pytorch学习笔记（2）--tensorforms

tensorform使用一：

from PIL import Image
from torch.utils.tensorboard import SummaryWriter
from torchvision import transforms
import cv2

# linux中的绝对路径
img_path = "/home/pinecone/PycharmProjects/pytorchProject/data/train/ants_image/0013035.jpg"
img = Image.open(img_path)

# 1 tensorform该如何使用
tensor_train = transforms.ToTensor()
tensor_img = tensor_train(img)

cv_img = cv2.imread(img_path)

writer = SummaryWriter("logs")

writer.add_image("Tensor_img", tensor_img)
writer.close()

print(img)
print(cv_img)

 2 ToTensor & Normalize

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


writer = SummaryWriter("logs")
img = Image.open("/home/pinecone/PycharmProjects/pytorchProject/data/train/ants_image/0013035.jpg")

# 1 ToTensor
trans_toTensor = transforms.ToTensor()
img_tensor = trans_toTensor(img)
writer.add_image("ToTensor", img_tensor)

# Normalize
print(img_tensor[0][0][0])
trans_norm = transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])
img_norm = trans_norm(img_tensor)
print(img_norm[0][0][0])
writer.add_image("Normalize", img_norm)

writer.close()

 

 3 Resize compose RandromCrop 同时注意可视化步骤显示

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


writer = SummaryWriter("logs")
img = Image.open("/home/pinecone/PycharmProjects/pytorchProject/data/train/ants_image/0013035.jpg")

# 1 ToTensor
trans_toTensor = transforms.ToTensor()
img_tensor = trans_toTensor(img)
writer.add_image("ToTensor", img_tensor)

# Normalize
trans_norm = transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])
img_norm = trans_norm(img_tensor)
writer.add_image("Normalize", img_norm)

# Resize
trans_resize = transforms.Resize((512, 512))
# img PIL -> resize -> img_size PIL
img_size = trans_resize(img)
# img_size PIL -> toTensor -> img_resize tensor
img_resize = trans_toTensor(img_size)
writer.add_image("Resize", img_resize, 0)

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

# RandomCrop
trans_random = transforms.RandomCrop((300, 400))
trans_compose_2 = transforms.Compose([trans_random, trans_toTensor])
for i in range(10):
    img_crop = trans_compose_2(img)
    writer.add_image("RandomCropHW", img_crop, i)

writer.close()