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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
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