足底压力仪优化提交

backend/devices/camera_manager.py

@@ -53,10 +53,14 @@ class CameraManager(BaseDevice):
         self.fps = config.get('fps', 30)
         self.buffer_size = config.get('buffer_size', 1)
         self.fourcc = config.get('fourcc', 'MJPG')
+
+        # 额外可调的降采样宽度（不改变外部配置语义，仅内部优化传输）
+        self._tx_max_width = int(config.get('tx_max_width', 640))
         
         # 流控制
         self.streaming_thread = None
-        self.frame_cache = deque(maxlen=10)
+        # 减小缓存长度，保留最近2帧即可，避免累计占用
+        self.frame_cache = deque(maxlen=int(config.get('frame_cache_len', 2)))
         self.last_frame = None
         self.frame_count = 0
         self.dropped_frames = 0
@@ -77,6 +81,12 @@ class CameraManager(BaseDevice):
             'actual_fps': 0,
             'dropped_frames': 0
         }
+
+        # OpenCV优化开关
+        try:
+            cv2.setUseOptimized(True)
+        except Exception:
+            pass
         
         self.logger.info(f"相机管理器初始化完成 - 设备索引: {self.device_index}")
         
@@ -90,7 +100,7 @@ class CameraManager(BaseDevice):
         try:
             self.logger.info(f"正在初始化相机设备 {self.device_index}...")
             
-            # 尝试多个后端
+            # 尝试多个后端（Windows下优先MSMF/DShow）
             backends = [cv2.CAP_MSMF, cv2.CAP_DSHOW, cv2.CAP_ANY]
             
             for backend in backends:
@@ -127,7 +137,10 @@ class CameraManager(BaseDevice):
             self.logger.error(f"相机初始化失败: {e}")
             self.is_connected = False
             if self.cap:
-                self.cap.release()
+                try:
+                    self.cap.release()
+                except Exception:
+                    pass
                 self.cap = None
             return False
             
@@ -151,8 +164,11 @@ class CameraManager(BaseDevice):
             # 设置帧率
             self.cap.set(cv2.CAP_PROP_FPS, self.fps)
             
-            # 设置缓冲区大小
-            self.cap.set(cv2.CAP_PROP_BUFFERSIZE, self.buffer_size)
+            # 设置缓冲区大小（部分后端不生效）
+            try:
+                self.cap.set(cv2.CAP_PROP_BUFFERSIZE, self.buffer_size)
+            except Exception:
+                pass
             
             # 获取实际设置的值
             actual_width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
@@ -199,7 +215,7 @@ class CameraManager(BaseDevice):
                     
             # 读取几帧来稳定相机
             for i in range(5):
-                ret, frame = self.cap.read()
+                ret, _ = self.cap.read()
                 if not ret:
                     self.logger.warning(f"校准时读取第{i+1}帧失败")
                     
@@ -253,7 +269,9 @@ class CameraManager(BaseDevice):
             self.is_streaming = False
             
             if self.streaming_thread and self.streaming_thread.is_alive():
+                # 等待线程退出
                 self.streaming_thread.join(timeout=3.0)
+            self.streaming_thread = None
                 
             self.logger.info("相机流已停止")
             return True
@@ -269,8 +287,13 @@ class CameraManager(BaseDevice):
         self.logger.info("相机流工作线程启动")
         
         reconnect_attempts = 0
-        
+
+        # 基于目标FPS的简单节拍器，防止无上限地读取/编码/发送导致对象堆积
+        frame_interval = 1.0 / max(self.fps, 1)
+        next_tick = time.time()
+
         while self.is_streaming:
+            loop_start = time.time()
             try:
                 if not self.cap or not self.cap.isOpened():
                     if reconnect_attempts < self.max_reconnect_attempts:
@@ -292,33 +315,51 @@ class CameraManager(BaseDevice):
                     self.dropped_frames += 1
                     if self.dropped_frames > 10:
                         self.logger.warning(f"连续丢帧过多: {self.dropped_frames}")
+                        # 仅在异常情况下触发一次GC，避免高频强制GC
+                        try:
+                            gc.collect()
+                        except Exception:
+                            pass
                         self.dropped_frames = 0
-                    time.sleep(0.01)
+                    # 防止空转占满CPU
+                    time.sleep(0.005)
                     continue
                     
                 # 重置丢帧计数
                 self.dropped_frames = 0
                 
-                # 处理帧
+                # 处理帧（降采样以优化传输负载）
                 processed_frame = self._process_frame(frame)
-                
-                # 缓存帧
-                self.last_frame = processed_frame.copy()
-                self.frame_cache.append(processed_frame)
+
+                # 缓存帧（不复制，减少内存占用）
+                # self.last_frame = processed_frame
+                # self.frame_cache.append(processed_frame)
                 
                 # 发送帧数据
                 self._send_frame_data(processed_frame)
                 
                 # 更新统计
                 self._update_statistics()
-                
-                # 内存管理
-                if self.frame_count % 30 == 0:
-                    gc.collect()
-                    
+
+                # 主动释放局部引用，帮助GC更快识别可回收对象
+                del frame
+                # 注意：processed_frame 被 last_frame 和 frame_cache 引用，不可删除其对象本身
+
+                # 限速：保证不超过目标FPS，减小发送端积压
+                now = time.time()
+                # 下一个tick基于固定间隔前移，避免误差累积
+                next_tick += frame_interval
+                sleep_time = next_tick - now
+                if sleep_time > 0:
+                    time.sleep(sleep_time)
+                else:
+                    # 如果处理耗时超过间隔，纠正节拍器，避免持续为负
+                    next_tick = now
+
             except Exception as e:
                 self.logger.error(f"相机流处理异常: {e}")
-                time.sleep(0.1)
+                # 小退避，避免异常情况下空转
+                time.sleep(0.02)
                 
         self.logger.info("相机流工作线程结束")
         
@@ -333,15 +374,14 @@ class CameraManager(BaseDevice):
             np.ndarray: 处理后的帧
         """
         try:
-            # 调整大小以优化传输
-            if frame.shape[1] > 640:
-                scale_factor = 640 / frame.shape[1]
-                new_width = 640
-                new_height = int(frame.shape[0] * scale_factor)
-                frame = cv2.resize(frame, (new_width, new_height))
-                
+            # 调整大小以优化传输（使用 INTER_AREA 质量好且更省内存/CPU）
+            h, w = frame.shape[:2]
+            if w > self._tx_max_width:
+                scale = self._tx_max_width / float(w)
+                new_w = self._tx_max_width
+                new_h = int(h * scale)
+                frame = cv2.resize(frame, (new_w, new_h), interpolation=cv2.INTER_AREA)
             return frame
-            
         except Exception as e:
             self.logger.error(f"处理帧失败: {e}")
             return frame
@@ -353,13 +393,21 @@ class CameraManager(BaseDevice):
         Args:
             frame: 视频帧
         """
+        # 将临时对象局部化，并在 finally 中删除引用，加速回收
+        buffer = None
+        frame_bytes = None
+        frame_data = None
         try:
             # 编码为JPEG
             encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 80]
-            _, buffer = cv2.imencode('.jpg', frame, encode_param)
+            ok, buffer = cv2.imencode('.jpg', frame, encode_param)
+            if not ok or buffer is None:
+                self.logger.warning("帧JPEG编码失败")
+                return
             
-            # 转换为base64
-            frame_data = base64.b64encode(buffer).decode('utf-8')
+            # 转换为bytes再做base64，减少中间numpy对象的长生命周期
+            frame_bytes = buffer.tobytes()
+            frame_data = base64.b64encode(frame_bytes).decode('utf-8')
             
