detect.py

import numpy as np
import cv2 
import imutils
import pytesseract
import pandas as pd
import time
import mysql.connector
import datetime
import sys
import re
import time
import requests
from PyQt5 import QtCore, QtWidgets, uic

image_path = 'images/10.jpg'

img = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
img = imutils.resize(img, width=500)
cv2.imshow(image_path, img)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#cv2.imshow("1 - Grayscale Conversion", gray)

gray = cv2.bilateralFilter(gray, 11, 17, 17)
#cv2.imshow("2 - Bilateral Filter", gray)

edged = cv2.Canny(gray, 170, 200)
#cv2.imshow("4 - Canny Edges", edged)

cnts= cv2.findContours(edged.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
cnts=sorted(cnts, key = cv2.contourArea, reverse = True)[:30] 
NumberPlateCnt = None 

count = 0
for c in cnts:
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.02 * peri, True)
        if len(approx) == 4:  
                NumberPlateCnt = approx 
                break

# Masking the part other than the number plate
mask = np.zeros(gray.shape,np.uint8)
new_image = cv2.drawContours(mask,[NumberPlateCnt],0,255,-1)
new_image = cv2.bitwise_and(img,img,mask=mask)
cv2.namedWindow("Final_image",cv2.WINDOW_NORMAL)
cv2.imshow("Final_image",new_image)

# Configuration for tesseract
config = ('-l eng --oem 1 --psm 3')

# Run tesseract OCR on image
text = str(pytesseract.image_to_string(new_image, config=config))

#Data is stored in CSV file
raw_data = {'date': [time.asctime( time.localtime(time.time()) )], 
        'v_number': [text]}

df = pd.DataFrame(raw_data, columns = ['date', 'v_number'])
df.to_csv('data.csv')

# Print recognized text
print(text)
cv2.waitKey(0)