.gitignore

@@ -115,6 +115,5 @@ dmypy.json
 *.swo
 
 # Project specific
-logs/
 face_recognition.log
 output.mp4

config.yaml

@@ -34,40 +34,34 @@ camera:
   width: 1280
   height: 720
   fps: 30
-  retry_interval: 2  # 打开摄像头失败后的重试间隔(秒)
+  retry_interval: 2 # 打开摄像头失败后的重试间隔(秒)
-  max_failures: 5  # 触发重新初始化的失败次数阈值
 
 # 人脸检测配置
 face_detection:
   frame_interval: 10  # 检测帧间隔(每N帧检测一次)
   quality_threshold: 10  # 图像质量阈值(Laplacian方差)
-  min_face_size: 80  # 最小人脸尺寸(像素)，越小检测距离越远
+  min_face_size: 80  # 最小人脸尺寸(像素)
   face_present_duration: 2.0  # 持续出现时长(秒)才触发识别
   max_yaw: 20.0  # 最大允许的偏航角(度)，超过此角度视为侧脸
   max_pitch: 20.0  # 最大允许的俯仰角(度)，超过此角度视为抬头或低头
-  no_face_threshold: 60  # 人脸消失计数器阈值(帧)，约2秒没有检测到人脸才清空
 
 # 人脸识别配置
 face_recognition:
+#  similarity_threshold: 0.85  # 相似度阈值(低于此值视为陌生人)
   recognition_cooldown: 20.0  # 同一人识别冷却时间(秒)
   
 # 角色映射配置
 role_mapping:
   stranger_threshold: 0.98  # 人脸识别阈值
-
+  # visitor_threshold: 0.70  # 访客识别阈值
-# 性能控制配置
+  # 低于visitor_threshold视为陌生人
-performance:
-  target_fps: 30  # 目标帧率
-  cleanup_interval: 60  # 清理过期记录的间隔(秒)
-  websocket_loop_delay: 0.01  # WebSocket消息循环延迟(秒)
 
 # 日志配置
 logging:
-  level: "INFO"  # DEBUG, INFO, WARNING, ERROR
+  level: "DEBUG"  # DEBUG, INFO, WARNING, ERROR
-  dir: "logs"  # 日志目录
+  file: "face_recognition.log"
   max_bytes: 10485760  # 10MB
   backup_count: 5
-  keep_days: 7  # 日志保留天数
 
 
 # 中文字体设置
@@ -76,9 +70,8 @@ display:
 
 
 stream:
-  #  enabled: true  # 开关推流功能
+#  enabled: true  # 开关推流功能
   enabled: false  # 开关推流功能
-  max_retries: 5  # 最大重试次数
   rtmp_url: "rtsp://127.0.0.1/live/video6"
   
   ffmpeg:

face_rec.py

@@ -18,41 +18,10 @@ import queue
 from compreface import CompreFace
 from compreface.service import RecognitionService, DetectionService
 
-# 把鼠标移到屏幕右下角
-def move_cursor_to_corner():
-    """把鼠标移到屏幕右下角"""
-    try:
-        import os
-        if not os.environ.get('DISPLAY'):
-            return
-            
-        import ctypes
-        libX11 = cdll.LoadLibrary('libX11.so.6')
-        
-        display = libX11.XOpenDisplay(None)
-        if not display:
-            return
-            
-        screen = libX11.XDefaultScreen(display)
-        width = libX11.XDisplayWidth(display, screen)
-        height = libX11.XDisplayHeight(display, screen)
-        
-        # 移动到右下角（减去一点偏移）
-        libX11.XWarpPointer(display, None, None, 0, 0, 0, 0, width - 10, height - 10)
-        libX11.XFlush(display)
-        libX11.XCloseDisplay(display)
-        
-        print(f"Cursor moved to corner: {width}x{height}")
-    except Exception as e:
-        print(f"Move cursor error: {e}")
-
 
 class FaceRecognitionSystem:
     def __init__(self, config_path: str = "config.yaml"):
         """初始化人脸识别系统"""
-        # 先移动鼠标光标到右下角（在任何窗口创建之前）
-        move_cursor_to_corner()
-        
         # 加载配置
         with open(config_path, 'r', encoding='utf-8') as f:
             self.config = yaml.safe_load(f)
@@ -77,18 +46,7 @@ class FaceRecognitionSystem:
             'is_speaking': False,
             'is_thinking': False,
             'listening': False,
-            'is_asr_processing': False,
+            'role_name': ''
-            'role_name': '',
-            'mode': '',  # 模式: await(待机)/local(展厅讲解员)/smart(访客引导者)
-            'face_detect_inited': False,  # 人脸识别系统是否准备就绪
-            'battery': 0,  # 电池电量 %
-            'bms_electric': 0,  # 电池电流 mA
-            'bms_voltage': 0,  # 电池电压 mV
-            'run_time': 0,  # 运行时间 s
-            'style_name': '',  # 当前风格
-            'is_actioning': False,  # 是否正在做动作
-            'volume': 0,  # 当前音量
-            'voice_id': '',  # 语音ID
         }
 
         # 人脸检测状态
@@ -111,7 +69,6 @@ class FaceRecognitionSystem:
             'quality': 0,
             'face_detected': False,
             'face_box': None,
-            'face_box_mirrored': False,  # 标记 face_box 是否已翻转
             'person_name': None,
             'person_role': None,
             'similarity': 0,
@@ -149,7 +106,7 @@ class FaceRecognitionSystem:
         self.ffmpeg_process = None
         self.stream_enabled = self.config.get('stream', {}).get('enabled', False)
         self.stream_retry_count = 0  # 推流重试计数
-        self.stream_max_retries = self.config.get('stream', {}).get('max_retries', 5)  # 最大重试次数
+        self.stream_max_retries = 5  # 最大重试次数
         self.stream_last_retry_time = None  # 上次重试时间
         self.stream_retry_cooldown = 10  # 重试冷却时间(秒)
 
