| # Magic Bench: A Comprehensive Text-to-Image Generation Evaluation Dataset | |
| ## 📖 Overview | |
| Magic Bench is a comprehensive evaluation dataset designed for text-to-image generation models. It contains 377 carefully curated prompts with detailed annotations across multiple dimensions, providing both Chinese and English versions for cross-lingual evaluation. | |
| ## 🎯 Dataset Features | |
| - **377 evaluation prompts** covering diverse scenarios | |
| - **Bilingual support**: Both Chinese and English prompts | |
| - **Multi-dimensional annotations**: 9 different evaluation dimensions | |
| - **Comprehensive coverage**: Aesthetic design and artistic photography scenarios | |
| ## 📊 Dataset Structure | |
| The dataset includes the following fields: | |
| | Field | Description | | |
| |-------|-------------| | |
| | `prompt_text_cn`| Chinese version of the prompt | | |
| | `prompt_text_en`| English version of the prompt | | |
| | `Application Scenario`| The application context | | |
| | `Expression Form`| Form of expression annotations | | |
| | `Element Composition`| Element combination patterns | | |
| | `Entity Description`| Entity description types | | |
| ## 🏷️ Annotation Dimensions | |
| ### 1. Application Scenario | |
| - **Aesthetic design**: Logo design, character design, product design, etc. | |
| - **Art** : Photography, artistic creation, etc. | |
| - **Entertainment** : Entertainment and personalized content | |
| - **Film** : Film and storytelling scenarios | |
| - **Functional design** : Efficiency and functional design | |
| ### 2. Expression Form | |
| - **Pronoun Reference**: Contains pronoun references | |
| - **Negation**: Contains negative expressions | |
| - **Consistency**: Requires consistent elements | |
| ### 3. Element Combination | |
| - **Anti-Realism**: Anti-realistic combinations | |
| - **Multi-Entity Feature Matching**: Complex multi-entity combinations | |
| - **Layout & Typography**: Specific layout requirements | |
| ### 4. Entity Description | |
| - **Attribute** : Attribute descriptions | |
| - **Relation** : Relationship descriptions | |
| - **Action/State** : Action or state descriptions | |
| - **Quantity** : Quantity specifications | |
| ## 📁 Files | |
| - `magic_bench_dataset.csv`: Complete dataset | |
| - `magic_bench_chinese.csv`: Chinese prompts with labels | |
| - `magic_bench_english.csv`: English prompts with labels | |
| ## 🚀 Usage | |
| ```python | |
| import pandas as pd | |
| # Load the complete dataset | |
| df = pd.read_csv('magic_bench_dataset.csv') | |
| # Load Chinese version | |
| df_cn = pd.read_csv('magic_bench_chinese.csv') | |
| # Load English version | |
| df_en = pd.read_csv('magic_bench_english.csv') | |
| ``` | |
| ## 📈 Statistics | |
| - **Total prompts**: 377 | |
| - **Aesthetic design prompts**: 95 (25.2%) | |
| - **Art prompts**: 80 (21.2%) | |
| - **Prompts with style specifications**: 241 (63.9%) | |
| - **Prompts requiring aesthetic knowledge**: 131 (34.7%) | |
| - **Prompts with atmospheric elements**: 22 (5.8%) | |
| ## 🎯 Use Cases | |
| 1. **Model Evaluation**: Comprehensive evaluation of text-to-image models | |
| 2. **Benchmark Comparison**: Compare different models across various dimensions | |
| 3. **Research**: Study model capabilities in different scenarios | |
| 4. **Fine-tuning**: Use as training or validation data for model improvement | |
| ## 📄 Citation | |
| If you use this dataset in your research, please cite: | |
| ```bibtex | |
| @dataset{magic_bench_377, | |
| title={Magic Bench: A Comprehensive Text-to-Image Generation Evaluation Dataset}, | |
| author={outongtong}, | |
| year={2025}, | |
| email={outongtong.ott@bytedance.com}, | |
| url={https://huggingface.co/datasets/ByteDance-Seed/MagicBench} | |
| } | |
| ``` | |
| ## 📜 License | |
| This dataset is released under the [cc-by-nc-4.0](LICENSE). | |
| ## 🤝 Contributing | |
| We welcome contributions to improve the dataset. Please feel free to: | |
| - Report issues or suggest improvements | |
| - Submit pull requests with enhancements | |
| - Share your evaluation results using this dataset | |
| ## 📞 Contact | |
| For questions or collaborations, please contact: outongtong.ott@bytedance.com | |
| --- | |
| **Keywords**: text-to-image, evaluation, benchmark, dataset, computer vision, AI, machine learning |