60 lines
1.7 KiB
Python
60 lines
1.7 KiB
Python
from pathlib import Path
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from fastapi.testclient import TestClient
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from app import main
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from app.main import app
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from app.modules.results.service import parse_training_curve
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def test_parse_yolo_results_curve(tmp_path: Path):
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csv_path = tmp_path / "results.csv"
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csv_path.write_text(
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"\n".join(
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[
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"epoch,time,train/box_loss,train/seg_loss,metrics/mAP50(M),val/seg_loss,lr/pg0",
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"1,1.0,1.5,3.0,0.12,2.8,0.001",
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"2,2.0,1.2,2.5,0.18,2.1,0.001",
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"3,3.0,0.9,2.0,0.25,1.9,0.001",
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]
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),
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encoding="utf-8",
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)
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curve = parse_training_curve(csv_path)
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assert curve is not None
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assert curve["x_key"] == "epoch"
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names = [item["name"] for item in curve["series"]]
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assert "train/seg_loss" in names
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assert "metrics/mAP50(M)" in names
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assert all("lr/" not in name for name in names)
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def test_results_api_honors_limit(monkeypatch):
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calls = {}
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def fake_scan_results(limit: int = 1000):
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calls["limit"] = limit
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return [{"name": "a.png", "relative_path": "var/a.png"}]
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monkeypatch.setattr(main, "scan_results", fake_scan_results)
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response = TestClient(app).get("/api/results?limit=123")
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assert response.status_code == 200
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assert calls["limit"] == 123
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def test_results_curve_api_honors_limit(monkeypatch):
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calls = {}
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def fake_scan_training_curves(limit: int = 100):
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calls["limit"] = limit
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return [{"name": "results", "relative_path": "var/results.csv"}]
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monkeypatch.setattr(main, "scan_training_curves", fake_scan_training_curves)
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response = TestClient(app).get("/api/results/curves?limit=77")
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assert response.status_code == 200
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assert calls["limit"] == 77
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