@@ -163,8 +120,8 @@ class FaceRecognitionSystem:
         # 添加摄像头状态跟踪
         self.camera_failure_count = 0  # 连续失败次数
         self.camera_last_retry_time = None  # 上次重试时间
-        self.camera_retry_cooldown = self.config['camera'].get('retry_interval', 2)  # 重试冷却时间(秒)
+        self.camera_retry_cooldown = 3  # 重试冷却时间(秒)
-        self.camera_max_failures = self.config['camera'].get('max_failures', 5)  # 触发重新初始化的失败次数阈值
+        self.camera_max_failures = 5  # 触发重新初始化的失败次数阈值
 
         # 缓存屏幕尺寸，避免每帧重新获取
         self._cache_screen_size()
@@ -203,7 +160,7 @@ class FaceRecognitionSystem:
             self.screen_height = screen.height
             self.logger.info(f"屏幕尺寸已缓存: {self.screen_width}x{self.screen_height}")
         except Exception as e:
-            self.logger.warning(f"无法获取屏幕尺寸，使用默认尺寸 1920x1080: {e}")
+            self.logger.debug(f"无法获取屏幕尺寸，使用默认尺寸: {e}")
 
     def _force_cleanup_ffmpeg(self):
         """强制清理所有FFmpeg相关资源 - 防止多进程推流"""
@@ -342,35 +299,14 @@ class FaceRecognitionSystem:
             # 准备状态文本
             status_texts = []
 
-            # 模式中文映射
-            mode_map = {
-                'await': '待机模式',
-                'local': '展厅讲解员',
-                'smart': '访客引导者'
-            }
-
-            # 显示当前模式
-            mode_prefix = ""
-            if self.robot_status['mode']:
-                mode_name = mode_map.get(self.robot_status['mode'], self.robot_status['mode'])
-                mode_prefix = f"{mode_name}: "
-
-            # 收集状态信息
-            status_parts = []
-            if self.robot_status['listening']:
-                status_parts.append("已开启对话")
-            else:
-                status_parts.append("已关闭对话")
             if self.robot_status['is_thinking']:
-                status_parts.append("正在思考...")
+                status_texts.append("🤔 正在思考...")
-            if self.robot_status['is_asr_processing']:
-                status_parts.append("正在倾听...")
-            if self.robot_status['is_speaking']:
-                status_parts.append("正在讲话...")
 
-            # 模式 + 状态信息在同一行
+            if self.robot_status['is_asr_processing']:
-            if mode_prefix or status_parts:
+                status_texts.append("👂 正在倾听...")
-                status_texts.append(mode_prefix + " ".join(status_parts))
+
+            if self.robot_status['is_speaking']:
+                status_texts.append("👂 正在讲话...")
 
             # 如果没有状态需要显示，直接返回原帧
             if not status_texts:
@@ -572,8 +508,176 @@ class FaceRecognitionSystem:
         # Composite
         image.alpha_composite(shadow_layer)
 
