fix(training): 修复 AI 跟练结束卡死，看不清时提示后退，加入开发版识别诊断

- 达到目标次数发生在识别回调里，同步关摄像头、销毁识别引擎会让 iOS 卡死：结算推迟到回调返回后，引擎延后销毁，停止后迟到的结果丢弃
- 补监听 addAnchors（与官方示例一致），首次识别到人、丢失后重现的结果不再丢掉
- 训练中连续 1.5 秒看不清时，屏幕和语音提示怎么站，而不是一声不吭不计数
- 开发版识别诊断：页面诊断面板；编译时设置 VITE_POSE_LOG_URL 可把识别数据实时发到电脑上的日志服务。发行版不生效

TUICallKit-Vue3/training/pages/components/pose-coach.scss

@@ -746,3 +746,24 @@ $ink-soft: #6b7a72;
     align-items: center;
     justify-content: center;
 }
+
+/* 开发版识别诊断面板：底部操作栏上方，不挡计数环和小窗，不拦截点击 */
+.diag {
+    position: absolute;
+    left: 16rpx;
+    right: 16rpx;
+    bottom: calc(270rpx + env(safe-area-inset-bottom));
+    z-index: 30;
+    padding: 10rpx 14rpx;
+    border-radius: 12rpx;
+    background: rgba(0, 0, 0, 0.62);
+    pointer-events: none;
+}
+
+.diag__text {
+    color: #a7f3d0;
+    font-size: 19rpx;
+    line-height: 1.45;
+    white-space: pre-wrap;
+    word-break: break-all;
+}

TUICallKit-Vue3/training/pages/pose-coach.vue

@@ -81,6 +81,11 @@
                 </view>
             </view>
 
+            <!-- 开发版真机排查：识别数据面板（只在摄像头识别模式显示，发行版不渲染） -->
+            <view v-if="IS_DEV && mode === 'vision'" class="diag">
+                <text class="diag__text">{{ diagText }}</text>
+            </view>
+
             <!-- 计数环 + 连击 -->
             <view v-if="hud.phase !== 'framing'" class="ring-slot" :style="{ top: pip.top + 'px' }">
                 <RepRing :count="hud.count" :target="target" :color="ex.color" :theme="theme" />
@@ -171,9 +176,9 @@ import AmountMeter from './components/amount-meter.vue'
 import PoseIntro from './components/pose-intro.vue'
 import PoseSummary from './components/pose-summary.vue'
 import { EXERCISES, bgmUrlOf, videoUrlOf } from '../pose/exercises'
-import { FRAMING_TIPS, type FramingIssue, type Pose } from '../pose/keypoints'
+import { FRAMING_TIPS, KP, isVisible, type FramingIssue, type Pose } from '../pose/keypoints'
 import { MOTIONS, MISTAKE_POSES, type MoveId, type Side } from '../pose/motions'
-import { tipTextsOf } from '../pose/counters'
+import { TRACK_MIN_SCORE, tipTextsOf } from '../pose/counters'
 import { TrainingSession, summarize, type SessionEvent, type SessionPhase, type SessionSummary } from '../pose/session'
 import { usePoseCamera } from '../pose/usePoseCamera'
 import { requestCameraPermission, type PermissionApi } from '../pose/cameraPermission'
@@ -181,6 +186,7 @@ import { useCoachVoice } from '../pose/useCoachVoice'
 import { useBgm } from '../pose/useBgm'
 import type { BgmState } from '../pose/bgm'
 import { appendHistory, uniStorage } from '../pose/history'
+import { remoteLogEnabled, rlog, rlogSession } from '../pose/remoteLog'
 
 const IS_DEV = process.env.NODE_ENV === 'development'
 const MIRROR_KEY = 'pose_coach_overlay_mirror'
@@ -236,6 +242,11 @@ let simTimer: ReturnType<typeof setInterval> | null = null
 let tipTimer: ReturnType<typeof setTimeout> | null = null
 let lastFramingVoice = 0
 let lastFramingIssue: FramingIssue = 'no_body'
+/** 训练中关键点看不清（算不出动作指标）从何时开始；持续一段时间就提示用户调整站位 */
+let blindSince = 0
+let lastBlindTip = 0
+const BLIND_TIP_AFTER_MS = 1500
+const BLIND_TIP_COOLDOWN_MS = 5000
 
 const videoUrl = computed(() => videoUrlOf(ex.value, IS_DEV))
 
