(self, x, x_1)
| 21 | ) |
| 22 | |
| 23 | def forward(self, x, x_1): |
| 24 | N, T, V,_ = x.size() |
| 25 | x_in = torch.cat((x, x_1), -1) |
| 26 | x_in = x_in.view(N, -1) |
| 27 | |
| 28 | score = self.post_refine(x_in).view(N,T,V,2) |
| 29 | score_cm = Variable(torch.ones(score.size()), requires_grad=False).cuda() - score |
| 30 | x_out = x.clone() |
| 31 | x_out[:, :, :, :2] = score * x[:, :, :, :2] + score_cm * x_1[:, :, :, :2] |
| 32 | |
| 33 | return x_out |
| 34 | |
| 35 | |
| 36 | def get_uvd2xyz(uvd, gt_3D, cam): |
nothing calls this directly
no outgoing calls
no test coverage detected