feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation

Major changes:
- New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind
- 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理
- Data catalog with charts (DMS/ADAS/Lane 3-tab view)
- Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance
- Audit enhancements: batch operations, rejection categories, Feishu notifications
- Operation audit log (操作日志)
- World model simulation studio (仿真工坊)
- Dataset version management with snapshots and diff
- ADAS 7-class dataset integration (138K images organized + compressed)
- User management with Feishu integration and pagination
- CRUD/search/filter on all pages, card layout redesign
- PIL-optimized image overlay rendering
- Auto-snapshot on build, in_review workflow stage
- Removed embedded algorithm code (now in workspace)

.dockerignore

@@ -3,7 +3,6 @@
 **/*.pyc
 **/.pytest_cache
 **/node_modules
-platform/web/dist
 **/runs
 **/log
 **/tmp

.env.example

@@ -2,9 +2,20 @@
 
 # 平台端口
 AS_PLATFORM_PORT=8787
-AS_DB_PORT=5432
+# 宿主机映射端口（与旧 active-safety 的 as-postgres:5432 / as-redis:6379 冲突时可改为 5433 / 6380）
-AS_REDIS_PORT=6379
+AS_DB_PORT=5433
+AS_REDIS_PORT=6380
 AS_WEB_DEV_PORT=5173
 
 # 外部 workspace（含 DMS/Lane 大文件数据时填写绝对路径；无则留默认占位目录）
 # AS_WORKSPACE_ROOT=/path/to/DATA/workspace
+
+# 车队地图 / T-Box 演示
+AS_FLEET_MAP_ENABLED=1
+AS_FLEET_MOCK_SEED=1
+AS_FLEET_MOCK_SIMULATE=1
+AS_FLEET_SIM_INTERVAL_SEC=8
+AS_TBOX_INGEST_TOKEN=hsap-demo-tbox-token
+# AS_AMAP_KEY=
+# 车队地图底图：gaode（国内推荐）| osm
+AS_MAP_TILE_PROVIDER=gaode

.gitignore

@@ -13,10 +13,6 @@ build/
 venv/
 
 # Node / frontend
-platform/web/node_modules/
-platform/web/dist/
-platform/web/tsconfig.tsbuildinfo
-
 # Secrets & local env
 .env
 manifests/feishu.env

