Auto-Detect Vehicle’s Number Plate Using Python
Task Description: →
?? In this task :
??Create a model that will detect a car in a live stream or video and recognize characters on the number plate of the car.
??Secondly, it will use the characters and fetch the owner's information using RTO APIs.
??Create a Web portal where all this information will be displayed (using HTML, CSS, and JS).
Step1?Read in image, Grayscale and Blur
Step 2 Apply filter and find edges for localization
Step 3 Find Contours and Apply Mask
Step 4 Use Easy OCR To Read?
Step 5 Result
import cv2
from matplotlib import pyplot as plt?
import numpy as np
import imutils
import easyocr
# 1. Read in image, Grayscale and Blur
img = cv2.imread('image1.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
plt.imshow(cv2.cvtColor(gray, cv2.COLOR_BGR2RGB))
#2. Apply filter and find edges for localization
bfilter = cv2.bilateralFilter(gray , 11, 17, 17) #noise reduction
edged = cv2.Canny(bfilter, 30, 200) #edge detection
plt.imshow(cv2.cvtColor(edged, cv2.COLOR_BGR2RGB))
# 3. Find Contours and Apply Mask
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
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)
plt.imshow(cv2.cvtColor(new_image, cv2.COLOR_BGR2RGB))
(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]
plt.imshow(cv2.cvtColor(cropped_image, cv2.COLOR_BGR2RGB))
# 4. Use Easy OCR To Read?
reader = easyocr.Reader(['en'])
result = reader.readtext(cropped_image)
result
# 5. Render Result
text = result[0][-2]
font = cv2.FONT_HERSHEY_SIMPLEX
res = cv2.putText(img, text=text, org=(approx[0][0][0], approx[1][0][1]+60), fontFace=font, fontScale=1, color=(0,255,-1), thickness=2, lineType=cv2.LINE_AA)
res = cv2.rectangle(img, tuple(approx[0][0]), tuple(approx[2][0]), (0,255,-1),3)
plt.imshow(cv2.cvtColor(res, cv2.COLOR_BGR2RGB))
text
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thank you!!!