feat: initial HSAP platform

Huaxu Sentinel Active Safety Platform with embedded algorithm code,
Docker Compose setup, and vendored dataset scaffolds for clone-and-run.

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

platform/as_platform/data/ingest/lane_mask.py

@@ -0,0 +1,48 @@
+"""Lane mask + list txt adapter."""
+from __future__ import annotations
+
+from pathlib import Path
+
+from as_platform.data.ingest.base import IngestAdapter, IngestContext, NormalizedDataset
+
+
+def _line_count(path: Path) -> int:
+    if not path.is_file():
+        return 0
+    try:
+        return sum(1 for _ in path.open(encoding="utf-8", errors="ignore"))
+    except OSError:
+        return 0
+
+
+class LaneMaskAdapter(IngestAdapter):
+    format_id = "lane_mask"
+    projects = ("lane",)
+
+    def can_handle(self, ctx: IngestContext) -> bool:
+        root = ctx.source_path
+        return (root / "list" / "train_gt.txt").is_file() or (root / "train_val_gt.txt").is_file()
+
+    def inspect(self, ctx: IngestContext) -> NormalizedDataset:
+        root = ctx.source_path
+        train = _line_count(root / "list" / "train_gt.txt")
+        val = _line_count(root / "list" / "val_gt.txt")
+        test = _line_count(root / "list" / "test_gt.txt")
+        if train == 0 and (root / "train_val_gt.txt").is_file():
+            train = _line_count(root / "train_val_gt.txt")
+
+        warnings: list[str] = []
+        if train == 0:
+            warnings.append("train split list is empty")
+
+        return NormalizedDataset(
+            format_id=self.format_id,
+            project=ctx.project,
+            task=ctx.task,
+            source_path=str(root),
+            split_counts={"train": train, "val": val, "test": test},
+            sample_count=train + val + test,
+            annotation_count=train + val + test,
+            artifacts=["list/train_gt.txt", "list/val_gt.txt", "list/test_gt.txt"],
+            warnings=warnings,
+        )