main.py 文件源码

def process_word(thresh,output):    
    # assign 2 rectangle kernel size 1 vertical and the other will be horizontal    
    kernel = np.ones((2,1), np.uint8)
    kernel2 = np.ones((1,4), np.uint8)
    # use closing morph operation but fewer iterations than the letter then erode to narrow the image   
    temp_img = cv2.morphologyEx(thresh,cv2.MORPH_CLOSE,kernel,iterations=2)
    #temp_img = cv2.erode(thresh,kernel,iterations=2)   
    word_img = cv2.dilate(temp_img,kernel2,iterations=1)

    (contours, _) = cv2.findContours(word_img.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

    for cnt in contours:
        x,y,w,h = cv2.boundingRect(cnt)
        cv2.rectangle(output,(x-1,y-5),(x+w,y+h),(0,255,0),1)

    return output   

#processing line by line boxing