@@ -293,6 +304,32 @@ const holdRingBg = computed(() => {
     const deg = Math.round(hud.holdProgress * 360)
     return `conic-gradient(#34d399 ${deg}deg, rgba(255,255,255,0.25) ${deg}deg)`
 })
+/** 诊断面板：识别引擎状态 → 原始数据 → 站位 / 阶段 / 幅度 / 次数，逐层看是哪一步断了 */
+const diagText = computed(() => {
+    const d = camera.diag.value
+    const e = d.events
+    return [
+        `识别 ${camera.status.value} ${camera.fps.value}次/秒 帧${frame.value.width}×${frame.value.height} 延迟${d.latencyMs}ms`,
+        `事件 add${e.add} upd${e.update} rm${e.remove} 超时${e.timeout} 错${e.error}`,
+        d.raw || '尚未识别到人',
+        `看清(≥${TRACK_MIN_SCORE}) 髋${seen(KP.L_HIP, KP.R_HIP)} 膝${seen(KP.L_KNEE, KP.R_KNEE)} 踝${seen(KP.L_ANKLE, KP.R_ANKLE)} 腕${seen(KP.L_WRIST, KP.R_WRIST)} 指标 ${metricText()}`,
+        `站位 ${hud.framingIssue} 阶段 ${hud.phase} 幅度 ${hud.liveAmount.toFixed(2)}/${goal.value.toFixed(2)} 次数 ${hud.count}`,
+    ].join('\n')
+})
+
+/** 一对左右关键点里看清了几个（按计数用的阈值） */
+function seen(...idx: number[]) {
+    const p = displayPose.value
+    return p ? idx.filter((i) => isVisible(p, i, TRACK_MIN_SCORE)).length : 0
+}
+
+/** 计数器最近一帧的原始指标；null 表示关键点看不清，这一帧被跳过 */
+function metricText() {
+    const m = session?.counter.metric
+    if (m === undefined) return '-'
+    return m === null ? '看不清(整帧跳过)' : m.toFixed(2)
+}
+
 const timeText = computed(() => {
     const s = Math.floor(hud.activeMs / 1000)
     return `${String(Math.floor(s / 60)).padStart(2, '0')}:${String(s % 60).padStart(2, '0')}`
@@ -462,6 +499,8 @@ function startStage(m: 'vision' | 'sim' | 'guided') {
     mode.value = m
     selfMain.value = false
     session = new TrainingSession(ex.value.id, target.value, { detectLost: m !== 'guided' })
+    rlogSession()
+    rlog('stage', { mode: m, move: ex.value.id, target: target.value })
     goal.value = session.counter.goal
     Object.assign(hud, { phase: 'framing', framingIssue: 'no_body', holdProgress: 0, count: 0, combo: 0, activeMs: 0, liveAmount: 0 })
     pop.key = 0
@@ -477,6 +516,7 @@ function startStage(m: 'vision' | 'sim' | 'guided') {
 }
 
 function onCameraReady() {
+    rlog('camera_ready', { mode: mode.value })
     if (mode.value !== 'vision') return
     camera.start()
 }
@@ -493,12 +533,14 @@ watch(
 )
 
 function onCameraError() {
+    rlog('camera_error')
     camera.onCameraError(null)
     fallbackToGuided('摄像头不可用，已切换为领练模式')
 }
 
