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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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platform/as_platform/tests/test_unified_ingest_sdk.py Normal file
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#!/usr/bin/env python3
"""Unified Ingest SDK 单元测试（无 pytest 依赖）。"""
from __future__ import annotations
import json
import shutil
import sys
import tempfile
from pathlib import Path
ROOT = Path(__file__).resolve().parents[2]
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 test_stage_aliases() -> None:
from as_platform.labeling.stage import effective_stage, matches_stage_filter
assert effective_stage("review_approved") == "labeling_submitted"
assert effective_stage("returned") == "returned"
assert matches_stage_filter("review_approved", "labeling_submitted")
assert not matches_stage_filter("raw_pool", "returned")
def test_bk2_class_map() -> None:
from as_platform.labeling.class_map import (
build_class_map,
load_adas_class_names,
normalize_detection_class,
remap_class_id,
)
names = load_adas_class_names()
assert names[0] == "pedestrian"
assert names[1] == "car"
cmap = build_class_map(names)
assert cmap["car"] == 1
assert cmap["pedestrian"] == 0
old = ["car", "pedestrian", "truck", "bus", "motorcycle", "tricycle", "traffic cone"]
assert remap_class_id(old, names, 0) == 1 # car was 0, now 1
det = normalize_detection_class({"class_name": "car", "class_id": 99})
assert det["class_id"] == 1
def test_validate_adas_cuboid() -> None:
from as_platform.data.promote.validate.adas_cuboid import validate_adas_cuboid_batch
from as_platform.labeling.class_map import load_adas_class_names
with tempfile.TemporaryDirectory() as td:
batch = Path(td)
qdir = batch / "labels" / "quaternion_json"
qdir.mkdir(parents=True)
names = load_adas_class_names()
good = {
"detections": [{"class_id": 1, "class_name": "car", "fit_ok": False}],
"text_prompts": names,
"K": [[1000, 0, 960], [0, 1000, 540], [0, 0, 1]],
}
(qdir / "a.json").write_text(json.dumps(good), encoding="utf-8")
(qdir / "empty.json").write_text(json.dumps({"detections": []}), encoding="utf-8")
(batch / "calib").mkdir()
(batch / "calib" / "cam.yaml").write_text("K: []\n", encoding="utf-8")
errors, warnings, stats = validate_adas_cuboid_batch(batch, allow_partial_3d=True)
assert not errors, errors
assert stats["files_with_detections"] == 1
assert any("empty" in w for w in warnings)
def test_fit_cuboid_detection() -> None:
from algorithms.adas_mono3d.fit_cuboid import cuboid_points_to_box2d, fit_cuboid_detection
pts = [770.0, 347.0, 834.0, 347.0, 772.0, 423.0, 835.0, 423.0,
806.0, 357.0, 861.0, 357.0, 807.0, 422.0, 862.0, 422.0]
box = cuboid_points_to_box2d(pts)
assert box is not None
assert box[0] < box[2] and box[1] < box[3]
K = [[1189.7, 0, 1007.5], [0, 1189.7, 517.5], [0, 0, 1]]
out = fit_cuboid_detection(pts, K, "car")
assert "center_3d" in out
assert "dimensions_wlh" in out
assert "quaternion_wxyz" in out
assert len(out["quaternion_wxyz"]) == 4
def test_export_cuboid_batch_class_id() -> None:
from as_platform.labeling.export_cuboid_batch import export_batch
with tempfile.TemporaryDirectory() as td:
batch = Path(td)
(batch / "images").mkdir()
img = batch / "images" / "frame1.jpg"
img.write_bytes(b"\xff\xd8\xff")
calib = batch / "calib" / "cam0.yaml"
calib.parent.mkdir()
calib.write_text(
"K:\n - [1000, 0, 960]\n - [0, 1000, 540]\n - [0, 0, 1]\n",
encoding="utf-8",
)
ann_dir = batch / "labels" / "ls_annotations"
ann_dir.mkdir(parents=True)
ann = {
"image": "frame1.jpg",
"result": [{
"type": "cuboid",
"label": "car",
"points": [770.0, 347.0, 834.0, 347.0, 772.0, 423.0, 835.0, 423.0,
806.0, 357.0, 861.0, 357.0, 807.0, 422.0, 862.0, 422.0],
"original_width": 1920,
"original_height": 1080,
}],
}
import hashlib
tid = hashlib.sha256(b"images/frame1.jpg").hexdigest()[:16]
(ann_dir / f"{tid}.json").write_text(json.dumps(ann), encoding="utf-8")
result = export_batch(batch)
assert result["written"] == 1
qjson = batch / "labels" / "quaternion_json" / "frame1.json"
assert qjson.is_file()
data = json.loads(qjson.read_text())
assert data["text_prompts"][0] == "pedestrian"
assert data["detections"][0]["class_id"] == 1
assert data["detections"][0]["class_name"] == "car"
def test_refresh_adas_lists() -> None:
from as_platform.data.promote.manifest import refresh_adas_lists
with tempfile.TemporaryDirectory() as td:
pack_root = Path(td) / "packs" / "test_pack"
src = pack_root / "sources" / "batch_a" / "labels" / "quaternion_json"
src.mkdir(parents=True)
(src / "img1.json").write_text('{"detections":[{}]}', encoding="utf-8")
(src / "img2.json").write_text('{"detections":[{}]}', encoding="utf-8")
wf = {
"projects": {
"adas": {
"root": str(Path(td)),
"registry": "adas.registry.yaml",
}
}
}
(Path(td) / "adas.registry.yaml").write_text("split:\n val_ratio: 0.5\n", encoding="utf-8")
out = refresh_adas_lists(wf, pack="test_pack")
train = Path(out["train_list"]).read_text().strip().splitlines()
val = Path(out["val_list"]).read_text().strip().splitlines()
assert len(train) + len(val) == 2
assert Path(out["pack_index"]).is_file()
def test_promote_adas_dry_run() -> None:
from as_platform.data.promote.adas_cuboid import AdasCuboidPromoteAdapter
from as_platform.data.promote.base import PromoteContext
from as_platform.labeling.class_map import load_adas_class_names
with tempfile.TemporaryDirectory() as td:
batch = Path(td) / "inbox" / "cuboid_7cls" / "b1"
qdir = batch / "labels" / "quaternion_json"
qdir.mkdir(parents=True)
names = load_adas_class_names()
payload = {
"detections": [{"class_id": 1, "class_name": "car"}],
"text_prompts": names,
"K": [[1000, 0, 960], [0, 1000, 540], [0, 0, 1]],
}
(qdir / "f.json").write_text(json.dumps(payload), encoding="utf-8")
(batch / "images").mkdir()
(batch / "images" / "f.jpg").write_bytes(b"x")
root = Path(td)
ctx = PromoteContext(
project="adas",
task="cuboid_7cls",
batch="b1",
pack="test_pack",
batch_dir=batch,
project_root=root,
dry_run=True,
)
adapter = AdasCuboidPromoteAdapter()
assert adapter.validate(ctx) == []
result = adapter.promote(ctx)
assert result.ok
assert result.detail.get("dry_run") is True
def main() -> None:
tests = [
test_stage_aliases,
test_bk2_class_map,
test_validate_adas_cuboid,
test_fit_cuboid_detection,
test_export_cuboid_batch_class_id,
test_refresh_adas_lists,
test_promote_adas_dry_run,
]
for fn in tests:
fn()
print(f"OK {fn.__name__}")
print(f"ALL {len(tests)} PASSED")
if __name__ == "__main__":
main()