EfficientNet4Lite
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).
EfficientNet-Lite 4 is the largest variant and most accurate of the set of EfficientNet-Lite model. It is an integer-only quantized model that produces the highest accuracy of all of the EfficientNet models. It achieves 80.4% ImageNet top-1 accuracy, while still running in real-time (e.g. 30ms/image) on a Pixel 4 CPU.
The model have
an input with the shape (1x224x224x3)
an output with the shape (1x1000)
See also
Constructors
EfficientNet4Lite
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fun EfficientNet4Lite()
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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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