Open topic with navigation

# TrainImageHash

Trains Media Server to identify duplicate images. This adds a new image hash, with a training image, to the training database.

This action is atomic, so that any interruption to the server does not leave the database in an inconsistent state. The database is not modified if the action returns an error, or if you stop it using the QueueInfo action. If training fails, Media Server does not add the image hash to the database.

Type: asynchronous

Parameter | Description | Required
--- | --- | ---
`database` | The name of the database to add the new image hash to. The database must already exist. | Yes
`identifier` | A unique identifier for the image hash (maximum 254 bytes). If you do not set this parameter, Media Server generates an identifier automatically. | No
`imagedata` | The training image to add. Files must be uploaded as multipart/form-data. For more information about sending data to Media Server, refer to the Media Server Administration Guide. | Set this or `imagepath`
`imagelabel` | A label to identify the image that you are adding (maximum 254 bytes). If you do not set this parameter, Media Server generates a label automatically. | No
`imagepath` | The path to the training image to add. The path must be absolute, or relative to the Media Server executable file. | Set this or `imagedata`

## Example

The following example trains Media Server by sending the path of a training image using the `imagepath` parameter:

    curl http://localhost:14000 -F action=TrainImageHash
                                -F database=ImageHashes
                                -F identifier=AnImage
                                -F imagepath=image.png

Alternatively, you can train Media Server by sending the image data, for example:

    curl http://localhost:14000 -F action=TrainImageHash
                                -F database=ImageHashes
                                -F identifier=AnImage
                                -F imagedata=@image.png

## Response

This action is asynchronous, so Media Server always returns success accompanied by a token:

    <autnresponse>
      <action>TRAINIMAGEHASH</action>
      <response>SUCCESS</response>
      <responsedata>
        <token>MTAuMi4xMDQuNTQ6MTgwMDA6VFJBSU5GQUNFOjE0MjkyNzE0NjAwMDQ1Ni0xMzAyMzQ3MDI2</token>
      </responsedata>
    </autnresponse>

You can use this token with the QueueInfo action to retrieve the status of the action:

    <autnresponse>
      <action>QUEUEINFO</action>
      <response>SUCCESS</response>
      <responsedata>
        <actions>
          <action>
            <status>Finished</status>
            <queued_time>2018-Jan-04 09:53:21</queued_time>
            <time_in_queue>0</time_in_queue>
            <process_start_time>2018-Jan-04 09:53:21</process_start_time>
            <time_processing>0</time_processing>
            <process_end_time>2018-Jan-04 09:53:21</process_end_time>
            <build>
              <image>
                <label>AnImage</label>
                <status>trained</status>
              </image>
            </build>
            <database>ImageHashes</database>
            <identifier>AnImage</identifier>
            <numimages>1</numimages>
            <numtrained>1</numtrained>
            <token>MTAuMi4xMDQuNTQ6MTgwMDA6VFJBSU5GQUNFOjE0MjkyNzE0NjAwMDQ1Ni0xMzAyMzQ3MDI2</token>
          </action>
        </actions>
      </responsedata>
    </autnresponse>

© 2018 Micro Focus or one of its affiliates | Send documentation feedback to Micro Focus Close Send documentation feedback To open the configured email client on this computer, open an email window. Otherwise, copy the information below to a web mail client, and send this email to swpdl.idoldocsfeedback@microfocus.com. We appreciate your feedback! Product: Topic Title: Help Topic: Feedback:

_FT_HTML5_bannerTitle.htm