PoseDetection

sealed class PoseDetection<T : InferenceModel, U : InferenceModel> : ModelType<T, U>

Pose detection models.

Types

MoveNetMultiPoseLighting
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A convolutional neural network model that runs on RGB images and predicts human joint locations of people in the image frame. The main differentiator between this MoveNet.MultiPose and its precedent, MoveNet.SinglePose model, is that this model is able to detect multiple people in the image frame at the same time while still achieving real-time speed.

MoveNetSinglePoseLighting
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This model is a convolutional neural network model that runs on RGB images and predicts human joint locations of a single person. (edges are available in org.jetbrains.kotlinx.dl.api.inference.onnx.posedetection.edgeKeyPointsPairs and keypoints are in org.jetbrains.kotlinx.dl.api.inference.onnx.posedetection.keyPoints).

MoveNetSinglePoseThunder
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This model is a convolutional neural network model that runs on RGB images and predicts human joint locations of a single person. (edges are available in org.jetbrains.kotlinx.dl.api.inference.onnx.posedetection.edgeKeyPointsPairs and keypoints are in org.jetbrains.kotlinx.dl.api.inference.onnx.posedetection.keyPoints).

Functions

model
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open fun model(modelHub: ModelHub): T
preInit
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open fun preInit(): InferenceModel
preprocessInput
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open fun preprocessInput(imageFile: File, preprocessing: Preprocessing): FloatArray
abstract fun preprocessInput(data: FloatArray, tensorShape: LongArray): FloatArray
pretrainedModel
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abstract fun pretrainedModel(modelHub: ModelHub): U

Properties

channelsFirst
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open override val channelsFirst: Boolean = true
modelRelativePath
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open override val modelRelativePath: String

Inheritors

ONNXModels.PoseDetection
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ONNXModels.PoseDetection
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ONNXModels.PoseDetection
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