| |
|
|
| from dataclasses import dataclass |
| from typing import Union |
| import torch |
|
|
|
|
| @dataclass |
| class DensePoseChartPredictorOutput: |
| """ |
| Predictor output that contains segmentation and inner coordinates predictions for predefined |
| body parts: |
| * coarse segmentation, a tensor of shape [N, K, Hout, Wout] |
| * fine segmentation, a tensor of shape [N, C, Hout, Wout] |
| * U coordinates, a tensor of shape [N, C, Hout, Wout] |
| * V coordinates, a tensor of shape [N, C, Hout, Wout] |
| where |
| - N is the number of instances |
| - K is the number of coarse segmentation channels ( |
| 2 = foreground / background, |
| 15 = one of 14 body parts / background) |
| - C is the number of fine segmentation channels ( |
| 24 fine body parts / background) |
| - Hout and Wout are height and width of predictions |
| """ |
|
|
| coarse_segm: torch.Tensor |
| fine_segm: torch.Tensor |
| u: torch.Tensor |
| v: torch.Tensor |
|
|
| def __len__(self): |
| """ |
| Number of instances (N) in the output |
| """ |
| return self.coarse_segm.size(0) |
|
|
| def __getitem__( |
| self, item: Union[int, slice, torch.BoolTensor] |
| ) -> "DensePoseChartPredictorOutput": |
| """ |
| Get outputs for the selected instance(s) |
| |
| Args: |
| item (int or slice or tensor): selected items |
| """ |
| if isinstance(item, int): |
| return DensePoseChartPredictorOutput( |
| coarse_segm=self.coarse_segm[item].unsqueeze(0), |
| fine_segm=self.fine_segm[item].unsqueeze(0), |
| u=self.u[item].unsqueeze(0), |
| v=self.v[item].unsqueeze(0), |
| ) |
| else: |
| return DensePoseChartPredictorOutput( |
| coarse_segm=self.coarse_segm[item], |
| fine_segm=self.fine_segm[item], |
| u=self.u[item], |
| v=self.v[item], |
| ) |
|
|
| def to(self, device: torch.device): |
| """ |
| Transfers all tensors to the given device |
| """ |
| coarse_segm = self.coarse_segm.to(device) |
| fine_segm = self.fine_segm.to(device) |
| u = self.u.to(device) |
| v = self.v.to(device) |
| return DensePoseChartPredictorOutput(coarse_segm=coarse_segm, fine_segm=fine_segm, u=u, v=v) |
|
|