+    def _build_qrcode_instruction_canvas(self, qr_image: np.ndarray, canvas_size: Tuple[int, int]) -> Optional[np.ndarray]:
+        try:
+            canvas_width, canvas_height = canvas_size
+            if canvas_width <= 0 or canvas_height <= 0:
+                return None
+
+            # Colors
+            PRIMARY_COLOR = (23, 43, 77)       # Dark Blue for headings
+            SECONDARY_COLOR = (94, 108, 132)   # Grey for secondary text
+            ACCENT_COLOR = (0, 82, 204)        # Bright Blue for highlights/numbers
+            
+            # 1. Background
+            bg = self._create_gradient_background((canvas_width, canvas_height), (245, 247, 250), (223, 225, 230)).convert("RGBA")
+            draw = ImageDraw.Draw(bg, "RGBA")
+            
+            # Layout Constants
+            MARGIN = 50
+            GUTTER = 40
+            
+            # Left Panel (QR Code) - 35% width approx
+            left_width = int((canvas_width - 2 * MARGIN - GUTTER) * 0.35)
+            # Ensure minimum width for QR code
+            left_width = max(left_width, 400)
+            right_width = canvas_width - 2 * MARGIN - GUTTER - left_width
+            
+            left_box = (MARGIN, MARGIN, MARGIN + left_width, canvas_height - MARGIN)
+            right_box = (MARGIN + left_width + GUTTER, MARGIN, canvas_width - MARGIN, canvas_height - MARGIN)
+            
+            # --- Draw Left Panel ---
+            # Shadow
+            self._draw_shadow(bg, left_box, radius=30, offset=(0, 10), blur=20, shadow_color=(0,0,0,30))
+            # Card
+            self._draw_rounded_rect(draw, left_box, radius=30, fill=(255, 255, 255, 255))
+            
+            # Left Content
+            cx = (left_box[0] + left_box[2]) // 2
+            cy_top = left_box[1] + 120
+            
+            # Title
+            text = "访客登记"
+            try:
+                w = draw.textlength(text, font=self.font_qr_title)
+            except:
+                w, _ = draw.textsize(text, font=self.font_qr_title)
+            draw.text((cx - w/2, cy_top), text, font=self.font_qr_title, fill=PRIMARY_COLOR)
+            
+            # Subtitle
+            text = "Visitor Registration"
+            try:
+                w = draw.textlength(text, font=self.font_qr_subtitle)
+            except:
+                w, _ = draw.textsize(text, font=self.font_qr_subtitle)
+            draw.text((cx - w/2, cy_top + 70), text, font=self.font_qr_subtitle, fill=SECONDARY_COLOR)
+            
+            # QR Code
+            qr_size = min(left_width - 100, 500)
+            qr_y = cy_top + 180
+            
+            # Resize QR
+            qr_pil = Image.fromarray(cv2.cvtColor(qr_image, cv2.COLOR_BGR2RGB))
+            qr_pil = qr_pil.resize((qr_size, qr_size), Image.LANCZOS)
+            bg.paste(qr_pil, (cx - qr_size//2, qr_y))
+            
+            # Scan Hint
+            hint_y = qr_y + qr_size + 50
+            hint_text = "请使用微信扫码登记"
+            try:
+                w = draw.textlength(hint_text, font=self.font_qr_step_title)
+            except:
+                w, _ = draw.textsize(hint_text, font=self.font_qr_step_title)
+            
+            # Draw a pill background for hint
+            pill_padding = 20
+            pill_box = (cx - w/2 - pill_padding, hint_y - pill_padding, cx + w/2 + pill_padding, hint_y + 40 + pill_padding)
+            self._draw_rounded_rect(draw, pill_box, radius=30, fill=(240, 242, 245), outline=None)
+            draw.text((cx - w/2, hint_y), hint_text, font=self.font_qr_step_title, fill=ACCENT_COLOR)
+            
+            # --- Draw Right Panel ---
+            
+            # Right Title Area - Compacted
+            rt_y = MARGIN + 20
+            draw.text((right_box[0], rt_y), self.qrcode_instruction_title, font=self.font_qr_title, fill=PRIMARY_COLOR)
+            draw.text((right_box[0], rt_y + 60), self.qrcode_instruction_subtitle, font=self.font_qr_subtitle, fill=SECONDARY_COLOR)
+            
+            # Separator Line
+            sep_y = rt_y + 110
+            draw.line((right_box[0], sep_y, right_box[2], sep_y), fill=(200, 200, 200), width=2)
+            
+            # Grid Configuration
+            grid_y_start = sep_y + 40
+            grid_width = right_width
+            cols = 2
+            col_gap = 30
+            row_gap = 30
+            
+            col_width = (grid_width - (cols - 1) * col_gap) // cols
+            
+            # Pre-calculate text layout to find uniform height
+            max_lines = 0
+            processed_steps = []
+            
+            padding = 30
+            badge_size = 50
+            text_left_margin = badge_size + 20
+            
+            # Calculate available width for text inside a card
+            text_max_width = col_width - padding * 2 - text_left_margin
+            
+            for i, step in enumerate(self.qrcode_instruction_steps):
+                # Remove "第一步：" etc prefix if present to make it cleaner, we have badges
+                clean_step = step.split("：", 1)[-1] if "：" in step else step
+                
+                lines = self._wrap_text_for_width(clean_step, self.font_qr_body, text_max_width, draw)
+                processed_steps.append(lines)
+                max_lines = max(max_lines, len(lines))
+            
+            # Calculate Card Height
+            # Padding top + max_lines * line_height + Padding bottom
+            line_height = self.font_qr_body.size + 10
+            card_content_height = max(badge_size, max_lines * line_height)
+            uniform_card_height = int(padding * 2 + card_content_height)
+            
+            # Draw Grid
+            for idx, lines in enumerate(processed_steps):
+                row = idx // cols
+                col = idx % cols
+                
+                x = right_box[0] + col * (col_width + col_gap)
+                y = grid_y_start + row * (uniform_card_height + row_gap)
+                
+                # Ensure we don't go out of bounds
+                if y + uniform_card_height > canvas_height:
+                     break
+                
+                card_box = (x, y, x + col_width, y + uniform_card_height)
+                
+                # Card Shadow
+                self._draw_shadow(bg, card_box, radius=20, offset=(0, 4), blur=12, shadow_color=(0,0,0,15))
+                # Card Body
+                self._draw_rounded_rect(draw, card_box, radius=20, fill=(255, 255, 255))
+                
+                # Badge (Step Number)
+                bx = x + padding
+                by = y + padding
+                draw.ellipse((bx, by, bx + badge_size, by + badge_size), fill=ACCENT_COLOR)
+                
+                num_text = str(idx + 1)
+                try:
+                    nw = draw.textlength(num_text, font=self.font_qr_badge)
+                except:
+                    nw, _ = draw.textsize(num_text, font=self.font_qr_badge)
+                # Center number
+                draw.text((bx + (badge_size - nw)/2, by + (badge_size - self.font_qr_badge.size)/2 - 2), 
+                          num_text, font=self.font_qr_badge, fill=(255, 255, 255))
+                
+                # Text
+                tx = x + padding + text_left_margin
+                ty = y + padding
+                
+                for line in lines:
+                    draw.text((tx, ty), line, font=self.font_qr_body, fill=PRIMARY_COLOR)
+                    ty += line_height
+
+            return cv2.cvtColor(np.array(bg.convert("RGB")), cv2.COLOR_RGB2BGR)
+        except Exception as e:
+            self.logger.error(f"渲染二维码指引面板失败: {e}")
+            return None
+
     def _show_qrcode(self):
-        """显示二维码图片 - 直接全屏铺满"""
+        """显示二维码图片"""
         try:
             if not os.path.exists(self.qrcode_image_path):
                 self.logger.error(f"二维码图片不存在: {self.qrcode_image_path}")
@@ -585,20 +689,44 @@ class FaceRecognitionSystem:
                 self.logger.error(f"无法读取二维码图片: {self.qrcode_image_path}")
                 return False
 
