mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 06:56:31 +00:00
Oleksandr Bezdieniezhnykh
27f4aceb52
- Updated the `Inference` class to replace the `get_onnx_engine_bytes` method with `download_model`, allowing for dynamic model loading based on a specified filename. - Modified the `convert_and_upload_model` method to accept `source_bytes` instead of `onnx_engine_bytes`, enhancing flexibility in model conversion. - Introduced a new property `engine_name` to the `Inference` class for better access to engine details. - Adjusted the `AIRecognitionConfig` structure to include a new method pointer `from_dict`, improving configuration handling. - Updated various test cases to reflect changes in model paths and timeout settings, ensuring consistency and reliability in testing.
112 lines
3.3 KiB
Python
112 lines
3.3 KiB
Python
import json
|
|
import re
|
|
import threading
|
|
import time
|
|
import uuid
|
|
from datetime import datetime
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
|
|
|
|
def _video_ai_body(video_path: str) -> dict:
|
|
return {
|
|
"probability_threshold": 0.25,
|
|
"tracking_intersection_threshold": 0.6,
|
|
"altitude": 400,
|
|
"focal_length": 24,
|
|
"sensor_width": 23.5,
|
|
"paths": [video_path],
|
|
"frame_period_recognition": 4,
|
|
"frame_recognition_seconds": 2,
|
|
}
|
|
|
|
|
|
@pytest.mark.skip(reason="Single video run — covered by test_ft_p09_sse_event_delivery")
|
|
@pytest.mark.slow
|
|
@pytest.mark.timeout(300)
|
|
def test_ft_n_08_nft_res_lim_02_sse_queue_bounded_best_effort(
|
|
warm_engine,
|
|
http_client,
|
|
jwt_token,
|
|
video_short_path,
|
|
sse_client_factory,
|
|
):
|
|
media_id = f"rlim-sse-{uuid.uuid4().hex}"
|
|
body = _video_ai_body(video_short_path)
|
|
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
|
|
assert done.wait(timeout=290)
|
|
th.join(timeout=5)
|
|
assert not thread_exc, thread_exc
|
|
assert collected
|
|
assert collected[-1].get("mediaStatus") == "AIProcessed"
|
|
|
|
|
|
|
|
@pytest.mark.slow
|
|
@pytest.mark.timeout(120)
|
|
def test_nft_res_lim_03_max_detections_per_frame(
|
|
warm_engine, http_client, image_dense
|
|
):
|
|
r = http_client.post(
|
|
"/detect",
|
|
files={"file": ("img.jpg", image_dense, "image/jpeg")},
|
|
timeout=120,
|
|
)
|
|
assert r.status_code == 200
|
|
body = r.json()
|
|
assert isinstance(body, list)
|
|
assert len(body) <= 300
|
|
|
|
|
|
@pytest.mark.slow
|
|
def test_nft_res_lim_04_log_file_rotation(warm_engine, http_client, image_small):
|
|
http_client.post(
|
|
"/detect",
|
|
files={"file": ("img.jpg", image_small, "image/jpeg")},
|
|
timeout=60,
|
|
)
|
|
candidates = [
|
|
Path(__file__).resolve().parent.parent / "logs",
|
|
Path("/app/Logs"),
|
|
]
|
|
log_dir = next((p for p in candidates if p.is_dir()), None)
|
|
if log_dir is None:
|
|
pytest.skip("Log directory not accessible from e2e-runner container")
|
|
today = datetime.now().strftime("%Y%m%d")
|
|
expected = f"log_inference_{today}.txt"
|
|
names = {p.name for p in log_dir.iterdir() if p.is_file()}
|
|
if expected not in names:
|
|
pat = re.compile(r"^log_inference_\d{8}\.txt$")
|
|
assert any(pat.match(n) for n in names), names
|