Create and update a warehouse asset

A connected Vision Warehouse ( corpus ) in a data-ingesting deployed app has one or more media object resources (for example, video resources). These media objects ( asset resources) contain metadata and resource annotations. Use the following commands to create and update these media objects.

Create a streaming video warehouse asset

After you have created a warehouse ( corpus resource), you can add one or more video asset resources to the warehouse.

REST & CMD LINE

The following code creates a new asset under the given warehouse ( corpus ) with the option to specify the asset's ID and a TTL.

Before using any of the request data, make the following replacements:

REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
PROJECT_NUMBER : Your Google Cloud project number .
LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
CORPUS_ID : The ID of your target corpus.
ASSET_ID : (Optional) A user-provided value for the asset ID. In this request, the value is added to the request URL in the form:
- https:// ENDPOINT /v1/ [...] /corpora/ CORPUS_ID /assets ?asset_id= ASSET_ID
TIME_TO_LIVE : The amount of time to live (TTL) for all assets under a corpus, or the TTL of a specific asset. For example, for a corpus with assets with a TTL of 100 days, provide the value 8640000 (seconds).

HTTP method and URL:

POST https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets

Request JSON body:

{
  "ttl": {
    "seconds": TIME_TO_LIVE 
}
}

To send your request, choose one of these options:

curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell , which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list .

Save the request body in a file named request.json , and execute the following command:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets"

PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list .

Save the request body in a file named request.json , and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
",
  "ttl": " TIME_TO_LIVE 
s"
}

Vertex AI Vision SDK

To send a request to read a model output stream you must install the Vertex AI Vision SDK .

When using the vaictl command line tool to create an asset you are not able to specify an asset ID or TTL.

Make the following variable substitutions:

PROJECT_NUMBER : Your Google Cloud project number.
LOCATION_ID : Your location ID. For example, us-central1 . Supported regions . More information .
CORPUS_ID : The ID of the target warehouse ( corpus resource).

 vaictl --project-id= PROJECT_NUMBER 
\
--location-id= LOCATION_ID 
\
--service-endpoint=warehouse-visionai.googleapis.com \
create asset CORPUS_ID

After an asset is created you can ingest video data directly into the warehouse for that asset by using the vaictl command line tool.

Update a streaming video warehouse asset

Use the following code sample to update an asset's time-to-live (TTL). You can only update the TTL field.

Use the updateMask query parameter in the following code sample to update an asset's TTL. You can use a query parameter to update the TTL field only. The updateMask works as follows:

If specified, only the fields in the updateMask are updated.
If update mask value is * , the request updates all the fields.
If the update mask is not specified, only the fields in the request URL with a value provided in the request body are updated.

REST & CMD LINE

The following code samples modify an asset's TTL using the projects.locations.corpora.assets.patch method.

Change a TTL value

This sample uses ?updateMask=ttl in the request URL, and includes a new ttl.seconds value in the request body to update the asset.

Before using any of the request data, make the following replacements:

REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
PROJECT_NUMBER : Your Google Cloud project number .
LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
CORPUS_ID : The ID of your target corpus.
ASSET_ID : The ID of your target asset.
?updateMask= fieldToUpdate : One of the available fields you can apply an updateMask to. Available fields:
- Time-to-live (TTL): ?updateMask=ttl
- Update all fields: ?updateMask=*

HTTP method and URL:

PATCH https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl

Request JSON body:

{
  "ttl": {
    "seconds": " 1 
"
  }
}

To send your request, choose one of these options:

curl

Save the request body in a file named request.json , and execute the following command:

curl -X PATCH \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl 
"

PowerShell

Save the request body in a file named request.json , and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method PATCH `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl 
" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
"
}

Remove a TTL value

This sample uses ?updateMask=ttl in the request URL, and includes an empty request body to clear the asset's TTL value.

Before using any of the request data, make the following replacements:

REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
PROJECT_NUMBER : Your Google Cloud project number .
LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
CORPUS_ID : The ID of your target corpus.
ASSET_ID : The ID of your target asset.
?updateMask= fieldToUpdate : One of the available fields you can apply an updateMask to. Available fields:
- Time-to-live (TTL): ?updateMask=ttl
- Update all fields: ?updateMask=*

HTTP method and URL:

PATCH https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl

Request JSON body:

{}

To send your request, choose one of these options:

curl

Save the request body in a file named request.json , and execute the following command:

curl -X PATCH \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl 
"

PowerShell

Save the request body in a file named request.json , and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
-Method PATCH `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https:// warehouse-visionai.googleapis.com 
/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
 ?updateMask=ttl 
" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/assets/ ASSET_ID 
"
}