Open omg777 opened 6 years ago
Try down sampling class1 to 10,000 to balance and train the model again.
Otherwise, if it makes sense to do some image augmentation to create more samples of class2, it is recommended as well.
Easily doable and suggested is adding gaussian noise to class2 images and create new samples. That way you don't have tagging problem for augmented images.
is there any hard mining methods recommended? thanks!
I am trying to fine-tune the model with yolo.weight.
If the data is imbalanced between the N classes like
number of class 1 data : 200,000 instances number of class 2 data : 10,000 intances ...etc
I wonder if it occurs bad influence.