 function fallbackToGuided(msg: string) {
     if (mode.value === 'guided') return
+    rlog('fallback_guided', { msg, status: camera.status.value, err: camera.errorText.value })
     camera.stop()
     stopSim()
     uni.showToast({ title: msg, icon: 'none', duration: 2500 })
@@ -510,6 +552,41 @@ function onPose(p: Pose | null) {
     displayPose.value = p
     if (!session) return
     handle(session.feed(p, Date.now()))
+    checkBlind()
+    if (remoteLogEnabled) logPose(p)
+}
+
+/** 训练中持续看不清（离太近、腿出画面等）时不会计数：提示用户怎么站，而不是让人干练不计数 */
+function checkBlind() {
+    if (!session || hud.phase !== 'training' || session.counter.metric !== null) {
+        blindSince = 0
+        return
+    }
+    const now = Date.now()
+    if (!blindSince) blindSince = now
+    if (now - blindSince < BLIND_TIP_AFTER_MS || now - lastBlindTip < BLIND_TIP_COOLDOWN_MS) return
+    lastBlindTip = now
+    const text = FRAMING_TIPS[hud.framingIssue === 'none' ? 'partial' : hud.framingIssue]
+    showTip(text, [])
+    voice.speak(text, 'high')
+    rlog('blind_tip', { issue: hud.framingIssue })
+}
+
+/** 远程日志：这一帧算到哪一步了（站位 → 阶段 → 指标 → 幅度 → 次数），以及关键点看清了几个 */
+function logPose(p: Pose | null) {
+    const m = session?.counter.metric
+    const key = [KP.L_HIP, KP.R_HIP, KP.L_KNEE, KP.R_KNEE, KP.L_ANKLE, KP.R_ANKLE]
+    const y = (a: number, b: number) => (p ? +(((p.points[a]?.y ?? 0) + (p.points[b]?.y ?? 0)) / 2).toFixed(3) : null)
+    rlog('pose', {
+        ph: hud.phase,
+        iss: hud.framingIssue,
+        m: m === null || m === undefined ? null : +m.toFixed(3),
+        amt: +hud.liveAmount.toFixed(2),
+        cnt: hud.count,
+        vis: `h${seen(KP.L_HIP, KP.R_HIP)}k${seen(KP.L_KNEE, KP.R_KNEE)}a${seen(KP.L_ANKLE, KP.R_ANKLE)}w${seen(KP.L_WRIST, KP.R_WRIST)}`,
+        sc: p ? +Math.min(...key.map((i) => p.scores[i] ?? 0)).toFixed(2) : null,
+        y: p ? { nose: +(p.points[KP.NOSE]?.y ?? 0).toFixed(3), hip: y(KP.L_HIP, KP.R_HIP), knee: y(KP.L_KNEE, KP.R_KNEE), ankle: y(KP.L_ANKLE, KP.R_ANKLE) } : null,
+    })
 }
 
 function handle(events: SessionEvent[]) {
@@ -537,6 +614,7 @@ function handle(events: SessionEvent[]) {
 }
 
 function onEvent(e: SessionEvent) {
+    rlog('ev', { ev: e })
     switch (e.type) {
         case 'phase':
             if (e.phase === 'countdown') voice.speak('准备', 'high')
@@ -544,7 +622,8 @@ function onEvent(e: SessionEvent) {
                 voice.speak('开始', 'high')
             }
             if (e.phase === 'lost') voice.speak('请回到画面中', 'high')
-            if (e.phase === 'done') finish()
+            // 达到目标次数通常发生在识别结果回调里：推迟到回调返回后再结算、关摄像头、切页面，避免在原生回调里拆掉自己
+            if (e.phase === 'done') setTimeout(finish, 0)
             break
         case 'countdown':
             voice.speak(String(e.n), 'high')
@@ -584,7 +663,7 @@ function shouldSpeakCount(n: number) {
 function voicePhrases() {
     const counts: string[] = []
     for (let i = 1; i <= target.value; i++) if (shouldSpeakCount(i)) counts.push(String(i))
-    const cues = ['准备', '开始', '3', '2', '1', '太棒了，完成训练', '请回到画面中', '请站到画面中间']
+    const cues = ['准备', '开始', '3', '2', '1', '太棒了，完成训练', '请回到画面中', '请站到画面中间', ...Object.values(FRAMING_TIPS)]
     return [...cues, ...counts, ...tipTextsOf(move.value)]
 }
 
