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{
    "name": "log_analytics_data_movement",
    "properties": {
        "activities": [
            {
                "name": "log_analytics_data_movement",
                "type": "Copy",
                "dependsOn": [],
                "policy": {
                    "timeout": "7.00:00:00",

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# Define the variables
$log_Analytics_Workspace_Resource_Group_Name = 'PLEASE_ENTER_YOUR_OWNED_LOG_ANALYTICS_WORKSPACE_RESOURCE_GROUP_NAME'
$log_Analytics_Workspace_Name = 'PLEASE_ENTER_YOUR_OWNED_LOG_ANALYTICS_WORKSPACE_NAME'
$log_Analytics_Export_Rule_Name = 'PLEASE_ENTER_RULE_NAME_TO_BE_CREATE'
$storageAccountResourceId = 'PLEASE_ENTER_YOUR_OWNED_BLOB_STORAGE_RESOURCE_PROPERTIES'

# Create new rule for Log Analytics export Container Insight and AKS related logs into Blob Storage
az monitor log-analytics workspace data-export create --resource-group $log_Analytics_Workspace_Resource_Group_Name --workspace-name $log_Analytics_Workspace_Name --name dnilaw01tostore01 --tables Heartbeat ContainerInventory ContainerImageInventory ContainerLog ContainerLogV2 ContainerNodeInventory ContainerServiceLog KubeEvents KubeHealth KubeMonAgentEvents KubeNodeInventory KubePodInventory KubeServices --destination $storageAccountResourceId

# Check newly created export rule

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    k = cv2.waitKey(1)
    if k%256 == 27:
        # ESC pressed
        print("Escape hit, closing...")
        break

# Release camera
cam.release()

# Close all camera windows

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        # Show CV2 circle points overlay on camera stream
        cv2.imshow('face_landmarks', pupilLeft)
        cv2.imshow('face_landmarks', pupilRight)
        cv2.imshow('face_landmarks', noseTip)
        cv2.imshow('face_landmarks', mouthLeft)
        cv2.imshow('face_landmarks', mouthRight)
        cv2.imshow('face_landmarks', eyebrowLeftOuter)
        cv2.imshow('face_landmarks', eyebrowLeftInner)
        cv2.imshow('face_landmarks', eyeLeftInner)
        cv2.imshow('face_landmarks', eyeLeftTop)

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        # Define CV2 circle points by face landmarks x y position
        pupilLeft = cv2.circle(frame,(int(pupilLeft['x']), int(pupilLeft['y'])), 8, (0, 0, 255), -1)
        pupilRight = cv2.circle(frame,(int(pupilRight['x']), int(pupilRight['y'])), 8, (0, 0, 255), -1)
        noseTip = cv2.circle(frame,(int(noseTip['x']), int(noseTip['y'])), 8, (0, 0, 255), -1)
        mouthLeft = cv2.circle(frame,(int(mouthLeft['x']), int(mouthLeft['y'])), 8, (0, 0, 255), -1)
        mouthRight = cv2.circle(frame,(int(mouthRight['x']), int(mouthRight['y'])), 8, (0, 0, 255), -1)
        eyebrowLeftOuter = cv2.circle(frame,(int(eyebrowLeftOuter['x']), int(eyebrowLeftOuter['y'])), 8, (0, 0, 255), -1)
        eyebrowLeftInner = cv2.circle(frame,(int(eyebrowLeftInner['x']), int(eyebrowLeftInner['y'])), 8, (0, 0, 255), -1)
        eyeLeftInner = cv2.circle(frame,(int(eyeLeftInner['x']), int(eyeLeftInner['y'])), 8, (0, 0, 255), -1)
        eyeLeftTop = cv2.circle(frame,(int(eyeLeftTop['x']), int(eyeLeftTop['y'])), 8, (0, 0, 255),

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        # Measure value between Left eye bottom and top position
        eyeLeftvalue =  int(eyeLeftBottom['y']) - int(eyeLeftTop['y'])
        # Define distance value for left eye blinking
        eyeLeftcloseValue = 20
        # Show Left Eye Blinking message if distance between top and bottom is lower than defined value
        if eyeLeftvalue < eyeLeftcloseValue:
            eyeLeftvalueMsg = cv2.putText(frame, "Left Eye Blinking", (50, 50), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 0, 255), 1, cv2.LINE_AA)
            cv2.imshow('face_landmarks', eyeLeftvalueMsg)

        # Measure value between Right eye bottom and top position

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    # Parse collected face landmarks into variables
    for face in faces:
        flm = face['faceLandmarks']
        pupilLeft = flm['pupilLeft']
        pupilRight = flm['pupilRight']
        noseTip = flm['noseTip']
        mouthLeft = flm['mouthLeft']
        mouthRight = flm['mouthRight']
        eyebrowLeftOuter = flm['eyebrowLeftOuter']
        eyebrowLeftInner = flm['eyebrowLeftInner']

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# While loop to continuously process the video frames 
while True:
    ret, frame = cam.read()
    if not ret:
        print("failed to grab frame")
        break
    cv2.imshow("face", frame)
    # Post video frames to Azure Face Service to obtain face landmarks
    image = cv2.imencode('.jpg', frame)[1].tostring()
    subscription_key = KEY

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# Initialize camera by CV2
cam = cv2.VideoCapture(0)
cv2.namedWindow("face")
img_counter = 0

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# Define Azure Face Service key and endpoint
KEY = "PLEASE_ENTER_YOUR_OWN_AZURE_FACE_SERVICE_KEY"
ENDPOINT = "https://PLEASE_ENTER_YOUR_OWN_AZURE_FACE_SERVICE_ENDPOINT_NAME.cognitiveservices.azure.com/"

# Define the Face Service client
face_client = FaceClient(ENDPOINT, CognitiveServicesCredentials(KEY))