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feat: Unified Ingest SDK for DMS/ADAS promote, cuboid export and 3D fit

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Replace subprocess build with promote_batch SDK, add ADAS cuboid export/fit/validate pipeline, stage normalization, and offline unit tests wired into smoke_labeling_api.

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Chengfang Lu
2026-06-16 09:58:35 +08:00
parent bc653d53a1
commit 0b8ade048e
42 changed files with 2074 additions and 104 deletions
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4
platform/as_platform/jobs/queue.py
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@@ -140,6 +140,10 @@ def _run_job(job_id: str) -> None:
from as_platform.labeling.batch_stage import on_labeling_export_job_succeeded
on_labeling_export_job_succeeded(job)
elif job.get("action") in ("build_dms", "build_adas", "build_lane"):
from as_platform.labeling.batch_stage import on_build_job_succeeded
on_build_job_succeeded(job)
except Exception as e:
_patch(job_id, status="failed", finished_at=_now(), result={"ok": False, "error": str(e)})
publish("job.failed", {"job_id": job_id, "error": str(e)})

86
platform/as_platform/jobs/runner.py
View File

@@ -4,6 +4,7 @@ from __future__ import annotations
import json
import subprocess
import sys
from pathlib import Path
from typing import Any
from as_platform.config import WORKSPACE, PLATFORM_DIR, LANE_DATA_VIZ_ENABLED
@@ -73,24 +74,52 @@ def execute_action(action: str, params: dict[str, Any]) -> dict[str, Any]:
return _run_ml(["train", "lane"], timeout=86400)
if action == "build_dms":
argv = ["build", "dms", p["task"]]
if p.get("pack"):
argv.extend(["--pack", str(p["pack"])])
if p.get("batch"):
argv.extend(["--batch", str(p["batch"])])
if p.get("all_sources"):
argv.append("--all-sources")
if p.get("dry_run"):
argv.append("--dry-run")
if p.get("skip_validate"):
argv.append("--skip-validate")
if p.get("no_refresh"):
argv.append("--no-refresh")
result = _run_ml(argv)
# 自动创建数据集快照
_auto_snapshot("dms", task=p.get("task", ""))
from as_platform.data.promote.runner import promote_batch
result = promote_batch(
"dms",
task=p["task"],
batch=p.get("batch"),
pack=p.get("pack"),
dry_run=bool(p.get("dry_run")),
skip_validate=bool(p.get("skip_validate")),
refresh=not p.get("no_refresh"),
)
return result
if action == "build_adas":
from as_platform.data.promote.runner import promote_batch
return promote_batch(
"adas",
task=p.get("task", "cuboid_7cls"),
batch=p.get("batch"),
pack=p.get("pack", "adas_moon3d_v1"),
dry_run=bool(p.get("dry_run")),
skip_validate=bool(p.get("skip_validate")),
allow_partial_3d=bool(p.get("allow_partial_3d", True)),
)
if action == "cuboid_fit_3d":
from as_platform.db.engine import session_scope
from as_platform.db.models import LabelingCampaign
from as_platform.labeling.annotate import resolve_campaign_batch_dir
from as_platform.labeling.fit_cuboid_batch import fit_batch
campaign_id = p.get("campaign_id", "")
batch_dir = None
if campaign_id:
with session_scope() as db:
camp = db.get(LabelingCampaign, campaign_id)
if camp:
batch_dir = resolve_campaign_batch_dir(camp)
if batch_dir is None and p.get("batch_dir"):
batch_dir = Path(p["batch_dir"])
if batch_dir is None:
raise ValueError("cuboid_fit_3d 需要 campaign_id 或 batch_dir")
conv = fit_batch(batch_dir)
return {"ok": True, "stdout": json.dumps(conv, ensure_ascii=False), "stderr": "", "fit_convert": conv}
if action == "build_lane":
result = _run_ml(["build", "lane"])
_auto_snapshot("lane")
@@ -229,10 +258,7 @@ def execute_action(action: str, params: dict[str, Any]) -> dict[str, Any]:
"export_ls_to_yolo: 无有效标注可导出 (written=0); "
f"skipped_empty={conv.get('skipped_empty')} missing_ann={conv.get('missing_ann')}"
)
argv = ["build", "dms", task, "--pack", pack, "--batch", batch]
result = _run_ml(argv)
result["export_convert"] = conv
return result
return {"ok": True, "stdout": json.dumps(conv, ensure_ascii=False), "stderr": "", "export_convert": conv}
if row.get("project") == "lane" and export == "lane_gt_txt":
scripts_dir = WORKSPACE / "datasets" / "lane" / "scripts"
if str(scripts_dir) not in sys.path:
@@ -250,10 +276,22 @@ def execute_action(action: str, params: dict[str, Any]) -> dict[str, Any]:
"export_ls_to_lane_gt: 无有效标注可导出 (written=0); "
f"skipped_empty={conv.get('skipped_empty')} missing_ann={conv.get('missing_ann')}"
)
argv = ["build", "lane"]
result = _run_ml(argv)
result["export_convert"] = conv
return result
return {"ok": True, "stdout": json.dumps(conv, ensure_ascii=False), "stderr": "", "export_convert": conv}
if row.get("project") == "adas" and export == "cvat_cuboid":
from as_platform.labeling.export_cuboid_batch import export_batch as export_cuboid_batch
with session_scope() as db:
camp = db.get(LabelingCampaign, campaign_id)
if not camp:
raise ValueError("campaign not found")
batch_dir = resolve_campaign_batch_dir(camp)
conv = export_cuboid_batch(batch_dir)
if conv.get("written", 0) == 0:
raise ValueError(
"export_cuboid_batch: 无有效 cuboid 可导出 (written=0); "
f"skipped_empty={conv.get('skipped_empty')} missing_ann={conv.get('missing_ann')}"
)
return {"ok": True, "stdout": json.dumps(conv, ensure_ascii=False), "stderr": "", "export_convert": conv}
return {
"ok": True,
"stdout": json.dumps({"export": export, "campaign": row}, ensure_ascii=False),