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HuangHai
@@ -118,117 +118,159 @@ class TeLaiDianCrawler(BaseCrawler):
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address = basic_info.get("address") or station_info.get("address")
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logger.info(f"详情页基础信息识别完成: {station_name} | {address}")
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# 2. 向上滑动以露出价格按钮
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logger.info(f"执行滑动操作以显示价格按钮 (距离比例: {DETAIL_SCROLL_DISTANCE_RATIO})...")
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# 从屏幕中间向上滑动
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d.swipe_ext("up", scale=DETAIL_SCROLL_DISTANCE_RATIO)
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await asyncio.sleep(1.5)
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# 3. 点击“价格信息”区域 (识别橘红色价格 P0)
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price_button_screen = take_screenshot(d, f"tld_before_price_click_{int(time.time())}.jpg")
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logger.info("正在通过 CV 寻找橘红色价格区域 (P0)...")
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# 2. 小步快跑寻找价格入口 (结合 CV 和 VLM)
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found_entrance = False
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entrance_point = None
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max_search_steps = 4
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click_point = detect_price_click_point_cv(price_button_screen)
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logger.info(f"开始“小步快跑”策略寻找价格入口，最多尝试 {max_search_steps} 次小幅度滑动...")
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# 调试：生成点击点标注图
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if click_point:
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debug_flag_path = price_button_screen.replace(".jpg", "_click_debug.jpg")
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img_debug = read_image(price_button_screen)
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if img_debug is not None:
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cv2.circle(img_debug, (click_point[0], click_point[1]), 20, (0, 0, 255), -1) # 红色大圆点
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cv2.line(img_debug, (click_point[0]-40, click_point[1]), (click_point[0]+40, click_point[1]), (255, 255, 255), 3)
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cv2.line(img_debug, (click_point[0], click_point[1]-40), (click_point[0], click_point[1]+40), (255, 255, 255), 3)
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save_image(debug_flag_path, img_debug)
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logger.info(f"点击点调试图已保存: {debug_flag_path}")
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try:
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if click_point:
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logger.info(f"CV 成功定位价格区域，点击坐标: {click_point}")
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d.click(click_point[0], click_point[1])
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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for step in range(max_search_steps):
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current_screen = take_screenshot(d, f"tld_search_price_step_{step}.jpg")
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logger.info(f"--- 寻找入口 第 {step+1} 步 ---")
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# 优先使用 CV 快速识别橘红色价格 P0
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logger.info("尝试 CV 识别价格卡片 (P0)...")
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cv_point = detect_price_click_point_cv(current_screen)
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if cv_point:
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logger.info(f"✅ CV 在第 {step+1} 步成功定位入口: {cv_point}")
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entrance_point = cv_point
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found_entrance = True
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else:
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logger.warning("CV 未能定位价格区域，尝试模板匹配兜底...")
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template_path = os.path.join(project_root, "Apps", "TeLaiDian", "Template", "jgxx.jpg")
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match = d.image.match(template_path)
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if match:
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d.image.click(template_path)
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# CV 没找到，使用 VLM 进行深度语义检查
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logger.info("CV 未找到，启动 VLM 深度语义识别...")
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vlm_res = await self.read_image_kit.find_price_entrance_vlm(current_screen)
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if vlm_res.get("found"):
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norm_point = vlm_res.get("point") # [x, y] in 0-1000
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if norm_point and len(norm_point) == 2:
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w, h = d.window_size()
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entrance_point = [int(norm_point[0] * w / 1000), int(norm_point[1] * h / 1000)]
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logger.info(f"✅ VLM 在第 {step+1} 步成功定位入口: {entrance_point} ({vlm_res.get('reason')})")
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found_entrance = True
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else:
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logger.warning("模板匹配也失败，执行坐标兜底...")
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w, h = d.window_size()
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d.click(w // 2, int(h * 0.45)) # 滑动后价格通常在屏幕中上部
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await asyncio.sleep(2.0) # 等待页面加载及小程序可能的自动滚动
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logger.info(f"第 {step+1} 步未发现入口: {vlm_res.get('reason', '未知原因')}")
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# 如果找到入口，进行标注并点击
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if found_entrance and entrance_point:
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debug_flag_path = current_screen.replace(".jpg", "_entrance_found.jpg")
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img_debug = read_image(current_screen)
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if img_debug is not None:
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cv2.circle(img_debug, (entrance_point[0], entrance_point[1]), 25, (0, 255, 0), 5) # 绿色大圆圈
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save_image(debug_flag_path, img_debug)
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logger.info(f"入口位置标注图已保存: {debug_flag_path}")
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# 额外处理：小程序可能会自动滚动到当前时段，我们需要手动滚回顶部以抓取完整数据
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logger.info("向上滚动 2 次，确保回到 00:00 时段顶部...")
