I have an issue related to the meaning and usefulness of Implicit2DWrapper function.
I understood that it is necessary to retrive a dictionary like python object containing data that also include first derivative, that is gradient, and the second order derivative that is laplacian.
But when I'm fetching data via Implicit2DWrapper and then I'm feeding a Siren based neural network, finally I'm going to measure PSNR and other metrices scores such as SSIM, someone made me notice that my metrices score recorded are too low.
So, I think that the issue is due to the fact that the self.transform instance attribute within class Implicit2DWrapper is containing a Normalization operation that it is not reported instead for explore_sire.ipynb where ImageFitting is defined in order to let a Siren-based model to be trained against Camera image.
Why do you decide to add such normalization process for Implicit2DWrapper in your dataio.py source file, but do not perfome such transformation when you have edited explore_sire.ipynb notebook, when showcasing the use of siren architecture for image fitting?
I have an issue related to the meaning and usefulness of
Implicit2DWrapperfunction.I understood that it is necessary to retrive a dictionary like python object containing data that also include first derivative, that is gradient, and the second order derivative that is laplacian.
But when I'm fetching data via
Implicit2DWrapperand then I'm feeding a Siren based neural network, finally I'm going to measure PSNR and other metrices scores such as SSIM, someone made me notice that my metrices score recorded are too low.So, I think that the issue is due to the fact that the
self.transforminstance attribute within classImplicit2DWrapperis containing a Normalization operation that it is not reported instead for explore_sire.ipynb where ImageFitting is defined in order to let a Siren-based model to be trained against Camera image.Why do you decide to add such normalization process for
Implicit2DWrapperin your dataio.py source file, but do not perfome such transformation when you have edited explore_sire.ipynb notebook, when showcasing the use of siren architecture for image fitting?