--- license: cc-by-4.0 dataset_info: features: - name: image dtype: Image - name: id dtype: string - name: original_prompt dtype: string - name: positive_prompt dtype: string - name: negative_prompt dtype: string - name: model dtype: string - name: nsfw dtype: string - name: url_real_image dtype: string - name: filepath dtype: string - name: aspect_ratio feature: - dtype: int64 - dtype: int64 dtype: Sequence splits: - name: train num_bytes: 445446704787.43 num_examples: 992655 download_size: 223034360161 dataset_size: 445926712527.43 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