为所有函数和类添加中文注释文档字符串

app/audio/rep_announcer.py

@@ -8,9 +8,11 @@ from typing import Any
 
 from loguru import logger
 
-
 class RepAnnouncer:
+    """运动次数语音播报器"""
+
     def __init__(self, *, enabled: bool = True, rate: int = 185, volume: float = 1.0) -> None:
+        """初始化TTS引擎（macOS用say，其他系统用pyttsx3）"""
         self.enabled = enabled
         self.rate = rate
         self.volume = volume
@@ -24,6 +26,7 @@ class RepAnnouncer:
             self._start()
 
     def announce_count(self, count: int) -> None:
+        """将次数放入队列进行异步语音播报"""
         if not self.enabled or count <= 0:
             return
         while True:
@@ -34,6 +37,7 @@ class RepAnnouncer:
         self._queue.put(str(count))
 
     def close(self) -> None:
+        """停止播报线程并释放资源"""
         if not self.enabled:
             return
         self._queue.put(None)
@@ -43,6 +47,7 @@ class RepAnnouncer:
             self._current_process.terminate()
 
     def _start(self) -> None:
+        """根据平台初始化TTS引擎并启动后台播报线程"""
         if sys.platform == "darwin":
             self._use_macos_say = True
             logger.info("Rep announcer initialized with macOS say")
@@ -63,6 +68,7 @@ class RepAnnouncer:
         self._thread.start()
 
     def _run(self) -> None:
+        """后台线程：从队列读取文本并调用TTS播放"""
         while True:
             text = self._queue.get()
             if text is None:

app/core/lifecycle.py

@@ -5,6 +5,7 @@ from configs.load import config
 
 
 def startup() -> None:
+    """应用启动初始化：开启崩溃日志和日志系统"""
     enable_crash_handler(config.logging.dir_path)
     from app.core.logging import setup_logging
     setup_logging()

app/core/logging.py

@@ -8,6 +8,7 @@ from configs.load import config
 
 
 def setup_logging() -> None:
+    """配置loguru日志输出到按日期轮转的日志文件"""
     log_dir = config.logging.dir_path
     log_dir.mkdir(parents=True, exist_ok=True)
 

app/diagnostics/crash_handler.py

@@ -5,6 +5,7 @@ from pathlib import Path
 
 
 def enable_crash_handler(log_dir: str | Path) -> None:
+    """启用faulthandler，将崩溃堆栈写入日志文件"""
     log_dir = Path(log_dir)
     log_dir.mkdir(parents=True, exist_ok=True)
     crash_log = open(log_dir / "posefit-crash.log", "a", buffering=1)

app/diagnostics/perf_timer.py

@@ -5,28 +5,33 @@ from contextlib import contextmanager
 
 from loguru import logger
 
-
 class PerfTimer:
+    """性能计时器，用于测量代码段执行耗时"""
+
     def __init__(self, name: str = "") -> None:
         self.name = name
         self._start = 0.0
         self._elapsed = 0.0
 
     def start(self) -> PerfTimer:
+        """启动计时器"""
         self._start = time.perf_counter()
         return self
 
     def stop(self) -> float:
+        """停止计时器并返回耗时（秒）"""
         self._elapsed = time.perf_counter() - self._start
         return self._elapsed
 
     @property
     def elapsed_ms(self) -> float:
+        """返回已记录耗时（毫秒）"""
         return self._elapsed * 1000
 
 
 @contextmanager
 def measure(name: str = ""):
+    """上下文管理器：进入时计时，退出时记录耗时日志"""
     timer = PerfTimer(name).start()
     yield timer
     elapsed = timer.stop()

app/exercises/dead_bug/detector.py

@@ -32,8 +32,9 @@ from app.vision.pose_types import (
     RIGHT_WRIST,
 )
 
-
 class DeadBugDetector:
+    """死虫式（Dead Bug）运动检测器"""
+
     def __init__(
         self,
         *,
@@ -43,6 +44,7 @@ class DeadBugDetector:
         reset_confirm_frames: int = 3,
         prefer_gpu: bool = True,
     ) -> None:
+        """初始化姿态检测器、状态机和可视化渲染组件"""
         self.visibility_threshold = visibility_threshold
 
         self._latest_result = None
@@ -72,9 +74,11 @@ class DeadBugDetector:
         self._last_timestamp_ms = -1
 
     def close(self) -> None:
+        """释放MediaPipe模型资源"""
         self._landmarker.close()
 
     def process_frame(self, bgr_frame: np.ndarray, timestamp_ms: int) -> tuple[np.ndarray, DeadBugResult]:
+        """处理单帧：姿态检测、指标计算、状态机更新、可视化叠加"""
         timestamp_ms = self._normalize_timestamp(timestamp_ms)
 
