合并代码

Module/FlaskService.py

@@ -246,7 +246,7 @@ def longPressAction():
 def growAccount():
     body = request.get_json()
     udid = body.get("udid")
-    # Variables.commentList = body.get("comment")
+    Variables.commentList = body.get("comment")
 
     manager = ScriptManager()
     event = threading.Event()
@@ -292,7 +292,7 @@ def passAnchorData():
 
         # 主播列表
         acList = data.get("anchorList", [])
-        # Variables.commentList = data.get("comment")
+        Variables.commentList = data.get("comment")
 
 
         LogManager.info(f"[INFO] 获取数据: {idList} {acList}")
@@ -662,17 +662,61 @@ def changeAccount():
 
 @app.route('/test', methods=['POST'])
 def test():
-    body = request.get_json()
+    import wda
+    import cv2
+    import numpy as np
 
-    manager = ScriptManager()
+    # 设备的UDID
-    threading.Event()
+    udid = "00008110-000120603C13801E"
 
-    # 启动脚本
+    # 连接到设备
-    manager.test()
+    client = wda.USBClient(udid)
-    # thread = threading.Thread(target=, args=(udid,))
+    session = client.session()
-    # # 添加到线程管理
+
-    # thread.start()
+    # 设置Appium的截图深度
-    return ResultData(data="", code=200, message="成功").toJson()
+    session.appium_settings({"snapshotMaxDepth": 15})
+
+    # 获取当前屏幕截图
+    screenshot = session.screenshot()
+    screenshot = cv2.imdecode(np.frombuffer(screenshot, np.uint8), cv2.IMREAD_COLOR)
+
+    # 读取大图和小图
+    large_image = screenshot  # 这里使用截图作为大图
+    template = cv2.imread(r'E:\python\Scrcpy_test\open-cv-tk\insert_comment.png', 0)  # 0 表示以灰度模式读取
+
+    # 检查图像是否成功加载
+    if template is None:
+        print("小图加载失败，请检查路径")
+        exit()
+
+    # 获取模板的宽度和高度
+    w, h = template.shape[::-1]
+
+    # 使用模板匹配方法
+    result = cv2.matchTemplate(large_image, template, cv2.TM_CCOEFF_NORMED)
+
+    # 设定阈值
+    threshold = 0.8
+    loc = np.where(result >= threshold)
+
+    # 遍历所有匹配点
+    if loc[0].size > 0:  # 检查是否有匹配点
+        for pt in zip(*loc[::-1]):  # 将坐标转换为 (x, y) 格式
+            cv2.rectangle(large_image, pt, (pt[0] + w, pt[1] + h), (0, 255, 0), 2)
+            print(f"找到匹配区域，坐标：{pt}，尺寸：{(w, h)}")
+    else:
+        print("未找到匹配区域，请检查模板和大图的内容，或调整阈值")
+
+    # 保存结果
+    cv2.imwrite('matched_result.png', large_image)
+
+    # 显示结果
+    cv2.imshow('Matched Result', large_image)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+
+    # 关闭会话
+    session.close()
 
 
 if __name__ == '__main__':

Utils/LogManager.py

@@ -26,7 +26,7 @@ def _force_utf8_everywhere():
     except Exception:
         pass
 
-# _force_utf8_everywhere()
+_force_utf8_everywhere()
 
 class LogManager:
     """

