Add test for segmentation table

Author: constantinpape

flamingo_tools/measurements.py

@@ -9,7 +9,7 @@
 from tqdm import tqdm
 
 from .file_utils import read_image_data
-from .segmentation.postprocessing import _compute_table
+from .segmentation.postprocessing import compute_table_on_the_fly
 
 
 def _measure_volume_and_surface(mask, resolution):
@@ -45,7 +45,7 @@ def compute_object_measures_impl(
         table: The segmentation table. Will be computed on the fly if it is not given.
     """
     if table is None:
-        table = _compute_table(segmentation, resolution)
+        table = compute_table_on_the_fly(segmentation, resolution=resolution)
 
     def intensity_measures(seg_id):
         # Get the bounding box.

flamingo_tools/segmentation/postprocessing.py

@@ -115,7 +115,9 @@ def neighbors_in_radius(table: pd.DataFrame, radius: float = 15) -> np.ndarray:
 #
 
 
-def _compute_table(segmentation, resolution):
+def compute_table_on_the_fly(segmentation: np.typing.ArrayLike, resolution: float) -> pd.DataFrame:
+    """
+    """
     props = measure.regionprops(segmentation)
     label_ids = np.array([prop.label for prop in props])
     coordinates = np.array([prop.centroid for prop in props]).astype("float32")
@@ -171,10 +173,9 @@ def filter_segmentation(
         n_ids
         n_ids_filtered
     """
-    # Compute the table on the fly.
-    # NOTE: this currently doesn't work for large segmentations.
+    # Compute the table on the fly. This doesn't work for large segmentations.
     if table is None:
-        table = _compute_table(segmentation, resolution=resolution)
+        table = compute_table_on_the_fly(segmentation, resolution=resolution)
     n_ids = len(table)
 
     # First apply the size filter.

flamingo_tools/test_data.py

@@ -6,12 +6,19 @@
 from skimage.data import binary_blobs, cells3d
 from skimage.measure import label
 
-from .segmentation.postprocessing import _compute_table
+from .segmentation.postprocessing import compute_table_on_the_fly
 
 SEGMENTATION_URL = "https://owncloud.gwdg.de/index.php/s/kwoGRYiJRRrswgw/download"
 
 
 def get_test_volume_and_segmentation(folder: str) -> Tuple[str, str, str]:
+    """Download a small volume with nuclei and corresponding segmentation.
+
+    Args:
+        folder:
+
+    Returns:
+    """
     os.makedirs(folder, exist_ok=True)
 
     segmentation_path = os.path.join(folder, "segmentation.tif")
@@ -29,7 +36,7 @@ def get_test_volume_and_segmentation(folder: str) -> Tuple[str, str, str]:
     imageio.imwrite(image_path, nuclei)
 
     table_path = os.path.join(folder, "default.tsv")
-    table = _compute_table(segmentation, resolution=0.38)
+    table = compute_table_on_the_fly(segmentation, resolution=0.38)
     table.to_csv(table_path, sep="\t", index=False)
 
     return image_path, segmentation_path, table_path
@@ -51,7 +58,7 @@ def create_image_data_and_segmentation(folder: str, size: int = 256) -> Tuple[st
     imageio.imwrite(segmentation_path, seg)
 
     table_path = os.path.join(folder, "default.tsv")
-    table = _compute_table(seg, resolution=0.38)
+    table = compute_table_on_the_fly(seg, resolution=0.38)
     table.to_csv(table_path, sep="\t", index=False)
 
     return image_path, segmentation_path, table_path

test/test_segmentation/test_postprocessing.py

@@ -2,9 +2,12 @@
 import tempfile
 import unittest
 
+import imageio.v3 as imageio
+import numpy as np
+import pandas as pd
 from elf.io import open_file
 from skimage.data import binary_blobs
-from skimage.measure import label
+from skimage.measure import label, regionprops_table
 
 
 class TestPostprocessing(unittest.TestCase):
@@ -44,6 +47,32 @@ def test_neighbors_in_radius(self):
 
         self._test_postprocessing(neighbors_in_radius, threshold=5)
 
+    def test_compute_table_on_the_fly(self):
+        from flamingo_tools.segmentation.postprocessing import compute_table_on_the_fly
+        from flamingo_tools.test_data import get_test_volume_and_segmentation
+
+        with tempfile.TemporaryDirectory() as tmp_dir:
+            _, seg_path, _ = get_test_volume_and_segmentation(tmp_dir)
+            segmentation = imageio.imread(seg_path)
+
+        resolution = 0.38
+        table = compute_table_on_the_fly(segmentation, resolution=resolution)
+
+        properties = ("label", "bbox", "centroid")
+        expected_table = regionprops_table(segmentation, properties=properties)
+        expected_table = pd.DataFrame(expected_table)
+
+        for (col, col_exp) in [
+            ("label_id", "label"),
+            ("anchor_x", "centroid-2"), ("anchor_y", "centroid-1"), ("anchor_z", "centroid-0"),
+            ("bb_min_x", "bbox-2"), ("bb_min_y", "bbox-1"), ("bb_min_z", "bbox-0"),
+            ("bb_max_x", "bbox-5"), ("bb_max_y", "bbox-4"), ("bb_max_z", "bbox-3"),
+        ]:
+            values = table[col].values
+            if col != "label_id":
+                values /= resolution
+            self.assertTrue(np.allclose(values, expected_table[col_exp].values))
+
 
 if __name__ == "__main__":
     unittest.main()