cast image to original data type

transforms/images/apply-flatfield-tool/Dockerfile

@@ -1,4 +1,4 @@
-FROM polusai/bfio:2.3.3
+FROM polusai/bfio:2.3.6
 
 # environment variables defined in polusai/bfio
 ENV EXEC_DIR="/opt/executables"

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

@@ -1,4 +1,4 @@
-# Apply Flatfield Plugin (v2.0.1-dev0)
+# Apply Flatfield Plugin (v2.0.1-dev1)
 
 This WIPP plugin applies a flatfield operation on every image in a collection.
 The algorithm used to apply the flatfield is as follows:
@@ -54,4 +54,5 @@ Command line options:
 | `--ffPattern`    | Filename pattern used to match flatfield files to image files         | Input  | string     |
 | `--dfPattern`    | Filename pattern used to match darkfield files to image files         | Input  | string     |
 | `--outDir`       | Output collection                                                     | Output | collection |
+| `--dataType`     | Save image in original data type                                      | Input  | boolean    |
 | `--preview`      | Preview the output images' names without actually running computation | Input  | boolean    |

transforms/images/apply-flatfield-tool/VERSION

@@ -1 +1 @@
-2.0.1-dev0
+2.0.1-dev1

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

@@ -1,14 +1,14 @@
 {
   "name": "Apply Flatfield",
-  "version": "2.0.1-dev0",
+  "version": "2.0.1-dev1",
   "title": "Apply Flatfield",
   "description": "Apply a flatfield algorithm to a collection of images.",
   "author": "Nick Schaub (Nick.Schaub@nih.gov), Najib Ishaq (najib.ishaq@nih.gov)",
   "institution": "National Center for Advancing Translational Sciences, National Institutes of Health",
   "repository": "https://github.com/labshare/polus-plugins",
   "website": "https://ncats.nih.gov/preclinical/core/informatics",
   "citation": "",
-  "containerId": "polusai/apply-flatfield-tool:2.0.1-dev0",
+  "containerId": "polusai/apply-flatfield-tool:2.0.1-dev1",
   "baseCommand": [
     "python3",
     "-m",
@@ -45,6 +45,12 @@
       "description": "Filename pattern used to match darkfield files to image files",
       "required": false
     },
+    {
+      "name": "dataType",
+      "type": "boolean",
+      "description": "Save image in original data type",
+      "required": false
+    },
     {
       "name": "preview",
       "type": "boolean",
@@ -85,6 +91,11 @@
       "title": "Darkfield file pattern",
       "description": "Filename pattern used to match darkfield files to image files"
     },
+    {
+      "key": "inputs.dataType",
+      "title": "Data Type",
+      "description": "Save image in original data type"
+    },
     {
       "key": "inputs.preview",
       "title": "Preview Output",

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

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polus-images-transforms-images-apply-flatfield"
-version = "2.0.1-dev0"
+version = "2.0.1-dev1"
 description = ""
 authors = [
     "Nick Schaub <nicholas.schaub@nih.gov>",
@@ -11,7 +11,7 @@ packages = [{include = "polus", from = "src"}]
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.12"
-bfio = { version = "^2.3.3", extras = ["all"] }
+bfio = { version = "^2.3.6", extras = ["all"] }
 filepattern = "2.0.4"
 typer = { version = "^0.7.0", extras = ["all"] }
 numpy = "^1.24.3"

transforms/images/apply-flatfield-tool/run-plugin.sh

@@ -26,4 +26,5 @@ docker run --mount type=bind,source=${datapath},target=/data/ \
             --ffDir ${ffDir} \
             --ffPattern ${ffPattern} \
             --ffPattern ${dfPattern} \
-            --outDir ${outDir}
+            --outDir ${outDir} \
+            --dataType

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-dev0"
+__version__ = "2.0.1-dev1"

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

@@ -64,6 +64,11 @@ def main(  # noqa: PLR0913
         resolve_path=True,
         file_okay=False,
     ),
+    data_type: typing.Optional[bool] = typer.Option(
+        False,
+        "--dataType",
+        help="Save images in original data type.",
+    ),
     preview: bool = typer.Option(
         False,
         "--preview",
@@ -86,6 +91,7 @@ def main(  # noqa: PLR0913
     logger.info(f"ffPattern = {ff_pattern}")
     logger.info(f"dfPattern = {df_pattern}")
     logger.info(f"outDir = {out_dir}")
+    logger.info(f"dataType = {data_type}")
     logger.info(f"preview = {preview}")
 
     out_files = apply(
@@ -95,6 +101,7 @@ def main(  # noqa: PLR0913
         ff_pattern=ff_pattern,
         df_pattern=df_pattern,
         out_dir=out_dir,
+        data_type=data_type,
         preview=preview,
     )
 

