Each output represents interface of a conformation and contains a set of local environments (*e.g. atomic density map, structure classes (S,C,R), topology of the interface, ...*)
An atomic density map is a 4 dimensional tensor: a voxelized 3D grid with a size of ```24*24*24```. Each voxel encodes some characteristics of the protein atoms. Namely, the first 167 dimensions correspond to the
atom types that can be found in amino acids (without the hydrogen). This dimension can be reduced to 4 element symbols (C,N,O,S) by running ```python generate_cubes_reduce_channels_multiproc.py```.
### Deep learning framework
Following commands will use the trained models that can be found in the directory 'Models'. This directory includes 3 sets of models:
