import cv2
from torch.utils.data import Dataset
from PIL import Image
import os
import matplotlib.pyplot as plt


class MyData(Dataset):
    # 初始化 root_dir大的路径和label_dir具体内容/获取地址
    def __init__(self, root_dir, label_dir):
        # 创建全局变量
        self.root_dir = root_dir
        self.label_dir = label_dir
        # 获取一个路径地址 join()作用为拼接地址
        self.path = os.path.join(self.root_dir + "/" + self.label_dir).replace("jpg", "png")
        # bmp
        # self.path = os.path.join(self.root_dir + "/" + self.label_dir).replace("bmp", "png")
        # 获取路径下的所有列表
        self.img_path = os.listdir(self.path)
        print(self.img_path)
        print("ok")

    # idex作为一个编号
    def __getitem__(self, idx):
        # 读取其中的一个图片
        img_name = self.img_path[idx]
        print(img_name)
        # 程序的相对路径
        img_iten_path = os.path.join(self.root_dir, self.label_dir, img_name)
        # 图片打开
        img = Image.open(img_iten_path)
        # 160 x120 == 640x480
        # new_img = img.resize((640, 480))

        # 256x256 == 1024 x1024
        # new_img = img.resize((1024, 1024))

        # 320x240 == 1280 x960
        # new_img = img.resize((1280, 960))

        # 384x288 == 1536x1152
        # new_img = img.resize((1536, 1152))

        # 640x480 == 2560 x1920
        # new_img = img.resize((2560, 1920))

        # 640x512 == 2560 x2048
        # new_img=img.resize((2560, 2048))

        # 1280 x1024 == 5120 x4196
        new_img = img.resize((5120, 4196))

        # 要保存的图片
        # 160x120 == 640x480
        # if not os.path.exists("../opencv/tu/480/"):
        #     os.mkdir("../opencv/tu/480/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/480/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 256x256 == 1024x1024
        # if not os.path.exists("../opencv/tu/1024/"):
        #     os.mkdir("../opencv/tu/1024/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/1024/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 320x240 == 1280x960
        # if not os.path.exists("../opencv/tu/960/"):
        #     os.mkdir("../opencv/tu/960/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/960/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 384x288 == 1536x1152
        # if not os.path.exists("../opencv/tu/1152/"):
        #     os.mkdir("../opencv/tu/1152/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/1152/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 640x480 == 2560x1920
        # if not os.path.exists("../opencv/tu/1920/"):
        #     os.mkdir("../opencv/tu/1920/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/1920/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 640x512 == 2560 x2048
        # if not os.path.exists("../opencv/tu/2048/"):
        #     os.mkdir("../opencv/tu/2048/")
        #     print("目录已经创建")
        # new_img.save("../opencv/tu/2048/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 1280x1024 == 5120x4196
        if not os.path.exists("../opencv/tu/1024/"):
            os.mkdir("../opencv/tu/1024/")
            print("目录已经创建")
        new_img.save("../opencv/tu/1024/" + img_name.replace("jpg", "png").replace("bmp", "png"))

        # 它的一个文件
        label = self.label_dir
        return img, label

    # 返回列表的一个长度
    def __len__(self):
        return len(self.img_path)


# 数据集路径
root_dir = "./tu"
# 路径要处理的图片
# 160x120==640x480
# low_label_dir="160x120"

# 256x256 == 1024 x1024
# low_label_dir="256x256"

# 320x240 == 1280 x960
# low_label_dir="320x240"

# 384x288==1536x1152
# low_label_dir="384x288"

# 640x480==2560x1920
# low_label_dir="640x480"

# 640x512==2560x2048
# low_label_dir="640x512"

# 1280x1024==5120x4196
low_label_dir = "1280x1024"
# 低分辩的数据集
low_dataset = MyData(root_dir, low_label_dir)
print("图片数量：", len(low_dataset))

for x in low_dataset:
    img, label = x

上面可根据自己需要更改，代码懒优化了就复制粘贴了，需要用到的路径和大小，不要的可以删除。这个是根据B站代码进行学习，然后做的修改B站的up主是小土堆，有兴趣的可以去b站学习一下，内容还是讲的非常细致的