-            # 直接铺满全屏
-            canvas_width = self.screen_width
-            canvas_height = self.screen_height
-            qr_image_scaled = cv2.resize(qr_image, (canvas_width, canvas_height), interpolation=cv2.INTER_LINEAR)
-
             # 创建二维码窗口
             cv2.namedWindow(self.qrcode_window_name, cv2.WINDOW_NORMAL | cv2.WINDOW_GUI_NORMAL)
+
+            # 使用缓存的屏幕尺寸
+            canvas_width = self.screen_width
+            canvas_height = self.screen_height
+            x_pos = 0
+            y_pos = 0
+
+            qr_height, qr_width = qr_image.shape[:2]
+
+            rendered = self._build_qrcode_instruction_canvas(qr_image, (canvas_width, canvas_height))
+            if rendered is None:
+                # 回退到原二维码展示
+                scale_width = canvas_width / qr_width
+                scale_height = canvas_height / qr_height
+                scale = min(scale_width, scale_height)
+                new_width = int(qr_width * scale)
+                new_height = int(qr_height * scale)
+                resized_qr = cv2.resize(qr_image, (new_width, new_height), interpolation=cv2.INTER_LINEAR)
+                
+                # 创建黑色背景画布，完全填充屏幕
+                rendered = np.zeros((canvas_height, canvas_width, 3), dtype=np.uint8)
+                
+                # 计算居中位置
+                x_offset = (canvas_width - new_width) // 2
+                y_offset = (canvas_height - new_height) // 2
+                
+                # 将二维码放在中央
+                rendered[y_offset:y_offset+new_height, x_offset:x_offset+new_width] = resized_qr
+
             cv2.resizeWindow(self.qrcode_window_name, canvas_width, canvas_height)
-            cv2.moveWindow(self.qrcode_window_name, 0, 0)
+            cv2.moveWindow(self.qrcode_window_name, x_pos, y_pos)
 
             # 设置窗口全屏显示
             cv2.setWindowProperty(self.qrcode_window_name, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
 
-            cv2.imshow(self.qrcode_window_name, qr_image_scaled)
+            cv2.imshow(self.qrcode_window_name, rendered)
 
             # 设置窗口置顶
             cv2.setWindowProperty(self.qrcode_window_name, cv2.WND_PROP_TOPMOST, 1)
@@ -682,53 +810,29 @@ class FaceRecognitionSystem:
     def _setup_logging(self):
         """设置日志系统"""
         log_config = self.config['logging']
-        log_dir = log_config.get('dir', 'logs')
-
-        # 确保日志目录存在
-        os.makedirs(log_dir, exist_ok=True)
-
-        # 按日期生成日志文件名
-        date_str = datetime.now().strftime('%Y%m%d')
-        log_file = os.path.join(log_dir, f'face_rec_{date_str}.log')
 
         self.logger = logging.getLogger('FaceRecognition')
-        self.logger.setLevel(getattr(logging, log_config.get('level', 'INFO')))
+        self.logger.setLevel(getattr(logging, log_config['level']))
 
-        # 清理旧日志（保留最近的5个）
+        # 文件处理器
-        self._cleanup_old_logs(log_dir)
-
-        # 只保留文件处理器
         file_handler = RotatingFileHandler(
-            log_file,
+            log_config['file'],
-            maxBytes=log_config.get('max_bytes', 10 * 1024 * 1024),
+            maxBytes=log_config['max_bytes'],
-            backupCount=log_config.get('backup_count', 5)
+            backupCount=log_config['backup_count']
         )
 
+        # 控制台处理器
+        console_handler = logging.StreamHandler()
+
         # 格式化
         formatter = logging.Formatter(
-            '%(asctime)s - %(levelname)s - %(message)s'
+            '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
         )
         file_handler.setFormatter(formatter)
+        console_handler.setFormatter(formatter)
 
         self.logger.addHandler(file_handler)
-
+        self.logger.addHandler(console_handler)
-        self.logger.info(f"日志文件: {log_file}")
-
-    def _cleanup_old_logs(self, log_dir: str, keep_days: int = None):
-        """清理旧的日志文件（保留最近N天）"""
-        if keep_days is None:
-            keep_days = self.config.get('logging', {}).get('keep_days', 7)
-        try:
-            from datetime import datetime, timedelta
-            cutoff_date = (datetime.now() - timedelta(days=keep_days)).strftime('%Y%m%d')
-            
-            for f in os.listdir(log_dir):
-                if f.startswith('face_rec_') and f.endswith('.log'):
-                    date_part = f.replace('face_rec_', '').replace('.log', '')
-                    if date_part < cutoff_date:
-                        os.remove(os.path.join(log_dir, f))
-        except Exception:
-            pass
 
     def _get_chinese_font(self) -> str:
         """获取中文字体路径"""
@@ -1482,9 +1586,6 @@ class FaceRecognitionSystem:
 
     async def handle_websocket_messages(self):
         """处理WebSocket接收的消息"""
-        # 从配置读取WebSocket循环延迟
-        ws_loop_delay = self.config.get('performance', {}).get('websocket_loop_delay', 0.01)
-
         try:
             while self.ws_connected:
                 try:
@@ -1498,16 +1599,6 @@ class FaceRecognitionSystem:
                         self.robot_status['listening'] = status.get('listening', False)
                         self.robot_status['is_asr_processing'] = status.get('is_asr_processing', False)
                         self.robot_status['role_name'] = status.get('role_name', '访客引导者')
-                        self.robot_status['mode'] = status.get('mode', '')
-                        self.robot_status['face_detect_inited'] = status.get('face_detect_inited', False)
-                        self.robot_status['battery'] = status.get('battery', 0)
-                        self.robot_status['bms_electric'] = status.get('bms_electric', 0)
-                        self.robot_status['bms_voltage'] = status.get('bms_voltage', 0)
-                        self.robot_status['run_time'] = status.get('run_time', 0)
-                        self.robot_status['style_name'] = status.get('style_name', '')
-                        self.robot_status['is_actioning'] = status.get('is_actioning', False)
-                        self.robot_status['volume'] = status.get('volume', 0)
-                        self.robot_status['voice_id'] = status.get('voice_id', '')
 
