[AZ-139] [AZ-140] [AZ-141] [AZ-142] Implement integration tests for health, single image, tiling, and async SSE

Made-with: Cursor
This commit is contained in:
Oleksandr Bezdieniezhnykh
2026-03-23 22:23:28 +02:00
parent e593f57884
commit 5418bd7d35
4 changed files with 434 additions and 4 deletions
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"""POST /detect/{media_id} async flow, SSE /detect/stream events, annotations callback.""" import json
import threading
import time
import uuid
import pytest
def _ai_config_video(mock_loader_url: str) -> dict:
base = mock_loader_url.rstrip("/")
return {
"probability_threshold": 0.25,
"tracking_intersection_threshold": 0.6,
"altitude": 400,
"focal_length": 24,
"sensor_width": 23.5,
"paths": [f"{base}/load/video_short01.mp4"],
"frame_period_recognition": 4,
"frame_recognition_seconds": 2,
}
def test_ft_p08_immediate_async_response(
warm_engine, http_client, jwt_token, mock_loader_url
):
media_id = f"async-{uuid.uuid4().hex}"
body = _ai_config_video(mock_loader_url)
headers = {"Authorization": f"Bearer {jwt_token}"}
t0 = time.monotonic()
r = http_client.post(f"/detect/{media_id}", json=body, headers=headers)
elapsed = time.monotonic() - t0
assert elapsed < 2.0
assert r.status_code == 200
assert r.json() == {"status": "started", "mediaId": media_id}
@pytest.mark.slow
@pytest.mark.timeout(120)
def test_ft_p09_sse_event_delivery(
warm_engine, http_client, jwt_token, mock_loader_url, sse_client_factory
):
media_id = f"sse-{uuid.uuid4().hex}"
body = _ai_config_video(mock_loader_url)
headers = {"Authorization": f"Bearer {jwt_token}"}
collected: list[dict] = []
thread_exc: list[BaseException] = []
done = threading.Event()
def _listen():
try:
with sse_client_factory() as sse:
time.sleep(0.3)
for event in sse.events():
if not event.data or not str(event.data).strip():
continue
data = json.loads(event.data)
if data.get("mediaId") != media_id:
continue
collected.append(data)
if (
data.get("mediaStatus") == "AIProcessed"
and data.get("mediaPercent") == 100
):
break
except BaseException as e:
thread_exc.append(e)
finally:
done.set()
th = threading.Thread(target=_listen, daemon=True)
th.start()
time.sleep(0.5)
r = http_client.post(f"/detect/{media_id}", json=body, headers=headers)
assert r.status_code == 200
ok = done.wait(timeout=120)
assert ok, "SSE listener did not finish within 120s"
th.join(timeout=5)
assert not thread_exc, thread_exc
assert any(e.get("mediaStatus") == "AIProcessing" for e in collected)
final = collected[-1]
assert final.get("mediaStatus") == "AIProcessed"
assert final.get("mediaPercent") == 100
def test_ft_n04_duplicate_media_id_409(
warm_engine, http_client, jwt_token, mock_loader_url
):
media_id = "dup-test"
body = _ai_config_video(mock_loader_url)
headers = {"Authorization": f"Bearer {jwt_token}"}
r1 = http_client.post(f"/detect/{media_id}", json=body, headers=headers)
assert r1.status_code == 200
r2 = http_client.post(f"/detect/{media_id}", json=body, headers=headers)
assert r2.status_code == 409
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"""Health & engine lifecycle tests (FT-P-01, FT-P-02, FT-P-14, FT-P-15).""" import time
import pytest
_DETECT_TIMEOUT = 60
def _get_health(http_client):
r = http_client.get("/health")
r.raise_for_status()
return r.json()
def _assert_active_ai(data):
assert data["status"] == "healthy"
assert data["aiAvailability"] not in ("None", "Downloading")
@pytest.mark.cpu
class TestHealthEngineStep01PreInit:
def test_ft_p_01_pre_init_health(self, http_client):
t0 = time.monotonic()
data = _get_health(http_client)
assert time.monotonic() - t0 < 2.0
assert data["status"] == "healthy"
assert data["aiAvailability"] == "None"
assert data.get("errorMessage") is None
@pytest.mark.cpu
@pytest.mark.slow
class TestHealthEngineStep02LazyInit:
def test_ft_p_14_lazy_initialization(self, http_client, image_small):
before = _get_health(http_client)
assert before["aiAvailability"] == "None"
files = {"file": ("lazy.jpg", image_small, "image/jpeg")}
