这是一个工具包，功能：反向操作transforms.Normalize和transforms.ToTensor函数，将tensor格式的图片转换成.jpg、.png格式的图片

（注：这里是我原始的写法，但是是存在着一些改进空间的【如评论区所言，会改变img_tensor的内容，但我这边就暂时保持原样了，详细的改进方法可见评论区】【感谢评论区大佬！】）

import torchimport numpy as npfrom PIL import Imageimport torchvision.transforms as transformsdef transform_convert(img_tensor, transform):"""param img_tensor: tensorparam transforms: torchvision.transforms"""if 'Normalize' in str(transform):normal_transform = list(filter(lambda x: isinstance(x, transforms.Normalize), transform.transforms))mean = torch.tensor(normal_transform[0].mean, dtype=img_tensor.dtype, device=img_tensor.device)std = torch.tensor(normal_transform[0].std, dtype=img_tensor.dtype, device=img_tensor.device)img_tensor.mul_(std[:,None,None]).add_(mean[:,None,None])img_tensor = img_tensor.transpose(0,2).transpose(0,1) # C x H x W ---> H x W x Cif 'ToTensor' in str(transform) or img_tensor.max() < 1:img_tensor = img_tensor.detach().numpy()*255if isinstance(img_tensor, torch.Tensor):img_tensor = img_tensor.numpy()if img_tensor.shape[2] == 3:img = Image.fromarray(img_tensor.astype('uint8')).convert('RGB')elif img_tensor.shape[2] == 1:img = Image.fromarray(img_tensor.astype('uint8')).squeeze()else:raise Exception("Invalid img shape, expected 1 or 3 in axis 2, but got {}!".format(img_tensor.shape[2]))return img

代码示例

import matplotlib.pyplot as pltimg = Image.open('./lena.jpg')ToTensor_transform = pose([transforms.ToTensor()])img_tensor = ToTensor_transform(img)img = transform_convert(img_tensor, ToTensor_transform)plt.imshow(img)plt.savefig('./lenaa.png')