Allow blank images in training data set (#42)

* Check length of points list before distance transform

* Add test case with no spots

* Add kwarg fill_value and pass in dtype

Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>

---------

Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>

deepcell_spots/utils.py

@@ -68,6 +68,14 @@ def subpixel_distance_transform(point_list, image_shape, dy=1, dx=1):
     # index in point_list of point nearest to pixel
     nearest_point = np.full(image_shape, np.nan)
 
+    # signed y distance to nearest point
+    delta_y = np.full(image_shape, fill_value=image_shape[1], dtype=np.float32)
+    # signed x distance to nearest point
+    delta_x = np.full(image_shape, fill_value=image_shape[0], dtype=np.float32)
+
+    if len(point_list) == 0:
+        return delta_y, delta_x, nearest_point
+
     # dictionary to be filled s.t.: pixel_to_contained_point_ind[(i,j)] = k if point_list[k]
     # is a point contained in pixel i,j of the image
     pixel_to_contained_point_ind = {}
@@ -82,11 +90,6 @@ def subpixel_distance_transform(point_list, image_shape, dy=1, dx=1):
     edt, inds = distance_transform_edt(
         contains_point, return_indices=True, sampling=[dy, dx])
 
-    # signed y distance to nearest point
-    delta_y = np.full(image_shape, np.inf)
-    # signed x distance to nearest point
-    delta_x = np.full(image_shape, np.inf)
-
     Ly, Lx = image_shape
     for j in range(0, Lx):
         for i in range(0, Ly):

deepcell_spots/utils_test.py

@@ -56,6 +56,20 @@ def test_subpixel_distance_transform(self):
         self.assertEqual(np.shape(delta_x), image_shape)
         self.assertEqual(np.shape(nearest_point), image_shape)
 
+        # test image with no points
+        point_list = np.random.random((0, 2))
+        image_shape = (30, 30)
+        delta_y, delta_x, nearest_point = subpixel_distance_transform(
+            point_list, image_shape)
+
+        self.assertEqual(np.shape(delta_y), image_shape)
+        self.assertEqual(np.shape(delta_x), image_shape)
+        self.assertEqual(np.shape(nearest_point), image_shape)
+
+        self.assertAllEqual(delta_y, np.full(image_shape, image_shape[1]).astype(float))
+        self.assertAllEqual(delta_x, np.full(image_shape, image_shape[0]).astype(float))
+        self.assertAllEqual(nearest_point, np.full(image_shape, np.nan))
+
     def test_generate_transformation_matrix(self):
         transform_parameters = {
             'theta': 0,