import cv2
from matplotlib import pyplot as plt
import numpy as np
import imutils
import easyocr

img = cv2.imread('vehicle_car_2.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#cv2.imshow('original img',gray)

bfilter = cv2.bilateralFilter(gray, 11, 17, 17) #Noise reduction
edged = cv2.Canny(bfilter, 30, 200) #Edge detection
#cv2.imshow('Noise reduction img',edged)

keypoints = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours = imutils.grab_contours(keypoints)
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]

location = None
for contour in contours:
    approx = cv2.approxPolyDP(contour, 10, True)
    if len(approx) == 4:
        location = approx
        break

#print(location)

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

(x,y) = np.where(mask==255)
(x1, y1) = (np.min(x), np.min(y))
(x2, y2) = (np.max(x), np.max(y))
cropped_image = gray[x1:x2+1, y1:y2+1]
cv2.imshow('cropped img',cropped_image)

reader = easyocr.Reader(['en'])
result = reader.readtext(cropped_image)
print(result)

cv2.waitKey(0)
cv2.destroyAllWindows()

