Hello,
I’m training detectnet-v2 on custom dataset. The dataset contains 11 classes that are not balanced in the dataset. I assigned different weights (class_weight) to the classes in the training spec file to offset the imbalance. I’m not sure though whether to set the enable_autoweighing paramter to True or False.
Thank you
You can set it to True.
Refer to
Distribute the dataset class: How do I balance the weight between classes if the dataset has significantly higher samples for one class versus another?
To account for imbalance, increase the class_weight for classes with fewer samples. You can also try disabling enable_autoweighting; in this case initial_weight is used to control cov/regression weighting. It is important to keep the number of samples of different classes balanced, which helps improve mAP.
Thank you