Register DrawBoundingBoxV2 op in image_ops.cc

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>

tensorflow/core/ops/image_ops.cc

@@ -594,6 +594,39 @@ REGISTER_OP("DrawBoundingBoxes")
       return shape_inference::UnchangedShape(c);
     });
 
+// --------------------------------------------------------------------------
+REGISTER_OP("DrawBoundingBoxesV2")
+    .Input("images: T")
+    .Input("boxes: float")
+    .Input("colors: float")
+    .Output("output: T")
+    .Attr("T: {float, half} = DT_FLOAT")
+    .SetShapeFn([](InferenceContext* c) {
+      return shape_inference::UnchangedShapeWithRankAtLeast(c, 3);
+    })
+    .Doc(R"doc(
+Draw bounding boxes on a batch of images.
+
+Outputs a copy of `images` but draws on top of the pixels zero or more bounding
+boxes specified by the locations in `boxes`. The coordinates of the each
+bounding box in `boxes` are encoded as `[y_min, x_min, y_max, x_max]`. The
+bounding box coordinates are floats in `[0.0, 1.0]` relative to the width and
+height of the underlying image.
+
+For example, if an image is 100 x 200 pixels (height x width) and the bounding
+box is `[0.1, 0.2, 0.5, 0.9]`, the upper-left and bottom-right coordinates of
+the bounding box will be `(40, 10)` to `(100, 50)` (in (x,y) coordinates).
+
+Parts of the bounding box may fall outside the image.
+
+images: 4-D with shape `[batch, height, width, depth]`. A batch of images.
+boxes: 3-D with shape `[batch, num_bounding_boxes, 4]` containing bounding
+  boxes.
+colors: 2-D. A list of RGBA colors to cycle through for the boxes.
+output: 4-D with the same shape as `images`. The batch of input images with
+  bounding boxes drawn on the images.
+)doc");
+
 // --------------------------------------------------------------------------
 REGISTER_OP("SampleDistortedBoundingBox")
     .Input("image_size: T")