fix KeyError: "None of [Index(['0_x', '1_x', '0_y', '1_y'], dtype='object')] are in the [columns]" in find_objects

dask_image/ndmeasure/_utils/_find_objects.py

@@ -1,7 +1,7 @@
+import dask.dataframe as dd
 import numpy as np
 import pandas as pd
 from dask.delayed import Delayed
-import dask.dataframe as dd
 
 
 def _array_chunk_location(block_id, chunks):
@@ -28,7 +28,8 @@ def _find_bounding_boxes(x, array_location):
     result = {}
     for val in unique_vals:
         positions = np.where(x == val)
-        slices = tuple(slice(np.min(pos) + array_location[i], np.max(pos) + 1 + array_location[i]) for i, pos in enumerate(positions))
+        slices = tuple(slice(np.min(pos) + array_location[i], np.max(pos) + 1 + array_location[i]) for i, pos in
+                       enumerate(positions))
         result[val] = slices
     column_names = [i for i in range(x.ndim)]  # column names are: 0, 1, ... nD
     return pd.DataFrame.from_dict(result, orient='index', columns=column_names)
@@ -70,6 +71,14 @@ def _find_objects(ndim, df1, df2):
         df1 = dd.from_delayed(df1, meta=meta)
     if isinstance(df2, Delayed):
         df2 = dd.from_delayed(df2, meta=meta)
-    ddf = dd.merge(df1, df2, how="outer", left_index=True, right_index=True)
+
+    if len(df1) > 0 and len(df2) > 0:
+        ddf = dd.merge(df1, df2, how="outer", left_index=True, right_index=True)
+    elif len(df1) > 0:
+        ddf = df1
+    elif len(df2) > 0:
+        ddf = df2
+    else:
+        ddf = pd.DataFrame()
     result = ddf.apply(_merge_bounding_boxes, ndim=ndim, axis=1, meta=meta)
     return result

tests/test_dask_image/test_ndmeasure/test_find_objects.py

@@ -1,4 +1,3 @@
-from dask_image.ndmeasure._utils import _labeled_comprehension_delayed
 import dask.array as da
 import dask.dataframe as dd
 import numpy as np
@@ -22,9 +21,9 @@ def label_image():
 
     """
     label_image = np.zeros((5, 10)).astype(int)
-    label_image[1:3,0:2] = 111
-    label_image[3,3:-2] = 222
-    label_image[0:2,-3:] = 333
+    label_image[1:3, 0:2] = 111
+    label_image[3, 3:-2] = 222
+    label_image[0:2, -3:] = 333
     label_image = da.from_array(label_image, chunks=(5, 5))
     return label_image
 
@@ -43,8 +42,8 @@ def label_image_with_empty_chunk():
             [  0,   0,   0,   0,   0,   0]])
     """
     label_image = np.zeros((6, 6)).astype(int)
-    label_image[1:3,0:2] = 111
-    label_image[4,3:] = 222
+    label_image[1:3, 0:2] = 111
+    label_image[4, 3:] = 222
     label_image = da.from_array(label_image, chunks=(3, 3))
     return label_image
 
@@ -55,14 +54,23 @@ def test_find_objects_err(label_image):
         dask_image.ndmeasure.find_objects(label_image)
 
 
+def test_empty_chunk():
+    test_labels = da.zeros((10, 10), dtype='int', chunks=(3, 3))
+    test_labels[0, 0] = 1
+    computed_result = dask_image.ndmeasure.find_objects(test_labels).compute()
+    expected = pd.DataFrame.from_dict({0: {1: slice(0, 1)},
+                                       1: {1: slice(0, 1)}, })
+    assert computed_result.equals(expected)
+
+
 def test_find_objects(label_image):
     result = dask_image.ndmeasure.find_objects(label_image)
     assert isinstance(result, dd.DataFrame)
     computed_result = result.compute()
     assert isinstance(computed_result, pd.DataFrame)
     expected = pd.DataFrame.from_dict(
         {0: {111: slice(1, 3), 222: slice(3, 4), 333: slice(0, 2)},
-        1: {111: slice(0, 2), 222: slice(3, 8), 333: slice(7, 10)}}
+         1: {111: slice(0, 2), 222: slice(3, 8), 333: slice(7, 10)}}
     )
     assert computed_result.equals(expected)
 
@@ -75,8 +83,8 @@ def test_3d_find_objects(label_image):
     assert isinstance(computed_result, pd.DataFrame)
     expected = pd.DataFrame.from_dict(
         {0: {111: slice(1, 3), 222: slice(3, 4), 333: slice(0, 2)},
-        1: {111: slice(0, 2), 222: slice(3, 8), 333: slice(7, 10)},
-        2: {111: slice(0, 2), 222: slice(0, 2), 333: slice(0, 2)}}
+         1: {111: slice(0, 2), 222: slice(3, 8), 333: slice(7, 10)},
+         2: {111: slice(0, 2), 222: slice(0, 2), 333: slice(0, 2)}}
     )
     assert computed_result.equals(expected)
 
@@ -88,6 +96,6 @@ def test_find_objects_with_empty_chunks(label_image_with_empty_chunk):
     assert isinstance(computed_result, pd.DataFrame)
     expected = pd.DataFrame.from_dict(
         {0: {111: slice(1, 3, None), 222: slice(4, 5, None)},
-        1: {111: slice(0, 2, None), 222: slice(3, 6, None)}}
+         1: {111: slice(0, 2, None), 222: slice(3, 6, None)}}
     )
     assert computed_result.equals(expected)