         with self._result_lock:
@@ -166,6 +170,7 @@ class DeadBugDetector:
         return annotated, result
 
     def _normalize_timestamp(self, timestamp_ms: int) -> int:
+        """确保时间戳严格递增（MediaPipe要求）"""
         if timestamp_ms <= self._last_timestamp_ms:
             timestamp_ms = self._last_timestamp_ms + 1
         self._last_timestamp_ms = timestamp_ms

app/exercises/dead_bug/metrics.py

@@ -7,6 +7,7 @@ from app.exercises.dead_bug.types import Point
 
 
 def angle(a: Point, b: Point, c: Point) -> float:
+    """计算以b为顶点的三点夹角（度数）"""
     ba = np.array([a.x - b.x, a.y - b.y], dtype=np.float32)
     bc = np.array([c.x - b.x, c.y - b.y], dtype=np.float32)
     denom = float(np.linalg.norm(ba) * np.linalg.norm(bc))
@@ -17,6 +18,7 @@ def angle(a: Point, b: Point, c: Point) -> float:
 
 
 def distance(a: Point, b: Point) -> float:
+    """计算两点之间的欧几里得距离（归一化坐标空间）"""
     return float(np.hypot(a.x - b.x, a.y - b.y))
 
 
@@ -37,6 +39,7 @@ def calculate_metrics(
     right_ankle: int,
     visibility_threshold: float = 0.45,
 ) -> dict:
+    """计算四肢关节角度、伸展状态及反馈信息"""
     left_elbow_angle = angle(lm[left_shoulder], lm[left_elbow], lm[left_wrist])
     right_elbow_angle = angle(lm[right_shoulder], lm[right_elbow], lm[right_wrist])
     left_knee_angle = angle(lm[left_hip], lm[left_knee], lm[left_ankle])

app/exercises/dead_bug/rules.py

@@ -4,10 +4,12 @@ from app.exercises.dead_bug.types import DeadBugMetrics, Point
 
 
 def has_required_visibility(landmarks: list[Point], required_indices: tuple[int, ...], visibility_threshold: float) -> bool:
+    """检查所有必需关键点的可见度是否高于阈值"""
     return all(landmarks[i].visibility >= visibility_threshold for i in required_indices)
 
 
 def detect_diagonal_extension(metrics: DeadBugMetrics) -> str | None:
+    """检测是否存在对角伸展（左臂+右腿 或 右臂+左腿）"""
     if metrics.left_leg_extended and metrics.right_leg_extended:
         return None
 
@@ -19,6 +21,7 @@ def detect_diagonal_extension(metrics: DeadBugMetrics) -> str | None:
 
 
 def is_ready_position(metrics: DeadBugMetrics) -> bool:
+    """判断是否处于准备姿态（膝盖弯曲且四肢未伸展）"""
     knees_bent = metrics.left_knee_angle <= 140 and metrics.right_knee_angle <= 140
     legs_not_extended = not metrics.left_leg_extended and not metrics.right_leg_extended
     return knees_bent and legs_not_extended and detect_diagonal_extension(metrics) is None

app/exercises/dead_bug/state_machine.py

@@ -3,9 +3,11 @@ from __future__ import annotations
 from app.exercises.dead_bug.rules import detect_diagonal_extension, is_ready_position
 from app.exercises.dead_bug.types import DeadBugMetrics, DeadBugPhase, DeadBugResult
 
-
 class DeadBugStateMachine:
+    """死虫式动作状态机：管理READY/EXTENDING/NEED_RESET/NO_POSE状态转换"""
+
     def __init__(self, *, extension_confirm_frames: int = 4, reset_confirm_frames: int = 3) -> None:
+        """初始化并设置状态转换确认帧数"""
         self.extension_confirm_frames = extension_confirm_frames
         self.reset_confirm_frames = reset_confirm_frames
 
@@ -17,6 +19,7 @@ class DeadBugStateMachine:
         self._reset_frames = 0
 
     def update(self, metrics: DeadBugMetrics) -> DeadBugResult:
+        """根据传入指标更新状态机并返回本次结果"""
         side = detect_diagonal_extension(metrics)
         ready = is_ready_position(metrics)
 

app/exercises/dead_bug/types.py

@@ -5,6 +5,7 @@ from enum import Enum
 
 
 class DeadBugPhase(str, Enum):
+    """死虫式动作阶段枚举"""
     READY = "ready"
     EXTENDING = "extending"
     NEED_RESET = "need_reset"
@@ -13,6 +14,7 @@ class DeadBugPhase(str, Enum):
 
