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.

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 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 Console. 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 from the Lab Details panel and paste it into the Sign in dialog. Click Next.

4. Copy the Password from the Lab Details panel and paste it into the Welcome dialog. Click Next.

   Important: You must use the credentials from the left panel. Do not use your Google Cloud Skills Boost credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

5. 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 Cloud Console opens in this tab.

Note: You can view the menu with a list of Google Cloud Products and Services by clicking 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 YOUR_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.

4. Your output should now look like this:

Output:

ACTIVE: * ACCOUNT: student-01-xxxxxxxxxxxx@qwiklabs.net To set the active account, run: $ gcloud config set account `ACCOUNT`

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

gcloud config list project

Output:

[core] project = <project_ID>

Example output:

[core] project = qwiklabs-gcp-44776a13dea667a6 Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Enable the Video Intelligence API

For this lab, the Cloud Video Intelligence API is enabled for you.

Task 2. Set up authorization

This lab creates and uses 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 3. Make an annotate video request

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!

Finish your quest

This self-paced lab is part of the Baseline: Deploy & Develop and Baseline: Data, ML, AI quests. A quest is a series of related labs that form a learning path. Completing a quest earns you a badge to recognize your achievement. You can make your badge or badges public and link to them in your online resume or social media account. Enroll in any quest that contains this lab and get immediate completion credit. See the Google Cloud Skills Boost catalog to see all available quests.

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 June 29, 2022

Lab Last Tested April 18, 2022

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