Utils/OCRUtils.py

@@ -0,0 +1,233 @@
+import cv2
+import numpy as np
+from typing import List, Tuple, Union, Optional
+from PIL import Image
+
+ArrayLikeImage = Union[np.ndarray, str, Image.Image]
+
+class OCRUtils:
+    @classmethod
+    def _to_gray(cls, img: ArrayLikeImage) -> np.ndarray:
+        """
+        接受路径/np.ndarray/PIL.Image，统一转为灰度 np.ndarray。
+        """
+        # 路径
+        if isinstance(img, str):
+            arr = cv2.imread(img, cv2.IMREAD_GRAYSCALE)
+            if arr is None:
+                raise FileNotFoundError(f"图像加载失败，请检查路径: {img}")
+            return arr
+
+        # PIL.Image
+        if isinstance(img, Image.Image):
+            return cv2.cvtColor(np.array(img.convert("RGB")), cv2.COLOR_RGB2GRAY)
+
+        # numpy 数组
+        if isinstance(img, np.ndarray):
+            if img.ndim == 2:
+                return img  # 已是灰度
+            if img.ndim == 3:
+                return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+            raise ValueError("不支持的图像维度（期望 2D 灰度或 3D BGR/RGB）")
+
+        raise TypeError("large_image 类型必须是 str / np.ndarray / PIL.Image.Image")
+
+    @classmethod
+    def non_max_suppression(
+        cls,
+        boxes: List[List[float]],
+        scores: Optional[np.ndarray] = None,
+        overlapThresh: float = 0.5
+    ) -> np.ndarray:
+        """
+        boxes: [ [x1,y1,x2,y2], ... ]
+        scores: 每个框的置信度（用于“按分数做 NMS”）。若为 None，则退化为按 y2 排序的经典近似。
+        返回: 经过 NMS 保留的 boxes(int) ndarray，形状 (N,4)
+        """
+        if len(boxes) == 0:
+            return np.empty((0, 4), dtype=int)
+
+        boxes = np.asarray(boxes, dtype=np.float32)
+        x1, y1, x2, y2 = boxes.T
+        areas = (x2 - x1 + 1) * (y2 - y1 + 1)
+
+        if scores is None:
+            order = np.argsort(y2)  # 经典写法
+        else:
+            scores = np.asarray(scores, dtype=np.float32)
+            order = np.argsort(scores)[::-1]  # 分数从高到低
+
+        keep = []
+        while order.size > 0:
+            i = order[0] if scores is not None else order[-1]
+            keep.append(i)
+
+            rest = order[1:] if scores is not None else order[:-1]
+
+            xx1 = np.maximum(x1[i], x1[rest])
+            yy1 = np.maximum(y1[i], y1[rest])
+            xx2 = np.minimum(x2[i], x2[rest])
+            yy2 = np.minimum(y2[i], y2[rest])
+
+            w = np.maximum(0, xx2 - xx1 + 1)
+            h = np.maximum(0, yy2 - yy1 + 1)
+            inter = w * h
+            ovr = inter / areas[rest]
+
+            inds = np.where(ovr <= overlapThresh)[0]
+            order = rest[inds]
+
+        return boxes[keep].astype(int)
+
+    # @classmethod
+    # def find_template(
+    #     cls,
+    #     template_path: str,
+    #     large_image: ArrayLikeImage,
+    #     threshold: float = 0.8,
+    #     overlapThresh: float = 0.5,
+    #     return_boxes: bool = False
+    # ) -> Union[List[Tuple[int, int]], Tuple[List[Tuple[int, int]], np.ndarray]]:
+    #     """
+    #     在 large_image 中查找 template_path 模板的位置。
+    #     - large_image 可为文件路径、np.ndarray 或 PIL.Image
+    #     - threshold: 模板匹配阈值（TM_CCOEFF_NORMED）
+    #     - overlapThresh: NMS 重叠阈值
+    #     - return_boxes: True 时同时返回保留的框数组 (N,4)
+    #
+    #     返回:
+    #       centers 或 (centers, boxes)
+    #       centers: [(cx, cy), ...]
+    #       boxes:   [[x1,y1,x2,y2], ...] (np.ndarray, int)
+    #     """
+    #     # 模板（灰度）
+    #     template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)
+    #     if template is None:
+    #         raise FileNotFoundError(f"模板图像加载失败，请检查路径: {template_path}")
+    #
+    #     # 大图（灰度）
+    #     gray = cls._to_gray(large_image)
+    #
+    #     # 模板尺寸
+    #     tw, th = template.shape[::-1]
+    #
+    #     # 模板匹配（相关系数归一化）
+    #     result = cv2.matchTemplate(gray, template, cv2.TM_CCOEFF_NORMED)
+    #
+    #     # 阈值筛选
+    #     ys, xs = np.where(result >= threshold)