                         self.logger.debug(f"机器人状态: {self.robot_status}")
 
@@ -1519,8 +1610,6 @@ class FaceRecognitionSystem:
                     self.logger.error(f"处理WebSocket消息错误: {e}")
                     self.ws_connected = False
                     break
-
-                await asyncio.sleep(ws_loop_delay)  # 短暂延迟，避免 CPU 空转
         except Exception as e:
             self.logger.error(f"WebSocket消息处理任务异常: {e}")
             self.ws_connected = False
@@ -1618,14 +1707,6 @@ class FaceRecognitionSystem:
         quality_threshold = self.config['face_detection']['quality_threshold']
         face_duration = self.config['face_detection']['face_present_duration']
 
-        # 从配置读取性能控制参数
-        perf_config = self.config.get('performance', {})
-        target_fps = perf_config.get('target_fps', 30)
-        cleanup_interval = perf_config.get('cleanup_interval', 60)
-        target_frame_interval_ms = 1000 // target_fps  # 每帧间隔毫秒
-
-        self.logger.info(f"目标帧率: {target_fps} FPS")
-
         self.logger.info("开始处理视频流")
 
         # 创建显示窗口并设置为全屏
@@ -1640,30 +1721,14 @@ class FaceRecognitionSystem:
         stream_check_counter = 0
         stream_check_interval = 150  # 每150帧（约5秒）检查一次
 
-        # 帧率控制初始化
-        last_frame_time = time.time() * 1000
-
-        # 清理定时控制
-        last_cleanup_time = time.time()
-
         # 添加人脸消失计数器
         no_face_counter = 0
-        no_face_threshold = self.config['face_detection'].get('no_face_threshold', 30)  # 连续N帧没有检测到人脸才清空
+        no_face_threshold = 30  # 连续30帧（约1秒）没有检测到人脸才清空
 
         try:
             while True:
-                current_time = time.time()
+                # 定期清理过期记录，防止内存无限增长
-
+                self.cleanup_expired_records()
-                # 每cleanup_interval秒清理一次过期记录，防止内存无限增长
-                if current_time - last_cleanup_time >= cleanup_interval:
-                    self.cleanup_expired_records()
-                    last_cleanup_time = current_time
-
-                # 帧率控制：控制到约target_fps
-                elapsed = time.time() * 1000 - last_frame_time
-                if elapsed < target_frame_interval_ms:
-                    await asyncio.sleep((target_frame_interval_ms - elapsed) / 1000)
-                last_frame_time = time.time() * 1000
 
                 # 检查机器人角色并显示/隐藏视频
                 self._check_role_and_display_video()
@@ -1741,7 +1806,6 @@ class FaceRecognitionSystem:
 
                         self.display_info['face_detected'] = True
                         self.display_info['face_box'] = face['box']
-                        self.display_info['face_box_mirrored'] = False  # 重置翻转标志
 
                         # 记录人脸出现时间
                         if self.face_present_start is None:
@@ -1848,39 +1912,9 @@ class FaceRecognitionSystem:
                 # 镜像翻转：使画面与实际场景一致（在绘制信息之前）
                 frame = cv2.flip(frame, 1)
 
-                # 调整 face_box 坐标以适应镜像翻转（只翻转一次）
-                if self.display_info['face_detected'] and self.display_info['face_box'] and not self.display_info['face_box_mirrored']:
-                    h_flip, w_flip = frame.shape[:2]
-                    box = self.display_info['face_box']
-                    x_min = int(box['x_min'])
-                    x_max = int(box['x_max'])
-                    # 水平翻转坐标
-                    self.display_info['face_box']['x_min'] = w_flip - 1 - x_max
-                    self.display_info['face_box']['x_max'] = w_flip - 1 - x_min
-                    self.display_info['face_box_mirrored'] = True
-
                 # 绘制信息
                 display_frame = self.draw_info_on_frame(frame)
 
-                # 绘制人脸轮廓引导框（屏幕中央）
-                h, w = display_frame.shape[:2]
-                center_x = w // 2
-                center_y = h // 2
-                # 椭圆参数：中心点、宽半轴、高半轴、旋转角度、起始角度、结束角度
-                cv2.ellipse(display_frame, (center_x, center_y), (150, 200), 0, 0, 360, (0, 200, 0), 3)
-
-                # 添加提示文字（使用中文支持函数）
-                guide_text = "请将脸部对准圆圈内"
-                # 计算文字位置：距离底部40像素，居中显示
-                # 使用PIL计算中文文字的实际宽度
-                img_temp = Image.new('RGB', (1, 1))
-                draw_temp = ImageDraw.Draw(img_temp)
-                bbox = draw_temp.textbbox((0, 0), guide_text, font=self.font_medium)
-                text_width = bbox[2] - bbox[0]
-                text_x = center_x - text_width // 2
-                text_y = h - 40
-                display_frame = self.cv2_add_chinese_text(display_frame, guide_text, (text_x, text_y), self.font_medium, (0, 200, 0))
-
                 # 使用缓存的屏幕尺寸拉伸视频帧到全屏
                 display_frame = cv2.resize(display_frame, (self.screen_width, self.screen_height), interpolation=cv2.INTER_LINEAR)
 

