Data type options added to Apply FlatField correction plugin

transforms/images/apply-flatfield-tool/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 2.0.1
+current_version = 2.0.1-dev1
 commit = False
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<dev>\d+))?

transforms/images/apply-flatfield-tool/CHANGELOG.md

@@ -0,0 +1,29 @@
+# Changelog
+
+All notable changes to this project will be documented in this file.
+
+The format is based on [Keep a Changelog],
+and this project adheres to [Semantic Versioning].
+
+
+## [2.0.1-dev1] - 2025-01-12
+
+### Added
+
+- "keepOrigDtype" option is added to the tool, so that the end user can choose to keep the original data type after the correction is applied, e.g., uint16 -> uint16. Otherwise, floating point output is kept.
+
+### Changed
+
+### Deprecated
+
+### Removed
+
+### Fixed
+
+### Security
+
+
+<!-- Links -->
+[keep a changelog]: https://keepachangelog.com/en/1.0.0/
+[semantic versioning]: https://semver.org/spec/v2.0.0.html
+

transforms/images/apply-flatfield-tool/README.md

@@ -55,3 +55,4 @@ Command line options:
 | `--dfPattern`    | Filename pattern used to match darkfield files to image files         | Input  | string     |
 | `--outDir`       | Output collection                                                     | Output | collection |
 | `--preview`      | Preview the output images' names without actually running computation | Input  | boolean    |
+| `--keepOrigDtype`| Keep the original image data type if true                             | Input  | boolean    |

transforms/images/apply-flatfield-tool/VERSION

@@ -1 +1 @@
-2.0.1
+2.0.1-dev1

transforms/images/apply-flatfield-tool/applyflatfield.cwl

@@ -29,6 +29,10 @@ inputs:
     inputBinding:
       prefix: --preview
     type: boolean?
+  keepOrigDtype:
+    inputBinding:
+      prefix: --keepOrigDtype
+    type: boolean?
 outputs:
   outDir:
     outputBinding:

transforms/images/apply-flatfield-tool/ict.yaml

@@ -42,6 +42,12 @@ inputs:
   name: preview
   required: false
   type: boolean
+- description: Keep original image data type if true, otherwise convert to float
+  format:
+  - boolean
+  name: keepOrigDtype
+  required: false
+  type: boolean
 name: polusai/ApplyFlatfield
 outputs:
 - description: Output collection

transforms/images/apply-flatfield-tool/plugin.json

@@ -50,7 +50,13 @@
       "type": "boolean",
       "description": "Preview the output images' names without actually running computation",
       "required": false
-    }
+    },
+    {
+        "name": "keepOrigDtype",
+        "type": "boolean",
+        "description": "Keep original image data type if true, otherwise convert to float",
+        "required": false
+      }
   ],
   "outputs": [
     {

transforms/images/apply-flatfield-tool/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-transforms-images-apply-flatfield"
-version = "2.0.1"
+version = "2.0.1-dev1"
 description = ""
 authors = [
     "Nick Schaub <nicholas.schaub@nih.gov>",

transforms/images/apply-flatfield-tool/src/polus/images/transforms/images/apply_flatfield/__init__.py

@@ -3,4 +3,4 @@
 from . import utils
 from .apply_flatfield import apply
 
-__version__ = "2.0.1"
+__version__ = "2.0.1-dev1"

transforms/images/apply-flatfield-tool/src/polus/images/transforms/images/apply_flatfield/__main__.py

@@ -6,8 +6,7 @@
 import typing
 
 import typer
-from polus.images.transforms.images.apply_flatfield import apply
-from polus.images.transforms.images.apply_flatfield import utils
+from polus.images.transforms.images.apply_flatfield import apply, utils
 
 # Initialize the logger
 logging.basicConfig(
@@ -69,6 +68,11 @@ def main(  # noqa: PLR0913
         "--preview",
         help="Preview the output without saving.",
     ),
+    keep_orig_dtype: typing.Optional[bool] = typer.Option(
+        True,
+        "--keepOrigDtype",
+        help="Keep the original dtype of the input images.",
+    ),
 ) -> None:
     """CLI for the Apply Flatfield plugin.
 
@@ -87,6 +91,7 @@ def main(  # noqa: PLR0913
     logger.info(f"dfPattern = {df_pattern}")
     logger.info(f"outDir = {out_dir}")
     logger.info(f"preview = {preview}")
+    logger.info(f"keepOrigDtype = {keep_orig_dtype}")
 
     out_files = apply(
         img_dir=img_dir,
@@ -96,6 +101,7 @@ def main(  # noqa: PLR0913
         df_pattern=df_pattern,
         out_dir=out_dir,
         preview=preview,
+        keep_orig_dtype=keep_orig_dtype,
     )
 
     if preview:

transforms/images/apply-flatfield-tool/src/polus/images/transforms/images/apply_flatfield/apply_flatfield.py

@@ -7,6 +7,7 @@
 
 import bfio
 import numpy
+import numpy as np
 import preadator
 import tqdm
 from filepattern import FilePattern
@@ -26,7 +27,8 @@ def apply(  # noqa: PLR0913
     df_pattern: typing.Optional[str],
     out_dir: pathlib.Path,
     preview: bool = False,
-) -> list[pathlib.Path]:
+    keep_orig_dtype: typing.Optional[bool] = True,
+) -> typing.List[pathlib.Path]:
     """Run batch-wise flatfield correction on the image collection.
 
