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### `tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, name=None)` {#decode_jpeg}
Decode a JPEG-encoded image to a uint8 tensor.
The attr `channels` indicates the desired number of color channels for the
decoded image.
Accepted values are:
* 0: Use the number of channels in the JPEG-encoded image.
* 1: output a grayscale image.
* 3: output an RGB image.
If needed, the JPEG-encoded image is transformed to match the requested number
of color channels.
The attr `ratio` allows downscaling the image by an integer factor during
decoding. Allowed values are: 1, 2, 4, and 8. This is much faster than
downscaling the image later.
##### Args:
* <b>`contents`</b>: A `Tensor` of type `string`. 0-D. The JPEG-encoded image.
* <b>`channels`</b>: An optional `int`. Defaults to `0`.
Number of color channels for the decoded image.
* <b>`ratio`</b>: An optional `int`. Defaults to `1`. Downscaling ratio.
* <b>`fancy_upscaling`</b>: An optional `bool`. Defaults to `True`.
If true use a slower but nicer upscaling of the
chroma planes (yuv420/422 only).
* <b>`try_recover_truncated`</b>: An optional `bool`. Defaults to `False`.
If true try to recover an image from truncated input.
* <b>`acceptable_fraction`</b>: An optional `float`. Defaults to `1`.
The minimum required fraction of lines before a truncated
input is accepted.
* <b>`name`</b>: A name for the operation (optional).
##### Returns:
A `Tensor` of type `uint8`. 3-D with shape `[height, width, channels]`..
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