Pytorch中的BanderverticalFlip

初始化的第一个参数是p（可选默认：0.5-type：int或float）： *备忘录：
• 这是图像是否被翻转的可能性。
  • >
  必须为0

from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import RandomVerticalFlip

randomverticalflip = RandomVerticalFlip()
randomverticalflip = RandomVerticalFlip(p=0.5)

randomverticalflip
# RandomVerticalFlip(p=0.5)

randomverticalflip.p
# 0.5

origin_data = OxfordIIITPet(
    root="data",
    transform=None
    # transform=RandomVerticalFlip(p=0)
)

p1_data = OxfordIIITPet(
    root="data",
    transform=RandomVerticalFlip(p=1)
)

p05_data = OxfordIIITPet(
    root="data",
    transform=RandomVerticalFlip(p=0.5)
)

import matplotlib.pyplot as plt

def show_images1(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_images1(data=origin_data, main_title="origin_data")
print()
show_images1(data=p1_data, main_title="p1_data")
show_images1(data=p1_data, main_title="p1_data")
show_images1(data=p1_data, main_title="p1_data")
print()
show_images1(data=p05_data, main_title="p05_data")
show_images1(data=p05_data, main_title="p05_data")
show_images1(data=p05_data, main_title="p05_data")

# ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓
def show_images2(data, main_title=None, prob=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)
        rvf = RandomVerticalFlip(p=prob)
        plt.imshow(X=rvf(im))
        plt.xticks(ticks=[])
        plt.yticks(ticks=[])
    plt.tight_layout()
    plt.show()

show_images2(data=origin_data, main_title="origin_data")
print()
show_images2(data=origin_data, main_title="p1_data", prob=1)
show_images2(data=origin_data, main_title="p1_data", prob=1)
show_images2(data=origin_data, main_title="p1_data", prob=1)
print()
show_images2(data=origin_data, main_title="p1_data", prob=0.5)
show_images2(data=origin_data, main_title="p1_data", prob=0.5)
show_images2(data=origin_data, main_title="p1_data", prob=0.5)

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