     Args:
@@ -41,6 +43,9 @@ def apply(  # noqa: PLR0913
         saved.
         preview: if True, return the paths to the images that would be saved
         without actually performing any other computation.
+        keep_orig_dtype: if True, the output images will be saved with the same
+        dtype as the input images. If False, the output images will be saved as
+        float32.
     """
     img_fp = FilePattern(str(img_dir), img_pattern)
     img_variables = img_fp.get_variables()
@@ -82,16 +87,17 @@ def apply(  # noqa: PLR0913
         if preview:
             out_files.extend(img_paths)
         else:
-            _unshade_images(img_paths, out_dir, ff_path, df_path)
+            _unshade_images(img_paths, out_dir, ff_path, df_path, keep_orig_dtype)
 
     return out_files
 
 
 def _unshade_images(
-    img_paths: list[pathlib.Path],
+    img_paths: typing.List[pathlib.Path],
     out_dir: pathlib.Path,
     ff_path: pathlib.Path,
     df_path: typing.Optional[pathlib.Path],
+    keep_orig_dtype: typing.Optional[bool] = True,
 ) -> None:
     """Remove the given flatfield components from all images and save outputs.
 
@@ -100,6 +106,9 @@ def _unshade_images(
         out_dir: directory to save the corrected images
         ff_path: path to the flatfield image
         df_path: path to the darkfield image
+        keep_orig_dtype: if True, the output images will be saved with the same
+        dtype as the input images. If False, the output images will be saved as
+        float32.
     """
     logger.info(f"Applying flatfield correction to {len(img_paths)} images ...")
     logger.info(f"{ff_path.name = } ...")
@@ -123,18 +132,16 @@ def _unshade_images(
         total=len(batch_indices) - 1,
     ):
         _unshade_batch(
-            img_paths[i_start:i_end],
-            out_dir,
-            ff_image,
-            df_image,
+            img_paths[i_start:i_end], out_dir, ff_image, df_image, keep_orig_dtype
         )
 
 
 def _unshade_batch(
-    batch_paths: list[pathlib.Path],
+    batch_paths: typing.List[pathlib.Path],
     out_dir: pathlib.Path,
     ff_image: numpy.ndarray,
     df_image: typing.Optional[numpy.ndarray] = None,
+    keep_orig_dtype: typing.Optional[bool] = True,
 ) -> None:
     """Apply flatfield correction to a batch of images.
 
@@ -143,6 +150,9 @@ def _unshade_batch(
         out_dir: directory to save the corrected images
         ff_image: component to be used for flatfield correction
         df_image: component to be used for flatfield correction
+        keep_orig_dtype: if True, the output images will be saved with the same
+        dtype as the input images. If False, the output images will be saved as
+        float32.
     """
     # Load images
     with preadator.ProcessManager(
@@ -162,12 +172,44 @@ def _unshade_batch(
     images = [img for _, img in sorted(images, key=operator.itemgetter(0))]
     img_stack = numpy.stack(images, axis=0).astype(numpy.float32)
 
+    # find min and max values of original images (across last 2 axes)
+    def get_min_max(img_stack):
+        min_val = img_stack.min(axis=(-1, -2), keepdims=True)
+        max_val = img_stack.max(axis=(-1, -2), keepdims=True)
+        return min_val, max_val
+
+    min_orig, max_orig = get_min_max(img_stack)  # dim: n_images x 1 x 1
+
     # Apply flatfield correction
     if df_image is not None:
         img_stack -= df_image
 
     img_stack /= ff_image + 1e-8
 
+    # calculate min and max values of corrected images
+    min_new, max_new = get_min_max(img_stack)
+
+    # scale corrected images to original range
+    img_stack = (img_stack - min_new) / (max_new - min_new) * (
+        max_orig - min_orig
+    ) + min_orig
+
+    if keep_orig_dtype:
+        orig_dtype = images[0].dtype
+        # if integer type
+        if np.issubdtype(orig_dtype, np.integer):
+            # clip out of range values for orig dtype
+            dtype_info = np.iinfo(orig_dtype)
+            img_stack = np.clip(img_stack, dtype_info.min, dtype_info.max)
+
+            # round and cast to original dtype
+            img_stack = np.round(img_stack).astype(orig_dtype)
+
+        elif np.issubdtype(orig_dtype, np.floating):
+            # floating point image, clamp to [0,1]
+            img_stack = np.clip(img_stack, 0.0, 1.0)
+            img_stack = img_stack.astype(orig_dtype)
+
     # Save outputs
     with preadator.ProcessManager(
         name="unshade_batch::save",

transforms/images/apply-flatfield-tool/src/polus/images/transforms/images/apply_flatfield/utils.py

@@ -1,9 +1,9 @@
 """Utilities for the apply flatfield plugin."""
-
 import logging
 import multiprocessing
 import os
 import pathlib
+import typing
 
 import bfio
 import numpy
@@ -13,7 +13,7 @@
 MAX_WORKERS = max(1, multiprocessing.cpu_count() // 2)
 
 
-def load_img(path: pathlib.Path, i: int) -> tuple[int, numpy.ndarray]:
+def load_img(path: pathlib.Path, i: int) -> typing.Tuple[int, numpy.ndarray]:
     """Load image from path.
 
     This method is intended to be used in a thread. The index is used to