+    #     if len(xs) == 0:
+    #         return ([], np.empty((0, 4), dtype=int)) if return_boxes else []
+    #
+    #     # 收集候选框与分数
+    #     boxes = []
+    #     scores = []
+    #     for (x, y) in zip(xs, ys):
+    #         boxes.append([x, y, x + tw, y + th])
+    #         scores.append(result[y, x])
+    #
+    #     # 按分数做 NMS
+    #     boxes_nms = cls.non_max_suppression(boxes, scores=np.array(scores), overlapThresh=overlapThresh)
+    #
+    #     # 计算中心点
+    #     centers = [((x1 + x2) // 2, (y1 + y2) // 2) for (x1, y1, x2, y2) in boxes_nms]
+    #
+    #
+    #
+    #     if return_boxes:
+    #         return centers, boxes_nms
+    #
+    #
+    #     return centers
+
+    @classmethod
+    def find_template(
+            cls,
+            template_path: str,
+            large_image: ArrayLikeImage,
+            threshold: float = 0.8,
+            overlapThresh: float = 0.5,
+            return_boxes: bool = False
+    ) -> Union[List[Tuple[int, int]], Tuple[List[Tuple[int, int]], np.ndarray]]:
+        """
+        在 large_image 中查找 template_path 模板的位置。
+        - large_image 可为文件路径、np.ndarray 或 PIL.Image
+        - threshold: 模板匹配阈值（TM_CCOEFF_NORMED）
+        - overlapThresh: NMS 重叠阈值
+        - return_boxes: True 时同时返回保留的框数组 (N,4)
+
+        若检测结果为空，则在相同阈值下最多重试三次（共 3 次尝试）。
+        返回:
+          centers 或 (centers, boxes)
+          centers: [(cx, cy), ...]
+          boxes:   [[x1,y1,x2,y2], ...] (np.ndarray, int)
+        """
+        # 模板（灰度）
+        template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)
+        if template is None:
+            raise FileNotFoundError(f"模板图像加载失败，请检查路径: {template_path}")
+
+        # 大图（灰度）
+        gray = cls._to_gray(large_image)
+
+        # 模板尺寸
+        tw, th = template.shape[::-1]
+
+        # 内部：执行一次匹配并返回 (centers, boxes_nms)
+        def _match_once(cur_threshold: float):
+            # 模板匹配（相关系数归一化）
+            result = cv2.matchTemplate(gray, template, cv2.TM_CCOEFF_NORMED)
+
+            # 阈值筛选
+            ys, xs = np.where(result >= cur_threshold)
+            if len(xs) == 0:
+                return [], np.empty((0, 4), dtype=int)
+
+            # 收集候选框与分数
+            boxes = []
+            scores = []
+            for (x, y) in zip(xs, ys):
+                boxes.append([int(x), int(y), int(x + tw), int(y + th)])
+                scores.append(float(result[y, x]))
+
+            # 按分数做 NMS
+            boxes_nms = cls.non_max_suppression(
+                boxes,
+                scores=np.asarray(scores, dtype=np.float32),
+                overlapThresh=overlapThresh
+            )
+
+            # 计算中心点（转为 Python int）
+            centers = [(int((x1 + x2) // 2), int((y1 + y2) // 2))
+                       for (x1, y1, x2, y2) in boxes_nms]
+
+            # 统一为 np.ndarray[int]
+            boxes_nms = np.asarray(boxes_nms, dtype=int)
+            return centers, boxes_nms
+
+        # ===== 重试控制（最多 3 次）=====
+        MAX_RETRIES = 3
+        THRESHOLD_DECAY = 0.0  # 如需越试越宽松，可改为 0.02~0.05；不需要则保持 0
+        MIN_THRESHOLD = 0.6
+
+        cur_threshold = float(threshold)
+        last_centers, last_boxes = [], np.empty((0, 4), dtype=int)
+
+        for attempt in range(MAX_RETRIES):
+            centers, boxes_nms = _match_once(cur_threshold)
+            if centers:
+                if return_boxes:
+                    return centers, boxes_nms
+                return centers
+
+            # 记录最后一次（若最终失败按规范返回空）
+            last_centers, last_boxes = centers, boxes_nms
+
+            # 为下一次尝试准备（这里默认不衰减阈值；如需可打开 THRESHOLD_DECAY）
+            if attempt < MAX_RETRIES - 1 and THRESHOLD_DECAY > 0.0:
+                cur_threshold = max(MIN_THRESHOLD, cur_threshold - THRESHOLD_DECAY)
+
+        # 全部尝试失败
+        if return_boxes:
+            return last_centers, last_boxes
+        return last_centers