@@ -646,6 +725,7 @@ function stopTimers() {
 // ───────── 暂停 / 结束 ─────────
 function onPause() {
     if (!session) return
+    rlog('pause', { phase: hud.phase })
     handle(session.pause())
 }
 
@@ -658,6 +738,7 @@ function onResume() {
 
 function finish() {
     if (!session || stage.value !== 'camera') return
+    rlog('finish', { count: hud.count, phase: hud.phase })
     // 只改状态、不派发 done 事件：done 的处理就是调用 finish，派发会重入，同一次训练记两条历史
     session.finish()
     const s = summarize(session, ex.value.netMet)
@@ -694,6 +775,7 @@ function onClose() {
 
 function toggleCoachMode() {
     coachMode.value = coachMode.value === 'demo' ? 'mirror' : 'demo'
+    rlog('coach_mode', { mode: coachMode.value })
     uni.showToast({ title: coachMode.value === 'demo' ? '跟练：跟着小甄的节奏' : '镜像：小甄模仿你的动作', icon: 'none' })
 }
 

TUICallKit-Vue3/training/pose/remoteLog.ts

@@ -0,0 +1,47 @@
+/**
+ * 开发版真机排查：把跟练的识别数据批量发到电脑上的日志服务，边练边看。
+ *
+ * 地址在编译时用环境变量 VITE_POSE_LOG_URL 指定（如 http://192.168.8.11:8787/log），不写进代码；
+ * 没设置或发行版时整个模块是空操作。需要项目关闭合法域名校验（manifest 里 urlCheck: false）。
+ */
+const LOG_URL: string = ((import.meta as any).env?.VITE_POSE_LOG_URL as string | undefined) || ''
+const FLUSH_MS = 1000
+/** 断网时最多攒这么多条，超出丢最旧的 */
+const MAX_QUEUE = 600
+
+export const remoteLogEnabled = Boolean(LOG_URL) && process.env.NODE_ENV === 'development'
+
+let queue: Record<string, unknown>[] = []
+let timer: ReturnType<typeof setTimeout> | null = null
+let session = ''
+let failWarned = false
+
+/** 开始一次新的跟练：之后的日志带上同一个会话编号 */
+export function rlogSession() {
+    session = String(Date.now())
+}
+
+export function rlog(type: string, data: Record<string, unknown> = {}) {
+    if (!remoteLogEnabled) return
+    queue.push({ t: Date.now(), type, ...data })
+    if (queue.length > MAX_QUEUE) queue = queue.slice(-MAX_QUEUE)
+    if (!timer) timer = setTimeout(flush, FLUSH_MS)
+}
+
+function flush() {
+    timer = null
+    if (!queue.length) return
+    const entries = queue
+    queue = []
+    uni.request({
+        url: LOG_URL,
+        method: 'POST',
+        data: { session, entries },
+        timeout: 3000,
+        fail: (e) => {
+            if (failWarned) return
+            failWarned = true
+            console.warn('[跟练日志] 发送失败，检查手机和电脑是否在同一网络、日志服务是否启动', LOG_URL, e)
+        },
+    })
+}

TUICallKit-Vue3/training/pose/usePoseCamera.ts

@@ -9,6 +9,7 @@
  */
 import { ref, shallowRef, onUnmounted } from 'vue'
 import { anchorToPose, smoothPose, type Pose } from './keypoints.ts'
+import { rlog } from './remoteLog.ts'
 
 export type CameraStatus = 'idle' | 'starting' | 'running' | 'unsupported' | 'denied' | 'error'
 
@@ -19,7 +20,23 @@ const DETECT_TIMEOUT_MS = 600
 /** 连续多久没检测到人，清空姿态 */
 const LOST_AFTER_MS = 800
 
+/** 诊断面板刷新间隔；console 摘要间隔 */
+const DIAG_REFRESH_MS = 500
+const DIAG_LOG_MS = 2000
+
 type FrameInfo = { width: number; height: number }
+type AnchorSource = 'add' | 'update' | 'remove' | 'timeout'
+
+/** 真机排查用：识别引擎的事件计数和最近一次识别到人的原始数据摘要（开发版跟练页显示） */
+export type PoseDiag = {
+    events: Record<AnchorSource | 'error', number>
+    /** detectBody 发出到收到结果的耗时 */
+    latencyMs: number
+    /** 最近一次识别到人的原始数据摘要 */
+    raw: string
+}
+
+const IS_DEV = process.env.NODE_ENV === 'development'
 
 export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
     const status = ref<CameraStatus>('idle')
@@ -28,6 +45,13 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
     const frame = ref<FrameInfo>({ width: 480, height: 640 })
     /** 实际检测帧率，调试用 */
     const fps = ref(0)
+    const diag = shallowRef<PoseDiag>(emptyDiag())
+    const events = { ...emptyDiag().events }
+    let latencyMs = 0
+    let lastRaw = ''
+    let firstAnchorLogged = false
+    let lastDiagAt = 0
+    let lastLogAt = 0
 
     let session: any = null
     let listener: any = null
@@ -52,12 +76,24 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
         }
     }
 
-    function handleAnchors(anchors: any[]) {
+    function handleAnchors(anchors: any[], source: AnchorSource) {
+        // 已经停止（训练结束、切到领练）后迟到的识别结果直接丢弃
+        if (!session) return
+        const now = Date.now()
+        if (pending && (source === 'add' || source === 'update')) latencyMs = now - lastSent
+        events[source] += 1
         clearPending()
         fpsCount += 1
-        const now = Date.now()
         // 画面里多人时取检测框最大的那个
         const best = (anchors || []).slice().sort((a, b) => area(b) - area(a))[0]
+        rlog('det', {
+            src: source,
+            lat: source === 'add' || source === 'update' ? latencyMs : undefined,
+            n: anchors?.length ?? 0,
+            // 原始坐标不是有效数字的点（画面外的点真机返回 NaN）
+            nan: best ? nanPoints(best) : undefined,
+        })
+        if (best) recordRaw(best)
         const next = best ? anchorToPose(best, sentFrame.width, sentFrame.height, now) : null
         if (next) {
             lastSeen = now
@@ -65,6 +101,32 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
         } else if (now - lastSeen > LOST_AFTER_MS) {
             emit(null)
         }
+        refreshDiag(now)
+    }
+
+    /** 记下原始 anchor 的摘要；第一次识别到人时把完整原始数据打到 console，便于核对字段格式 */
+    function recordRaw(anchor: any) {
+        if (IS_DEV && !firstAnchorLogged) {
+            firstAnchorLogged = true
+            // anchor 是原生对象，字段不可枚举，直接 JSON.stringify 得到 {}；逐个取出再序列化，NaN 显式写出来
+            const json = JSON.stringify(plainAnchor(anchor))
+            console.log('[跟练诊断] 首个原始 anchor', `帧 ${sentFrame.width}x${sentFrame.height}`, json.slice(0, 1500))
+            rlog('first_anchor', { frame: `${sentFrame.width}x${sentFrame.height}`, anchor: json.slice(0, 4000) })
+        }
+        lastRaw = summarizeAnchor(anchor)
+    }
+
+    function refreshDiag(now: number) {
+        if (now - lastDiagAt < DIAG_REFRESH_MS) return
+        lastDiagAt = now
+        diag.value = { events: { ...events }, latencyMs, raw: lastRaw }
+        if (IS_DEV && now - lastLogAt >= DIAG_LOG_MS) {
+            lastLogAt = now
+            const e = events
+            console.log(
+                `[跟练诊断] 帧 ${frame.value.width}x${frame.value.height} 延迟 ${latencyMs}ms 事件 add${e.add} upd${e.update} rm${e.remove} 超时${e.timeout} 错${e.error} | ${lastRaw || '尚未识别到人'}`,
+            )
+        }
     }
 
