Implements more tolerant tests based on image distances

bob/ip/stereo/test/test.py

@@ -28,6 +28,59 @@ def resource_path(relative_path, package="bob.ip.stereo"):
     return resource_filename(package, relative_path)
 
 
+def sum_of_squared_absolute_difference(array1, array2):
+    """Sum the squared absolute difference between the input arrays.
+    """
+
+    return np.sum((np.abs(array1.astype(np.float64)) - np.abs(array2.astype(np.float64))) ** 2)
+
+
+def euclidian_distance(array1, array2):
+    """Euclidian distance between the 2 input arrays (2 norm of the difference)
+    """
+
+    return np.sqrt(np.sum(np.square(array1.astype(np.float64) - array2.astype(np.float64))))
+
+
+def manhattan_distance(array1, array2):
+    """Manhattan (or city block) distance between 2 inputs
+    """
+
+    return np.sum(np.abs(array1.astype(np.float64) - array2.astype(np.float64)))
+
+
+def canberra_distance(array1, array2):
+    """Camberra distance between the 2 inputs
+    """
+
+    return np.sum(
+        np.abs(array1.astype(np.float64) - array2.astype(np.float64))
+        / (np.abs(array1.astype(np.float64)) + np.abs(array2.astype(np.float64)))
+    )
+
+
+def is_close_enough(image1, image2):
+    """Checks if the 2 inputs are close enough to pass the test, using different metrics.
+
+    The test is considered passed if the difference between the inputs is not more than the a small value for each pixel.
+    Eg: the first test is considered passed if "distance(image1, image2) < distance(image1, image1 + 2)"
+
+    The images are expected to be in unsigned int format (so positive).
+
+    """
+
+    assert image1.shape == image2.shape
+
+    nb_elements = np.prod(image1.shape)
+
+    return (
+        sum_of_squared_absolute_difference(image1, image2) < 2 * nb_elements
+        and euclidian_distance(image1, image2) < 4 * nb_elements
+        and manhattan_distance(image1, image2) < 2 * nb_elements
+        and canberra_distance(image1, image2) < 2 * nb_elements / (np.mean(image1) + np.mean(image2))
+    )
+
+
 def test_stereo_mapping_and_project():
     """
     Test that an image projected onto the left camera of a camera pair is close
@@ -45,7 +98,7 @@ def test_stereo_mapping_and_project():
     nir_right_stereo = load_camera_config(resource_path("config/idiap_face_calibration.json"), "nir_right")
     color = load_camera_config(resource_path("config/idiap_face_calibration.json"), "color")
     camera_pair = CameraPair(nir_left_stereo, nir_right_stereo)
-    
+
     stereo_parameters = StereoParameters()
     stereo_parameters.erode = True  # remove small features
     stereo_parameters.inpaint = True  # fill holes
@@ -63,5 +116,18 @@ def test_stereo_mapping_and_project():
     assert groundtruth_color_image.shape == projected_image.shape
     assert groundtruth_map_3d.shape == map_3d.shape
 
-    assert np.allclose(groundtruth_color_image, projected_image)
-    assert np.allclose(groundtruth_map_3d, map_3d)
+    # assert np.allclose(groundtruth_color_image, projected_image)
+    # assert np.allclose(groundtruth_map_3d, map_3d)
+
+    print("ssad", sum_of_squared_absolute_difference(groundtruth_color_image, projected_image))
+    print("n2", euclidian_distance(groundtruth_color_image, projected_image))
+    print("manhattan", manhattan_distance(groundtruth_color_image, projected_image))
+    print("canberra", canberra_distance(groundtruth_color_image, projected_image))
+
+    print("ssad", sum_of_squared_absolute_difference(groundtruth_map_3d, map_3d))
+    print("n2", euclidian_distance(groundtruth_map_3d, map_3d))
+    print("manhattan", manhattan_distance(groundtruth_map_3d, map_3d))
+    print("canberra", canberra_distance(groundtruth_map_3d, map_3d))
+
+    assert is_close_enough(groundtruth_color_image, projected_image)
+    assert is_close_enough(groundtruth_map_3d, map_3d)