mirror of
https://github.com/azaion/gps-denied-onboard.git
synced 2026-06-21 10:21:13 +00:00
Yuzviak
5744ff65ac
- Add pytestmark = [pytest.mark.<category>] to all 23 root test files and 14 e2e test files - Marker distribution: 22 unit, 7 integration, 1 blackbox, 1 sitl, 5 e2e + 2 e2e integration - Add import pytest to test_models.py, test_download.py, test_synthetic_adapter.py (were missing) - Convert test_sitl_integration.py's bare pytestmark to list form preserving skipif guard - Union of all 5 markers = 298/298 = 100% coverage; 216 tests pass with --strict-markers
55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
"""Tests for Model Manager (F16)."""
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import numpy as np
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import pytest
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from gps_denied.core.models import ModelManager
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pytestmark = [pytest.mark.unit]
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def test_load_and_get_model():
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manager = ModelManager()
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# Should auto-load
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engine = manager.get_inference_engine("SuperPoint")
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assert engine.model_name == "SuperPoint"
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# Check fallback/dummy
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assert manager.fallback_to_onnx("SuperPoint") is True
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assert manager.optimize_to_tensorrt("SuperPoint", "path.onnx") == "path.onnx.trt"
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def test_mock_superpoint():
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manager = ModelManager()
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engine = manager.get_inference_engine("SuperPoint")
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dummy_img = np.zeros((480, 640, 3), dtype=np.uint8)
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res = engine.infer(dummy_img)
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assert "keypoints" in res
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assert "descriptors" in res
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assert "scores" in res
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assert len(res["keypoints"]) == 500
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assert res["descriptors"].shape == (500, 256)
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def test_mock_lightglue():
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manager = ModelManager()
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engine = manager.get_inference_engine("LightGlue")
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# Need mock features
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class DummyF:
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def __init__(self, keypoints):
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self.keypoints = keypoints
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f1 = DummyF(np.random.rand(120, 2))
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f2 = DummyF(np.random.rand(150, 2))
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res = engine.infer({"features1": f1, "features2": f2})
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assert "matches" in res
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assert len(res["matches"]) == 100 # min(100, 120, 150)
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assert res["keypoints1"].shape == (100, 2)
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assert res["keypoints2"].shape == (100, 2)
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