OpenCV和selenum实现点击操作

import cv2 as cv
import numpy as np

from PIL import Image, ImageDraw, ImageFont

import os

from selenium.webdriver.common.action_chains import ActionChains
from selenium import webdriver as driver1

resultlist = []
device = 'PC'
path = os.path.abspath('..')
imglist = []
show =1

url="http://www.bjjs.gov.cn/bjjs/index/index.shtml"
driver = driver1.Chrome(executable_path=path+"/Program/chromedriver")

"""
首先:加载原始图像和要搜索的图像模板
其次:OpenCV对原始图像进行处理,创建一个灰度版本
再次:在灰度图像里进行处理和查找匹配
最后:使用相同的坐标在原始图像中进行还原并输出
"""

def opencv_elementActive(value=0.8, type='OK', msg='流程', title='测试_冀', desc='北京建房委员会', devices='PC'):
    try:
       target = path+r"\Run\Demo2\pic\PC\BJ_GOV\background\img.png"
       temp = r"C:\Users\lenovo\Desktop\newI\UI\temp.png"

       # 加载原始的RGB图像
       img_rgb = cv.imread(target)
       # 色彩空间转换(因为在opencv中默认的颜色空间是BGR)
       # 创建一个原始图像的灰度版本,所有操作在灰度版本中处理
       img_gray = cv.cvtColor(img_rgb, cv.COLOR_BGR2GRAY)
       # 加载将要搜索的图像模板
       template = cv.imread(temp, 0)

       # 高斯函数对图形进行高斯滤波
       merged = cv.GaussianBlur(np.uint8(np.clip((1.0 * img_rgb - 60), 0, 200)), (0, 0), 3)
       # shape 图片的尺寸
       w, h = template.shape[::-1]

       # 使用matchTemple对原始灰度图像和图像模板进行匹配(在原始图像中查找并匹配图像模板中的内容,并设置阈值)
       res = cv.matchTemplate(img_gray, template, cv.TM_CCOEFF_NORMED)
       threshold = value
       pt = []
    except Exception as e:
        print(" Error:",e)
    try:
        loc = np.where(res >= threshold)
        # 使用灰度图像中的坐标对原始RGB图像进行标记
        for pt in zip(*loc[::-1]):
            cv.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0, 30, 255), 10)
            cropImg=img_rgb[pt[1]:pt[1] + h,pt[0]:pt[0] + w]
            merged[pt[1]:pt[1] + h,pt[0]:pt[0] + w] = cropImg

        creatImgDebug(merged,pt,h)
        x, y = eval("pt[0]+w/2,pt[1]+h/2")
        click(x,y)
    except Exception as e:

        print("===================================================================================================")

def creatImgDebug(img_rgb, pt, h):
    cv_im = cv.cvtColor(img_rgb, cv.COLOR_BGR2RGB)
    # arary转换成image
    pil_im = Image.fromarray(cv_im)
    # 创建绘制对象
    draw = ImageDraw.Draw(pil_im)
    font = ImageFont.truetype(path + "/Program/FZYTK.TTF", 80, encoding="utf-8")
    font1 = ImageFont.truetype(path + "/Program/FZYTK.TTF", 40, encoding="utf-8")
    draw.text((80, 50), "图像识别 {}检测：成功".format("图片识别成功"), (40, 250, 50), font=font)
    draw.text((pt[0], pt[1] + h + 20), "坐标位：%s,%s" % (pt[0], pt[1]), (250, 40, 1), font=font1)
    cv_text_im = cv.cvtColor(np.array(pil_im), cv.COLOR_RGB2BGR)
    cv.namedWindow("Target", 0)
    cv.resizeWindow("Target", 1600, 900)
    cv.moveWindow("Target", 10, 50)
    cv.imshow("Target", cv_text_im) #创建一个窗口显示图片,第一个参数是窗口名字,第二个参数是读入的图片
    cv.waitKey(1200)
    cv.destroyWindow("Target") # 删除建立的全部窗口

def click(x,y):
    actions = ActionChains(driver)
    el = driver.find_element_by_xpath('/html/body')
    actions.move_to_element_with_offset(el, x, y).perform()
    actions.move_by_offset(0,0).click().perform()
    driver.implicitly_wait(6)

def selenium_start():
    driver.get(url)
    driver.maximize_window()
    driver.implicitly_wait(4)

def screenshot():
    driver.save_screenshot(path+r"\Run\Demo2\pic\PC\BJ_GOV\background\img.png")

if __name__ == '__main__':
    """
    第一步:启动浏览器,输入网址
    第二步:截取图片,保存到相应路径
    第三步:在大图上匹配小的图片
    第四步:返回坐标,selenium点击操作
    """
    selenium_start()
    screenshot()
    opencv_elementActive()
    driver.close()