             # 发送数据
             data = {
@@ -374,6 +422,11 @@ class CameraManager(BaseDevice):
             
         except Exception as e:
             self.logger.error(f"发送帧数据失败: {e}")
+        finally:
+            # 显式删除临时大对象的引用，避免在高吞吐下堆积
+            del buffer
+            del frame_bytes
+            del frame_data
             
     def _update_statistics(self):
         """
@@ -405,7 +458,11 @@ class CameraManager(BaseDevice):
         """
         try:
             if self.cap:
-                self.cap.release()
+                try:
+                    self.cap.release()
+                except Exception:
+                    pass
+                self.cap = None
                 
             time.sleep(1.0)  # 等待设备释放
             
@@ -471,6 +528,7 @@ class CameraManager(BaseDevice):
         Returns:
             Optional[np.ndarray]: 最新帧，无帧返回None
         """
+        # 对外提供拷贝，内部保持原对象，避免重复持有
         return self.last_frame.copy() if self.last_frame is not None else None
         
     def disconnect(self):
@@ -481,7 +539,10 @@ class CameraManager(BaseDevice):
             self.stop_streaming()
             
             if self.cap:
-                self.cap.release()
+                try:
+                    self.cap.release()
+                except Exception:
+                    pass
                 self.cap = None
                 
             self.is_connected = False
@@ -498,7 +559,10 @@ class CameraManager(BaseDevice):
             self.stop_streaming()
             
             if self.cap:
-                self.cap.release()
+                try:
+                    self.cap.release()
+                except Exception:
+                    pass
                 self.cap = None
                 
             self.frame_cache.clear()
@@ -508,4 +572,4 @@ class CameraManager(BaseDevice):
             self.logger.info("相机资源清理完成")
             
         except Exception as e:
-            self.logger.error(f"清理相机资源失败: {e}")
+            self.logger.error(f"清理相机资源失败: {e}")

backend/devices/femtobolt_manager.py

@@ -98,8 +98,31 @@ class FemtoBoltManager(BaseDevice):
         self.max_reconnect_attempts = 3
         self.reconnect_delay = 3.0
         
+        # 发送频率控制（内存优化）
+        self.send_fps = self.config.get('send_fps', 20)  # 默认20FPS发送
+        self._min_send_interval = 1.0 / self.send_fps if self.send_fps > 0 else 0.05
+        self._last_send_time = 0
+        
+        # 编码参数缓存（避免每帧创建数组）
+        self._encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), int(self.config.get('jpeg_quality', 80))]
+        
+        # 预计算伽马LUT（避免每帧计算）
+        self._gamma_lut = None
+        self._current_gamma = None
+        self._update_gamma_lut()
+        
+        # 预生成网格背景（避免每帧创建）
+        self._grid_bg = None
+        self._grid_size = (480, 640)  # 默认尺寸
+        
         self.logger.info("FemtoBolt管理器初始化完成")
         
+    def _update_gamma_lut(self):
+        """更新伽马校正查找表"""
+        if self._current_gamma != self.gamma_value:
+            self._gamma_lut = np.array([((i / 255.0) ** self.gamma_value) * 255 for i in range(256)]).astype("uint8")
+            self._current_gamma = self.gamma_value
+        
     def initialize(self) -> bool:
         """
         初始化FemtoBolt设备
@@ -391,7 +414,7 @@ class FemtoBoltManager(BaseDevice):
                             
                     capture.release()
                 else:
-                    self.logger.warning(f"校准时无法获取第{i+1}帧")
+                    self.logger.warning(f"校时时无法获取第{i+1}帧")
                     
                 time.sleep(0.1)
                 
@@ -464,162 +487,160 @@ class FemtoBoltManager(BaseDevice):
         
         try:
             while self.is_streaming:
+                # 发送频率限制
+                now = time.time()
+                if now - self._last_send_time < self._min_send_interval:
+                    time.sleep(0.001)
+                    continue
+                
                 if self.device_handle and self._socketio:
                     try:
                         capture = self.device_handle.update()
                         if capture is not None:
-                            ret, depth_image = capture.get_depth_image()
-                            if ret and depth_image is not None:
-                                
-                                # 使用与device_manager.py相同的处理逻辑
-                                depth_image = depth_image.copy()
-                                
-                                # === 生成灰色背景 + 白色网格 ===
-                                rows, cols = depth_image.shape[:2]
-                                background = np.ones((rows, cols, 3), dtype=np.uint8) * 128
-                                cell_size = 50
-                                grid_color = (255, 255, 255)
-                                grid_bg = np.zeros_like(background)
-                                for x in range(0, cols, cell_size):
-                                    cv2.line(grid_bg, (x, 0), (x, rows), grid_color, 1)
-                                for y in range(0, rows, cell_size):
-                                    cv2.line(grid_bg, (0, y), (cols, y), grid_color, 1)
-                                mask_grid = (grid_bg.sum(axis=2) > 0)
-                                background[mask_grid] = grid_bg[mask_grid]
-
-                                # === 处理深度图满足区间的部分 ===
-                                depth_clipped = depth_image.copy()
-                                depth_clipped[depth_clipped < self.depth_range_min] = 0
-                                depth_clipped[depth_clipped > self.depth_range_max] = 0
-                                depth_normalized = np.clip(depth_clipped, self.depth_range_min, self.depth_range_max)
-                                depth_normalized = ((depth_normalized - self.depth_range_min) / (self.depth_range_max - self.depth_range_min) * 255).astype(np.uint8)
-                                
-                                # 对比度和伽马校正
-                                alpha, beta, gamma = 1.5, 0, 0.8
-                                depth_normalized = cv2.convertScaleAbs(depth_normalized, alpha=alpha, beta=beta)
-                                lut = np.array([((i / 255.0) ** gamma) * 255 for i in range(256)]).astype("uint8")
-                                depth_normalized = cv2.LUT(depth_normalized, lut)
-
-                                # 伪彩色
-                                depth_colored = cv2.applyColorMap(depth_normalized, cv2.COLORMAP_JET)
-
-                                # 将有效深度覆盖到灰色背景上
-                                mask_valid = (depth_clipped > 0)
-                                for c in range(3):
-                                    background[:, :, c][mask_valid] = depth_colored[:, :, c][mask_valid]
-
-                                depth_colored_final = background
-
-                                # 裁剪宽度
-                                height, width = depth_colored_final.shape[:2]
-                                target_width = height // 2
-                                if width > target_width:
-                                    left = (width - target_width) // 2
-                                    right = left + target_width
-                                    depth_colored_final = depth_colored_final[:, left:right]
-
-                                # 缓存图像
-                                self.last_depth_frame = depth_colored_final.copy()
-                                self.depth_frame_cache.append(depth_colored_final.copy())
-
-                                # 推送SocketIO
-                                success, buffer = cv2.imencode('.jpg', depth_colored_final, [int(cv2.IMWRITE_JPEG_QUALITY), 80])
-                                if success and self._socketio:
-                                    jpg_as_text = base64.b64encode(buffer).decode('utf-8')
-                                    # 发送到femtobolt命名空间，使用前端期望的事件名和数据格式
-                                    self._socketio.emit('femtobolt_frame', {
-                                        'depth_image': jpg_as_text,
-                                        'frame_count': frame_count,
-                                        'timestamp': time.time(),
-                                        'fps': self.actual_fps,
-                                        'device_id': self.device_id,
-                                        'depth_range': {
-                                            'min': self.depth_range_min,
-                                            'max': self.depth_range_max
-                                        }
-                                    }, namespace='/devices')
-                                    frame_count += 1
+                            try:
+                                ret, depth_image = capture.get_depth_image()
+                                if ret and depth_image is not None:
+                                    # 确保二维数据
+                                    if depth_image.ndim == 3 and depth_image.shape[2] == 1:
+                                        depth_image = depth_image[:, :, 0]
                                     