script/ScriptManager.py

@@ -1,26 +1,20 @@
-import atexit
 import random
 import re
-import subprocess
 import threading
 import time
-from datetime import datetime
-from enum import Enum
 from pathlib import Path
 
 import wda
 import os
-
+from datetime import datetime
-# from ultralytics import YOLO
-
 from Entity import Variables
 from Utils.AiUtils import AiUtils
 from Utils.ControlUtils import ControlUtils
 from Utils.IOSAIStorage import IOSAIStorage
 from Utils.JsonUtils import JsonUtils
 from Utils.LogManager import LogManager
-from Entity.Variables import anchorList, removeModelFromAnchorList, anchorWithSession
+from Entity.Variables import anchorList
-# from Utils.OCRUtils import OCRUtils
+from Utils.OCRUtils import OCRUtils
 from Utils.Requester import Requester
 import Entity.Variables as ev
 from Utils.TencentOCRUtils import TencentOCR
@@ -40,38 +34,38 @@ class ScriptManager():
 
     def __init__(self):
         super().__init__()
-        # weight_path = Path(__file__).resolve().parent.parent / "best.pt"
+
-        # self.model = YOLO(weight_path)  # 只传一个参数
+        # 初始化获取模版所在的地址
+        current_dir = Path(__file__).resolve().parent
+        # 项目根目录（假设你的类文件在项目的子目录里，比如 Module/OCR/OCRUtils.py）
+        project_root = current_dir.parent  # 如果你确定这个文件就在项目根目录下，可省略这行
+        # resources 文件夹路径
+
+        # 获取相应的模板的地址
+        self.resources_dir = project_root / "resources"
+        self.comment_dir = self.resources_dir / "comment.png"
+        self.comment_add_dir = self.resources_dir / "insert_comment.png"
 
         self.initialized = True  # 标记已初始化
 
-    # 检测yolo识别的坐标
-    def get_comment_coords(self, file_path, imgsz=960, conf=0.01):
-        """
-        用 YOLOv8 检测评论区域，返回第一个框的中心坐标 (cx, cy)
-        未检测到返回 None
-        """
-        results = self.model.predict(source=file_path, imgsz=imgsz, conf=conf)
-        for r in results:
-            if len(r.boxes) == 0:
-                continue
-            for box in r.boxes:
-                xy = box.xyxy[0][:4].cpu().numpy()
-                cx, cy = (xy[0] + xy[2]) / 2, (xy[1] + xy[3]) / 2
-                return int(cx), int(cy)
-        return None
-
     # ========= 评论逻辑 =========
     def comment_flow(self, filePath, session, udid, recomend_cx, recomend_cy):
         """评论一条龙：点评论框->输入->发送->返回"""
-        coord = self.get_comment_coords(filePath)
+
+
+
+        coord = OCRUtils.find_template(str(self.comment_dir), filePath)
         if not coord:
             return  # 没检测到评论按钮就拉倒
+
         print(11111111111)
-        cx, cy = coord
+        cx, cy = coord[0]  # ✅ 注意这里取第一个点
-        session.tap(int(cx / 3), int(cy / 3))
+
+        session.click(int(cx / 3), int(cy / 3))
+
+        print(f"点击评论的坐标：{int(cx / 3)}, {int(cy / 3)}")
         time.sleep(2)
-        print(f"评论的坐标：{cx}, {cy}")
+
         # 截图二判（防止键盘弹出后坐标变化）
         img = session.screenshot()
         time.sleep(2)
@@ -81,13 +75,16 @@ class ScriptManager():
         # 从评论列表中随机取出一条数据,进行评论
         single_comment = random.choice(Variables.commentList)
 
