Contents

init(validation:batchSize:maximumIterations:predictionWindowSize:augmentationOptions:algorithm:targetFrameRate:)

Creates a set of training session parameters for a hand action classifier task.

Declaration

init(validation: MLHandActionClassifier.ModelParameters.ValidationData = .split(strategy: .automatic), batchSize: Int = MLHandActionClassifier.__Defaults.batchSize, maximumIterations: Int = MLHandActionClassifier.__Defaults.maximumIterations, predictionWindowSize: Int = MLHandActionClassifier.__Defaults.predictionWindowSize, augmentationOptions: MLHandActionClassifier.VideoAugmentationOptions = [], algorithm: MLHandActionClassifier.ModelParameters.ModelAlgorithmType = .gcn, targetFrameRate: Double = MLHandActionClassifier.__Defaults.targetFrameRate)

Discussion

  • validation: An MLHandActionClassifier.ModelParameters.ValidationData instance.

  • batchSize: The number of videos the training session uses for each of its training iterations.

  • maximumIterations: The largest number of training iterations the training session can use.

  • predictionWindowSize: The number of frames the training session uses to train a hand action classifier. For example, set to 60 to capture hand actions that take 2 seconds from videos that have a frame rate of 30 frames per second.

  • augmentationOptions: The variations the training session uses to add more variety to its training dataset.

  • algorithm: The algorithm the training session uses to train the hand action classifier.

  • targetFrameRate: The number of frames the training session uses per second of video to train a hand action classifier.