feat: 合并 Docker Compose、标注表格优化与部署文档

将 platform + CVAT 合并为单文件 docker-compose.yml，完善 .env 与 init/dev_up 脚本；
新增 docs/DEPLOY.md 与更新 README 以支持新机器部署；含数据湖示例、车队地图、
紧凑表格 UI、ADAS det_7cls 路径与批次台账等近期改动。

Co-authored-by: Cursor <cursoragent@cursor.com>

platform/as_platform/tests/run_dms_e2e_pipeline.py

@@ -0,0 +1,280 @@
+#!/usr/bin/env python3
+"""DMS 2 图 E2E：标完后自动 提交→质检→导出→build 入库。"""
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import sys
+import time
+import urllib.error
+import urllib.request
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parents[3]
+PLATFORM = ROOT / "platform"
+if str(PLATFORM) not in sys.path:
+    sys.path.insert(0, str(PLATFORM))
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+
+def campaign_id(project: str, task: str, mode: str | None, batch: str, location: str = "inbox") -> str:
+    from as_platform.labeling.scope import format_scope_key
+
+    sk = format_scope_key(project, task, mode)
+    raw = f"{sk}:{batch}:{location}"
+    return hashlib.sha256(raw.encode()).hexdigest()[:20]
+
+
+class ApiClient:
+    def __init__(self, base: str, token: str) -> None:
+        self.base = base.rstrip("/")
+        self.token = token
+
+    def _request(self, method: str, path: str, body: dict | None = None) -> Any:
+        data = json.dumps(body).encode() if body is not None else None
+        req = urllib.request.Request(
+            f"{self.base}{path}",
+            data=data,
+            headers={
+                "Authorization": f"Bearer {self.token}",
+                "Content-Type": "application/json",
+            },
+            method=method,
+        )
+        try:
+            with urllib.request.urlopen(req, timeout=120) as resp:
+                raw = resp.read().decode()
+                return json.loads(raw) if raw else {}
+        except urllib.error.HTTPError as e:
+            detail = e.read().decode()
+            raise RuntimeError(f"{method} {path} -> {e.code}: {detail}") from e
+
+    def get(self, path: str) -> Any:
+        return self._request("GET", path)
+
+    def post(self, path: str, body: dict | None = None) -> Any:
+        return self._request("POST", path, body)
+
+
+def login(base: str, name: str = "e2e-runner") -> ApiClient:
+    req = urllib.request.Request(
+        f"{base.rstrip('/')}/api/v1/auth/dev/login",
+        data=json.dumps({"name": name}).encode(),
+        headers={"Content-Type": "application/json"},
+        method="POST",
+    )
+    with urllib.request.urlopen(req, timeout=30) as resp:
+        data = json.loads(resp.read().decode())
+    return ApiClient(base, data["access_token"])
+
+
+def wait_job(api: ApiClient, job_id: str, timeout: int = 180) -> dict[str, Any]:
+    deadline = time.time() + timeout
+    while time.time() < deadline:
+        job = api.get(f"/api/v1/jobs/{job_id}")
+        st = job.get("status")
+        if st in ("succeeded", "failed"):
+            return job
+        time.sleep(1)
+    raise TimeoutError(f"job {job_id} not finished in {timeout}s")
+
+
+def labeled_count(batch_dir: Path) -> int:
+    ann_dir = batch_dir / "labels" / "ls_annotations"
+    if not ann_dir.is_dir():
+        return 0
+    from as_platform.labeling.progress import _annotation_has_result
+
+    n = 0
+    for p in ann_dir.glob("*.json"):
+        if _annotation_has_result(p):
+            n += 1
+    return n
+
+
+def batch_stage(batch_dir: Path) -> str:
+    meta = batch_dir / "batch.meta.yaml"
+    if not meta.is_file():
+        return "raw_pool"
+    import yaml
+
+    data = yaml.safe_load(meta.read_text(encoding="utf-8")) or {}
+    return str(data.get("stage") or "raw_pool")
+
+
+def cmd_info(args: argparse.Namespace) -> None:
+    cid = campaign_id(args.project, args.task, None, args.batch)
+    print(f"campaign_id={cid}")
+    print(f"annotate_url=/labeling/annotate/{cid}")
+    print(f"batch_path=datasets/dms/inbox/{args.task}/{args.batch}")
+    wf_root = ROOT / "datasets" / "dms"
+    batch_dir = wf_root / "inbox" / args.task / args.batch
+    if batch_dir.is_dir():
+        print(f"stage={batch_stage(batch_dir)} labeled={labeled_count(batch_dir)}")
+    try:
+        api = login(args.api)
+        row = next(
+            (i for i in api.get("/api/v1/labeling/batches?limit=100").get("items", [])
+             if i.get("batch") == args.batch and i.get("task") == args.task),
+            None,
+        )
+        if row:
+            print(f"platform_stage={row.get('stage')} status={row.get('campaign_status')}")
+            print(f"progress={row.get('completed_tasks', '?')}/{row.get('total_tasks', '?')}")
+    except Exception as e:
+        print(f"api_skip={e}")
+
+
+def cmd_setup(args: argparse.Namespace) -> None:
+    api = login(args.api)
+    body = {
+        "project": args.project,
+        "task": args.task,
+        "batch": args.batch,
+        "location": "inbox",
+    }
+    row = api.post("/api/v1/labeling/campaigns/open", body)
+    print(json.dumps({"campaign_id": row.get("id"), "stage": row.get("stage"), "cvat_task_id": row.get("cvat_task_id")}, ensure_ascii=False))
