Spaces:
Runtime error
Runtime error
| # -*- coding: utf-8 -*- | |
| # Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is | |
| # holder of all proprietary rights on this computer program. | |
| # You can only use this computer program if you have closed | |
| # a license agreement with MPG or you get the right to use the computer | |
| # program from someone who is authorized to grant you that right. | |
| # Any use of the computer program without a valid license is prohibited and | |
| # liable to prosecution. | |
| # | |
| # Copyright©2019 Max-Planck-Gesellschaft zur Förderung | |
| # der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute | |
| # for Intelligent Systems. All rights reserved. | |
| # | |
| # Contact: [email protected] | |
| from __future__ import absolute_import, division, print_function | |
| import numpy as np | |
| import torch | |
| import torch.nn as nn | |
| from .utils import to_tensor | |
| class VertexJointSelector(nn.Module): | |
| def __init__(self, vertex_ids=None, use_hands=True, use_feet_keypoints=True, **kwargs): | |
| super(VertexJointSelector, self).__init__() | |
| extra_joints_idxs = [] | |
| face_keyp_idxs = np.array( | |
| [ | |
| vertex_ids["nose"], | |
| vertex_ids["reye"], | |
| vertex_ids["leye"], | |
| vertex_ids["rear"], | |
| vertex_ids["lear"], | |
| ], | |
| dtype=np.int64, | |
| ) | |
| extra_joints_idxs = np.concatenate([extra_joints_idxs, face_keyp_idxs]) | |
| if use_feet_keypoints: | |
| feet_keyp_idxs = np.array( | |
| [ | |
| vertex_ids["LBigToe"], | |
| vertex_ids["LSmallToe"], | |
| vertex_ids["LHeel"], | |
| vertex_ids["RBigToe"], | |
| vertex_ids["RSmallToe"], | |
| vertex_ids["RHeel"], | |
| ], | |
| dtype=np.int32, | |
| ) | |
| extra_joints_idxs = np.concatenate([extra_joints_idxs, feet_keyp_idxs]) | |
| if use_hands: | |
| self.tip_names = ["thumb", "index", "middle", "ring", "pinky"] | |
| tips_idxs = [] | |
| for hand_id in ["l", "r"]: | |
| for tip_name in self.tip_names: | |
| tips_idxs.append(vertex_ids[hand_id + tip_name]) | |
| extra_joints_idxs = np.concatenate([extra_joints_idxs, tips_idxs]) | |
| self.register_buffer("extra_joints_idxs", to_tensor(extra_joints_idxs, dtype=torch.long)) | |
| def forward(self, vertices, joints): | |
| extra_joints = torch.index_select(vertices, 1, self.extra_joints_idxs) | |
| joints = torch.cat([joints, extra_joints], dim=1) | |
| return joints | |