dianna
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Deep Insight And Neural Network Analysis
  It should have given the valid options as well (RISE, LIME, kernelSHAP).
Currently we are masking images with zeros which is not always sensible. The behavior will be very different for a bright image as opposed to a dark image I would...
Rise outputs a numpy array with dimensions n_labels, height, width, while Lime outputs a list of numpy arrays with dimensions height, width. It should both output the same data structure.
It only seems to work with model objects which is inconsistent with how the other methods work. We always want to support model functions and model objects. We should think...
DIANNA should be able to run on models with more than 1 input. Inspired by the Lorentz workshop CNN-post-processing use case. For example data and quick fix, see the link...
DIANNA should be able to process images as inputs and models trained with more than 3 (e.g. RGB) channels. Inspired by the Lorentz workshop CNN-post-processing use case. For example data...
follows from #406 Related to the prepared model for the Coffee dataset (#385)
follows from #406