UIAutomator2+python大图识别小图

import uiautomator2 as u2
import cv2
import time


def cross_click(d, template_path, threshold=0.8, retry=3):
    """跨分辨率图像点击核心方法"""
    for attempt in range(retry):
        try:
            # 获取设备参数
            device_w = d.info['displayWidth']
            device_h = d.info['displayHeight']
            print(device_w)
            print(device_h)
            scale_factor = 1080 / device_w  # 基准缩放系数‌:ml-citation{ref="1,8" data="citationList"}

            # 屏幕截图处理
            screen = d.screenshot(format='opencv')
            # 强制修改为 600x400 分辨率
            # resized = cv2.resize(screen, (720, 1600), interpolation=cv2.INTER_AREA)
            # cv2.imwrite("D:/stretched.png", resized)  # 保存为JPEG:ml-citation{ref="3,6" data="citationList"}
            # screen = "D:/stretched.png"
            screen_gray = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
            scaled_screen = cv2.resize(screen_gray, (0,0), fx=scale_factor, fy=scale_factor)

            # 模板处理
            template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)
            scaled_template = cv2.resize(template, (0,0), fx=scale_factor, fy=scale_factor)
            h, w = scaled_template.shape

            # 多算法匹配
            res = cv2.matchTemplate(scaled_screen, scaled_template, cv2.TM_CCOEFF_NORMED)
            min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
            print(max_val)
            print(threshold)
            if max_val > threshold:
                # 坐标逆向计算
                raw_x = int((max_loc[0] + w/2) / scale_factor)
                raw_y = int((max_loc[1] + h/2) / scale_factor)

                # 安全边界处理
                safe_x = max(10, min(raw_x, device_w-10))
                safe_y = max(10, min(raw_y, device_h-10))

                d.click(safe_x, safe_y)
                return True

        except Exception as e:
            print(f"第{attempt+1}次尝试失败: {str(e)}")
            time.sleep(1)

    return False

# 使用示例
d = u2.connect("bd197cc7")
cross_click(d, r"D:\png\mt\sy\0.png", threshold=0.75)