Resolve "In painting has different output based on computer OS"

Closes #2 (closed)

As discussed in #2 (closed), small differences coming from difference linear algebra libraries can be amplified during further computation (especially in uint8 precision) and lead to slightly different output on different systems. This is not something that can be easily worked around, therefore the chosen solution is to increase the tolerance of the unit tests to allow for these small modifications.

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)