sedna/examples/joint_inference/helmet_detection_inference/helmet_detection_inference.yaml

apiVersion: sedna.io/v1alpha1
kind: JointInferenceService
metadata:
  name: helmet-detection-inference-example
  namespace: default
spec:
  edgeWorker:
    model:
      name: "helmet-detection-inference-little-model"
    hardExampleMining:
      name: "IBT"
      parameters:
        - key: "threshold_img"
          value: "0.9"
        - key: "threshold_box"
          value: "0.9"
    template:
      spec:
        nodeName: $EDGE_NODE
        containers:
          - image: kubeedge/sedna-example-joint-inference-helmet-detection-little:v0.3.0
            imagePullPolicy: IfNotPresent
            name: little-model
            env: # user defined environments
              - name: input_shape
                value: "416,736"
              - name: "video_url"
                value: "rtsp://localhost/video"
              - name: "all_examples_inference_output"
                value: "/data/output"
              - name: "hard_example_cloud_inference_output"
                value: "/data/hard_example_cloud_inference_output"
              - name: "hard_example_edge_inference_output"
                value: "/data/hard_example_edge_inference_output"
            resources: # user defined resources
              requests:
                memory: 64M
                cpu: 100m
              limits:
                memory: 2Gi
            volumeMounts:
              - name: outputdir
                mountPath: /data/
        volumes: # user defined volumes
          - name: outputdir
            hostPath:
              # user must create the directory in host
              path: /joint_inference/output
              type: Directory

  cloudWorker:
    model:
      name: "helmet-detection-inference-big-model"
    template:
      spec:
        nodeName: $CLOUD_NODE
        containers:
          - image: kubeedge/sedna-example-joint-inference-helmet-detection-big:v0.3.0
            name: big-model
            imagePullPolicy: IfNotPresent
            env: # user defined environments
              - name: "input_shape"
                value: "544,544"
            resources: # user defined resources
              requests:
                memory: 2Gi