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for _ in range(2):
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d.swipe_ext("down", scale=0.9) # 向下滑动 = 页面向上滚动
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await asyncio.sleep(0.8)
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logger.info(f"正在点击价格入口: {entrance_point}")
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d.click(entrance_point[0], entrance_point[1])
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# 清理临时截图
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if os.path.exists(current_screen): os.remove(current_screen)
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break
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# 没找到，小步向上滚动
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if step < max_search_steps - 1:
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scroll_scale = 0.35
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logger.info(f"未发现入口，执行小幅度向上滑动 (scale={scroll_scale})...")
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d.swipe_ext("up", scale=scroll_scale)
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await asyncio.sleep(1.2)
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# 清理临时截图
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if os.path.exists(current_screen): os.remove(current_screen)
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if not found_entrance:
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logger.warning("“小步快跑”策略未能找到价格入口，尝试坐标兜底...")
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w, h = d.window_size()
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d.click(w // 2, int(h * 0.45))
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await asyncio.sleep(WAIT_DETAIL_PAGE_LOAD)
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# 3. 进入分时电价页面后的处理
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try:
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# 1. 延长等待时间，等待小程序自动定位到当前时段的滚动完成
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logger.info("已点击进入价格详情，等待小程序自动滚动定位完成 (4秒)...")
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await asyncio.sleep(4.0)
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# 2. 回到 00:00 原点：要看到上面的内容，需要“向下拉动”页面（即向上滚动列表）
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logger.info("执行向下拉动，尝试回到 00:00 时段顶部...")
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for i in range(3):
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# swipe_ext("down") 是手指从上往下划，动作是“向下”，结果是页面“向上”滚动
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d.swipe_ext("down", scale=0.8)
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await asyncio.sleep(0.5)
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except Exception as e:
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logger.error(f"点击价格区域失败: {e}")
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finally:
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if os.path.exists(price_button_screen): os.remove(price_button_screen)
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logger.error(f"处理分时电价页面初始状态失败: {e}")
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# 4. 循环滑动抓取完整分时电价
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all_prices = []
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last_price_md5 = None
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price_page_count = 0
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max_price_pages = 3 # 分时电价通常不会超过3页
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max_price_pages = 4 # 增加到4页确保覆盖 00:00-24:00
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screenshot_tasks = [] # 用于异步分析图片的任务列表
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temp_screenshots = [] # 记录临时文件以便后续清理
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logger.info("开始循环截图并异步抓取完整分时电价...")
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logger.info("开始循环截图（UI操作优先，后台并行分析）...")
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while price_page_count < max_price_pages:
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price_screen_path = take_screenshot(d, f"tld_detail_price_{int(time.time())}_{price_page_count}.jpg")
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# 校验页面是否发生滚动变化
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curr_md5 = get_image_content_md5(price_screen_path, top_ratio=0.2, bottom_ratio=0.2)
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if curr_md5 == last_price_md5:
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logger.info("价格页面内容无变化，判定已触底")
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if os.path.exists(price_screen_path): os.remove(price_screen_path)
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break
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last_price_md5 = curr_md5
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temp_screenshots.append(price_screen_path)
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try:
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while price_page_count < max_price_pages:
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price_screen_path = take_screenshot(d, f"tld_detail_price_{int(time.time())}_{price_page_count}.jpg")
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# 校验页面是否发生滚动变化
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curr_md5 = get_image_content_md5(price_screen_path, top_ratio=0.2, bottom_ratio=0.2)
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if curr_md5 == last_price_md5:
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logger.info("价格页面内容无变化，判定已触底")
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if os.path.exists(price_screen_path): os.remove(price_screen_path)
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break
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last_price_md5 = curr_md5
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temp_screenshots.append(price_screen_path)
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logger.info(f"已截取价格详情页第 {price_page_count + 1} 页: {price_screen_path}，加入异步分析队列")
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# 创建异步任务，但不立即 await
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task = self.read_image_kit.analyze_detail_price(price_screen_path)
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screenshot_tasks.append(task)
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# 向上滑动，继续抓取下一屏
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logger.info("向上滑动，准备截取下一屏价格...")
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d.swipe_ext("up", scale=0.8)
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await asyncio.sleep(1.2)
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price_page_count += 1
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logger.info(f"已截取价格详情页第 {price_page_count + 1} 页: {price_screen_path}，启动后台异步分析")
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# 使用 asyncio.create_task 立即在后台开始执行分析
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task = asyncio.create_task(self.read_image_kit.analyze_detail_price(price_screen_path))
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screenshot_tasks.append(task)
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# 向上滚动列表（手指向上划），看后面的时段
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logger.info("向上滚动列表，准备截取下一屏价格...")
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d.swipe_ext("up", scale=0.8)
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await asyncio.sleep(1.0)
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price_page_count += 1
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# 异步等待所有图片识别任务完成
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if screenshot_tasks:
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logger.info(f"正在异步分析 {len(screenshot_tasks)} 张价格截图...")
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results = await asyncio.gather(*screenshot_tasks)
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# 等待所有后台分析任务完成
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if screenshot_tasks:
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logger.info(f"UI 操作已完成，等待 {len(screenshot_tasks)} 个后台分析任务结束...")
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results = await asyncio.gather(*screenshot_tasks, return_exceptions=True)
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for res in results:
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if isinstance(res, Exception):
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logger.error(f"后台分析任务出错: {res}")
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continue
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if res:
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# 深度去重：根据时段 (start, end) 合并
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for p in res:
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is_duplicate = False
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for existing in all_prices:
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if p.get('start') == existing.get('start') and p.get('end') == existing.get('end'):
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is_duplicate = True
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# 字段补全逻辑
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for key in ['price', 'plus_price', 'market_price', 'elec_price', 'service_price']:
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if p.get(key) is not None and (existing.get(key) is None or existing.get(key) == 0):
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existing[key] = p[key]
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break
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if not is_duplicate:
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all_prices.append(p)
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except Exception as e:
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logger.error(f"抓取价格详情过程中发生异常: {e}")
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finally:
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# 无论是否异常，都要确保清理未完成的任务，避免 "never awaited" 警告
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for task in screenshot_tasks:
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if not task.done():
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task.cancel()
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for page_prices in results:
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if page_prices:
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# 深度去重：根据时段 (start, end) 合并
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for p in page_prices:
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is_duplicate = False
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for existing in all_prices:
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if p.get('start') == existing.get('start') and p.get('end') == existing.get('end'):
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is_duplicate = True
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# 如果已有条目信息不全，则更新它（比如之前没识别出 PLUS 价格）
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for key in ['price', 'plus_price', 'market_price', 'elec_price', 'service_price']:
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if p.get(key) is not None and existing.get(key) is None:
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existing[key] = p[key]
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break
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if not is_duplicate:
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all_prices.append(p)
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# 清理所有临时截图
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for path in temp_screenshots:
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if os.path.exists(path):
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try:
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os.remove(path)
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except:
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pass
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# 清理所有临时截图
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for path in temp_screenshots:
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if os.path.exists(path):
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try:
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os.remove(path)
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except:
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pass
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# 5. 保存数据
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if all_prices:
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@@ -20,6 +20,34 @@ class ReadImageKit:
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def __init__(self):
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self.vlm = VLMKit()
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async def find_price_entrance_vlm(self, image_path):
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"""
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使用 VLM 在详情页寻找价格入口（如：1.1556元/度 的卡片或价格信息按钮）
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"""
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prompt = """
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分析这张充电站详情页截图，找到进入“分时电价详情”的点击入口。
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入口特征：
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1. 包含价格数字的卡片，例如 "1.1556元/度"。
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2. 或者标有 "价格信息"、"电价详情" 字样的按钮。
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请判断该入口是否存在，并给出其中心坐标。
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输出格式为 JSON：
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{
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"found": true/false,
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"reason": "为什么认为这是入口",
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"point": [x, y], // 归一化坐标 [0-1000]，例如 [500, 600] 代表屏幕中心偏下
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"type": "price_card" / "button"
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}
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"""
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try:
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res_text = await self.vlm.analyze_image(image_path, prompt)
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json_str = self.vlm.extract_json(res_text)
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data = json.loads(json_str)
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return data
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except Exception as e:
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logger.error(f"VLM 寻找价格入口失败: {e}")
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return {"found": False}
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async def analyze_detail_price(self, image_path):
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"""
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分析详情页截图，提取电价信息，包括优惠价、PLUS价和挂牌价
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