Decode and Crop a JPEG-encoded image to a uint8 tensor.
tf.io.decode_and_crop_jpeg(
contents: Annotated[Any, _atypes.String],
crop_window: Annotated[Any, _atypes.Int32],
channels: int = 0,
ratio: int = 1,
fancy_upscaling: bool = True,
try_recover_truncated: bool = False,
acceptable_fraction: float = 1,
dct_method: str = '',
name=None
) -> Annotated[Any, _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.
It is equivalent to a combination of decode and crop, but much faster by only decoding partial jpeg image.
Args |
|---|
contents
Tensor of type string. 0-D. The JPEG-encoded image.
crop_window
Tensor of type int32.
1-D. The crop window: [crop_y, crop_x, crop_height, crop_width].
channels
int. Defaults to 0.
Number of color channels for the decoded image.
ratio
int. Defaults to 1. Downscaling ratio.
fancy_upscaling
bool. Defaults to True.
If true use a slower but nicer upscaling of the
chroma planes (yuv420/422 only).
try_recover_truncated
bool. Defaults to False.
If true try to recover an image from truncated input.
acceptable_fraction
float. Defaults to 1.
The minimum required fraction of lines before a truncated
input is accepted.
dct_method
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
Returns | |
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A Tensor of type uint8.
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