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# Default values for deepsight.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.
timeZone: "Asia/Calcutta" # Timezone for the application
cpuResourceType: low # Type of CPU resources (low, medium, high)
githubtoken: # GitHub token for private repository access
softwaretag: # Tag for software version
# Container Image Configuration
image:
pullPolicy: IfNotPresent # Image pull policy
imagePullSecrets: [name: "registrypullsecret"] # Image pull secrets for private registries
# Features Configuration (Block)
features:
entryexit: true # Enable or disable EntryExit feature
reactgui: true # Enable or disable React GUI feature
streamlitgui: true # Enable or disable Streamlit GUI feature
inference3: true # Enable or disable Inference3 feature
faceRecognition: true
videoSaving: true
# Database Configuration (Block)
database:
replicaCount: 1 # Number of database replicas
databasename: cam_db # Database name
containerName: database # Name of the database container
repository: mysql # Repository for the database image
tagName: debian # Tag for the database image
port: 3306 # Database port
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "0.8" # High resource limits for CPU
memory: "2G" # High resource limits for memory
requests:
cpu: "0.8" # High resource requests for CPU
memory: "2G" # High resource requests for memory
mysqlRootPassword: Dsal@123 # Root password for the MySQL database
mysqlUser: pi # Username for MySQL
mysqlPassword: raspberry # Password for the MySQL user
##FIXME - Remove fixed
args: ["--max_connections=2000"] # Additional command-line arguments
serviceName: database-service # Name of the database service
serviceType: ClusterIP # Service type for the database service
labels:
app: database # Labels for identifying the application
# Logs Configuration (Block)
logs:
replicaCount: 1 # Number of logs server replicas
containerName: logs-server # Name of the logs server container
repository: balabit/syslog-ng # Repository for the logs server image
tagName: 3.38.1 # Tag for the logs server image
port: 514 # Port for logs server
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "0.5" # High resource limits for CPU
memory: "2G" # High resource limits for memory
requests:
cpu: "0.5" # High resource requests for CPU
memory: "2G" # High resource requests for memory
serviceName: logs-server-service # Name of the logs server service
serviceType: ClusterIP # Service type for the logs server service
labels:
app: logs-server # Labels for identifying the application
# Inference Configuration (Block)
inference:
replicaCount: 1 # Number of inference replicas
containerName: inference1 # Name of the inference container
repository: openvino/model_server # Repository for the inference image
tagName: latest # Tag for the inference image
softwaretag: coal-india-updates # Tag for software version
# Model Weight Files
weightfile1:
xml: weights/13may_normal_yolov5s_openvino/13may22_yolov5s.xml # XML file for model weights
bin: weights/13may_normal_yolov5s_openvino/13may22_yolov5s.bin # Binary file for model weights
mapping: weights/13may_normal_yolov5s_openvino/13may22_yolov5s.mapping # Mapping file for model weights
weightfile2:
xml: weights/ppe/last.xml # XML file for another model's weights
bin: weights/ppe/last.bin # Binary file for another model's weights
mapping: weights/ppe/last.mapping # Mapping file for another model's weights
# Resource Configuration
metaResources:
low:
resources:
limits:
cpu: "1" # Low resource limits for CPU
memory: "2G" # Low resource limits for memory
requests:
cpu: "1" # Low resource requests for CPU
memory: "2G" # Low resource requests for memory
high:
resources:
limits:
cpu: "4" # High resource limits for CPU
memory: "8G" # High resource limits for memory
requests:
cpu: "4" # High resource requests for CPU
memory: "8G" # High resource requests for memory
serviceName: inference-service1 # Name of the inference service
serviceType: ClusterIP # Service type for the inference service
port: 9000 # Port for the inference service
grpcWorkers: 2 # Number of gRPC workers
labels:
app: inference1 # Labels for identifying the application
# Inference3 Configuration (Block)
inference3:
replicaCount: 1 # Number of inference3 replicas
containerName: inference3 # Name of the inference3 container
repository: openvino/model_server # Repository for the inference3 image
tagName: latest # Tag for the inference3 image
