InferenceModel

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6. def doCalibrateTF(modelPath: String, networkType: String, validationFilePath: String, subset: Int, opencvLibPath: String, outputDir: String): Unit

   

   calibrate tensorflow model

   calibrate tensorflow model

   modelPath

   Path to an .xml file with a trained model

   networkType

   Type of an inferred network, "C" to calibrate Classification, "OD" to calibrate Object Detection, "RawC" to collect only statistics for Classification, "RawOD" to collect only statistics for Object Detection

   validationFilePath

   Path to a directory with validation images

   subset

   Number of pictures from the whole validation set to create the calibration dataset.

   opencvLibPath

   the lib path whwere libopencv_imgcodecs.so.4.0, libopencv_core.so.4.0 and libopencv_imgproc.so.4.0 can be found

   outputDir

   the output directory

7. def doOptimizeTF(modelPath: String, imageClassificationModelType: String, checkpointPath: String, inputShape: Array[Int], ifReverseInputChannels: Boolean, meanValues: Array[Float], scale: Float, outputDir: String): Unit

   

   optimize TF model as OpenVINO IR

   optimize TF model as OpenVINO IR

   modelPath

   the path of the tensorflow model

   imageClassificationModelType

   the type of the tensorflow model

   checkpointPath

   the path of the tensorflow checkpoint file

   inputShape

   input shape that should be fed to an input node(s) of the model

   ifReverseInputChannels

   the boolean value of if need reverse input channels. switch the input channels order from RGB to BGR (or vice versa).

   meanValues

   all input values coming from original network inputs will be divided by this value.

   scale

   the scale value, to be used for the input image per channel.

   outputDir

   the output dir

8. def doOptimizeTF(modelPath: String, objectDetectionModelType: String, pipelineConfigPath: String, extensionsConfigPath: String, outputDir: String): Unit

   

   optimize TF model as OpenVINO IR

   optimize TF model as OpenVINO IR

   modelPath

   the path of the tensorflow model

   objectDetectionModelType

   the type of the tensorflow model

   pipelineConfigPath

   the path of the pipeline configure file

   extensionsConfigPath

   the path of the extensions configure file

   outputDir

   the output dir

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