---
license: cc-by-4.0
dataset_info:
  features:
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 445446704787.43
    num_examples: 992655
  download_size: 231662266092
  dataset_size: 445446704787.43
task_categories:
- image-classification
---

# ELSA - Multimedia use case

![elsa_slow.gif](https://cdn-uploads.huggingface.co/production/uploads/6380ccd084022715e0d49d4e/k_Zs325tahEteMx_Df1fW.gif)

**ELSA Multimedia is a large collection of Deep Fake images, generated using diffusion models**

### Dataset Summary

This dataset was developed as part of the EU project ELSA. Specifically for the Multimedia use-case.
Official webpage: https://benchmarks.elsa-ai.eu/
This dataset aims to develop effective solutions for detecting and mitigating the spread of deep fake images in multimedia content. Deep fake images, which are highly realistic and deceptive manipulations, pose significant risks to privacy, security, and trust in digital media. This dataset can be used to train robust and accurate models that can identify and flag instances of deep fake images.

```python
from datasets import load_dataset
elsa_data = load_dataset("rs9000/ELSA1M_track1")
```

## Dataset Structure

Each parquet file contains nearly 1k images and a JSON file with metadata.

The Metadata for generated images are:

- ID: Laion image ID
- original_prompt: Laion Prompt
- positive_prompt: positive prompt used for image generation
- negative_prompt: negative prompt used for image generation
- model: model used for the image generation
- nsfw: nsfw tag from Laion
- url_real_image: Url of the real image associated to the same prompt
- filepath: filepath of the fake image
- aspect_ratio: aspect ratio of the generated image


### Dataset Curators

- Leonardo (rosario.dicarlo.ext@leonardo.com)
- UNIMORE