README.md

---
annotations_creators: []
language: en
size_categories:
- n<1K
task_categories:
- video-classification
task_ids: []
pretty_name: 2025.01.16.10.33.04
tags:
- fiftyone
- video
dataset_summary: >




  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 335
  samples.


  ## Installation


  If you haven't already, install FiftyOne:


  ```bash

  pip install -U fiftyone

  ```


  ## Usage


  ```python

  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)

  ```
license: mit
---

# 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.


![image/png](https://cdn-uploads.huggingface.co/production/uploads/63f516f6b51da4d61da6bca8/YsJoRwVLM3lqmzuyyZILR.png)



This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 335 samples.

## Installation

If you haven't already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
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

<!-- Provide a longer summary of what this dataset is. -->


- **Original Dataset:** [GMNCSA24 Repo](https://github.com/ekramalam/GMDCSA24-A-Dataset-for-Human-Fall-Detection-in-Videos/blob/master/LICENSE)
- **Curated by:** [Paula Ramos](https://huggingface.co/pjramg)
- **Language(s):** en
- **License:** [MIT License]

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **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](https://medium.com/@paularamos_phd/journey-into-visual-ai-exploring-fiftyone-together-part-iii-preparing-a-computer-vision-e5709684ee34)
- **Notebook:** [fiftyOne Example](https://github.com/voxel51/fiftyone-examples/blob/master/examples/elderly_action_recognition.ipynb)
- **Readme_DataPrepartation** [Awesome_FiftyOne](https://github.com/paularamo/awesome-fiftyone/tree/main/ear-challenge)

## Uses

[Elderly Action Recognition Challenge](https://voxel51.com/computer-vision-events/elderly-action-recognition-challenge-wacv-2025/)