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+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/shape_inference.h"
+
+namespace tensorflow {
+
+using shape_inference::InferenceContext;
+
+REGISTER_OP("SingleImageRandomDotStereograms")
+    .Attr("T: {double,float,int64,int32}")
+    .Input("depth_values: T")
+    .Output("image: uint8")
+    .Attr("hidden_surface_removal: bool = true")
+    .Attr("convergence_dots_size: int = 8")
+    .Attr("dots_per_inch: int = 72")
+    .Attr("eye_separation: float = 2.5")
+    .Attr("mu: float = .3333")
+    .Attr("normalize: bool = true")
+    .Attr("normalize_max: float = -100.0")
+    .Attr("normalize_min: float = 100.0")
+    .Attr("border_level: float = 0.0")
+    .Attr("number_colors: int = 256")
+    .Attr(
+        "output_image_shape: shape = { dim {size:1024} dim {size: 768} dim "
+        "{size: 1}}")
+    .Attr("output_data_window: shape = { dim {size:1022} dim {size: 757}}")
+    .Doc(R"doc(
+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.
+
+This Op is based upon:
+'http://www.learningace.com/doc/4331582/b6ab058d1e206d68ab60e4e1ead2fe6e/sirds-paper'
+
+Example use which outputs a SIRDS image as picture_out.png:
+```python
+img=[[1,2,3,3,2,1],
+     [1,2,3,4,5,2],
+     [1,2,3,4,5,3],
+     [1,2,3,4,5,4],
+     [6,5,4,4,5,5]]
+
+session = tf.InteractiveSession()
+
+sirds = single_image_random_dot_stereograms(img,convergence_dots_size=8,number_colors=256,normalize=True)
+
+out = sirds.eval()
+
+png = tf.image.encode_png(out).eval()
+
+with open('picture_out.png', 'wb') as f:
+    f.write(png)
+```
+
+depth_values: Z values of data to encode into 'output_data_window' window, 
+  lower values are further away {0.0 floor(far), 1.0 ceiling(near) after normalization}, must be 2-D tensor
+hidden_surface_removal: Activate hidden surface removal
+convergence_dots_size: Black dot size in pixels to help view converge image, drawn on bottom of image
+dots_per_inch: Output device in dots/inch
+eye_separation: Separation between eyes in inches
+mu: Depth of field, Fraction of viewing distance (eg. 1/3 = .3333)
+normalize: Normalize input data to [0.0, 1.0] 
+normalize_max: Fix MAX value for Normalization - if < MIN, autoscale
+normalize_min: Fix MIN value for Normalization - if > MAX, autoscale
+border_level: Value of border depth 0.0 {far} to 1.0 {near}
+number_colors: 2 (Black & White),256 (grayscale), and Numbers > 256 (Full Color) are all that are supported currently
+output_image_shape: Output size of returned image in X,Y, Channels 1-grayscale, 3 color (1024, 768, 1),
+  channels will be updated to 3 if 'number_colors' > 256
+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'
+)doc");
+
+}  // namespace tensorflow