issue

[yunfan-li]

issue

[Yunfan-Li]

Have you checked the dimension of CCH?

[NWPU-Li]

I have set thd dimension of CCH with class_num

[NWPU-Li]

After 20 epochs, i tested 'ImageNet-dogs',i print len(indices) and i get 1,but 'CIFAR10/100' is True

[NWPU-Li]

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[Yunfan-Li]

Perhaps it is because the file organization of ImageNet-dogs is wrong. You may check the ground-truth labels and see if it contains 0-14.

[NWPU-Li]

I get the datasets from http://vision.stanford.edu/aditya86/ImageNetDogs/,it includes images and annotations .
How do i deal with?
Thanks.

[Yunfan-Li]

I command using ImageFolder following the instructions in https://pytorch.org/vision/stable/datasets.html#imagefolder.

[Yunfan-Li]

The dataset you downloaded seems to be inconsistent with the one used in the paper. In our experiments, the ImageNet-dogs data consists of 15 subclasses of the original Imagenet dataset, the indices of which are given in /datasets/ImageNet-dogs.txt.

[NWPU-Li]

I have already corrected the data consists of 15subclasses, and then I need to merge 'images' with 'annotations'？

[Yunfan-Li]

Please follow the instructions in https://pytorch.org/vision/stable/datasets.html#imagefolder and arrange images of different classes in different subfolders.

[NWPU-Li]

Now，i followed the indices and arrange images of different classes in in different subfolders with the indices,but i only get 2436 images...

[Yunfan-Li]

Each class contains 1300 images and thus there should be 19500 images in total.

[NWPU-Li]

The datasets with 120 classes downloaded from http://vision.stanford.edu/aditya86/ImageNetDogs, now, I process this dataset according to the index, but per class only has more than 100.

[Yunfan-Li]

Perhaps you need to download the ImageNet dataset and select its 15 subclasses.