mirror of
https://github.com/azaion/gps-denied-onboard.git
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Yuzviak
094895b21b
Phase 2 — Visual Odometry: - ORBVisualOdometry (dev/CI), CuVSLAMVisualOdometry (Jetson) - TRTInferenceEngine (TensorRT FP16, conditional import) - create_vo_backend() factory Phase 3 — Satellite Matching + GPR: - SatelliteDataManager: local z/x/y tiles, ESKF ±3σ tile selection - GSD normalization (SAT-03), RANSAC inlier-ratio confidence (SAT-04) - GlobalPlaceRecognition: Faiss index + numpy fallback Phase 4 — MAVLink I/O: - MAVLinkBridge: GPS_INPUT 15+ fields, IMU callback, 1Hz telemetry - 3-consecutive-failure reloc request - MockMAVConnection for CI Phase 5 — Pipeline Wiring: - ESKF wired into process_frame: VO update → satellite update - CoordinateTransformer + SatelliteDataManager via DI - MAVLink state push per frame (PIPE-07) - Real pixel_to_gps via ray-ground projection (PIPE-06) - GTSAM ISAM2 update when available (PIPE-03) Phase 6 — Docker + CI: - Multi-stage Dockerfile (python:3.11-slim) - docker-compose.yml (dev), docker-compose.sitl.yml (ArduPilot SITL) - GitHub Actions: ci.yml (lint+pytest+docker smoke), sitl.yml (nightly) - tests/test_sitl_integration.py (8 tests, skip without SITL) Phase 7 — Accuracy Validation: - AccuracyBenchmark + SyntheticTrajectory - AC-PERF-1: 80% within 50m ✅ - AC-PERF-2: 60% within 20m ✅ - AC-PERF-3: p95 latency < 400ms ✅ - AC-PERF-4: VO drift 1km < 100m ✅ (actual ~11m) - scripts/benchmark_accuracy.py CLI Tests: 195 passed / 8 skipped Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
"""Tests for Image Input Pipeline (F05)."""
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import asyncio
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import cv2
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import numpy as np
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import pytest
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from gps_denied.core.pipeline import ImageInputPipeline, QueueFullError, ValidationError
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from gps_denied.schemas.image import ImageBatch
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@pytest.fixture
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def pipeline(tmp_path):
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storage = str(tmp_path / "images")
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return ImageInputPipeline(storage_dir=storage, max_queue_size=2)
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def test_batch_validation(pipeline):
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# VO-05: minimum batch size is now 1 (not 10)
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# Zero images is still invalid
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b0 = ImageBatch(images=[], filenames=[], start_sequence=1, end_sequence=0, batch_number=1)
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val0 = pipeline.validate_batch(b0)
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assert not val0.valid
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assert "Batch is empty" in val0.errors
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# Single image is now valid
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b1 = ImageBatch(images=[b"fake"], filenames=["AD000001.jpg"], start_sequence=1, end_sequence=1, batch_number=1)
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val1 = pipeline.validate_batch(b1)
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assert val1.valid, f"Single-image batch should be valid; errors: {val1.errors}"
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# 2-image batch — also valid under new rule
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b2 = ImageBatch(images=[b"1", b"2"], filenames=["AD000001.jpg", "AD000002.jpg"], start_sequence=1, end_sequence=2, batch_number=1)
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val2 = pipeline.validate_batch(b2)
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assert val2.valid
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# Large valid batch
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fake_imgs = [b"fake"] * 10
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fake_names = [f"AD{i:06d}.jpg" for i in range(1, 11)]
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b10 = ImageBatch(images=fake_imgs, filenames=fake_names, start_sequence=1, end_sequence=10, batch_number=1)
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val10 = pipeline.validate_batch(b10)
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assert val10.valid
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@pytest.mark.asyncio
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async def test_queue_and_process(pipeline):
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flight_id = "test_f1"
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# Create valid fake images
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fake_img_np = np.zeros((10, 10, 3), dtype=np.uint8)
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_, encoded = cv2.imencode(".jpg", fake_img_np)
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fake_bytes = encoded.tobytes()
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fake_imgs = [fake_bytes] * 10
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fake_names = [f"AD{i:06d}.jpg" for i in range(1, 11)]
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b = ImageBatch(images=fake_imgs, filenames=fake_names, start_sequence=1, end_sequence=10, batch_number=1)
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pipeline.queue_batch(flight_id, b)
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# Process
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processed = await pipeline.process_next_batch(flight_id)
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assert processed is not None
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assert len(processed.images) == 10
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assert processed.images[0].sequence == 1
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assert processed.images[-1].sequence == 10
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# Status
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st = pipeline.get_processing_status(flight_id)
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assert st.total_images == 10
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assert st.processed_images == 10
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# Sequential get
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next_img = pipeline.get_next_image(flight_id)
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assert next_img is not None
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assert next_img.sequence == 1
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# Second get
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next_img2 = pipeline.get_next_image(flight_id)
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assert next_img2 is not None
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assert next_img2.sequence == 2
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@pytest.mark.asyncio
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async def test_exact_sequence_lookup_no_collision(pipeline, tmp_path):
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"""VO-05: sequence 1 must NOT match AD000011.jpg or AD000010.jpg."""
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flight_id = "exact_test"
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fake_img_np = np.zeros((10, 10, 3), dtype=np.uint8)
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_, encoded = cv2.imencode(".jpg", fake_img_np)
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fake_bytes = encoded.tobytes()
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# Sequences 1 and 11 stored in the same flight
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names = ["AD000001.jpg", "AD000011.jpg"]
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imgs = [fake_bytes, fake_bytes]
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b = ImageBatch(images=imgs, filenames=names, start_sequence=1, end_sequence=11, batch_number=1)
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pipeline.queue_batch(flight_id, b)
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await pipeline.process_next_batch(flight_id)
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img1 = pipeline.get_image_by_sequence(flight_id, 1)
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img11 = pipeline.get_image_by_sequence(flight_id, 11)
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assert img1 is not None
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assert img1.filename == "AD000001.jpg", f"Expected AD000001.jpg, got {img1.filename}"
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assert img11 is not None
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assert img11.filename == "AD000011.jpg", f"Expected AD000011.jpg, got {img11.filename}"
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def test_queue_full(pipeline):
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flight_id = "test_full"
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fake_imgs = [b"fake"] * 10
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fake_names = [f"AD{i:06d}.jpg" for i in range(1, 11)]
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b = ImageBatch(images=fake_imgs, filenames=fake_names, start_sequence=1, end_sequence=10, batch_number=1)
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pipeline.queue_batch(flight_id, b)
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pipeline.queue_batch(flight_id, b)
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with pytest.raises(QueueFullError):
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pipeline.queue_batch(flight_id, b)
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