Перебор пикселей

import cv2
import numpy as np
import glob
from PIL import Image
from collections import OrderedDict
import threading, concurrent.futures
 
#path img
path_img = 'path_to_image'
 
color_map = OrderedDict([
('Sky       '   ,np.array([0],dtype = np.uint8)),
('Building  '   ,np.array([1],dtype = np.uint8)),
('Pole      '   ,np.array([2],dtype = np.uint8)),
('Road_marking' ,np.array([3],dtype = np.uint8)),
('Road      '   ,np.array([4],dtype = np.uint8)),
('Pavement  '   ,np.array([5],dtype = np.uint8)),
('Tree      '   ,np.array([6],dtype = np.uint8)),
('SignSymbol'       ,np.array([7],dtype = np.uint8)),
('Fence     '   ,np.array([8],dtype = np.uint8)),
('Car       '   ,np.array([9],dtype = np.uint8)),
('Pedestrian'       ,np.array([10],dtype = np.uint8)),
('Bicyclist '   ,np.array([11],dtype = np.uint8)),
('Unlabelled'   ,np.array([12],dtype = np.uint8))
])
 
#color map for dataset
 
 
#f(class) = frequency(class) / (image_count(class) * 480*360)
 
#load files
files = glob.glob(path_img+'/'+'*png')
weights_cl  = np.zeros(len(color_map.items()))
F_cl        = np.zeros(len(color_map.items()))
file_count  = np.zeros(len(color_map.items()))
 
#step 1
def frec(count_class):
 
    frec_cl =           0
    image_count_cl =    0
    exist_im_cl = False
    img_size = (0,0)
    cnt = 0
 
    for file in files:
        img = Image.open(file)
 
        #calc frecuency
        for pixel in img.getdata():
            if pixel == color_map.items()[count_class][1]:
                frec_cl +=1
                exist_im_cl = True
 
        # class exists in image
        if exist_im_cl:
            image_count_cl += 1
 
        #reset flag
        exist_im_cl = False
 
        cnt+=1
 
        print (str(cnt)+":"+str(len(files)))
 
    F_cl[count_class]       = frec_cl
    file_count[count_class] = image_count_cl
 
executor = concurrent.futures.ProcessPoolExecutor(13)
futures = [executor.submit(frec, i) for i in range(len(color_map.items()))]
concurrent.futures.wait(futures)