Post - Optimise Python code for data preparation using Concurrent features

compress.py

from PIL import Image
from io import BytesIO


def compress_image(image_file, max_size=4000, max_dim=150, dim_diff_w=0, dim_diff_h=0, orig_image_w=None, orig_image_h=None):
    print_values = {
        'max_size': max_size,
        'max_dim': max_dim,
        'dim_diff_w': dim_diff_w,
        'dim_diff_h': dim_diff_h,
        'orig_image_w': orig_image_w,
        'orig_image_h': orig_image_h,
    }
    print(print_values)

    orig_image = Image.open(image_file)
    orig_image_w, orig_image_h = orig_image.size

    if orig_image_w > max_dim:
        dim_diff_w = orig_image_w - max_dim

        orig_image_w = max_dim
        orig_image_h = orig_image_h - dim_diff_w

    if orig_image_h > max_dim:
        dim_diff_h = orig_image_h - max_dim

        orig_image_h = max_dim
        orig_image_w = orig_image_w - dim_diff_h

    with BytesIO() as file_bytes:
        if dim_diff_h + dim_diff_w > 0 or file_bytes.tell() >= max_size:
            resize_image = orig_image.resize((orig_image_w, orig_image_h), Image.ANTIALIAS)

            resize_image.save(file_bytes, optimize=True, quality=100, format='png')

            if file_bytes.tell() <= max_size:
                file_bytes.seek(0, 0)
                with open(image_file, 'wb') as f_output:
                    f_output.write(file_bytes.read())
            else:
                new_max_dim = round(max_dim - (max_dim * 0.10))
                compress_image(image_file, max_size=max_size, max_dim=new_max_dim, dim_diff_w=0, dim_diff_h=0,
                               orig_image_w=orig_image_w, orig_image_h=orig_image_h)