image_path = '/home/org/19.bmp'
label_path = '/home/mask/19.png'
image = Image.open(image_path)
print(image.size)
label = Image.open(label_path)
plt.figure()
plt.subplot(2, 2, 1)
plt.imshow(image)
plt.subplot(2, 2, 2)
plt.imshow(label)
p = np.random.choice([0, 1])#在0，1二者中隨機取一個，
print(p)
transform = transforms.Compose([
    transforms.RandomHorizontalFlip(p),#指定是否翻轉
    transforms.ToTensor()
])
img = transform(image)
lab = transform(label)
unloader = transforms.ToPILImage()
img = unloader(img)
lab = unloader(lab)
# print(img.shape)
plt.subplot(2, 2, 3)
plt.imshow(img)
plt.subplot(2, 2, 4)
plt.imshow(lab)
plt.show()

from PIL import Image
import os.path as osp
import os
from torchvision.transforms import ToTensor
test_path = '../dataset/BSD500/images/test'
images_ls = os.listdir(test_path)
images_all_path = []
for image in images_ls:
    s_images_path = osp.join(test_path, image)
    images_all_path.append(s_images_path)
# print(images_all_path)
image = Image.open(images_all_path[0]).convert('YCbCr')
# image.show()
# print(image)
y, cb, cr = image.split()
print(y)
print(cb)
print(cr)
# y.show()
# cb.show()
image_to_tensor = ToTensor()
y = image_to_tensor(y)
print(y.shape)