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# -*- 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: ps-license@tuebingen.mpg.de | |
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 | |