mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 05:26:32 +00:00
Oleksandr Bezdieniezhnykh
07c2afb62e
- Add tests/test_az178_realvideo_streaming.py: integration test that validates frame decoding begins while upload is still in progress using a real video fixture - Add conftest.py: pytest plugin for per-test duration reporting - Update e2e tests (async_sse, performance, security, streaming_video_upload, video) and run-tests.sh for updated test suite - Move AZ-178 task to done/; add data/ to .gitignore (StreamingBuffer temp files) - Update autopilot state to step 12 (Security Audit) for new feature cycle Made-with: Cursor
78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
import json
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import time
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import pytest
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def _percentile_ms(sorted_ms, p):
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n = len(sorted_ms)
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if n == 0:
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return 0.0
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if n == 1:
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return float(sorted_ms[0])
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k = (n - 1) * (p / 100.0)
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lo = int(k)
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hi = min(lo + 1, n - 1)
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w = k - lo
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return sorted_ms[lo] * (1 - w) + sorted_ms[hi] * w
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@pytest.mark.timeout(60)
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def test_nft_perf_01_single_image_latency_p95(
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warm_engine, http_client, image_small
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):
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times_ms = []
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for _ in range(10):
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t0 = time.perf_counter()
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r = http_client.post(
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"/detect",
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files={"file": ("img.jpg", image_small, "image/jpeg")},
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timeout=8,
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)
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elapsed_ms = (time.perf_counter() - t0) * 1000.0
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assert r.status_code == 200
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times_ms.append(elapsed_ms)
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sorted_ms = sorted(times_ms)
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p50 = _percentile_ms(sorted_ms, 50)
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p95 = _percentile_ms(sorted_ms, 95)
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p99 = _percentile_ms(sorted_ms, 99)
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print(
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"nft_perf_01_csv,run_ms,"
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+ ",".join(f"{x:.2f}" for x in sorted_ms)
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+ f",p50,{p50:.2f},p95,{p95:.2f},p99,{p99:.2f}"
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)
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assert p95 < 5000.0
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@pytest.mark.timeout(60)
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def test_nft_perf_03_tiling_overhead_large_image(
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warm_engine, http_client, image_small, image_large
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):
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t_small = time.perf_counter()
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r_small = http_client.post(
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"/detect",
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files={"file": ("small.jpg", image_small, "image/jpeg")},
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timeout=8,
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)
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small_ms = (time.perf_counter() - t_small) * 1000.0
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assert r_small.status_code == 200
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config = json.dumps(
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{"altitude": 400, "focal_length": 24, "sensor_width": 23.5}
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)
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t_large = time.perf_counter()
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r_large = http_client.post(
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"/detect",
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files={"file": ("large.jpg", image_large, "image/jpeg")},
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data={"config": config},
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timeout=20,
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)
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large_ms = (time.perf_counter() - t_large) * 1000.0
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assert r_large.status_code == 200
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assert large_ms < 30_000.0
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print(
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f"nft_perf_03_csv,baseline_small_ms,{small_ms:.2f},large_ms,{large_ms:.2f}"
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)
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assert large_ms > small_ms - 500.0
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