from __future__ import (division, absolute_import, print_function, unicode_literals)
import glob
import os,sys
import cv2 as cv
import numpy as np
from pandas import DataFrame as df
import pandas as pd
from matplotlib import pyplot as plt


########
#Globals
#########

img_dir = "path_to_images/*.*"

###########
#Functions
###########

def white_balance(img):
result = cv.cvtColor(img, cv.COLOR_BGR2LAB)
avg_a = np.average(result[:, :, 1])
avg_b = np.average(result[:, :, 2])
result[:, :, 1] = result[:, :, 1] - ((avg_a - 128) * (result[:, :, 0] / 255.0) * 1.1)
result[:, :, 2] = result[:, :, 2] - ((avg_b - 128) * (result[:, :, 0] / 255.0) * 1.1)
result = cv.cvtColor(result, cv.COLOR_LAB2BGR)
return result


## Get all the images in the specified dir:
images = sorted(glob.glob(img_dir))




#Reading images in folder
for image in images:
    img = cv.imread(os.path.join(img_dir, image)) #Read images one by one

    ################
    #Pre-processing#
    ################
    #Performing white balancing (gray world)
    #final = np.hstack((img, white_balance(img))) #white balancing; showing Original and filtered.
    final = white_balance(img) #white balance on a single image.


    #Saving images:
    i = 0
    cv.imwrite("path_to_results/preproc%04i.jpg" %i, final) #save images in sequence (numbering)
    i += 1 #numbering variable