preview_qrcode.py

@@ -0,0 +1,333 @@
+import math
+import os
+import cv2
+import yaml
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont, ImageFilter
+
+# Canvas Configuration
+CANVAS_SIZE = (1920, 1080)
+BG_COLOR_START = (240, 242, 245)
+BG_COLOR_END = (200, 210, 230)
+
+# Colors
+PRIMARY_COLOR = (23, 43, 77)       # Dark Blue for headings
+SECONDARY_COLOR = (94, 108, 132)   # Grey for secondary text
+ACCENT_COLOR = (0, 82, 204)        # Bright Blue for highlights/numbers
+CARD_BG_COLOR = (255, 255, 255)
+CARD_SHADOW_COLOR = (9, 30, 66, 40) # Shadow color
+
+INSTRUCTION_TITLE = "访客预约流程"
+INSTRUCTION_SUBTITLE = "Visitor Registration Process"
+INSTRUCTION_STEPS = [
+    "第一步：扫码关注“康达新材”公众号。",
+    "第二步：点击【关于我们】→【我是访客】进入“访客注册”界面，填写并上传相应信息并点击“提交”。",
+    "第三步：将第二步信息提交完毕后在“访客预约”界面选择右下角的“+”号按钮，填写预约信息。",
+    "第四步：请仔细阅读安全告知书，点击我知道了。",
+    "第五步：填写被访人信息及来访事由等内容并提交。",
+    "第六步：显示提交成功，并且手机、微信会收到预约相关短信通知。",
+]
+
+def load_config(path="config.yaml"):
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            return yaml.safe_load(f)
+    except FileNotFoundError:
+        return {}
+
+def resolve_font(size: int, preferred: str | None = None) -> ImageFont.FreeTypeFont:
+    candidates = [preferred] if preferred else []
+    candidates += [
+        "C:/Windows/Fonts/msyhbd.ttc", # Microsoft YaHei Bold
+        "C:/Windows/Fonts/msyh.ttc",   # Microsoft YaHei
+        "C:/Windows/Fonts/simhei.ttf",
+        "/usr/share/fonts/truetype/noto/NotoSansCJK-Bold.ttc",
+        "/usr/share/fonts/truetype/noto/NotoSansCJK-Regular.ttc",
+        "/usr/share/fonts/truetype/noto/NotoMono-Regular.ttf",
+    ]
+    for path in candidates:
+        if path and os.path.exists(path):
+            try:
+                return ImageFont.truetype(path, size)
+            except OSError:
+                continue
+    return ImageFont.load_default()
+
+def wrap_text(text: str, font: ImageFont.FreeTypeFont, max_width: int, draw: ImageDraw.ImageDraw):
+    lines = []
+    current = ""
+    for ch in text:
+        tentative = current + ch
+        # Pillow 10+ uses textlength, older uses textsize
+        try:
+            width = draw.textlength(tentative, font=font)
+        except AttributeError:
+            width, _ = draw.textsize(tentative, font=font)
+            
+        if width <= max_width:
+            current = tentative
+        else:
+            if current:
+                lines.append(current)
+            current = ch
+    if current:
+        lines.append(current)
+    return lines
+
+def create_gradient_background(size: tuple[int, int], start_color: tuple[int, int, int], end_color: tuple[int, int, int]) -> Image.Image:
+    width, height = size
+    # Vertical gradient
+    base = Image.new('RGB', size, start_color)
+    top = Image.new('RGB', size, end_color)
+    mask = Image.new('L', size)
+    mask_data = np.tile(np.linspace(0, 255, height, dtype=np.uint8), (width, 1)).T
+    mask = Image.fromarray(mask_data, 'L')
+    return Image.composite(top, base, mask)
+
+def draw_rounded_rect(draw, box, radius, fill, outline=None, width=0):
+    draw.rounded_rectangle(box, radius=radius, fill=fill, outline=outline, width=width)
+
+def draw_shadow(image, box, radius, offset=(0, 4), blur=10, shadow_color=(0,0,0,50)):
+    # Create a separate shadow layer
+    shadow_layer = Image.new('RGBA', image.size, (0,0,0,0))
+    shadow_draw = ImageDraw.Draw(shadow_layer)
+    
+    sx0, sy0, sx1, sy1 = box
+    dx, dy = offset
+    
+    shadow_box = (sx0 + dx, sy0 + dy, sx1 + dx, sy1 + dy)
+    shadow_draw.rounded_rectangle(shadow_box, radius=radius, fill=shadow_color)
+    
+    # Blur the shadow
+    shadow_layer = shadow_layer.filter(ImageFilter.GaussianBlur(blur))
+    
+    # Composite
+    image.alpha_composite(shadow_layer)
+
+def build_canvas(qr_image: np.ndarray, title_font, subtitle_font, body_font, step_title_font, badge_font) -> np.ndarray:
+    canvas_width, canvas_height = CANVAS_SIZE
+    
+    # 1. Background
+    bg = create_gradient_background(CANVAS_SIZE, (245, 247, 250), (223, 225, 230)).convert("RGBA")
+    
+    draw = ImageDraw.Draw(bg, "RGBA")
+    
+    # Layout Constants
+    MARGIN = 50
+    GUTTER = 40
+    
+    # Left Panel (QR Code) - 35% width approx
+    left_width = int((canvas_width - 2 * MARGIN - GUTTER) * 0.35)
+    right_width = canvas_width - 2 * MARGIN - GUTTER - left_width
+    
+    left_box = (MARGIN, MARGIN, MARGIN + left_width, canvas_height - MARGIN)
+    right_box = (MARGIN + left_width + GUTTER, MARGIN, canvas_width - MARGIN, canvas_height - MARGIN)
+    
+    # --- Draw Left Panel ---
+    # Shadow
+    draw_shadow(bg, left_box, radius=30, offset=(0, 10), blur=20, shadow_color=(0,0,0,30))
+    # Card
+    draw_rounded_rect(draw, left_box, radius=30, fill=(255, 255, 255, 255))
+    
+    # Left Content
+    cx = (left_box[0] + left_box[2]) // 2
+    cy_top = left_box[1] + 120
+    
+    # Title
+    text = "访客登记"
+    try:
+        w = draw.textlength(text, font=title_font)
+    except:
+        w, _ = draw.textsize(text, font=title_font)
+    draw.text((cx - w/2, cy_top), text, font=title_font, fill=PRIMARY_COLOR)
+    
+    # Subtitle
+    text = "Visitor Registration"
+    try:
+        w = draw.textlength(text, font=subtitle_font)
+    except:
+        w, _ = draw.textsize(text, font=subtitle_font)
+    draw.text((cx - w/2, cy_top + 70), text, font=subtitle_font, fill=SECONDARY_COLOR)
+    
+    # QR Code
+    qr_size = min(left_width - 100, 500)
+    qr_y = cy_top + 180
+    
+    # Resize QR
+    qr_pil = Image.fromarray(cv2.cvtColor(qr_image, cv2.COLOR_BGR2RGB))
+    qr_pil = qr_pil.resize((qr_size, qr_size), Image.LANCZOS)
+    bg.paste(qr_pil, (cx - qr_size//2, qr_y))
+    
+    # Scan Hint
+    hint_y = qr_y + qr_size + 50
+    hint_text = "请使用微信扫码登记"
+    try:
+        w = draw.textlength(hint_text, font=step_title_font)
+    except:
+        w, _ = draw.textsize(hint_text, font=step_title_font)
+    
+    # Draw a pill background for hint
+    pill_padding = 20
+    pill_box = (cx - w/2 - pill_padding, hint_y - pill_padding, cx + w/2 + pill_padding, hint_y + 40 + pill_padding)
+    draw.rounded_rectangle(pill_box, radius=30, fill=(240, 242, 245), outline=None)
