https://github.com/long-gong/datasets-e2h

Datasets Euclidean to Hamming Conversion
https://github.com/long-gong/datasets-e2h

cpp datasets eigen3 euclidean2hamming hdf5 simhash

Last synced: 11 months ago
JSON representation

Datasets Euclidean to Hamming Conversion

• Host: GitHub
• URL: https://github.com/long-gong/datasets-e2h
• Owner: long-gong
• Created: 2019-12-23T21:20:56.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-08-25T20:21:03.000Z (almost 6 years ago)
• Last Synced: 2025-03-09T08:41:00.855Z (over 1 year ago)
• Topics: cpp, datasets, eigen3, euclidean2hamming, hdf5, simhash
• Language: C++
• Homepage: https://github.com/long-gong/datasets
• Size: 186 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# E2H: Euclidean Datasets to Hamming Datasets

[![Build Status](https://travis-ci.org/long-gong/datasets-E2H.svg?branch=master)](https://travis-ci.org/long-gong/datasets-E2H)

E2H implements the preprocessing tool used in our recent paper, 

"Long Gong, Huayi Wang, Mitsunori Ogihara, and Jun Xu. 2020. IDEC: indexable distance estimating codes for approximate nearest neighbor search. Proc. VLDB Endow. 13, 9 (May 2020), 1483–1497. DOI:https://doi.org/10.14778/3397230.3397243." 

E2H is used to convert Euclidean datasets to Hamming datasets. 

## Install Dependecies

```bash

./install_deps.sh

```

## Usage

```bash

make 

./ m 

```

``: audio|glove|mnist|enron|sift1m|gist1m|sift1b|gist80m 

`m`: dimension for Hamming data (suggested value: rounding original dim to multiples of 64)