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Added camera config
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@@ -32,7 +32,7 @@ graph LR
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| Cython inference pipeline | Python 3, Cython 3.1.3, OpenCV 4.10 | Near-C performance for tight detection loops while retaining Python ecosystem | Build complexity, limited IDE/debug support | Compilation step via setup.py | N/A | Low (open-source) | High — critical for postprocessing throughput |
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| Dual engine strategy (TensorRT + ONNX) | TensorRT 10.11, ONNX Runtime 1.22 | Maximum GPU speed with CPU fallback; auto-conversion and caching | Two code paths; GPU-specific engine files not portable | NVIDIA GPU (CC ≥ 6.1) for TensorRT | N/A | TensorRT free for NVIDIA GPUs | High — balances performance and portability |
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| FastAPI HTTP service | FastAPI, Uvicorn, Pydantic | Async SSE, auto-generated docs, fast development | Sync inference offloaded to ThreadPoolExecutor (2 workers) | Python 3.8+ | Bearer token pass-through | Low (open-source) | High — fits async streaming + sync inference pattern |
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| GSD-based image tiling | OpenCV, NumPy | Preserves small object detail in large aerial images | Complex tile dedup logic; overlap increases compute | Camera metadata (altitude, focal length, sensor width) | N/A | Compute cost scales with image size | High — essential for aerial imagery use case |
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| GSD-based image tiling | OpenCV, NumPy | Preserves small object detail in large aerial images | Complex tile dedup logic; overlap increases compute | Camera metadata (`camera_config`: height, angle, zoom, focal length, sensor width) | N/A | Compute cost scales with image size | High — essential for aerial imagery use case |
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| Lazy engine initialization | pynvml, threading | Fast API startup; background model conversion | First request has high latency; engine may be unavailable | None | N/A | N/A | High — prevents blocking startup on slow model download/conversion |
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## 3. Testing Strategy
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