Upgrade async GPU analysis and workbench UX
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@@ -61,6 +61,41 @@ class _UltralyticsSegmentationAdapterBase:
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message="Segmentation dependencies are not installed. Install backend optional extras with geointel-backend[ai].",
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status_code=503,
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)
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self.validate_runtime()
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def validate_runtime(self) -> None:
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"""Fail closed when the deployment contract requires NVIDIA CUDA.
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Detection and segmentation share ``YOLO_DEVICE`` and
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``YOLO_REQUIRE_CUDA``. Without this check segmentation could advertise
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a GPU job while Ultralytics silently used CPU or failed only after the
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model had already been loaded.
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"""
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if not self.settings.yolo_require_cuda:
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return
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try:
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import torch
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except Exception as exc:
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raise AppError(
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code="SEGMENTATION_ACCELERATOR_UNAVAILABLE",
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message="NVIDIA CUDA is required for configured segmentation, but PyTorch is not importable.",
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status_code=503,
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) from exc
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if not torch.cuda.is_available():
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raise AppError(
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code="SEGMENTATION_ACCELERATOR_UNAVAILABLE",
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message="NVIDIA CUDA is required for configured segmentation, but no CUDA device is available.",
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details={"configured_device": self.settings.yolo_device},
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status_code=503,
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)
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if not str(self.settings.yolo_device).lower().startswith(("cuda", "0", "1", "2", "3")):
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raise AppError(
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code="SEGMENTATION_ACCELERATOR_MISCONFIGURED",
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message="NVIDIA CUDA is required, but YOLO_DEVICE does not select a CUDA device.",
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details={"configured_device": self.settings.yolo_device},
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status_code=503,
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)
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def _predict(self, model, tile_path: Path, confidence_threshold: float) -> list[Any]:
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if not tile_path.exists() or not tile_path.is_file():
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