Open YIBO-0805 opened 2 years ago
Hi, ImageNet-10 is a subset of ImageNet with 10 class indices provided in the dataset folder. The data augmentation for ImageNet-10 could be found at https://github.com/Yunfan-Li/Contrastive-Clustering/blob/dfda491ce22541265228e119d7e708fe752d4ad7/modules/transform.py#L21.
Thank you for your reply. Following the dataset folder, I got 14,216 images. I would like to know how you screen out 13,000 images and how many images are in each category.
In our experiment, the training set of ImageNet is used with 1300 images in each class.
Hi,
I did not find a description about the distribution of the Imagenet-10 and the data-augment method you used in your paper and code. And I get a bad accuracy on this dataset.
I would like to know if you could describe in detail or if I get something wrong?