From cb72f020302b7188793650687ee6c777e5e6f823 Mon Sep 17 00:00:00 2001 From: HuangHai <10402852@qq.com> Date: Mon, 26 Jan 2026 19:57:19 +0800 Subject: [PATCH] 'commit' --- WeiXin/T2_ChatMonitor.py | 35 ++++--- WeiXin/WxUtil.py | 108 +++++++++++++++++----- WeiXin/__pycache__/WxUtil.cpython-310.pyc | Bin 22276 -> 23816 bytes 3 files changed, 108 insertions(+), 35 deletions(-) diff --git a/WeiXin/T2_ChatMonitor.py b/WeiXin/T2_ChatMonitor.py index c41d31e..e4a0979 100644 --- a/WeiXin/T2_ChatMonitor.py +++ b/WeiXin/T2_ChatMonitor.py @@ -144,6 +144,16 @@ class ChatMonitorBot: """主运行循环""" logger.info("🚀 大张老师自动巡课系统启动 (T2 增强版)...") + # 定义 JSON 序列化辅助函数 + def numpy_serializer(obj): + if isinstance(obj, np.integer): + return int(obj) + if isinstance(obj, np.floating): + return float(obj) + if isinstance(obj, np.ndarray): + return obj.tolist() + raise TypeError(f"Type {type(obj)} not serializable") + # 1. 环境准备 if not self.step_1_prepare_env(): return if not self.step_2_connect_device(): return @@ -171,22 +181,18 @@ class ChatMonitorBot: # 格式化输出：[发送者] 内容 (类型) sender = msg.get('sender', '未知') content = msg.get('content', '') - msg_type = msg.get('type', 'unknown') - logger.info(f"[{sender}] {content} ({msg_type})") + msg_type = "语音" if msg.get('type') == 'voice' else "文字" + + # 按照用户要求的格式输出 + logger.info(f"说话人: {sender}") + logger.info(f"消息类型: {msg_type}") + logger.info(f"消息内容: {content}") + logger.info("-" * 20) logger.info("="*50 + "\n") # 初始化最后处理的消息哈希，避免重复回复第一条 last_msg = self.dialogue_log[-1] # last_msg 是字典，需要转字符串再 encode - def numpy_serializer(obj): - if isinstance(obj, np.integer): - return int(obj) - if isinstance(obj, np.floating): - return float(obj) - if isinstance(obj, np.ndarray): - return obj.tolist() - raise TypeError(f"Type {type(obj)} not serializable") - msg_str = json.dumps(last_msg, sort_keys=True, ensure_ascii=False, default=numpy_serializer) self.last_processed_msg_hash = hashlib.md5(msg_str.encode('utf-8')).hexdigest() self.last_screen_hash = self.get_image_hash(self.screenshot_path) @@ -233,10 +239,13 @@ class ChatMonitorBot: # D. 只关注最后一条消息 last_msg = dialogue_log[-1] - current_msg_hash = hashlib.md5(last_msg.encode('utf-8')).hexdigest() + # last_msg 是字典，需要序列化 + msg_str = json.dumps(last_msg, sort_keys=True, ensure_ascii=False, default=numpy_serializer) + current_msg_hash = hashlib.md5(msg_str.encode('utf-8')).hexdigest() # E. 判断是否需要回复 (对方发送且非重复消息) - if "对方:" in last_msg: + sender = last_msg.get('sender', '') + if sender == "对方": if current_msg_hash != self.last_processed_msg_hash: event_shot = WxUtil.get_next_debug_path("event_new_msg") self.device.screenshot(event_shot) diff --git a/WeiXin/WxUtil.py b/WeiXin/WxUtil.py index 17e7088..1f69cc5 100644 --- a/WeiXin/WxUtil.py +++ b/WeiXin/WxUtil.py @@ -173,10 +173,35 @@ def _scan_chat_messages(image_path): logger.info("正在执行 OCR 识别...") ocr_results = ocr_kit.read_text(image_path) + # 4.5 尝试提取聊天标题 (对方昵称) + chat_title = "对方" + potential_titles = [] + for bbox, text, conf in ocr_results: + c_y = int((bbox[0][1] + bbox[2][1]) / 2) + c_x = int((bbox[0][0] + bbox[2][0]) / 2) + # 标题区域通常在顶部 (状态栏下方，消息列表上方) + if 60 < c_y < 140: + clean = text.strip() + # 排除时间、信号、返回按钮等 + if re.match(r'^\d{1,2}:\d{2}$', clean): continue + if "微信" in clean or "WeChat" in clean: continue + if clean in ["<", "返回", "消息", "(", ")"]: continue + if re.match(r'^\d+$', clean): continue # 排除纯数字(如未读数) + if len(clean) > 0: + potential_titles.append((c_x, clean)) + + if potential_titles: + # 优先取最接近水平中心的文本作为标题 + potential_titles.sort(key=lambda x: abs(x[0] - w/2)) + chat_title = potential_titles[0][1] + # 去除可能包含的括号(比如备注名后的群聊人数，虽然后面会被截断) + chat_title = re.sub(r'\(\d+\)$', '', chat_title).strip() + logger.info(f"识别到聊天标题/对方昵称: {chat_title}") + # 微信菜单关键字（用于排除干扰） MENU_KEYWORDS = ["听筒播放", "收藏", "背景播放", "删除", "多选", "取消转文字", "转文字", "引用", "提醒"] # 忽略的系统消息内容 - IGNORE_CONTENT = ["撤回了一条消息", "打招呼的消息", "拍了拍", "你撤回了一条消息", "引用"] + IGNORE_CONTENT = ["撤回了一条消息", "打招呼的消息", "拍了拍", "你撤回了一条消息", "引用", "Clear Text", "Switch IME", "Done"] # 5. 整合所有消息 messages = [] @@ -188,6 +213,8 @@ def _scan_chat_messages(image_path): cv2.putText(debug_img, "TOP_FILTER", (10, 140), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 1) cv2.putText(debug_img, "BOTTOM_FILTER", (10, h - 110), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 0, 255), 1) + claimed_ocr_indices = set() + # A. 添加语音消息 for ax, ay in audio_matches: # 标记所有找到的语音图标 (用于调试) @@ -211,12 +238,18 @@ def _scan_chat_messages(image_path): # 改进：判断是否已转文字 is_converted = False converted_trigger_text = "" - for bbox, text, conf in ocr_results: + associated_texts = [] # 存储关联的多行文本 [(y, x, text)] + + for i, (bbox, text, conf) in enumerate(ocr_results): + if i in claimed_ocr_indices: continue + c_x = int((bbox[0][0] + bbox[2][0]) / 2) c_y = int((bbox[0][1] + bbox[2][1]) / 2) - # 判定逻辑：文本在语音下方且水平偏移不大 - if 30 < c_y - ay < 600 and abs(c_x - ax) < 600: + # 判定逻辑：文本在语音下方且水平偏移不大 (放宽 Y 轴限制以包含侧边的时长文本) + # 2025-01-26: 增加 X 轴范围到 900 以适配超长语音条的右侧时长/文本 + # 增加 Y 轴范围到 800 以适配多行转文字内容 + if -50 < c_y - ay < 800 and abs(c_x - ax) < 900: # 检查中间是否有其他语音图标 has_intermediate_audio = False for other_ax, other_ay in audio_matches: @@ -236,24 +269,35 @@ def _scan_chat_messages(image_path): # 判定是否为系统消息 is_ignored = any(k in clean_text for k in IGNORE_CONTENT) - if not is_duration and not is_timestamp and clean_text not in MENU_KEYWORDS and not is_ignored: + # 噪音判定 (例如 "少3"") + is_noise = "少" in clean_text and len(clean_text) < 8 and re.search(r'\d', clean_text) + + if not is_duration and not is_timestamp and clean_text not in MENU_KEYWORDS and not is_ignored and not is_noise: is_converted = True - # 针对 "少3"" 这种特殊噪点进行过滤，但仍标记为已转换 - # 如果包含 "少" 且长度短且包含数字，视为噪点 (例如 "少3"") - if "少" in clean_text and len(clean_text) < 6 and re.search(r'\d', clean_text): - logger.info(f"语音({ax},{ay}) 判定为已转换，但内容判定为噪点('{clean_text}')，置为空") - converted_trigger_text = "" - else: - converted_trigger_text = clean_text - logger.info(f"语音({ax},{ay}) 判定为已转换，关联到有效文本: '{clean_text}'") - break + associated_texts.append((c_y, c_x, clean_text)) + claimed_ocr_indices.add(i) + # 不再 break，继续寻找后续文本行 else: + # 这些文本虽然不作为内容，但它们属于语音消息的附属信息，标记为已处理 + claimed_ocr_indices.add(i) + if is_timestamp: logger.info(f"语音({ax},{ay}) 忽略下方时间戳文本: '{clean_text}'") elif is_duration: logger.info(f"语音({ax},{ay}) 忽略时长文本: '{clean_text}'") + elif is_noise: + logger.info(f"语音({ax},{ay}) 忽略噪音文本: '{clean_text}'") elif is_ignored: logger.info(f"语音({ax},{ay}) 忽略系统消息文本: '{clean_text}'") + else: + logger.info(f"语音({ax},{ay}) 忽略其他文本(可能是菜单): '{clean_text}'") + + # 整合所有关联文本 + if associated_texts: + # 按 Y 轴排序，如果 Y 接近则按 X 轴排序 + associated_texts.sort(key=lambda x: (x[0], x[1])) + converted_trigger_text = "".join([t[2] for t in associated_texts]) + logger.info(f"语音({ax},{ay}) 判定为已转换，最终合并文本: '{converted_trigger_text}'") if is_converted: logger.info(f"语音消息 ({ax}, {ay}) 已有转换文字: '{converted_trigger_text}'，跳过") @@ -275,7 +319,8 @@ def _scan_chat_messages(image_path): }) # B. 添加文本消息 - for bbox, text, conf in ocr_results: + for i, (bbox, text, conf) in enumerate(ocr_results): + if i in claimed_ocr_indices: continue c_x = int((bbox[0][0] + bbox[2][0]) / 2) c_y = int((bbox[0][1] + bbox[2][1]) / 2) @@ -284,12 +329,25 @@ def _scan_chat_messages(image_path): time_pattern = r'(\d{4}年|\d{1,2}月|\d{1,2}日|\d{1,2}:\d{2}|昨天|今天|星期|上午|下午|晚上)' if len(text) < 20 and (re.search(time_pattern, text) or re.match(r'^[0-9:\s日年月\-]+$', text)): + logger.info(f"忽略时间戳/日期文本: '{text}'") continue clean_text = text.strip() - if re.match(r'^.?[0-9]{1,2}"?$', clean_text): continue - if clean_text in MENU_KEYWORDS: continue - if any(k in clean_text for k in IGNORE_CONTENT): continue + if re.match(r'^.?[0-9]{1,2}"?$', clean_text): + logger.info(f"忽略疑似时长文本: '{clean_text}'") + continue + + # 噪音判定 (例如 "少3"") + if "少" in clean_text and len(clean_text) < 8 and re.search(r'\d', clean_text): + logger.info(f"忽略噪音文本: '{clean_text}'") + continue + + if clean_text in MENU_KEYWORDS: + logger.info(f"忽略菜单关键词: '{clean_text}'") + continue + if any(k in clean_text for k in IGNORE_CONTENT): + logger.info(f"忽略系统消息内容: '{clean_text}'") + continue left_x = bbox[0][0] sender = "对方" if left_x < w * 0.5 else "我" @@ -304,7 +362,7 @@ def _scan_chat_messages(image_path): # 6. 排序 messages.sort(key=lambda x: x['y']) - return messages, debug_img + return messages, debug_img, chat_title async def analyze_chat_image(image_path, output_path, device=None, target_name="对方", process_strategy="ALL"): """ @@ -339,10 +397,16 @@ async def analyze_chat_image(image_path, output_path, device=None, target_name=" logger.info(f"--- 分析循环 第 {loop_count} 次 ---") # 1. 扫描当前屏幕 - messages, debug_img = _scan_chat_messages(current_image_path) + messages, debug_img, chat_title = _scan_chat_messages(current_image_path) if messages is None: # 读取失败 return [], None - + + # 更新消息发送者名称 (将 "对方" 替换为 实际标题) + if chat_title and chat_title != "对方": + for m in messages: + if m['sender'] == "对方": + m['sender'] = chat_title + # 保存当前状态的调试图 if current_output_path: cv2.imwrite(current_output_path, debug_img) @@ 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