69 lines
2.0 KiB
YAML
69 lines
2.0 KiB
YAML
metadata:
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name: emdetector
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namespace: cvat
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annotations:
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name: EM14 v1
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type: detector
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framework: pytorch
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spec: |
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[
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{ "id": 0, "name": "EM14", "type": "rectangle" },
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{ "id": 1, "name": "EM18", "type": "rectangle" },
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{ "id": 2, "name": "EM17", "type": "rectangle" },
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{ "id": 3, "name": "EM170", "type": "rectangle" },
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{ "id": 4, "name": "EM19", "type": "rectangle" },
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{ "id": 5, "name": "EM190", "type": "rectangle" },
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{ "id": 6, "name": "EM20", "type": "rectangle" },
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{ "id": 7, "name": "EM200", "type": "rectangle" },
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{ "id": 8, "name": "EM201", "type": "rectangle" },
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{ "id": 9, "name": "EM202", "type": "rectangle" },
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{ "id": 10, "name": "EM203", "type": "rectangle" }
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]
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spec:
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description: 工位检测
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runtime: "python:3.9"
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handler: main:handler
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eventTimeout: 30s
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build:
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image: cvat.pth.yolo8.emdetector:latest-gpu
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baseImage: python:3.9
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directives:
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preCopy:
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- kind: ENV
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value: DEBIAN_FRONTEND=noninteractive
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- kind: RUN
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value: apt-get update && apt-get install -y libgl1 libglib2.0-0 && apt-get clean
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- kind: RUN
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value: pip install ultralytics torch torchvision opencv-python-headless && pip cache purge
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triggers:
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myHttpTrigger:
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numWorkers: 1
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kind: 'http'
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workerAvailabilityTimeoutMilliseconds: 10000
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attributes:
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# Set value from the calculation of tracking of 100 objects at the same time on a 4k image
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maxRequestBodySize: 268435456 # 256MB
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volumes:
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- volume:
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name: model-volume
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hostPath:
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path: /DATA/wjl/cvat/models/best.pt # 可选：如果使用HostPath挂载模型
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volumeMount:
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name: model-volume
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mountPath: /opt/nuclio/best.pt
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resources:
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limits:
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nvidia.com/gpu: 1
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platform:
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attributes:
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restartPolicy:
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name: always
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maximumRetryCount: 3
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mountMode: volume
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