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Me too. I get
Distance from dog(cabinet)+dog(bed) to dog(shelf): 0.025099006366425383
Distance from dog(bag)+dog(box) to dog(shelf): 0.7551661411955383
Distance from dog(bench)+dog(bike) to dog(shelf): 1.0487592910420251
Distance from dog(boat)+dog(surfboard) to dog(shelf): 1.3317174855037681
In my case, after editing the code quite a bit to finally make main_generalization work on Domain generalization example, I have very strong accuracy ~59% when training on dog(boat)+dog(surfboard). Only the accuracy on dog(shelf) is low (28%) but still not matching at all what is reported in Table 1... I don't know what are the 129 and 400 images though... In my case dog(shelf) is of size 306 images for ex.
Hello,
How to reproduce the distances of Table 1 in the paper ?
When running the script of
dataset/domain_generalization_cat_dog.py
, I getinstead of
d=0.44
Is there specific data to be included or removed?
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