aleju · aleju · Sep 13, 2019 · Sep 8, 2019 · Sep 8, 2019 · Sep 8, 2019
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -399,6 +399,42 @@
       `JpegCompression`.
     * [rarely breaking] Removed attribute `minimum_quality` from
       `JpegCompression`.
+* Refactored `Affine` to improve code quality and decrease code
+  duplication. #413
+* Refactored `PiecewiseAffine` to improve code quality and decrease code
+  duplication. #413
+* Refactored `PerspectiveTransform` to improve code quality and decrease code
+  duplication. #413
+* Refactored `ElasticTransformation` to improve code quality and decrease code
+  duplication. #413
+  * [rarely breaking] Renamed `ElasticTransformation.generate_shift_maps()` to
+    `ElasticTransformation._generate_shift_maps()`.
+  * [rarely breaking] Renamed `ElasticTransformation.map_coordinates()` to
+    `ElasticTransformation._map_coordinates()`.
+* Refactored `Rot90` to improve code quality and decrease code
+  duplication. #413
+* Added `imgaug.testutils.ArgCopyingMagicMock`. #413
+* Refactored `Augmenter.augment_images()`, `Augmenter.augment_heatmaps()`,
+  `Augmenter.augment_segmentation_maps()`, `Augmenter.augment_polygons()`,
+  `Augmenter.augment_line_strings()` and `Augmenter._augment_coord_augables()`
+  to improve code quality and remove redundancies. #413
+* Refactored `imgaug.imgaug.imresize_single_image()`. #413
+* Added module `imgaug.validation`. #413
+  * Added `imgaug.validation.convert_iterable_to_string_of_types()`.
+  * Added `imgaug.validation.is_iterable_of()`.
+  * Added `imgaug.validation.assert_is_iterable_of()`.
+* Refactored `Sequential` to reduce code duplication. #413
+* Refactored `SomeOf` to improve code quality. #413
+* Refactored `Sometimes` to reduce code duplication. #413
+* Refactored `AssertShape` to reduce code duplication. #413
+* Refactored `ChannelShuffle` to improve code quality. #413
+* [rarely breaking] Changed `KeypointsOnImage.from_keypoints_image()` to
+  return `(x+0.5, y+0.5)` instead of `(x, y)` where `(x, y)` denotes the
+  coordinates of the pixel in which a maximum was found. This change matches
+  the standard that all pixels are given with subpixel accuracy and therefore
+  any whole pixel with a maximum should denote the coordinates of that
+  pixel's center. #413
+
 
 ## Improved Segmentation Map Augmentation #302
 

diff --git a/imgaug/augmentables/kps.py b/imgaug/augmentables/kps.py
@@ -706,9 +706,12 @@ def from_keypoint_image(image, if_not_found_coords={"x": -1, "y": -1},
         for i in sm.xrange(nb_keypoints):
             maxidx_flat = np.argmax(image[..., i])
             maxidx_ndim = np.unravel_index(maxidx_flat, (height, width))
+
             found = (image[maxidx_ndim[0], maxidx_ndim[1], i] >= threshold)
             if found:
-                keypoints.append(Keypoint(x=maxidx_ndim[1], y=maxidx_ndim[0]))
+                x = maxidx_ndim[1] + 0.5
+                y = maxidx_ndim[0] + 0.5
+                keypoints.append(Keypoint(x=x, y=y))
             else:
                 if drop_if_not_found:
                     # dont add the keypoint to the result list, i.e. drop it

diff --git a/imgaug/augmenters/blur.py b/imgaug/augmenters/blur.py
@@ -246,17 +246,7 @@ def blur_gaussian_(image, sigma, ksize=None, backend="auto", eps=1e-3):
             # ksize = ((sig - 0.8)/0.3 + 1)/0.5 + 1
 
             if ksize is None:
-                if sigma < 3.0:
-                    ksize = 3.3 * sigma  # 99% of weight
-                elif sigma < 5.0:
-                    ksize = 2.9 * sigma  # 97% of weight
-                else:
-                    ksize = 2.6 * sigma  # 95% of weight
-
-                # we use 5x5 here as the minimum size as that simplifies
-                # comparisons with gaussian_filter() in the tests
-                # TODO reduce this to 3x3
-                ksize = int(max(ksize, 5))
+                ksize = _compute_gaussian_blur_ksize(sigma)
             else:
                 assert ia.is_single_integer(ksize), (
                     "Expected 'ksize' argument to be a number, "
@@ -283,6 +273,21 @@ def blur_gaussian_(image, sigma, ksize=None, backend="auto", eps=1e-3):
     return image
 
 
+def _compute_gaussian_blur_ksize(sigma):
+    if sigma < 3.0:
+        ksize = 3.3 * sigma  # 99% of weight
+    elif sigma < 5.0:
+        ksize = 2.9 * sigma  # 97% of weight
+    else:
+        ksize = 2.6 * sigma  # 95% of weight
+
+    # we use 5x5 here as the minimum size as that simplifies
+    # comparisons with gaussian_filter() in the tests
+    # TODO reduce this to 3x3
+    ksize = int(max(ksize, 5))
+    return ksize
+
+
 # TODO offer different values for sigma on x/y-axis, supported by cv2 but not
 #      by scipy
 # TODO add channelwise flag - channelwise=False would be supported by scipy

diff --git a/imgaug/augmenters/contrast.py b/imgaug/augmenters/contrast.py
@@ -1016,8 +1016,7 @@ def _augment_images(self, images, random_state, parents, hooks):
                     c_param += 1
 
             # combine channels to one image
-            image_warped = np.array(image_warped, dtype=image_warped[0].dtype)
-            image_warped = image_warped.transpose((1, 2, 0))
+            image_warped = np.stack(image_warped, axis=-1)
 
             images[i] = image_warped
         return images