Update Cellpose for reproducibility

tools/cellpose/cellpose.xml

@@ -2,7 +2,7 @@
     <description>with Cellpose</description>
     <macros>
         <token name="@TOOL_VERSION@">3.1.0</token>
-        <token name="@VERSION_SUFFIX@">0</token>
+        <token name="@VERSION_SUFFIX@">1</token>
         <xml name="channel">
             <option value="0" selected="true">grayscale/None</option>
             <option value="1">red</option>
@@ -19,6 +19,7 @@
     <version_command>echo "@VERSION@"</version_command>
     <command detect_errors="exit_code">
          <![CDATA[
+        export MKL_NUM_THREADS=1 &&
         export CELLPOSE_LOCAL_MODELS_PATH='cellpose_models' &&
         mkdir -p segmentation &&
         ln -s '${img_in}' ./image.${img_in.ext} &&
@@ -34,7 +35,7 @@
         <inputs name="inputs" />
     </configfiles>
     <inputs>
-        <param name="img_in" type="data" format="ome.tiff,tiff,jpeg,png" label="Choose the image file for segmention (usually after registration)"/>
+        <param name="img_in" type="data" format="ome.tiff,tiff,jpg,png" label="Choose the image file for segmention (usually after registration)"/>
         <param name="model_type" type="select" label="Choose the pre-trained model type">
             <option value="nuclei" selected="true">nuclei</option>
             <option value="cyto">cyto</option>
@@ -115,7 +116,9 @@
             <param name="model_type" value="cyto"/>
             <param name="chan" value="2"/>
             <param name="chan2" value="3"/>
-            <param name="diameter" value="50"/>
+            <section name="options">
+                <param name="diameter" value="50"/>
+            </section>
             <output name="cp_mask" file="img02_cp_masks_diameter.tif" compare="image_diff"/>
             <output name="cp_segm" file="img02_cp_segm_diameter.png" compare="image_diff"/>
         </test>

tools/cellpose/cp_segmentation.py

@@ -6,9 +6,20 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import skimage.io
+import torch
 from cellpose import models, plot, transforms
 
 
+# Make sure, that MKL_NUM_THREADS is set to 1, to ensure reproducibility:
+# https://forum.image.sc/t/reproducibility-how-we-spent-years-building-containers-and-then-mkl-decided-to-screw-our-results/109599
+assert str(os.environ['MKL_NUM_THREADS']) == '1'
+
+# Apply PyTorch guidelines for reproducibility
+torch.backends.cudnn.benchmark = True
+torch.backends.cudnn.deterministic = True
+torch.manual_seed(0)
+
+
 def main(inputs, img_path, img_format, output_dir):
     """
     Parameter