Skip to main content

Revised splits for Office31 domain adaptation experiments

Project description

Splits for Office31 domain adaptation tasks

This repository contains the revised protocol for creating Office31 splits for few shot domain adaptation.

Contrary to the usual splits, we define an independent test split here (split using a hardcoded seed), and let the train-val split vary according to a user-defined random seed.


pip install office31


Getting the splits is a simple as:

from office31 import office31

train, val, test = office31(
    source_name = "webcam",
    target_name = "amazon",
    image_resize=(240, 240),
    group_in_out=True, # groups data: ((img_s, img_t), (lbl_s, _lbl_t))
    office_path = None, #automatically downloads to "~/data"

The function automatically downloads and unpacks the data if necessary. It then creates the splits using the Dataset Ops library. Depending on your choice of machine learning library, the dataset can be converted to Tensorflow or PyTorch (assuming either is pre-installed) using Dataset Ops.

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

office31-0.1.3.tar.gz (3.8 kB view hashes)

Uploaded source

Built Distribution

office31-0.1.3-py3-none-any.whl (5.3 kB view hashes)

Uploaded py3

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