问如果我使用多进程，为什么Python代码运行较慢

EN

'''
Created on 17.11.2017

@author: Max
'''
#!/usr/bin/env python

import os, sys, errno
import re
import argparse
from time import time
import multiprocessing
import glob
import numpy as np
import matplotlib.pyplot as plt
import cv2
def computeFeatures(input, chunk_num):
    thresholded_chunk = []
    #print("Processing Chunk,",chunk_num)
    cv2.threshold(input,127,255,cv2.THRESH_BINARY_INV)
    cv2.threshold(input,127,255,cv2.THRESH_BINARY_INV)
    cv2.threshold(input,127,255,cv2.THRESH_BINARY_INV)
    cv2.threshold(input,127,255,cv2.THRESH_BINARY_INV)
    thresholded_chunk.append(cv2.threshold(input,127,255,cv2.THRESH_BINARY_INV))   
    return (thresholded_chunk, chunk_num)


if __name__ == '__main__':
    num_Proc = 2
    max_Proc = 20
    while num_Proc != max_Proc:

        start = time()
        # Handle command line options
        numProcessors = num_Proc

        # Start my pool
        pool = multiprocessing.Pool(numProcessors)

        # Build task list
        path = "InputSimulation\*" 
        tasks = []
        image_list= []
        img_idx = 0
        image_pathes = glob.glob(path+".jpg")
        results = []
        index_for_chunk = numProcessors
        while img_idx < len(image_pathes):
            #print("InsterImageNumber",img_idx)
            tasks.append( (cv2.imread(image_pathes[img_idx],0), img_idx, ) )
            if img_idx % numProcessors == 0:
                result = [pool.apply_async( computeFeatures, t ) for t in tasks]
                results.append(result)
                tasks = []
            img_idx +=1
        pool.close()
        pool.join()
            # Run tasks    #Flatten list before print

        end = time()
        print("DURATION FOR " +str(num_Proc) +" PROCESSES",end - start)
        num_Proc +=1
        # Process results