| | --- |
| | 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} |
| | } |
| | ``` |
