address comments

python/mxnet/image/image.py

@@ -46,7 +46,7 @@
 def imread(filename, *args, **kwargs):
     """Read and decode an image to an NDArray.
 
-    Note: `imread` uses OpenCV (not the CV2 Python library).
+    .. note:: `imread` uses OpenCV (not the CV2 Python library).
     MXNet must have been built with USE_OPENCV=1 for `imdecode` to work.
 
     Parameters
@@ -84,11 +84,11 @@ def imread(filename, *args, **kwargs):
     return _internal._cvimread(filename, *args, **kwargs)
 
 
-def imresize(src, w, h, interp):
+def imresize(src, w, h, *args, **kwargs):
     r"""Resize image with OpenCV.
 
-    Note: `imread` uses OpenCV (not the CV2 Python library).
-    MXNet must have been built with USE_OPENCV=1 for `imdecode` to work.
+    .. note:: `imresize` uses OpenCV (not the CV2 Python library). MXNet must have been built
+    with USE_OPENCV=1 for `imresize` to work.
 
     Parameters
     ----------
@@ -98,8 +98,25 @@ def imresize(src, w, h, interp):
         Width of resized image.
     h : int, required
         Height of resized image.
-    interp : int, optional, default='1'
+    interp : int, optional, default=1
         Interpolation method (default=cv2.INTER_LINEAR).
+        Possible values:
+        0: Nearest Neighbors Interpolation.
+        1: Bilinear interpolation.
+        2: Area-based (resampling using pixel area relation). It may be a
+        preferred method for image decimation, as it gives moire-free
+        results. But when the image is zoomed, it is similar to the Nearest
+        Neighbors method. (used by default).
+        3: Bicubic interpolation over 4x4 pixel neighborhood.
+        4: Lanczos interpolation over 8x8 pixel neighborhood.
+        9: Cubic for enlarge, area for shrink, bilinear for others
+        10: Random select from interpolation method metioned above.
+        Note:
+        When shrinking an image, it will generally look best with AREA-based
+        interpolation, whereas, when enlarging an image, it will generally look best
+        with Bicubic (slow) or Bilinear (faster but still looks OK).
+        More details can be found in the documentation of OpenCV, please refer to
+        http://docs.opencv.org/master/da/d54/group__imgproc__transform.html.
 
     out : NDArray, optional
         The output NDArray to hold the result.
@@ -121,13 +138,13 @@ def imresize(src, w, h, interp):
     >>> new_image
     <NDArray 2321x3482x3 @cpu(0)>
     """
-    return _internal._cvimresize(src, w, h, interp)
+    return _internal._cvimresize(src, w, h, *args, **kwargs)
 
 
 def imdecode(buf, *args, **kwargs):
     """Decode an image to an NDArray.
 
-    Note: `imdecode` uses OpenCV (not the CV2 Python library).
+    .. note:: `imdecode` uses OpenCV (not the CV2 Python library).
     MXNet must have been built with USE_OPENCV=1 for `imdecode` to work.
 
     Parameters
@@ -275,7 +292,7 @@ def _get_interp_method(interp, sizes=()):
 def resize_short(src, size, interp=2):
     """Resizes shorter edge to size.
 
-    Note: `resize_short` uses OpenCV (not the CV2 Python library).
+    .. note:: `resize_short` uses OpenCV (not the CV2 Python library).
     MXNet must have been built with OpenCV for `resize_short` to work.
 
     Resizes the original image by setting the shorter edge to size

tests/python/unittest/test_image.py

@@ -141,7 +141,7 @@ def test_imdecode(self):
         try:
             import cv2
         except ImportError:
-            return
+            raise unittest.SkipTest("Unable to import cv2.")
         for img in TestImage.IMAGES:
             with open(img, 'rb') as fp:
                 str_image = fp.read()
@@ -175,11 +175,12 @@ def test_scale_down(self):
         assert mx.image.scale_down((360, 1000), (480, 500)) == (360, 375)
         assert mx.image.scale_down((300, 400), (0, 0)) == (0, 0)
 
+    @with_seed()
     def test_resize_short(self):
         try:
             import cv2
         except ImportError:
-            return
+            raise unittest.SkipTest("Unable to import cv2")
         for img in TestImage.IMAGES:
             cv_img = cv2.imread(img)
             mx_img = mx.nd.array(cv_img[:, :, (2, 1, 0)])
@@ -196,21 +197,25 @@ def test_resize_short(self):
                     mx_resized = mx.image.resize_short(mx_img, new_size, interp)
                     assert_almost_equal(mx_resized.asnumpy()[:, :, (2, 1, 0)], cv_resized, atol=3)
 
+    @with_seed()
     def test_imresize(self):
         try:
             import cv2
         except ImportError:
-            return
+            raise unittest.SkipTest("Unable to import cv2")
         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 in range(0, 2):
-                    cv_resized = cv2.resize(cv_img, (new_w, new_h), interpolation=interp)
-                    mx_resized = mx.image.imresize(mx_img, new_w, new_h, interp)
+                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):