Please see the README.md
in each folder of this directory for more details.
For example, to run a segmentation network (*):
# training
net_segment train -c /path/to/customised_config
# inference
net_segment inference -c /path/to/customised_config
where /path/to/customised_config
implements all parameters listed by running:
net_segment -h
please see configuration documentations for more details and config file examples.
Commandline parameters override the default settings defined in /path/to/customised_config
.
For example,
# training
net_segment train -c /path/to/customised_config --lr 0.1
Uses all parameter specified in /path/to/customised_config
but sets the
learning rate to 0.1
(*) Please note that these instructions are for a pip
-installed NiftyNet.
If you are using the NiftyNet command line interface from within the NiftyNet source code, please use python net_segment.py [...]
(provided that the current working directory is the root folder of the NiftyNet repository clone) instead of net_segment [...]
.