Updated batch processing description

_includes/batch_processing/batch_measure_nuclei_shape.py

@@ -15,6 +15,10 @@
 # Create a function that analyses one image
 # Below, this function will be called several times, for all images
 def analyse(image_path, output_folder):
+
+    # This prints which image is currently analysed
+    print("Analyzing:", image_path)
+
     image, axes, scales, units = open_ij_tiff(image_path)
 
     # Binarize the image using auto-thresholding
@@ -67,7 +71,6 @@ def analyse(image_path, output_folder):
                "https://github.com/NEUBIAS/training-resources/raw/master/image_data/xy_8bit__mitocheck_incenp_t70.tif"]
 
 for image_path in image_paths:
-    print("Analyzing:", image_path)
     analyse(image_path, output_dir)
 
 # %%

_includes/batch_processing/batch_measure_nuclei_shapes.md

@@ -2,3 +2,16 @@
 
 - In a previous module [there is a workflow to measure the shapes of nuclei in one image](https://neubias.github.io/training-resources/workflow_segment_2d_nuclei_measure_shape/index.html#2dnuclei)
 - Adapt this workflow for automated batch analysis of many images
+- Start by building the skeleton of the workflow without filling in the functionality;
+
+  Note that the code below runs fine, but does not produce any results:
+
+```
+def analyse(image_path, output_folder):
+    print("Analyzing:", image_path)
+    
+for image_path in image_paths:
+    analyse(image_path, output_dir)
+```
+
+ - Make sure the loop with the (almost) empty analyse function runs without error before filling in the image analysis steps