-        coord2 = self.get_comment_coords(filePath)
+        coord2 = OCRUtils.find_template(str(self.comment_add_dir), filePath)
-        print(single_comment)
+        # print(single_comment)
         if coord2:  # 二判命中
-            cx2, cy2 = coord2
+            cx2, cy2 = coord2[0]
             print(f"添加评论：{cx2, cy2}")
             session.tap(int(cx2 / 3), int(cy2 / 3))
+            print(f"点击添加评论的坐标：{int(cx2 / 3)}, {int(cy2 / 3)}")
+
             session.send_keys(f"{single_comment}\n")
+            # session.send_keys(f"hello\n")
             time.sleep(2)
             LogManager.method_info("评论成功", "养号", udid)
 
@@ -101,12 +98,10 @@ class ScriptManager():
         print("调用刷视频")
         while not event.is_set():
 
-            print(11111111111111111)
             try:
                 # ========= 初始化 =========
                 client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
-                print(2222222222222222)
                 # 关闭并重新打开 TikTok
                 if not is_monitoring:
                     ControlUtils.closeTikTok(session, udid)
@@ -114,8 +109,6 @@ class ScriptManager():
                     ControlUtils.openTikTok(session, udid)
                     event.wait(timeout=3)
 
-
-
                 LogManager.method_info("养号重启tiktok", "养号", udid)
 
                 AiUtils.makeUdidDir(udid)
@@ -136,7 +129,6 @@ class ScriptManager():
                         recomend_cx = bounds[0] + bounds[2] // 2
                         recomend_cy = bounds[1] + bounds[3] // 2
 
-
                     if not el.exists:
                         # 记录日志
                         LogManager.method_error("找不到推荐按钮,养号出现问题,重启养号功能", "养号", udid=udid)
@@ -206,7 +198,7 @@ class ScriptManager():
                                 LogManager.method_info("继续观看视频", "养号", udid)
 
                                 LogManager.method_info("准备划到下一个视频", "养号", udid)
-                                ControlUtils.swipe_up(udid)
+                                # ControlUtils.swipe_up(udid)
                             else:
                                 LogManager.method_error("找不到首页按钮。出错了", "养号", udid)
                         # else:
@@ -217,11 +209,9 @@ class ScriptManager():
                         #         event.wait(timeout=1)
                         #     client.swipe_up()
 
-                        # 评论
-                        # 使用训练好的best.pt(yolo v8模型)进行识别评论区域
 
-                        # if random.random() > 0.70:
+                        if random.random() > 0.70:
-                        #     self.comment_flow(filePath, session, udid, recomend_cx, recomend_cy)
+                            self.comment_flow(filePath, session, udid, recomend_cx, recomend_cy)
 
                         videoTime = random.randint(15, 30)
                         for _ in range(videoTime):
@@ -272,7 +262,7 @@ class ScriptManager():
         while not event.is_set():
             try:
                 # —— 每次重启都新建 client/session ——
-                client = wda.USBClient(udid,ev.wdaFunctionPort)
+                client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
                 session.appium_settings({"snapshotMaxDepth": 15})
 
