tf.io.decode_jpeg

Decode a JPEG-encoded image to a uint8 tensor.

tf.io.decode_jpeg(
    contents: _atypes.TensorFuzzingAnnotation[_atypes.String],
    channels: int = 0,
    ratio: int = 1,
    fancy_upscaling: bool = True,
    try_recover_truncated: bool = False,
    acceptable_fraction: float = 1,
    dct_method: str = '',
    name=None
) -> _atypes.TensorFuzzingAnnotation[_atypes.UInt8]

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.

This op also supports decoding PNGs and non-animated GIFs since the interface is the same, though it is cleaner to use tf.io.decode_image.

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).

A Tensor of type uint8.