Classes
Members
canOptimize
Check if renderer has optimization target layer set.
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compileInput
Generates input parametrization and initializes regularization transform chain.
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compileLossF
Prepares loss function for current objective.
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compileObjective
Prepares optimization for current objective.
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dispose
Disposes renderer.
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getActivationMaps
Returns activation tensors for currently selected layer.
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getActivationShape
Returns activation tensor shape for currently selected layer.
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getCentralNeuronCoords
Get the 2D coordinates of the central neuron for
a specific layer.
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getChannelNumber
Returns number of channels of current layer.
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getClassPrediction
Returns class prediction of current input image.
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getObjectiveF
Returns objective function depending on specified type.
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initObjectiveParamsForModel
initObjectiveParamsForModel - Initializes parameters according to model to provide
some fitting default parameters for convenience:
- layer: last Conv layer
- neuron: central neuron for initial layer
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initTransformF
Builds input transform chain
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optimize
Do one optimization step
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resizeStyleImage
Resizes style image to fit input image dimensions.
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setChannel
Sets target channel. Can be changed interactively during
optimization.
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setClass
Sets target class. Can be changed interactively during
optimization.
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setContentImage
Set content image for style transfer.
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setFeatureMapLayer
Sets layer to output featuremaps for.
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setInputParams
setInputParams - Sets input params and causes re-compilation of model,
not possible during running optimization.
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setJitter
Set input jitter
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setLayer
Sets layer for optimization objective. Can't change during
optimization. Resets target neuron to central neuron.
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setLearningRate
Set optimizer learning rate
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setModel
Assigns model to the renderer.
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setNegative
Set negative optimization objective status
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setNeuron
Sets target neuron. Can be changed interactively during
optimization.
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setObjectiveType
Sets the optimization objective type.
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setStyleImage
Set style image for style transfer.
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setStyleLayers
Sets layers that should be considered for style loss.
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startOptimization
Stars optimization loop.
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stopOptimization
Stops optimization loop.
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Methods
deprocessFeatureMap()
Returns feature map tensor in 0 - 255 color range.
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