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user_9363972
python
5 months ago
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import cv2 import numpy as np import imutils import easyocr # Loading image img = cv2.imread('images/7.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) bfilter = cv2.bilateralFilter(gray, 11, 17, 17) edged = cv2.Canny(bfilter, 30, 200) # Get location of contours and also array of sorted width 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] # Grab location based on shape that has 4 points (Plate) location = None for contour in contours: approx = cv2.approxPolyDP(contour, 10, True) if len(approx) == 4: location = approx break # Drawing Black Screen except the plate number 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) # # Cropped Image (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] # Using OCR reader = easyocr.Reader(['en']) result = reader.readtext(cropped_image) print(result) # Drawing the image again text = result[0][-2] res = cv2.putText(img, text, (approx[0][0][0], approx[1] [0][1]+60), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2) res = cv2.rectangle(img, tuple(approx[0][0]), tuple( approx[2][0]), (0, 255, 0), 3) cv2.imshow("Image", cv2.cvtColor(res, cv2.COLOR_BGR2RGB)) cv2.waitKey(0)
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