vgg16noTopAdditionalTraining
fun vgg16noTopAdditionalTraining()
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This examples demonstrates the transfer learning concept on VGG'16 model:
Model configuration, model weights and labels are obtained from TFModelHub.
Weights are loaded from .h5 file, configuration is loaded from .json file.
All layers, are added to the new Neural Network, its weights are frozen.
New Dense layers are added and initialized via defined initializers.
Model is re-trained on dogsCatsSmallDatasetPath dataset.
We use the Preprocessing DSL to describe the dataset generation pipeline. We demonstrate the workflow on the subset of Kaggle Cats vs Dogs binary classification dataset.