P10.Transforms的使用（二）

10.1为什么需要Tensor数据类型

1.通过transforms.ToTensor去看两个问题：

①transforms的使用（pytorch)；②为什么需要ToTensor数据类型。

2.为什么需要ToTensor数据类型？

因为他包装了我们反向神经网络所需要的理论基础的参数

点击查看代码

from PIL import Image
from torch.utils.tensorboard import SummaryWriter
from torchvision import transforms
# python的语法--tensor的数据类型
# 通过transforms.ToTensor去看两个问题
# 1.transforms的使用（pytorch)
# 2.为什么需要ToTensor数据类型
img_path = "Data_antbee/hymenoptera_data/train/ants_img/0013035.jpg"
img = Image.open(img_path)
print(img)
# 1.transforms的使用（pytorch)
#img_tensor = transforms.ToTensor(img)错误，他是类不是函数，应该先创建实例再调用
tensor_trans = transforms.ToTensor()  #创建实例
#ToTensor是类，相当于一个工具的模板（即工厂的模具），而tensor_trans相当于一个具体的工具
img_tensor = tensor_trans(img)
#调用实例（这一步相当于使用工具）

输出结果如下：

点击查看代码

D:\anaconda3\envs\pytorch\python.exe D:/DeepLearning/Learn_torch/P9_Transform.py
<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=768x512 at 0x2A2DB8B74C0>

进程已结束,退出代码0

3.ToTensor类

10.2Transforms使用

1.PIL转换成tensor格式

之前是将PIL格式的照片转换为numpy.array格式，这次是PIL转换成tensor格式

2.通过add_image()将tensor格式的照片在tensorboard上打开

代码如下：

点击查看代码

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

img_path = "Data_antbee/hymenoptera_data/train/ants_img/0013035.jpg"
img = Image.open(img_path)
print(img)

tensor_trans = transforms.ToTensor()  
img_tensor = tensor_trans(img)

writer = SummaryWriter("log")  
writer.add_image("img_tensor",img_tensor)

print(img_tensor)
writer.close()

输出结果如下：

点击查看代码

D:\anaconda3\envs\pytorch\python.exe D:/DeepLearning/Learn_torch/P9_Transform.py
<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=768x512 at 0x1A291B2A3A0>
tensor([[[0.3137, 0.3137, 0.3137,  ..., 0.3176, 0.3098, 0.2980],
         [0.3176, 0.3176, 0.3176,  ..., 0.3176, 0.3098, 0.2980],
         [0.3216, 0.3216, 0.3216,  ..., 0.3137, 0.3098, 0.3020],
         ...,
         [0.3412, 0.3412, 0.3373,  ..., 0.1725, 0.3725, 0.3529],
         [0.3412, 0.3412, 0.3373,  ..., 0.3294, 0.3529, 0.3294],
         [0.3412, 0.3412, 0.3373,  ..., 0.3098, 0.3059, 0.3294]],

        [[0.5922, 0.5922, 0.5922,  ..., 0.5961, 0.5882, 0.5765],
         [0.5961, 0.5961, 0.5961,  ..., 0.5961, 0.5882, 0.5765],
         [0.6000, 0.6000, 0.6000,  ..., 0.5922, 0.5882, 0.5804],
         ...,
         [0.6275, 0.6275, 0.6235,  ..., 0.3608, 0.6196, 0.6157],
         [0.6275, 0.6275, 0.6235,  ..., 0.5765, 0.6275, 0.5961],
         [0.6275, 0.6275, 0.6235,  ..., 0.6275, 0.6235, 0.6314]],

        [[0.9137, 0.9137, 0.9137,  ..., 0.9176, 0.9098, 0.8980],
         [0.9176, 0.9176, 0.9176,  ..., 0.9176, 0.9098, 0.8980],
         [0.9216, 0.9216, 0.9216,  ..., 0.9137, 0.9098, 0.9020],
         ...,
         [0.9294, 0.9294, 0.9255,  ..., 0.5529, 0.9216, 0.8941],
         [0.9294, 0.9294, 0.9255,  ..., 0.8863, 1.0000, 0.9137],
         [0.9294, 0.9294, 0.9255,  ..., 0.9490, 0.9804, 0.9137]]])

进程已结束,退出代码0