Media Server 25.2
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# FinetuneFaceDatabase

Performs a final, optional, stage in the training process that optimizes the neural network to improve recognition accuracy.

This action acts on a single face database, which must meet several requirements:

- The database must have been created with fine-tuning enabled (see the `finetuning` parameter in the action CreateFaceDatabase).
- The database must contain a reasonable number of faces. OpenText recommends more than 50.
- The database must contain multiple training images for most or all of the faces.

NOTE: OpenText recommends that you fine-tune the neural network only if your training data is similar to the media that you will ingest. For example, if you are planning to ingest video captured from a CCTV camera, the training data should ideally have been captured from CCTV. In some cases, using `action=FinetuneFaceDatabase` can result in overfitting and reduce recognition accuracy. If you find that accuracy is reduced, you can revert to the default neural network by setting `DisableFineTuning=TRUE` in your face recognition task.

OpenText recommends running the action BuildAllFaces before running `FinetuneFaceDatabase`, because untrained images are not used to optimize the neural network.

NOTE: The optimized network is used automatically, but you must set the Database parameter when you configure the face recognition task in your session configuration. Otherwise, Media Server uses a generic face recognition network that is suitable for all databases, rather than the optimized network produced by this action.

Running this action does not require a GPU.

Type: asynchronous

Parameter | Description | Required
--- | --- | ---
`database` | The name of a database to process. | Yes

## Example

    /action=FinetuneFaceDatabase&database=politicians

## Response

This action is asynchronous, so Media Server always returns success accompanied by a token. You can use this token with the QueueInfo action to retrieve the status of your request.

The `FinetuneFaceDatabase` action can take a significant amount of time to complete (over an hour with a large database). It writes progress information to the application log.

Copyright 2025 Open Text
Version 25.2 | Last updated April 2025

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Product: Knowledge Discovery Media Server 25.2

Topic Title: FinetuneFaceDatabase