-                                # 更新统计
-                                self._update_statistics()
-                            else:
-                                time.sleep(0.01)
+                                    rows, cols = depth_image.shape[:2]
+                                    # 生成或复用网格背景
+                                    if (self._grid_bg is None) or (self._grid_size != (rows, cols)):
+                                        bg = np.ones((rows, cols, 3), dtype=np.uint8) * 128
+                                        cell_size = 50
+                                        grid_color = (255, 255, 255)
+                                        grid = np.zeros_like(bg)
+                                        for x in range(0, cols, cell_size):
+                                            cv2.line(grid, (x, 0), (x, rows), grid_color, 1)
+                                        for y in range(0, rows, cell_size):
+                                            cv2.line(grid, (0, y), (cols, y), grid_color, 1)
+                                        mask_grid = (grid.sum(axis=2) > 0)
+                                        bg[mask_grid] = grid[mask_grid]
+                                        self._grid_bg = bg
+                                        self._grid_size = (rows, cols)
+                                    
+                                    # 深度范围过滤 + 归一化
+                                    depth_clipped = np.where(
+                                        (depth_image >= self.depth_range_min) & (depth_image <= self.depth_range_max),
+                                        depth_image, 0
+                                    )
+                                    if np.max(depth_clipped) > 0:
+                                        depth_normalized = ((depth_clipped - self.depth_range_min) / (self.depth_range_max - self.depth_range_min) * 255).astype(np.uint8)
+                                    else:
+                                        depth_normalized = np.zeros((rows, cols), dtype=np.uint8)
+                                    
+                                    # 对比度与伽马
+                                    depth_normalized = cv2.convertScaleAbs(depth_normalized, alpha=1.5, beta=0)
+                                    if self._gamma_lut is None or self._current_gamma != self.gamma_value:
+                                        self._update_gamma_lut()
+                                    depth_gamma = cv2.LUT(depth_normalized, self._gamma_lut)
+                                    
+                                    # 伪彩色
+                                    depth_colored = cv2.applyColorMap(depth_gamma, cv2.COLORMAP_JET)
+                                    
+                                    # 合成到背景（避免copy，使用背景副本）
+                                    background = self._grid_bg.copy()
+                                    mask_valid = (depth_clipped > 0)
+                                    for c in range(3):
+                                        channel = background[:, :, c]
+                                        channel[mask_valid] = depth_colored[:, :, c][mask_valid]
+                                    depth_colored_final = background
+                                    
+                                    # 裁剪宽度
+                                    height, width = depth_colored_final.shape[:2]
+                                    target_width = height // 2
+                                    if width > target_width:
+                                        left = (width - target_width) // 2
+                                        right = left + target_width
+                                        depth_colored_final = depth_colored_final[:, left:right]
+                                    
+                                    # 推送SocketIO
+                                    success, buffer = cv2.imencode('.jpg', depth_colored_final, self._encode_param)
+                                    if success and self._socketio:
+                                        jpg_as_text = base64.b64encode(memoryview(buffer).tobytes()).decode('utf-8')
+                                        self._socketio.emit('femtobolt_frame', {
+                                            'depth_image': jpg_as_text,
+                                            'frame_count': frame_count,
+                                            'timestamp': now,
+                                            'fps': self.actual_fps,
+                                            'device_id': self.device_id,
+                                            'depth_range': {
+                                                'min': self.depth_range_min,
+                                                'max': self.depth_range_max
+                                            }
+                                        }, namespace='/devices')
+                                        frame_count += 1
+                                        self._last_send_time = now
+                                    
+                                    # 更新统计
+                                    self._update_statistics()
+                                else:
+                                    time.sleep(0.005)
+                            except Exception as e:
+                                # 捕获处理过程中出现异常，记录并继续
+                                self.logger.error(f"FemtoBolt捕获处理错误: {e}")
+                            finally:
+                                # 无论处理成功与否，都应释放capture以回收内存:contentReference[oaicite:3]{index=3}
+                                try:
+                                    if hasattr(capture, 'release'):
+                                        capture.release()
+                                except Exception:
+                                    pass
                         else:
-                            time.sleep(0.01)
+                            time.sleep(0.005)
 
                     except Exception as e:
                         self.logger.error(f'FemtoBolt帧推送失败: {e}')
-                        time.sleep(0.1)
+                        time.sleep(0.05)
 
-                time.sleep(1/30)  # 30 FPS
+                # 降低空转CPU
+                time.sleep(0.001)
                 
         except Exception as e:
             self.logger.error(f"FemtoBolt流处理异常: {e}")
         finally:
             self.is_streaming = False
             self.logger.info("FemtoBolt流工作线程结束")
-        
+
     def _process_depth_image(self, depth_image) -> np.ndarray:
         """
         处理深度图像
-        
-        Args:
-            depth_image: 原始深度图像
-            
-        Returns:
-            np.ndarray: 处理后的深度图像
         """
         try:
-            # 确保输入是numpy数组
             if not isinstance(depth_image, np.ndarray):
                 self.logger.error(f"输入的深度图像不是numpy数组: {type(depth_image)}")
                 return np.zeros((480, 640, 3), dtype=np.uint8)
             
-            # 深度范围过滤
             mask = (depth_image >= self.depth_range_min) & (depth_image <= self.depth_range_max)
             filtered_depth = np.where(mask, depth_image, 0)
             
-            # 归一化到0-255
             if np.max(filtered_depth) > 0:
-                normalized = ((filtered_depth - self.depth_range_min) / 
-                             (self.depth_range_max - self.depth_range_min) * 255).astype(np.uint8)
+                normalized = ((filtered_depth - self.depth_range_min) / (self.depth_range_max - self.depth_range_min) * 255).astype(np.uint8)
             else:
                 normalized = np.zeros_like(filtered_depth, dtype=np.uint8)
-                
-            # 对比度增强
+            
             enhanced = cv2.convertScaleAbs(normalized, alpha=self.contrast_factor, beta=0)
             
-            # 伽马校正
-            gamma_corrected = np.power(enhanced / 255.0, self.gamma_value) * 255
-            gamma_corrected = gamma_corrected.astype(np.uint8)
+            if self._gamma_lut is None or self._current_gamma != self.gamma_value:
+                self._update_gamma_lut()
+            gamma_corrected = cv2.LUT(enhanced, self._gamma_lut)
             
-            # 伪彩色映射
             if self.use_pseudo_color:
                 colored = cv2.applyColorMap(gamma_corrected, cv2.COLORMAP_JET)
             else:
                 colored = cv2.cvtColor(gamma_corrected, cv2.COLOR_GRAY2BGR)
-                
-            return colored
             
+            return colored
         except Exception as e:
             self.logger.error(f"处理深度图像失败: {e}")
             return np.zeros((480, 640, 3), dtype=np.uint8)
-            
+
     def _send_depth_data(self, depth_image: np.ndarray, color_image: Optional[np.ndarray] = None):
-        """
-        发送深度数据
-        
-        Args:
-            depth_image: 深度图像
-            color_image: 彩色图像（可选）
-        """
         try:
-            # 压缩深度图像
-            encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 85]
-            _, depth_buffer = cv2.imencode('.jpg', depth_image, encode_param)
-            depth_data = base64.b64encode(depth_buffer).decode('utf-8')
+            _, depth_buffer = cv2.imencode('.jpg', depth_image, self._encode_param)
+            depth_data = base64.b64encode(memoryview(depth_buffer).tobytes()).decode('utf-8')
             
-            # 准备发送数据
             send_data = {
                 'timestamp': time.time(),
                 'frame_count': self.frame_count,
@@ -633,18 +654,15 @@ class FemtoBoltManager(BaseDevice):
                 'last_update': time.strftime('%H:%M:%S')
             }
             
-            # 添加彩色图像（如果有）
             if color_image is not None:
-                _, color_buffer = cv2.imencode('.jpg', color_image, encode_param)
-                color_data = base64.b64encode(color_buffer).decode('utf-8')
+                _, color_buffer = cv2.imencode('.jpg', color_image, self._encode_param)
+                color_data = base64.b64encode(memoryview(color_buffer).tobytes()).decode('utf-8')
                 send_data['color_image'] = color_data
-                
-            # 发送到SocketIO
-            self._socketio.emit('femtobolt_frame', send_data, namespace='/devices')
             