CLAUDE.md

@@ -0,0 +1,506 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code when working with code in this repository.
+
+## Project Overview
+
+**HSAP** (Huaxu Sentinel Active Safety Platform / 华胥 Sentinel 主动安全平台) is a truck active safety algorithm iteration platform covering DMS (Driver Monitoring), Lane detection, and ADAS perception tasks.
+
+It is NOT a training framework — it is a **platform** that orchestrates collaboration workflows: data ingestion → labeling → audit → training → promotion, with full traceability and governance.
+
+## Architecture: Three-Layer Decoupling
+
+The top-level directory is strictly separated into three layers:
+
+```
+HSAP/
+├── platform/          # Orchestration layer (API, auth, audit, jobs, web UI)
+├── algorithms/        # Algorithm code layer (YOLO, UFLD adapters + registries)
+├── datasets/          # Data layer (packs, inbox, sources, labeling configs)
+├── scripts/           # Operational scripts (init, smoke tests, sync, worker)
+├── docs/              # Documentation (20+ md files covering all aspects)
+├── lake/              # Data lake staging area
+├── reports/           # Reports, CSVs, figures
+├── manifests/         # Runtime configs (feishu.env, DB, job logs, catalog cache)
+├── as.py              # CLI entry point for workflow commands
+├── workflow.registry.yaml  # Central registry: projects, packs, automation rules
+├── docker-compose.yml      # PostgreSQL + Redis + platform + worker + optional minio
+├── Dockerfile              # Python 3.11-slim, FastAPI on port 8787
+└── Makefile                # up/down/dev/logs/build/ps/health shortcuts
+```
+
+### Layer Responsibilities
+
+| Layer | Purpose | Key Files |
+|-------|---------|-----------|
+| `platform/as_platform/` | FastAPI backend: API routes, auth (Feishu SSO + JWT), job queue, labeling service, data lake ingest, fleet map, DB models | `api/server.py`, `config.py`, `sdk.py` |
+| `algorithms/` | Algorithm adapters: DMS YOLO and Lane UFLD, each with an `adapter.py` and metadata | `registry.yaml` for algorithm registration |
+| `datasets/` | Dataset scaffolds: DMS packs (YAML registry), Lane packs (JSON registry), labeling configs | `dms/data_packs.yaml`, `lane/datasets_registry.json` |
+
+## Key Design Decisions
+
+### 1. Platform orchestrates, does NOT implement training
+Training is routed through adapters (`algorithms/*/adapter.py`) and the job runner (`platform/as_platform/jobs/runner.py`). Adding a new task type only requires a new adapter + registry entry.
+
+### 2. Audit-first governance
+All write operations (build/train/promote/register) go through an audit queue by default. This ensures every model-affecting action is reviewable and traceable.
+
+### 3. Dual execution modes
+- **`thread`**: In-process thread execution (local dev, no Redis needed). Set via `AS_JOB_EXECUTOR=thread`.
+- **`worker`**: Redis-backed async execution (Docker/production). Set via `AS_JOB_EXECUTOR=worker`. Worker runs `scripts/worker.py`.
+
+### 4. Database flexibility
+- Docker: PostgreSQL 16 (auto-configured)
+- Local: Auto-falls back to SQLite (`manifests/platform.db`) when PostgreSQL is unavailable
+
+### 5. Authentication
+- Feishu (飞书) OAuth2 SSO with JWT tokens
+- Dev mode: `AS_DEV_AUTH=true` bypasses Feishu login
+- RBAC roles: `admin`, `reviewer`, `engineer`, `labeler`, `viewer`
+
+## Platform Subsystems (`platform/as_platform/`)
+
+```
+as_platform/
+├── api/           # FastAPI routes: auth, labeling, delivery, fleet, Feishu callbacks
+├── auth/          # Feishu OAuth, JWT tokens, user management, RBAC deps
+├── db/            # SQLAlchemy engine, models (User, Job, Campaign, etc.), init
+├── data/          # Data lake core: ingest pipelines (DMS COCO/YOLO, Lane lines/mask), batch staging, catalog cache
+│   └── ingest/    # Ingest adapters: dms_coco, dms_yolo, dms_inbox_raw, lane_lines, lane_mask
+├── labeling/      # Labeling service: annotate, batch staging, vendor import, scope, progress, locks
