Open kenrickfernandes opened 3 years ago
Sounds like you know what you are doing, but just in case, did you also remember to turn down the colour-based data augmentation? E.g., https://www.ccoderun.ca/darkmark/DataAugmentationColour.html
Yes, I have removed all color-based augmentations except exposure. Do you think removing exposure augmentations would help? Thanks for the reply!
A cfg parameter called "counters_per_class" exists for Object Detection to tackle imbalanced data. Is it possible to add this feature for classification purposes? And if not, could you guide me on how to tackle class imbalance for classification purposes? (Darknet53 model used) I have a scenario where two classes look very similar, the only difference being a small part of the objects' color. Object A has a lot of samples (9k) and Object B has around 2k samples. Upon testing, all samples under Object B are classified as Object A. How do I resolve this? Thanks for your help!