RandomCrop随机裁剪

最新推荐文章于 2025-04-24 07:30:00 发布

YLTommi

最新推荐文章于 2025-04-24 07:30:00 发布

阅读量744

点赞数 3

文章标签： pytorch 人工智能 python 神经网络机器学习

本文链接：https://blog.youkuaiyun.com/yangleileileilei/article/details/138612947

版权

# RandomCrop随机裁剪方式一
img_path = "D:/05深度学习笔记/Data/FirstTypeData/train/ants/0013035.jpg"
img = Image.open(img_path)
print(img)

writer = SummaryWriter("logs4")

trans_tensor = transforms.ToTensor()
img_tensor = trans_totensor(img)  # 转化为张量

trans_random = transforms.RandomCrop(312)  # 随即裁剪成 312×312
trans_compose_2 = transforms.Compose([trans_random, trans_tensor])
# Compose函数中后面一个参数的输入为前面一个参数的输出
writer.add_image("img_tensor", img_tensor)

for i in range(10):
    img_crop = trans_compose_2(img)
    writer.add_image("RandomCrop", img_crop, i)
    print(img_crop.size())

writer.close()

# RandomCrop随机裁剪方式二
img_path = "D:/05深度学习笔记/Data/FirstTypeData/train/ants/0013035.jpg"
img = Image.open(img_path)

writer = SummaryWriter("logs5")

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

trans_random = transforms.RandomCrop((312, 100))  # 指定随即裁剪的宽和高
trans_compose_3 = transforms.Compose([trans_random, trans_tensor])
for i in range(10):
    img_crop = trans_compose_3(img)
    writer.add_image("RandomCrop", img_crop, i)
    print(img_crop.size())

writer.close()