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| import cv2 | |
| from local_utils import detect_lp | |
| from get_plate import get_plate | |
| #for test | |
| # from transfer import load_model | |
| # from preprocessing import preprocess_image | |
| # import glob | |
| # import matplotlib.pyplot as plt | |
| # from os.path import splitext,basename | |
| # import matplotlib.gridspec as gridspec | |
| # 1. see what it looks like in different types: plate_image, gray, blur, binary,thre_mor | |
| def DiffImage(LpImg): | |
| if (len(LpImg)): #check if there is at least one license image | |
| # Scales, calculates absolute values, and converts the result to 8-bit. | |
| plate_image = cv2.convertScaleAbs(LpImg[0], alpha=(255.0)) | |
| # convert to grayscale and blur the image | |
| # | |
| gray = cv2.cvtColor(plate_image, cv2.COLOR_BGR2GRAY) | |
| blur = cv2.GaussianBlur(gray,(7,7),0) | |
| # Applied inversed thresh_binary | |
| binary = cv2.threshold(blur, 180, 255, | |
| cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1] | |
| kernel3 = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) | |
| thre_mor = cv2.morphologyEx(binary, cv2.MORPH_DILATE, kernel3) | |
| return plate_image,gray,blur,binary,thre_mor | |
| # Create sort_contours() function to grab the contour of each digit from left to right | |
| def sort_contours(cnts,reverse = False): | |
| i = 0 | |
| boundingBoxes = [cv2.boundingRect(c) for c in cnts] | |
| (cnts, boundingBoxes) = zip(*sorted(zip(cnts, boundingBoxes), | |
| key=lambda b: b[1][i], reverse=reverse)) | |
| return cnts | |
| def get_Crop_Letter(wpod_net,image): | |
| vehicle, LpImg,cor = get_plate(wpod_net,image) | |
| plate_image,gray,blur,binary,thre_mor=DiffImage(LpImg) | |
| cont, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) | |
| #print(len(cont)) | |
| # creat a copy version "test_roi" of plat_image to draw bounding box | |
| test_roi = plate_image.copy() | |
| # Initialize a list which will be used to append charater image | |
| crop_characters = [] | |
| # define standard width and height of character | |
| digit_w, digit_h = 30, 60 | |
| for c in sort_contours(cont): | |
| (x, y, w, h) = cv2.boundingRect(c) | |
| ratio = h/w | |
| if 1<=ratio<=5: # Only select contour with defined ratio | |
| if h/plate_image.shape[0]>=0.5: # Select contour which has the height larger than XXX% of the plate | |
| # Draw bounding box arroung digit number | |
| cv2.rectangle(test_roi, (x, y), (x + w, y + h), (0, 255,0), 2 ) | |
| # Sperate number and gibe prediction | |
| curr_num = thre_mor[y:y+h,x:x+w] | |
| curr_num = cv2.resize(curr_num, dsize=(digit_w, digit_h)) | |
| _, curr_num = cv2.threshold(curr_num, 200, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU) | |
| crop_characters.append(curr_num) | |
| #print("Detect {} numbers!".format(len(crop_characters))) | |
| return test_roi,crop_characters | |