(img)
| 86 | |
| 87 | |
| 88 | def tensor_to_pil(img): |
| 89 | inv_mean = [-mean / std for mean, std in zip(cfg.DATASET.MEAN, |
| 90 | cfg.DATASET.STD)] |
| 91 | inv_std = [1 / std for std in cfg.DATASET.STD] |
| 92 | inv_normalize = standard_transforms.Normalize( |
| 93 | mean=inv_mean, std=inv_std |
| 94 | ) |
| 95 | img = inv_normalize(img) |
| 96 | img = img.cpu() |
| 97 | img = standard_transforms.ToPILImage()(img).convert('RGB') |
| 98 | return img |
| 99 | |
| 100 | |
| 101 | def eval_metrics(iou_acc, args, net, optim, val_loss, epoch, mf_score=None): |