+ 
Deep Learning Models#
+Naming models#
+Each model is saved in its own repository under the ivadomed organization. The convention for naming repositories is the following:
+model_task_animal_pathology_region_contrast_architecture
+
+Should be small letters only.
+
+Fields:
+- task = {seg, label, find}, default=seg
+- animal = {human, dog, cat, rat, mouse, ...}, default=human
+- pathology = {ms, sci}
+- region = {sc, gm, csf, brainstem, axon, myelin, ...}, default=sc
+- contrast = {t1, t2, t2star, dwi, sem, tem, oi, ...}, default=None
+- architecture = {unet2d, unet3d, filmCharley, hemisAndreanne}, default=unet2d
+
+Examples:
+
+model_seg_monkey_sc_t1_unet3d
+
+# multi-channel, multi-class
+model_seg_sc-gm_t1-t2_unet3d
+Packaging models#
+Models to be used by 3rd party software (e.g. SCT) should be uploaded as โassetsโ to a release of the repository. The steps are:
+-
+
Create a release of the repository. The tag and title of the release should be
rYYYYMMDD, example:r20211223.
+Put the model and JSON file inside a folder that has the name of the model.
+Zip the folder and upload it as an asset in the release
+Publish the release.
+