twi = twist[:, i] | |
| r, rg = self.single_child_rot(self.bones[self.child[i]].reshape(1, 3, 1), | |
| p.reshape(-1, 3, 1), | |
| pose_global[:, self.parents[i]], | |
| twi) | |
| pose[:, i] = r | |
| pose_global[:, i] = rg | |
| if expand_dim: | |
| pose = pose[0] | |
| return pose | |
| if __name__ == "__main__": | |
| jts2rot_hybrik = HybrIKJointsToRotmat() | |
| joints = np.array(SMPL_BODY_BONES).reshape(1, 24, 3)[:, :22] | |
| parents = [0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 9, 12, 13, 14, 16, 17, 18, 19] | |
| for i in range(1, 22): | |
| joints[:, i] = joints[:, i] + joints[:, parents[i]] | |
| pose = jts2rot_hybrik(joints) | |
| print(pose) | |