Perform evaluation on the FlyingChairs (test) split
(model)
| 25 | |
| 26 | @torch.no_grad() |
| 27 | def validate_chairs(model): |
| 28 | """ Perform evaluation on the FlyingChairs (test) split """ |
| 29 | model.eval() |
| 30 | epe_list = [] |
| 31 | |
| 32 | val_dataset = datasets.FlyingChairs(split='validation') |
| 33 | for val_id in range(len(val_dataset)): |
| 34 | image1, image2, flow_gt, _ = val_dataset[val_id] |
| 35 | image1 = image1[None].cuda() |
| 36 | image2 = image2[None].cuda() |
| 37 | flow_pre, _ = model(image1, image2) |
| 38 | |
| 39 | epe = torch.sum((flow_pre[0].cpu() - flow_gt)**2, dim=0).sqrt() |
| 40 | epe_list.append(epe.view(-1).numpy()) |
| 41 | |
| 42 | epe = np.mean(np.concatenate(epe_list)) |
| 43 | print("Validation Chairs EPE: %f" % epe) |
| 44 | return {'chairs': epe} |
| 45 | |
| 46 | |
| 47 | @torch.no_grad() |
no outgoing calls
no test coverage detected