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

@@ -25,6 +25,7 @@ def apply(  # noqa: PLR0913
     ff_pattern: str,
     df_pattern: typing.Optional[str],
     out_dir: pathlib.Path,
+    data_type: typing.Optional[bool] = False,
     preview: bool = False,
 ) -> list[pathlib.Path]:
     """Run batch-wise flatfield correction on the image collection.
@@ -41,6 +42,7 @@ def apply(  # noqa: PLR0913
         saved.
         preview: if True, return the paths to the images that would be saved
         without actually performing any other computation.
+        data_type: if True, save images in original dtype.
     """
     img_fp = FilePattern(str(img_dir), img_pattern)
     img_variables = img_fp.get_variables()
@@ -82,7 +84,7 @@ 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, data_type)
 
     return out_files
 
@@ -92,6 +94,7 @@ def _unshade_images(
     out_dir: pathlib.Path,
     ff_path: pathlib.Path,
     df_path: typing.Optional[pathlib.Path],
+    data_type: typing.Optional[bool] = False,
 ) -> None:
     """Remove the given flatfield components from all images and save outputs.
 
@@ -100,6 +103,7 @@ 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
+        data_type: Save images in original dtype
     """
     logger.info(f"Applying flatfield correction to {len(img_paths)} images ...")
     logger.info(f"{ff_path.name = } ...")
@@ -122,19 +126,15 @@ def _unshade_images(
         zip(batch_indices[:-1], batch_indices[1:]),
         total=len(batch_indices) - 1,
     ):
-        _unshade_batch(
-            img_paths[i_start:i_end],
-            out_dir,
-            ff_image,
-            df_image,
-        )
+        _unshade_batch(img_paths[i_start:i_end], out_dir, ff_image, df_image, data_type)
 
 
 def _unshade_batch(
     batch_paths: list[pathlib.Path],
     out_dir: pathlib.Path,
     ff_image: numpy.ndarray,
     df_image: typing.Optional[numpy.ndarray] = None,
+    data_type: typing.Optional[bool] = False,
 ) -> None:
     """Apply flatfield correction to a batch of images.
 
@@ -143,6 +143,7 @@ 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
+        data_type: Save images in original dtype
     """
     # Load images
     with preadator.ProcessManager(
@@ -175,5 +176,11 @@ def _unshade_batch(
         threads_per_process=2,
     ) as save_executor:
         for inp_path, img in zip(batch_paths, img_stack):
-            save_executor.submit_process(utils.save_img, inp_path, img, out_dir)
+            save_executor.submit_process(
+                utils.save_img,
+                inp_path,
+                img,
+                out_dir,
+                data_type,
+            )
         save_executor.join_processes()

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

@@ -4,6 +4,8 @@
 import multiprocessing
 import os
 import pathlib
+import re
+import typing
 
 import bfio
 import numpy
@@ -33,23 +35,37 @@ def save_img(
     inp_path: pathlib.Path,
     image: numpy.ndarray,
     out_dir: pathlib.Path,
+    data_type: typing.Optional[bool] = False,
 ) -> None:
     """Save image to disk.
 
     Args:
         inp_path: path to input image
         image: image to be saved
         out_dir: directory to save image
+        data_type: Save images in original dtype
     """
-    out_stem = inp_path.stem
-    if ".ome" in out_stem:
-        out_stem = out_stem.split(".ome")[0]
-
-    out_path = out_dir / f"{out_stem}{POLUS_IMG_EXT}"
+    match = re.search(r"^(.*?)\.", inp_path.name)
+    if match is not None:
+        name = match.group(1)
+    else:
+        ValueError("Unable to detect files in a directory")
+    out_path = out_dir / f"{name}{POLUS_IMG_EXT}"
     with bfio.BioReader(inp_path, MAX_WORKERS) as reader, bfio.BioWriter(
         out_path,
         MAX_WORKERS,
         metadata=reader.metadata,
     ) as writer:
-        writer.dtype = image.dtype
-        writer[:] = image
+        if data_type:
+            info_uint_type = numpy.iinfo(reader.dtype)
+            scaled_image = (
+                (image - numpy.min(image))
+                / (numpy.max(image) - numpy.min(image))
+                * int(info_uint_type.max)
+            )
+            uint_image = scaled_image.astype(reader.dtype)
+            writer.dtype = reader.dtype
+            writer[:] = uint_image
+        else:
+            writer.dtype = image.dtype
+            writer[:] = image