Resize函数用于对PIL图像的预处理,它的包在: from torchvision.transforms import Compose, CenterCrop, ToTensor, Resize 使用如: def input_transform(crop_size, upscale_factor): return Compose([ CenterCrop(crop_size), Resiz
Resize函数用于对PIL图像的预处理,它的包在:
from torchvision.transforms import Compose, CenterCrop, ToTensor, Resize
使用如:
def input_transform(crop_size, upscale_factor): return Compose([ CenterCrop(crop_size), Resize(crop_size // upscale_factor), ToTensor(), ])
而Resize函数有两个参数,
CLASS torchvision.transforms.Resize(size, interpolation=2)
size (sequence or int) – Desired output size. If size is a sequence like (h, w), output size will be matched to this. If size is an int, smaller edge of the image will be matched to this number. i.e, if height > width, then image will be rescaled to (size * height / width, size)
interpolation (int, optional) – Desired interpolation. Default is PIL.Image.BILINEAR
size : 获取输出图像的大小
interpolation : 插值,默认的 PIL.Image.BILINEAR, 一共有4中的插值方法
Image.BICUBIC,PIL.Image.LANCZOS,PIL.Image.BILINEAR,PIL.Image.NEAREST
到此这篇关于pytorch之Resize()函数具体使用详解的文章就介绍到这了,更多相关pytorch Resize() 内容请搜索易盾网络以前的文章或继续浏览下面的相关文章希望大家以后多多支持易盾网络!