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# Example Configurations

This section includes example configurations that demonstrate how to configure feedback chaining.

The following configuration, for the upstream Media Server, runs face detection and then sends records to a Media Server at `gpu-mediaserver:14000` for remote face recognition:

    [Session]
    Engine0=Ingest
    Engine1=FaceDetect
    Engine2=Crop
    Engine3=RemoteAnalysis
    Engine4=XML

    [Ingest]
    Type=Video

    [FaceDetect]
    Type=FaceDetect
    FaceDirection=Front
    MinSize=200
    SizeUnit=pixel

    [Crop]
    Type=Crop
    Input=FaceDetect.ResultWithSource

    [RemoteAnalysis]
    Type=RemoteAnalysis
    Host=gpu-mediaserver
    Port=14000
    ConfigName=RemoteFaceRecognition
    Input=DetectedFaces:Crop.Output
    Output=RecognizedFaces:FaceRecognition.Result

    [XML]
    Type=XML
    Input=RemoteAnalysis.RecognizedFaces
    XMLOutputPath=./output/html/%segment.type%_results_%segment.sequence%.html
    XSLTemplate=toHTML.xsl
    Mode=Time
    OutputInterval=30s

The following configuration, for the remote Media Server, runs face recognition on records received from the upstream Media Server. To match the upstream configuration, above, this should be saved as `RemoteFaceRecognition.cfg`, in the folder specified by the `ConfigDirectory` parameter on the remote Media Server.

    [Session]
    Engine0=RecordsFromUpstream
    Engine1=FaceRecognition

    [RecordsFromUpstream]
    Type=Receive
    Input=DetectedFaces

    [FaceRecognition]
    Type=FaceRecognize
    Input=RecordsFromUpstream.DetectedFaces
    RecognitionThreshold=60
    MaxRecognitionResults=1

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