r = http_client.post("/detect", files=files, timeout=_DETECT_TIMEOUT)
r.raise_for_status()
body = r.json()
assert isinstance(body, list)
after = _get_health(http_client)
_assert_active_ai(after)
@pytest.mark.cpu
@pytest.mark.slow
class TestHealthEngineStep03Warmed:
@pytest.fixture(autouse=True)
def _warm(self, warm_engine):
pass
def test_ft_p_02_post_init_health(self, http_client):
data = _get_health(http_client)
_assert_active_ai(data)
assert data.get("errorMessage") is None
def test_ft_p_15_onnx_cpu_detect(self, http_client, image_small):
files = {"file": ("onnx.jpg", image_small, "image/jpeg")}
r = http_client.post("/detect", files=files, timeout=_DETECT_TIMEOUT)
r.raise_for_status()
body = r.json()
assert isinstance(body, list)
if body:
d = body[0]
for k in (
"centerX",
"centerY",
"width",
"height",
"classNum",
"label",
"confidence",
):
assert k in d
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"""Synchronous POST /detect single-image scenarios (bounding boxes, config, class mapping).""" import json
from pathlib import Path
import pytest
_DETECT_SLOW_TIMEOUT = 120
_EPS = 1e-6
_WEATHER_CLASS_STRIDE = 20
def _jpeg_width_height(data):
if len(data) < 2 or data[0:2] != b"\xff\xd8":
return None
i = 2
while i + 1 < len(data):
if data[i] != 0xFF:
i += 1
continue
i += 1
while i < len(data) and data[i] == 0xFF:
i += 1
if i >= len(data):
break
m = data[i]
i += 1
if m in (0xD8, 0xD9):
continue
if i + 3 > len(data):
break
seg_len = (data[i] << 8) | data[i + 1]
i += 2
if m in (0xC0, 0xC1, 0xC2, 0xC3, 0xC5, 0xC6, 0xC7):
if i + 5 > len(data):
return None
h = (data[i + 1] << 8) | data[i + 2]
w = (data[i + 3] << 8) | data[i + 4]
return w, h
i += max(0, seg_len - 2)
return None
def _overlap_to_min_area_ratio(a, b):
ox = 0.5 * (a["width"] + b["width"]) - abs(a["centerX"] - b["centerX"])
oy = 0.5 * (a["height"] + b["height"]) - abs(a["centerY"] - b["centerY"])
overlap_area = max(0.0, ox) * max(0.0, oy)
aa = a["width"] * a["height"]
ab = b["width"] * b["height"]
m = min(aa, ab)
if m <= 0:
return 0.0
return overlap_area / m
def _load_classes_media():
p = Path("/media/classes.json")
if not p.is_file():
pytest.skip(f"missing {p}")
raw = json.loads(p.read_text())
by_id = {}
names = []
for row in raw:
cid = row["Id"]
by_id[cid] = float(row["MaxSizeM"])
names.append(row["Name"])
return by_id, names
def _weather_label_ok(label, base_names):
for n in base_names:
if label == n:
return True
if label == n + "(Wint)" or label == n + "(Night)":
return True
return False
@pytest.mark.slow
def test_ft_p_03_detection_response_structure_ac1(http_client, image_small, warm_engine):
r = http_client.post(
"/detect",
files={"file": ("img.jpg", image_small, "image/jpeg")},
)
assert r.status_code == 200
body = r.json()
assert isinstance(body, list)
for d in body:
assert isinstance(d["centerX"], (int, float))
assert isinstance(d["centerY"], (int, float))
assert isinstance(d["width"], (int, float))
assert isinstance(d["height"], (int, float))
assert 0.0 <= float(d["centerX"]) <= 1.0
assert 0.0 <= float(d["centerY"]) <= 1.0
assert 0.0 <= float(d["width"]) <= 1.0
assert 0.0 <= float(d["height"]) <= 1.0
assert isinstance(d["classNum"], int)
assert isinstance(d["label"], str)
assert isinstance(d["confidence"], (int, float))
assert 0.0 <= float(d["confidence"]) <= 1.0
@pytest.mark.slow
def test_ft_p_05_confidence_filtering_ac2(http_client, image_small, warm_engine):
cfg_hi = json.dumps({"probability_threshold": 0.8})
r_hi = http_client.post(
"/detect",
files={"file": ("img.jpg", image_small, "image/jpeg")},
data={"config": cfg_hi},
)
assert r_hi.status_code == 200
hi = r_hi.json()
assert isinstance(hi, list)
for d in hi:
assert float(d["confidence"]) + _EPS >= 0.8
cfg_lo = json.dumps({"probability_threshold": 0.1})
r_lo = http_client.post(
"/detect",
files={"file": ("img.jpg", image_small, "image/jpeg")},
data={"config": cfg_lo},
)
assert r_lo.status_code == 200
lo = r_lo.json()
assert isinstance(lo, list)
