download tiny-ImageNet using `datasets` and save as ImageNet train/test split with individual categorical sub-directory

tiny_ImageNet_download.py

from datasets import load_dataset
import os
from PIL import Image
from tqdm import tqdm

os.makedirs("train", exist_ok=True)
os.chdir("train")
tiny_imagenet = load_dataset('Maysee/tiny-imagenet', split='train')

size = 100000
for i in tqdm(range(size)):
    img = tiny_imagenet[i]['image']
    label = tiny_imagenet[i]['label']
    os.makedirs(str(label), exist_ok=True)
    img.save(f"{label}/{i}.jpg")

os.chdir("../")
os.makedirs("val", exist_ok=True)
os.chdir("val")

tiny_imagenet = load_dataset('Maysee/tiny-imagenet', split='valid')

size = 10000
for i in tqdm(range(size)):
    img = tiny_imagenet[i]['image']
    label = tiny_imagenet[i]['label']
    os.makedirs(str(label), exist_ok=True)
    img.save(f"{label}/{i}.jpg")