+├── audit/         # Audit queue and preview logic
+├── jobs/          # Job queue (Redis List or in-memory), runner, Feishu Bitable sync
+├── deliveries/    # Delivery/model handoff service
+├── fleet/         # Fleet map: GPS tracking, T-Box ingest, mock data seeding
+├── training/      # Training service orchestration
+├── agents/        # Agent graphs: ingest_flow, labeling_flow, train_promote_flow
+│   └── graphs/    # Workflow graph definitions
+├── integrations/  # Third-party: Feishu Bitable, Feishu notify, delivery ingest
+├── redis/         # Redis pub/sub bus
+├── config.py      # Central config from env vars (AS_* prefix)
+└── sdk.py         # Python SDK for platform operations
+```
+
+## CLI Usage (`as.py`)
+
+```bash
+python as.py status                    # Show workspace and active packs
+python as.py pending                   # Show pending audit items
+python as.py add dms dam --src ...     # Register a DMS batch
+python as.py build dms dam             # Build dataset from active packs
+python as.py train dms dam --track local     # Train locally
+python as.py train dms dam --track platform  # Train via platform (requires audit)
+```
+
+## Workflow Registry (`workflow.registry.yaml`)
+
+Central configuration for:
+- **Projects**: `dms` (DMS YOLO) and `lane` (Lane UFLD), each with root paths, registries, active packs
+- **Platform settings**: batch metadata schema, drop zones for inbox/sources, training tracks, agent graphs
+- **Automation rules**: eval-before-promote requirement, minimum delta thresholds, baseline metrics
+
+## Docker Services
+
+| Service | Port | Description |
+|---------|------|-------------|
+| platform | 8787 | FastAPI + static web UI |
+| postgres | 5432 (host mapped to 5433) | PostgreSQL 16 |
+| redis | 6379 (host mapped to 6380) | Redis 7 |
+| worker | - | Async job executor (same image, different command) |
+| minio | 9000/9001 | Optional S3-compatible staging (profile: minio) |
+
+## Build & Run Commands
+
+```bash
+# Quick start (Docker)
+bash scripts/init_after_clone.sh   # Generate .env / feishu.env
+bash scripts/dev_up.sh             # Or: make up
+
+# Local dev (no Docker for platform)
+pip install -r requirements.txt
+bash scripts/run_local.sh
+
+# Infrastructure only (Docker) + local platform
+docker compose up -d postgres redis
+bash scripts/run_local.sh
+
+# Utilities
+make logs      # platform + worker logs
+make down      # stop all
+make dev       # with Vite hot reload on :5173
+make health    # check API health
+```
+
+## Key Environment Variables
+
+| Variable | Default | Purpose |
+|----------|---------|---------|
+| `AS_PLATFORM_PORT` | 8787 | Platform API port |
+| `AS_DB_HOST/PORT/USER/PASSWORD/NAME` | - | PostgreSQL connection |
+| `AS_REDIS_URL` | - | Redis connection URL |
+| `AS_JOB_EXECUTOR` | `thread` | `thread` or `worker` |
+| `AS_DEV_AUTH` | `false` | Bypass Feishu auth in dev |
+| `AS_JWT_SECRET` | - | JWT signing secret |
+| `AS_WORKSPACE_ROOT` | - | External workspace path for large files |
+| `AS_FLEET_MAP_ENABLED` | `1` | Enable fleet map APIs |
+| `AS_FLEET_MOCK_SEED` | `1` | Seed demo vehicles on first start |
+
+## Important Conventions
+
+1. **Never commit**: `.env`, `feishu.env`, `node_modules`, `*.pt` (model weights), images/videos
+2. **Python path**: Platform code runs with `PYTHONPATH=platform` from repo root
+3. **Package name**: The Python package is `as_platform` (historical name preserved)
+4. **Web UI**: React/Vite frontend sources are external (in workspace), built via `scripts/build_hsap_ls_ui.sh`
+5. **Large files**: Images, videos, model weights live in external workspace, mounted at `/data/workspace` in Docker
+
+## Documentation Index
+
+Key docs in `docs/`:
+- `DEVELOPMENT_GUIDE.md` — Architecture, conventions, design decisions
+- `DEVELOPMENT_ROADMAP.md` — Q2 2026 roadmap with phased milestones
+- `DATA_LAKE_CHECKLIST.md` — Data lake operations checklist
