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authorGravatar Dan Osipov <danospv@gmail.com>2018-06-05 16:39:47 -0700
committerGravatar Dan Osipov <danospv@gmail.com>2018-06-05 16:39:47 -0700
commit7edb417cd05fe438d587372fcf07e7c45e1dd8f8 (patch)
treeba257cbcbb24d9da0d0559160ffd898da0cc04e9 /tensorflow/python/ops/image_ops_impl.py
parent7eaef86f7766e7c0577614e646dc8d6a972b91f9 (diff)
Fix lint errors
Diffstat (limited to 'tensorflow/python/ops/image_ops_impl.py')
-rw-r--r--tensorflow/python/ops/image_ops_impl.py18
1 files changed, 11 insertions, 7 deletions
diff --git a/tensorflow/python/ops/image_ops_impl.py b/tensorflow/python/ops/image_ops_impl.py
index f3f9a02f01..231b49fbf5 100644
--- a/tensorflow/python/ops/image_ops_impl.py
+++ b/tensorflow/python/ops/image_ops_impl.py
@@ -971,7 +971,7 @@ def resize_images(images,
@tf_export('image.resize_image_with_pad')
def resize_image_with_pad(image, target_height, target_width,
- method=ResizeMethod.BILINEAR):
+ method=ResizeMethod.BILINEAR):
"""
Resizes and pads an image to a target width and height.
@@ -1038,17 +1038,21 @@ def resize_image_with_pad(image, target_height, target_width,
ratio = max_(f_width / f_target_width, f_height / f_target_height)
resized_height_float = f_height / ratio
resized_width_float = f_width / ratio
- resized_height = math_ops.cast(math_ops.floor(resized_height_float), dtype=dtypes.int32)
- resized_width = math_ops.cast(math_ops.floor(resized_width_float), dtype=dtypes.int32)
-
- f_padding_height = math_ops.floor((f_target_height - resized_height_float) / 2)
- f_padding_width = math_ops.floor((f_target_width - resized_width_float) / 2)
+ resized_height = math_ops.cast(math_ops.floor(resized_height_float),
+ dtype=dtypes.int32)
+ resized_width = math_ops.cast(math_ops.floor(resized_width_float),
+ dtype=dtypes.int32)
+
+ padding_height = (f_target_height - resized_height_float) / 2
+ padding_width = (f_target_width - resized_width_float) / 2
+ f_padding_height = math_ops.floor(padding_height)
+ f_padding_width = math_ops.floor(padding_width)
p_height = max_(0, math_ops.cast(f_padding_height, dtype=dtypes.int32))
p_width = max_(0, math_ops.cast(f_padding_width, dtype=dtypes.int32))
# Resize first, then pad to meet requested dimensions
resized = resize_images(image, [resized_height, resized_width], method)
-
+
padded = pad_to_bounding_box(resized, p_height, p_width,
target_height, target_width)