Easy OCR 간단하게 사용해보기

nicknochnack/ANPRwithPython

 

0. Install and Import Dependencies

pip install easyocr
pip install imutils​

# OMP: ERROR #15: Initializing libiomp5md.dll, but found libiomp5md.dll already initialized.
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'


import cv2
from matplotlib import pyplot as plt
import numpy as np
import imutils
import easyocr​

 

1. Read Image, Gray scale

img = cv2.imread("image3.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

# 컨투어 찾기
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]

# 컨투어 폐곡선으로 근사했을 때 꼭짓점 개수가 4개인 결과를 location에 저장
location = None
for contour in contours:
    approx = cv2.approxPolyDP(contour, 10, True)
    if len(approx) == 4:
        location = approx
        break

# 해당 꼭짓점을 이었을 때 생기는 영역을 제외한 나머지 부분을 0으로 초기화
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))

# ROI로 확대
(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 Text

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, 0), thickness = 2, lineType = cv2.LINE_AA)
res = cv2.rectangle(img, tuple(approx[0][0]), tuple(approx[2][0]), (0, 255, 0), 3)
plt.imshow(cv2.cvtColor(res, cv2.COLOR_BGR2RGB))