+            self._socketio.emit('femtobolt_frame', send_data, namespace='/devices')
         except Exception as e:
             self.logger.error(f"发送深度数据失败: {e}")
-            
+
     def _update_statistics(self):
         """
         更新性能统计
@@ -848,4 +866,4 @@ class FemtoBoltManager(BaseDevice):
             self.logger.info("FemtoBolt资源清理完成")
             
         except Exception as e:
-            self.logger.error(f"清理FemtoBolt资源失败: {e}")
+            self.logger.error(f"清理FemtoBolt资源失败: {e}")

backend/devices/pressure_manager.py

@@ -45,6 +45,20 @@ except ImportError:
     logger.warning("matplotlib不可用，将使用简化的压力图像生成")
 
 
+# 定义 C 结构体
+class FPMS_DEVICE_INFO(ctypes.Structure):
+    _fields_ = [
+        ("mn", ctypes.c_uint16),
+        ("sn", ctypes.c_char * 64),
+        ("fwVersion", ctypes.c_uint16),
+        ("protoVer", ctypes.c_uint8),
+        ("pid", ctypes.c_uint16),
+        ("vid", ctypes.c_uint16),
+        ("rows", ctypes.c_uint16),
+        ("cols", ctypes.c_uint16),
+    ]
+
+
 class RealPressureDevice:
     """真实SMiTSense压力传感器设备"""
     
@@ -63,11 +77,11 @@ class RealPressureDevice:
         self.frame_size = 0
         self.buf = None
         
-        # 设置DLL路径 - 使用正确的DLL文件名
+        # 设置DLL路径 - 使用Wrapper.dll
         if dll_path is None:
             # 尝试多个可能的DLL文件名
             dll_candidates = [
-                os.path.join(os.path.dirname(__file__), '..', 'dll', 'smitsense', 'SMiTSenseUsbWrapper.dll'),
+                os.path.join(os.path.dirname(__file__), '..', 'dll', 'smitsense', 'Wrapper.dll'),
                 os.path.join(os.path.dirname(__file__), '..', 'dll', 'smitsense', 'SMiTSenseUsb-F3.0.dll')
             ]
             dll_path = None
@@ -97,31 +111,24 @@ class RealPressureDevice:
                 raise FileNotFoundError(f"DLL文件未找到: {self.dll_path}")
             
             # 加载DLL
-            self.dll = ctypes.WinDLL(self.dll_path)
+            self.dll = ctypes.CDLL(self.dll_path)
             logger.info(f"成功加载DLL: {self.dll_path}")
             
-            # 设置函数签名（基于testsmit.py的工作代码）
-            self.dll.SMiTSenseUsb_Init.argtypes = [ctypes.c_int]
-            self.dll.SMiTSenseUsb_Init.restype = ctypes.c_int
+            # 设置函数签名（基于test22new.py的工作代码）
+            self.dll.fpms_usb_init_wrap.argtypes = [ctypes.c_int]
+            self.dll.fpms_usb_init_wrap.restype = ctypes.c_int
             
-            self.dll.SMiTSenseUsb_ScanDevices.argtypes = [ctypes.POINTER(ctypes.c_int)]
-            self.dll.SMiTSenseUsb_ScanDevices.restype = ctypes.c_int
+            self.dll.fpms_usb_get_device_list_wrap.argtypes = [ctypes.POINTER(FPMS_DEVICE_INFO), ctypes.c_int, ctypes.POINTER(ctypes.c_int)]
+            self.dll.fpms_usb_get_device_list_wrap.restype = ctypes.c_int
             
-            self.dll.SMiTSenseUsb_OpenAndStart.argtypes = [
-                ctypes.c_int,
-                ctypes.POINTER(ctypes.c_uint16),
-                ctypes.POINTER(ctypes.c_uint16)
-            ]
-            self.dll.SMiTSenseUsb_OpenAndStart.restype = ctypes.c_int
+            self.dll.fpms_usb_open_wrap.argtypes = [ctypes.c_int, ctypes.POINTER(ctypes.c_uint64)]
+            self.dll.fpms_usb_open_wrap.restype = ctypes.c_int
             
-            self.dll.SMiTSenseUsb_GetLatestFrame.argtypes = [
-                ctypes.POINTER(ctypes.c_uint16),
-                ctypes.c_int
-            ]
-            self.dll.SMiTSenseUsb_GetLatestFrame.restype = ctypes.c_int
+            self.dll.fpms_usb_read_frame_wrap.argtypes = [ctypes.c_uint64, ctypes.POINTER(ctypes.c_uint16), ctypes.c_size_t]
+            self.dll.fpms_usb_read_frame_wrap.restype = ctypes.c_int
             
-            self.dll.SMiTSenseUsb_StopAndClose.argtypes = []
-            self.dll.SMiTSenseUsb_StopAndClose.restype = ctypes.c_int
+            self.dll.fpms_usb_close_wrap.argtypes = [ctypes.c_uint64]
+            self.dll.fpms_usb_close_wrap.restype = ctypes.c_int
             
             logger.info("DLL函数签名设置完成")
             
@@ -133,27 +140,30 @@ class RealPressureDevice:
         """初始化设备连接"""
         try:
             # 初始化USB连接
-            ret = self.dll.SMiTSenseUsb_Init(0)
-            if ret != 0:
-                raise RuntimeError(f"USB初始化失败: {ret}")
+            if self.dll.fpms_usb_init_wrap(0) != 0:
+                raise RuntimeError("初始化失败")
             
-            # 扫描设备
+            # 获取设备列表
             count = ctypes.c_int()
-            ret = self.dll.SMiTSenseUsb_ScanDevices(ctypes.byref(count))
-            if ret != 0 or count.value == 0:
-                raise RuntimeError(f"设备扫描失败或未找到设备: {ret}, count: {count.value}")
+            devs = (FPMS_DEVICE_INFO * 10)()
+            r = self.dll.fpms_usb_get_device_list_wrap(devs, 10, ctypes.byref(count))
+            if r != 0 or count.value == 0:
+                raise RuntimeError(f"未检测到设备: {r}, count: {count.value}")
             
-            logger.info(f"发现 {count.value} 个SMiTSense设备")
+            logger.info(f"检测到设备数量: {count.value}")
+            dev = devs[0]
+            self.rows, self.cols = dev.rows, dev.cols
+            logger.info(f"使用设备 SN={dev.sn.decode(errors='ignore')}  {self.rows}x{self.cols}")
             
-            # 打开并启动第一个设备
-            rows = ctypes.c_uint16()
-            cols = ctypes.c_uint16()
-            ret = self.dll.SMiTSenseUsb_OpenAndStart(0, ctypes.byref(rows), ctypes.byref(cols))
-            if ret != 0:
-                raise RuntimeError(f"设备启动失败: {ret}")
+            # 打开设备
+            self.device_handle = ctypes.c_uint64()
+            r = self.dll.fpms_usb_open_wrap(0, ctypes.byref(self.device_handle))
+            if r != 0:
+                raise RuntimeError("设备打开失败")
             
-            self.rows = rows.value
-            self.cols = cols.value
+            logger.info(f"设备已打开, 句柄 = {self.device_handle.value}")
+            
+            # 准备数据缓冲区
             self.frame_size = self.rows * self.cols
             self.buf_type = ctypes.c_uint16 * self.frame_size
             self.buf = self.buf_type()
@@ -173,9 +183,9 @@ class RealPressureDevice:
                 return self._get_empty_data()
             
             # 读取原始压力数据
-            ret = self.dll.SMiTSenseUsb_GetLatestFrame(self.buf, self.frame_size)
-            if ret != 0:
-                logger.warning(f"读取数据帧失败: {ret}")
+            r = self.dll.fpms_usb_read_frame_wrap(self.device_handle.value, self.buf, self.frame_size)
+            if r != 0:
+                logger.warning(f"读取帧失败, code= {r}")
                 return self._get_empty_data()
             
             # 转换为numpy数组
@@ -248,10 +258,10 @@ class RealPressureDevice:
             right_total_pct = float((right_total_abs / total_abs * 100) if total_abs > 0 else 0)
 
