Pads images such that dimensions are divisible by 8
| 30 | TRAIN_SIZE = [432, 960] |
| 31 | |
| 32 | class InputPadder: |
| 33 | """ Pads images such that dimensions are divisible by 8 """ |
| 34 | def __init__(self, dims, mode='sintel'): |
| 35 | self.ht, self.wd = dims[-2:] |
| 36 | pad_ht = (((self.ht // 8) + 1) * 8 - self.ht) % 8 |
| 37 | pad_wd = (((self.wd // 8) + 1) * 8 - self.wd) % 8 |
| 38 | if mode == 'sintel': |
| 39 | self._pad = [pad_wd//2, pad_wd - pad_wd//2, pad_ht//2, pad_ht - pad_ht//2] |
| 40 | elif mode == 'kitti432': |
| 41 | self._pad = [0, 0, 0, 432 - self.ht] |
| 42 | elif mode == 'kitti400': |
| 43 | self._pad = [0, 0, 0, 400 - self.ht] |
| 44 | elif mode == 'kitti376': |
| 45 | self._pad = [0, 0, 0, 376 - self.ht] |
| 46 | else: |
| 47 | self._pad = [pad_wd//2, pad_wd - pad_wd//2, 0, pad_ht] |
| 48 | |
| 49 | def pad(self, *inputs): |
| 50 | return [F.pad(x, self._pad, mode='constant', value=0.0) for x in inputs] |
| 51 | |
| 52 | def unpad(self,x): |
| 53 | ht, wd = x.shape[-2:] |
| 54 | c = [self._pad[2], ht-self._pad[3], self._pad[0], wd-self._pad[1]] |
| 55 | return x[..., c[0]:c[1], c[2]:c[3]] |
| 56 | |
| 57 | def compute_grid_indices(image_shape, patch_size=TRAIN_SIZE, min_overlap=20): |
| 58 | if min_overlap >= patch_size[0] or min_overlap >= patch_size[1]: |
nothing calls this directly
no outgoing calls
no test coverage detected