OpenVinoInferenceSupportive

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def calibrateOpenVinoIRFromTempDir(modelName: String, tempDir: String, networkType: String, validationFilePath: String, subset: Int, opencvLibPath: String): Unit

   

6. val calibrateRelativePath: String

   

7. var calibrateSHPath: String

   

8. def calibrateTensorflowModel(modelPath: String, networkType: String, validationFilePath: String, subset: Int, opencvLibPath: String, outputDir: String): Unit

   

9. var calibrationLibPath: String

   

10. var calibrationToolPath: String

    

11. def clearWeightBias(model: Module[Float]): Unit

    

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    InferenceSupportive

12. def clone(): AnyRef

    

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    protected[java.lang]

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13. final def eq(arg0: AnyRef): Boolean

    

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14. def equals(arg0: Any): Boolean

    

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15. def finalize(): Unit

    

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    protected[java.lang]

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    @throws( classOf[java.lang.Throwable] )

16. final def getClass(): Class[_]

    

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17. def hashCode(): Int

    

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18. final def isInstanceOf[T0]: Boolean

    

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19. def load(path: String): Unit

    

20. def loadOpenVinoIR(modelFilePath: String, weightFilePath: String, deviceType: DeviceTypeEnumVal): OpenVINOModel

    

21. def loadOpenVinoIRFromTempDir(modelName: String, tempDir: String): OpenVINOModel

    

22. def loadOpenVinoIRInt8(modelFilePath: String, weightFilePath: String, deviceType: DeviceTypeEnumVal, batchSize: Int): OpenVINOModel

    

23. def loadTensorflowModel(modelPath: String, modelType: String, checkpointPath: String, inputShape: Array[Int], ifReverseInputChannels: Boolean, meanValues: Array[Float], scale: Float): OpenVINOModel

    

24. def loadTensorflowModel(modelPath: String, modelType: String, pipelineConfigPath: String, extensionsConfigPath: String): OpenVINOModel

    

25. def loadTensorflowModelAsCalibrated(modelPath: String, modelType: String, checkpointPath: String, inputShape: Array[Int], ifReverseInputChannels: Boolean, meanValues: Array[Float], scale: Float, networkType: String, validationFilePath: String, subset: Int, opencvLibPath: String): OpenVINOModel

    

26. val logger: Logger

    

27. def makeMetaModel(original: AbstractModule[Activity, Activity, Float]): AbstractModule[Activity, Activity, Float]

    

    Definition Classes

    InferenceSupportive

28. def makeUpModel(clonedModel: Module[Float], weightBias: Array[Tensor[Float]]): AbstractModule[Activity, Activity, Float]

    

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    InferenceSupportive

29. var motfpyFilePath: String

    

30. final def ne(arg0: AnyRef): Boolean

    

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31. final def notify(): Unit

    

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32. final def notifyAll(): Unit

    

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33. var openvinoTempDirPath: String

    

34. val optimizeImageClassificationRelativePath: String

    

35. var optimizeImageClassificationSHPath: String

    

36. val optimizeObjectDetectionRelativePath: String

    

37. var optimizeObjectDetectionSHPath: String

    

38. def optimizeTFImageClassificationModel(modelPath: String, modelType: String, checkpointPath: String, inputShape: Array[Int], ifReverseInputChannels: Boolean, meanValues: Array[Float], scale: Float, outputDir: String): Unit

    

39. def optimizeTFObjectDetectionModel(modelPath: String, modelType: String, pipelineConfigPath: String, extensionsConfigPath: String, outputDir: String): Unit

    

40. def releaseWeightBias(model: Module[Float]): Unit

    

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41. final def synchronized[T0](arg0: ⇒ T0): T0

    

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42. def timing[T](name: String)(f: ⇒ T): T

    

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43. def toString(): String

    

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44. def transferBatchTableToJListOfJListOfJTensor(batchTable: Table, batchSize: Int): List[List[JTensor]]

    

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    InferenceSupportive

45. def transferBatchTensorToJListOfJListOfJTensor(batchTensor: Tensor[Float], batchSize: Int): List[List[JTensor]]

    

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    InferenceSupportive

46. def transferListOfActivityToActivityOfBatch(inputs: List[List[JTensor]], batchSize: Int): Activity

    

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    InferenceSupportive

47. def transferTensorToJTensor(input: Tensor[Float]): JTensor

    

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48. def transferTensorsToTensorOfBatch(tensors: Array[JTensor]): Tensor[Float]

    

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49. final def wait(): Unit

    

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50. final def wait(arg0: Long, arg1: Int): Unit

    

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51. final def wait(arg0: Long): Unit

    

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52. def writeFile(inputStream: InputStream, dirPath: String, filePath: String): File