Added organization description for deep learning models

data/README.md

@@ -1,26 +1,41 @@
 # <span>💾</span> Data
 
+## Dataset curation
+
 For the details of how we structure datasets at the lab, see:
 
 ```{toctree}
 :maxdepth: 1
 dataset-curation
 ```
 
+## Dataset storage
+
+MRI, microscopy and other research data are stored in the following servers:
+
+```{toctree}
+:maxdepth: 1
+git-datasets
+duke
+```
+
+And [here](https://docs.google.com/spreadsheets/d/1yjcA8Z0COn4OZxusIDHjStH2DpeXvscsj-aWE2X-_sg) is a useful list of MRI data to use for various projects.
+
+
+## Dataset management (admin)
+
 For instructions on how to do various admin tasks on our data server, see:
 
 ```{toctree}
 :maxdepth: 1
 admin-guide
 ```
 
-MRI, microscopy and other research data are stored in the following servers:
+## Deep learning models
+
+If you train deep learning models, here's how to organize them:
 
 ```{toctree}
 :maxdepth: 1
-git-datasets
-duke
-django
+deeplearning-models
 ```
-
-[Here](https://docs.google.com/spreadsheets/d/1yjcA8Z0COn4OZxusIDHjStH2DpeXvscsj-aWE2X-_sg) is a useful list of MRI data to use for various projects.

data/deeplearning-models.md

@@ -0,0 +1,34 @@
+# Deep Learning Models
+
+## Naming models
+
+Each model is saved in its own repository under the [ivadomed](https://github.com/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](https://spinalcordtoolbox.com/)) should be uploaded as 'assets' 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.