import json

import cv2

from albumentations import Compose, Normalize

from albumentations.pytorch.transforms import ToTensorV2

from torch.utils.data import DataLoader, Dataset

augment = Compose([Normalize(), ToTensorV2()])

class EcgDataset2D(Dataset):

    def __init__(self, ann_path, mapping_path):

        super().__init__()

        self.data = json.load(open(ann_path))

        self.mapper = json.load(open(mapping_path))

    def __getitem__(self, index):

        img = cv2.imread(self.data[index]["path"])

        img = augment(**{"image": img})["image"]

        return {"image": img, "class": self.mapper[self.data[index]["label"]]}

    def get_dataloader(self, num_workers=4, batch_size=16, shuffle=True):

        data_loader = DataLoader(

            self, batch_size=batch_size, shuffle=shuffle, num_workers=num_workers,

        )

        return data_loader

    def __len__(self):

        return len(self.data)

def callback_get_label(dataset, idx):

    return dataset[idx]["class"]