@@ -390,7 +380,7 @@ class ScriptManager():
                 LogManager.method_error(f"watchLiveForGrowth 异常（第{retry_count}次）：{repr(e)}", "直播养号", udid)
                 # 尝试轻量恢复一次，避免一些短暂性 session 失效
                 try:
-                    client = wda.USBClient(udid,ev.wdaFunctionPort)
+                    client = wda.USBClient(udid, ev.wdaFunctionPort)
                     _ = client.session()
                 except Exception:
                     pass
@@ -426,7 +416,7 @@ class ScriptManager():
     # 关注打招呼以及回复主播消息
     def greetNewFollowers(self, udid, needReply, needTranslate, event):
 
-        client = wda.USBClient(udid,ev.wdaFunctionPort)
+        client = wda.USBClient(udid, ev.wdaFunctionPort)
         session = client.session()
 
         print(f"是否要自动回复消息：{needReply}")
@@ -594,9 +584,8 @@ class ScriptManager():
                         event.wait(timeout=1)
                     LogManager.method_info("停止脚本成功", method="task")
 
-
                     # 使用yolo v8模型进行评论
-                    # self.comment_flow(filePath, session, udid, 100, 100)
+                    self.comment_flow(filePath, session, udid, 100, 100)
 
                     if count != 0:
                         ControlUtils.swipe_up(udid)
@@ -735,7 +724,7 @@ class ScriptManager():
                     event.wait(timeout=3)
 
                 print("重新创建wda会话 防止wda会话失效")
-                client = wda.USBClient(udid,ev.wdaFunctionPort)
+                client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
                 # 执行完成之后。继续点击搜索
                 session.appium_settings({"snapshotMaxDepth": 15})
@@ -764,7 +753,7 @@ class ScriptManager():
     # 关注打招呼以及回复主播消息(联盟号)
     def followAndGreetUnion(self, udid, needReply, needTranslate, event):
 
-        client = wda.USBClient(udid,ev.wdaFunctionPort)
+        client = wda.USBClient(udid, ev.wdaFunctionPort)
         session = client.session()
 
         print(f"是否要自动回复消息：{needReply}")
@@ -994,7 +983,7 @@ class ScriptManager():
                     event.wait(timeout=3)
 
                 print("重新创建wda会话 防止wda会话失效")
-                client = wda.USBClient(udid,ev.wdaFunctionPort)
+                client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
                 # 执行完成之后。继续点击搜索
                 session.appium_settings({"snapshotMaxDepth": 15})
@@ -1007,7 +996,7 @@ class ScriptManager():
     def replyMessages(self, udid, event):
 
         try:
-            client = wda.USBClient(udid,ev.wdaFunctionPort)
+            client = wda.USBClient(udid, ev.wdaFunctionPort)
             session = client.session()
         except Exception as e:
             LogManager.method_error(f"创建wda会话异常: {e}", "检测消息", udid)
@@ -1032,7 +1021,7 @@ class ScriptManager():
                 LogManager.method_info(f"出现异常时，稍等再重启 TikTok 并重试 异常是: {e}", "监控消息", udid)
 
                 LogManager.method_info(f"出现异常，重新创建wda", "监控消息", udid)
-                client = wda.USBClient(udid,ev.wdaFunctionPort)
+                client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
 
                 LogManager.method_info(f"重启 TikTok", "监控消息", udid)
@@ -1077,7 +1066,6 @@ class ScriptManager():
                 while True:
                     print("循环开始")
 
-
                     info_count = 0
 
                     # 创建新的会话
@@ -1248,9 +1236,6 @@ class ScriptManager():
                                 break
                             time.sleep(1)
 
-
-
-
                         LogManager.method_info(f"获取主播的名称:{anchor_name}", "检测消息", udid)
                         LogManager.method_info(f"获取主播最后发送的消息 即将翻译:{last_in}", "检测消息", udid)
                         chinese_last_msg_text = Requester.translationToChinese(last_in)
@@ -1272,8 +1257,6 @@ class ScriptManager():
                         LogManager.method_info(f"主播最后发送的数据，传递给前端进行记录:{chinese_last_msg_text}",
                                                "检测消息", udid)
 
