import os
import math
import random
from collections import defaultdict
from .utils import Datum, DatasetBase, read_json, write_json, build_data_loader

import torch
import torchvision
import torchvision.transforms as transforms
from collections import OrderedDict


def read_classnames(text_file):
    """Return a dictionary containing
    key-value pairs of <folder name>: <class name>.
    """
    classnames = OrderedDict()
    with open(text_file, "r") as f:
        lines = f.readlines()
        for line in lines:
            line = line.strip().split(" ")
            folder = line[0]
            classname = " ".join(line[1:])
            classnames[folder] = classname
    return classnames

def listdir_nohidden(path, sort=False):
    """List non-hidden items in a directory.

    Args:
         path (str): directory path.
         sort (bool): sort the items.
    """
    items = [f for f in os.listdir(path) if not f.startswith(".")]
    if sort:
        items.sort()
    return items
class ImageNetSketch(DatasetBase):
    """ImageNet-Sketch.

    This dataset is used for testing only.
    """

    dataset_dir ="imagenet_sketch"

    def __init__(self, data_dir):
        root = data_dir
        self.dataset_dir = os.path.join(root, self.dataset_dir)
        self.image_dir = os.path.join(self.dataset_dir, 'images')


        text_file = os.path.join(self.dataset_dir, "classnames.txt")
        classnames = read_classnames(text_file)

        data = self.read_data(classnames)

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

    def read_data(self, classnames):
        image_dir = self.image_dir
        folders = listdir_nohidden(image_dir, sort=True)
        items = []

        for label, folder in enumerate(folders):
            imnames = listdir_nohidden(os.path.join(image_dir, folder))
            classname = classnames[folder]
            for imname in imnames:
                impath = os.path.join(image_dir, folder, imname)
                item = Datum(
                    impath=impath,
                    label=label,
                    classname=classname
                )
                items.append(item)

        return items