docs(math): docs for image pair operations

.github/workflows/build-and-publish-docs.yml

@@ -3,7 +3,7 @@ on:
   push:
     branches:
       - master
-      - qy/add-plantseg-v1-installation
+      - qy/mask-pred
 
 permissions:
   contents: write

docs/chapters/plantseg_interactive_napari/preprocessing.md

@@ -11,3 +11,9 @@ This section describes the data processing functionalities available in PlantSeg
 ## Widget: Image Rescaling
 
 --8<-- "napari/dataprocessing/rescale.md"
+
+## Widget: Image Pair Operations
+
+```python exec="1" html="1"
+--8<-- "napari/dataprocessing/image_pair_operations.py"
+```

docs/chapters/python_api/functionals/data_processing.md

@@ -10,6 +10,7 @@ Basic data processing functions are provided in the `dataprocessing` module. The
 ::: plantseg.functionals.dataprocessing.dataprocessing.image_median
 ::: plantseg.functionals.dataprocessing.dataprocessing.image_gaussian_smoothing
 ::: plantseg.functionals.dataprocessing.dataprocessing.image_crop
+::: plantseg.functionals.dataprocessing.dataprocessing.process_images
 
 ## Segmentation Functions
 

docs/chapters/python_api/tasks/dataprocessing_tasks.md

@@ -1,41 +1,45 @@
-# Import and export tasks
+# Data Processing Tasks
 
-## Gaussian smoothing task
+## Image Preprocessing Tasks
+
+### Gaussian smoothing task
 
 ::: plantseg.tasks.dataprocessing_tasks.gaussian_smoothing_task
 
-## Image cropping task
+### Image cropping task
 
 ::: plantseg.tasks.dataprocessing_tasks.image_cropping_task
 
-
-## Image rescale to shape task
+### Image rescale to shape task
 
 ::: plantseg.tasks.dataprocessing_tasks.image_rescale_to_shape_task
 
-
-## Image rescale to voxel size task
+### Image rescale to voxel size task
 
 ::: plantseg.tasks.dataprocessing_tasks.image_rescale_to_voxel_size_task
 
-## Set image voxel size task
+### Set image voxel size task
 
 ::: plantseg.tasks.dataprocessing_tasks.set_voxel_size_task
 
-## Label Postprocessing
+## Image pair operation task
+
+::: plantseg.tasks.dataprocessing_tasks.image_pair_operation_task
+
+## Label Postprocessing Tasks
 
-## Remove false positives task
+### Remove false positives task
 
 ::: plantseg.tasks.dataprocessing_tasks.remove_false_positives_by_foreground_probability_task
 
-## Fix Over/Under segmentation task
+### Fix Over/Under segmentation task
 
 ::: plantseg.tasks.dataprocessing_tasks.fix_over_under_segmentation_from_nuclei_task
 
-## Set biggest object as background task
+### Set biggest object as background task
 
 ::: plantseg.tasks.dataprocessing_tasks.set_biggest_instance_to_zero_task
 
-## Relabel task
+### Relabel task
 
 ::: plantseg.tasks.dataprocessing_tasks.relabel_segmentation_task

docs/snippets/napari/dataprocessing/image_pair_operations.py

@@ -0,0 +1,10 @@
+import sys
+
+sys.path.append("docs/snippets")
+
+from napari_widgets_render import render_widget
+
+from plantseg.viewer_napari.widgets import widget_image_pair_operations
+
+html = render_widget(widget_image_pair_operations)
+print(html)

plantseg/tasks/dataprocessing_tasks.py

@@ -326,6 +326,9 @@ def image_pair_operation_task(
         image1 (PlantSegImage): First image to process.
         Image2 (PlantSegImage): Second image to process.
         operation (str): Operation to perform on the images.
+        normalize_input (bool): Normalize input images before processing.
+        clip_output (bool): Clip output values to the range [0, 1].
+        normalize_output (bool): Normalize output values to the range [0, 1].
 
     Returns:
         PlantSegImage: New image resulting from the operation.

tests/functionals/dataprocessing/test_image_math.py

@@ -11,15 +11,13 @@
 )
 
 
-# Mock normalize_01 function (replace with your actual implementation)
 def normalize_01(image: np.ndarray) -> np.ndarray:
     min_val, max_val = image.min(), image.max()
     if max_val - min_val == 0:
         return np.zeros_like(image)
     return (image - min_val) / (max_val - min_val)
 
 
-# Test cases for process_images
 @pytest.mark.parametrize(
     "operation, expected_result",
     [
@@ -103,12 +101,16 @@ def test_max_images():
     assert np.allclose(result, expected), "Max operation failed"
 
 
-# Error handling
 def test_process_images_invalid_operation():
     image1 = np.array([[1, 2], [3, 4]])
     image2 = np.array([[1, 2], [3, 4]])
 
     with pytest.raises(ValueError, match="Unsupported operation: invalid"):
         process_images(
-            image1, image2, operation="invalid", normalize_input=False, clip_output=False, normalize_output=False
+            image1,
+            image2,
+            operation="invalid",
+            normalize_input=False,
+            clip_output=False,
+            normalize_output=False,
         )