copyMakeBorder

docs/api/python/image/image.md

@@ -20,6 +20,7 @@ images provided in
     image.imdecode
     image.imresize
     image.scale_down
+    image.copyMakeBorder
     image.resize_short
     image.fixed_crop
     image.random_crop
@@ -169,6 +170,7 @@ and a list of augmenters specific for `Object detection` is provided
 .. automethod:: mxnet.image.imdecode
 .. automethod:: mxnet.image.imresize
 .. automethod:: mxnet.image.scale_down
+.. automethod:: mxnet.image.copyMakeBorder
 .. automethod:: mxnet.image.resize_short
 .. automethod:: mxnet.image.fixed_crop
 .. automethod:: mxnet.image.random_crop

python/mxnet/image/image.py

@@ -38,7 +38,6 @@
 from ..base import numeric_types
 from .. import ndarray as nd
 from ..ndarray import _internal
-from ..ndarray._internal import _cvcopyMakeBorder as copyMakeBorder
 from .. import io
 from .. import recordio
 
@@ -136,7 +135,7 @@ def imresize(src, w, h, *args, **kwargs):
     <NDArray 2321x3482x3 @cpu(0)>
     >>> new_image = mx.img.resize(image, 240, 360)
     >>> new_image
-    <NDArray 2321x3482x3 @cpu(0)>
+    <NDArray 240x360x3 @cpu(0)>
     """
     return _internal._cvimresize(src, w, h, *args, **kwargs)
 
@@ -234,6 +233,59 @@ def scale_down(src_size, size):
     return int(w), int(h)
 
 
+def copyMakeBorder(src, top, bot, left, right, *args, **kwargs):
+    """Pad image border with OpenCV.
+
+    Parameters
+    ----------
+    src : NDArray
+        source image
+    top : int, required
+        Top margin.
+    bot : int, required
+        Bottom margin.
+    left : int, required
+        Left margin.
+    right : int, required
+        Right margin.
+    type : int, optional, default='0'
+        Filling type (default=cv2.BORDER_CONSTANT).
+        0 - cv2.BORDER_CONSTANT - Adds a constant colored border.
+        1 - cv2.BORDER_REFLECT - Border will be mirror reflection of the
+        border elements, like this : fedcba|abcdefgh|hgfedcb
+        2 - cv2.BORDER_REFLECT_101 or cv.BORDER_DEFAULT - Same as above,
+        but with a slight change, like this : gfedcb|abcdefgh|gfedcba
+        3 - cv2.BORDER_REPLICATE - Last element is replicated throughout,
+        like this: aaaaaa|abcdefgh|hhhhhhh
+        4 - cv2.BORDER_WRAP - it will look like this : cdefgh|abcdefgh|abcdefg
+    value : double, optional, default=0
+        (Deprecated! Use ``values`` instead.) Fill with single value.
+    values : tuple of <double>, optional, default=[]
+        Fill with value(RGB[A] or gray), up to 4 channels.
+
+    out : NDArray, optional
+        The output NDArray to hold the result.
+
+    Returns
+    -------
+    out : NDArray or list of NDArrays
+        The output of this function.
+
+    Example
+    --------
+    >>> with open("flower.jpeg", 'rb') as fp:
+    ...     str_image = fp.read()
+    ...
+    >>> image = mx.img.imdecode(str_image)
+    >>> image
+    <NDArray 2321x3482x3 @cpu(0)>
+    >>> new_image = mx_border = mx.image.copyMakeBorder(mx_img, 1, 2, 3, 4, type=0)
+    >>> new_image
+    <NDArray 2324x3489x3 @cpu(0)>
+    """
+    return _internal._cvcopyMakeBorder(src, top, bot, left, right, *args, **kwargs)
+
+
 def _get_interp_method(interp, sizes=()):
     """Get the interpolation method for resize functions.
     The major purpose of this function is to wrap a random interp method selection

tests/python/unittest/test_image.py

@@ -149,16 +149,15 @@ def test_imresize(self):
         for img in TestImage.IMAGES:
             cv_img = cv2.imread(img)
             mx_img = mx.nd.array(cv_img[:, :, (2, 1, 0)])
-            for _ in range(3):
-                new_h = np.random.randint(1, 1000)
-                new_w = np.random.randint(1, 1000)
-                for interp_val in range(0, 2):
-                    cv_resized = cv2.resize(cv_img, (new_w, new_h), interpolation=interp_val)
-                    mx_resized = mx.image.imresize(mx_img, new_w, new_h, interp=interp_val)
-                    assert_almost_equal(mx_resized.asnumpy()[:, :, (2, 1, 0)], cv_resized, atol=3)
-                    out_img = mx.nd.zeros((new_h, new_w, 3), dtype=mx_img.dtype)
-                    mx.image.imresize(mx_img, new_w, new_h, interp=interp_val, out=out_img)
-                    assert_almost_equal(out_img.asnumpy()[:, :, (2, 1, 0)], cv_resized, atol=3)
+            new_h = np.random.randint(1, 1000)
+            new_w = np.random.randint(1, 1000)
+            for interp_val in range(0, 2):
+                cv_resized = cv2.resize(cv_img, (new_w, new_h), interpolation=interp_val)
+                mx_resized = mx.image.imresize(mx_img, new_w, new_h, interp=interp_val)
+                assert_almost_equal(mx_resized.asnumpy()[:, :, (2, 1, 0)], cv_resized, atol=3)
+                out_img = mx.nd.zeros((new_h, new_w, 3), dtype=mx_img.dtype)
+                mx.image.imresize(mx_img, new_w, new_h, interp=interp_val, out=out_img)
+                assert_almost_equal(out_img.asnumpy()[:, :, (2, 1, 0)], cv_resized, atol=3)
 
     def test_color_normalize(self):
         for _ in range(10):
@@ -253,6 +252,31 @@ def check_imageiter(dtype='float32'):
         # test with default dtype
         check_imageiter()
 
+    @with_seed()
+    def test_copyMakeBorder(self):
+        try:
+            import cv2
+        except ImportError:
+            raise unittest.SkipTest("Unable to import cv2")
+        for img in TestImage.IMAGES:
+            cv_img = cv2.imread(img)
+            mx_img = mx.nd.array(cv_img)
+            top = np.random.randint(1, 10)
+            bot = np.random.randint(1, 10)
+            left = np.random.randint(1, 10)
+            right = np.random.randint(1, 10)
+            new_h, new_w, _ = mx_img.shape
+            new_h += top + bot
+            new_w += left + right
+            val = [np.random.randint(1, 255)] * 3
+            for type_val in range(0, 5):
+                cv_border = cv2.copyMakeBorder(cv_img, top, bot, left, right, borderType=type_val, value=val)
+                mx_border = mx.image.copyMakeBorder(mx_img, top, bot, left, right, type=type_val, values=val)
+                assert_almost_equal(mx_border.asnumpy(), cv_border)
+                out_img = mx.nd.zeros((new_h , new_w, 3), dtype=mx_img.dtype)
+                mx.image.copyMakeBorder(mx_img, top, bot, left, right, type=type_val, values=val, out=out_img)
+                assert_almost_equal(out_img.asnumpy(), cv_border)
+
     @with_seed()
     def test_augmenters(self):
         # ColorNormalizeAug