Skip to main content

Auton Lab TA1 primitives

Project description

The Auton Lab TA1 primitives

This repository contains additional Auton Lab TA1 primitives for the D3M program.

  1. Iterative Labeling - Blackbox based iterative labeling for semi-supervised learning
  2. Video featurizer - Video Feature Extraction for Action Classification With 3D ResNet

Installation

To install primitives, run:

pip install -U autonbox

Video featurizer requires a static file, for pre-trained model weights. To download it, run:

mkdir -p /tmp/cmu/pretrained_files
python3 -m d3m index download -o /tmp/cmu/pretrained_files # requires d3m core

Video featurizer

The primitive outputs a data frame of size N x M, where N is the number of videos and M is 2024 features of type float.

It supports running on GPUs.

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

autonbox-0.2.2.tar.gz (18.9 kB view details)

Uploaded Source

Built Distribution

autonbox-0.2.2-py3-none-any.whl (27.3 kB view details)

Uploaded Python 3

File details

Details for the file autonbox-0.2.2.tar.gz.

File metadata

  • Download URL: autonbox-0.2.2.tar.gz
  • Upload date:
  • Size: 18.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.15

File hashes

Hashes for autonbox-0.2.2.tar.gz
Algorithm Hash digest
SHA256 2402d8b6040ed340beab4f375c98dd304357c2d662e883ce03dd2ac567f7f544
MD5 f9f4194ee907e7b10c12773e797cb27c
BLAKE2b-256 baabec335c14fed05732ea407bdd3cb8e5ec3d45541d6dbb89eb38be3faf2620

See more details on using hashes here.

File details

Details for the file autonbox-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: autonbox-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 27.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.15

File hashes

Hashes for autonbox-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8f943143066ee626fc31b43d5a744c7b2bdf932df090291a60f694f07a1fa37a
MD5 82efcde89488175a323def99d7d1b9b2
BLAKE2b-256 7f0abd72a5861f6fdadfc00c4ba6e5e6e657313580cc27435641006072580d75

See more details on using hashes here.

Supported by

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