Thanks for your great work.
In main_evaluated.py the result is shown as
print( f'| K64 | Det: {det_64:.3f} Seg:{seg_64:.3f} | K32 | Det: {det_32:.3f} Seg:{seg_32:.3f} | sum | Det: {det_sum:.3f} Seg:{seg_sum:.3f} | mult | Det: {det_mult:.3f} Seg:{seg_mult:.3f} ({obj})')
However, in the paper, you report Random Encoder, Raw Patch and L2-AE. Is there some relationship between them?
Well, the codes in this repo is basically for training and evaluating Patch SVDD model.
You can reproduce the random encoder result by executing evaluation without training.
Thanks for your great work. In main_evaluated.py the result is shown as
print( f'| K64 | Det: {det_64:.3f} Seg:{seg_64:.3f} | K32 | Det: {det_32:.3f} Seg:{seg_32:.3f} | sum | Det: {det_sum:.3f} Seg:{seg_sum:.3f} | mult | Det: {det_mult:.3f} Seg:{seg_mult:.3f} ({obj})')
However, in the paper, you report Random Encoder, Raw Patch and L2-AE. Is there some relationship between them?