decode_png

torchvision.io.decode_png(input: Tensor, mode: ImageReadMode = ImageReadMode.UNCHANGED, apply_exif_orientation: bool = False) → Tensor

[DEPRECATED] Use TorchCodec instead.

Decodes a PNG image into a 3 dimensional RGB or grayscale Tensor.

Warning

The image decoding and encoding capabilities of TorchVision are deprecated since torchvision 0.29 and will be removed in a future release. They are superseded by the more complete decoders and encoders of TorchCodec (from torchcodec 0.16). Please see this migration guide on how to migrate your code.

The values of the output tensor are in uint8 in [0, 255] for most cases. If the image is a 16-bit png, then the output tensor is uint16 in [0, 65535] (supported from torchvision 0.21). Since uint16 support is limited in pytorch, we recommend calling torchvision.transforms.v2.functional.to_dtype() with scale=True after this function to convert the decoded image into a uint8 or float tensor.

Parameters:

• input (Tensor[1]) – a one dimensional uint8 tensor containing the raw bytes of the PNG image.

• mode (str or ImageReadMode) – The mode to convert the image to, e.g. “RGB”. Default is “UNCHANGED”. See ImageReadMode for available modes.

• apply_exif_orientation (bool) – apply EXIF orientation transformation to the output tensor. Default: False.

Returns:

output (Tensor[image_channels, image_height, image_width])