opencv

import time
import cv2
import pyautogui
 
 
def get_xy(img_model_path):
    """
    用来判定游戏画面的点击坐标
    :param img_model_path: 用来检测的模板图片的路径
    :return: 以元组形式返回检测到的区域的中心坐标
    """
    # 将屏幕截图保存
    pyautogui.screenshot().save("./pic/screenshot.png")
    # 载入截图
    img = cv2.imread("./pic/screenshot.png")
    # 图像模板
    img_terminal = cv2.imread("pic/terminal1.png")
    # 读取模板的宽度和高度
    height, width, channel = img_terminal.shape
    # 进行模板匹配
    result = cv2.matchTemplate(img, img_terminal, cv2.TM_SQDIFF_NORMED)
    # 解析出匹配区域的左上角坐标
    upper_left = cv2.minMaxLoc(result)[2]
    # 计算匹配区域右下角的坐标
    lower_right = (upper_left[0] + width, upper_left[1] + height)
    # 计算中心区域的坐标并且返回
    avg = (int((upper_left[0] + lower_right[0]) / 2), int((upper_left[1] + lower_right[1]) / 2))
    return avg
 
 
def auto_click(var_avg):
    """
    接受一个元组参数，自动点击
    :param var_avg: 坐标元组
    :return: None
    """
    pyautogui.click(var_avg[0], var_avg[1], button='left')
    time.sleep(1)
 
 
def routine(img_model_path, name):
    avg = get_xy(img_model_path)
    print(f'正在点击{name}')
    auto_click(avg)
 
 
def print_hi(name):
    # Use a breakpoint in the code line below to debug your script.
    print(f'Hi, {name}')  # Press Ctrl+F8 to toggle the breakpoint.
 
 
def find_img_center_and_click(img_model_path, name):
    result = pyautogui.locateCenterOnScreen(img_model_path, confidence=0.8)
    print(f'正在点击{name}' + f'{result}')
    auto_click(result)
 
 
if __name__ == '__main__':
    print_hi('PyCharm')
    while (True):
        # routine("./pic/terminal1.png", '播放')
        # time.sleep(3)
        # routine("./pic/terminal2.png", '停止')
        # time.sleep(3)
 
        find_img_center_and_click("./pic/terminal1.png", '播放')
        time.sleep(3)
        find_img_center_and_click("./pic/terminal2.png", '停止')
        time.sleep(3)