mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 22:16:31 +00:00
8baa96978b
- Updated the detection image endpoint to require a channel ID for event streaming. - Introduced a new endpoint for streaming detection events, allowing clients to receive real-time updates. - Enhanced the internal buffering mechanism for detection events to manage multiple channels. - Refactored the inference module to support the new event handling structure. Made-with: Cursor
154 lines
5.0 KiB
Python
154 lines
5.0 KiB
Python
import json
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import threading
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import time
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import uuid
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import pytest
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import sseclient
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_DETECT_TIMEOUT = 60
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def _get_health(http_client):
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r = http_client.get("/health")
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r.raise_for_status()
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return r.json()
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def _assert_active_ai(data):
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assert data["status"] == "healthy"
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assert data["aiAvailability"] not in ("None", "Downloading")
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@pytest.mark.cpu
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class TestHealthEngineStep01PreInit:
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def test_ft_p_01_pre_init_health(self, http_client):
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t0 = time.monotonic()
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data = _get_health(http_client)
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assert time.monotonic() - t0 < 2.0
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assert data["status"] == "healthy"
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assert data["aiAvailability"] == "None", (
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f"engine already initialized (aiAvailability={data['aiAvailability']}); "
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"pre-init tests must run before any test that triggers warm_engine"
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)
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assert data.get("errorMessage") is None
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@pytest.mark.cpu
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@pytest.mark.slow
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class TestHealthEngineStep02LazyInit:
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def test_ft_p_14_lazy_initialization(self, http_client, image_small, auth_headers):
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before = _get_health(http_client)
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assert before["aiAvailability"] == "None", (
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f"engine already initialized (aiAvailability={before['aiAvailability']}); "
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"lazy-init test must run before any test that triggers warm_engine"
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)
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cid = str(uuid.uuid4())
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headers = {**auth_headers, "X-Channel-Id": cid}
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done = threading.Event()
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connected = threading.Event()
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def _listen():
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try:
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with http_client.get(
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f"/detect/events/{cid}",
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stream=True,
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timeout=_DETECT_TIMEOUT + 2,
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headers=auth_headers,
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) as resp:
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resp.raise_for_status()
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connected.set()
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for ev in sseclient.SSEClient(resp).events():
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if not ev.data or not str(ev.data).strip():
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continue
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data = json.loads(ev.data)
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if data.get("mediaStatus") in ("AIProcessed", "Error"):
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break
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except Exception:
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pass
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finally:
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connected.set()
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done.set()
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th = threading.Thread(target=_listen, daemon=True)
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th.start()
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connected.wait(timeout=5)
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files = {"file": ("lazy.jpg", image_small, "image/jpeg")}
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r = http_client.post("/detect/image", files=files, headers=headers, timeout=_DETECT_TIMEOUT)
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assert r.status_code == 202
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done.wait(timeout=_DETECT_TIMEOUT)
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th.join(timeout=2)
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after = _get_health(http_client)
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_assert_active_ai(after)
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@pytest.mark.cpu
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@pytest.mark.slow
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class TestHealthEngineStep03Warmed:
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@pytest.fixture(autouse=True)
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def _warm(self, warm_engine):
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pass
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def test_ft_p_02_post_init_health(self, http_client):
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data = _get_health(http_client)
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_assert_active_ai(data)
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assert data.get("errorMessage") is None
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def test_ft_p_15_onnx_cpu_detect(self, http_client, image_small, auth_headers):
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cid = str(uuid.uuid4())
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headers = {**auth_headers, "X-Channel-Id": cid}
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all_detections = []
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done = threading.Event()
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connected = threading.Event()
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def _listen():
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try:
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with http_client.get(
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f"/detect/events/{cid}",
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stream=True,
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timeout=_DETECT_TIMEOUT + 2,
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headers=auth_headers,
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) as resp:
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resp.raise_for_status()
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connected.set()
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for ev in sseclient.SSEClient(resp).events():
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if not ev.data or not str(ev.data).strip():
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continue
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data = json.loads(ev.data)
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if data.get("mediaStatus") == "AIProcessing":
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all_detections.extend(data.get("annotations", []))
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if data.get("mediaStatus") in ("AIProcessed", "Error"):
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break
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except Exception:
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pass
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finally:
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connected.set()
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done.set()
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th = threading.Thread(target=_listen, daemon=True)
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th.start()
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connected.wait(timeout=5)
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files = {"file": ("onnx.jpg", image_small, "image/jpeg")}
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r = http_client.post("/detect/image", files=files, headers=headers, timeout=_DETECT_TIMEOUT)
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r.raise_for_status()
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assert r.status_code == 202
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done.wait(timeout=_DETECT_TIMEOUT)
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th.join(timeout=2)
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if all_detections:
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d = all_detections[0]
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for k in (
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"centerX",
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"centerY",
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"width",
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"height",
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"classNum",
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"label",
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"confidence",
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):
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assert k in d
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