+
+
+def wait_labels(batch_dir: Path, min_images: int, wait_sec: int) -> None:
+    if labeled_count(batch_dir) >= min_images:
+        return
+    if wait_sec <= 0:
+        raise RuntimeError(
+            f"仅标注 {labeled_count(batch_dir)}/{min_images} 张，请先在平台画框保存，再执行 run 或 run-wait"
+        )
+    print(f"等待标注 {min_images} 张 (最多 {wait_sec}s)...")
+    deadline = time.time() + wait_sec
+    while time.time() < deadline:
+        n = labeled_count(batch_dir)
+        if n >= min_images:
+            print(f"labeled={n}")
+            return
+        time.sleep(3)
+    raise TimeoutError(f"超时：仅 {labeled_count(batch_dir)}/{min_images} 张有标注")
+
+
+def cmd_run(args: argparse.Namespace) -> None:
+    cid = campaign_id(args.project, args.task, None, args.batch)
+    batch_dir = ROOT / "datasets" / "dms" / "inbox" / args.task / args.batch
+    if not batch_dir.is_dir():
+        raise FileNotFoundError(batch_dir)
+
+    wait_labels(batch_dir, args.min_images, args.wait_label_sec)
+    api = login(args.api)
+
+    print("==> 1. 提交质检")
+    api.post(f"/api/v1/labeling/campaigns/{cid}/submit")
+    row = next(
+        i for i in api.get("/api/v1/labeling/batches?limit=100").get("items", [])
+        if i.get("campaign_id") == cid
+    )
+    assert row.get("stage") == "in_review", row
+
+    print("==> 2. 质检通过 (全部 good)")
+    queue = api.get(f"/api/v1/labeling/campaigns/{cid}/review-queue?limit=50")
+    items = queue.get("items") or []
+    scores = [{"image_path": it["image_path"], "score": "good"} for it in items]
+    res = api.post(
+        f"/api/v1/labeling/campaigns/{cid}/review-submit",
+        {"scores": scores},
+    )
+    print("review", res)
+    row = next(
+        i for i in api.get("/api/v1/labeling/batches?limit=100").get("items", [])
+        if i.get("campaign_id") == cid
+    )
+    assert row.get("stage") == "labeling_submitted", row
+
+    print("==> 3. 执行导出")
+    exp = api.post(f"/api/v1/labeling/campaigns/{cid}/export")
+    job_id = (exp.get("job") or {}).get("id")
+    assert job_id, exp
+    job = wait_job(api, job_id)
+    if job.get("status") != "succeeded":
+        raise RuntimeError(f"export failed: {job}")
+    print("export_job", job.get("result"))
+
+    row = next(
+        i for i in api.get("/api/v1/labeling/batches?limit=100").get("items", [])
+        if i.get("campaign_id") == cid
+    )
+    assert row.get("stage") == "returned", row
+    yolo = list((batch_dir / "labels").rglob("*.txt"))
+    assert yolo, "export 后应有 YOLO txt"
+
+    print("==> 4. 提交 build 审核")
+    appr = api.post(
+        "/api/v1/system/audit/submit-build-batch",
+        {
+            "project": args.project,
+            "task": args.task,
+            "batch": args.batch,
+            "pack": args.pack,
+            "location": "inbox",
+            "note": f"E2E smoke {args.batch}",
+        },
+    )
+    approval_id = appr.get("id")
+    assert approval_id, appr
+    print("approval_id", approval_id)
+
+    print("==> 5. 批准 build")
+    done = api.post(f"/api/v1/system/audit/{approval_id}/approve", {"comment": "e2e auto approve"})
+    build_job_id = done.get("job_id")
+    if build_job_id:
+        bjob = wait_job(api, build_job_id, timeout=300)
+        if bjob.get("status") != "succeeded":
+            raise RuntimeError(f"build failed: {bjob}")
+        print("build_job", bjob.get("result"))
+
+    row = next(
+        i for i in api.get("/api/v1/labeling/batches?limit=100").get("items", [])
+        if i.get("campaign_id") == cid
+    )
+    assert row.get("stage") == "ingested", row
+    assert batch_stage(batch_dir) == "ingested", batch_stage(batch_dir)
+
+    dest = ROOT / "datasets" / "dms" / "packs" / args.pack / args.task / "sources" / args.batch
+    assert dest.is_dir(), f"missing pack source: {dest}"
+    dest_labels = list(dest.rglob("labels/**/*.txt")) + list(dest.rglob("labels/*.txt"))
+    assert dest_labels, f"pack 内应有 labels: {dest}"
+
+    print("DMS_E2E_PIPELINE_OK")
+    print(json.dumps({
+        "campaign_id": cid,
+        "batch": args.batch,
+        "pack": args.pack,
+        "dest": str(dest),
+        "yolo_in_inbox": len(yolo),
+        "stage": row.get("stage"),
+    }, ensure_ascii=False, indent=2))
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("command", choices=("setup", "run", "info"))
+    ap.add_argument("--api", default="http://127.0.0.1:8787")
+    ap.add_argument("--project", default="dms")
+    ap.add_argument("--task", default="addw")
+    ap.add_argument("--batch", default="e2e_2img_20260616")
+    ap.add_argument("--pack", default="dms_v1")
+    ap.add_argument("--min-images", type=int, default=2)
+    ap.add_argument("--wait-label-sec", type=int, default=0)
+    ap.add_argument("--skip-files", action="store_true")
+    args = ap.parse_args()
+
+    if args.command == "info":
+        cmd_info(args)
+    elif args.command == "setup":
+        cmd_setup(args)
+    elif args.command == "run":
+        cmd_run(args)
+
+
+if __name__ == "__main__":
+    main()

