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-rw-r--r--tensorflow/contrib/image/kernels/adjust_hsv_in_yiq_op_gpu.cu.cc2
-rw-r--r--tensorflow/contrib/image/ops/distort_image_ops.cc4
-rw-r--r--tensorflow/contrib/image/ops/image_ops.cc2
-rwxr-xr-xtensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc4
-rw-r--r--tensorflow/contrib/image/python/ops/image_ops.py2
-rwxr-xr-xtensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py2
6 files changed, 8 insertions, 8 deletions
diff --git a/tensorflow/contrib/image/kernels/adjust_hsv_in_yiq_op_gpu.cu.cc b/tensorflow/contrib/image/kernels/adjust_hsv_in_yiq_op_gpu.cu.cc
index 1be97ae3d6..bbb3a3b18f 100644
--- a/tensorflow/contrib/image/kernels/adjust_hsv_in_yiq_op_gpu.cu.cc
+++ b/tensorflow/contrib/image/kernels/adjust_hsv_in_yiq_op_gpu.cu.cc
@@ -53,7 +53,7 @@ void AdjustHsvInYiqGPU::operator()(OpKernelContext* ctx, int channel_count,
OP_REQUIRES_OK(ctx, ctx->allocate_temp(
DT_FLOAT, TensorShape({kChannelSize * kChannelSize}),
&tranformation_matrix));
- // TODO(huangyp): It takes about 3.5 us to comute tranformation_matrix
+ // TODO(huangyp): It takes about 3.5 us to compute tranformation_matrix
// with one thread. Improve its performance if necessary.
internal::compute_tranformation_matrix_cuda<<<1, 1, 0, cu_stream>>>(
delta_h, scale_s, scale_v, tranformation_matrix.flat<float>().data(),
diff --git a/tensorflow/contrib/image/ops/distort_image_ops.cc b/tensorflow/contrib/image/ops/distort_image_ops.cc
index b169b0b2b2..ca49635d5d 100644
--- a/tensorflow/contrib/image/ops/distort_image_ops.cc
+++ b/tensorflow/contrib/image/ops/distort_image_ops.cc
@@ -36,9 +36,9 @@ REGISTER_OP("AdjustHsvInYiq")
Adjust the YIQ hue of one or more images.
`images` is a tensor of at least 3 dimensions. The last dimension is
-interpretted as channels, and must be three.
+interpreted as channels, and must be three.
-We used linear transfomation described in:
+We used linear transformation described in:
beesbuzz.biz/code/hsv_color_transforms.php
The input image is considered in the RGB colorspace. Conceptually, the RGB
colors are first mapped into YIQ space, rotated around the Y channel by
diff --git a/tensorflow/contrib/image/ops/image_ops.cc b/tensorflow/contrib/image/ops/image_ops.cc
index e97267fb89..295908d44b 100644
--- a/tensorflow/contrib/image/ops/image_ops.cc
+++ b/tensorflow/contrib/image/ops/image_ops.cc
@@ -137,7 +137,7 @@ row_to_col_match_indices: A vector of length num_rows, which is the number of
If `row_to_col_match_indices[i]` is not -1, row i is matched to column
`row_to_col_match_indices[i]`.
col_to_row_match_indices: A vector of length num_columns, which is the number
- of columns of the input ditance matrix.
+ of columns of the input distance matrix.
If `col_to_row_match_indices[j]` is not -1, column j is matched to row
`col_to_row_match_indices[j]`.
)doc");
diff --git a/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc b/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc
index 8139d4272d..bd784c6bda 100755
--- a/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc
+++ b/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc
@@ -69,7 +69,7 @@ Outputs a single image random dot stereogram for export via encode_PNG/JPG OP.
Given the 2-D tensor 'depth_values' with encoded Z values, this operation will
encode 3-D data into a 2-D image. The output of this Op is suitable for the
encode_PNG/JPG ops. Be careful with image compression as this may corrupt the
-encode 3-D data witin the image.
+encode 3-D data within the image.
This Op is based upon:
'http://www.learningace.com/doc/4331582/b6ab058d1e206d68ab60e4e1ead2fe6e/sirds-paper'
@@ -111,7 +111,7 @@ output_image_shape: Output size of returned image in X,Y, Channels 1-grayscale,
output_data_window: Size of "DATA" window, must be equal to or smaller than 'output_image_shape', will be centered
and use 'convergence_dots_size' for best fit to avoid overlap if possible
-image:= A tensor of size 'output_image_shape' with the encloded 'depth_values'
+image:= A tensor of size 'output_image_shape' with the encoded 'depth_values'
)doc");
} // namespace tensorflow
diff --git a/tensorflow/contrib/image/python/ops/image_ops.py b/tensorflow/contrib/image/python/ops/image_ops.py
index a8d8cf8c5c..d3c114a88d 100644
--- a/tensorflow/contrib/image/python/ops/image_ops.py
+++ b/tensorflow/contrib/image/python/ops/image_ops.py
@@ -438,7 +438,7 @@ def bipartite_match(distance_mat,
of rows of the input `distance_matrix`. If `row_to_col_match_indices[i]`
is not -1, row i is matched to column `row_to_col_match_indices[i]`.
col_to_row_match_indices: A vector of length num_columns, which is the
- number of columns of the input ditance matrix.
+ number of columns of the input distance matrix.
If `col_to_row_match_indices[j]` is not -1, column j is matched to row
`col_to_row_match_indices[j]`.
"""
diff --git a/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py b/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py
index d4a6a5bcbb..0ceb683ff4 100755
--- a/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py
+++ b/tensorflow/contrib/image/python/ops/single_image_random_dot_stereograms.py
@@ -45,7 +45,7 @@ def single_image_random_dot_stereograms(depth_values,
Given the 2-D tensor 'depth_values' with encoded Z values, this operation
will encode 3-D data into a 2-D image. The output of this Op is suitable
for the encode_PNG/JPG ops. Be careful with image compression as this may
- corrupt the encode 3-D data witin the image.
+ corrupt the encode 3-D data within the image.
Based upon [this
paper](http://www.learningace.com/doc/4331582/b6ab058d1e206d68ab60e4e1ead2fe6e/sirds-paper).