mirror of
https://github.com/azaion/gps-denied-onboard.git
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Yuzviak
dd9835c0cd
- ruff --fix: removed trailing whitespace (W293), sorted imports (I001) - Manual: broke long lines (E501) in eskf, rotation, vo, gpr, metric, pipeline, rotation tests - Removed unused imports (F401) in models.py, schemas/__init__.py - pyproject.toml: line-length 100→120, E501 ignore for abstract interfaces ruff check: 0 errors. pytest: 195 passed / 8 skipped. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
113 lines
4.0 KiB
Python
113 lines
4.0 KiB
Python
"""Tests for Global Place Recognition (F08)."""
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import numpy as np
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import pytest
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from gps_denied.core.gpr import GlobalPlaceRecognition
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from gps_denied.core.models import ModelManager
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from gps_denied.schemas.gpr import TileCandidate
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@pytest.fixture
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def gpr():
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manager = ModelManager()
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gpr = GlobalPlaceRecognition(manager)
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gpr.load_index("flight_123", "dummy_path.faiss")
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return gpr
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def test_compute_location_descriptor(gpr):
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img = np.zeros((200, 200, 3), dtype=np.uint8)
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desc = gpr.compute_location_descriptor(img)
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assert desc.shape == (4096,)
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# Should be L2 normalized
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assert np.isclose(np.linalg.norm(desc), 1.0)
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def test_retrieve_candidate_tiles(gpr):
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img = np.zeros((200, 200, 3), dtype=np.uint8)
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candidates = gpr.retrieve_candidate_tiles(img, top_k=5)
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assert len(candidates) == 5
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for c in candidates:
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assert isinstance(c, TileCandidate)
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assert c.similarity_score >= 0.0
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def test_retrieve_candidate_tiles_for_chunk(gpr):
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imgs = [np.zeros((200, 200, 3), dtype=np.uint8) for _ in range(5)]
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candidates = gpr.retrieve_candidate_tiles_for_chunk(imgs, top_k=3)
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assert len(candidates) == 3
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# Ensure they are sorted descending (GPR-03)
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assert candidates[0].similarity_score >= candidates[1].similarity_score
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# ---------------------------------------------------------------
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# GPR-01: Real Faiss index with file path
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# ---------------------------------------------------------------
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def test_load_index_missing_file_falls_back(tmp_path):
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"""GPR-01: non-existent index path → numpy fallback, still usable."""
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from gps_denied.core.gpr import GlobalPlaceRecognition
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from gps_denied.core.models import ModelManager
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g = GlobalPlaceRecognition(ModelManager())
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ok = g.load_index("f1", str(tmp_path / "nonexistent.index"))
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assert ok is True
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assert g._is_loaded is True
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# Should still answer queries
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img = np.zeros((200, 200, 3), dtype=np.uint8)
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cands = g.retrieve_candidate_tiles(img, top_k=3)
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assert len(cands) == 3
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def test_load_index_not_loaded_returns_empty():
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"""query_database before load_index → empty list (no crash)."""
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from gps_denied.core.gpr import GlobalPlaceRecognition
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from gps_denied.core.models import ModelManager
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g = GlobalPlaceRecognition(ModelManager())
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desc = np.random.rand(4096).astype(np.float32)
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matches = g.query_database(desc, top_k=5)
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assert matches == []
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# ---------------------------------------------------------------
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# GPR-03: Ranking is deterministic (sorted by similarity)
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# ---------------------------------------------------------------
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def test_rank_candidates_sorted(gpr):
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"""rank_candidates must return descending similarity order."""
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from gps_denied.schemas import GPSPoint
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from gps_denied.schemas.gpr import TileCandidate
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from gps_denied.schemas.satellite import TileBounds
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dummy_bounds = TileBounds(
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nw=GPSPoint(lat=49.1, lon=32.0), ne=GPSPoint(lat=49.1, lon=32.1),
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sw=GPSPoint(lat=49.0, lon=32.0), se=GPSPoint(lat=49.0, lon=32.1),
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center=GPSPoint(lat=49.05, lon=32.05), gsd=0.6,
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)
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cands = [
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TileCandidate(
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tile_id="a", gps_center=GPSPoint(lat=49, lon=32),
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bounds=dummy_bounds, similarity_score=0.3, rank=3,
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),
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TileCandidate(
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tile_id="b", gps_center=GPSPoint(lat=49, lon=32),
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bounds=dummy_bounds, similarity_score=0.9, rank=1,
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),
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TileCandidate(
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tile_id="c", gps_center=GPSPoint(lat=49, lon=32),
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bounds=dummy_bounds, similarity_score=0.6, rank=2,
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),
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]
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ranked = gpr.rank_candidates(cands)
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scores = [c.similarity_score for c in ranked]
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assert scores == sorted(scores, reverse=True)
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def test_descriptor_is_l2_normalised(gpr):
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"""DINOv2 descriptor returned by compute_location_descriptor is unit-norm."""
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img = np.random.randint(0, 255, (200, 200, 3), dtype=np.uint8)
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desc = gpr.compute_location_descriptor(img)
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assert np.isclose(np.linalg.norm(desc), 1.0, atol=1e-5)
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