root_feature generates nan value with zero division

I encountered an error that happened during Flann feature matching. The reason is one of the feature descriptors for one specific image has all nan values. After further investigation, the problem is caused by the raw feature descriptor being all zeros, based on how root_feature is calculated, there will be a zero division and cause nan value.
https://github.com/mapillary/OpenSfM/blob/c798da16206aa52395eaef09ea4d7746028479d3/opensfm/features.py#L282-L288

This happens rarely and mostly probably due to a feature point having all 0 intensity pixels around it, here is an example dumped in the middle of the feature extraction (the problematic feature point is at the under-exposed dark area at the left side). It can be reproduced by reading the raw gray image and using the below function call to reproduce

from opensfm import features
import cv2
image = cv2.imread("path_to_image", 0) # read gray image 
features.extract_features_sift(image, {'sift_edge_threshold':10.0, 'sift_peak_threshold':0.066, 'feature_root':True}, 16000)

I guess the solution is adding an epsilon value or checking if s is zero. But I'm not sure if keeping all-zero features is reasonable, maybe discarding them is better.

Start in opensfm/features.py at the linked lines where root_feature normalizes the descriptor, then run the provided extract_features_sift reproduction with the zero-valued image region. Decide how zero descriptors should be handled and verify that the reproduction no longer produces NaN feature values.