import torch
from torch.utils.data import Dataset
from torchvision import transforms
from PIL import Image
tf=transforms.Compose([
    transforms.ToTensor()
])

class MyDataset(Dataset):
    def __init__(self,root):
        f=open(root,'r')
        self.dataset=f.readlines()
    def __len__(self):
        return len(self.dataset)
    def __getitem__(self, index):
        data=self.dataset[index]
        img_path=data.split(' ')[0]
        img_data=Image.open(img_path)
        points=data.split(' ')[1:-2]
        points=[int(i)/100 for i in points]

        return tf(img_data),torch.Tensor(points)


if __name__ == '__main__':
    data=MyDataset('data_center.txt')
    for i in data:
        print(i[0].shape)
        print(i[1].shape)