+- `LABELING_SOP.md` — Labeling standard operating procedure
+- `FLEET_MAP.md` — Fleet map / T-Box GPS tracking
+- `FEISHU_BITABLE_OPS.md` — Feishu Bitable integration operations
+- `BATCH_DELIVERY_OPS.md` — Batch delivery operations
+- `LANE_LABELING_PLAN.md` — Lane labeling plan
+- `MINIO_STAGING.md` — S3-compatible staging setup
+- `PILOT_BATCH.md` — Pilot batch procedures
+- `GIT_PUSH.md` — Git push checklist
+
+## Module Navigation (4-Module Architecture)
+
+The frontend (`platform/web/`) is organized into 4 decoupled modules, each with its own tab sub-navigation:
+
+| Module | Route Prefix | API Prefix | Sub-pages |
+|--------|-------------|-----------|-----------|
+| **数据送标** (Labeling) | `/labeling/*` | `/api/v1/labeling/*` | 数据上载、送标工作台、标注进度、导出与入库、批次台账、数据目录 |
+| **模型管理** (Models) | `/models/*` | `/api/v1/models/*` | 模型概览、训练提交、训练记录、评估管理、模型晋级 |
+| **车队管理** (Fleet) | `/fleet/*` | `/api/v1/fleet/*` | 车队总览、车辆管理、实时地图、行程记录、T-Box配置 |
+| **系统管理** (System) | `/system/*` | `/api/v1/system/*` | 审核队列、任务监控、执行日志、用户管理 |
+
+**Key files:**
+- `platform/web/src/app/Sidebar.tsx` — Collapsible accordion sidebar with permission-gated module groups
+- `platform/web/src/app/MainShell.tsx` — Main layout with sidebar + content area + legacy redirects
+- `platform/web/src/modules/{labeling,models,fleet,system}/*Shell.tsx` — Module shells with tab sub-navigation
+- `platform/as_platform/api/models_routes.py` — `/api/v1/models/*` (model lifecycle APIs)
+- `platform/as_platform/api/system_routes.py` — `/api/v1/system/*` (audit, jobs, traces, users APIs)
+
+**Legacy route redirects** (old → new):
+- `/deliveries` → `/labeling/deliveries`
+- `/catalog` → `/labeling/catalog`
+- `/audit` → `/system/audit`
+- `/jobs` → `/system/jobs`
+- `/training` → `/models/training/records`
+- `/labeling/ml` → `/models/overview`
+
+## Technology Stack
+
+- **Backend**: Python 3.11, FastAPI, SQLAlchemy 2.0, Uvicorn
+- **Frontend**: React 18 + TypeScript + Vite + Tailwind CSS (`platform/web/`)
+- **Database**: PostgreSQL 16 (production), SQLite (local fallback)
+- **Queue**: Redis (List-based job queue + Pub/Sub)
+- **Auth**: Feishu OAuth2 + JWT (python-jose)
+- **Container**: Docker Compose v2
+- **Algorithms**: YOLOv6 (DMS), UFLD (Lane detection)
+
+## 开发计划 — 缺失功能 Todo
+
+### P0 · 首页仪表盘 (1天)
+- [ ] 新建 `/` 路由仪表盘页，替代当前直接跳转批次台账
+- [ ] 数据流水线 KPI 卡片：各阶段批次数（待送标/标中/待入库/已入库）
+- [ ] 模型健康卡片：最新 mAP、训练中任务数、生产模型版本
+- [ ] 审核待办卡片：pending 审核数、今日处理量
+- [ ] 车队实时卡片：在线车辆数、活跃行程数
+- [ ] 最近活动时间线（最近登记/审核/训练事件）
+
+### P0 · 飞书审核通知 (0.5天)
+- [ ] 审核提交时 → 通知审核员群："{user} 提交了 {action}，请审核"
+- [ ] 审核通过/驳回时 → 通知提审人："你的 {action} 已{通过/驳回}"
+- [ ] 复用已有 `integrations/feishu_notify.py`，接入 `audit/queue.py`
+- [ ] 环境变量 `FEISHU_LABELING_CHAT_ID` 控制通知目标群
+
+### P1 · 入库基础质检 (1天)
+- [ ] 扫描入库时增加基础质量检测：
+  - 图片可读性（损坏/全黑/全白检测）
+  - 分辨率分布（中位数/最小/最大）
+  - 标注文件格式正确性（YOLO 格式校验）
+  - 标注框越界/零宽高检测
+- [ ] 质检结果在扫描面板展示（通过/警告/拒绝）
+- [ ] 拒绝的批次不允许登记，需人工处理
+
+### P1 · 操作审计日志 (0.5天) — 详细设计
+
+#### DB 设计
+- [ ] A1. 新增 `OperationLog` 表 (SQLAlchemy model)
+  - `id` (int, PK, auto)
+  - `timestamp` (datetime, 操作时间)
+  - `user_id` (int, FK → users.id, nullable, 操作人)
+  - `user_name` (str, 操作人姓名冗余)
+  - `category` (str, 操作分类: auth/data/labeling/audit/training/system)
+  - `action` (str, 具体操作: login/logout/register_batch/open_campaign/submit_approval/approve/reject/set_roles/create_snapshot/build_dms/train_dms 等)
+  - `target_type` (str, 操作对象类型: user/batch/campaign/approval/job/snapshot/role)
+  - `target_id` (str, 操作对象 ID)
+  - `summary` (str, 一行摘要，如 "登记批次 ddaw/20260601_pilot → raw_pool")
+  - `detail_json` (text, 完整上下文 JSON，可选)
+  - `ip_address` (str, 请求来源 IP，可选)
+- [ ] A2. 自动建表 (`Base.metadata.create_all` + `_ensure_*_columns`)
+- [ ] A3. 定期清理：保留 90 天，超过的自动归档/删除
+
+#### 后端埋点
+- [ ] B1. 新增 `audit_log.py` 工具模块，提供 `log_op(db, **kwargs)` 便捷函数
+- [ ] B2. 在以下关键操作处插入日志记录：
+
+| 分类 | 操作 | 文件位置 |
+|------|------|---------|
+| auth | login (dev/feishu) | `auth_routes.py` |
