Merge branch 'master' into v4

axondeepseg · Nov 11, 2021 · 92f1013 · 92f1013
2 parents 5ab224f + 5596b72
commit 92f1013
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Showing 20 changed files with 104 additions and 31 deletions.
diff --git a/.readthedocs.yml b/.readthedocs.yml
@@ -0,0 +1,14 @@
+# .readthedocs.yml
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+# Required
+version: 2
+
+# Build documentation in the docs/ directory with Sphinx
+sphinx:
+  configuration: docs/source/conf.py
+  fail_on_warning: false
+
+conda:
+  environment: docs/environment.yml
diff --git a/AxonDeepSeg/download_tests.py b/AxonDeepSeg/download_tests.py
@@ -10,7 +10,7 @@ def download_tests(destination=None):
         destination = convert_path(destination)
         test_files_destination = destination / "__test_files__"
 
-    url_tests = "https://github.com/axondeepseg/data-testing/archive/refs/tags/r20210625.zip"  
+    url_tests = "https://github.com/axondeepseg/data-testing/archive/refs/tags/r20210906b.zip"  
     files_before = list(Path.cwd().iterdir())
 
     if (

diff --git a/AxonDeepSeg/morphometrics/compute_morphometrics.py b/AxonDeepSeg/morphometrics/compute_morphometrics.py
@@ -156,11 +156,19 @@ def get_axon_morphometrics(im_axon, path_folder=None, im_myelin=None, pixel_size
                 # Perimeter of axonmyelin instance (outer perimeter of myelin) in micrometers
                 axonmyelin_perimeter = prop_axonmyelin.perimeter * pixelsize
 
-                stats['myelin_thickness'] = myelin_thickness
-                stats['myelin_area'] = myelin_area
-                stats['axonmyelin_area'] = axonmyelin_area
-                stats['axonmyelin_perimeter'] = axonmyelin_perimeter
-                stats['gratio'] = (axon_diam / 2) / (axon_diam / 2 + myelin_thickness)
+                try:
+                    stats['gratio'] = (axon_diam / 2) / (axon_diam / 2 + myelin_thickness)
+                    stats['myelin_thickness'] = myelin_thickness
+                    stats['myelin_area'] = myelin_area
+                    stats['axonmyelin_area'] = axonmyelin_area
+                    stats['axonmyelin_perimeter'] = axonmyelin_perimeter
+                except ZeroDivisionError:
+                    print(f"ZeroDivisionError caught on invalid object #{idx}.")
+                    stats['gratio'] = float('NaN')
+                    stats['myelin_thickness'] = float('NaN')
+                    stats['myelin_area'] = float('NaN')
+                    stats['axonmyelin_area'] = float('NaN')
+                    stats['axonmyelin_perimeter'] = float('NaN')
 
             else:
                 print(

diff --git a/AxonDeepSeg/morphometrics/launch_morphometrics_computation.py b/AxonDeepSeg/morphometrics/launch_morphometrics_computation.py
@@ -216,10 +216,10 @@ def main(argv=None):
             try:
                 # Export to excel
                 if morph_filename.endswith('.xlsx'):
-                    pd.DataFrame(x).to_excel(current_path_target.parent / morph_filename)
+                    pd.DataFrame(x).to_excel(current_path_target.parent / morph_filename, na_rep='NaN')
                 # Export to csv    
                 else: 
-                    pd.DataFrame(x).to_csv(current_path_target.parent / morph_filename)
+                    pd.DataFrame(x).to_csv(current_path_target.parent / morph_filename, na_rep='NaN')
 
                 # Generate the index image
                 indexes_outfile = current_path_target.parent /(str(current_path_target.with_suffix("")) +

diff --git a/README.md b/README.md
@@ -11,7 +11,7 @@ Based on a convolutional neural network architecture. Pixels are classified as e
 
 For more information, see the [documentation website](http://axondeepseg.readthedocs.io/).
 
-![alt tag](https://github.com/neuropoly/axondeepseg/blob/master/docs/source/_static/fig0.png)
+![alt tag](https://raw.githubusercontent.com/axondeepseg/doc-figures/main/index/fig0.png)
 
 
 

diff --git a/ads_plugin.py b/ads_plugin.py
@@ -33,7 +33,7 @@
 import pandas as pd
 import imageio
 
-VERSION = "0.2.18"
+VERSION = "0.2.19"
 
 class ADSsettings:
     """
@@ -54,6 +54,7 @@ def __init__(self, ads_control):
         self.use_custom_resolution = False  # Unused
         self.custom_resolution = 0.07  # Unused
         self.zoom_factor = 1.0
+        self.axon_shape = "circle"
 
     def on_settings_button(self, event):
         """
@@ -65,20 +66,44 @@ def on_settings_button(self, event):
 
         # Add the overlap value to the settings menu
         sizer_overlap_value = wx.BoxSizer(wx.HORIZONTAL)
+        overlap_value_tooltip = wx.ToolTip("Represents the number of pixels that overlap two patches of the image when "
+                                           "applying the prediction model")
         sizer_overlap_value.Add(wx.StaticText(self.settings_frame, label="Overlap value (pixels): "))
         self.overlap_value_spinCtrl = wx.SpinCtrl(self.settings_frame, min=0, max=100, initial=self.overlap_value)
         self.overlap_value_spinCtrl.Bind(wx.EVT_SPINCTRL, self.on_overlap_value_changed)
+        self.overlap_value_spinCtrl.SetToolTip(overlap_value_tooltip)
         sizer_overlap_value.Add(self.overlap_value_spinCtrl, flag=wx.SHAPED, proportion=1)
         frame_sizer_h.Add(sizer_overlap_value)
 
         # Add the zoom factor to the settings menu
         sizer_zoom_factor = wx.BoxSizer(wx.HORIZONTAL)
+        zoom_factor_tooltip = wx.ToolTip("When applying the model, the pixel size of the image will be "
+                                         "multiplied by this number. The zoom factor does not affect the computation of morphometrics.")
         sizer_zoom_factor.Add(wx.StaticText(self.settings_frame, label="Zoom factor: "))
         self.zoom_factor_spinCtrlDouble = wx.SpinCtrlDouble(self.settings_frame, initial=self.zoom_factor, inc=0.0001)
         self.zoom_factor_spinCtrlDouble.Bind(wx.EVT_SPINCTRLDOUBLE, self.on_zoom_factor_changed)
+        self.zoom_factor_spinCtrlDouble.SetToolTip(zoom_factor_tooltip)
         sizer_zoom_factor.Add(self.zoom_factor_spinCtrlDouble, flag=wx.SHAPED, proportion=1)
         frame_sizer_h.Add(sizer_zoom_factor)
 
+        # Add the axon shape selection
+        axon_shape_choices = ["circle", "ellipse"]
+        sizer_axon_shape = wx.BoxSizer(wx.HORIZONTAL)
+        axon_shape_tooltip = wx.ToolTip('Select what is the shape of the axons that will be considered when computing '
+                                        'the morphometrics. "circle" will use the equivalent diameter (diameter of a circle with the same area as the axon). '
+                                        '"ellipse" will use minor axis of a fitted ellipse as diameter.')
+        sizer_axon_shape.Add(wx.StaticText(self.settings_frame, label="Axon shape: "))
+        self.axon_shape_combobox = wx.ComboBox(
+            self.settings_frame,
+            choices=axon_shape_choices,
+            size=(100, 20),
+            value=self.axon_shape
+        )
+        self.axon_shape_combobox.Bind(wx.EVT_COMBOBOX, self.on_axon_shape_combobox_item_selected)
+        self.axon_shape_combobox.SetToolTip(axon_shape_tooltip)
+        sizer_axon_shape.Add(self.axon_shape_combobox, flag=wx.SHAPED, proportion=1)
+        frame_sizer_h.Add(sizer_axon_shape)
+
         # Add the done button
         sizer_done_button = wx.BoxSizer(wx.HORIZONTAL)
         done_button = wx.Button(self.settings_frame, label="Done")
@@ -95,6 +120,9 @@ def on_overlap_value_changed(self, event):
     def on_zoom_factor_changed(self, event):
         self.zoom_factor = self.zoom_factor_spinCtrlDouble.GetValue()
 
+    def on_axon_shape_combobox_item_selected(self, event):
+        self.axon_shape = self.axon_shape_combobox.GetStringSelection()
+
     def on_done_button(self, event):
         # TODO: make sure every setting is saved
         self.settings_frame.Close()
@@ -660,7 +688,9 @@ def on_compute_morphometrics_button(self, event):
 
         # Compute statistics
         stats_array, index_image_array = compute_morphs.get_axon_morphometrics(im_axon=pred_axon, im_myelin=pred_myelin,
-                                             pixel_size=pixel_size, return_index_image=True)
+                                                                               pixel_size=pixel_size,
+                                                                               axon_shape=self.settings.axon_shape,
+                                                                               return_index_image=True)
         for stats in stats_array:
 
             x = np.append(x,

diff --git a/docs/environment.yml b/docs/environment.yml
@@ -0,0 +1,10 @@
+# File: docs/environment.yaml
+
+name: docs
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - sphinx==4.2.0
+  - sphinx_rtd_theme>=0.2.4
+  - recommonmark
diff --git a/docs/source/_static/GUI_image.png b/docs/source/_static/GUI_image.png
diff --git a/docs/source/_static/bad_mask_example.png b/docs/source/_static/bad_mask_example.png
diff --git a/docs/source/_static/fig0.png b/docs/source/_static/fig0.png
diff --git a/docs/source/_static/fig1.png b/docs/source/_static/fig1.png
diff --git a/docs/source/_static/fig2.png b/docs/source/_static/fig2.png
diff --git a/docs/source/_static/fig3.png b/docs/source/_static/fig3.png
diff --git a/docs/source/_static/good_mask_example.png b/docs/source/_static/good_mask_example.png
diff --git a/docs/source/_static/image_example.png b/docs/source/_static/image_example.png
diff --git a/docs/source/documentation.rst b/docs/source/documentation.rst
@@ -100,6 +100,12 @@ Once your virtual environment is installed and activated, install the AxonDeepSe
 
 .. WARNING :: When re-installing the application, the ``default_SEM_model``, ``default_TEM_model`` and ``model_seg_pns_bf`` folders in ``AxonDeepSeg/models`` will be deleted and re-downloaded. Please do not store valuable data in these folders.
 
+.. raw:: html
+
+   <iframe width="700" height="394" src="https://www.youtube.com/embed/7RwZihR0HWk" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
+
+
+
 Testing the installation
 ------------------------
 .. WARNING :: Ensure that the virtual environment is activated.
@@ -133,7 +139,7 @@ Graphical User Interface (GUI) (optional)
 
 AxonDeepSeg can be run via a Graphical User Interface (GUI) instead of the Terminal command line. This GUI is a plugin for the software `FSLeyes <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes>`_. Beyond the convenience of running AxonDeepSeg with the click of a button, this GUI is also an excellent way to manually correct output segmentations (if need to).
 
-.. image:: _static/GUI_image.png
+.. image:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/introduction/GUI_image.png
 
 Launch FSLeyes ::
 
@@ -150,8 +156,7 @@ In case, you find trouble installing FSLeyes plugin for ADS you could refer the
 
 .. raw:: html
 
-   <div style="position: relative; padding-bottom: 5%; height: 0; overflow: hidden; max-width: 100%; height: auto;">
-     <iframe width="700" height="394" src="https://www.youtube.com/embed/qzWeG5vaVyo" frameborder="0" allowfullscreen></iframe>
+   <iframe width="700" height="394" src="https://www.youtube.com/embed/ImElcp9_k6Y" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
 
 
 .. NOTE :: For some users, the ADScontrol tab will not appear after first installing the plugin.
@@ -560,21 +565,21 @@ These options and detailed procedures are described in the section below "Manual
 
 Here are examples of an image, a good manual mask and a bad manual mask.
 
-.. figure:: _static/image_example.png
+.. figure:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/introduction/image_example.png
     :width: 750px
     :align: center
     :alt: Image example
 
     Image example
 
-.. figure:: _static/good_mask_example.png
+.. figure:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/introduction/good_mask_example.png
     :width: 750px
     :align: center
     :alt: Good manual mask example
 
     Good manual mask example
 
-.. figure:: _static/bad_mask_example.png
+.. figure:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/introduction/bad_mask_example.png
     :width: 750px
     :align: center
     :alt: Bad manual mask example

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -10,7 +10,7 @@ Welcome to the AxonDeepSeg framework. In this site you will find the documentati
 
 AxonDeepSeg is a segmentation software for microscopy data of nerve fibers. It is based on a convolutional neural network.
 
-.. image:: _static/fig0.png
+.. image:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/index/fig0.png
    :scale: 35 %
    :alt: alternate text
    :align: center
@@ -19,7 +19,7 @@ AxonDeepSeg is a segmentation software for microscopy data of nerve fibers. It i
 
 * AxonDeepSeg pipeline:
 
-.. image:: _static/fig1.png
+.. image:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/index/fig1.png
    :scale: 35 %
    :alt: alternate text
    :align: center
@@ -28,7 +28,7 @@ AxonDeepSeg is a segmentation software for microscopy data of nerve fibers. It i
 
 * Segmentation of axon/myelin from various species/contrasts:
 
-.. image:: _static/fig2.png
+.. image:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/index/fig2.png
    :scale: 35 %
    :alt: alternate text
    :align: center
@@ -37,7 +37,7 @@ AxonDeepSeg is a segmentation software for microscopy data of nerve fibers. It i
 
 * Segmentation of full slice histology and morphometrics extraction:
 
-.. image:: _static/fig3.png
+.. image:: https://raw.githubusercontent.com/axondeepseg/doc-figures/main/index/fig3.png
    :scale: 35 %
    :alt: alternate text
    :align: center

diff --git a/readthedocs.yml b/readthedocs.yml
diff --git a/setup.py b/setup.py
@@ -48,11 +48,6 @@ def run(self):
                         'models/default_TEM_model/*',
                         'data_test/*'],
     },
-    extras_require={
-        'docs': ['sphinx>=1.6',
-                 'sphinx_rtd_theme>=0.2.4',
-                 'recommonmark'],
-    },
     include_package_data=True,
     entry_points={
         'console_scripts': [

diff --git a/test/morphometrics/test_compute_morphometrics.py b/test/morphometrics/test_compute_morphometrics.py
@@ -43,6 +43,12 @@ def setup(self):
         pred_myelin_path = self.test_folder_path / ('image' + str(myelin_suffix))
         self.pred_myelin = imageio_imread(pred_myelin_path, as_gray=True)
 
+        # Image to test NaN output
+        bad_pred_axon_path = self.test_folder_path / ('invalid_gratio' + str(axon_suffix))
+        self.bad_pred_axon = imageio_imread(bad_pred_axon_path, as_gray=True)
+        bad_pred_myelin_path = self.test_folder_path / ('invalid_gratio' + str(myelin_suffix))
+        self.bad_pred_myelin = imageio_imread(bad_pred_myelin_path, as_gray=True)
+
         # simulated image of axon myelin where axon shape is circle; `plane angle = 0`
         self.path_sim_image_circle = (
             self.testPath /
@@ -175,6 +181,16 @@ def test_get_axon_morphometrics_with_myelin_mask_with_axon_as_ellipse(self):
 
         assert stats_array[1]['gratio'] == pytest.approx(0.78, rel=0.01)
 
+    @pytest.mark.unit
+    def test_get_axon_morphometrics_with_invalid_gratio_with_axon_as_ellipse(self):
+        stats_array = get_axon_morphometrics(
+            self.bad_pred_axon,
+            str(self.test_folder_path),
+            im_myelin=self.bad_pred_myelin,
+            axon_shape=self.axon_shape
+            )
+        assert np.isnan(stats_array[0]['gratio'])
+
     @pytest.mark.unit
     def test_get_axon_morphometrics_with_myelin_mask_simulated_axons(self):
         path_pred = (