lint

docker/install/python.sh

@@ -24,5 +24,5 @@ apt-get update && apt-get install -y python-dev python3-dev
 # the version of the pip shipped with ubuntu may be too lower, install a recent version here
 cd /tmp && wget https://bootstrap.pypa.io/get-pip.py && python3 get-pip.py && python2 get-pip.py
 
-pip2 install nose pylint numpy nose-timer requests
-pip3 install nose pylint numpy nose-timer requests
+pip2 install nose pylint numpy nose-timer requests Pillow
+pip3 install nose pylint numpy nose-timer requests Pillow

python/mxnet/gluon/data/vision/__init__.py

@@ -16,6 +16,8 @@
 # under the License.
 
 # coding: utf-8
+# pylint: disable=wildcard-import
+"""Vision utilities."""
 
 from .datasets import *
 

python/mxnet/gluon/data/vision/transforms.py

@@ -16,12 +16,13 @@
 # under the License.
 
 # coding: utf-8
+# pylint: disable= arguments-differ
+"Image transforms."
 
-from .. import dataset
 from ...block import Block, HybridBlock
 from ...nn import Sequential, HybridSequential
-from .... import ndarray, initializer, image
-from ....base import _Null, numeric_types
+from .... import image
+from ....base import numeric_types
 
 
 class Compose(Sequential):

python/mxnet/ndarray/__init__.py

@@ -31,4 +31,5 @@
 from .sparse import _ndarray_cls
 from .ndarray import _GRAD_REQ_MAP
 
-__all__ = op.__all__ + ndarray.__all__ + utils.__all__ + ['contrib', 'linalg', 'random', 'sparse', 'image']
+__all__ = op.__all__ + ndarray.__all__ + utils.__all__ + \
+          ['contrib', 'linalg', 'random', 'sparse', 'image']

src/operator/image/image_random-inl.h

@@ -175,7 +175,7 @@ template<typename DType, int axis>
 void FlipImpl(const TShape &shape, DType *src, DType *dst) {
   int head = 1, mid = shape[axis], tail = 1;
   for (int i = 0; i < axis; ++i) head *= shape[i];
-  for (int i = axis+1; i < shape.ndim(); ++i) tail *= shape[i];
+  for (uint32_t i = axis+1; i < shape.ndim(); ++i) tail *= shape[i];
 
   for (int i = 0; i < head; ++i) {
     for (int j = 0; j < (mid >> 1); ++j) {

tests/python/unittest/test_gluon_data.py

@@ -107,27 +107,6 @@ def test_multi_worker():
         assert (batch.asnumpy() == i).all()
 
 
-def test_transformer():
-    from mxnet.gluon.data.vision import transforms
-
-    transform = transforms.Compose([
-		transforms.Resize(300),
-		transforms.CenterCrop(256),
-		transforms.RandomResizedCrop(224),
-		transforms.RandomHorizontalFlip(),
-		transforms.RandomColorJitter(0.1, 0.1, 0.1, 0.1),
-		transforms.RandomBrightness(0.1),
-		transforms.RandomContrast(0.1),
-		transforms.RandomSaturation(0.1),
-		transforms.RandomHue(0.1),
-		transforms.RandomLighting(0.1),
-		transforms.ToTensor(),
-		transforms.Normalize([0, 0, 0], [1, 1, 1])])
-
-    transform(mx.nd.ones((245, 480, 3), dtype='uint8')).wait_to_read()
-
-
 if __name__ == '__main__':
-    test_transformer()
     import nose
     nose.runmodule()

tests/python/unittest/test_gluon_data_vision.py

@@ -18,7 +18,6 @@
 import mxnet as mx
 import mxnet.ndarray as nd
 import numpy as np
-from PIL import Image
 from mxnet import gluon
 from mxnet.gluon.data.vision import transforms
 from mxnet.test_utils import assert_almost_equal
@@ -42,15 +41,37 @@ def test_normalize():
 
 def test_flip_left_right():
     data_in = np.random.uniform(0, 255, (300, 300, 3)).astype(dtype=np.uint8)
-    pil_img = Image.fromarray(data_in).transpose(Image.FLIP_LEFT_RIGHT)
+    flip_in = data_in[:, ::-1, :]
     data_trans = nd.image.flip_left_right(nd.array(data_in, dtype='uint8'))
-    assert_almost_equal(np.array(pil_img), data_trans.asnumpy())
+    assert_almost_equal(flip_in, data_trans.asnumpy())
 
 def test_flip_top_bottom():
     data_in = np.random.uniform(0, 255, (300, 300, 3)).astype(dtype=np.uint8)
-    pil_img = Image.fromarray(data_in).transpose(Image.FLIP_TOP_BOTTOM)
+    flip_in = data_in[::-1, :, :]
     data_trans = nd.image.flip_top_bottom(nd.array(data_in, dtype='uint8'))
-    assert_almost_equal(np.array(pil_img), data_trans.asnumpy())
+    assert_almost_equal(flip_in, data_trans.asnumpy())
+
+
+def test_transformer():
+    from mxnet.gluon.data.vision import transforms
+
+    transform = transforms.Compose([
+		transforms.Resize(300),
+		transforms.CenterCrop(256),
+		transforms.RandomResizedCrop(224),
+		transforms.RandomFlipLeftRight(),
+		transforms.RandomColorJitter(0.1, 0.1, 0.1, 0.1),
+		transforms.RandomBrightness(0.1),
+		transforms.RandomContrast(0.1),
+		transforms.RandomSaturation(0.1),
+		transforms.RandomHue(0.1),
+		transforms.RandomLighting(0.1),
+		transforms.ToTensor(),
+		transforms.Normalize([0, 0, 0], [1, 1, 1])])
+
+    transform(mx.nd.ones((245, 480, 3), dtype='uint8')).wait_to_read()
+
+
 
 if __name__ == '__main__':
     import nose