+| auth | logout | (前端触发，可选) |
+| data | register_batch | `server.py` api_register_batch |
+| data | scan_inbox | `server.py` (只记录登记动作) |
+| labeling | open_campaign | `labeling_routes.py` |
+| labeling | submit_campaign | `labeling_routes.py` |
+| labeling | labeling_export | `labeling_routes.py` |
+| labeling | import_vendor | `labeling_routes.py` |
+| audit | submit_approval | `queue.py` |
+| audit | approve | `queue.py` |
+| audit | reject | `queue.py` |
+| training | create_training | `server.py` / `models_routes.py` |
+| system | set_user_roles | `auth_routes.py` |
+| system | sync_feishu_users | `system_routes.py` |
+| data | create_snapshot | `models_routes.py` |
+| delivery | create/submit/delete | `delivery_routes.py` |
+
+- [ ] B3. 所有日志记录使用 `threading.Thread(daemon=True)` 异步写入，不阻塞主流程
+
+#### 后端 API
+- [ ] C1. `GET /api/v1/system/audit-log` — 查询日志列表
+  - 参数: `user_id`, `category`, `action`, `target_type`, `search`(模糊搜索 summary), `offset`, `limit`
+  - 返回: `{items: [...], total: N}`
+  - 权限: `admin:users` 或 `*`
+- [ ] C2. `GET /api/v1/system/audit-log/stats` — 统计摘要
+  - 返回: `{today_count, top_users, top_actions, by_category}`
+
+#### 前端页面
+- [ ] D1. 系统管理 → 新增"操作日志"Tab
+  - 时间线列表视图（倒序），每行显示：时间、用户头像+姓名、分类Badge、操作摘要
+  - 筛选栏：按用户、分类、操作类型、时间范围
+  - 点击展开查看 detail JSON
+  - 分页
+- [ ] D2. 仪表盘增加"最近操作"卡片（可选，后做）
+
+### P2 · 标注质量抽检 (1.5天)
+- [ ] 标注提交后随机抽取 N 张（可配置比例），进入抽检队列
+- [ ] 抽检页面：并排显示图片+标注框，通过/不通过
+- [ ] 不通过 → 退回标注员重标
+- [ ] 统计抽检通过率、各标注员准确率
+
+### P2 · 模型预标（需要模型）(2天)
+- [ ] 选已有模型 → 对新批次跑推理 → 生成预标注
+- [ ] 标注员在预标基础上修正，而非从零开始
+- [ ] 记录预标模型版本，关联到后续训练
+
+### P3 · 模型部署追踪（需要生产环境）
+- [ ] 模型版本状态：experiment → candidate → production → retired
+- [ ] 部署历史：何时上线、运行多久、何时下线
+- [ ] 线上推理效果监控（回传误检/漏检统计）
+
+### P3 · 采集任务管理（需要车队运营）
+- [ ] 创建采集任务：指定场景/路线/时间段
+- [ ] 关联车队车辆：指派车辆执行采集
+- [ ] 数据回传状态追踪：已采集/已传输/已入库
+
+---
+
+## 当前完成状态
+
+| 模块 | 页面 | 状态 |
+|------|------|------|
+| 数据送标 | 送标工作台 (扫描入库) | ✅ |
+| 数据送标 | 标注进度 (Campaigns) | ✅ |
+| 数据送标 | 导出与入库 (供应商回传) | ✅ |
+| 数据送标 | 批次台账 (Deliveries) | ✅ |
+| 数据送标 | 数据目录 (可视化) | ✅ |
+| 模型管理 | 模型概览 (KPI卡片) | ✅ |
+| 模型管理 | 数据集版本 (自动快照+diff) | ✅ |
+| 模型管理 | 训练提交 (表单校验) | ✅ |
+| 模型管理 | 训练记录 (分页+展开详情) | ✅ |
+| 模型管理 | 评估管理 (mAP对比图) | ✅ |
+| 模型管理 | 模型晋级 (版本选择+历史) | ✅ |
+| 车队管理 | 总览/车辆/地图/行程/T-Box | ✅ |
+| 系统管理 | 审核队列 (批量操作+驳回分类) | ✅ |
+| 系统管理 | 任务监控 (自动刷新) | ✅ |
+| 系统管理 | 执行日志 (Trace查看) | ✅ |
+| 系统管理 | 用户管理 (飞书信息+分页) | ✅ |
+| 🆕 P0 | 首页仪表盘 | ❌ |
+| 🆕 P0 | 飞书审核通知 | ❌ |
+| 🆕 P1 | 入库基础质检 | ❌ |
+| 🆕 P1 | 操作审计日志 | ❌ |
+
+---
+
+## 新增架构：世界模型仿真 + 视频预处理管线
+
+### 一、整体数据闭环（完整架构）
+
+```
+                        ┌──────────────────────────────┐
+                        │      T-Box / 采集车 GPS       │
+                        │  多帧视频流 (连续帧)           │
+                        └──────────────┬───────────────┘
+                                       │
+                                       ▼
+┌──────────────────────────────────────────────────────────────┐
+│              视频预处理管线 (Preprocess Pipeline)              │
+│                                                              │
+│  ① 去噪 (Denoise)    ② 去重 (Dedup)    ③ 异常过滤 (Anomaly) │
+│  光流/像素级去噪       SSIM/感知哈希      全黑/模糊/过曝检测   │
+│       │                    │                    │            │
+│       └────────────────────┴────────────────────┘            │
+│                            │                                  │
+│                      ④ 关键帧提取                              │
+│                   场景切换/间隔采样                             │
+│                            │                                  │
+│                      ⑤ 质量评分                               │
+│                  每帧 quality_score 0-100                      │
+└────────────────────────────┬─────────────────────────────────┘
+                             │
+                             ▼
+                    ┌─────────────────┐
+                    │  扫描入库/登记    │
+                    │  stage: raw_pool │
+                    └────────┬────────┘
