Skip to main content

Multimodal PyTorch dataset library

Project description

banner

rbyte provides a PyTorch Dataset with tensorclass samples built from multimodal data

Installation

uv add rbyte [--extra <EXTRA>]

See pyproject.toml for available extras.

Examples

  1. Install required tools:
  1. Clone:
git clone https://github.com/yaak-ai/rbyte
  1. Run:
cd rbyte
just notebook examples/nuscenes_mcap.ipynb

Development

  1. Install required tools:
  1. Clone:
git clone https://github.com/yaak-ai/rbyte
  1. Run:
cd rbyte
just setup

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rbyte-0.25.0.tar.gz (31.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

rbyte-0.25.0-py3-none-any.whl (49.6 kB view details)

Uploaded Python 3

File details

Details for the file rbyte-0.25.0.tar.gz.

File metadata

  • Download URL: rbyte-0.25.0.tar.gz
  • Upload date:
  • Size: 31.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for rbyte-0.25.0.tar.gz
Algorithm Hash digest
SHA256 b362c52e5854d56e6ce614f2f7e4114537937ee9e4f7891640c2c0b68d0a4d86
MD5 031743ddffb5fcd9066b099e970d7d97
BLAKE2b-256 682b17a3acf8974d0669df91d9f92d98f695d1e07edeb8a1a0d1e101fd6d177e

See more details on using hashes here.

Provenance

The following attestation bundles were made for rbyte-0.25.0.tar.gz:

Publisher: release.yaml on yaak-ai/rbyte

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file rbyte-0.25.0-py3-none-any.whl.

File metadata

  • Download URL: rbyte-0.25.0-py3-none-any.whl
  • Upload date:
  • Size: 49.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for rbyte-0.25.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a7bb9a09a951957461eb61496d63978ed8d79045502019760a182cec25fd8421
MD5 d25ae586e8d3ecb1ffb5b7803d909974
BLAKE2b-256 1267d298dfc666ef235faf924a11eff1d57174451c4a5e2a5ed2bb85c32094c9

See more details on using hashes here.

Provenance

The following attestation bundles were made for rbyte-0.25.0-py3-none-any.whl:

Publisher: release.yaml on yaak-ai/rbyte

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page