     function area(a: any) {
@@ -77,6 +139,12 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
     function start() {
         if (status.value === 'running' || status.value === 'starting') return
         status.value = 'starting'
+        Object.assign(events, emptyDiag().events)
+        latencyMs = 0
+        lastRaw = ''
+        firstAnchorLogged = false
+        diag.value = emptyDiag()
+        rlog('camera_start', deviceInfo())
         // #ifdef MP-WEIXIN
         startVisionKit()
         // #endif
@@ -90,22 +158,28 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
             const w: any = wx
             if (typeof w.createVKSession !== 'function' || (w.isVKSupport && !w.isVKSupport('v1'))) {
                 status.value = 'unsupported'
+                rlog('vk_unsupported', { hasCreate: typeof w.createVKSession === 'function' })
                 return
             }
             session = w.createVKSession({ track: { body: { mode: 2 } }, version: 'v1' })
-            session.on('updateAnchors', (anchors: any[]) => handleAnchors(anchors))
-            session.on('removeAnchors', () => handleAnchors([]))
+            // 连续帧（sourceType 0）会跟踪人体：首次识别到人、丢失后重新出现走 addAnchors，之后每帧走 updateAnchors（同官方示例）
+            session.on('addAnchors', (anchors: any[]) => handleAnchors(anchors, 'add'))
+            session.on('updateAnchors', (anchors: any[]) => handleAnchors(anchors, 'update'))
+            session.on('removeAnchors', () => handleAnchors([], 'remove'))
             session.start((err: any) => {
                 if (err) {
                     status.value = 'unsupported'
                     errorText.value = String(err?.errMsg || err)
+                    rlog('vk_start_error', { err: errorText.value })
                     return
                 }
+                rlog('vk_started')
                 startFrames()
             })
         } catch (e: any) {
             status.value = 'unsupported'
             errorText.value = String(e?.message || e)
+            rlog('vk_exception', { err: errorText.value })
         }
     }
 
@@ -113,6 +187,7 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
         const cam: any = uni.createCameraContext()
         if (!cam?.onCameraFrame) {
             status.value = 'unsupported'
+            rlog('no_camera_frame_api')
             return
         }
         listener = cam.onCameraFrame((f: { data: ArrayBuffer; width: number; height: number }) => {
@@ -120,11 +195,12 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
             if (pending || now - lastSent < DETECT_INTERVAL_MS || !session) return
             if (frame.value.width !== f.width || frame.value.height !== f.height) {
                 frame.value = { width: f.width, height: f.height }
+                rlog('frame_size', { w: f.width, h: f.height, bytes: f.data?.byteLength })
             }
             pending = true
             lastSent = now
             sentFrame = { width: f.width, height: f.height }
-            pendingTimer = setTimeout(() => handleAnchors([]), DETECT_TIMEOUT_MS)
+            pendingTimer = setTimeout(() => handleAnchors([], 'timeout'), DETECT_TIMEOUT_MS)
             try {
                 session.detectBody({
                     frameBuffer: f.data,
@@ -135,12 +211,16 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
                     sourceType: 0,
                 })
             } catch (e) {
+                events.error += 1
+                if (IS_DEV) console.warn('[跟练诊断] detectBody 异常', e)
+                rlog('detect_err', { err: String((e as any)?.message || e) })
                 clearPending()
             }
         })
         listener.start({
             success: () => {
                 status.value = 'running'
+                rlog('frames_started')
                 fpsTimer = setInterval(() => {
                     fps.value = fpsCount
                     fpsCount = 0
@@ -149,6 +229,7 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
             fail: (e: any) => {
                 status.value = 'error'
                 errorText.value = String(e?.errMsg || e)
+                rlog('frames_fail', { err: errorText.value })
             },
         })
     }
@@ -159,11 +240,17 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
             listener?.stop?.()
         } catch (e) {}
         listener = null
-        try {
-            session?.stop?.()
-            session?.destroy?.()
-        } catch (e) {}
+        const oldSession = session
         session = null
+        rlog('camera_stop')
+        // 停止可能发生在识别引擎自己的回调里（第 N 次计数 → 结束 → 关摄像头）：在回调里同步销毁引擎，iOS 真机会卡死。
+        // 先断开引用（之后迟到的回调全部丢弃），等当前回调返回后再销毁
+        setTimeout(() => {
+            try {
+                oldSession?.stop?.()
+                oldSession?.destroy?.()
+            } catch (e) {}
+        }, 0)
         if (fpsTimer) clearInterval(fpsTimer)
         fpsTimer = null
         if (status.value === 'running' || status.value === 'starting') status.value = 'idle'
@@ -178,5 +265,59 @@ export function usePoseCamera(onPose?: (pose: Pose | null) => void) {
 
