Adjust hue of RGB images.

This is a convenience method that converts an RGB image to float representation, converts it to HSV, adds an offset to the hue channel, converts back to RGB and then back to the original data type. If several adjustments are chained it is advisable to minimize the number of redundant conversions.

`image` is an RGB image. The image hue is adjusted by converting the image(s) to HSV and rotating the hue channel (H) by `delta`. The image is then converted back to RGB.

`delta` must be in the interval `[-1, 1]`.

#### Usage Example:

````x = [[[1.0, 2.0, 3.0],`
`      [4.0, 5.0, 6.0]],`
`    [[7.0, 8.0, 9.0],`
`      [10.0, 11.0, 12.0]]]`
`tf.image.adjust_hue(x, 0.2)`
`<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=`
`array([[[ 2.3999996,  1.       ,  3.       ],`
`        [ 5.3999996,  4.       ,  6.       ]],`
`      [[ 8.4      ,  7.       ,  9.       ],`
`        [11.4      , 10.       , 12.       ]]], dtype=float32)>`
```

`image` RGB image or images. The size of the last dimension must be 3.
`delta` float. How much to add to the hue channel.
`name` A name for this operation (optional).

Adjusted image(s), same shape and DType as `image`.

#### Usage Example:

````image = [[[1, 2, 3], [4, 5, 6]],`
`         [[7, 8, 9], [10, 11, 12]],`
`         [[13, 14, 15], [16, 17, 18]]]`
`image = tf.constant(image)`
`tf.image.adjust_hue(image, 0.2)`
`<tf.Tensor: shape=(3, 2, 3), dtype=int32, numpy=`
`array([[[ 2,  1,  3],`
`      [ 5,  4,  6]],`
`     [[ 8,  7,  9],`
`      [11, 10, 12]],`
`     [[14, 13, 15],`
`      [17, 16, 18]]], dtype=int32)>`
```
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[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]