Method loss_smpl_pose

models/aios/criterion_smplx.py:1141–1193

(self, outputs, targets, indices, idx, num_boxes,
                       data_batch, face_hand_kpt=False)

        return losses

    def loss_smpl_pose(self, outputs, targets, indices, idx, num_boxes,
                       data_batch, face_hand_kpt=False):
        indices = indices[0]
        device = outputs['pred_logits'].device

        pred_smpl_body_pose = outputs['pred_smpl_pose'][idx] # 22
        pred_smpl_lhand_pose = outputs['pred_smpl_lhand_pose'][idx] # 15
        pred_smpl_rhand_pose = outputs['pred_smpl_rhand_pose'][idx] # 15
        pred_smpl_jaw_pose = outputs['pred_smpl_jaw_pose'][idx]

        pred_smplx_pose = torch.cat((pred_smpl_body_pose, pred_smpl_lhand_pose,
                                     pred_smpl_rhand_pose, pred_smpl_jaw_pose),
                                    dim=1)

        targets_smpl_pose = torch.cat(
            [t[i] for t, (_, i) in zip(data_batch['smplx_pose'], indices)],
            dim=0)
        targets_smpl_pose = batch_rodrigues(targets_smpl_pose.view(
            -1, 3)).view(-1, 53, 3, 3)
        conf = torch.cat([
            t[i] for t, (_, i) in zip(data_batch['smplx_pose_valid'], indices)
            ], dim=0)
        body_pose_valid = conf[:, :22].sum(-1) > 0
        lhand_pose_valid = conf[:, 22:37].sum(-1) > 0
        rhand_pose_valid = conf[:, 37:52].sum(-1) > 0
        face_pose_valid = conf[:, 52].sum(-1) > 0
        
        losses = {}
        loss_smpl_pose = \
            F.l1_loss(
                pred_smplx_pose,
                targets_smpl_pose,
                reduction='none'
            )
        loss_smpl_pose = loss_smpl_pose.sum([-1,-2]) * conf

        if face_hand_kpt:
            losses = {
                'loss_smpl_pose_root': loss_smpl_pose[:, 0].sum() / (body_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_body': loss_smpl_pose[:, 1:22].sum() / (body_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_lhand': loss_smpl_pose[:, 22:37].sum() / (lhand_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_rhand': loss_smpl_pose[:, 37:52].sum() / (rhand_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_jaw': loss_smpl_pose[:, 52].sum() / (face_pose_valid.sum() + 1e-6),
            }
        else:
            losses = {
                'loss_smpl_pose_root': loss_smpl_pose[:, 0].sum() / (body_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_body': loss_smpl_pose[:, 1:22].sum() / (body_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_lhand': 0 * loss_smpl_pose[:, 22:37].sum()/(lhand_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_rhand': 0 * loss_smpl_pose[:, 37:52].sum() / (rhand_pose_valid.sum() + 1e-6),
                'loss_smpl_pose_jaw': 0*loss_smpl_pose[:, 52].sum() / (face_pose_valid.sum() + 1e-6),
            }
        return losses

    def loss_smpl_beta(self, outputs, targets, indices, idx, num_boxes,
                       data_batch, face_hand_kpt=False):