     onUnmounted(stop)
 
-    return { status, errorText, pose, frame, fps, start, stop, onCameraError }
+    return { status, errorText, pose, frame, fps, diag, start, stop, onCameraError }
+}
+
+const num = (v: unknown) => (typeof v === 'number' ? (Number.isFinite(v) ? +v.toFixed(4) : String(v)) : v)
+const rawXY = (p: any) => (Array.isArray(p) ? [p[0], p[1]] : [p?.x, p?.y])
+
+/** 原始坐标不是有效数字的点的序号，如 "13,14,15,16" */
+function nanPoints(anchor: any): string {
+    const pts: any[] = Array.isArray(anchor?.points) ? anchor.points : []
+    return pts
+        .map((p, i) => (rawXY(p).every((v) => typeof v === 'number' && Number.isFinite(v)) ? -1 : i))
+        .filter((i) => i >= 0)
+        .join(',')
+}
+
+function plainAnchor(a: any) {
+    return {
+        keys: Object.keys(a ?? {}),
+        score: num(a?.score),
+        origin: a?.origin ? [num(a.origin.x), num(a.origin.y)] : a?.origin,
+        size: a?.size ? [num(a.size.width), num(a.size.height)] : a?.size,
+        points: Array.isArray(a?.points) ? a.points.map((p: any) => rawXY(p).map(num)) : typeof a?.points,
+        confidence: Array.isArray(a?.confidence) ? a.confidence.map(num) : typeof a?.confidence,
+    }
+}
+
+/** 机型与微信版本，排查机型差异用 */
+function deviceInfo() {
+    try {
+        const s: any = uni.getSystemInfoSync()
+        return { brand: s.brand, model: s.model, system: s.system, platform: s.platform, wx: s.version, sdk: s.SDKVersion }
+    } catch (e) {
+        return {}
+    }
+}
+
+function emptyDiag(): PoseDiag {
+    return { events: { add: 0, update: 0, remove: 0, timeout: 0, error: 0 }, latencyMs: 0, raw: '' }
+}
+
+const f2 = (v: unknown) => (typeof v === 'number' ? v.toFixed(2) : String(v))
+
+/** 原始 anchor 摘要：点数、坐标是比例还是像素、置信度范围，以及鼻子 / 髋 / 踝的原始坐标 */
+function summarizeAnchor(a: any): string {
+    const pts: any[] = Array.isArray(a?.points) ? a.points : []
+    const xy = (i: number) => {
+        const p = pts[i]
+        if (!p) return '-'
+        return Array.isArray(p) ? `${f2(p[0])},${f2(p[1])}` : `${f2(p.x)},${f2(p.y)}`
+    }
+    const flat = pts.flatMap((p) => (Array.isArray(p) ? p : [p?.x, p?.y])).filter((v) => typeof v === 'number')
+    const unit = flat.some((v) => v > 1.5) ? '像素' : '比例'
+    const conf: number[] = Array.isArray(a?.confidence) ? a.confidence : []
+    const confText = conf.length ? `${f2(Math.min(...conf))}~${f2(Math.max(...conf))}` : '无'
+    return `${pts.length}点 ${unit} 框分${f2(a?.score)} 点置信${confText} 鼻${xy(0)} 左髋${xy(11)} 右髋${xy(12)} 左踝${xy(15)} 右踝${xy(16)}`
 }