Add cellpose segmentation

.github/workflows/test.yml

@@ -26,7 +26,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11.0-beta.5 - 3.11']
+        python-version: ['3.8', '3.9', '3.10', '3.11']
 
     steps:
     - uses: actions/checkout@v3

config_cellpose.yml

@@ -0,0 +1,18 @@
+# SPDX-FileCopyrightText: 2023 Friedrich Miescher Institute for Biomedical Research (FMI), Basel (Switzerland)
+#
+# SPDX-License-Identifier: MIT
+
+# Required
+file_selection:  # criteria for file selection in case of multiple channels/slices per position
+    channel: C01
+process:  # choose method how to segment, filter, and sample the objects
+    segment: cellpose
+    filter: []
+    sample: centers
+
+# Each subsequent section provides arguments to one of the methods defined in 'process'
+cellpose:
+    diameter: 10.0
+    pretrained_model: cyto2
+    cellprob_threshold: 0.0
+    flow_threshold: 0.4

pyproject.toml

@@ -10,7 +10,7 @@ build-backend = "hatchling.build"
 name = "faim-wako-searchfirst"
 description = ''
 readme = "README.md"
-requires-python = ">=3.7"
+requires-python = ">=3.8"
 license = "MIT"
 keywords = []
 authors = [
@@ -19,7 +19,6 @@ authors = [
 classifiers = [
   "Development Status :: 4 - Beta",
   "Programming Language :: Python",
-  "Programming Language :: Python :: 3.7",
   "Programming Language :: Python :: 3.8",
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
@@ -28,6 +27,7 @@ classifiers = [
   "Programming Language :: Python :: Implementation :: PyPy",
 ]
 dependencies = [
+  "cellpose",
   "confuse",
   "rich",
   "scikit-image",
@@ -55,7 +55,7 @@ cov = "pytest --cov-report=term-missing --cov-config=pyproject.toml --cov=faim_w
 no-cov = "cov --no-cov {args}"
 
 [[tool.hatch.envs.test.matrix]]
-python = ["37", "38", "39", "310", "311"]
+python = ["38", "39", "310", "311"]
 
 [tool.coverage.run]
 branch = true

src/faim_wako_searchfirst/segment.py

@@ -9,8 +9,11 @@
 """
 
 import logging
+from pathlib import Path
+from typing import Union
 
 import numpy as np
+from cellpose import models
 from scipy.ndimage import binary_fill_holes
 from skimage.measure import label, regionprops
 
@@ -26,10 +29,6 @@ def threshold(
     :param img: input image
     :param threshold: global threshold
     :param include_holes: if true, holes will be filled
-    :param min_size: minimum object size
-    :param max_size: maximum object size
-    :param min_eccentricity: minimum eccentricity of object
-    :param max_eccentricity: maximum eccentricity of object
     :param logger:
 
     :return: a label image representing the detected objects
@@ -41,3 +40,32 @@ def threshold(
     regions = regionprops(labeled_image)
     logger.info(f"Found {len(regions)} connected components.")
     return labeled_image
+
+
+def cellpose(
+    img,
+    diameter: float,
+    pretrained_model: Union[str, Path] = "cyto2",
+    logger=logging,
+    **kwargs,
+):
+    """Segment a given image by global thresholding.
+
+    :param img: input image
+    :param diameter: expected object diameter
+    :param pretrained_model: name of cellpose model, or path to pretrained model
+    :param logger:
+
+    :return: a label image representing the detected objects
+    """
+    logger.info(f"Load cellpose model: {pretrained_model}")
+    model: models.CellposeModel = models.CellposeModel(
+        pretrained_model=pretrained_model,
+    )
+    mask, _, _ = model.eval(
+        img,
+        channels=[0, 0],
+        diameter=diameter,
+        **kwargs,
+    )
+    return mask

tests/test_cellpose.py

@@ -0,0 +1,36 @@
+# SPDX-FileCopyrightText: 2023 Friedrich Miescher Institute for Biomedical Research (FMI), Basel (Switzerland)
+#
+# SPDX-License-Identifier: MIT
+
+"""Test faim_wako_searchfirst module."""
+import csv
+import shutil
+from pathlib import Path
+
+import pytest
+from faim_wako_searchfirst.main import run
+
+
+@pytest.fixture
+def _data_path(tmp_path):
+    # copy test set into tmp_path, return resulting Path
+    testset_path = Path("tests/resources/TestSet")
+    assert testset_path.exists()
+    return shutil.copytree(testset_path, tmp_path / "TestSet")
+
+
+def test_cellpose(_data_path):
+    """Test run with parameters defined in the sample config_cellpose.yml file."""
+    run(_data_path, configfile="config_cellpose.yml")
+    csv_path = _data_path / "TestSet_D07_T0001F002L01A02Z01C01.csv"
+    assert csv_path.exists()
+    with open(csv_path, "r") as csv_file:
+        reader = csv.reader(csv_file, quoting=csv.QUOTE_NONNUMERIC)
+        entries = list(reader)
+        assert len(entries) == 3, "Incorrect number of objects detected."
+        assert entries[0] == pytest.approx([1, 40.5, 30.5])
+        assert entries[1] == pytest.approx([2, 158.5, 58.5])
+        assert entries[2] == pytest.approx([3, 79.5287, 146.4483])
+
+    segmentation_folder = _data_path.parent / (_data_path.name + "_segmentation")
+    assert sum(1 for _ in segmentation_folder.glob("*")) == 1