             # 前后占比（相对于各自单足总压）
-            left_front_pct = float((left_front / left_total_abs * 100) if left_total_abs > 0 else 0)
-            left_rear_pct = float((left_rear / left_total_abs * 100) if left_total_abs > 0 else 0)
-            right_front_pct = float((right_front / right_total_abs * 100) if right_total_abs > 0 else 0)
-            right_rear_pct = float((right_rear / right_total_abs * 100) if right_total_abs > 0 else 0)
+            left_front_pct = float((left_front / total_abs * 100) if total_abs > 0 else 0)
+            left_rear_pct = float((left_rear / total_abs * 100) if total_abs > 0 else 0)
+            right_front_pct = float((right_front / total_abs * 100) if total_abs > 0 else 0)
+            right_rear_pct = float((right_rear / total_abs * 100) if total_abs > 0 else 0)
 
             return {
                 'left_front': round(left_front_pct),
@@ -284,7 +294,7 @@ class RealPressureDevice:
             return "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNkYPhfDwAChwGA60e6kgAAAABJRU5ErkJggg=="
     
     def _generate_heatmap_image(self, raw_data) -> str:
-        """生成基于原始数据的热力图（OpenCV实现，固定范围映射，效果与matplotlib一致）"""
+        """生成基于原始数据的热力图（OpenCV实现，自适应归一化，黑色背景）"""
         try:
             import cv2
             import numpy as np
@@ -292,12 +302,20 @@ class RealPressureDevice:
             from io import BytesIO
             from PIL import Image
 
-            # 固定映射范围（与 matplotlib vmin/vmax 一致）
-            vmin, vmax = 0, 1000
-            norm_data = np.clip((raw_data - vmin) / (vmax - vmin) * 255, 0, 255).astype(np.uint8)
+            # 自适应归一化（基于test22new.py的方法2）
+            vmin = 10  # 最小阈值，低于此值显示为黑色
+            dmin, dmax = np.min(raw_data), np.max(raw_data)
+            norm_data = np.clip((raw_data - dmin) / max(dmax - dmin, 1) * 255, 0, 255).astype(np.uint8)
 
             # 应用 jet 颜色映射
             heatmap = cv2.applyColorMap(norm_data, cv2.COLORMAP_JET)
+            
+            # 将低于阈值的区域设置为黑色
+            heatmap[raw_data <= vmin] = (0, 0, 0)
+            
+            # 放大图像以便更好地显示细节
+            rows, cols = raw_data.shape
+            heatmap = cv2.resize(heatmap, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
 
             # OpenCV 生成的是 BGR，转成 RGB
             heatmap_rgb = cv2.cvtColor(heatmap, cv2.COLOR_BGR2RGB)
@@ -363,6 +381,10 @@ class RealPressureDevice:
             ax.text(2, 0.5, '左足', ha='center', va='center', fontsize=12, weight='bold')
             ax.text(8, 0.5, '右足', ha='center', va='center', fontsize=12, weight='bold')
             
+            # 设置图形背景为黑色
+            fig.patch.set_facecolor('black')
+            ax.set_facecolor('black')
+            
             # 保存为base64
             buffer = BytesIO()
             plt.savefig(buffer, format='png', bbox_inches='tight', dpi=100, facecolor='black')
@@ -394,8 +416,8 @@ class RealPressureDevice:
     def close(self):
         """显式关闭压力传感器连接"""
         try:
-            if self.is_connected and self.dll:
-                self.dll.SMiTSenseUsb_StopAndClose()
+            if self.is_connected and self.dll and self.device_handle:
+                self.dll.fpms_usb_close_wrap(self.device_handle.value)
                 self.is_connected = False
                 logger.info('SMiTSense压力传感器连接已关闭')
         except Exception as e:

backend/devices/utils/config.ini

@@ -15,7 +15,7 @@ backup_interval = 24
 max_backups = 7
 
 [CAMERA]
-device_index = 0
+device_index = 3
 width = 1280
 height = 720
 fps = 30
@@ -24,8 +24,8 @@ fps = 30
 color_resolution = 1080P
 depth_mode = NFOV_UNBINNED
 fps = 30
-depth_range_min = 1200
-depth_range_max = 1500
+depth_range_min = 1400
+depth_range_max = 1700
 
 [DEVICES]
 imu_device_type = real

backend/tests/lib_fpms_usb.h

@@ -0,0 +1,57 @@
+#pragma once
+#define __DLL_EXPORTS__ 
+
+#ifdef __DLL_EXPORTS__
+#define DLLAPI  __declspec(dllexport)
+#else
+#define DLLAPI __declspec(dllimport)
+#endif
+
+#include <windows.h>
+#include <cstdint>
+#include <vector>
+using namespace std;
+
+typedef void* SM_HANDLE;
+
+typedef struct _FPMS_DEVICE
+{
+    uint16_t mn;
+    std::string sn;
+    uint16_t fwVersion;
+    uint8_t protoVer;
+    uint16_t pid;
+    uint16_t vid;
+    uint16_t rows;
+    uint16_t cols;
+
+} FPMS_DEVICE_T;
+
+extern "C"
+{
+    DLLAPI
+        int WINAPI fpms_usb_init(int debugFlag);
+
+    DLLAPI
+        int WINAPI fpms_usb_get_device_list(std::vector<FPMS_DEVICE_T>& gDevList);
+
+    DLLAPI
+        int WINAPI fpms_usb_open(FPMS_DEVICE_T dev, SM_HANDLE& gHandle);
+
+    DLLAPI
+        int WINAPI fpms_usb_read_frame(SM_HANDLE gHandle, uint16_t* frame);
+
+    DLLAPI
+        int WINAPI fpms_usb_config_sensitivity(SM_HANDLE gHandle, uint8_t bWriteFlash, const uint8_t level);
+
+    DLLAPI
+        int WINAPI fpms_usb_get_sensitivity(SM_HANDLE gHandle, uint8_t& level);
+
+    DLLAPI
+        int WINAPI fpms_usb_close(SM_HANDLE gHandle);
+}
+
+
+
+
+

backend/tests/test111.py

@@ -0,0 +1,79 @@
+import ctypes
+import time
+import numpy as np
+
+# === DLL 加载 ===
+dll = ctypes.WinDLL(r"D:\BodyBalanceEvaluation\backend\dll\smitsense\SMiTSenseUsbWrapper.dll")
+
+# === DLL 函数声明 ===
+dll.SMiTSenseUsb_Init.argtypes = [ctypes.c_int]
+dll.SMiTSenseUsb_Init.restype = ctypes.c_int
+
+dll.SMiTSenseUsb_ScanDevices.argtypes = [ctypes.POINTER(ctypes.c_int)]
+dll.SMiTSenseUsb_ScanDevices.restype = ctypes.c_int
+
+dll.SMiTSenseUsb_OpenAndStart.argtypes = [
+    ctypes.c_int,
+    ctypes.POINTER(ctypes.c_uint16),
+    ctypes.POINTER(ctypes.c_uint16)
+]
+dll.SMiTSenseUsb_OpenAndStart.restype = ctypes.c_int
+
+dll.SMiTSenseUsb_GetLatestFrame.argtypes = [
+    ctypes.POINTER(ctypes.c_uint16),
+    ctypes.c_int
+]
+dll.SMiTSenseUsb_GetLatestFrame.restype = ctypes.c_int
+
+dll.SMiTSenseUsb_StopAndClose.argtypes = []
+dll.SMiTSenseUsb_StopAndClose.restype = ctypes.c_int
+
+# === 初始化设备 ===
+ret = dll.SMiTSenseUsb_Init(0)
+if ret != 0:
+    raise RuntimeError(f"Init failed: {ret}")
+
+count = ctypes.c_int()
+ret = dll.SMiTSenseUsb_ScanDevices(ctypes.byref(count))
+if ret != 0 or count.value == 0:
+    raise RuntimeError("No devices found")
+
+# 打开设备
+rows = ctypes.c_uint16()
+cols = ctypes.c_uint16()
+ret = dll.SMiTSenseUsb_OpenAndStart(0, ctypes.byref(rows), ctypes.byref(cols))
+if ret != 0:
+    raise RuntimeError("OpenAndStart failed")
+
+rows_val, cols_val = rows.value, cols.value
+frame_size = rows_val * cols_val
+buf_type = ctypes.c_uint16 * frame_size
+buf = buf_type()
+
+# 创建一个 NumPy 数组视图，复用内存
+data_array = np.ctypeslib.as_array(buf).reshape((rows_val, cols_val))
+
+print(f"设备已打开: {rows_val}x{cols_val}")
+
+try:
+    while True:
+       ret = dll.SMiTSenseUsb_GetLatestFrame(buf, frame_size)
+       time.sleep(1)
+    # while True:
+    #     ret = dll.SMiTSenseUsb_GetLatestFrame(buf, frame_size)
+    #     if ret == 0:
+    #         # data_array 已经复用缓冲区内存，每次直接访问即可
+    #         # 例如打印最大值和前5行前5列的数据
+    #         print("最大压力值:", data_array.max())
+    #         print("前5x5数据:\n", data_array[:5, :5])
+    #     else:
+    #         print("读取数据帧失败")
+
+    #     time.sleep(1)  # 每秒读取一帧
+
+except KeyboardInterrupt:
+    print("退出中...")
+
+finally:
+    dll.SMiTSenseUsb_StopAndClose()
+    print("设备已关闭")