+    draw.text((cx - w/2, hint_y), hint_text, font=step_title_font, fill=ACCENT_COLOR)
+    
+    # --- Draw Right Panel ---
+    
+    # Right Title Area - Compacted
+    rt_y = MARGIN + 20
+    draw.text((right_box[0], rt_y), INSTRUCTION_TITLE, font=title_font, fill=PRIMARY_COLOR)
+    draw.text((right_box[0], rt_y + 60), INSTRUCTION_SUBTITLE, font=subtitle_font, fill=SECONDARY_COLOR)
+    
+    # Separator Line
+    sep_y = rt_y + 110
+    draw.line((right_box[0], sep_y, right_box[2], sep_y), fill=(200, 200, 200), width=2)
+    
+    # Grid Configuration
+    grid_y_start = sep_y + 40
+    grid_width = right_width
+    cols = 2
+    col_gap = 30
+    row_gap = 30
+    
+    col_width = (grid_width - (cols - 1) * col_gap) // cols
+    
+    # Pre-calculate text layout to find uniform height
+    max_lines = 0
+    processed_steps = []
+    
+    padding = 30
+    badge_size = 50
+    text_left_margin = badge_size + 20
+    
+    # Calculate available width for text inside a card
+    text_max_width = col_width - padding * 2 - text_left_margin
+    
+    for i, step in enumerate(INSTRUCTION_STEPS):
+        # Remove "第一步：" etc prefix if present to make it cleaner, we have badges
+        clean_step = step.split("：", 1)[-1] if "：" in step else step
+        
+        lines = wrap_text(clean_step, body_font, text_max_width, draw)
+        processed_steps.append(lines)
+        max_lines = max(max_lines, len(lines))
+    
+    # Calculate Card Height
+    # Padding top + max_lines * line_height + Padding bottom
+    line_height = body_font.size + 10
+    card_content_height = max(badge_size, max_lines * line_height)
+    uniform_card_height = int(padding * 2 + card_content_height)
+    
+    # Check if we overflow canvas height
+    total_grid_height = 3 * uniform_card_height + 2 * row_gap
+    if grid_y_start + total_grid_height > canvas_height - MARGIN:
+        print(f"Warning: Content might overflow vertically. Required: {grid_y_start + total_grid_height}, Available: {canvas_height - MARGIN}")
+        # Dynamic adjustment if needed (e.g. reduce gaps) but for now we rely on the font resizing done in main()
+    
+    # Draw Grid
+    for idx, lines in enumerate(processed_steps):
+        row = idx // cols
+        col = idx % cols
+        
+        x = right_box[0] + col * (col_width + col_gap)
+        y = grid_y_start + row * (uniform_card_height + row_gap)
+        
+        card_box = (x, y, x + col_width, y + uniform_card_height)
+        
+        # Card Shadow
+        draw_shadow(bg, card_box, radius=20, offset=(0, 4), blur=12, shadow_color=(0,0,0,15))
+        # Card Body
+        draw_rounded_rect(draw, card_box, radius=20, fill=(255, 255, 255))
+        
+        # Badge (Step Number)
+        bx = x + padding
+        by = y + padding
+        draw.ellipse((bx, by, bx + badge_size, by + badge_size), fill=ACCENT_COLOR)
+        
+        num_text = str(idx + 1)
+        try:
+            nw = draw.textlength(num_text, font=badge_font)
+        except:
+            nw, _ = draw.textsize(num_text, font=badge_font)
+        # Center number
+        draw.text((bx + (badge_size - nw)/2, by + (badge_size - badge_font.size)/2 - 2), 
+                  num_text, font=badge_font, fill=(255, 255, 255))
+        
+        # Text
+        tx = x + padding + text_left_margin
+        ty = y + padding
+        
+        for line in lines:
+            draw.text((tx, ty), line, font=body_font, fill=PRIMARY_COLOR)
+            ty += line_height
+
+    return cv2.cvtColor(np.array(bg.convert("RGB")), cv2.COLOR_RGB2BGR)
+
+def create_mock_qrcode(size: int = 640) -> np.ndarray:
+    img = np.full((size, size, 3), 255, dtype=np.uint8) # White background
+    
+    # Draw some patterns
+    block = size // 15
+    for y in range(0, size, block):
+        for x in range(0, size, block):
+            if (x // block + y // block) % 2 == 0:
+                color = (0, 0, 0)
+                # Corner markers
+                if (x < 3*block and y < 3*block) or (x > size-4*block and y < 3*block) or (x < 3*block and y > size-4*block):
+                     color = (0, 0, 0)
+                elif np.random.rand() > 0.3:
+                     color = (0, 0, 0)
+                else:
+                     color = (255, 255, 255)
+                
+                cv2.rectangle(img, (x, y), (x + block, y + block), color, -1)
+                
+    # Borders for markers
+    marker_len = 3 * block
+    thickness = block
+    # Top Left
+    cv2.rectangle(img, (0,0), (marker_len, marker_len), (0,0,0), thickness)
+    # Top Right
+    cv2.rectangle(img, (size-marker_len,0), (size, marker_len), (0,0,0), thickness)
+    # Bottom Left
+    cv2.rectangle(img, (0,size-marker_len), (marker_len, size), (0,0,0), thickness)
+    
+    return img
+
+def main():
+    config = load_config()
+    preferred_font = config.get("display", {}).get("font_path") if config else None
+    
+    # Define Fonts - Adjusted sizes for better fit
+    # Title for left/right headers
+    title_font = resolve_font(56, preferred_font)
+    # Subtitles
+    subtitle_font = resolve_font(30, preferred_font)
+    # Step text - Reduced to ensure fit
+    body_font = resolve_font(24, preferred_font)
+    # Step titles or emphasis
+    step_title_font = resolve_font(28, preferred_font)
+    # Badge numbers
+    badge_font = resolve_font(30, preferred_font)
+
+    # Mock data
+    mock_qr = create_mock_qrcode(500)
+    
+    # Build
+    canvas = build_canvas(mock_qr, title_font, subtitle_font, body_font, step_title_font, badge_font)
+
+    # Display
+    window_name = "Visitor Registration Preview"
+    cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
+    cv2.resizeWindow(window_name, 1280, 720)
+    cv2.imshow(window_name, canvas)
+    
+    print("Displaying preview. Press any key to exit.")
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+    
+    # Save for verification
+    cv2.imwrite("preview_qrcode_sota.png", canvas)
+    print("Saved preview to preview_qrcode_sota.png")
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -1,9 +0,0 @@
-pencv-python>=4.8.0
-websockets>=12.0
-pyyaml>=6.0
-pillow>=10.0.0
-numpy>=1.24.0
-psutil>=5.9.0
-requests>=2.31.0
-compreface-sdk>=0.6.0
-screeninfo>=0.8

