Create and update a Batch Video Warehouse

Create a Batch Video Warehouse that is ready to use for search.

Setting up a minimal Batch Video Warehouse

There are two common ways to set up a minimal Batch Video Warehouse.

Option 1: Deploy an empty index first, and then gradually add video assets. The typical API sequence for this approach is as follows:
- Set up a corpus: CreateCorpus, then CreateDataSchema.
- Set up an empty index: CreateIndex, CreateIndexEndpoint, and DeployIndex.
- Add video assets: CreateAsset, UploadAsset, AnalyzeAsset, and IndexAsset.
  - (Optional) Add video annotations: CreateAnnotation.
Option 2: Import video assets first, and then deploy an index. The typical API sequence for this approach is as follows:
- Set up a corpus: CreateCorpus, then CreateDataSchema.
- Add video assets: CreateAsset, UploadAsset, and AnalyzeAsset.
  - (Optional) Add video annotations: CreateAnnotation.
- Set up an index with existing assets: CreateIndex, CreateIndexEndpoint, and DeployIndex.

Choosing an approach: The best approach for you will depend on your specific needs. If you need to start searching videos as soon as possible, you may want to use the first approach. If you have a large number of videos to import, you may want to use the latter option.

Create a corpus

To begin, you must create a corpus resource. When creating a Batch Video Warehouse corpus, specify EMBEDDING_SEARCH as the default value of the searchCapabilitySetting property.

REST & CMD LINE

Creates a corpus resource under the given project with the option to specify the corpus's display name and description.

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.
DISPLAY_NAME: Display name for the warehouse.
WAREHOUSE_DESCRIPTION: The description of the warehouse (corpus).

HTTP method and URL:

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

Request JSON body:

{
  "display_name": "DISPLAY_NAME",
  "description": "WAREHOUSE_DESCRIPTION",
  "type": "VIDEO_ON_DEMAND",
  "search_capability_setting": {
    "search_capabilities": {
      "type": "EMBEDDING_SEARCH"
    }
  }
}

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"

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" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/warehouseoperations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.CreateCorpusMetadata"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.Corpus",
    "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID",
    "displayName": "DISPLAY_NAME",
    "description": "WAREHOUSE_DESCRIPTION",
    "type": "VIDEO_ON_DEMAND",
    "search_capability_setting": {
      "search_capabilities": {
        "type": "EMBEDDING_SEARCH"
      }
    }
  }
}

Create, upload, and analyze assets

To add a video to Batch Video Warehouse, first create an asset.

REST & CMD LINE

To create an asset resource, send a POST request by using the projects.locations.corpora.assets.create method.

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:

{
}

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 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

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"
}

The next step is to upload the video from a Cloud Storage URI. Note that Batch Video Warehouse does not store a copy of the video file. The UploadAsset API only verifies video metadata to make sure no quotas or limits are violated.

REST & CMD LINE

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.

HTTP method and URL:

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

Request JSON body:

{
  "asset_source": {
    "asset_gcs_source": {
      "gcs_uri": "GCS_URI"
    }
  }
}

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 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/ASSET_ID:upload"

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 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/ASSET_ID:upload" | 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/operations/OPERATION_ID",
}

The uploaded video needs to be analyzed before going into search indexes.

REST & CMD LINE

Analyze a video asset using the projects.locations.corpora.assets.analyze method. By default, Batch Video Warehouse runs embedding analysis on video content.

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.

HTTP method and URL:

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

Request JSON body:

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

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 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/ASSET_ID:analyze"

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 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/ASSET_ID:analyze" | 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/operations/OPERATION_ID"
}

Create data schemas

A data schema is mandatory if you want to annotate the videos with custom metadata and search for the metadata. Each data schema has a unique key, which is to be associated with annotations and used as filter criteria in search.

REST & CMD LINE

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.
DATASCHEMA_KEY: This key must match the key of a user-specified annotation and unique inside a corpus. For example, data-key.
ANNOTATION_DATA_TYPE: The data type of the annotation. Available values are:
- DATA_TYPE_UNSPECIFIED
- INTEGER
- FLOAT
- STRING
- DATETIME
- GEO_COORDINATE
- PROTO_ANY
- BOOLEAN
For more information, see the API reference documentation.
ANNOTATION_GRANULARITY: The granularity of the annotations under this dataSchema. Available values are:
- GRANULARITY_UNSPECIFIED - Unspecified granularity.
- GRANULARITY_ASSET_LEVEL - Asset-level granularity (annotations must not contain temporal partition information for the media asset).
- GRANULARITY_PARTITION_LEVEL - Partition-level granularity (annotations must contain temporal partition information for the media asset).
SEARCH_STRATEGY: One of the available enum values. The types of search strategies to be applied on the annotation key. Available values are:
- NO_SEARCH
- EXACT_SEARCH
- SMART_SEARCH

HTTP method and URL:

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

Request JSON body:

{
  "key": "DATASCHEMA_KEY",
  "schema_details": {
    "type": "ANNOTATION_DATA_TYPE",
    "granularity": "ANNOTATION_GRANULARITY",
    "search_strategy": {
      "search_strategy_type": "SEARCH_STRATEGY"
    }
  }
}

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 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/dataSchemas"

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 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/dataSchemas" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/dataSchemas/DATASCHEMA_ID",
  "key": "data-key",
  "schemaDetails": {
    "type": "BOOLEAN",
    "granularity": "GRANULARITY_ASSET_LEVEL",
    "searchStrategy": {
      "search_strategy_type": "EXACT_SEARCH"
    }
  }
}

Create annotations

You can annotate a video with either asset-level annotations or annotations with relative temporal partitions. Each annotation must be specified with an existing data schema key.

