GSP154

Overview

Google Cloud Video Intelligence makes videos searchable and discoverable by extracting metadata with an easy to use REST API. You can now search every moment of every video file in your catalog. It quickly annotates videos stored in Cloud Storage, and helps you identify key entities (nouns) within your video; and when they occur within the video. Separate signal from noise by retrieving relevant information within the entire video, shot-by-shot, -or per frame.

What you'll do

In this lab, you learn how to:

• Set up authorization for a custom service account
• Send an annotate video request to the Video Intelligence API

Setup and requirements

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.

This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

• Access to a standard internet browser (Chrome browser recommended).

Note: Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.

• Time to complete the lab---remember, once you start, you cannot pause a lab.

Note: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your account.

How to start your lab and sign in to the Google Cloud console

1. Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:

   • The Open Google Cloud console button
   • Time remaining
   • The temporary credentials that you must use for this lab
   • Other information, if needed, to step through this lab

2. Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).

   The lab spins up resources, and then opens another tab that shows the Sign in page.

   Tip: Arrange the tabs in separate windows, side-by-side.

   Note: If you see the Choose an account dialog, click Use Another Account.

3. If necessary, copy the Username below and paste it into the Sign in dialog.

   {{{user_0.username | "Username"}}}

   You can also find the Username in the Lab Details panel.

4. Click Next.

5. Copy the Password below and paste it into the Welcome dialog.

   {{{user_0.password | "Password"}}}

   You can also find the Password in the Lab Details panel.

6. Click Next.

   Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

7. Click through the subsequent pages:

   • Accept the terms and conditions.
   • Do not add recovery options or two-factor authentication (because this is a temporary account).
   • Do not sign up for free trials.

After a few moments, the Google Cloud console opens in this tab.

Note: To view a menu with a list of Google Cloud products and services, click the Navigation menu at the top-left.

Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

1. Click Activate Cloud Shell at the top of the Google Cloud console.

When you are connected, you are already authenticated, and the project is set to your Project_ID, . The output contains a line that declares the Project_ID for this session:

Your Cloud Platform project in this session is set to {{{project_0.project_id | "PROJECT_ID"}}}

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

2. (Optional) You can list the active account name with this command:

gcloud auth list

3. Click Authorize.

Output:

ACTIVE: * ACCOUNT: {{{user_0.username | "ACCOUNT"}}} To set the active account, run: $ gcloud config set account `ACCOUNT`

4. (Optional) You can list the project ID with this command:

gcloud config list project

Output:

[core] project = {{{project_0.project_id | "PROJECT_ID"}}} Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Set up authorization

For this lab, you create and use a service account that is tied to your Google Cloud project for authorization.

1. In Cloud Shell, run the following command to create a new service account named quickstart:

gcloud iam service-accounts create quickstart

2. Create a service account key file, replacing <your-project-123> with your Project ID:

gcloud iam service-accounts keys create key.json --iam-account quickstart@<your-project-123>.iam.gserviceaccount.com

3. Now authenticate your service account, passing the location of your service account key file:

gcloud auth activate-service-account --key-file key.json

4. Obtain an authorization token using your service account:

gcloud auth print-access-token

The token will print in the output, and you'll be using it in a future step.

Click Check my progress to verify the objective. Set up authorization

Task 2. Make an annotate video request

Note: In this lab, the Cloud Video Intelligence API is already enabled for you.

1. Run this command to create a JSON request file with the following text, and save it as request.json :

cat > request.json <<EOF { "inputUri":"gs://spls/gsp154/video/train.mp4", "features": [ "LABEL_DETECTION" ] } EOF Note: To make the process simpler, a public video of a train available to your project is used as the value for your inputUri. If preferred or running in a personal project, any video can be used in place by uploading it to Cloud Storage and providing its Cloud Storage URI (format: `gs://bucket/object`) for the value of inputUri.

2. Use curl to make a videos:annotate request passing the filename of the entity request:

curl -s -H 'Content-Type: application/json' \ -H 'Authorization: Bearer '$(gcloud auth print-access-token)'' \ 'https://videointelligence.googleapis.com/v1/videos:annotate' \ -d @request.json

The Video Intelligence API creates an operation to process your request. You should now see a response that includes your operation name, which should look similar to this one:

{ "name": "projects/474887704060/locations/asia-east1/operations/16366331060670521152" }

You will use this operation name, locations and projects in the future step.

3. Use this script to request information on the operation by calling the v1.operations endpoint. Replace the PROJECTS, LOCATIONS and OPERATION_NAME with the value you just received in the previous command:

curl -s -H 'Content-Type: application/json' \ -H 'Authorization: Bearer '$(gcloud auth print-access-token)'' \ 'https://videointelligence.googleapis.com/v1/projects/PROJECTS/locations/LOCATIONS/operations/OPERATION_NAME'

You'll now see information related to your operation. If the operation has completed, a done field is included and set to true:

{ "name": "projects/425437283751/locations/asia-east1/operations/17938636079131796601", "metadata": { "@type": "type.googleapis.com/google.cloud.videointelligence.v1.Annota tionProgressMetadata", "progressMetadata": [ { "inputUri": "gs://spls/gsp154/video/train.mp4", "startTime": "2016-09-22T21:41:56.766091Z", "lastUpdateTime": "2016-09-22T21:42:03.889743Z" } ] }, ... }

4. After giving the request some time (about a minute, typically), re-run the command and the same request returns annotated results:

{ "name": "projects/425437283751/locations/asia-east1/operations/17938636079131796601", "metadata": { "@type": "type.googleapis.com/google.cloud.videointelligence.v1.AnnotateVideoProgress", "annotationProgress": [ { "inputUri": "/spls/gsp154/video/train.mp4", "progressPercent": 100, "startTime": "2017-02-17T22:39:00.333942Z", "updateTime": "2017-02-17T22:39:11.414399Z" } ] }, "done": true, "response": { "@type": "type.googleapis.com/google.cloud.videointelligence.v1.AnnotateVideoResponse", "annotationResults": [ { "inputUri": "/spls/gsp154/video/train.mp4", "segmentLabelAnnotations": [ { "entity": { "entityId": "/m/01yrx", "languageCode": "en-US" }, "segments": [ { "segment": { "startTimeOffset": "0s", "endTimeOffset": "14.833664s" }, "confidence": 0.98509187 } ] }, ...

You've sent your first request to Cloud Video Intelligence API.

Click Check my progress to verify the objective. Make an annotate video request

Congratulations!

You sent an annotate video request to the Video Intelligence API and received results.

Next steps / Learn more

This lab is also part of a series of labs called Qwik Starts. These labs are designed to give you a little taste of the many features available with Google Cloud. Search for "Qwik Starts" in the Google Cloud Skills Boost catalog to find the next lab you'd like to take!

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Manual Last Updated February 04, 2024

Lab Last Tested December 22, 2023

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