softwaretag: coal-india-updates # Tag for software version
# Model Weight Files for Inference3
weightfile1:
xml: weights/fire_0509/last.xml # XML file for fire detection model weights
bin: weights/fire_0509/last.bin # Binary file for fire detection model weights
mapping: weights/fire_0509/last.mapping # Mapping file for fire detection model weights
weightfile2:
xml: weights/vehicle/last.xml # XML file for vehicle detection model weights
bin: weights/vehicle/last.bin # Binary file for vehicle detection model weights
mapping: weights/vehicle/last.mapping # Mapping file for vehicle detection model weights
# Resource Configuration for Inference3
metaResources:
low:
resources:
limits:
cpu: "1" # Low resource limits for CPU
memory: "2G" # Low resource limits for memory
requests:
cpu: "1" # Low resource requests for CPU
memory: "2G" # Low resource requests for memory
high:
resources:
limits:
cpu: "4" # High resource limits for CPU
memory: "8G" # High resource limits for memory
requests:
cpu: "4" # High resource requests for CPU
memory: "8G" # High resource requests for memory
serviceName: inference-service3 # Name of the inference service
serviceType: ClusterIP # Service type for the inference service
port: 9000 # Port for the inference service
grpcWorkers: 2 # Number of gRPC workers
labels:
app: inference3 # Labels for identifying the application
# Video Saving Configuration (Block)
videoSaving:
replicaCount: 1 # Number of video saving replicas
containerName: video-saving # Name of the video-saving container
repository: deepsightailabs/rpi_image # Repository for the video-saving image
tagName: api.0.21.5 # Tag for the video-saving image
port: 8090 # Port for the video-saving service
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "5" # High resource limits for CPU
memory: "10G" # High resource limits for memory
requests:
cpu: "5" # High resource requests for CPU
memory: "10G" # High resource requests for memory
serviceName: video-saving-service # Name of the video-saving service
serviceType: ClusterIP # Service type for the video-saving service
labels:
app: video-saving # Labels for identifying the application
faceRecognition:
replicaCount: 1 # Number of video saving replicas
containerName: face-recognition # Name of the video-saving container
repository: deepsightailabs/rpi_image # Repository for the video-saving image
tagName: api.0.21.5 # Tag for the video-saving image
port: 8080 # Port for the video-saving service
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "5" # High resource limits for CPU
memory: "10G" # High resource limits for memory
requests:
cpu: "5" # High resource requests for CPU
memory: "10G" # High resource requests for memory
serviceName: face-recognition-service # Name of the video-saving service
serviceType: ClusterIP # Service type for the video-saving service
labels:
app: faceRecognition # Labels for identifying the application
# React GUI Configuration (Block)
react:
replicaCount: 1 # Number of React GUI replicas
containerName: react-gui # Name of the React GUI container
repository: deepsightailabs/rpi_image # Repository for the React GUI image
tagName: reactgui.2.0.9 # Tag for the React GUI image
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "1" # High resource limits for CPU
memory: "2G" # High resource limits for memory
requests:
cpu: "1" # High resource requests for CPU
memory: "2G" # High resource requests for memory
serviceName: react-gui-service # Name of the React GUI service
# TODO: If someone selects it as NodePort, they will use the following ports
serviceType: NodePort # Service type for the React GUI service
ports:
react:
port: 3000 # Port for the React application
nodePort: 31000 # NodePort for the React application
name: react # Name of the React application port
middleware:
port: 8000 # Port for the middleware
nodePort: 31002 # NodePort for the middleware
name: middleware # Name of the middleware port
labels:
app: react-gui # Labels for identifying the application
# License Configuration (Block)
license:
replicaCount: 1 # Number of license replicas
containerName: license # Name of the license container
repository: deepsightailabs/rpi_image # Repository for the license image
tagName: licnese17feb # Tag for the license image
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "1" # High resource limits for CPU
memory: "1G" # High resource limits for memory
requests:
cpu: "0.5" # High resource requests for CPU