+                             │
+              ┌──────────────┼──────────────┐
+              │              │              │
+              ▼              ▼              ▼
+        真实数据标注    质检审核通过    仿真数据生成
+              │              │              │
+              └──────────────┼──────────────┘
+                             │
+                             ▼
+                    ┌─────────────────┐
+                    │  build 入库      │
+                    │  自动版本快照     │
+                    └────────┬────────┘
+                             │
+                             ▼
+                    ┌─────────────────┐
+                    │  模型训练/评估    │
+                    └────────┬────────┘
+                             │
+                    ┌────────┴────────┐
+                    │ 评估反馈 → 数据缺口│
+                    │ mAP低 → 仿真补数据 │
+                    └─────────────────┘
+```
+
+### 二、视频预处理管线设计
+
+#### 2.1 数据模型
+```
+预处理Job:
+  id, source_path, status, created_at
+  params: {denoise_method, dedup_threshold, anomaly_filters, keyframe_interval}
+  result: {
+    input_frames, output_frames, removed_duplicates,
+    removed_anomalies, quality_distribution, processing_time
+  }
+```
+
+#### 2.2 去噪 (Denoise)
+| 方法 | 适用场景 | 计算量 |
+|------|---------|--------|
+| `fast_nonlocal_means` | 夜间/低光图像 | 中 |
+| `bilateral_filter` | 保留边缘的平滑 | 低 |
+| `temporal_median` | 连续帧时序去噪 | 高 |
+| `none` | 光线充足的日间 | 无 |
+
+#### 2.3 去重 (Dedup)
+| 方法 | 阈值 | 说明 |
+|------|------|------|
+| `ssim` | 0.95 | 结构相似度 > 0.95 视为重复 |
+| `phash` | hamming ≤ 5 | 感知哈希距离 ≤ 5 视为重复 |
+| `histogram` | correlation > 0.98 | 直方图相关 > 0.98 视为重复 |
+
+#### 2.4 异常过滤 (Anomaly)
+| 检测项 | 阈值 | 动作 |
+|--------|------|------|
+| 全黑图 | mean_pixel < 5 | 丢弃 |
+| 全白图 | mean_pixel > 250 | 丢弃 |
+| 模糊图 | Laplacian variance < 100 | 丢弃 |
+| 过曝 | overexposed_ratio > 0.4 | 丢弃 |
+| 遮挡 | black_border_ratio > 0.3 | 标记 |
+
+#### 2.5 关键帧提取策略
+| 策略 | 适用场景 |
+|------|---------|
+| `fixed_interval` | 等间隔采样，每 N 帧取 1 帧 |
+| `scene_change` | 检测场景切换时抽取 |
+| `motion_peak` | 运动幅度最大帧（最有信息量） |
+| `quality_top` | 取质量分最高的 K% |
+
+### 三、API 设计
+
+```
+# 视频预处理
+POST   /api/v1/preprocess/analyze        # 分析视频（不解码全量，采样统计）
+POST   /api/v1/preprocess/run            # 执行预处理（异步 Job）
+GET    /api/v1/preprocess/jobs           # 预处理任务列表
+GET    /api/v1/preprocess/jobs/{id}      # 任务详情 + 统计
+GET    /api/v1/preprocess/jobs/{id}/frames  # 预览帧（抽样展示）
+POST   /api/v1/preprocess/jobs/{id}/ingest # 处理后数据入库
+
+# 仿真生成
+POST   /api/v1/simulate/generate         # 提交生成任务
+GET    /api/v1/simulate/jobs             # 生成历史
+GET    /api/v1/simulate/jobs/{id}/images # 预览生成结果
+POST   /api/v1/simulate/jobs/{id}/ingest # 入库
+```
+
+### 四、前端页面设计
+
+#### 4.1 视频预处理页 `/labeling/preprocess`
+```
+┌─ 配置面板 ────────────────────────────┐
+│ 源路径: [________________] [浏览]      │
+│                                       │
+│ 去噪: [none ▼]                        │
+│ 去重: [ssim ▼]  阈值: [0.95]          │
+│ 异常: ☑全黑 ☑模糊 ☑过曝              │
+│ 关键帧: [fixed_interval ▼] 间隔: [10] │
+│                                       │
+│ [🔍 分析视频]  [▶ 执行预处理]          │
+├─ 分析结果 ────────────────────────────┤
+│ 总帧数: 12,340                        │
+│ 预计去重后: ~8,500 (去重率 31%)        │
+│ 异常帧: 234 (1.9%)                     │
+│ 质量分布: ████████░░ 85% good          │
+├─ 处理后预览 ──────────────────────────┤
+│ [缩略图网格] [采样帧对比] [去重前后对比] │
+└──────────────────────────────────────┘
+```
+
+#### 4.2 仿真工坊页 `/labeling/simulate` (已实现，见源码)
+
+### 五、后端模块结构
+
+```
+platform/as_platform/data/
+├── simulate.py       # 世界模型仿真 API 层 (已实现)
+├── preprocess.py     # 视频预处理管线 (待实现)
+│   ├── denoise.py    # 去噪算法
+│   ├── dedup.py      # 去重算法
+│   └── anomaly.py    # 异常检测
+└── quality.py        # 图像质量评分引擎
+```
+
+### 六、依赖
+
+```txt
+# 视频预处理
+opencv-python-headless>=4.8.0   # 帧提取、去噪、Laplacian
+scikit-image>=0.21.0            # SSIM、直方图
+Pillow>=10.0.0                  # (已有) 基础图像操作
+imagehash>=4.3.1                # 感知哈希去重
+```
+| 🆕 P2 | 标注质量抽检 | ❌ |