start.sh

@@ -1,15 +1,30 @@
 #!/bin/bash
 
-# 创建日志目录
+# --- 日志相关 ---
-LOG_DIR="/home/unitree/robot_face_rec/logs"
+LOG_DIR="/home/unitree/robot_face_rec/logs/face_rec"
 mkdir -p "$LOG_DIR"
+LOG_FILE="$LOG_DIR/face_rec_$(date +%Y%m%d_%H%M%S).log"
+
+{
+  echo "===== $(date) Starting face_rec script ====="
+  echo "User: $(whoami)"
+  echo "PWD before cd: $(pwd)"
+  echo "Python: $(which python) / Version: $(python --version 2>&1)"
+} >> "$LOG_FILE"
 
 # 切换到项目目录
 cd /home/unitree/robot_face_rec || {
-  echo "Failed to cd to project dir"
+  echo "Failed to cd to project dir" >> "$LOG_FILE"
   exit 1
 }
 
+{
+  echo "PWD after cd: $(pwd)"
+  echo "Env before display detection: DISPLAY=$DISPLAY, XAUTHORITY=$XAUTHORITY"
+} >> "$LOG_FILE"
+
+# --- DISPLAY 和 XAUTHORITY 设置逻辑 ---
+
 # 设置DISPLAY环境变量
 # 使用Linux系统最常见的默认值:0
 export DISPLAY=":0"
@@ -46,5 +61,12 @@ fi
 export XAUTHORITY="$xauth_path"
 echo "Using XAUTHORITY: $XAUTHORITY"
 
-# 执行 Python 程序（Python 代码自己管理日志）
+export XAUTHORITY="$xauth_path"
-exec python face_rec.py
+
+{
+  echo "Chosen DISPLAY = $DISPLAY"
+  echo "Using XAUTHORITY = $XAUTHORITY"
+} >> "$LOG_FILE"
+
+# 最终执行 Python 程序（不后台化，用 exec 替换进程）
+exec python face_rec.py >> "$LOG_FILE" 2>&1