Hello video data: Set up your project and environment

If you plan to use the Vertex AI SDK for Python, make sure that the service account initializing the client has the Vertex AI Service Agent (roles/aiplatform.serviceAgent) IAM role.

This tutorial has several pages:

1. Setting up your project.

2. Creating a video classification dataset.

3. Training an AutoML video classification model.

4. Deploying the model for batch predictions.

5. Cleaning up your project.

Each page assumes that you've already performed the instructions from the previous pages of the tutorial.

Set up your project and environment

Throughout this tutorial use Google Cloud console to interact with Google Cloud. Complete the following steps before using Vertex AI functionality.

1. In the Google Cloud console, go to the project selector page.

   Go to project selector

2. Select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

3. Make sure that billing is enabled for your Google Cloud project.

4. Open Cloud Shell. Cloud Shell is an interactive shell environment for Google Cloud that lets you manage your projects and resources from your web browser.
Go to Cloud Shell
5. In the Cloud Shell, set the current project to your Google Cloud project ID and store it in the projectid shell variable:

     gcloud config set project PROJECT_ID &&
     projectid=PROJECT_ID &&
     echo $projectid

   Replace PROJECT_ID with your project ID. You can locate your project ID in the Google Cloud console. For more information, see Find your project ID.

6. Enable the IAM, Compute Engine, Notebooks, Cloud Storage, and Vertex AI APIs:

   gcloud services enable iam.googleapis.com  compute.googleapis.com notebooks.googleapis.com storage.googleapis.com aiplatform.googleapis.com

7. Grant roles to your user account. Run the following command once for each of the following IAM roles: roles/aiplatform.user, roles/storage.admin

   gcloud projects add-iam-policy-binding PROJECT_ID --member="user:USER_IDENTIFIER" --role=ROLE

   • Replace PROJECT_ID with your project ID.

   • Replace USER_IDENTIFIER with the identifier for your user account. For example, user:[e-mail].

   • Replace ROLE with each individual role.
The Vertex AI User (roles/aiplatform.user) IAM role provides access to use all resources in Vertex AI. The Storage Admin (roles/storage.admin) role lets you store the document's training dataset in Cloud Storage.

What's next

Follow the next page of this tutorial to use the Google Cloud console to create a video classification dataset.