Package org.jetbrains.kotlinx.dl.impl.inference.imagerecognition

Types

ImageRecognitionModel

jvm

class ImageRecognitionModel(internalModel: InferenceModel, inputColorMode: ColorMode, channelsFirst: Boolean, preprocessor: Operation<Pair<FloatArray, TensorShape>, Pair<FloatArray, TensorShape>>, modelKindDescription: String?) : ImageRecognitionModelBase<BufferedImage>

The light-weight API for solving Image Recognition task with one of the Model Hub models trained on ImageNet dataset.

ImageRecognitionModelBase

common

abstract class ImageRecognitionModelBase<I>(internalModel: <ERROR CLASS>, modelKindDescription: String?)

Base class for image classification models.

InputType

common

enum InputType : Enum<InputType>

Different Neural Networks were trained on ImageNet dataset with different image preprocessing. The main types of preprocessing widely used in keras.applications are presented in this enumeration.

Functions

predictTop5Labels

common

fun <ERROR CLASS>.predictTop5Labels(data: FloatArray, classLabels: Map<Int, String>): List<<ERROR CLASS><String, Float>>

Returns top-5 labels for the given data encoded with mapping classLabels.

predictTopNLabels

common

fun <ERROR CLASS>.predictTopNLabels(floatArray: FloatArray, labels: Map<Int, String>, n: Int = 5): List<<ERROR CLASS><String, Float>>

Returns top-N labels for the given floatArray encoded with mapping labels.