assert len(lo) >= len(hi)
@pytest.mark.slow
def test_ft_p_06_overlap_deduplication_ac3(http_client, image_dense, warm_engine):
cfg_loose = json.dumps({"tracking_intersection_threshold": 0.6})
r1 = http_client.post(
"/detect",
files={"file": ("img.jpg", image_dense, "image/jpeg")},
data={"config": cfg_loose},
timeout=_DETECT_SLOW_TIMEOUT,
)
assert r1.status_code == 200
dets = r1.json()
assert isinstance(dets, list)
by_label = {}
for d in dets:
by_label.setdefault(d["label"], []).append(d)
for label, group in by_label.items():
for i in range(len(group)):
for j in range(i + 1, len(group)):
ratio = _overlap_to_min_area_ratio(group[i], group[j])
assert ratio <= 0.6 + _EPS, (label, ratio)
cfg_strict = json.dumps({"tracking_intersection_threshold": 0.01})
r2 = http_client.post(
"/detect",
files={"file": ("img.jpg", image_dense, "image/jpeg")},
data={"config": cfg_strict},
timeout=_DETECT_SLOW_TIMEOUT,
)
assert r2.status_code == 200
strict = r2.json()
assert isinstance(strict, list)
assert len(strict) <= len(dets)
@pytest.mark.slow
def test_ft_p_07_physical_size_filtering_ac4(http_client, image_small, warm_engine):
by_id, _ = _load_classes_media()
wh = _jpeg_width_height(image_small)
assert wh is not None
image_width_px, _ = wh
altitude = 400.0
focal_length = 24.0
sensor_width = 23.5
gsd = (sensor_width * altitude) / (focal_length * image_width_px)
cfg = json.dumps(
{
"altitude": altitude,
"focal_length": focal_length,
"sensor_width": sensor_width,
}
)
r = http_client.post(
"/detect",
files={"file": ("img.jpg", image_small, "image/jpeg")},
data={"config": cfg},
timeout=_DETECT_SLOW_TIMEOUT,
)
assert r.status_code == 200
body = r.json()
assert isinstance(body, list)
for d in body:
base_id = d["classNum"] % _WEATHER_CLASS_STRIDE
assert base_id in by_id
physical_width = float(d["width"]) * image_width_px * gsd
assert physical_width <= by_id[base_id] + _EPS
@pytest.mark.slow
def test_ft_p_13_weather_mode_class_variants_ac5(
http_client, image_different_types, warm_engine
):
_, base_names = _load_classes_media()
r = http_client.post(
"/detect",
files={"file": ("img.jpg", image_different_types, "image/jpeg")},
timeout=_DETECT_SLOW_TIMEOUT,
)
assert r.status_code == 200
body = r.json()
assert isinstance(body, list)
for d in body:
label = d["label"]
assert isinstance(label, str)
assert len(label) > 0
assert _weather_label_ok(label, base_names)
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"""Large-image tiling and overlap behavior for POST /detect.""" import json
import pytest
_TILING_TIMEOUT = 120
_GSD = {"altitude": 400, "focal_length": 24, "sensor_width": 23.5}
_DUP_THRESHOLD = 0.01
def _assert_coords_normalized(detections):
for d in detections:
for k in ("centerX", "centerY", "width", "height"):
v = d[k]
assert 0.0 <= v <= 1.0
def _assert_no_same_label_near_duplicate_centers(detections):
by_label = {}
for d in detections:
label = d["label"]
cx, cy = d["centerX"], d["centerY"]
prev = by_label.setdefault(label, [])
for pcx, pcy in prev:
assert not (
abs(cx - pcx) < _DUP_THRESHOLD and abs(cy - pcy) < _DUP_THRESHOLD
), f"near-duplicate centers for label {label!r}: ({pcx},{pcy}) vs ({cx},{cy})"
prev.append((cx, cy))
@pytest.mark.slow
def test_ft_p_04_gsd_based_tiling_ac1(http_client, image_large, warm_engine):
config = json.dumps(_GSD)
r = http_client.post(
"/detect",
files={"file": ("img.jpg", image_large, "image/jpeg")},
data={"config": config},
timeout=_TILING_TIMEOUT,
)
assert r.status_code == 200
body = r.json()
assert isinstance(body, list)
_assert_coords_normalized(body)
@pytest.mark.slow
def test_ft_p_16_tile_boundary_deduplication_ac2(http_client, image_large, warm_engine):
config = json.dumps({**_GSD, "big_image_tile_overlap_percent": 20})
r = http_client.post(
"/detect",
files={"file": ("img.jpg", image_large, "image/jpeg")},
data={"config": config},
timeout=_TILING_TIMEOUT,
)
assert r.status_code == 200
body = r.json()
assert isinstance(body, list)
_assert_no_same_label_near_duplicate_centers(body)