-
-
                         # 把主播的名称存储到c盘
                         JsonUtils.append_json_items(last_data, "log/last_message.json")
 
@@ -1470,7 +1453,7 @@ class ScriptManager():
             try:
                 LogManager.method_info("开始进行切换账号", "切换账号", udid)
 
-                client = wda.USBClient(udid,ev.wdaFunctionPort)
+                client = wda.USBClient(udid, ev.wdaFunctionPort)
                 session = client.session()
 
                 # 重启打开

script/mac_wda_agent.py

@@ -1,38 +0,0 @@
-# windows_run.py（替换你起 iproxy 的那几行）
-import os, subprocess, time, requests, wda
-from pathlib import Path
-
-UDID = "00008110-00067D0014D3B01E"
-MAC = "http://192.168.1.219:8765"
-
-# 让 Mac 起 WDA（不转发）
-requests.post(f"{MAC}/startWDA", json={"udid": UDID}, timeout=600).raise_for_status()
-
-# 计算 iproxy 绝对路径（项目根/resources/iproxy/iproxy.exe）
-BASE = Path(__file__).resolve().parents[1]  # iOSAI/
-IPROXY = BASE / "resources" / "iproxy" / "iproxy.exe"
-if not IPROXY.exists():
-    raise FileNotFoundError(f"iproxy 不在这里: {IPROXY}")
-
-# 可选：把 iproxy 目录加入 PATH，避免 DLL 依赖找不到
-env = os.environ.copy()
-env["PATH"] = str(IPROXY.parent) + os.pathsep + env.get("PATH", "")
-try:
-    os.add_dll_directory(str(IPROXY.parent))  # 仅 Windows 有效
-except Exception:
-    pass
-
-# 起 iproxy：本地 9111 -> 设备 8100
-p = subprocess.Popen([str(IPROXY), "-u", UDID, "9111", "8100"],
-                     cwd=str(IPROXY.parent),
-                     stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
-                     text=True, creationflags=0x08000000)
-
-# 探活 WDA
-c = wda.Client("http://127.0.0.1:9111")
-
-for _ in range(120):
-    try:
-        print(c.status()); break
-    except:
-        time.sleep(1)

script/windows_run.py

@@ -1,35 +0,0 @@
-from pathlib import Path
-import os, subprocess, time, requests, wda
-
-UDID = "00008110-00067D0014D3B01E"
-MAC  = "http://192.168.1.90:8765"
-
-# 让 Mac 起 WDA
-requests.post(f"{MAC}/startWDA", json={"udid": UDID}, timeout=600).raise_for_status()
-
-# 计算 iproxy 绝对路径：项目根/resources/iproxy/iproxy.exe
-BASE = Path(__file__).resolve().parents[1]          # iOSAI/
-IPROXY = BASE / "resources" / "iproxy" / "iproxy.exe"
-if not IPROXY.exists():
-    raise FileNotFoundError(f"iproxy 不在这里：{IPROXY}")
-
-# 避免 DLL 找不到：把目录加入 PATH（以及 Windows 的 DLL 搜索路径）
-env = os.environ.copy()
-env["PATH"] = str(IPROXY.parent) + os.pathsep + env.get("PATH", "")
-try:
-    os.add_dll_directory(str(IPROXY.parent))
-except Exception:
-    pass
-
-# 起 iproxy：本地 9111 -> 设备 8100
-p = subprocess.Popen([str(IPROXY), "-u", UDID, "9111", "8100"],
-                     cwd=str(IPROXY.parent),
-                     stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)
-
-# 探活 WDA
-c = wda.Client("http://127.0.0.1:9111")
-for _ in range(120):
-    try:
-        print(c.status()); break
-    except Exception:
-        time.sleep(1)