After oversampling/undersampling is it always appropriate to adjust probabilities using the odds ratio regardless of the sampling method used?

Question

1. I have an imbalanced dataset where the target class is <1% of sample.
2. I apply oversampling or undersampling e.g. https://github.com/scikit-learn-contrib/imbalanced-learn.
3. I run random forest on the resampled data
4. I adjust probabilities back to the original sample by multiplying by the ratio of odds ratios as explained here: https://yiminwu.wordpress.com/2013/12/03/how-to-undo-oversampling-explained/

Is step 4 always the same regardless of the type of oversampling or undersampling employed?