import os

from dassl.data.datasets import DATASET_REGISTRY, Datum, DatasetBase

from .oxford_pets import OxfordPets
from .dtd import DescribableTextures as DTD
from .datasetbase import MYDatasetBase


@DATASET_REGISTRY.register()
class Food101(DatasetBase):

    dataset_dir = "Food101/food-101"

    def __init__(self, cfg):
        root = os.path.abspath(os.path.expanduser(cfg.DATASET.ROOT))
        self.dataset_dir = os.path.join(root, self.dataset_dir)
        self.image_dir = os.path.join(self.dataset_dir, "images")
        self.split_path = os.path.join(self.dataset_dir, "split_zhou_Food101.json")

        if os.path.exists(self.split_path):
            train, val, test = OxfordPets.read_split(self.split_path, self.image_dir)
        else:
            train, val, test = DTD.read_and_split_data(self.image_dir)
            OxfordPets.save_split(train, val, test, self.split_path, self.image_dir)

        num_shots = cfg.DATASET.NUM_SHOTS
        train = self.generate_fewshot_dataset(train, num_shots=num_shots)
        val = self.generate_fewshot_dataset(val, num_shots=min(num_shots, 4))

        super().__init__(train_x=train, val=val, test=test)


@DATASET_REGISTRY.register()
class MYFood101(MYDatasetBase):

    dataset_dir = "Food101/food-101"

    def __init__(self, cfg):
        root = os.path.abspath(os.path.expanduser(cfg.DATASET.ROOT))
        self.dataset_dir = os.path.join(root, self.dataset_dir)
        self.image_dir = os.path.join(self.dataset_dir, "images")
        self.split_path = os.path.join(self.dataset_dir, "split_zhou_Food101.json")

        if os.path.exists(self.split_path):
            train, val, test = self.read_split(self.split_path, self.image_dir)
        else:
            train, val, test = DTD.read_and_split_data(self.image_dir)
            OxfordPets.save_split(train, val, test, self.split_path, self.image_dir)

        mytrain = self.read_mytrain_data(self.split_path, self.image_dir)
        num_shots = cfg.DATASET.NUM_SHOTS
        train = self.generate_fewshot_dataset(train, num_shots=-1)
        val = self.generate_fewshot_dataset(val, num_shots=-1)
        super().__init__(train_x=train, val = val, test=test, mytrain=mytrain)