memory: "800Mi" # High resource requests for memory
labels:
app: license # Labels for identifying the application
# Backend Configuration (Block)
backend:
minReplicaCount: 0 # Minimum number of backend replicas
maxReplicaCount: 5 # Maximum number of backend replicas
pollingInterval: 1 # Polling interval for backend scaling
cooldownPeriod: 1 # Cooldown period for backend scaling
labels:
app: backend # Labels for identifying the application
maxCamera: 10 # Maximum number of supported cameras
serviceName: headless-backend-service # Name of the backend service
containerName: backend # Name of the backend container
repository: deepsightailabs/rpi_image # Repository for the backend image
tagName: backend.0.21.5 # Tag for the backend image
metaResources:
low:
resources:
limits:
cpu: "2" # Low resource limits for CPU
memory: "4G" # Low resource limits for memory
requests:
cpu: "2" # Low resource requests for CPU
memory: "4G" # Low resource requests for memory
high:
resources:
limits:
cpu: "2" # High resource limits for CPU
memory: "4G" # High resource limits for memory
requests:
cpu: "2" # High resource requests for CPU
memory: "4G" # High resource requests for memory
# Streamlit GUI Configuration (Block)
streamlit:
replicaCount: 1 # Number of Streamlit GUI replicas
containerName: gui # Name of the Streamlit GUI container
repository: deepsightailabs/rpi_image # Repository for the Streamlit GUI image
tagName: backend.0.21.5 # Tag for the Streamlit GUI image
metaResources:
low:
resources: {} # Low resource configuration (CPU and memory limits/requests)
high:
resources:
limits:
cpu: "0.5" # High resource limits for CPU
memory: "1G" # High resource limits for memory
requests:
cpu: "0.5" # High resource requests for CPU
memory: "1G" # High resource requests for memory
serviceName: streamlit-gui-service # Name of the Streamlit GUI service
# TODO: If someone selects it as NodePort, they will use the following ports
serviceType: LoadBalancer # Service type for the Streamlit GUI service
ports:
autosetup:
port: 8501 # Port for Streamlit GUI autosetup
nodePort: 30051 # NodePort for Streamlit GUI autosetup
name: autosetup # Name of the autosetup port
dashboard:
port: 8502 # Port for Streamlit GUI dashboard
nodePort: 30052 # NodePort for Streamlit GUI dashboard
name: dashboard # Name of the dashboard port
labels:
app: streamlit-gui # Labels for identifying the application
# EntryExit Configuration (Block)
entryexit:
minReplicaCount: 0 # Minimum number of EntryExit replicas
maxReplicaCount: 5 # Maximum number of EntryExit replicas
pollingInterval: 1 # Polling interval for EntryExit scaling
cooldownPeriod: 1 # Cooldown period for EntryExit scaling
labels:
app: entryexit # Labels for identifying the application
maxCamera: 10 # Maximum number of supported cameras
serviceName: headless-entryexit-service # Name of the EntryExit service
containerName: entryexit # Name of the EntryExit container
repository: deepsightailabs/rpi_image # Repository for the EntryExit image
tagName: backend.0.21.5 # Tag for the EntryExit image
metaResources:
low:
resources:
limits:
cpu: "3" # Low resource limits for CPU
memory: "5G" # Low resource limits for memory
requests:
cpu: "3" # Low resource requests for CPU
memory: "5G" # Low resource requests for memory
high:
resources:
limits:
cpu: "5" # High resource limits for CPU
memory: "10G" # High resource limits for memory
requests:
cpu: "5" # High resource requests for CPU
memory: "10G" # High resource requests for memory
# Persistent Volume Claims Configuration (Block)
persistentVolumeCalim:
database: database-pv-claim # Name of the database persistent volume claim
commonFiles: common-files-claim # Name of the common files persistent volume claim
logs: pv-serverlogs-claim # Name of the server logs persistent volume claim
savedVideo: shared-video-files-claim # Name of the shared video files persistent volume claim
alertImage: shared-files-claim # Name of the shared alert image persistent volume claim
videoFrame: shared-frames-files-claim # Name of the shared frames files persistent volume claim
modelData: model-data-claim # Name of the model data persistent volume claim
frData: fr-data-claim
# Persistent Volumes Configuration (Block)
persistentVolume:
# USE FULL PATH, don't use any variable like BASH Variables
basepath: /mnt/k8s/ # Base path for persistent volumes
commonFiles:
name: common-files # Name of the common files persistent volume
labels:
type: local # Labels for identifying the volume type
