function-gpu.yaml

metadata:
  name: pth-dschoerk-transt
  namespace: cvat
  annotations:
    name: TransT
    type: tracker
    spec:

spec:
  description: Fast Online Object Tracking and Segmentation
  runtime: 'python:3.8'
  handler: main:handler
  eventTimeout: 30s
  env:
    - name: PYTHONPATH
      value: /opt/nuclio/trans-t

  build:
    image: cvat.pth.dschoerk.transt:latest-gpu
    baseImage: nvidia/cuda:11.7.1-devel-ubuntu20.04

    directives:
      preCopy:
        - kind: RUN
          value: |-
            apt update \
              && apt install -y --no-install-recommends \
                git \
                ca-certificates \
                python-is-python3 \
                python3 \
                python3-pip \
              && rm -rf /var/lib/apt/lists/*
        - kind: WORKDIR
          value: /opt/nuclio
        - kind: RUN
          value: git clone --depth 1 --branch v1.0 https://github.com/dschoerk/TransT trans-t
        - kind: RUN
          value: |-
            pip install \
              jsonpickle opencv-python-headless \
              torch==1.7.1+cu110 torchvision==0.8.2+cu110 \
              --extra-index-url https://download.pytorch.org/whl/cu110
        - kind: ADD
          value: https://drive.google.com/uc?id=1Pq0sK-9jmbLAVtgB9-dPDc2pipCxYdM5 /transt.pth

  triggers:
    myHttpTrigger:
      maxWorkers: 1
      kind: 'http'
      workerAvailabilityTimeoutMilliseconds: 10000
      attributes:
        # Set value from the calculation of tracking of 100 objects at the same time on a 4k image
        maxRequestBodySize: 268435456 # 256MB

  resources:
    limits:
      nvidia.com/gpu: 1

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