 @dataclass(frozen=True)
 class Point:
+    """三维关键点坐标及可见度"""
     x: float
     y: float
     z: float
@@ -21,6 +23,7 @@ class Point:
 
 @dataclass
 class DeadBugMetrics:
+    """四肢关节度量数据"""
     left_arm_extended: bool
     right_arm_extended: bool
     left_leg_extended: bool
@@ -34,6 +37,7 @@ class DeadBugMetrics:
 
 @dataclass
 class DeadBugResult:
+    """单帧检测结果"""
     rep_count: int
     phase: DeadBugPhase
     side: str | None

app/main.py

@@ -9,6 +9,7 @@ from app.signaling.websocket_server import main as serve
 
 
 def main():
+    """应用入口：启动服务并运行WebSocket信令服务器"""
     startup()
     logger.info("Starting server...")
     try:

app/rendering/overlay_renderer.py

@@ -7,6 +7,7 @@ from app.exercises.dead_bug.types import DeadBugResult
 
 
 def draw_status_overlay(image: np.ndarray, result: DeadBugResult) -> None:
+    """在图像上叠加动作状态信息（次数、阶段、反馈）"""
     color = (60, 220, 90) if result.is_standard else (50, 180, 255)
     cv2.rectangle(image, (12, 12), (520, 142), (20, 20, 20), -1)
     cv2.putText(image, f"Dead bug reps: {result.rep_count}", (28, 48), cv2.FONT_HERSHEY_SIMPLEX, 0.9, color, 2)

app/rendering/skeleton_renderer.py

@@ -18,6 +18,7 @@ def draw_landmarks(
     line_thickness: int = 2,
     point_radius: int = 4,
 ) -> None:
+    """绘制人体骨架关键点与连接线（仅绘制可见度达标的点）"""
     if connections is None:
         connections = _POSE_CONNECTIONS
 

app/rendering/window_display.py

@@ -6,16 +6,20 @@ WINDOW_NAME = "Android Camera (WebRTC)"
 
 
 def show_frame(image, window_name: str = WINDOW_NAME) -> None:
+    """在OpenCV窗口中显示图像帧"""
     cv2.imshow(window_name, image)
 
 
 def wait_key(delay_ms: int = 1) -> int:
+    """等待按键并返回ASCII码"""
     return cv2.waitKey(delay_ms) & 0xFF
 
 
 def is_esc_pressed() -> bool:
+    """检测ESC键是否被按下"""
     return wait_key(1) == 27
 
 
 def close_window() -> None:
+    """关闭所有OpenCV窗口"""
     cv2.destroyAllWindows()

app/signaling/ice_parser.py

@@ -7,6 +7,7 @@ from aiortc import RTCIceCandidate
 
 
 def parse_ice(data: dict[str, Any]) -> RTCIceCandidate | None:
+    """解析ICE候选者字符串为RTCIceCandidate对象"""
     match = re.match(
         r'candidate:(\S+) (\d) (\S+) (\d+) (\S+) (\d+) typ (\S+)(?: raddr (\S+) rport (\d+))?',
         data["candidate"],

app/signaling/message_models.py

@@ -1,10 +1,11 @@
 from __future__ import annotations
 
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 
 
 @dataclass
 class SignalingMessage:
+    """WebRTC信令消息数据模型"""
     type: str
     sdp: str = ""
     candidate: str = ""

app/signaling/websocket_server.py

@@ -11,6 +11,7 @@ from configs.load import config
 
 
 async def handle_client(websocket):
+    """处理单个WebSocket客户端连接"""
     client = websocket.remote_address
     logger.info(f"Client connected: {client}")
 
@@ -21,6 +22,7 @@ async def handle_client(websocket):
 
 
 async def main():
+    """启动WebSocket信令服务器"""
     cfg = config.server
     logger.info(f"WebRTC signaling server: ws://{cfg.host}:{cfg.port}")
     async with websockets.serve(handle_client, cfg.host, cfg.port, max_size=cfg.max_ws_size):

app/vision/frame_utils.py

@@ -9,6 +9,7 @@ TARGET_HEIGHT = 720
 
 
 def resize_to_target(image: np.ndarray, width: int = TARGET_WIDTH, height: int = TARGET_HEIGHT) -> np.ndarray:
+    """将图像缩放到目标尺寸（仅当尺寸不一致时）"""
     h, w = image.shape[:2]
     if w == width and h == height:
         return image
@@ -16,8 +17,10 @@ def resize_to_target(image: np.ndarray, width: int = TARGET_WIDTH, height: int =
 
