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 pixels [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