Note
This is a Hugging Face dataset. Learn how to load datasets from the Hub in the Hugging Face integration docs.
Dataset Card for Elderly Action Recognition Challenge#
This dataset is a modified version of the GMNCSA24 dataset, tailored for video classification tasks focusing on Activities of Daily Living (ADL) and fall detection in older populations. It is designed to support research in human activity recognition and safety monitoring. The dataset includes annotated video samples for various ADL and fall scenarios, making it ideal for training and evaluating machine learning models in healthcare and assistive technology applications.
This is a FiftyOne dataset with 335 samples.
Installation#
If you haven’t already, install FiftyOne:
pip install -U fiftyone
Usage#
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/GMNCSA24-FO")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details#
Dataset Description#
Original Dataset: GMNCSA24 Repo
Curated by: Paula Ramos
Language(s): en
License: [MIT License]
Dataset Sources [optional]#
Repository: [https://github.com/ekramalam/GMDCSA24-A-Dataset-for-Human-Fall-Detection-in-Videos]
Paper [optional]: [E. Alam, A. Sufian, P. Dutta, M. Leo, I. A. Hameed “GMDCSA24: A Dataset for Human Fall Detection in Videos”, Data in Brief (communicated)]
Blog [optional]: Journey with FiftyOn: Part III
Notebook: fiftyOne Example
Readme_DataPrepartation Awesome_FiftyOne