mmdet.models.utils.misc 源代码

from torch.nn import functional as F


[文档]def upsample_like(source, target, mode='bilinear', align_corners=False): """Upsample the source to the shape of the target. Upsample the source to the shape of target. The input must be a Tensor, but the target can be a Tensor or a np.ndarray with the shape (..., target_h, target_w). Args: source (Tensor): A 3D/4D Tensor with the shape (N, H, W) or (N, C, H, W). target (Tensor | np.ndarray): The upsampling target with the shape (..., target_h, target_w). mode (str): Algorithm used for upsampling. The options are the same as those in F.interpolate(). Default: ``'bilinear'``. align_corners (bool): The same as the argument in F.interpolate(). Returns: Tensor: The upsampled source Tensor. """ assert len(target.shape) >= 2 def _upsample_like(source, target, mode='bilinear', align_corners=False): """Upsample the source (4D) to the shape of the target.""" target_h, target_w = target.shape[-2:] source_h, source_w = source.shape[-2:] if target_h != source_h or target_w != source_w: source = F.interpolate( source, size=(target_h, target_w), mode=mode, align_corners=align_corners) return source if len(source.shape) == 3: source = source[:, None, :, :] source = _upsample_like(source, target, mode, align_corners) return source[:, 0, :, :] else: return _upsample_like(source, target, mode, align_corners)