backend/tests/test22new.py

@@ -0,0 +1,142 @@
+import ctypes
+import numpy as np
+import cv2
+import sys
+import time
+
+# ------------------- DLL 加载 -------------------
+dll = ctypes.CDLL(r"D:\BodyBalanceEvaluation\backend\tests\Wrapper.dll")
+
+# 定义 C 结构体
+class FPMS_DEVICE_INFO(ctypes.Structure):
+    _fields_ = [
+        ("mn", ctypes.c_uint16),
+        ("sn", ctypes.c_char * 64),
+        ("fwVersion", ctypes.c_uint16),
+        ("protoVer", ctypes.c_uint8),
+        ("pid", ctypes.c_uint16),
+        ("vid", ctypes.c_uint16),
+        ("rows", ctypes.c_uint16),
+        ("cols", ctypes.c_uint16),
+    ]
+
+# 函数声明
+dll.fpms_usb_init_wrap.argtypes = [ctypes.c_int]
+dll.fpms_usb_init_wrap.restype = ctypes.c_int
+
+dll.fpms_usb_get_device_list_wrap.argtypes = [ctypes.POINTER(FPMS_DEVICE_INFO), ctypes.c_int, ctypes.POINTER(ctypes.c_int)]
+dll.fpms_usb_get_device_list_wrap.restype = ctypes.c_int
+
+dll.fpms_usb_open_wrap.argtypes = [ctypes.c_int, ctypes.POINTER(ctypes.c_uint64)]
+dll.fpms_usb_open_wrap.restype = ctypes.c_int
+
+dll.fpms_usb_read_frame_wrap.argtypes = [ctypes.c_uint64, ctypes.POINTER(ctypes.c_uint16), ctypes.c_size_t]
+dll.fpms_usb_read_frame_wrap.restype = ctypes.c_int
+
+dll.fpms_usb_close_wrap.argtypes = [ctypes.c_uint64]
+dll.fpms_usb_close_wrap.restype = ctypes.c_int
+
+# ------------------- 初始化 -------------------
+if dll.fpms_usb_init_wrap(0) != 0:
+    print("初始化失败")
+    sys.exit(1)
+
+# 获取设备列表
+count = ctypes.c_int()
+devs = (FPMS_DEVICE_INFO * 10)()
+r = dll.fpms_usb_get_device_list_wrap(devs, 10, ctypes.byref(count))
+if r != 0 or count.value == 0:
+    print("未检测到设备")
+    sys.exit(1)
+
+print("检测到设备数量:", count.value)
+dev = devs[0]
+rows, cols = dev.rows, dev.cols
+print(f"使用设备 SN={dev.sn.decode(errors='ignore')}  {rows}x{cols}")
+
+# 打开设备
+handle = ctypes.c_uint64()
+r = dll.fpms_usb_open_wrap(0, ctypes.byref(handle))
+if r != 0:
+    print("设备打开失败")
+    sys.exit(1)
+print("设备已打开, 句柄 =", handle.value)
+
+# ------------------- 循环读取帧数据 -------------------
+buf_len = rows * cols
+FrameArray = (ctypes.c_uint16 * buf_len)()
+
+vmin, vmax = 100, 1000   # 根据实际传感器数据范围调整
+
+try:
+    while True:
+        r = dll.fpms_usb_read_frame_wrap(handle.value, FrameArray, buf_len)
+        if r != 0:
+            print("读取帧失败, code=", r)
+            time.sleep(0.05)
+            continue
+
+        # 转 numpy
+        data = np.frombuffer(FrameArray, dtype=np.uint16).reshape((rows, cols))
+
+        # ------------------- 方法1: 固定线性映射 -------------------
+        norm1 = np.clip((data - vmin) / (vmax - vmin) * 255, 0, 255).astype(np.uint8)
+        heatmap1 = cv2.applyColorMap(norm1, cv2.COLORMAP_JET)
+        heatmap1[data <= vmin] = (0,0,0)
+        heatmap1 = cv2.resize(heatmap1, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
+        cv2.imshow("方法1: 固定线性", heatmap1)
+
+        # ------------------- 方法2: 自适应归一化 -------------------
+        dmin, dmax = np.min(data), np.max(data)
+        norm2 = np.clip((data - dmin) / max(dmax - dmin, 1) * 255, 0, 255).astype(np.uint8)
+        heatmap2 = cv2.applyColorMap(norm2, cv2.COLORMAP_JET)
+        heatmap2[data <= vmin] = (0,0,0)
+        heatmap2 = cv2.resize(heatmap2, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
+        cv2.imshow("方法2: 自适应归一化", heatmap2)
+
+        # ------------------- 方法3: 对数映射 -------------------
+        log_data = np.log1p(data - vmin)
+        log_max = np.max(log_data)
+        norm3 = np.clip(log_data / max(log_max, 1) * 255, 0, 255).astype(np.uint8)
+        heatmap3 = cv2.applyColorMap(norm3, cv2.COLORMAP_JET)
+        heatmap3[data <= vmin] = (0,0,0)
+        heatmap3 = cv2.resize(heatmap3, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
+        cv2.imshow("方法3: 对数映射", heatmap3)
+
+        # ------------------- 方法4: 平方根映射 -------------------
+        sqrt_data = np.sqrt(np.clip(data - vmin, 0, None))
+        sqrt_max = np.max(sqrt_data)
+        norm4 = np.clip(sqrt_data / max(sqrt_max, 1) * 255, 0, 255).astype(np.uint8)
+        heatmap4 = cv2.applyColorMap(norm4, cv2.COLORMAP_JET)
+        heatmap4[data <= vmin] = (0,0,0)
+        heatmap4 = cv2.resize(heatmap4, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
+        cv2.imshow("方法4: 平方根映射", heatmap4)
+
+        # ------------------- 方法5: 分段颜色映射 -------------------
+        heatmap5 = np.zeros((rows, cols, 3), dtype=np.uint8)
+        # 定义压力区间和对应颜色 (B,G,R)
+        bins = [vmin, 250, 400, 600, 800, vmax]
+        colors = [
+            (0,0,0),
+            (0,0,255),     # 蓝
+            (0,255,0),     # 绿
+            (0,255,255),   # 黄
+            (255,0,0),     # 红
+        ]
+        for i in range(len(bins)-1):
+            mask = (data > bins[i]) & (data <= bins[i+1])
+            heatmap5[mask] = colors[i]
+        heatmap5 = cv2.resize(heatmap5, (cols*4, rows*4), interpolation=cv2.INTER_NEAREST)
+        cv2.imshow("方法5: 分段映射", heatmap5)
+
+        # ------------------- 退出 -------------------
+        if cv2.waitKey(1) & 0xFF == 27:  # ESC 退出
+            break
+
+except KeyboardInterrupt:
+    pass
+
+# ------------------- 清理 -------------------
+dll.fpms_usb_close_wrap(handle.value)
+cv2.destroyAllWindows()
+print("已退出")

