decode_avif#

torchcodec.decoders.decode_avif(source: str | Path | bytes | Tensor, *, mode: Literal['UNCHANGED', 'GRAY', 'GRAY_ALPHA', 'RGB', 'RGB_ALPHA'] | ImageReadMode = 'RGB', output_dtype: dtype | Literal['auto'] = torch.uint8, num_threads: int = 1) → Tensor[source]#

Decode an AVIF image into a [N]CHW tensor.

The output shape is (C, H, W) for a still AVIF and (N, C, H, W) for an animated one (N frames).

Example

from torchcodec.decoders import decode_avif

img = decode_avif("image.avif")

Parameters:

source (str, pathlib.Path, bytes, or torch.Tensor) – The encoded AVIF data: a path (str or pathlib.Path), a bytes object, or a 1-D uint8 torch.Tensor of the raw encoded bytes.
mode (str or ImageReadMode, optional) – Desired color mode of the output image. Can be one of "UNCHANGED", "GRAY", "GRAY_ALPHA", "RGB", or "RGB_ALPHA". Default is "RGB".
output_dtype (torch.dtype or "auto", optional) – desired dtype of the output image tensor. Accepted values are torch.uint8 (default), torch.uint16, and "auto". AVIF can store more than 8 bits per channel (e.g. 10- or 12-bit sources). torch.uint16 always scales the samples up to fill the full 16-bit range [0, 65535] (8-bit 0-255, 10-bit 0-1023 and 12-bit 0-4095 sources are all upscaled), while torch.uint8 scales higher-bit sources down. "auto" yields uint8 for 8-bit AVIFs and uint16 (again filling [0, 65535]) for higher-bit ones.
num_threads (int, optional) – Number of threads to use for decoding, directly passed to libavif. Default is 1.

Returns:

The decoded image, of shape (C, H, W) (still) or (N, C, H, W) (animated).

Return type:

torch.Tensor

Examples using decode_avif:

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