The max distance in Weighted Hausdorff Loss is not the actual max distance

[donguklim]

The maximum possible distance is calculated with resized image size.

https://github.com/javiribera/locating-objects-without-bboxes/blob/e51f75ec925f67bb4054ab4a6e9b20d1d8e689cc/object-locator/losses.py#L143

But this should be calculated with the original image size, as bellow code also calculates distances in the original image.

Bellow two lines need to be changed

https://github.com/javiribera/locating-objects-without-bboxes/blob/e51f75ec925f67bb4054ab4a6e9b20d1d8e689cc/object-locator/losses.py#L224

https://github.com/javiribera/locating-objects-without-bboxes/blob/e51f75ec925f67bb4054ab4a6e9b20d1d8e689cc/object-locator/losses.py#L204

Suggested change

            max_dist = (orig_size_b **2).sum().sqrt()
....
            # Corner case: no GT points
            if gt_b.ndimension() == 1 and (gt_b < 0).all().item() == 0:
                terms_1.append(torch.tensor([0],
                                            dtype=torch.get_default_dtype()))
                terms_2.append(torch.tensor([max_dist],
                                            dtype=torch.get_default_dtype()))
                continue
.....
            weighted_d_matrix = (1 - p_replicated)*max_dist  + p_replicated*d_matrix

I am sorry, too lazy to make pull request to fix it by myself now.