import cv2 as cv

def read_image(image_path):

    return cv.imread(image_path)

def show_image(img, delay_ms=0):

    cv.imshow(“Image”, img)

    cv.waitKey(delay_ms)

    cv.destroyAllWindows()

def filter_image(img):

    # Binarize Image (Change Color Space)

    gray_img = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

    # Blurring (Smoothing)

    bilateral = cv.bilateralFilter(gray_img, 13, 75, 75)

    # Edge Detection

    edged = cv.Canny(bilateral, 30, 200)

    return edged

def get_contours(filtered_image):

    contours, _ = cv.findContours(

        filtered_image.copy(),

        cv.RETR_LIST,

        cv.CHAIN_APPROX_SIMPLE)

    sorted_contours = sorted(

        contours,

        key=cv.contourArea,

        reverse=True)[:10]

    return sorted_contours

def approximate_contours(contours):

    for contour in contours:

        perimeter = cv.arcLength(contour, True)

        epsilon = 0.02 * perimeter

        approx = cv.approxPolyDP(contour, epsilon, True)

        if len(approx) == 4:

            return approx

    return None

def roi(approx_cnt, img):

    x, y, w, h = cv.boundingRect(approx_cnt)

    return img[y:y+h, x:x+w]

_________________________________

#config

import os

class Config:

    BASE_DIR_PATH = os.path.dirname(os.path.abspath(__file__))

    SRC_DIR_PATH = os.path.join(BASE_DIR_PATH, “Plate_Licenses”)

    SRC_FILE_PATH = os.path.join(SRC_DIR_PATH, “plate_license_C.jpg”)

    def __init__(self):

        self.SRC_ABSOLUTE_PATH_LIST = list()

        for file_item in os.listdir(self.SRC_DIR_PATH):

            file_item_abs_path = os.path.join(self.SRC_DIR_PATH, file_item)

            self.SRC_ABSOLUTE_PATH_LIST.append(file_item_abs_path)

_________________________________________

#errors

class ContoursNotFoundError(Exception):

    pass

___________________________________________

#main

# Methods for finding plate licenses:

#   a) Machine Learning

#   b) Haar Cascades Method

#   c) Manually Method (Contours)

#‌ Worst case scenarios:

#   The contour fails to detect the license plate correctly

#        a) we have to again relay on Machine learning.

#        b) improve the quality of the picture.

# The accuracy depends on the clarity of image, orientation, light exposure.

if __name__ == “__main__”:

    from config import Config

    from errors import ContoursNotFoundError

    from license_plate_detection import (filter_image, read_image, get_contours,

                                         approximate_contours, roi, show_image)

    conf = Config()

    SRC_DIR_PATH = conf.SRC_DIR_PATH

    IMG_FILE_PATH = conf.SRC_FILE_PATH

    PLATE_LICENSES_ITEMS = conf.SRC_ABSOLUTE_PATH_LIST

    if IMG_FILE_PATH in PLATE_LICENSES_ITEMS:

        img = read_image(IMG_FILE_PATH)

        filtered_image = filter_image(img)

        sorted_contours = get_contours(filtered_image)

        approx_cnt = approximate_contours(sorted_contours)

        if approx_cnt is None:

            raise ContoursNotFoundError(“No contours detected”)

        roi_img = roi(approx_cnt, img)

        show_image(roi_img)

    else:

        raise FileNotFoundError(f”File not found at {SRC_DIR_PATH}”)