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Saturate when converting image between datatypes in adjust_jpeg_quality.

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PiperOrigin-RevId: 308677540
Change-Id: Ibd1f2cfebb11fce2dcce8cafb1c7e191ce8ae368
This commit is contained in:
A. Unique TensorFlower 2020-04-27 12:41:38 -07:00 committed by TensorFlower Gardener
parent 40d89f69e1
commit 5cac87ab5a
1 changed files with 6 additions and 6 deletions
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12
tensorflow/python/ops/image_ops_impl.py
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@ -2308,10 +2308,10 @@ def adjust_jpeg_quality(image, jpeg_quality, name=None):
... [10.0, 11.0, 12.0]]]
>>> tf.image.adjust_jpeg_quality(x, 75)
<tf.Tensor: shape=(2, 2, 3), dtype=float32, numpy=
array([[[1. , 1. , 1. ],
[0.9960785 , 0.9960785 , 0.9960785 ]],
[[0.98823535, 0.98823535, 0.98823535],
[0.98823535, 0.98823535, 0.98823535]]], dtype=float32)>
array([[[1., 1., 1.],
[1., 1., 1.]],
[[1., 1., 1.],
[1., 1., 1.]]], dtype=float32)>
Args:
image: 3D image. The size of the last dimension must be None, 1 or 3.
@ -2330,14 +2330,14 @@ def adjust_jpeg_quality(image, jpeg_quality, name=None):
channels = image.shape.as_list()[-1]
# Remember original dtype to so we can convert back if needed
orig_dtype = image.dtype
image = convert_image_dtype(image, dtypes.uint8)
image = convert_image_dtype(image, dtypes.uint8, saturate=True)
if not _is_tensor(jpeg_quality):
# If jpeg_quality is a int (not tensor).
jpeg_quality = ops.convert_to_tensor(jpeg_quality, dtype=dtypes.int32)
image = gen_image_ops.encode_jpeg_variable_quality(image, jpeg_quality)
image = gen_image_ops.decode_jpeg(image, channels=channels)
return convert_image_dtype(image, orig_dtype)
return convert_image_dtype(image, orig_dtype, saturate=True)
@tf_export('image.random_saturation')