# -*- coding: utf-8 -*-

"""

Created on Tue Apr 20 18:30:57 2020

@author: Yashwant-Kumar

"""

#imported necessary packages.

import mysql.connector

import cv2

import pytesseract

pytesseract.pytesseract.tesseract_cmd = r'C:\Users\USER\AppData\Local\Tesseract-OCR\tesseract.exe'

#creating connection to my databse.

mydb = mysql.connector.connect(

)

mycurser = mydb.cursor(buffered=True)

#reading video which is in the same folder.

cap = cv2.VideoCapture('6.mp4')

#getting the frames from video.

ret,frame1 = cap.read()

ret,frame2 = cap.read()

ret1 = True

while cap.isOpened():

if(ret1 == True):

#finding the difference between each frame.

diff = cv2.absdiff(frame1,frame2)

#converting the frame to gray scale.

im_gray = cv2.cvtColor(diff,cv2.COLOR_BGR2GRAY)

blur = cv2.GaussianBlur(im_gray,(5,5),0)

_,thresh = cv2.threshold(blur,20,255,cv2.THRESH_BINARY)

#it helps to remove the useless information or background distrubance.

dilate = cv2.dilate(thresh,None,iterations=5)

#finding the contours.

contour,_ = cv2.findContours(dilate,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

for cnt in contour:

#finding the coordinates of each contour found.

x,y,w,h = cv2.boundingRect(cnt)

#trying to find the car in each frame by finding the area of each contour.

if(cv2.contourArea(cnt)>=19000 and cv2.contourArea(cnt)<=24000):

frame_gray = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)

#Finding the edges using canny edge detection.

canny = cv2.Canny(frame_gray,170,255)

contours,_ = cv2.findContours(canny.copy(),cv2.RETR_LIST,cv2.CHAIN_APPROX_NONE)

contours = sorted(contours, key= cv2.contourArea,reverse = True)[:35]

#iterating through those contours to find the number plate in the frame.

for cnt in contours:

perimeter = cv2.arcLength(cnt,True)

approx = cv2.approxPolyDP(cnt,0.01*perimeter,True)

if len(approx) == 4:

cnt_with_plate = approx

#geting the coordinates of the number plate in the frame

x,y,w,h = cv2.boundingRect(cnt)

break

#applying filters to the number plate to remove any useless information.

num_plate = cv2.bilateralFilter(frame_gray[y:y+h,x:x+w],5,17,17)

thresh , num_plate = cv2.threshold(num_plate,95,255,cv2.THRESH_BINARY)

cv2.imshow('res',num_plate)

#extracting the number from the number plate in the form of text.

num_plate_text = pytesseract.image_to_string(num_plate)

#getting the data from the database.

mycurser.execute("select * from vid_nums")

#using as a flag

f=0

#checking whether the car number is matched in our database.

for x in mycurser:

if(num_plate_text == x[0]):

f=1

print("ENTRY GRANTED!!")

cv2.destroyAllWindows()

cap.release()

break

if(f==1):

break

frame1 = frame2

#reading frames.

ret1,frame2 = cap.read()

cv2.waitKey(20)

elif(ret1 == False):

print("ENTRY DENIED!!")

cv2.destroyAllWindows()

cap.release()

break