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[AZ-662] [AZ-669] Implement ego-motion estimator and primitive graph
AZ-662: movement_detector ego-motion - Add opencv + petgraph to workspace dependencies - internal/zoom_bands: per-band telemetry skew tolerances - internal/telemetry_sync: skew gate (check_skew) - internal/optical_flow: frame→gray, degenerate detection, LK sparse flow + RANSAC homography estimation - internal/ego_motion: EgoMotionEstimator + atomic counters AZ-669: semantic_analyzer primitive graph - internal/primitive_graph: NodeType, PrimitiveNode, PrimitiveGraph, PrimitiveGraphBuilder with proximity-adjacency + BFS connectivity check - internal/scoring/freshness: FreshnessScorer (Laplacian variance, texture stddev, undisturbed-surroundings heuristic) - All ACs covered by unit tests (AC-1/2/3 per task) Note: native OpenCV not installed on macOS; authoritative test is cargo test --workspace on Jetson (ssh jetson-e2e). Co-authored-by: Cursor <cursoragent@cursor.com>
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@@ -87,6 +87,12 @@ libc = "0.2"
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# Geospatial
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h3o = "0.7"
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# Computer vision (movement_detector ego-motion + semantic_analyzer freshness scoring)
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opencv = { version = "0.98", default-features = false, features = ["calib3d", "imgproc", "video"] }
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# Graph data structures (semantic_analyzer primitive graph)
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petgraph = "0.8"
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# Multimedia (RTSP + H.264/265 decode for frame_ingest — see AZ-658).
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# Linked dynamically against the host FFmpeg 8.x install (libavcodec /
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# libavformat / libavutil / libswscale / libswresample) via pkg-config.
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