PyTorch 中的随机水平翻转

from torchvision.datasets import oxfordiiitpetfrom torchvision.transforms.v2 import randomhorizontalfliprandomhorizontalflip()# randomhorizontalflip(p=0.5)randomhorizontalflip().p# 0.5origin_data = oxfordiiitpet(    root="data",    transform=none)trans100_data = oxfordiiitpet(    root="data",    transform=randomhorizontalflip(p=1.0))trans50_data = oxfordiiitpet(    root="data",    transform=randomhorizontalflip(p=0.5))import matplotlib.pyplot as pltdef show_images(data, main_title=none):    plt.figure(figsize=(10, 5))    plt.suptitle(t=main_title, y=0.8, fontsize=14)    for i, (im, _) in zip(range(1, 6), data):        plt.subplot(1, 5, i)        plt.imshow(x=im)        plt.xticks(ticks=[])        plt.yticks(ticks=[])    plt.tight_layout()    plt.show()show_images(data=origin_data, main_title="origin_data")show_images(data=trans100_data, main_title="trans100_data")show_images(data=trans50_data, main_title="trans50_data")

from torchvision.datasets import OxfordIIITPetfrom torchvision.transforms.v2 import RandomHorizontalFlipmy_data = OxfordIIITPet(    root="data",    transform=None)import matplotlib.pyplot as pltdef show_images(data, main_title=None, prob=0.0):    plt.figure(figsize=(10, 5))    plt.suptitle(t=main_title, y=0.8, fontsize=14)    for i, (im, _) in zip(range(1, 6), data):        plt.subplot(1, 5, i)        rhf = RandomHorizontalFlip(p=prob)        plt.imshow(X=rhf(im))        plt.xticks(ticks=[])        plt.yticks(ticks=[])    plt.tight_layout()    plt.show()show_images(data=my_data, main_title="origin_data")show_images(data=my_data, main_title="trans100_data", prob=1.0)show_images(data=my_data, main_title="trans50_data", prob=0.5)