tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, dct_method=None, name=None)

tf.image.decode_jpeg(contents, channels=None, ratio=None, fancy_upscaling=None, try_recover_truncated=None, acceptable_fraction=None, dct_method=None, name=None)

See the guide: Images > Encoding and Decoding

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:

• contents: A Tensor of type string. 0-D. The JPEG-encoded image.
• channels: An optional int. Defaults to 0. Number of color channels for the decoded image.
• ratio: An optional int. Defaults to 1. Downscaling ratio.
• fancy_upscaling: An optional bool. Defaults to True. If true use a slower but nicer upscaling of the chroma planes (yuv420/422 only).
• try_recover_truncated: An optional bool. Defaults to False. If true try to recover an image from truncated input.
• acceptable_fraction: An optional float. Defaults to 1. The minimum required fraction of lines before a truncated input is accepted.
• dct_method: An optional string. Defaults to "". string specifying a hint about the algorithm used for decompression. Defaults to "" which maps to a system-specific default. Currently valid values are ["INTEGER_FAST", "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal jpeg library changes to a version that does not have that specific option.)
• name: A name for the operation (optional).

Returns:

A Tensor of type uint8. 3-D with shape [height, width, channels]..

Defined in tensorflow/python/ops/gen_image_ops.py.