import cv2
import imutils
import numpy as np
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files (x86)\Tesseract-OCR\tesseract.exe"

img = cv2.imread(r'D:\Agilan\VII Sem\MiniProj\Code\test_images\test6.jpg')
img = cv2.resize(img, (600,400) )

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
gray = cv2.bilateralFilter(gray, 13, 15, 15) 

edged = cv2.Canny(gray, 30, 200) 
contours = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(contours)
contours = sorted(contours, key = cv2.contourArea, reverse = True)[:10]
screenCnt = None

for c in contours:
    
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.018 * peri, True)
 
    if len(approx) == 4:
        screenCnt = approx
        break

if screenCnt is None:
    detected = 0
    print ("No contour detected")
else:
     detected = 1

if detected == 1:
    cv2.drawContours(img, [screenCnt], -1, (0, 0, 255), 3)

    mask = np.zeros(gray.shape,np.uint8)
    new_image = cv2.drawContours(mask,[screenCnt],0,255,-1,)
    new_image = cv2.bitwise_and(img,img,mask=mask)

    (x, y) = np.where(mask == 255)
    (topx, topy) = (np.min(x), np.min(y))
    (bottomx, bottomy) = (np.max(x), np.max(y))
    Cropped = gray[topx:bottomx+1, topy:bottomy+1]

    Cropped = cv2.resize(Cropped, None, fx=1.2, fy=1.2, interpolation=cv2.INTER_CUBIC)
    kernel = np.ones((1, 1), np.uint8)
    Cropped = cv2.dilate(Cropped, kernel, iterations=1)
    Cropped = cv2.erode(Cropped, kernel, iterations=1)
    cv2.threshold(cv2.GaussianBlur(Cropped, (5, 5), 0), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

    cv2.threshold(cv2.bilateralFilter(Cropped, 5, 75, 75), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

    cv2.threshold(cv2.medianBlur(Cropped, 3), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

    cv2.adaptiveThreshold(cv2.GaussianBlur(Cropped, (5, 5), 0), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    cv2.adaptiveThreshold(cv2.bilateralFilter(Cropped, 9, 75, 75), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    cv2.adaptiveThreshold(cv2.medianBlur(Cropped, 3), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)

    text = pytesseract.image_to_string(Cropped, config='--psm 11')
    print("Detected license plate Number is:",text)
    img = cv2.resize(img,(500,300))
    Cropped = cv2.resize(Cropped,(400,200))
    cv2.imshow('car',img)
    cv2.imshow('Cropped',Cropped)

    cv2.waitKey(0)
    cv2.destroyAllWindows()