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Responsibility of each layer #5
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There are three layers for using tflite pose estimation model:
TFLiteImageInterpretor
: the wrapper class for image preprocessing before inferencePoseEstimator
: a simple protocol for abstractionPoseNetPoseEstimator
: concrete implement for PoseNet modelTFLiteImageInterpretor
TFLiteImageInterpretor
is similar toVNCoreMLRequest
. It has some pre-process logic for image and a tflite interpretor. OnlyTFLiteImageInterpretor
class has a dependency withTensorFlowLiteSwift
.PoseEstimator
A simple protocol for abstraction. Users can create the concrete type conforming to
PoseEstimator
protocol and then use the estimator instance with the protocol, not concrete type. So except for the creation point, there is no use of the concrete type.PoseNetPoseEstimator
PoseNetPoseEstimator
is concrete type ofPoseEstimator
. It has PoseNet model specific information like input/output shape and normalization type.For example, tensorflow/examples's PoseNet model needs following information:
[1, 257, 257, 3]
[1, 9, 9, 17]
0.0
~1.0
float32
false
TODO
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