Scanning User-generated Content Using the Cloud Video Intelligence and Cloud Vision APIs
Social marketing campaigns often invite consumers to submit user-generated images and videos. Campaigns that solicit videos and images often use them for contest submissions, product testimonials, or as user-generated content for public campaign websites. Processing these submissions at scale requires considerable resources. The Cloud Video Intelligence and Cloud Vision APIs offer you a scalable and serverless way to implement intelligent image and video filtering, accelerating submission processing. If you use the safe-search feature in the Vision API solution and the explicit content detection feature in the Video Intelligence API, you can eliminate images and videos that are identified as unsafe or undesirable content before further processing.
- Deploy four Cloud Functions.
- Create the supporting Cloud Storage buckets, Cloud Pub/Sub topics, and Cloud Storage Pub/Sub Notifications.
- Create the supporting BigQuery dataset and table.
Image files and/or video files that you can upload into the lab for analysis. Ideally they would be of different types - with people whose faces can be seen, no people, landscape, close-ups - so you can see how the image analysis treats the image. You can also just use a single image or video.
Setup and Requirements
What you'll need
To complete this lab, you'll need:
- Access to a standard internet browser (Chrome browser recommended).
- Time. Note the lab's Completion time in Qwiklabs, which is an estimate of the time it should take to complete all steps. Plan your schedule so you have time to complete the lab. Once you start the lab, you will not be able to pause and return later (you begin at step 1 every time you start a lab).
- You do NOT need a Google Cloud Platform account or project. An account, project and associated resources are provided to you as part of this lab.
- If you already have your own GCP account, make sure you do not use it for this lab.
- If your lab prompts you to log into the console, use only the student account provided to you by the lab. This prevents you from incurring charges for lab activities in your personal GCP account.
Start your lab
When you are ready, click Start Lab. You can track your lab's progress with the status bar at the top of your screen.
Find Your Lab's GCP Username and Password
To access the resources and console for this lab, locate the Connection Details panel in Qwiklabs. Here you will find the account ID and password for the account you will use to log in to the Google Cloud Platform:
If your lab provides other resource identifiers or connection-related information, it will appear on this panel as well.
Log in to Google Cloud Console
Using the Qwiklabs browser tab/window (preferably in Incognito mode) or the separate browser you are using for the Qwiklabs session, copy the Username from the Connection Details panel and click the orange "Open Google Console" button. Paste in the Username, and then the Password as prompted:
Accept the terms and conditions.
Since this is a temporary account, which you will only have access to for this one lab:
- Do not add recovery options
- Do not sign up for free trials
Activate Google Cloud Shell
From the GCP Console click the Cloud Shell icon on the top right toolbar:
Then click "Start Cloud Shell":
It should only take a few moments to provision and connect to the environment:
This virtual machine is loaded with all the development tools you'll need. It offers a persistent 5GB home directory, and runs on the Google Cloud, greatly enhancing network performance and authentication. Much, if not all, of your work in this lab can be done with simply a browser or your Google Chromebook.
Once connected to the cloud shell, you should see that you are already authenticated and that the project is already set to your PROJECT_ID:
gcloud auth list
Credentialed accounts: - <myaccount>@<mydomain>.com (active)
gcloud config list project
[core] project = <PROJECT_ID>
If it is not, you can set it with this command:
gcloud config set project <PROJECT_ID>
Updated property [core/project].
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