REST & CMD LINE

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.
ANNOTATION_ID: (Optional) A user-provided value for the annotation ID. In this request, the value is added to the request URL in the form:
- https://ENDPOINT/v1/[...]/corpora/CORPUS_ID/assets/ASSET_ID/annotations?annotation_id=ANNOTATION_ID

HTTP method and URL:

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

Request JSON body:

{
  "user_specified_annotation": {
    "key": "object-detected",
    "value": {
      "str_value": "cat"
    },
    "partition": {
      "relative_temporal_partition": {
        "start_offset": {
          "seconds": "60"
        },
        "end_offset": {
          "seconds": "300"
        }
      }
    }
  }
}

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 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/ASSET_ID/annotations"

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 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/ASSET_ID/annotations" | 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/annotations/ANNOTATION_ID",
  "userSpecifiedAnnotation": {
    "key": "object-detected",
    "value": {
      "strValue": "cat"
    },
    "partition": {
      "relative_temporal_partition": {
        "start_offset": "60s",
        "end_offset": "300s"
      }
    }
  }
}

Create an index

After you have added video assets and annotations, you can proceed to create an index on a corpus. An index captures the state of the corpus at the creation time, which includes all analyzed assets and annotations.

REST & CMD LINE

This sample shows you how to create an index resource.

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.
INDEX_ID: (Optional) A user-provided value for the index ID. In this request, the value is added to the request URL in the form:
- https://REGIONALIZED_ENDPOINT/v1/[...]/corpora/CORPUS_ID/indexes?index_id=INDEX_ID

HTTP method and URL:

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

Request JSON body:

{
  "display_name": "DISPLAY_NAME",
  "description": "INDEX_DESCRIPTION",
}

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 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/indexes"

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 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/indexes" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/indexes/INDEX_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.CreateIndexMetadata"
  }
}

Deploy index to index endpoint

An index has to be deployed to an index endpoint before it can be used for search. An index endpoint provides the access point to sending search request.

This example shows you how to create an index endpoint.

REST & CMD LINE

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.
INDEX_ENDPOINT_ID: (Optional) A user-provided value for the index endpoint ID. In this request, the value is added to the request URL in the form:
- https://REGIONALIZED_ENDPOINT/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/indexEndpoints?index_endpoint_id=INDEX_ENDPOINT_ID

HTTP method and URL:

POST https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/indexEndpoints

Request JSON body:

{
  "display_name": "DISPLAY_NAME",
  "description": "DESCRIPTION",
}

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 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/indexEndpoints"

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 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/indexEndpoints" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/indexEndpoints/INDEX_ENDPOINT_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.CreateIndexEndpointMetadata"
  }
}

This example shows you how to deploy an index to an index endpoint.

REST & CMD LINE

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.
INDEX_ENDPOINT_ID: The ID of your target index endpoint.
CORPUS_ID: The ID of your target corpus.
INDEX_ID: The ID of your target index.

HTTP method and URL:

POST https://warehouse-visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/indexEndpoints/INDEX_ENDPOINT_ID:deployIndex

Request JSON body:

{
  "deployedIndex": {
    "index": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/indexes/INDEX_ID"
  }
}

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 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/indexEndpoints/INDEX_ENDPOINT_ID:deployIndex"

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 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/indexEndpoints/INDEX_ENDPOINT_ID:deployIndex" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/indexEndpoints/INDEX_ENDPOINT_ID/operations/OPERATION_ID",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.DeployIndexMetadata",
    "deployedIndex": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/indexes/INDEX_ID"
  }
}

Streaming update assets in index

You can use the IndexAsset or RemoveIndexAsset methods to update or remove a single asset in a deployed index. Streaming update lets you update and search the index in a short time.

This example shows you how to update an asset in index.

REST & CMD LINE

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.

HTTP method and URL:

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

Request JSON body:

{
  "index": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/indexes/INDEX_ID"
}

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 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/ASSET_ID:index"

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 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/ASSET_ID:index" | 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/operations/OPERATION_ID",
}

This example shows you how to remove an asset from index.

REST & CMD LINE

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.

HTTP method and URL:

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

Request JSON body:

{
  "index": "projects/PROJECT_NUMBER/locations/LOCATION_ID/corpora/CORPUS_ID/indexes/INDEX_ID"
}

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 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/ASSET_ID:removeIndex"

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 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/ASSET_ID:removeIndex" | 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/operations/OPERATION_ID",
}

What's next

Learn how to search in Batch Video Warehouse.