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Move rgb_to_hsv example.

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PiperOrigin-RevId: 298404199
Change-Id: I1c1cb83d430c3f81681813704c6db74420d54529
This commit is contained in:
Mark Daoust 2020-03-02 11:37:25 -08:00 committed by TensorFlower Gardener
parent e82714b529
commit b55101409d
2 changed files with 12 additions and 11 deletions
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12
tensorflow/core/api_def/base_api/api_def_RGBToHSV.pbtxt
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@ -21,5 +21,17 @@ are in `[0,1]`.
`output[..., 0]` contains hue, `output[..., 1]` contains saturation, and
`output[..., 2]` contains value. All HSV values are in `[0,1]`. A hue of 0
corresponds to pure red, hue 1/3 is pure green, and 2/3 is pure blue.
Usage Example:
>>> blue_image = tf.stack([
... tf.zeros([5,5]),
... tf.zeros([5,5]),
... tf.ones([5,5])],
... axis=-1)
>>> blue_hsv_image = tf.image.rgb_to_hsv(blue_image)
>>> blue_hsv_image[0,0].numpy()
array([0.6666667, 1. , 1. ], dtype=float32)
END
}

11
tensorflow/python/ops/image_grad.py
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@ -177,17 +177,6 @@ def _RGBToHSVGrad(op, grad):
separately before adding them in the end. Formulas are given before each
partial derivative calculation.
Usage Example:
>>> rgb_image = tf.stack([
... tf.zeros([5,5]),
... tf.zeros([5,5]),
... tf.ones([5,5])],
... axis=-1)
>>> hsv_image = tf.image.rgb_to_hsv(rgb_image)
>>> hsv_image[1,1].numpy()
array([0.6666667, 1. , 1. ], dtype=float32)
Args:
op: The `rgb_to_hsv` `Operation` that we are differentiating.
grad: Gradient with respect to the output of the `rgb_to_hsv` op.