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38b191e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 | #!/usr/bin/env python3
import torch
import os
import numpy as np
import trimesh
from common.utils.utils_hand import batch_euler2matzxy, coordtrans
from kornia.geometry.conversions import axis_angle_to_rotation_matrix, quaternion_to_rotation_matrix, euler_from_quaternion, rotation_matrix_to_quaternion, quaternion_from_euler, rotation_matrix_to_axis_angle
euler_coordtrans_RIGHT = np.array([
[ 15, -6, 10,
15, 1, -5,
15, -15, 0,
0, 20, 2,
0, 10, -2,
0, 10, 10,
15, 25, 10,
10, 37, 8,
7, 35, 8,
0, 12, 5,
0, 25, -5,
0, 25, 15,
-30, -75, -35,
-30, -45, -30,
-30, -45, -30]]) / 180 * np.pi
euler_coordtrans_LEFT = np.array([
[ 15, 6, -10,
15, -1, 5,
15, 15, 0,
0, -20, -2,
0, -10, 2,
0, -10, -10,
15, -25, -10,
10, -37, -8,
7, -35, -8,
0, -12, -5,
0, -25, 5,
0, -25, -15,
-30, 75, 35,
-30, 45, 30,
-30, 45, 30]]) / 180 * np.pi
# range of motion
BOF_RIGHT = np.array([
[
0, -30, -40, # index0
0, 0, 0, # index1
0, 0, -5, # index2
0, -22.5, -40, # middle0
0, 0, 0, # middle1
0, 0, -5, # middle2
0, -25, -40, # pinky0
0, 0, 0, # pinky1
0, 0, -5, # pinky2
0, -22.5, -40, # ring0
0, 0, 0, # ring1
0, 0, -5, # ring2
-180, -60, -15, # thumb0
-180,-5, -180, # thumb1
-180, -5, -10], # thumb0
# MAX VALUES
[
0, 30, 90, # index0
0, 0, 110, # index1
0, 0, 90, # index2
0, 22.5, 90, # middle0
0, 0, 110, # middle1
0, 0, 90, # middle2
0, 25, 90, # pinky0
0, 0, 135, # pinky1
0, 0, 90, # pinky2
0, 22.5, 90, # ring0
0, 0, 120, # ring1
0, 0, 90, # ring2
180, 60, 90, # thumb0
180, 5, 80, # thumb1
180, 5, 80]])
BOF_LEFT = np.array([
[
0, -30, -90, # index0
0, 0,-110, # index1
0, 0, -90, # index2
0, -22.5, -90, # middle0
0, 0, -110, # middle1
0, 0, -90, # middle2
0, -25, -90, # pinky0
0, 0, -135, # pinky1
0, 0, -90, # pinky2
0, -22.5, -90, # ring0
0, 0, -120, # ring1
0, 0, -90, # ring2
-180, -60, -90, # thumb0
-180, -5, -80, # thumb1
-180, -5, -80], # thumb2
[
0, 30, 40, # index0
0, 0, 0, # index1
0, 0, 5, # index2
0, 22.5, 40, # middle0
0, 0, 0, # middle1
0, 0, 5, # middle2
0, 25, 40, # pinky0
0, 0, 0, # pinky1
0, 0, 5, # pinky2
0, 22.5, 40, # ring0
0, 0, 0, # ring1
0, 0, 5, # ring2
180, 60, 15, # thumb0
180, 5, 180, # thumb1
180, 5, 10], # thumb2
])
def do_clipping(input_angles, side, rotation_type):
device = input_angles.device
if side == "LEFT":
max = torch.tensor(BOF_LEFT[1,:], dtype=torch.float32).reshape(15,3).to(device)
min = torch.tensor(BOF_LEFT[0,:], dtype=torch.float32).reshape(15,3).to(device)
min_np = torch.deg2rad(min) # shape (N, 3)
max_np = torch.deg2rad(max)
elif side == "RIGHT":
max = torch.tensor(BOF_RIGHT[1,:], dtype=torch.float32).reshape(15,3).to(device)
min = torch.tensor(BOF_RIGHT[0,:], dtype=torch.float32).reshape(15,3).to(device)
min_np = torch.deg2rad(min) # shape (N, 3)
max_np = torch.deg2rad(max)
input_angles = input_angles.reshape(-1,15,3)
B, J, N = input_angles.shape
if rotation_type == "quat":
org_mats = quaternion_to_rotation_matrix(input_angles).float()
elif rotation_type == "aa":
org_mats = axis_angle_to_rotation_matrix(input_angles.reshape(-1, 3)).float()
if len(org_mats.shape)!=4:
org_mats = org_mats.unsqueeze(0)
rotmat_mano = org_mats.clone()
rotmat_mano = rotmat_mano.view(-1,15,3,3)
name = f"euler_coordtrans_{side.upper()}"
mat = globals()[name]
local2global = torch.from_numpy(mat).type(torch.float32).to(device)
local2global = batch_euler2matzxy(local2global.view(-1,3)).view(-1,15,3,3).expand(1,-1,-1,-1)
anatom_space_mats = coordtrans(rotmat_mano, local2global, 0)
mat_to_quat = rotation_matrix_to_quaternion(anatom_space_mats)
roll, pitch, yaw = euler_from_quaternion(mat_to_quat[:, :, 0], mat_to_quat[:, :, 1], mat_to_quat[:, :, 2], mat_to_quat[:, :, 3])
euler_from_quat = torch.stack([roll, pitch, yaw], dim=-1) # shape (1, 15, 3)
euler_from_quat = torch.clip(euler_from_quat, min_np, max_np) # root joint is always zero
qw, qx, qy, qz = quaternion_from_euler(euler_from_quat[:,:, 0], euler_from_quat[:,:, 1], euler_from_quat[:,:, 2])
rots_anat = torch.stack([qw, qx, qy, qz], dim=-1) # shape (1, 15, 4)
anat_mats = quaternion_to_rotation_matrix(rots_anat)
corrected_mano_space = coordtrans(anat_mats, local2global, 1)
corrected_aa = rotation_matrix_to_axis_angle(corrected_mano_space).reshape(B, J*3)
return corrected_aa
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