| 21 | |
| 22 | |
| 23 | class LossTracking(Loss[LossTrackingCfg]): |
| 24 | def __init__(self, cfg: LossTrackingCfg) -> None: |
| 25 | super().__init__(cfg) |
| 26 | self.mapping = get_mapping(cfg.mapping) |
| 27 | |
| 28 | def compute_unweighted_loss( |
| 29 | self, |
| 30 | batch: Batch, |
| 31 | flows: Flows, |
| 32 | tracks: list[Tracks] | None, |
| 33 | model_output: ModelOutput, |
| 34 | global_step: int, |
| 35 | ) -> Float[Tensor, ""]: |
| 36 | # Tracks must be available for the tracking loss. |
| 37 | assert tracks is not None |
| 38 | |
| 39 | _, _, _, h, w = batch.videos.shape |
| 40 | |
| 41 | loss_sum = 0 |
| 42 | valid_sum = 0 |
| 43 | |
| 44 | for segment_tracks in tracks: |
| 45 | _, f, _, _ = segment_tracks.xy.shape |
| 46 | s = segment_tracks.start_frame |
| 47 | |
| 48 | xy_target, visibility = compute_track_flow( |
| 49 | model_output.surfaces[:, s : s + f], |
| 50 | model_output.extrinsics[:, s : s + f], |
| 51 | model_output.intrinsics[:, s : s + f], |
| 52 | segment_tracks, |
| 53 | ) |
| 54 | xy_target_gt = rearrange(segment_tracks.xy, "b ft p xy -> b () ft p xy") |
| 55 | |
| 56 | loss = self.mapping.forward(xy_target, xy_target_gt, (h, w)) * visibility |
| 57 | |
| 58 | loss_sum = loss_sum + loss.sum() |
| 59 | valid_sum = valid_sum + visibility.sum() |
| 60 | |
| 61 | return loss_sum / (valid_sum or 1) |
nothing calls this directly
no outgoing calls
no test coverage detected