ResNet50noTopCustom
This model is a neural network for image classification that take images as input and classify the major object in the image into a set of 1000 different classes (labels are available via org.jetbrains.kotlinx.dl.api.core.util.loadImageNetClassLabels method).
This model has 50 layers with ResNetv1 architecture.
The model have
an input with the shape (1x224x224x3)
an output with the shape (N,M3,M4,2048)
NOTE: This model is converted from Keras.applications, the last two layers in the model have been removed so that the user can fine-tune the model for his specific task.
See also
Functions
model
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preInit
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preprocessInput
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open fun preprocessInput(imageFile: File, preprocessing: Preprocessing): FloatArray
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open override fun preprocessInput(data: FloatArray, tensorShape: LongArray): FloatArray
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pretrainedModel
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open override fun pretrainedModel(modelHub: ModelHub): ImageRecognitionModel
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