File size: 1,388 Bytes
15bc41b |
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 |
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
from torch.autograd import Variable
import numpy as np
import torch.nn.functional as F
from manopth.manolayer import ManoLayer
def create_mano_layers(mano_path, device, n_cmps):
class Output:
def __init__(self, vertices, joints):
self.vertices = vertices
self.joints = joints
class SmplxAdapter:
def __init__(self, side):
self.m = ManoLayer(mano_root=f'{mano_path}/mano', use_pca=True, ncomps=n_cmps, side=side, flat_hand_mean=False, robust_rot=True).to(device)
self.faces = self.m.th_faces.cpu().numpy()
self.shapedirs = self.m.th_shapedirs
def __call__(self, global_orient, hand_pose, betas, transl):
vertices, joints = self.m(torch.cat([global_orient, hand_pose], 1), betas, transl)
vertices /= 1000
joints /= 1000
return Output(vertices, joints)
mano_layer = {
'left': SmplxAdapter(side='left'),
'right': SmplxAdapter(side='right')
}
if torch.sum(torch.abs(mano_layer['left'].m.th_shapedirs[:,0,:] - mano_layer['right'].m.th_shapedirs[:,0,:])) < 1:
print('Fix th_shapedirs bug of MANO')
mano_layer['left'].m.th_shapedirs[:,0,:] *= -1
return mano_layer
|