brightness

import numpy as np
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import requests
import cv2
from math import sqrt

def urlToImage(url):
    global image
    response = requests.get(url)
    image = np.asarray(bytearray(response.content), dtype='uint8')
    image = cv2.imdecode(image, cv2.IMREAD_COLOR)

    return image

def imageProcessing(image):
    global img
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

    height, width = image.shape[:2]
    img = cv2.resize(image, (int(round(width/10)), int(round(height/10))), interpolation = cv2.INTER_AREA)
    img = img.reshape((img.shape[0]*img.shape[1], 3))

    return img

def findBrightness(img):
    global lighter, darker
    lighter = 0
    darker = 0
    for c in img:
        r = c[0]
        g = c[1]
        g = c[2]

        brightness = sqrt(0.299*r*r + 0.587*g*g + 0.114*b*b)

        if brightness > 0.5:
            lighter = lighter+1
        if brightness < 0.5:
            darker = darker+1
        if lighter>darker:
            return print('image is higher in brightness')
        if lighter<darker:
            return print('image is lower in brightness')
urlToImage('https://www.gardapost.it/wp-content/uploads/2019/04/foresta-bosco.jpg')
imageProcessing(image)
findBrightness(img)