import sys
import glob
import os
import glob
import numpy as np
import cv2
from PIL import Image
import pytesseract
import re

def clean2_plate(plate):
    gray_img = cv2.cvtColor(plate, cv2.COLOR_BGR2GRAY)

    _, thresh = cv2.threshold(gray_img, 110, 255, cv2.THRESH_BINARY)
    #if cv2.waitKey(0) & 0xff == ord('q'):
    #    pass
    num_contours,hierarchy = cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

    if num_contours:
        contour_area = [cv2.contourArea(c) for c in num_contours]
        max_cntr_index = np.argmax(contour_area)

        max_cnt = num_contours[max_cntr_index]
        max_cntArea = contour_area[max_cntr_index]
        x,y,w,h = cv2.boundingRect(max_cnt)

        if not ratioCheck(max_cntArea,w,h):
            return plate,None

        final_img = thresh[y:y+h, x:x+w]
        return final_img,[x,y,w,h]

    else:
        return plate,None

def ratioCheck(area, width, height):
    ratio = float(width) / float(height)
    if ratio < 1:
        ratio = 1 / ratio
    if (area < 1063.62 or area > 73862.5) or (ratio < 3 or ratio > 6):
        return False
    return True

def isMaxWhite(plate):
    avg = np.mean(plate)
    if(avg>=115):
        return True
    else:
        return False

def ratio_and_rotation(rect):
    (x, y), (width, height), rect_angle = rect

    if(width>height):
        angle = -rect_angle
    else:
        angle = 90 + rect_angle

    if angle>15:
        return False

    if height == 0 or width == 0:
        return False

    area = height*width
    if not ratioCheck(area,width,height):
        return False
    else:
        return True


#Detecting numberplate
def number_plate_detection(img):
    img2 = cv2.GaussianBlur(img, (5,5), 0)
    img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
    
    img2 = cv2.Sobel(img2,cv2.CV_8U,1,0,ksize=3)	
    _,img2 = cv2.threshold(img2,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
    
    element = cv2.getStructuringElement(shape=cv2.MORPH_RECT, ksize=(17, 3))
    morph_img_threshold = img2.copy()
    cv2.morphologyEx(src=img2, op=cv2.MORPH_CLOSE, kernel=element, dst=morph_img_threshold)
    num_contours, hierarchy= cv2.findContours(morph_img_threshold,mode=cv2.RETR_EXTERNAL,method=cv2.CHAIN_APPROX_NONE)
    cv2.drawContours(img2, num_contours, -1, (0,255,0), 1)
    
    
    for i,cnt in enumerate(num_contours):
        min_rect = cv2.minAreaRect(cnt)
        if ratio_and_rotation(min_rect):
            x,y,w,h = cv2.boundingRect(cnt)
            plate_img = img[y:y+h,x:x+w]
            if(isMaxWhite(plate_img)):
                clean_plate, rect = clean2_plate(plate_img)
                if rect:
                    fg=0
                    x1,y1,w1,h1 = rect
                    x,y,w,h = x+x1,y+y1,w1,h1
                    plate_im = Image.fromarray(clean_plate)
                    text = pytesseract.image_to_string(plate_im, lang='eng')
                    return text



print("HELLO!!")
print("Welcome to the Number Plate Detection System.\n")

array=[]

dir = os.path.dirname(__file__)

for img in glob.glob(dir+"/Images/*.jpeg") :
    img=cv2.imread(img)
    
    img2 = cv2.resize(img, (600, 600))
    cv2.imshow("Image of car ",img2)
    cv2.waitKey(1000)
    cv2.destroyAllWindows()
    
    
    number_plate=number_plate_detection(img)
    res2 = str("".join(re.split("[^a-zA-Z0-9]*", number_plate)))
    res2=res2.upper()
    print(res2)

    array.append(res2)
import pprint
pprint.pprint(array)
img = cv2.imread("./Search_Image/Car.jpeg")
number_plate=number_plate_detection(img)
import pdb; pdb.set_trace() 
res2 = str("".join(re.split("[^a-zA-Z0-9]*", number_plate)))

print("The car number is:- ",res2)