Open 16rq opened 9 months ago
I also encountered this problem. However I think it is depending on the original data, maybe the original WSI is too diverse to cluster (?)
Hi, regarding to the AP clustering, I have some suggestions.
Considering the high time complexity of AP, it might be beneficial to reduce the number of patches through sampling before clustering.
Patch features can significantly influence clustering results. If you just use the model pretrained on ImageNet to extract patch features, clustering may not be work. In this work, we actually pretrained the patch-level feature extractor using Max-Pooling MIL to obtain patch features, so it may be worth trying patch features obtained through self-supervised learning.
Is there any suggetions to 'ConvergenceWarning: Affinity propagation did not converge, this model will not have any cluster centers.' in cluster.py?