name: common-files-tag # Labels for identifying the volume name
path: "common_files" # Path within the volume
storageCapacity: 1Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
database:
name: database-pv # Name of the database persistent volume
labels:
type: local # Labels for identifying the volume type
name: database-tag # Labels for identifying the volume name
path: "database" # Path within the volume
storageCapacity: 5Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
logs:
name: pv-serverlogs # Name of the server logs persistent volume
labels:
type: local # Labels for identifying the volume type
name: serverlogsfolder # Labels for identifying the volume name
path: "serverlogs" # Path within the volume
storageCapacity: 30Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
savedVideo:
name: shared-video-files # Name of the shared video files persistent volume
labels:
type: local # Labels for identifying the volume type
name: shared-video-files-tag # Labels for identifying the volume name
path: "shared-video-files" # Path within the volume
storageCapacity: 30Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
alertImage:
name: shared-files # Name of the shared alert image persistent volume
labels:
type: local # Labels for identifying the volume type
name: shared-files-tag # Labels for identifying the volume name
path: "shared-files" # Path within the volume
storageCapacity: 15Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
videoFrame:
name: shared-frames-files # Name of the shared frames files persistent volume
labels:
type: local # Labels for identifying the volume type
name: shared-frames-files-tag # Labels for identifying the volume name
path: "shared-frames-files" # Path within the volume
storageCapacity: 15Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
frData:
name: fr-data-files # Name of the shared frames files persistent volume
labels:
type: local # Labels for identifying the volume type
name: fr-data-files-tag # Labels for identifying the volume name
path: "fr-data-files" # Path within the volume
storageCapacity: 60Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
modelData:
name: model-data # Name of the model data persistent volume
labels:
type: local # Labels for identifying the volume type
name: model-tag # Labels for identifying the volume name
path: "models" # Path within the volume
storageCapacity: 1Gi # Storage capacity for the volume
storageClassName: manual # Storage class name for the volume
# ConfigMap Configuration (Block)
configMap:
database: sql-init-config # Name of the ConfigMap for database initialization
syslogConf: configmap-syslog-conf # Name of the ConfigMap for syslog configuration
syslogConfig: configmap-syslog-config # Name of the ConfigMap for syslog configuration
inferenceConfig1: inference-config-1 # Name of the ConfigMap for inference configuration 1
inferenceConfig3: inference-config-3 # Name of the ConfigMap for inference configuration 3
nameOverride: ""
fullnameOverride: ""
serviceAccount:
# Specifies whether a service account should be created
create: false
# Annotations to add to the service account
annotations: {}
# The name of the service account to use.
# If not set and create is true, a name is generated using the fullname template
name: ""
podAnnotations: {}
podSecurityContext:
{}
# fsGroup: 2000
securityContext:
{}
# capabilities:
# drop:
# - ALL
# readOnlyRootFilesystem: true
# runAsNonRoot: true
# runAsUser: 1000
# service:
# type: ClusterIP
# port: 80
# ingress:
# enabled: false
# className: ""
# annotations:
# {}
# # kubernetes.io/ingress.class: nginx
# # kubernetes.io/tls-acme: "true"
# hosts:
# - host: chart-example.local
# paths:
# - path: /
# pathType: ImplementationSpecific
# tls: []
# # - secretName: chart-example-tls
# # hosts:
# # - chart-example.local
# resources:
# {}
# # We usually recommend not to specify default resources and to leave this as a conscious
# # choice for the user. This also increases chances charts run on environments with little
# # resources, such as Minikube. If you do want to specify resources, uncomment the following
# # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
# # limits:
# # cpu: 100m
# # memory: 128Mi
# # requests:
# # cpu: 100m
# # memory: 128Mi
# autoscaling:
# enabled: false
# minReplicas: 1
# maxReplicas: 100
# targetCPUUtilizationPercentage: 80
# # targetMemoryUtilizationPercentage: 80
nodeSelector: {}
tolerations: []
affinity: {}