I have been getting really nice clustering results using the UMAP method in DimensionReduce (Mathematica 13) where the data is a list of images, for example:

rep = DimensionReduce[ imagelist, 3, Method->"UMAP", TargetDevice -> "GPU"];

Without specifying any other options (like FeatureExtractor), does the above command implement any kind of automatic preprocessing on the image data before applying UMAP? The reason I ask is that when I compare the Python implementation of UMAP on the same set of images (where the RGB values are converted to numpy arrays, with no other preprocessing) I get results that are consistently much worse. So it seems like there is something useful that the Mathematica algorithm is doing under the hood to the images. Would it be possible to find out the details?

Thanks, Mike