Add tests

tests/impls/gen_object_detector_blackbox_sal/test_occlusion_based.py

@@ -14,6 +14,31 @@
 
 class TestPerturbationOcclusion:
 
+    class StubPI (PerturbImage):
+        """
+        Stub perturber that returns masks of ones.
+        """
+
+        def perturb(self, ref_image: np.ndarray) -> np.ndarray:
+            return np.ones((6, *ref_image.shape[:2]), dtype=bool)
+
+        get_config = None  # type: ignore
+
+    class StubGen (GenerateDetectorProposalSaliency):
+        """
+        Stub saliency generator that returns zeros with correct shape.
+        """
+
+        def generate(
+            self,
+            ref_dets: np.ndarray,
+            pert_dets: np.ndarray,
+            pert_masks: np.ndarray
+        ) -> np.ndarray:
+            return np.zeros((ref_dets.shape[0], *pert_masks.shape[1:]), dtype=np.float16)
+
+        get_config = None  # type: ignore
+
     def teardown(self) -> None:
         # Collect any temporary implementations so they are not returned during
         # later `*.get_impl()` requests.
@@ -24,7 +49,7 @@ def test_configuration(self) -> None:
         Test configuration suite using known simple implementations.
         """
 
-        class StubPI (PerturbImage):
+        class StubPIWithArgs (PerturbImage):
             perturb = None  # type: ignore
 
             def __init__(self, stub_param: int):
@@ -33,7 +58,7 @@ def __init__(self, stub_param: int):
             def get_config(self) -> Dict[str, Any]:
                 return {'stub_param': self.p}
 
-        class StubGen (GenerateDetectorProposalSaliency):
+        class StubGenWithArgs (GenerateDetectorProposalSaliency):
             generate = None  # type: ignore
 
             def __init__(self, stub_param: int):
@@ -46,47 +71,22 @@ def get_config(self) -> Dict[str, Any]:
         test_spi_p = 0
         test_sgn_p = 1
         inst = PerturbationOcclusion(
-            StubPI(test_spi_p),
-            StubGen(test_sgn_p),
+            StubPIWithArgs(test_spi_p),
+            StubGenWithArgs(test_sgn_p),
             threads=87
         )
         for inst_i in configuration_test_helper(inst):
             assert inst_i._threads == test_threads
-            assert isinstance(inst_i._perturber, StubPI)
+            assert isinstance(inst_i._perturber, StubPIWithArgs)
             assert inst_i._perturber.p == test_spi_p
-            assert isinstance(inst_i._generator, StubGen)
+            assert isinstance(inst_i._generator, StubGenWithArgs)
             assert inst_i._generator.p == test_sgn_p
 
     def test_generate_success(self) -> None:
         """
         Test successfully invoking _generate().
         """
 
-        class StubPI (PerturbImage):
-            """
-            Stub perturber that returns masks of ones.
-            """
-
-            def perturb(self, ref_image: np.ndarray) -> np.ndarray:
-                return np.ones((6, *ref_image.shape[:2]), dtype=bool)
-
-            get_config = None  # type: ignore
-
-        class StubGen (GenerateDetectorProposalSaliency):
-            """
-            Stub saliency generator that returns zeros with correct shape.
-            """
-
-            def generate(
-                self,
-                ref_dets: np.ndarray,
-                pert_dets: np.ndarray,
-                pert_masks: np.ndarray
-            ) -> np.ndarray:
-                return np.zeros((ref_dets.shape[0], *pert_masks.shape[1:]), dtype=np.float16)
-
-            get_config = None  # type: ignore
-
         class StubDetector (DetectImageObjects):
             """
             Stub object detector that returns known detections.
@@ -106,8 +106,8 @@ def detect_objects(
 
             get_config = None  # type: ignore
 
-        test_pi = StubPI()
-        test_gen = StubGen()
+        test_pi = TestPerturbationOcclusion.StubPI()
+        test_gen = TestPerturbationOcclusion.StubGen()
         test_detector = StubDetector()
 
         test_image = np.ones((64, 64, 3), dtype=np.uint8)
@@ -160,3 +160,42 @@ def detect_objects(
             m_kwargs = m_occ_img.call_args[-1]
             assert "fill" in m_kwargs
             assert m_kwargs['fill'] == test_fill
+
+    def test_empty_detections(self) -> None:
+        """
+        Test invoking _generate() with empty detections.
+        """
+
+        class StubDetector (DetectImageObjects):
+            """
+            Stub object detector that returns known detections.
+            """
+
+            def detect_objects(
+                self,
+                img_iter: Iterable[np.ndarray]
+            ) -> Iterable[Iterable[Tuple[AxisAlignedBoundingBox, Dict[Hashable, float]]]]:
+                for i, _ in enumerate(img_iter):
+                    # Return zero  detections for each image
+                    yield []
+
+            get_config = None  # type: ignore
+
+        test_pi = TestPerturbationOcclusion.StubPI()
+        test_gen = TestPerturbationOcclusion.StubGen()
+        test_detector = StubDetector()
+
+        test_image = np.ones((64, 64, 3), dtype=np.uint8)
+
+        test_bboxes = np.ones((3, 4))
+        test_scores = np.ones((3, 2))
+
+        inst = PerturbationOcclusion(test_pi, test_gen)
+        test_result = inst._generate(
+            test_image,
+            test_bboxes,
+            test_scores,
+            test_detector
+        )
+
+        assert len(test_result) == 0

tests/interfaces/test_gen_object_detector_blackbox_sal.py

@@ -1,8 +1,10 @@
 import unittest.mock as mock
 import numpy as np
 import pytest
+from typing import Iterable, Tuple, Dict, Hashable
 
 from smqtk_detection import DetectImageObjects
+from smqtk_detection.utils.bbox import AxisAlignedBoundingBox
 
 from xaitk_saliency.interfaces.gen_object_detector_blackbox_sal import GenerateObjectDetectorBlackboxSaliency
 from xaitk_saliency.exceptions import ShapeMismatchError
@@ -301,3 +303,38 @@ def test_call_alias() -> None:
         None  # no objectness passed
     )
     assert test_ret == expected_return
+
+
+def test_return_empty_map() -> None:
+    """
+    Test that an empty array of maps is returned properly
+    """
+    m_impl = mock.Mock(spec=GenerateObjectDetectorBlackboxSaliency)
+    m_detector = mock.Mock(spec=DetectImageObjects)
+
+    # test reference detections inputs with matching lengths
+    test_bboxes = np.ones((5, 4), dtype=float)
+    test_scores = np.ones((5, 3), dtype=float)
+
+    # 2-channel image as just HxW should work
+    test_image = np.ones((256, 256), dtype=np.uint8)
+
+    expected_return = np.array([])
+    m_impl._generate.return_value = expected_return
+
+    test_ret = GenerateObjectDetectorBlackboxSaliency.generate(
+        m_impl,
+        test_image,
+        test_bboxes,
+        test_scores,
+        m_detector,
+    )
+
+    m_impl._generate.assert_called_with(
+        test_image,
+        test_bboxes,
+        test_scores,
+        m_detector,
+        None  # no objectness passed
+    )
+    assert len(test_ret) == 0