Uncertainties for different classes / class imbalance problem

[ahmetdemirkayaee]

Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with a fewer number of images? Or will it be the other way around? Which part of the code should I tweak if I want to prioritize some of the classes during the active learning cycle? I really appreciate any help you can provide.

[nabi-rony]

Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with a fewer number of images? Or will it be the other way around? Which part of the code should I tweak if I want to prioritize some of the classes during the active learning cycle? I really appreciate any help you can provide.

Hello, I am also working kind of similar time of the problem where we have a class imbalance problem. Sometimes, we have some classes which don't have any testing samples. Just let me know if you get any solutions. Also, did you try a custom dataset? I tried with my own dataset, but I got a bunch of 0 or -1 for AP calculation and the mean AP is also some negative values. I am not sure why.

[AliceShynie]

Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with a fewer number of images? Or will it be the other way around? Which part of the code should I tweak if I want to prioritize some of the classes during the active learning cycle? I really appreciate any help you can provide.

Hello, I am also working kind of similar time of the problem where we have a class imbalance problem. Sometimes, we have some classes which don't have any testing samples. Just let me know if you get any solutions. Also, did you try a custom dataset? I tried with my own dataset, but I got a bunch of 0 or -1 for AP calculation and the mean AP is also some negative values. I am not sure why.

I am having the same problem. I trained it on FLIR dataset and I am getting nan values for my mean AP as well. Have you solved this?

[nabi-rony]

Hello, Thank you for the paper and the repo. I was wondering how can I deal with class imbalance during the active learning loop. Do you think the model will be choosing more samples from a class with a fewer number of images? Or will it be the other way around? Which part of the code should I tweak if I want to prioritize some of the classes during the active learning cycle? I really appreciate any help you can provide.

Hello, I am also working kind of similar time of the problem where we have a class imbalance problem. Sometimes, we have some classes which don't have any testing samples. Just let me know if you get any solutions. Also, did you try a custom dataset? I tried with my own dataset, but I got a bunch of 0 or -1 for AP calculation and the mean AP is also some negative values. I am not sure why.

I am having the same problem. I trained it on FLIR dataset and I am getting nan values for my mean AP as well. Have you solved this?
I solved the problem for my custom dataset. It happened as the classname in annotation didn't match with classname in VOC_CLASSES in /data/voc0712.py. It was upper and lower case issue. You may need to see the ground truth is found for each prediction.