fix: use eigh instead of eig for blob orientation/ellipse moments

src/machinevisiontoolbox/ImageBlobs.py

@@ -458,7 +458,10 @@ def __init__(
 
                 ## Equivalent ellipse
                 J = np.array([[M["mu20"], M["mu11"]], [M["mu11"], M["mu02"]]])
-                e, X = np.linalg.eig(J)
+                # J is real-symmetric, so use eigh (not eig): eig can return
+                # complex128 for a symmetric matrix due to floating-point
+                # noise even though the eigenvalues are mathematically real.
+                e, X = np.linalg.eigh(J)
                 blob_params["a"] = 2.0 * np.sqrt(e.max() / M["m00"])
                 blob_params["b"] = 2.0 * np.sqrt(e.min() / M["m00"])
 

tests/test_image_blobs.py

@@ -119,6 +119,23 @@ def test_two_blobs_different_sizes(self):
         self.assertEqual(blobs[1].area, 4)
         self.assertEqual(blobs[1].perimeter_length, 7)
 
+    def test_orientation_square_blob_degenerate_moments(self):
+        # A square (or any blob with equal mu20/mu02 and mu11≈0) has a
+        # moment matrix that is a scalar multiple of the identity: its two
+        # eigenvalues are exactly equal. np.linalg.eig (general, non-
+        # symmetric solver) can return complex128 for this case due to
+        # floating-point noise even though the matrix is real-symmetric and
+        # the eigenvalues are mathematically real, which then makes
+        # np.arctan2() raise TypeError. np.linalg.eigh (symmetric solver)
+        # does not have this failure mode. See ImageBlobs.py's equivalent
+        # ellipse / orientation calculation.
+        im = Image.Squares(1, size=61, fg=255, bg=0)
+        blobs = im.blobs()
+
+        orientation = blobs[0].orientation
+        self.assertIsInstance(orientation, float)
+        self.assertFalse(np.iscomplexobj(orientation))
+
 
 # ============================================================================ #
 #  Fixtures