Dockerfile

@@ -1,12 +1,8 @@
 # syntax=docker/dockerfile:1
 
-# ── React 构建 ──
+# ── HSAP UI：Label Studio 工程 (apps/hsap-platform) ──
-FROM node:22-alpine AS web-build
+# 构建前在宿主机执行: bash scripts/build_hsap_ls_ui.sh
-WORKDIR /web
+# 或 CI 将 dist 拷入 platform/ui-hsap/dist
-COPY platform/web/package.json platform/web/package-lock.json* ./
-RUN npm ci --ignore-scripts 2>/dev/null || npm install
-COPY platform/web/ ./
-RUN npm run build
 
 # ── Platform API ──
 FROM python:3.11-slim AS platform
@@ -26,9 +22,9 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY platform/ ./platform/
 COPY scripts/ ./scripts/
+COPY datasets/ ./datasets/
 COPY as.py workflow.registry.yaml ./
 COPY algorithms/registry.yaml ./algorithms/
-COPY --from=web-build /web/dist ./platform/web/dist
 
 COPY docker/entrypoint.sh /entrypoint.sh
 RUN chmod +x /entrypoint.sh

README.md

@@ -60,6 +60,8 @@ make dev       # 额外启动 Vite 热更新 :5173
 
 **开发登录：** 默认 `manifests/feishu.env` 中 `AS_DEV_AUTH=true`，无需飞书即可登录。
 
+**改 HSAP 前端后（源码在 `platform/web/`）：** 须执行 `bash scripts/build_web.sh` 并 `docker compose restart platform`，否则 8787 仍为旧静态包。
+
 ---
 
 ## 本机直跑（不用 Docker 跑 Platform）

algorithms/dms_yolo/adapter.py

@@ -1,6 +1,7 @@
 """DMS YOLO 引擎：local 研发轨 / platform 平台轨。"""
 from __future__ import annotations
 
+import os
 import subprocess
 import sys
 from pathlib import Path
@@ -13,11 +14,25 @@ YOLO_ROOT = WORKSPACE / "algorithms/dms_yolo/code"
 DATASET_ROOT = WORKSPACE / "datasets/dms"
 