 
 def bgr_to_rgba(bgr: np.ndarray) -> np.ndarray:
+    """将BGR格式图像转换为RGBA格式"""
     return cv2.cvtColor(bgr, cv2.COLOR_BGR2RGBA)
 
 
 def bgr_to_rgb(bgr: np.ndarray) -> np.ndarray:
+    """将BGR格式图像转换为RGB格式"""
     return cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)

app/vision/pose_landmarker.py

@@ -14,8 +14,9 @@ PoseLandmarkerOptions = mp.tasks.vision.PoseLandmarkerOptions
 VisionRunningMode = mp.tasks.vision.RunningMode
 BaseOptions = mp.tasks.BaseOptions
 
-
 class PoseLandmarkerWrapper:
+    """MediaPipe姿态关键点检测器封装"""
+
     def __init__(
         self,
         *,
@@ -23,6 +24,7 @@ class PoseLandmarkerWrapper:
         prefer_gpu: bool = True,
         result_callback: Callable | None = None,
     ) -> None:
+        """初始化姿态检测器，优先尝试GPU委托，失败则回退到CPU"""
         self.model_path = model_path or DEFAULT_MODEL_PATH
 
         if prefer_gpu:
@@ -39,6 +41,7 @@ class PoseLandmarkerWrapper:
         logger.info("MediaPipe PoseLandmarker initialized with CPU delegate")
 
     def _create(self, delegate, result_callback=None):
+        """根据委托类型和回调创建PoseLandmarker实例"""
         options = PoseLandmarkerOptions(
             base_options=BaseOptions(model_asset_path=self.model_path, delegate=delegate),
             running_mode=VisionRunningMode.LIVE_STREAM,
@@ -51,7 +54,9 @@ class PoseLandmarkerWrapper:
         return PoseLandmarker.create_from_options(options)
 
     def detect_async(self, mp_image, timestamp_ms: int) -> None:
+        """异步执行姿态检测"""
         return self._landmarker.detect_async(mp_image, timestamp_ms)
 
     def close(self) -> None:
+        """释放MediaPipe资源"""
         self._landmarker.close()

app/webrtc/frame_source.py

@@ -9,6 +9,7 @@ TARGET_HEIGHT = 720
 
 
 def validate_frame_size(image: np.ndarray, width: int = TARGET_WIDTH, height: int = TARGET_HEIGHT) -> None:
+    """验证视频帧尺寸是否与目标尺寸一致，不一致时记录警告"""
     h, w = image.shape[:2]
     if w != width or h != height:
         logger.warning("Unexpected frame size: {}x{}", w, h)

app/webrtc/peer_session.py

@@ -10,13 +10,15 @@ from loguru import logger
 from app.signaling.ice_parser import parse_ice
 from app.webrtc.video_receiver import VideoReceiver
 
-
 class PeerSession:
+    """WebRTC对等连接会话管理"""
+
     def __init__(self) -> None:
         self._pc = RTCPeerConnection()
         self._video_task: asyncio.Task | None = None
 
     async def handle(self, websocket) -> None:
+        """处理WebSocket信令交互与WebRTC连接建立"""
         self._setup_events()
 
         try:
@@ -47,6 +49,7 @@ class PeerSession:
             await self._cleanup()
 
     def _setup_events(self) -> None:
+        """注册ICE连接状态变化和视频轨道接收事件处理器"""
         @self._pc.on("track")
         async def on_track(track):
             logger.info(f"Track received: kind={track.kind}")
@@ -61,6 +64,7 @@ class PeerSession:
                 await self._pc.close()
 
     async def _cleanup(self) -> None:
+        """清理视频任务并关闭对等连接"""
         if self._video_task:
             self._video_task.cancel()
             try:

app/webrtc/video_receiver.py

@@ -13,6 +13,7 @@ from configs.load import config
 
 
 def _format_pose_debug(pose_result) -> str:
+    """格式化姿态检测结果用于调试日志输出"""
     metrics = pose_result.metrics
     if metrics is None:
         return "metrics=None"
@@ -24,12 +25,14 @@ def _format_pose_debug(pose_result) -> str:
         f"ll={metrics.left_leg_extended}, rl={metrics.right_leg_extended})"
     )
 
-
 class VideoReceiver:
+    """视频轨道接收与运动检测流水线"""
+
     def __init__(self, track) -> None:
         self._track = track
 
     async def run(self) -> None:
+        """持续接收视频帧并进行姿态检测、渲染和语音播报"""
         logger.info("Start receiving video frames, process_every_n={}", config.video.process_every_n_frames)
 
         frame_count = 0