Pytorch上下采样函数--interpolate

最新推荐文章于 2024-04-15 22:10:12 发布

Tra_cy

最新推荐文章于 2024-04-15 22:10:12 发布

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本文链接：https://blog.youkuaiyun.com/Tra_cy/article/details/104695826

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本文介绍了PyTorch中的interpolate函数，该函数用于实现图像的上采样和下采样操作。通过指定输入张量、输出尺寸、缩放因子和模式，可以灵活地进行不同方式的采样。默认模式为'nearest'，其他可用模式包括'linear'、'bilinear'等。示例展示了函数的用法及其结果。

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pytorch中使用interpolate可以很轻松的完成上采样和下采样。

官方文档
torch.nn.functional.interpolate(input, size=None, scale_factor=None, mode=‘nearest’, align_corners=None)
函数的参数如下：

input (Tensor) – the input tensor
size (int or Tuple[int] or Tuple[int, int] or Tuple[int, int, int]) – output spatial size.
scale_factor (float or Tuple[float]) – multiplier for spatial size. Has to match input size if it is a tuple.
mode (str) – algorithm used for upsampling: ‘nearest’ | ‘linear’ | ‘bilinear’ | ‘bicubic’ |‘trilinear’ | ‘area’. Default: ‘nearest’
align_corners (bool, optional) – Geometrically, we consider the pixels of the input and output as squares rather than points. If set to True, the input and output tensors are aligned by the center points of their corner pixels, preserving the values at the corner pixels. If set to False, the input and output tensors are aligned by the corner points of their corner pixels,