Updated docs to clarify behaviour of inference/training

Updating docs to clarify inference, based on #20

Author: C-Achard

.gitignore

@@ -97,3 +97,4 @@ venv/
 /napari_cellseg3d/models/saved_weights/
 /docs/res/logo/old_logo/
 /reqs/
+*.db

docs/res/guides/inference_module_guide.rst

@@ -3,9 +3,13 @@
 Inference module guide
 =================================
 
-This module allows you to use  pre-trained segmentation algorithms (written in Pytorch) on volumes
+This module allows you to use  pre-trained segmentation algorithms (written in Pytorch) on 3D volumes
 to automatically label cells.
 
+.. important::
+    Currently, only inference on **3D volumes is supported**. Your image and label folders should both contain a set of
+    **3D image files**, currently either **.tif** or **.tiff**. Loading a folder of 2D images as a stack is not supported as of yet.
+
 Currently, the following pre-trained models are available :
 
 ==============   ================================================================================================
@@ -31,7 +35,7 @@ Interface and functionalities
 
 * **Loading data** :
 
-  | When launching the module, you will be asked to provide an **image folder** containing all the volumes you'd like to be labeled.
+  | When launching the module, you will be asked to provide an **image folder** containing all the 3D volumes you'd like to be labeled.
   | All images with the chosen extension (**.tif** or **.tiff** currently supported) in this folder will be labeled.
   | You can then choose an **output folder**, where all the results will be saved.
 

docs/res/guides/training_module_guide.rst

@@ -6,6 +6,11 @@ Training module guide
 This module allows you to train pre-defined Pytorch models for cell segmentation.
 Pre-defined models are stored in napari-cellseg-3d/models.
 
+.. important::
+    Currently, only inference on **3D volumes is supported**. Your image and label folders should both contain a set of
+    **3D image files**, currently either **.tif** or **.tiff**. Loading a folder of 2D images as a stack is not supported as of yet.
+
+
 Currently, the following pre-defined models are available :
 
 ==============   ================================================================================================
@@ -31,8 +36,8 @@ The training module is comprised of several tabs.
 
 1) The first one, **Data**, will let you set :
 
-* The path to the images folder
-* The path to the labels folder
+* The path to the images folder (3D image files)
+* The path to the labels folder (3D image files)
 * The path to the results folder
 
 * Whether to copy results to a zip file (for easier transferability)