Closed crazySyaoran closed 5 years ago
Yes I'm sorry I found it and closed the issue. But I didn't find how do you change the hard (binary) result into a soft (real) predictions. Did you give some detail in your paper? Thanks
During training, binary predictions are used (via Sigmoid activation function). Since it is Sigmoid, the values will not always be 1 or 0, they will be close to either of these numbers. If you have a surface extraction function which can uses non binary values, it can be used to improve detail (on better trained models) and result in a less blocky model. MATLAB's isosurface
function supports these non binary values and hence the MATLAB version in this repo works better than the Python version.
Cool. Thank you.
It is explained under the section "Error Metric" - but it's Normalised Mean Error.