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I think there exists a data leakage problem in your code, which severely hurts the fair comparison with other methods.
Take coco 10shot for example, you will first construct a meta-data set encomprising 30 (3x shots) (prn_image, prn_mask) pairs for each class. The image indexes of these sampled images are saved in a file named annotations/instances_shot2014.json.
After that, roidb needs to be contructed to provide query samples for finetuning purpose. According to the definition of few-shot setting, you can only access to the N-shot (N instances per class) data no matter whether you perform finetuning or not. Therefore, the roidb dataset should contain the same instances as in meta-data set, otherwise it will exceed the designated number of shots. However, as I find in your code, you does not save the anno_index of the selected instances in meta-data set. Instead, you again randomly sample the shot instances from the images list indicated in annotations/instances_shot2014.json. In this case, I am concern about how you guarantee that the newly sampled instances are exactly the same as the ones in meta-data set.
Hope that you can check about this issue and clarify my concern. Thanks a lot.
The text was updated successfully, but these errors were encountered:
Ze-Yang
changed the title
How to ensure that the N-shot(object) meta data are exactly the same as the input(roidb) of the model
Report data leakage that causes unfair few-shot setting
Jan 6, 2021
I think there exists a data leakage problem in your code, which severely hurts the fair comparison with other methods.
Take coco 10shot for example, you will first construct a meta-data set encomprising 30 (3x shots) (prn_image, prn_mask) pairs for each class. The image indexes of these sampled images are saved in a file named
annotations/instances_shot2014.json
.After that, roidb needs to be contructed to provide query samples for finetuning purpose. According to the definition of few-shot setting, you can only access to the N-shot (N instances per class) data no matter whether you perform finetuning or not. Therefore, the roidb dataset should contain the same instances as in meta-data set, otherwise it will exceed the designated number of shots. However, as I find in your code, you does not save the
anno_index
of the selected instances in meta-data set. Instead, you again randomly sample the shot instances from the images list indicated inannotations/instances_shot2014.json
. In this case, I am concern about how you guarantee that the newly sampled instances are exactly the same as the ones in meta-data set.Hope that you can check about this issue and clarify my concern. Thanks a lot.
The text was updated successfully, but these errors were encountered: