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环境:
/opt/sedna/build/crds
# YAML 存放位置:https://github.com/kubeedge/sedna/tree/main/build/crds
# 主要拉取的就是这几个YAML文件, 当然还有另外一个gm文件夹,你如果拉取不下来,也可以仿造
sedna.io_datasets.yaml
sedna.io_federatedlearningjobs.yaml
sedna.io_incrementallearningjobs.yaml
sedna.io_jointinferenceservices.yaml
sedna.io_lifelonglearningjobs.yaml
sedna.io_models.yaml
download_yamls函数
download_yamls() {
yaml_files=(
sedna.io_datasets.yaml
sedna.io_federatedlearningjobs.yaml
sedna.io_incrementallearningjobs.yaml
sedna.io_jointinferenceservices.yaml
sedna.io_lifelonglearningjobs.yaml
sedna.io_models.yaml
)
#只需要注释掉这一行就好了,然后通过bash命令启动,这个修改好的shell脚本
# _download_yamls build/crds
yaml_files=(
gm.yaml
)
_download_yamls build/gm/rbac
}
一行命令安装:
curl https://raw.githubusercontent.com/kubeedge/sedna/main/scripts/installation/install.sh
手动设置安装:
https://raw.githubusercontent.com/kubeedge/sedna/main/scripts/installation/install.sh
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
dnsPolicy: ClusterFirstWithHostNet <----------- LOOK AT HERE!!!
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