Image Resizer.

image_resizer.py

#!/usr/bin/env python
# coding: utf-8

# Run this from the directory where you see data/.
# %%sh
# ls -F
# data/

# Also create directory data_resized with test and train subdirectories
# %%sh
# ls -F
# data/
# data_resized/

# Install the python-resize-image package
# `pip install python-resize-image`

from PIL import Image
from resizeimage import resizeimage

import os


def resize_image(directory, image_name, new_directory, new_dims=[256, 256]):
    with open(directory + image_name, 'r+b') as f:
        with Image.open(f) as image:
            cover = resizeimage.resize_cover(image, new_dims)
            cover.save(new_directory + image_name, image.format)


def resize_images_into_new_directory(old_directory, new_directory):
    for image_name in os.listdir(old_directory):
        resize_image(old_directory, image_name, new_directory)


old_train_directory = 'data/train/'
old_test_directory = 'data/test/'
new_train_directory = 'data_resized/train/'
new_test_directory = 'data_resized/test/'


# Resize train data
resize_images_into_new_directory(old_train_directory, new_train_directory)

# Resize test data
resize_images_into_new_directory(old_test_directory, new_test_directory)

# Depending on your system configuration this can take quite a lot of time. 
# On my machine (16 GB RAM, I5 8th gen processor), I was able to resize about 1800 images per minute.