Function reverse_mask

core/utils/utils.py:222–235

Input: mask: B x 1 x H x W torch.Tensor.cuda, represent the mask of A grid_map: B x H x W x 2 torch.Tensor.cuda, grid mapping from B to A Output: reverse_map: B x H x W x 2 torch.Tensor.cuda, grid mapping from A to B

(mask, grid_map)

    return reverse_map

def reverse_mask(mask, grid_map):
    '''
    Input:
        mask: B x 1 x H x W torch.Tensor.cuda, represent the mask of A
        grid_map: B x H x W x 2 torch.Tensor.cuda, grid mapping from B to A
    Output:
        reverse_map: B x H x W x 2 torch.Tensor.cuda, grid mapping from A to B
    '''
    _, H, W, _ = grid_map.shape
    grid_norm = grid_map.clone()
    grid_norm[:, :, :, 0] = (grid_norm[:, :, :, 0] * 2 - W + 1) / (W - 1)
    grid_norm[:, :, :, 1] = (grid_norm[:, :, :, 1] * 2 - H + 1) / (H - 1)
    reverse_mask = F.grid_sample(mask, grid_norm, align_corners=True).permute([0, 2, 3, 1])
    return reverse_mask

def refine_grid(grid):
    H, W, _ = grid.shape