backend/tests/test_smitsense_dll.py

@@ -1,479 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-SMiTSense足部压力传感器DLL测试程序
-测试SMiTSenseUsb-F3.0.dll的Python接口调用
-"""
-
-import ctypes
-import os
-import sys
-import time
-from ctypes import Structure, c_int, c_float, c_char_p, c_void_p, c_uint32, POINTER, byref
-import logging
-
-# 设置日志
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
-
-class SMiTSensePressureSensor:
-    """
-    SMiTSense足部压力传感器Python接口类
-    """
-    
-    def __init__(self, dll_path=None):
-        """
-        初始化SMiTSense压力传感器
-        
-        Args:
-            dll_path: DLL文件路径，如果为None则使用默认路径
-        """
-        self.dll = None
-        self.device_handle = None
-        self.is_connected = False
-        
-        # 设置DLL路径
-        if dll_path is None:
-            dll_path = os.path.join(os.path.dirname(__file__), 'SMiTSenseUsb-F3.0.dll')
-        
-        self.dll_path = dll_path
-        self._load_dll()
-    
-    def _load_dll(self):
-        """
-        加载SMiTSense DLL并设置函数签名
-        """
-        try:
-            if not os.path.exists(self.dll_path):
-                raise FileNotFoundError(f"DLL文件未找到: {self.dll_path}")
-            
-            # 加载DLL
-            self.dll = ctypes.WinDLL(self.dll_path)
-            logger.info(f"成功加载DLL: {self.dll_path}")
-            
-            # 设置函数签名
-            self._setup_function_signatures()
-            
-        except Exception as e:
-            logger.error(f"加载DLL失败: {e}")
-            raise
-    
-    def _setup_function_signatures(self):
-        """
-        设置DLL函数的参数类型和返回类型
-        """
-        try:
-            # fpms_usb_init - 初始化USB连接
-            self.dll.fpms_usb_init.argtypes = []
-            self.dll.fpms_usb_init.restype = c_int
-            
-            # fpms_usb_get_device_list - 获取设备列表
-            self.dll.fpms_usb_get_device_list.argtypes = [POINTER(c_int)]
-            self.dll.fpms_usb_get_device_list.restype = c_int
-            
-            # fpms_usb_open - 打开设备
-            self.dll.fpms_usb_open.argtypes = [c_int]
-            self.dll.fpms_usb_open.restype = c_void_p
-            
-            # fpms_usb_close - 关闭设备
-            self.dll.fpms_usb_close.argtypes = [c_void_p]
-            self.dll.fpms_usb_close.restype = c_int
-            
-            # fpms_usb_read_frame - 读取压力数据帧
-            self.dll.fpms_usb_read_frame.argtypes = [c_void_p, POINTER(c_float), c_int]
-            self.dll.fpms_usb_read_frame.restype = c_int
-            
-            # fpms_usb_get_sensitivity - 获取灵敏度
-            self.dll.fpms_usb_get_sensitivity.argtypes = [c_void_p, POINTER(c_float)]
-            self.dll.fpms_usb_get_sensitivity.restype = c_int
-            
-            # fpms_usb_config_sensitivity - 配置灵敏度
-            self.dll.fpms_usb_config_sensitivity.argtypes = [c_void_p, c_float]
-            self.dll.fpms_usb_config_sensitivity.restype = c_int
-            
-            logger.info("DLL函数签名设置完成")
-            
-        except AttributeError as e:
-            logger.error(f"设置函数签名失败，可能是函数名不匹配: {e}")
-            raise
-    
-    def initialize(self):
-        """
-        初始化USB连接
-        
-        Returns:
-            bool: 初始化是否成功
-        """
-        try:
-            result = self.dll.fpms_usb_init()
-            if result == 0:
-                logger.info("USB连接初始化成功")
-                return True
-            else:
-                logger.error(f"USB连接初始化失败，错误码: {result}")
-                return False
-        except Exception as e:
-            logger.error(f"初始化异常: {e}")
-            return False
-    
-    def get_device_list(self):
-        """
-        获取可用设备列表
-        
-        Returns:
-            list: 设备ID列表
-        """
-        try:
-            device_count = c_int()
-            result = self.dll.fpms_usb_get_device_list(byref(device_count))
-            
-            if result == 0:
-                count = device_count.value
-                logger.info(f"发现 {count} 个SMiTSense设备")
-                return list(range(count))
-            else:
-                logger.error(f"获取设备列表失败，错误码: {result}")
-                return []
-        except Exception as e:
-            logger.error(f"获取设备列表异常: {e}")
-            return []
-    
-    def connect(self, device_id=0):
-        """
-        连接到指定设备
-        
-        Args:
-            device_id: 设备ID，默认为0
-            
-        Returns:
-            bool: 连接是否成功
-        """
-        try:
-            self.device_handle = self.dll.fpms_usb_open(device_id)
-            
-            if self.device_handle:
-                self.is_connected = True
-                logger.info(f"成功连接到设备 {device_id}")
-                return True
-            else:
-                logger.error(f"连接设备 {device_id} 失败")
-                return False
-        except Exception as e:
-            logger.error(f"连接设备异常: {e}")
-            return False
-    
-    def disconnect(self):
-        """
-        断开设备连接
-        
-        Returns:
-            bool: 断开是否成功
-        """
-        try:
-            if self.device_handle and self.is_connected:
-                result = self.dll.fpms_usb_close(self.device_handle)
-                
-                if result == 0:
-                    self.is_connected = False
-                    self.device_handle = None
-                    logger.info("设备连接已断开")
-                    return True
-                else:
-                    logger.error(f"断开连接失败，错误码: {result}")
-                    return False
-            else:
-                logger.warning("设备未连接，无需断开")
-                return True
-        except Exception as e:
-            logger.error(f"断开连接异常: {e}")
-            return False
-    
-    def read_pressure_data(self, sensor_count=16):
-        """
-        读取压力传感器数据
-        
-        Args:
-            sensor_count: 传感器数量，默认16个
-            
-        Returns:
-            list: 压力值列表，如果失败返回None
-        """
-        try:
-            if not self.is_connected or not self.device_handle:
-                logger.error("设备未连接")
-                return None
-            
-            # 创建压力数据缓冲区
-            pressure_data = (c_float * sensor_count)()
-            
-            result = self.dll.fpms_usb_read_frame(
-                self.device_handle, 
-                pressure_data, 
-                sensor_count
-            )
-            
-            if result == 0:
-                # 转换为Python列表
-                data_list = [pressure_data[i] for i in range(sensor_count)]
-                logger.debug(f"读取压力数据成功: {data_list}")
-                return data_list
-            else:
-                logger.error(f"读取压力数据失败，错误码: {result}")
-                return None
-                
-        except Exception as e:
-            logger.error(f"读取压力数据异常: {e}")
-            return None
-    
-    def get_sensitivity(self):
-        """
-        获取传感器灵敏度
-        
-        Returns:
-            float: 灵敏度值，如果失败返回None
-        """
-        try:
-            if not self.is_connected or not self.device_handle:
-                logger.error("设备未连接")
-                return None
-            
-            sensitivity = c_float()
-            result = self.dll.fpms_usb_get_sensitivity(self.device_handle, byref(sensitivity))
-            
-            if result == 0:
-                value = sensitivity.value
-                logger.info(f"当前灵敏度: {value}")
