SHIFT15M: multiobjective large-scale fashion dataset with distributional shifts

Related tags

Deep Learningmachine-learningresearchdeep-learningfashiondatasetdatasetscovariate-shiftfill-in-the-blankdataset-shiftsdistributional-shifttarget-shiftset-matchingfill-in-the-n-blank
Overview

License: MIT Python GitHub code size in bytes Downloads GitHub Workflow Status PyPI version GitHub issues GitHub commit activity GitHub last commit arXiv

[arXiv]

The main motivation of the SHIFT15M project is to provide a dataset that contains natural dataset shifts collected from a web service IQON, which was actually in operation for a decade. In addition, the SHIFT15M dataset has several types of dataset shifts, allowing us to evaluate the robustness of the model to different types of shifts (e.g., covariate shift and target shift).

We provide the Datasheet for SHIFT15M. This datasheet is based on the Datasheets for Datasets [1] template.

System Python 3.6 Python 3.7 Python 3.8
Linux CPU
Linux GPU
Windows CPU / GPU Status Currently Unavailable Status Currently Unavailable Status Currently Unavailable
Mac OS CPU

SHIFT15M is a large-scale dataset based on approximately 15 million items accumulated by the fashion search service IQON.

Installation

From PyPi

$ pip install shift15m

From source

$ git clone https://github.com/st-tech/zozo-shift15m.git
$ cd zozo-shift15m
$ poetry build
$ pip install dist/shift15m-xxxx-py3-none-any.whl

Download SHIFT15M dataset

Use Dataset class

You can download SHIFT15M dataset as follows:

from shift15.datasets import NumLikesRegression

dataset = NumLikesRegression(root="./data", download=True)

Download directly by using download scripts

Please download the dataset as follows:

$ bash scripts/download_all.sh

To avoid downloading the test dataset for set matching (80GB), which is not required in training, you can use the following script.

$ bash scripts/download_all_wo_set_testdata.sh

Tasks

The following tasks are now available:

Tasks Task type Shift type # of input dim # of output dim
NumLikesRegression regression target shift (N, 25) (N, 1)
SumPricesRegression regression covariate shift, target shift (N, 1) (N, 1)
ItemPriceRegression regression target shift (N, 4096) (N, 1)
ItemCategoryClassification classification target shift (N, 4096) (N, 7)
Set2SetMatching set-to-set matching covariate shift (N, 4096)x(M, 4096) (1)

Benchmarks

As templates for numerical experiments on the SHIFT15M dataset, we have published experimental results for each task with several models.

Original Dataset Structure

The original dataset is maintained in json format, and a row consists of the following:

{
  "user":{"user_id":"xxxx", "fav_brand_ids":"xxxx,xx,..."},
  "like_num":"xx",
  "set_id":"xxx",
  "items":[
    {"price":"xxxx","item_id":"xxxxxx","category_id1":"xx","category_id2":"xxxxx"},
    ...
  ],
  "publish_date":"yyyy-mm-dd"
}

Contributing

To learn more about making a contribution to SHIFT15M, please see the following materials:

License

The dataset itself is provided under a CC BY-NC 4.0 license. On the other hand, the software in this repository is provided under the MIT license.

Dataset metadata

The following table is necessary for this dataset to be indexed by search engines such as Google Dataset Search.

property value
name SHIFT15M Dataset
alternateName SHIFT15M
alternateName shift15m-dataset
url
sameAs https://github.com/st-tech/zozo-shift15m
description SHIFT15M is a multi-objective, multi-domain dataset which includes multiple dataset shifts.
provider
property value
name ZOZO Research
sameAs https://ja.wikipedia.org/wiki/ZOZO
license
property value
name CC BY-NC 4.0
url

Citation

@misc{Kimura_SHIFT15M_Multiobjective_LargeScale_2021,
author = {Kimura, Masanari and Nakamura, Takuma and Saito, Yuki},
month = {8},
title = {SHIFT15M: Multiobjective Large-Scale Fashion Dataset with Distributional Shifts},
year = {2021}
}

Errata

No errata are currently available.

