The primary purpose of the Nuralogix DeepAffex™ Extraction Library (DFX ExtLib) is to convert a series of face-tracked images into resultant blood-flow. This procedure is referred to as 'blood-flow extraction' and is the first stage in the Transdermal Optical Imaging (TOI) pipeline required for DeepAffex™ processing. The SDK is then used to generate measurement data chunks that are then forwarded to the DeepAffex™ Server for analysis and processing.
libdfxdotnet is a .NET Framework wrapper for the DFX ExtLib and currently targets .NET Framework 4.7.2. All the classes in it are under the Dfx.Sdk namespace.
This package contains:
Nuralogix.Dfx.Sdk.4.12.0.nupkg - a NuGet package targeting .NET Framework 4.7.2
libdfxdotnet.chm - Documentation for libdfxdotnet
The SDK leaves it up to the client application to capture frames (from a camera or a video file) and to populate the VideoFrame structure. This is done so that client applications and devices can capture in any format that is most suitable to their environment.
The client application is also responsible for ensuring that Frames (created from VideoFrames) have accurate timestamps and Faces. We provide no built-in face pose estimation as it is available as a commodity with implementations like dlib and Visage or via platform-specific libraries like Apple's Vision Framework or Android's FaceDetector. Whatever the output of the face tracking engine, it will need to be transformed into PosePoint definitions conforming to the standard MPEG-4 Facial Data Points and attached to the Face structure.
Once sufficient Frames have been added to the collector, the collector will indicate that a chunk is ready (ChunkReady) and the client application will need to get the Payload (using calls to ChunkData and Payload) and make a network call to the DeepAffex™ Server API.