import numpy as np
import matplotlib.pyplot as plt
import time
from collections import Counter
from Tkinter import *
from PIL import ImageTk, Image
import os, sys, glob, ntpath
from os.path import relpath


def create_database():
    number_arr_ex = open('numArEx.txt', 'a')
    numbers_we_have = range(0, 10)
    versions_we_have = range(1, 10)
    for eachNum in numbers_we_have:
        for eachVer in versions_we_have:
            img_file_path = 'images/numbers/'+str(eachNum)+'.'+str(eachVer)+'.jpg'
            ei = Image.open(img_file_path)
            eiar = np.array(ei)
            eiar1 = str(eiar.tolist())
            line_to_write = str(eachNum)+'::'+eiar1+'\n'
            number_arr_ex.write(line_to_write)


def tresh_from_img_np_array(img_arr):
    balance_arr = []
    new_arr = img_arr
    for row in new_arr:
        for pixel in row:
            avg_num = pixel[0]/3+(pixel[1]/3)+(pixel[2]/3)
            balance_arr.append(avg_num)
    balance = reduce(lambda x, y: x+y, balance_arr)/len(balance_arr)
    for row in new_arr:
        for pixel in row:
            temp = pixel[0] / 3 + (pixel[1] / 3) + (pixel[2] / 3)
            if temp > balance:
                pixel[0] = 255
                pixel[1] = 255
                pixel[2] = 255
            else:
                pixel[0] = 0
                pixel[1] = 0
                pixel[2] = 0
    return new_arr


def tresh_from_img(img):
    imgarr = np.asarray(img)
    imgarr.flags.writeable = True
    balance_arr = []
    new_arr = imgarr
    for row in new_arr:
        for pixel in row:
            avg_num = pixel[0]/3+(pixel[1]/3)+(pixel[2]/3)
            balance_arr.append(avg_num)
    balance = reduce(lambda x, y: x+y, balance_arr)/len(balance_arr)
    for row in new_arr:
        for pixel in row:
            temp = pixel[0] / 3 + (pixel[1] / 3) + (pixel[2] / 3)
            if temp > balance:
                pixel[0] = 255
                pixel[1] = 255
                pixel[2] = 255
            else:
                pixel[0] = 0
                pixel[1] = 0
                pixel[2] = 0
    image = Image.fromarray(new_arr)
    return image


def tresh_from_img_path(path):
    img = Image.open(path)
    to_arr = np.asarray(img)
    to_arr.flags.writeable = True
    balance_arr = []
    new_arr = to_arr
    for row in new_arr:
        for pixel in row:
            avg_num = pixel[0]/3+(pixel[1]/3)+(pixel[2]/3)
            balance_arr.append(avg_num)
    balance = reduce(lambda x, y: x + y, balance_arr)/len(balance_arr)
    for row in new_arr:
        for pixel in row:
            temp = pixel[0] / 3 + (pixel[1] / 3) + (pixel[2] / 3)
            if temp > balance:
                pixel[0] = 255
                pixel[1] = 255
                pixel[2] = 255
            else:
                pixel[0] = 0
                pixel[1] = 0
                pixel[2] = 0
    image = Image.fromarray(new_arr)
    return image


def what_num(my_file):
    matched_black = []
    max_matched_one_pic = []
    miss_match = []
    load_ex = open('numArEx.txt','r').read()
    load_ex = load_ex.split('\n')
    iar = my_file
    iar1 = iar.tolist()
    in_qst = str(iar1)
    in_qst = in_qst.split('],')
    i = 0
    for eachEx in load_ex:
        if len(eachEx) > 3:
            split_ex = eachEx.split('::')
            current_num = split_ex[0]
            current_ar = split_ex[1]
            each_pix_ex = current_ar.split('],')
            x = 0
            matched_one_pic = []
            while x < len(each_pix_ex):
                if each_pix_ex[x] == in_qst[x]:
                    matched_one_pic.append(int(current_num))
                    matched_black.append(int(current_num))
                    if len(matched_one_pic) > len(max_matched_one_pic):
                        max_matched_one_pic = matched_one_pic
                else:
                    miss_match.append(int(current_num))
                x += 1
        i += 1
    x = Counter(matched_black)
    print matched_black
    print x
    for number, count in x.most_common(1):
        print "Your number is "+str(number)
        print "Most accurate number was "+str(max_matched_one_pic[0])

### grafikai ###
    # graphX = []
    # graphY = []
    # for each in x:
    #     graphX.append(each)
    #     graphY.append(x[each])
    # fig = plt.figure()
    # ax1 = plt.subplot2grid((4,4),(0,0),rowspan = 1, colspan=4)
    # ax2 = plt.subplot2grid((4,4),(1,0),rowspan = 3, colspan=4)
    # ax1.imshow(iar)
    # ax2.bar(graphX,graphY,align='center')

    #plt.ylim(400)
   # xloc = plt.MaxNLocator(12)
    #ax2.xaxis.set_major_locator(xloc)
   # plt.show()
    #
    # fig = plt.figure()
    # ax1 = plt.subplot2grid((4,3),(0,0),rowspan=12,colspan=9)
    # ax1.imshow(iar)
    # plt.show()

# for i in range(0,10):
#     for j in range(1,10):
#         print i,j
#         pic = Image.open("images/numbers/"+str(i)+"."+str(j)+".png")

# -------------------------------------------------------

# path = "/Users/erlandas_t/PycharmProjects/untitled5/images/numbers"
# dirs = os.listdir(path)
# print len(dirs)
# for fil in dirs:
#     print "images/numbers/"+fil
#     pic = Image.open("images/numbers/"+fil)
#     iar = np.asarray(pic)
#     iar.flags.writeable = True
#     print "aa"
#     what_num(tresh(iar))
# -------------------------------------


def crop_white_edges(img):
    print
# -------------------------------------


def convert_to_jpg(img, path):
    head, tail = ntpath.split(path)
    img.save("images/jpg/" + tail[:-4] + ".jpg", format='JPEG', subsampling=0, quality=100)


def convert_dir_cont_to_jpg(dir_path):
    dirs = os.listdir(dir_path)
    print len(dirs)
    for fil in dirs:
        img = tresh_from_img_path(dir_path+fil)
        convert_to_jpg(img, dir_path+fil)


def main():
    path = "/Users/erlandas_t/PycharmProjects/untitled5/images/numbers/"
    convert_dir_cont_to_jpg(path)
    create_database()


# root = Tk()
# img = ImageTk.PhotoImage(Image.open("images/test.png"))
# panel = Label(root, image=img)
# panel.pack(side="bottom", fill="both", expand="yes")
# root.mainloop()
if __name__ == "__main__":
    main()