platform/as_platform/tests/test_batch_index.py

@@ -0,0 +1,54 @@
+"""批次索引：列表走 DB，重建走扫盘。"""
+from __future__ import annotations
+
+import time
+
+from as_platform.labeling.batch_index import (
+    index_is_empty,
+    list_batches_from_index,
+    rebuild_batch_index,
+)
+from as_platform.labeling.service import list_labeling_batches
+
+
+def test_rebuild_and_list_from_index():
+    r = rebuild_batch_index()
+    assert r["ok"] is True
+    assert r["count"] >= 0
+
+    t0 = time.perf_counter()
+    out = list_batches_from_index(limit=100)
+    elapsed_ms = (time.perf_counter() - t0) * 1000
+    assert out["source"] == "index"
+    assert "items" in out
+    assert elapsed_ms < 500, f"index list too slow: {elapsed_ms:.0f}ms"
+
+
+def test_list_labeling_batches_uses_index():
+    if index_is_empty():
+        rebuild_batch_index()
+    t0 = time.perf_counter()
+    out = list_labeling_batches(limit=50)
+    elapsed_ms = (time.perf_counter() - t0) * 1000
+    assert "items" in out
+    assert elapsed_ms < 800, f"list_labeling_batches too slow: {elapsed_ms:.0f}ms"
+
+
+def test_archive_batch_hides_from_list():
+    from as_platform.db.engine import session_scope
+    from as_platform.db.models import BatchIndex
+    from as_platform.labeling.batch_index import archive_batch, list_batches_from_index
+
+    with session_scope() as db:
+        rec = (
+            db.query(BatchIndex)
+            .filter(BatchIndex.archived.is_(False), BatchIndex.stage == "raw_pool")
+            .first()
+        )
+        if not rec:
+            return
+        cid = rec.campaign_id
+
+    archive_batch(cid)
+    out = list_batches_from_index(stage="raw_pool", limit=500)
+    assert all(r.get("campaign_id") != cid for r in out["items"])