Pytorch学习日记——常见的Transforms（二）

学习视频——B站【小土堆】

代码

from PIL import Image
from torch.utils.tensorboard import SummaryWriter
from torchvision import transforms

writer = SummaryWriter("logs")
img = Image.open("dataset/train/0a7940e11293d1d4404c5c35065a56565d732c46_raw.jpg")
print(img)

# ToTensor使用
trans_totensor = transforms.ToTensor()
img_tensor = trans_totensor(img)
writer.add_image("ToTensor", img_tensor)

# Normalize归一化/规范化
print(img_tensor[0][0][0])
trans_norm = transforms.Normalize([1, 3, 5], [3, 2, 1])
img_norm = trans_norm(img_tensor)
print(img_norm[0][0][0])
writer.add_image("Normalize", img_norm, 1)

# 更改尺寸
print(img.size)
trans_resize = transforms.Resize((512,512))
# img PIL -> resize ->img_resize PIL
img_resize = trans_resize(img)
# img_resize PIL -> totensor -> img_resize totensor
img_resize = trans_totensor(img_resize)
writer.add_image('Resize', img_resize,0)
print(img_resize)

# compose - resize - 2
trans_resize_2 = transforms.Resize(512)
# PIL -> PIL -> tensor
trans_compose = transforms.Compose([trans_resize_2, trans_totensor])
img_resize_2 = trans_compose(img)
writer.add_image('Resize', img_resize_2, 1)



writer.close()

将图片缩小

结果：

 

 将图片等比缩小

结果：