Normalize pixel values and pad to a square input.
(
x,
pixel_mean=torch.Tensor([123.675, 116.28, 103.53]).view(-1, 1, 1),
pixel_std=torch.Tensor([58.395, 57.12, 57.375]).view(-1, 1, 1),
img_size=1024,
)
| 51 | |
| 52 | |
| 53 | def preprocess( |
| 54 | x, |
| 55 | pixel_mean=torch.Tensor([123.675, 116.28, 103.53]).view(-1, 1, 1), |
| 56 | pixel_std=torch.Tensor([58.395, 57.12, 57.375]).view(-1, 1, 1), |
| 57 | img_size=1024, |
| 58 | ) -> torch.Tensor: |
| 59 | """Normalize pixel values and pad to a square input.""" |
| 60 | # Normalize colors |
| 61 | x = (x - pixel_mean) / pixel_std |
| 62 | # Pad |
| 63 | h, w = x.shape[-2:] |
| 64 | padh = img_size - h |
| 65 | padw = img_size - w |
| 66 | x = F.pad(x, (0, padw, 0, padh)) |
| 67 | return x |
| 68 | |
| 69 | |
| 70 | args = parse_args(sys.argv[1:]) |