---
license: mit
task_categories:
- image-generation
language:
- en
size_categories:
- n<1K
dataset_info:
  features:
  - name: image
    dtype: image
  - name: text
    dtype: string
  - name: model
    dtype: string
  - name: category
    dtype: string
  - name: sub_category
    dtype: string
  splits:
  - name: train
    num_bytes: 18397027.0
    num_examples: 16
  download_size: 18293528
  dataset_size: 18397027.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Diffusion Studio Generations

This dataset contains 16 high-quality AI-generated images created using various diffusion models. Each image is accompanied by detailed prompts and model information, showcasing different styles and techniques in AI image generation.

## Dataset Description

- **Curated by:** shodiBoy
- **Language:** English
- **License:** MIT
- **Size:** 16 images
- **Task:** Image Generation
- **Repository:** diffusion_studio_generations

## Dataset Structure

Each entry in the dataset contains:

- `id`: Unique identifier for the entry
- `prompt`: Detailed text prompt used to generate the image
- `image`: Path to the generated image
- `model`: AI model used to generate the image
- `category`: Main category of the image (Sports, Fashion, Cinematic)
- `sub_category`: More specific classification

## Models Used

- **flux-1-1-pro**: Black Forest Labs FLUX.1 Pro model
- **GPT-IMAGE-1**: OpenAI's GPT Image Generation model
- **RECRAFT-V3**: Recraft V3 model

## Image Categories

The dataset includes various types of images:
- **Sports**: Alpine/skiing scenes, basketball action shots
- **Fashion**: Portraits, avant-garde fashion photography
- **Cinematic**: Sci-fi scenes, urban photography, vintage aesthetics

## Usage

This dataset can be used for:
- Training image generation models
- Prompt engineering research
- Model comparison studies
- Computer vision research
- Style analysis and categorization

## File Structure

```
dataset/
├── images/
│   └── chosen/      # Generated images (16 files)
├── metadata/        # Individual JSON files for each image
├── dataset.json     # Main dataset file with all entries
├── dataset_info.json # Dataset metadata
└── README.md        # This file
```

## Citation

If you use this dataset in your research, please cite:

```bibtex
@dataset{diffusion_studio_generations_2024,
  author = {shodiBoy},
  title = {Diffusion Studio Generations},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/shodiBoy/diffusion_studio_generations}
}
```