(self, imagedata, activations, unit=None,
            above=None, below=None)
return PIL.Image.fromarray(
            result_image.permute(1, 2, 0).cpu().numpy())
Visualizes the given activations, thresholded at a specified level,
        overlaid on the given image, as a PIL image.
Visualizes the given activations, thresholded at a specified level,
        overlaid on the given image, as a PIL image.
Visualizes the given activations thresholded at a specified level overlaid on the given image as a PIL image .
def masked_delta(self, imagedata, activations, unit=None,
            above=None, below=None):
        '''
        Visualizes the given activations, thresholded at a specified level,
        overlaid on the given image, as a PIL image.
        '''
        result_image = self.pytorch_masked_delta(imagedata, activations,
                unit=unit, above=above, below=below)
        return PIL.Image.fromarray(
            result_image.permute(1, 2, 0).cpu().numpy())
def masked_delta ( self , imagedata , activations , unit = None , above = None , below = None ) : result_image = self . pytorch_masked_delta ( imagedata , activations , unit = unit , above = above , below = below ) return PIL . Image . fromarray ( result_image . permute ( 1 , 2 , 0 ) . cpu ( ) . numpy ( ) )