metadata:
  name: custom-model-yolov8
  namespace: cvat
  annotations:
    name: custom-model-yolov8
    type: detector
    framework: pytorch
    # change this accordingly to your model output/classes
    spec: |
      [
        {"id": 0, "name": "bicycle_rider"}
      ]
spec:
  description: custom-model-yolov8
  runtime: 'python:3.9'
  handler: main:handler
  eventTimeout: 30s

  build:
    image: custom-model-yolov8
    baseImage: ubuntu:22.04

    directives:
      preCopy:
        - kind: ENV
          value: DEBIAN_FRONTEND=noninteractive
        - kind: RUN
          value: apt-get update && apt-get -y install curl git python3 python3-pip 
        - kind: RUN
          value: apt-get -y install libgl1-mesa-glx libglib2.0-dev
        - kind: WORKDIR
          value: /opt/nuclio
          #
          # make sure that for the next step (at least) the ultralytics package version
          # is compatible to that of the the ultralytics package used to train the custom model
        - kind: RUN
          value: pip3 install ultralytics==8.0.114 opencv-python==4.7.0.72 numpy==1.24.3
          #
        - kind: RUN
          value: ln -s /usr/bin/pip3 /usr/local/bin/pip
        - kind: RUN
          value: ln -s /usr/bin/python3 /usr/local/bin/python

  triggers:
    myHttpTrigger:
      maxWorkers: 1
      kind: 'http'
      workerAvailabilityTimeoutMilliseconds: 10000
      attributes:
        maxRequestBodySize: 33554432 # 32MB

  platform:
    attributes:
      restartPolicy:
        name: always
        maximumRetryCount: 3
      mountMode: volume