fast_res_conversion.py

import glob
import os
import cv2
import concurrent.futures


def load_and_resize(image_filename):
  ### Read in the image data
  img = cv2.imread(image_filename)
  
  ### Resize the image
  img = cv2.resize(img, (600, 600)) 
  

### Create a pool of processes. By default, one is created for each CPU in your machine.
with concurrent.futures.ProcessPoolExecutor() as executor:
    ### Get a list of files to process
    image_files = glob.glob("*.jpg")

    ### Process the list of files, but split the work across the process pool to use all CPUs
    ### Loop through all jpg files in the current folder 
    ### Resize each one to size 600x600
    executor.map(load_and_resize, image_files)