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GOCR数字识别

郭俊人
2023-12-01
import os
import numpy as np
import cv2
from time import time

camera=cv2.VideoCapture(0)
camera.set(3,128) #设置分辨率
camera.set(4,128)
camera.set(5,120)


def equalize_transfrom(gray_img):
    return cv2.equalizeHist(gray_img)

start = time()
    #gray = cv2.blur(gray,(5,5))
    #gray = equalize_transfrom(gray)
    #ret,det = cv2.threshold(gray,40,255,cv2.THRESH_BINARY)
    #det = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,3,3)
    #det= gray #cv2.medianBlur(det,3)
    
memfile = './data.png'
kernel = np.ones((3,3),np.uint8)
#erosion = cv2.erode(src,kernel)

while True:    
    (grabbed,scr)=camera.read()
    gray = cv2.cvtColor(scr,cv2.COLOR_RGB2GRAY)
    ret,det = cv2.threshold( equalize_transfrom(gray) ,40,255,cv2.THRESH_BINARY)  #直方图均衡之后二值化
    cv2.blur(det,(5,5))  #模糊
    cv2.medianBlur(det,5)  
    #det = cv2.dilate(det,kernel)
    contours,hierarchy = cv2.findContours(det,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE) #扫描轮廓
    #print("number of contours:%d" % len(contours))
    
    mask = np.zeros([128, 128], np.uint8)
    for i in range(len(contours)):
        sz = len( contours[i] )  #轮廓像素个数
        ln = cv2.arcLength(contours[i],True)  #获取轮廓周长面积
        ar = cv2.contourArea(contours[i])
        
        if sz>10 and sz<100 and ln<ar:
            x,y,w,h = cv2.boundingRect(contours[i])  #获取轮廓框
            if y<100:
                #print( [len(contours[i]),ln,ar,x,y] )
                for row in range(y,y+h-1):            #遍历高
                    for col in range(x,x+w-1):         #遍历宽
                        if( det[row,col] == 0 ):
                            mask[row,col] = 255
    mask = 255-mask
    #mask = cv2.erode(mask,kernel)
    cv2.imshow("scr",mask)
    cv2.waitKey(1)
    cv2.imwrite(memfile,mask)
    with os.popen('gocr -a 90 -C 0123456789A=+ -i '+memfile, "r") as p:
        line = p.readline()
        if( line.find('_')<0 ):print (line)
        while line:line = p.readline()
            #print (line)
    if cv2.waitKey(1) & 0xFF == 27:
        break

cv2.destroyAllWindows()
print(time() - start)
print('end')

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