Object Recognition using CV model

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import cv2
import pytesseract
carplate_img = cv2.imread(‘./cars/car_image.png’)
carplate_img_rgb = cv2.cvtColor(carplate_img, cv2.COLOR_BGR2RGB)
plt.imshow(carplate_img_rgb)
carplate_haar_cascade = cv2.CascadeClassifier(‘haarcascade_russian_plate_number.xml’)
def carplate_detect(image):
carplate_overlay = image.copy()
carplate_rects = carplate_haar_cascade.detectMultiScale(carplate_overlay,scaleFactor=1.1, minNeighbors=3)
for x,y,w,h in carplate_rects:
cv2.rectangle(carplate_overlay, (x,y), (x+w,y+h), (255,0,0), 5)
return carplate_overlay
detected_carplate_img = carplate_detect(carplate_img_rgb)
plt.imshow(detected_carplate_img)
def carplate_extract(image):

carplate_rects = carplate_haar_cascade.detectMultiScale(image,scaleFactor=1.1, minNeighbors=5)
for x,y,w,h in carplate_rects:
carplate_img = image[y+15:y+h-10 ,x+15:x+w-20]
return carplate_img
def enlarge_img(image, scale_percent):
width = int(image.shape[1] * scale_percent / 100)
height = int(image.shape[0] *scale_percent / 100)
dim = (width, height)
resized_image = cv2.resize(image, dim, interpolation = cv2.INTER_AREA)
return resized_image
carplate_extract_img = carplate_extract(carplate_img_rgb)
carplate_extract_img = enlarge_img(carplate_extract_img, 150)
plt.imshow(carplate_extract_img);
carplate_extract_img_gray = cv2.cvtColor(carplate_extract_img, cv2.COLOR_RGB2GRAY)
plt.axis(‘off’)
plt.imshow(carplate_extract_img_gray, cmap = ‘gray’);
carplate_extract_img_gray_blur = cv2.medianBlur(carplate_extract_img_gray,3) # kernel size 3
plt.axis(‘off’)
plt.imshow(carplate_extract_img_gray_blur, cmap = ‘gray’);
import easyocr
reader=easyocr.Reader([‘en’])
result=reader.readtext(carplate_extract_img_gray_blur)
result

This extracts the number plate from the image and prints in the form of text.

Thanks!!!