-                return value
-            else:
-                logger.error(f"获取灵敏度失败，错误码: {result}")
-                return None
-                
-        except Exception as e:
-            logger.error(f"获取灵敏度异常: {e}")
-            return None
-    
-    def set_sensitivity(self, sensitivity_value):
-        """
-        设置传感器灵敏度
-        
-        Args:
-            sensitivity_value: 灵敏度值
-            
-        Returns:
-            bool: 设置是否成功
-        """
-        try:
-            if not self.is_connected or not self.device_handle:
-                logger.error("设备未连接")
-                return False
-            
-            result = self.dll.fpms_usb_config_sensitivity(
-                self.device_handle, 
-                c_float(sensitivity_value)
-            )
-            
-            if result == 0:
-                logger.info(f"灵敏度设置成功: {sensitivity_value}")
-                return True
-            else:
-                logger.error(f"设置灵敏度失败，错误码: {result}")
-                return False
-                
-        except Exception as e:
-            logger.error(f"设置灵敏度异常: {e}")
-            return False
-    
-    def get_foot_pressure_zones(self, pressure_data):
-        """
-        将原始压力数据转换为足部区域压力
-        
-        Args:
-            pressure_data: 原始压力数据列表
-            
-        Returns:
-            dict: 足部各区域压力数据
-        """
-        if not pressure_data or len(pressure_data) < 16:
-            return None
-        
-        try:
-            # 假设16个传感器的布局（可根据实际传感器布局调整）
-            # 左脚前部: 传感器 0-3
-            # 左脚后部: 传感器 4-7  
-            # 右脚前部: 传感器 8-11
-            # 右脚后部: 传感器 12-15
-            
-            left_front = sum(pressure_data[0:4])
-            left_rear = sum(pressure_data[4:8])
-            right_front = sum(pressure_data[8:12])
-            right_rear = sum(pressure_data[12:16])
-            
-            left_total = left_front + left_rear
-            right_total = right_front + right_rear
-            total_pressure = left_total + right_total
-            
-            return {
-                'left_front': left_front,
-                'left_rear': left_rear,
-                'right_front': right_front,
-                'right_rear': right_rear,
-                'left_total': left_total,
-                'right_total': right_total,
-                'total_pressure': total_pressure,
-                'raw_data': pressure_data
-            }
-            
-        except Exception as e:
-            logger.error(f"处理足部压力区域数据异常: {e}")
-            return None
-
-
-def test_smitsense_sensor():
-    """
-    测试SMiTSense压力传感器的主要功能
-    """
-    logger.info("开始SMiTSense压力传感器测试")
-    
-    # 创建传感器实例
-    sensor = SMiTSensePressureSensor()
-    
-    try:
-        # 1. 初始化
-        logger.info("1. 初始化USB连接...")
-        if not sensor.initialize():
-            logger.error("初始化失败，测试终止")
-            return False
-        
-        # 2. 获取设备列表
-        logger.info("2. 获取设备列表...")
-        devices = sensor.get_device_list()
-        if not devices:
-            logger.warning("未发现SMiTSense设备")
-            return False
-        
-        logger.info(f"发现设备: {devices}")
-        
-        # 3. 连接第一个设备
-        logger.info("3. 连接设备...")
-        if not sensor.connect(devices[0]):
-            logger.error("连接设备失败")
-            return False
-        
-        # 4. 获取当前灵敏度
-        logger.info("4. 获取传感器灵敏度...")
-        sensitivity = sensor.get_sensitivity()
-        if sensitivity is not None:
-            logger.info(f"当前灵敏度: {sensitivity}")
-        
-        # 5. 设置新的灵敏度（可选）
-        logger.info("5. 设置传感器灵敏度...")
-        if sensor.set_sensitivity(1.0):
-            logger.info("灵敏度设置成功")
-        
-        # 6. 读取压力数据
-        logger.info("6. 开始读取压力数据...")
-        for i in range(10):  # 读取10次数据
-            pressure_data = sensor.read_pressure_data()
-            
-            if pressure_data:
-                # 转换为足部区域数据
-                foot_zones = sensor.get_foot_pressure_zones(pressure_data)
-                
-                if foot_zones:
-                    logger.info(f"第{i+1}次读取:")
-                    logger.info(f"  左脚前部: {foot_zones['left_front']:.2f}")
-                    logger.info(f"  左脚后部: {foot_zones['left_rear']:.2f}")
-                    logger.info(f"  右脚前部: {foot_zones['right_front']:.2f}")
-                    logger.info(f"  右脚后部: {foot_zones['right_rear']:.2f}")
-                    logger.info(f"  总压力: {foot_zones['total_pressure']:.2f}")
-                else:
-                    logger.warning(f"第{i+1}次读取: 数据处理失败")
-            else:
-                logger.warning(f"第{i+1}次读取: 无数据")
-            
-            time.sleep(0.1)  # 等待100ms
-        
-        logger.info("压力数据读取测试完成")
-        return True
-        
-    except Exception as e:
-        logger.error(f"测试过程中发生异常: {e}")
-        return False
-        
-    finally:
-        # 7. 断开连接
-        logger.info("7. 断开设备连接...")
-        sensor.disconnect()
-        logger.info("SMiTSense压力传感器测试结束")
-
-
-def test_dll_functions():
-    """
-    测试DLL函数的基本调用（不需要实际硬件）
-    """
-    logger.info("开始DLL函数基本调用测试")
-    
-    try:
-        sensor = SMiTSensePressureSensor()
-        logger.info("DLL加载成功")
-        
-        # 测试初始化函数
-        logger.info("测试初始化函数...")
-        result = sensor.initialize()
-        logger.info(f"初始化结果: {result}")
-        
-        # 测试获取设备列表
-        logger.info("测试获取设备列表...")
-        devices = sensor.get_device_list()
-        logger.info(f"设备列表: {devices}")
-        
-        logger.info("DLL函数基本调用测试完成")
-        return True
-        
-    except Exception as e:
-        logger.error(f"DLL函数测试失败: {e}")
-        return False
-
-
-if __name__ == "__main__":
-    print("SMiTSense足部压力传感器DLL测试程序")
-    print("=" * 50)
-    
-    # 检查DLL文件是否存在
-    dll_path = os.path.join(os.path.dirname(__file__), 'SMiTSenseUsb-F3.0.dll')
-    if not os.path.exists(dll_path):
-        print(f"错误: DLL文件不存在 - {dll_path}")
-        print("请确保SMiTSenseUsb-F3.0.dll文件在当前目录中")
-        sys.exit(1)
-    
-    print(f"DLL文件路径: {dll_path}")
-    print()
-    
-    # 运行测试
-    try:
-        # 首先测试DLL基本功能
-        print("1. DLL基本功能测试")
-        print("-" * 30)
-        if test_dll_functions():
-            print("✅ DLL基本功能测试通过")
-        else:
-            print("❌ DLL基本功能测试失败")
-        
-        print()
-        
-        # 然后测试完整的传感器功能（需要硬件）
-        print("2. 完整传感器功能测试（需要硬件连接）")
-        print("-" * 30)
-        if test_smitsense_sensor():
-            print("✅ 传感器功能测试通过")
-        else:
-            print("❌ 传感器功能测试失败（可能是硬件未连接）")
-            
-    except KeyboardInterrupt:
-        print("\n用户中断测试")
-    except Exception as e:
-        print(f"\n测试过程中发生未处理的异常: {e}")
-        import traceback
-        traceback.print_exc()
-    
-    print("\n测试程序结束")

backend/tests/testsmit.py

@@ -4,7 +4,7 @@ import numpy as np
 import cv2
 
 # === DLL 加载 ===
-dll = ctypes.WinDLL(r"D:\Trae_space\BodyBalanceEvaluation\backend\tests\SMiTSenseUsbWrapper.dll")
+dll = ctypes.WinDLL(r"D:\BodyBalanceEvaluation\backend\dll\smitsense\SMiTSenseUsbWrapper.dll")
 
 dll.SMiTSenseUsb_Init.argtypes = [ctypes.c_int]
 dll.SMiTSenseUsb_Init.restype = ctypes.c_int
@@ -76,7 +76,7 @@ try:
                 break
         else:
             print("读取数据帧失败")
-        time.sleep(0.05)  # 20 FPS
+        time.sleep(1)  # 20 FPS
 except KeyboardInterrupt:
     pass
 finally: