python 识别图片点击，设置坐标，离设置坐标越近的优先识别点击

import pyautogui
import cv2
import numpy as np
import mathdef 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 = xmatch_y = ydistance = 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 = 100target_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 mathdef 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 = 100target_y = 200# 查找并打印匹配结果find_and_print_matches(template_path, target_x, target_y)