This project aims to train a model to recognise human activities (like walking, standing, or sitting) based on accelerometer and gyroscope data collected with a smartphone.
Project description
Human Activity Recognition Using Smartphones
This project aims to train a model to recognise human activities (like walking, standing, or sitting) based on accelerometer and gyroscope data collected with a smartphone.
For installation and usage instructions, please refer to our documentation.
Dataset
This package use the "Human Activity Recognition Using Smartphones Data Set". For more information about it, please refer to the original publication.
Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.
License
This repository is made publicly available under the MIT License.
Authors
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file rrgp-1.0.5.tar.gz.
File metadata
- Download URL: rrgp-1.0.5.tar.gz
- Upload date:
- Size: 141.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/3.8.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
df3fc701ed7f09a13d02784c1b4f03ef53ba20237a426b40ac0e107ccfd49891
|
|
| MD5 |
8e68a1b34b9f30ed41579d04b65da25c
|
|
| BLAKE2b-256 |
ef79518b9606e299e3332bbca1af4c2e6d1f76e7b0b1cdeab8a7956bf5edf7f8
|