References

  • [1] Gebru, Timnit, et al. "Datasheets for datasets." arXiv preprint arXiv:1803.09010 (2018).
Comments
Releases(v0.2.0)

  • v0.2.0(Sep 20, 2022)

    • add tags info as follows:
    {
  "user":{"user_id":"xxxx", "fav_brand_ids":"xxxx,xx,..."},
  "like_num":"xx",
  "set_id":"xxx",
  "items":[
    {"price":"xxxx","item_id":"xxxxxx","category_id1":"xx","category_id2":"xxxxx"},
    ...
  ],
  "publish_date":"yyyy-mm-dd",
  "tags": "tag_a, tag_b, tag_c, ..."
}
    • add superset matching benchmark
    • fix a label creation bug on set matching with multiple splits
    Source code(tar.gz)
    Source code(zip)

  • v.0.1.2(Nov 24, 2021)

  • v.0.1.1(Sep 6, 2021)

Owner
ZOZO, Inc.
ZOZO, Inc.
GitHub Repository
A Python package for time series augmentation

tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn

Arundo Analytics 278 Jan 01, 2023
Sentinel-1 vessel detection model used in the xView3 challenge

sar_vessel_detect Code for the AI2 Skylight team's submission in the xView3 competition (https://iuu.xview.us) for vessel detection in Sentinel-1 SAR

AI2 6 Sep 10, 2022
GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich

Course Description The programming language Julia is being more and more adopted in High Performance Computing (HPC) due to its unique way to combine

Samuel Omlin 192 Jan 03, 2023
Doge-Prediction - Coding Club prediction ig

Doge-Prediction Coding Club prediction ig Basically: Create an application that

1 Jan 10, 2022
python library for invisible image watermark (blind image watermark)

invisible-watermark invisible-watermark is a python library and command line tool for creating invisible watermark over image.(aka. blink image waterm

Shield Mountain 572 Jan 07, 2023
Benchmark for evaluating open-ended generation

OpenMEVA Contributed by Jian Guan, Zhexin Zhang. Thank Jiaxin Wen for DeBugging. OpenMEVA is a benchmark for evaluating open-ended story generation me

25 Nov 15, 2022
Voice Conversion Using Speech-to-Speech Neuro-Style Transfer

This repo contains the official implementation of the VAE-GAN from the INTERSPEECH 2020 paper Voice Conversion Using Speech-to-Speech Neuro-Style Transfer.

Ehab AlBadawy 93 Jan 05, 2023
Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

Jingyun Liang 159 Dec 30, 2022
Official PyTorch Implementation of Mask-aware IoU and maYOLACT Detector [BMVC2021]

The official implementation of Mask-aware IoU and maYOLACT detector. Our implementation is based on mmdetection. Mask-aware IoU for Anchor Assignment

Kemal Oksuz 46 Sep 29, 2022
Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image (ICCV 2021)

Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color

75 Dec 02, 2022
Streaming over lightweight data transformations

Description Data augmentation libarary for Deep Learning, which supports images, segmentation masks, labels and keypoints. Furthermore, SOLT is fast a

Research Unit of Medical Imaging, Physics and Technology 256 Jan 08, 2023
Tensorflow implementation of Character-Aware Neural Language Models.

Character-Aware Neural Language Models Tensorflow implementation of Character-Aware Neural Language Models. The original code of author can be found h

Taehoon Kim 751 Dec 26, 2022
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.

#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p

Andrej 5.3k Jan 07, 2023
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).

Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em

Benedek Rozemberczki 69 Sep 22, 2022
Reinforcement learning library in JAX.

Reinforcement learning library in JAX.

Yicheng Luo 96 Oct 30, 2022
This repository contains the code for the paper Neural RGB-D Surface Reconstruction

Neural RGB-D Surface Reconstruction Paper | Project Page | Video Neural RGB-D Surface Reconstruction Dejan Azinović, Ricardo Martin-Brualla, Dan B Gol

Dejan 406 Jan 04, 2023
CHERRY is a python library for predicting the interactions between viral and prokaryotic genomes

CHERRY is a python library for predicting the interactions between viral and prokaryotic genomes. CHERRY is based on a deep learning model, which consists of a graph convolutional encoder and a link

Kenneth Shang 12 Dec 15, 2022
🛰️ List of earth observation companies and job sites

Earth Observation Companies & Jobs source Portals & Jobs Geospatial Geospatial jobs newsletter: ~biweekly newsletter with geospatial jobs by Ali Ahmad

Dahn 64 Dec 27, 2022
Custom implementation of Corrleation Module

Pytorch Correlation module this is a custom C++/Cuda implementation of Correlation module, used e.g. in FlowNetC This tutorial was used as a basis for

Clément Pinard 361 Dec 12, 2022
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks

Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope

Amirsina Torfi 1.7k Dec 18, 2022