 
-def _latest_run(task: str) -> tuple[str | None, str | None]:
+def _resolve_yaml_key(task: str, submode: str | None = None) -> tuple[str, str]:
+    import sys
+
+    scripts = DATASET_ROOT / "scripts"
+    if str(scripts) not in sys.path:
+        sys.path.insert(0, str(scripts))
+    from task_registry import get_mode_config, resolve_task_id, train_yaml_key
+
     reg = yaml.safe_load((DATASET_ROOT / "datasets.registry.yaml").read_text(encoding="utf-8"))
-    typ = reg["tasks"][task]["type"]
+    task, submode = resolve_task_id(task, submode)
+    mcfg = get_mode_config(task, submode, reg)
+    key = train_yaml_key(task, submode, reg)
+    return key, mcfg["type"]
+
+
+def _latest_run(task: str, submode: str | None = None) -> tuple[str | None, str | None]:
+    yaml_key, typ = _resolve_yaml_key(task, submode)
     mode_yolo = {"detect": "detect", "pose": "pose", "classify": "classify"}[typ]
-    runs = sorted((YOLO_ROOT / "runs" / mode_yolo).glob(f"{task}_*"), key=lambda p: p.stat().st_mtime, reverse=True)
+    runs = sorted((YOLO_ROOT / "runs" / mode_yolo).glob(f"{yaml_key}_*"), key=lambda p: p.stat().st_mtime, reverse=True)
     if not runs:
         return None, None
     run_dir = runs[0].resolve()
@@ -25,17 +40,21 @@ def _latest_run(task: str) -> tuple[str | None, str | None]:
     return str(run_dir), str(best) if best.is_file() else None
 
 
-def train_local(task: str, mode: str = "full", config_overrides: dict | None = None) -> dict[str, Any]:
+def train_local(task: str, mode: str = "full", config_overrides: dict | None = None, submode: str | None = None) -> dict[str, Any]:
     """研发轨：train.sh，不 refresh yaml_active，不更新 candidate。"""
+    env = {**os.environ}
+    if submode:
+        env["SUBMODE"] = submode
     proc = subprocess.run(
         [str(DATASET_ROOT / "scripts" / "train.sh"), task, mode],
         cwd=str(DATASET_ROOT),
         capture_output=True,
         text=True,
+        env=env,
     )
     if proc.returncode != 0:
         raise RuntimeError(proc.stderr or proc.stdout)
-    run_dir, best_weights = _latest_run(task)
+    run_dir, best_weights = _latest_run(task, submode)
     return {
         "ok": True,
         "stdout": proc.stdout,
@@ -48,28 +67,33 @@ def train_local(task: str, mode: str = "full", config_overrides: dict | None = N
     }
 
 
-def train_platform(task: str, mode: str = "full") -> dict[str, Any]:
+def train_platform(task: str, mode: str = "full", submode: str | None = None) -> dict[str, Any]:
     """平台轨：refresh yaml_active + train + 更新 candidate。"""
+    yaml_key, _ = _resolve_yaml_key(task, submode)
     subprocess.check_call(
         [sys.executable, str(DATASET_ROOT / "scripts/refresh_yaml.py"), "--task", task],
         cwd=str(DATASET_ROOT),
     )
+    env = {**os.environ}
+    if submode:
+        env["SUBMODE"] = submode
     proc = subprocess.run(
         [str(DATASET_ROOT / "scripts" / "train.sh"), task, mode],
         cwd=str(DATASET_ROOT),
         capture_output=True,
         text=True,
+        env=env,
     )
     if proc.returncode != 0:
         raise RuntimeError(proc.stderr or proc.stdout)
 
-    run_dir, best_weights = _latest_run(task)
+    run_dir, best_weights = _latest_run(task, submode)
     candidate = None
     if best_weights:
         candidate = best_weights
         versions_path = DATASET_ROOT / "manifests/train_versions.yaml"
         versions = yaml.safe_load(versions_path.read_text(encoding="utf-8"))
-        versions[task]["candidate"] = candidate
+        versions[yaml_key]["candidate"] = candidate
         versions_path.write_text(yaml.dump(versions, allow_unicode=True, sort_keys=False), encoding="utf-8")
 
     return {

algorithms/dms_yolo/code

@@ -0,0 +1 @@
+../../../workspace/DMS/Code/yolo26_rknn_ultralytics-main