prepare_tiny.py

import os

# Create separate validation subfolders for the validation images based on
# their labels indicated in the val_annotations txt file
DATA_DIR = '../tiny-imagenet-200' # Original images come in shapes of [3,64,64]
TRAIN_DIR = os.path.join(DATA_DIR, 'train')
VALID_DIR = os.path.join(DATA_DIR, 'val')

val_img_dir = os.path.join(VALID_DIR, 'images')

# Open and read val annotations text file
fp = open(os.path.join(VALID_DIR, 'val_annotations.txt'), 'r')
data = fp.readlines()

# Create dictionary to store img filename (word 0) and corresponding
# label (word 1) for every line in the txt file (as key value pair)
val_img_dict = {}
for line in data:
    words = line.split('\t')
    val_img_dict[words[0]] = words[1]
fp.close()

# Display first 10 entries of resulting val_img_dict dictionary
{k: val_img_dict[k] for k in list(val_img_dict)[:10]}

# Create subfolders (if not present) for validation images based on label,
# and move images into the respective folders
for img, folder in val_img_dict.items():
    newpath = (os.path.join(val_img_dir, folder))
    if not os.path.exists(newpath):
        os.makedirs(newpath)
    if os.path.exists(os.path.join(val_img_dir, img)):
        os.rename(os.path.join(val_img_dir, img), os.path.join(newpath, img))