import os
import datasets
import urllib.request
import csv

_CITATION = """\
@InProceedings{huggingface:dataset,
title = {diffusion train set},
}
"""

_DESCRIPTION = """\
This is a dataset that image data and caption txt
"""
_HOMEPAGE = ""

_LICENSE = ""

_URL = "./"

_URLS = {        
            "train": "/content/drive/MyDrive/",
            "reg": "/content/drive/MyDrive/",
            }


train = open("/content/drive/MyDrive/train_dataset.csv", "r")
train_reader = csv.DictReader(train)
# if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
#     os.makedirs(outpath)
for row in train_reader:
    class_name = f"{row['Class_name']}"
    file_name = f"{row['file_name']}"
    url = f"{row['file_id']}"
    path = os.path.join('./img',class_name,file_name)
    folder = os.path.join('./img',class_name)
    if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
        os.makedirs(folder)
    urllib.request.urlretrieve(url, path)

reg = open("/content/drive/MyDrive/reg_dataset.csv", "r")
reg_reader = csv.DictReader(reg)
# if not os.path.isdir(outpath): #폴더가 존재하지 않는다면 폴더 생성
#     os.makedirs(outpath)
for row in reg_reader:
    class_name = f"{row['Class_name']}"
    file_name = f"{row['file_name']}"
    url = f"{row['file_id']}"
    path = os.path.join('./reg',class_name,file_name)
    folder = os.path.join('./reg',class_name)
    if not os.path.isdir(folder): #폴더가 존재하지 않는다면 폴더 생성
        os.makedirs(folder)
    urllib.request.urlretrieve(url, path)