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Do video retrieval using vectorization (version 4.0 preview)

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Azure AI Video Retrieval APIs are part of Azure AI Vision and enable developers to create an index, add documents (videos and images) to it, and search with natural language. Developers can define metadata schemas for each index and ingest metadata to the service to help with retrieval. Developers can also specify what features to extract from the index (vision, speech) and filter their search based on features.

Prerequisites

Input requirements

Supported formats

File format Description
asf ASF (Advanced / Active Streaming Format)
avi AVI (Audio Video Interleaved)
flv FLV (Flash Video)
matroskamm, webm Matroska / WebM
mov,mp4,m4a,3gp,3g2,mj2 QuickTime / MOV

Supported video codecs

Codec Format
h264 H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10
h265 H.265/HEVC
libvpx-vp9 libvpx VP9 (codec vp9)
mpeg4 MPEG-4 part 2

Supported audio codecs

Codec Format
aac AAC (Advanced Audio Coding)
mp3 MP3 (MPEG audio layer 3)
pcm PCM (uncompressed)
vorbis Vorbis
wmav2 Windows Media Audio 2

Call the Video Retrieval APIs

To use the Video Retrieval APIs in a typical pattern, you would do the following steps:

  1. Create an index using PUT - Create an index.
  2. Add video documents to the index using PUT - CreateIngestion.
  3. Wait for the ingestion to complete, checking with GET - ListIngestions.
  4. Search for a keyword or phrase using POST - SearchByText.

The Video Retrieval APIs allows a user to add metadata to video files. Metadata is additional information associated with video files such as "Camera ID," "Timestamp," or "Location" that can be used to organize, filter, and search for specific videos. This example demonstrates how to create an index, add video files with associated metadata, and perform searches using different features.

Step 1: Create an Index

To begin, you need to create an index to store and organize the video files and their metadata. The example below demonstrates how to create an index named "my-video-index" using the Create Index API.

curl.exe -v -X PUT "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
{
  'metadataSchema': {
    'fields': [
      {
        'name': 'cameraId',
        'searchable': false,
        'filterable': true,
        'type': 'string'
      },
      {
        'name': 'timestamp',
        'searchable': false,
        'filterable': true,
        'type': 'datetime'
      }
    ]
  },
  'features': [
    {
      'name': 'vision',
      'domain': 'surveillance'
    },
    {
      'name': 'speech'
    }
  ]
}"

Response:

HTTP/1.1 201 Created
Content-Length: 530
Content-Type: application/json; charset=utf-8
request-id: cb036529-d1cf-4b44-a1ef-0a4e9fc62885
api-supported-versions: 2023-01-15-preview,2023-05-01-preview
x-envoy-upstream-service-time: 202
Date: Thu, 06 Jul 2023 18:05:05 GMT
Connection: close

{
  "name": "my-video-index",
  "metadataSchema": {
    "language": "en",
    "fields": [
      {
        "name": "cameraid",
        "searchable": false,
        "filterable": true,
        "type": "string"
      },
      {
        "name": "timestamp",
        "searchable": false,
        "filterable": true,
        "type": "datetime"
      }
    ]
  },
  "userData": {},
  "features": [
    {
      "name": "vision",
      "modelVersion": "2023-05-31",
      "domain": "surveillance"
    },
    {
      "name": "speech",
      "modelVersion": "2023-06-30",
      "domain": "generic"
    }
  ],
  "eTag": "\"7966244a79384cca9880d67a4daa9eb1\"",
  "createdDateTime": "2023-07-06T18:05:06.7582534Z",
  "lastModifiedDateTime": "2023-07-06T18:05:06.7582534Z"
}

Step 2: Add video files to the index

Next, you can add video files to the index with their associated metadata. The example below demonstrates how to add two video files to the index using SAS URLs with the Create Ingestion API.

curl.exe -v -X PUT "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index/ingestions/my-ingestion?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
{
  'videos': [
    {
      'mode': 'add',
      'documentId': '02a504c9cd28296a8b74394ed7488045',
      'documentUrl': 'https://example.blob.core.windows.net/videos/02a504c9cd28296a8b74394ed7488045.mp4?sas_token_here',
      'metadata': {
        'cameraId': 'camera1',
        'timestamp': '2023-06-30 17:40:33'
      }
    },
    {
      'mode': 'add',
      'documentId': '043ad56daad86cdaa6e493aa11ebdab3',
      'documentUrl': '[https://example.blob.core.windows.net/videos/043ad56daad86cdaa6e493aa11ebdab3.mp4?sas_token_here',
      'metadata': {
        'cameraId': 'camera2'
      }
    }
  ]
}"

Response:

HTTP/1.1 202 Accepted
Content-Length: 152
Content-Type: application/json; charset=utf-8
request-id: ee5e48df-13f8-4a87-a337-026947144321
operation-location: http://api.example.com.trafficmanager.net/retrieval/indexes/my-test-index/ingestions/my-ingestion
api-supported-versions: 2023-01-15-preview,2023-05-01-preview
x-envoy-upstream-service-time: 709
Date: Thu, 06 Jul 2023 18:15:34 GMT
Connection: close

{
  "name": "my-ingestion",
  "state": "Running",
  "createdDateTime": "2023-07-06T18:15:33.8105687Z",
  "lastModifiedDateTime": "2023-07-06T18:15:34.3418564Z"
}

Step 3: Wait for ingestion to complete

After you add video files to the index, the ingestion process starts. It might take some time depending on the size and number of files. To ensure the ingestion is complete before performing searches, you can use the Get Ingestion API to check the status. Wait for this call to return "state" = "Completed" before proceeding to the next step.

curl.exe -v -X GET "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index/ingestions?api-version=2023-05-01-preview&$top=20" -H "ocp-apim-subscription-key: <YOUR_SUBSCRIPTION_KEY>"

Response:

HTTP/1.1 200 OK
Content-Length: 164
Content-Type: application/json; charset=utf-8
request-id: 4907feaf-88f1-4009-a1a5-ad366f04ee31
api-supported-versions: 2023-01-15-preview,2023-05-01-preview
x-envoy-upstream-service-time: 12
Date: Thu, 06 Jul 2023 18:17:47 GMT
Connection: close

{
  "value": [
    {
      "name": "my-ingestion",
      "state": "Completed",
      "createdDateTime": "2023-07-06T18:15:33.8105687Z",
      "lastModifiedDateTime": "2023-07-06T18:15:34.3418564Z"
    }
  ]
}

Step 4: Perform searches with metadata

After you add video files to the index, you can search for specific videos using metadata. This example demonstrates two types of searches: one using the "vision" feature and another using the "speech" feature.

Search with "vision" feature

To perform a search using the "vision" feature, use the Search By Text API with the vision filter, specifying the query text and any other desired filters.

curl.exe -v -X POST "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index:queryByText?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
{
  'queryText': 'a man with black hoodie',
  'filters': {
    'stringFilters': [
      {
        'fieldName': 'cameraId',
        'values': [
          'camera1'
        ]
      }
    ],
    'featureFilters': ['vision']
  }
}"

Response:

HTTP/1.1 200 OK
Content-Length: 3289
Content-Type: application/json; charset=utf-8
request-id: 4c2477df-d89d-4a98-b433-611083324a3f
api-supported-versions: 2023-05-01-preview
x-envoy-upstream-service-time: 233
Date: Thu, 06 Jul 2023 18:42:08 GMT
Connection: close

{
  "value": [
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "VideoFrame",
      "start": "00:01:58",
      "end": "00:02:09",
      "best": "00:02:03",
      "relevance": 0.23974405229091644
    },
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "VideoFrame",
      "start": "00:02:27",
      "end": "00:02:29",
      "best": "00:02:27",
      "relevance": 0.23762696981430054
    },
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "VideoFrame",
      "start": "00:00:26",
      "end": "00:00:27",
      "best": "00:00:26",
      "relevance": 0.23250913619995117
    },
  ]
}

Search with "speech" feature

To perform a search using the "speech" feature, use the Search By Text API with the speech filter, providing the query text and any other desired filters.

curl.exe -v -X POST "https://<YOUR_ENDPOINT_URL>com/computervision/retrieval/indexes/my-video-index:queryByText?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
{
  'queryText': 'leave the area',
  'dedup': false,
  'filters': {
    'stringFilters': [
      {
        'fieldName': 'cameraId',
        'values': [
          'camera1'
        ]
      }
    ],
    'featureFilters': ['speech']
  }
}"

Response:

HTTP/1.1 200 OK
Content-Length: 49001
Content-Type: application/json; charset=utf-8
request-id: b54577bb-1f46-44d8-9a91-c9326df3ac23
api-supported-versions: 2023-05-01-preview
x-envoy-upstream-service-time: 148
Date: Thu, 06 Jul 2023 18:43:07 GMT
Connection: close

{
  "value": [
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "SpeechTextSegment",
      "start": "00:07:07.8400000",
      "end": "00:07:08.4400000",
      "best": "00:07:07.8400000",
      "relevance": 0.8597901463508606
    },
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "SpeechTextSegment",
      "start": "00:07:02.0400000",
      "end": "00:07:03.0400000",
      "best": "00:07:02.0400000",
      "relevance": 0.8506758213043213
    },
    {
      "documentId": "02a504c9cd28296a8b74394ed7488045",
      "documentKind": "SpeechTextSegment",
      "start": "00:07:10.4400000",
      "end": "00:07:11.5200000",
      "best": "00:07:10.4400000",
      "relevance": 0.8474636673927307
    }
  ]
}

Next steps

Multimodal embeddings concepts