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)

datasets/dms/scripts/test_export_ls_to_yolo.py

@@ -0,0 +1,143 @@
+#!/usr/bin/env python3
+"""export_ls_to_yolo 单元测试（无 pytest 依赖）。"""
+from __future__ import annotations
+
+import hashlib
+import json
+import sys
+import tempfile
+from pathlib import Path
+
+SCRIPT_DIR = Path(__file__).resolve().parent
+sys.path.insert(0, str(SCRIPT_DIR))
+
+from export_ls_to_yolo import (  # noqa: E402
+    convert_regions_to_yolo_lines,
+    export_batch,
+)
+from ingest_incremental import validate_detect_label, validate_pose_label  # noqa: E402
+
+
+def _task_id(rel: str) -> str:
+    return hashlib.sha256(rel.encode()).hexdigest()[:16]
+
+
+def test_detect_conversion() -> None:
+    regions = [
+        {
+            "type": "rectanglelabels",
+            "value": {
+                "x": 10.0,
+                "y": 20.0,
+                "width": 30.0,
+                "height": 40.0,
+                "rectanglelabels": ["face"],
+            },
+        }
+    ]
+    lines = convert_regions_to_yolo_lines(
+        regions,
+        mode="detect",
+        class_map={"face": 0, "eye_open": 1},
+    )
+    assert len(lines) == 1
+    parts = lines[0].split()
+    assert len(parts) == 5
+    assert parts[0] == "0"
+    assert abs(float(parts[1]) - 0.25) < 1e-5  # cx = (10+15)/100
+    assert abs(float(parts[2]) - 0.40) < 1e-5  # cy = (20+20)/100
+    err = validate_detect_label("\n".join(lines), 4)
+    assert err is None, err
+
+
+def test_pose_conversion() -> None:
+    regions = [
+        {
+            "type": "rectanglelabels",
+            "value": {
+                "x": 10.0,
+                "y": 20.0,
+                "width": 30.0,
+                "height": 40.0,
+                "rectanglelabels": ["face"],
+            },
+        },
+        {
+            "type": "keypointlabels",
+            "value": {"x": 35.6, "y": 52.9, "width": 0.5, "keypointlabels": ["kp_01"]},
+        },
+        {
+            "type": "keypointlabels",
+            "value": {"x": 50.0, "y": 50.0, "width": 0.5, "keypointlabels": ["kp_10"]},
+        },
+    ]
+    kpt_map = {f"kp_{i:02d}": i for i in range(37)}
+    lines = convert_regions_to_yolo_lines(
+        regions,
+        mode="pose",
+        class_map={"face": 0},
+        kpt_map=kpt_map,
+        kpt_shape=[37, 3],
+    )
+    assert len(lines) == 1
+    parts = lines[0].split()
+    assert len(parts) == 116
+    assert parts[0] == "0"
+    # kp_01 at index 1 -> fields 5+3..5+5
+    assert abs(float(parts[8]) - 0.356) < 1e-3
+    assert abs(float(parts[9]) - 0.529) < 1e-3
+    assert parts[10] == "2.000000"
+    err = validate_pose_label("\n".join(lines), [37, 3])
+    assert err is None, err
+
+
+def test_export_batch_end_to_end() -> None:
+    with tempfile.TemporaryDirectory() as tmp:
+        batch = Path(tmp)
+        img_rel = "images/train/sample.jpg"
+        img_path = batch / img_rel
+        img_path.parent.mkdir(parents=True)
+        img_path.write_bytes(b"\xff\xd8\xff")
+
+        tid = _task_id(img_rel)
+        ann = {
+            "task_id": tid,
+            "result": [
+                {
+                    "type": "rectanglelabels",
+                    "value": {
+                        "x": 10.0,
+                        "y": 20.0,
+                        "width": 30.0,
+                        "height": 40.0,
+                        "rectanglelabels": ["face"],
+                    },
+                },
+                {
+                    "type": "keypointlabels",
+                    "value": {"x": 25.0, "y": 40.0, "width": 0.5, "keypointlabels": ["kp_00"]},
+                },
+            ],
+        }
+        ann_dir = batch / "labels" / "ls_annotations"
+        ann_dir.mkdir(parents=True)
+        (ann_dir / f"{tid}.json").write_text(json.dumps(ann), encoding="utf-8")
+
+        result = export_batch(batch, "addw_face", mode="pose")
+        assert result["written"] == 1
+        out = batch / "labels" / "train" / "sample.txt"
+        assert out.is_file()
+        parts = out.read_text().strip().split()
+        assert len(parts) == 116
+
+
+def main() -> int:
+    test_detect_conversion()
+    test_pose_conversion()
+    test_export_batch_end_to_end()
+    print("OK export_ls_to_yolo tests")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())