1 files changed, 105 insertions, 1 deletions
diff --git a/tensorflow/python/ops/image_ops_impl.py b/tensorflow/python/ops/image_ops_impl.py
index 2c231ef56c..14a38f25d1 100644
--- a/tensorflow/python/ops/image_ops_impl.py
+++ b/tensorflow/python/ops/image_ops_impl.py
@@ -1508,7 +1508,7 @@ def sample_distorted_bounding_box(image_size,
                                   bounding_boxes,
                                   seed=None,
                                   seed2=None,
-                                  min_object_covered=None,
+                                  min_object_covered=0.1,
                                   aspect_ratio_range=None,
                                   area_range=None,
                                   max_attempts=None,
@@ -1669,3 +1669,107 @@ def non_max_suppression(boxes,
     return gen_image_ops._non_max_suppression_v2(boxes, scores, max_output_size,
                                                  iou_threshold)
     # pylint: enable=protected-access
+
+
+_rgb_to_yiq_kernel = [[0.299, 0.59590059,
+                       0.2115], [0.587, -0.27455667, -0.52273617],
+                      [0.114, -0.32134392, 0.31119955]]
+
+
+def rgb_to_yiq(images):
+  """Converts one or more images from RGB to YIQ.
+
+  Outputs a tensor of the same shape as the `images` tensor, containing the YIQ
+  value of the pixels.
+  The output is only well defined if the value in images are in [0,1].
+
+  Args:
+    images: 2-D or higher rank. Image data to convert. Last dimension must be
+    size 3.
+
+  Returns:
+    images: tensor with the same shape as `images`.
+  """
+  images = ops.convert_to_tensor(images, name='images')
+  kernel = ops.convert_to_tensor(
+      _rgb_to_yiq_kernel, dtype=images.dtype, name='kernel')
+  ndims = images.get_shape().ndims
+  return math_ops.tensordot(images, kernel, axes=[[ndims - 1], [0]])
+
+
+_yiq_to_rgb_kernel = [[1, 1, 1], [0.95598634, -0.27201283, -1.10674021],
+                      [0.6208248, -0.64720424, 1.70423049]]
+
+
+def yiq_to_rgb(images):
+  """Converts one or more images from YIQ to RGB.
+
+  Outputs a tensor of the same shape as the `images` tensor, containing the RGB
+  value of the pixels.
+  The output is only well defined if the Y value in images are in [0,1],
+  I value are in [-0.5957,0.5957] and Q value are in [-0.5226,0.5226].
+
+  Args:
+    images: 2-D or higher rank. Image data to convert. Last dimension must be
+    size 3.
+
+  Returns:
+    images: tensor with the same shape as `images`.
+  """
+  images = ops.convert_to_tensor(images, name='images')
+  kernel = ops.convert_to_tensor(
+      _yiq_to_rgb_kernel, dtype=images.dtype, name='kernel')
+  ndims = images.get_shape().ndims
+  return math_ops.tensordot(images, kernel, axes=[[ndims - 1], [0]])
+
+
+_rgb_to_yuv_kernel = [[0.299, -0.14714119,
+                       0.61497538], [0.587, -0.28886916, -0.51496512],
+                      [0.114, 0.43601035, -0.10001026]]
+
+
+def rgb_to_yuv(images):
+  """Converts one or more images from RGB to YUV.
+
+  Outputs a tensor of the same shape as the `images` tensor, containing the YUV
+  value of the pixels.
+  The output is only well defined if the value in images are in [0,1].
+
+  Args:
+    images: 2-D or higher rank. Image data to convert. Last dimension must be
+    size 3.
+
+  Returns:
+    images: tensor with the same shape as `images`.
+  """
+  images = ops.convert_to_tensor(images, name='images')
+  kernel = ops.convert_to_tensor(
+      _rgb_to_yuv_kernel, dtype=images.dtype, name='kernel')
+  ndims = images.get_shape().ndims
+  return math_ops.tensordot(images, kernel, axes=[[ndims - 1], [0]])
+
+
+_yuv_to_rgb_kernel = [[1, 1, 1], [0, -0.394642334, 2.03206185],
+                      [1.13988303, -0.58062185, 0]]
+
+
+def yuv_to_rgb(images):
+  """Converts one or more images from YUV to RGB.
+
+  Outputs a tensor of the same shape as the `images` tensor, containing the RGB
+  value of the pixels.
+  The output is only well defined if the Y value in images are in [0,1],
+  U and V value are in [-0.5,0.5].
+
+  Args:
+    images: 2-D or higher rank. Image data to convert. Last dimension must be
+    size 3.
+
+  Returns:
+    images: tensor with the same shape as `images`.
+  """
+  images = ops.convert_to_tensor(images, name='images')
+  kernel = ops.convert_to_tensor(
+      _yuv_to_rgb_kernel, dtype=images.dtype, name='kernel')
+  ndims = images.get_shape().ndims
+  return math_ops.tensordot(images, kernel, axes=[[ndims - 1], [0]])