| 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 | |