import pyautogui
import cv2
import numpy as np
import math

def find_and_click(template_path, target_x, target_y, match_threshold=0.8):
    """
    在屏幕上查找目标图片并点击。

    Args:
        template_path: 目标图片的路径。
        target_x: 预设的坐标 x 轴值。
        target_y: 预设的坐标 y 轴值。
        match_threshold: 匹配阈值，默认值为 0.8。

    Returns:
        如果找到目标图片，则返回 True，否则返回 False。
    """

    # 加载目标图片
    template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)

    # 获取屏幕截图
    screenshot = pyautogui.screenshot()
    screenshot = np.array(screenshot)
    screenshot = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)

    # 使用模板匹配查找目标图片
    result = cv2.matchTemplate(screenshot, template, cv2.TM_CCOEFF_NORMED)

    # 获取匹配结果
    match_locations = np.where(result >= match_threshold)

    # 如果找到匹配结果
    if len(match_locations[0]) > 0:
        # 获取匹配结果的中心坐标
        match_x = match_locations[1][0]
        match_y = match_locations[0][0]

        # 计算匹配结果与预设坐标的距离
        distance = math.sqrt((match_x - target_x)**2 + (match_y - target_y)**2)

        # 如果有多个匹配结果，则选择距离最近的进行点击
        if len(match_locations[0]) > 1:
            for i in range(1, len(match_locations[0])):
                x = match_locations[1][i]
                y = match_locations[0][i]
                new_distance = math.sqrt((x - target_x)**2 + (y - target_y)**2)
                if new_distance < distance:
                    match_x = x
                    match_y = y
                    distance = new_distance

        # 点击目标图片
        pyautogui.click(match_x, match_y)
        return True

    # 如果没有找到匹配结果
    else:
        return False

# 示例代码
if __name__ == "__main__":
    # 目标图片路径
    template_path = "4.png"

    # 预设的坐标
    target_x = 100
    target_y = 100

    # 查找并点击目标图片
    if find_and_click(template_path, target_x, target_y):
        print("目标图片已点击！")
    else:
        print("未找到目标图片！")

优化代码，输出近似图片的位置坐标

import pyautogui
import cv2
import numpy as np
import math

def find_and_print_matches(template_path, target_x, target_y, match_threshold=0.8):
    """
    在屏幕上查找目标图片并打印所有匹配结果的位置。

    Args:
        template_path: 目标图片的路径。
        target_x: 预设的坐标 x 轴值。
        target_y: 预设的坐标 y 轴值。
        match_threshold: 匹配阈值，默认值为 0.8。
    """

    # 加载目标图片
    template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)

    # 获取屏幕截图
    screenshot = pyautogui.screenshot()
    screenshot = np.array(screenshot)
    screenshot = cv2.cvtColor(screenshot, cv2.COLOR_BGR2GRAY)

    # 使用模板匹配查找目标图片
    result = cv2.matchTemplate(screenshot, template, cv2.TM_CCOEFF_NORMED)

    # 获取匹配结果
    match_locations = np.where(result >= match_threshold)

    # 如果找到匹配结果
    if len(match_locations[0]) > 0:
        # 打印所有匹配结果的位置
        print("找到以下匹配结果：")
        for i in range(len(match_locations[0])):
            match_x = match_locations[1][i]
            match_y = match_locations[0][i]
            distance = math.sqrt((match_x - target_x)**2 + (match_y - target_y)**2)
            print(f"位置：({match_x}, {match_y})，距离：{distance:.2f}")
    else:
        print("未找到匹配结果！")

# 示例代码
if __name__ == "__main__":
    # 目标图片路径
    template_path = "4.png"

    # 预设的坐标
    target_x = 100
    target_y = 200

    # 查找并打印匹配结果
    find_and_print_matches(template_path, target_x, target_y)