I would like it to ignore the top non-English letters as I don't need them, but I don't know how to ignore them. I thought about removing the index of these areas but unfortunately the index is not the same for all plate numbers so it's not going to work. Does anyone know how I can take the contours of the numbers and the bottom English letters only without the top non-English letters. I would highly appreciate your help.
The image:
The code:
`
import cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
img = cv2.imread('c1.png')
img1 = img.copy()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray,(7,7),0)
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)
contours, hierarchy = cv2.findContours(thre_mor,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
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
cont, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
crop_characters = []
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<=10:
if h/img.shape[0]>=0.20:
cv2.rectangle(img1, (x, y), (x + w, y + h), (255, 0,0), 2)
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, 220, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
crop_characters.append(curr_num)
print("Detect {} letters...".format(len(crop_characters)))
fig = plt.figure(figsize=(10,6))
plt.axis(False)
plt.imshow(img1)
plt.show()`
The output:
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent