Merge branch 'master' into qy/unify-prediction

.pre-commit-config.yaml

@@ -9,12 +9,12 @@ default_install_hook_types:
 
 repos:
   - repo: https://github.com/crate-ci/typos
-    rev: v1.27.0
+    rev: typos-dict-v0.11.37
     hooks:
       - id: typos
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.7.2
+    rev: v0.8.1
     hooks:
       - id: ruff
         types_or: [python, pyi, jupyter]

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/__version__.py

@@ -1 +1 @@
-__version__ = '2.0.0a7'
+__version__ = '2.0.0a8'

plantseg/core/image.py

@@ -331,7 +331,7 @@ def to_h5(self, path: Path | str, key: str | None, mode: Literal["a", "w", "w-"]
         if isinstance(path, str):
             path = Path(path)
 
-        if path.suffix not in H5_EXTENSIONS:
+        if path.suffix.lower() not in H5_EXTENSIONS:
             raise ValueError(f"File format {path.suffix} not supported, should be one of {H5_EXTENSIONS}")
 
         key = key if key is not None else self.name

plantseg/functionals/dataprocessing/__init__.py

@@ -3,8 +3,11 @@
     remove_false_positives_by_foreground_probability,
 )
 from plantseg.functionals.dataprocessing.dataprocessing import (
+    ImagePairOperation,
+    add_images,
     compute_scaling_factor,
     compute_scaling_voxelsize,
+    divide_images,
     fix_layout,
     fix_layout_to_CYX,
     fix_layout_to_CZYX,
@@ -14,10 +17,14 @@
     image_gaussian_smoothing,
     image_median,
     image_rescale,
+    max_images,
+    multiply_images,
     normalize_01,
     normalize_01_channel_wise,
+    process_images,
     scale_image_to_voxelsize,
     select_channel,
+    subtract_images,
 )
 from plantseg.functionals.dataprocessing.labelprocessing import (
     relabel_segmentation,
@@ -45,6 +52,14 @@
     "fix_layout_to_ZYX",
     "fix_layout_to_YX",
     "fix_layout",
+    # simple image operations
+    "ImagePairOperation",
+    "process_images",
+    "max_images",
+    "add_images",
+    "subtract_images",
+    "multiply_images",
+    "divide_images",
     # labelprocessing
     "relabel_segmentation",
     "set_background_to_value",

plantseg/functionals/dataprocessing/dataprocessing.py

@@ -353,3 +353,155 @@ def normalize_01_channel_wise(data: np.ndarray, channel_axis: int = 0, eps=1e-12
 
     # Move the axis back to its original position
     return np.moveaxis(normalized_channels, 0, channel_axis)
+
+
+ImagePairOperation = Literal["add", "multiply", "subtract", "divide", "max"]
+
+
+def process_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    operation: ImagePairOperation,
+    normalize_input: bool = False,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+) -> np.ndarray:
+    """
+    General function for performing image operations with optional preprocessing and post-processing.
+
+    Args:
+        image1 (np.ndarray): First input image.
+        image2 (np.ndarray): Second input image.
+        operation (str): Operation to perform ('add', 'multiply', 'subtract', 'divide', 'max').
+        normalize_input (bool): Whether to normalize the input images to the range [0, 1]. Default is False.
+        clip_output (bool): Whether to clip the resulting image values to the range [0, 1]. Default is False.
+        normalize_output (bool): Whether to normalize the output image to the range [0, 1]. Default is True.
+
+    Returns:
+        np.ndarray: The resulting image after performing the operation.
+    """
+    # Preprocessing: Normalize input images if specified
+    if normalize_input:
+        image1, image2 = normalize_01(image1), normalize_01(image2)
+
+    # Perform the specified operation
+    if operation == "add":
+        result = image1 + image2
+    elif operation == "multiply":
+        result = image1 * image2
+    elif operation == "subtract":
+        result = image1 - image2
+    elif operation == "divide":
+        result = image1 / image2
+    elif operation == "max":
+        result = np.maximum(image1, image2)
+    else:
+        raise ValueError(f"Unsupported operation: {operation}")
+
+    # Post-processing: Clip and/or normalize output if specified
+    if clip_output:
+        result = np.clip(result, 0, 1)
+    if normalize_output:
+        result = normalize_01(result)
+
+    return result
+
+
+def add_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+    normalize_input: bool = False,
+) -> np.ndarray:
+    """
+    Adds two images with optional preprocessing and post-processing.
+    """
+    return process_images(
+        image1,
+        image2,
+        operation="add",
+        clip_output=clip_output,
+        normalize_output=normalize_output,
+        normalize_input=normalize_input,
+    )
+
+
+def multiply_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+    normalize_input: bool = False,
+) -> np.ndarray:
+    """
+    Multiplies two images with optional preprocessing and post-processing.
+    """
+    return process_images(
+        image1,
+        image2,
+        operation="multiply",
+        clip_output=clip_output,
+        normalize_output=normalize_output,
+        normalize_input=normalize_input,
+    )
+
+
+def subtract_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+    normalize_input: bool = False,
+) -> np.ndarray:
+    """
+    Subtracts the second image from the first with optional preprocessing and post-processing.
+    """
+    return process_images(
+        image1,
+        image2,
+        operation="subtract",
+        clip_output=clip_output,
+        normalize_output=normalize_output,
+        normalize_input=normalize_input,
+    )
+
+
+def divide_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+    normalize_input: bool = False,
+) -> np.ndarray:
+    """
+    Divides the first image by the second with optional preprocessing and post-processing.
+    """
+    return process_images(
+        image1,
+        image2,
+        operation="divide",
+        clip_output=clip_output,
+        normalize_output=normalize_output,
+        normalize_input=normalize_input,
+    )
+
+
+def max_images(
+    image1: np.ndarray,
+    image2: np.ndarray,
+    clip_output: bool = False,
+    normalize_output: bool = True,
+    normalize_input: bool = False,
+) -> np.ndarray:
+    """
+    Computes the pixel-wise maximum of two images with optional preprocessing and post-processing.
+    """
+    return process_images(
+        image1,
+        image2,
+        operation="max",
+        clip_output=clip_output,
+        normalize_output=normalize_output,
+        normalize_input=normalize_input,
+    )

plantseg/headless/headless.py

@@ -51,7 +51,7 @@ def parse_import_image_task(input_path, allow_dir: bool) -> list[Path]:
     else:
         raise ValueError(f"Path {input_path} is not a file or a directory.")
 
-    list_files = [f for f in list_files if f.suffix in allowed_data_format]
+    list_files = [f for f in list_files if f.suffix.lower() in allowed_data_format]
     if not list_files:
         raise ValueError(f"No valid files found in {input_path}.")
 

plantseg/io/h5.py

@@ -13,7 +13,7 @@
 
 
 def _validate_h5_file(path: Path) -> None:
-    assert path.suffix in H5_EXTENSIONS, f"File extension not supported. Supported extensions: {H5_EXTENSIONS}"
+    assert path.suffix.lower() in H5_EXTENSIONS, f"File extension not supported. Supported extensions: {H5_EXTENSIONS}"
     assert path.exists(), f"File not found: {path}"
 
 
@@ -73,7 +73,7 @@ def load_h5(
         np.ndarray: dataset as numpy array
     """
 
-    assert path.suffix in H5_EXTENSIONS, f"File extension not supported. Supported extensions: {H5_EXTENSIONS}"
+    assert path.suffix.lower() in H5_EXTENSIONS, f"File extension not supported. Supported extensions: {H5_EXTENSIONS}"
     assert path.exists(), f"File not found: {path}"
 
     with h5py.File(path, "r") as f:

plantseg/io/io.py

@@ -32,7 +32,7 @@ def smart_load(path: Path, key: str | None = None, default=load_tiff) -> np.ndar
         >>> data = smart_load('path/to/file.h5', key='raw')
 
     """
-    ext = path.suffix
+    ext = (path.suffix).lower()
     if key == "":
         key = None
 
@@ -72,7 +72,7 @@ def smart_load_with_vs(path: Path, key: str | None = None, default=load_tiff) ->
         >>> data = smart_load('path/to/file.h5', key='raw')
 
     """
-    ext = path.suffix
+    ext = (path.suffix).lower()
     if key == "":
         key = None
 
@@ -85,9 +85,9 @@ def smart_load_with_vs(path: Path, key: str | None = None, default=load_tiff) ->
     if ext in PIL_EXTENSIONS:
         return load_pil(path), None
 
-    if ".zarr" in path.suffixes:
+    if ext in ZARR_EXTENSIONS:
         return load_zarr(path, key), read_zarr_voxel_size(path, key)
 
     else:
-        logger.warning(f"No default found for {ext}, reverting to default loader.")
-        return default(path)
+        logger.warning(f"No default found for {ext}, reverting to default loader with no voxel size reader.")
+        return default(path), None