Bump torchcodec from 0.7.0 to 0.16.0 in /apps/agent

[dependabot]

Bumps torchcodec from 0.7.0 to 0.16.0.

Release notes

Sourced from torchcodec's releases.

TorchCodec 0.16 - Image decoding and encoding

TorchCodec 0.16 is out! It is compatible with torch >= 2.11. The headline feature of this release is image decoding and encoding: TorchCodec now natively decodes and encodes JPEG (CPU and CUDA), PNG, WebP, GIF, AVIF and HEIC. These image decoders and encoders replace their torchvision counterparts, which are now deprecated.

TorchCodec is the recommended way to decode and encode images in the PyTorch ecosystem. If you are coming from torchvision, we wrote a migration guide

Image decoding

TorchCodec exposes one entry-point per format, plus a generic decode_image() that automatically detects the format. The API is largely backward-compatible with TorchVision:

from torchcodec.decoders import decode_image, decode_jpeg, decode_png
img = decode_image("image.jpg")  # CHW uint8 tensor, format auto-detected
img = decode_image("image.avif")
img = decode_image("image.heic")
Or use the format-specific decoders for format-specific options
img = decode_jpeg("image.jpg", device="cuda")

Sources can be a path (str or pathlib.Path), bytes, or a 1D uint8 tensor of encoded bytes:

img = decode_image(open("image.png", "rb").read())
img = decode_image(torch.frombuffer(encoded_bytes, dtype=torch.uint8))

Animated and multi-image formats (WebP, GIF, AVIF, HEIC) decode into an (N, C, H, W) tensor:

from torchcodec.decoders import decode_gif
frames = decode_gif("animated.gif")  # (N, C, H, W)

JPEG decoding is also supported on CUDA, through nvJPEG. For CUDA, prefer passing a batch of sources: the whole batch is decoded in a single nvJPEG call, which is much faster than decoding images one at a time.

from torchcodec.decoders import decode_jpeg
imgs = decode_jpeg(["a.jpg", "b.jpg", "c.jpg"], device="cuda")  # list of CUDA tensors

Read more in our image decoding tutorial

Image encoding

Image encoders follow the same class-based design as our video and audio encoders: build the encoder from a CHW uint8 tensor, then choose where the encoded bytes go: a file, a file-like object, or a tensor.

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Commits

• ce046a8 Release 0.16 (#1622)
• d68f9d6 Add migration guide from torchvision to torchcodec (#1621)
• 4cf853d Add tests on FFmpeg 9 (#1618)
• 95434fc Add CUDA jpeg decoding to benchmark (#1620)
• 276f9c9 Fix AudioDecoder seeks on MPEG-PS files (#1619)
• 574d78a AudioDecoder: fix chunk decoding when split is exactly at half a sample bound...
• 088c229 Audio resampler postroll fix (#1615)
• de0340f Fix audio resampling: decoding in chunks should return identical samples to d...
• 1f36e84 Let Blocks output the raw YUV frames (#1608)
• a87fcd5 Build against FFmpeg 9 (#1607)
• Additional commits viewable in compare view

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