Support for distributed feature extraction / training

[pierotofy]

• Modify pctrain by adding a --extract-features <path>.opcfeat.bin parameter. When set, execution should stop at https://github.com/uav4geo/OpenPointClass/blob/main/randomforest.cpp#L30 and https://github.com/uav4geo/OpenPointClass/blob/main/gbm.cpp#L45
• Serialize the required vectors (for RF that's gt, ft, GBT populates the structures similarly although not identically). It might also be possible to serialize in a single format regardless of RF or GBT if one creates a new function that simply does the serialization (like train, but stops after creating the features). One might want to encode the various scale, radius, treeDepth, etc. parameters into the serialized output to avoid repeating them and validating other serialized outputs. All serialized output's parameters from different processes need to match.
• Modify pctrain by checking for .opcfeat.bin file input extensions; if all files passed as input are .opcfeat.bin, then read features directly instead of computing them by adapting the rf::train and gbt::train functions. If you have serialized the scale, radius, etc. parameters one can read them from the serialized files instead of passing them manually.

[hobu]

Implemented over here but only for rf, and it isn't so convenient to use quite yet. It seems to work ok though.

[Ty4Code]

Implemented over here but only for rf, and it isn't so convenient to use quite yet. It seems to work ok though.

This is awesome stuff, thanks for sharing!

I'm considering trying to adapt it to save the files in something more Python/Pandas friendly like .CSV. If anyone might find it useful let me know, otherwise will just use it for my own training