Duplicate from sugiv/synthetic_cards

Co-authored-by: Sugi Venugeethan <sugiv@users.noreply.huggingface.co>

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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- visual-question-answering
+- image-to-text
+- object-detection
+- document-question-answering
+- image-text-to-text
+language:
+- en
+tags:
+- synthetic-data
+- identity-documents
+- driver-license
+- credit-cards
+- vlm-training
+- document-ai
+- ocr
+- computer-vision
+size_categories:
+- 10K<n<100K
+viewer: false
+---
+
+# Synthetic Identity Documents Dataset
+
+## 📋 Dataset Summary
+
+This dataset contains **15,110 high-quality synthetic identity documents** specifically designed for fine-tuning Vision Language Models (VLMs). The dataset includes realistic driver's licenses and credit cards with diverse variations in design, layout, and content.
+
+**⚠️ IMPORTANT: This dataset is intended EXCLUSIVELY for Vision Language Model training and research purposes. Not for production identity verification systems.**
+
+## 🎯 Intended Use
+
+### ✅ Permitted Uses:
+- **Vision Language Model (VLM) fine-tuning**
+- **Document AI research and development** 
+- **Optical Character Recognition (OCR) model training**
+- **Computer vision research**
+- **Academic research and education**
+- **Proof-of-concept applications**
+
+### ❌ Prohibited Uses:
+- **Real identity verification systems**
+- **Production document authentication**
+- **Fraud detection training** (use real anonymized data instead)
+- **Any application that could facilitate document forgery**
+- **Commercial identity verification services**
+
+## 📊 Dataset Structure
+
+```
+Total Files: 15,110 synthetic documents
+├── Root Directory/     → 9,610 documents
+└── batch_2/           → 5,500 documents
+
+Document Types:
+├── Driver's Licenses  → ~50% (Multiple US states)
+└── Credit Cards       → ~50% (Multiple brands)
+```
+
+## 🔢 Dataset Statistics
+
+- **Total Images**: 15,110
+- **File Format**: PNG
+- **Image Resolution**: Variable (realistic document sizes)
+- **Total Size**: ~866MB
+- **States Covered**: All 50 US states + DC
+- **Card Brands**: Visa, Mastercard, American Express, Discover
+- **Variations**: Front/back views, different designs, diverse demographics
+
+## 🏗️ Dataset Creation
+
+### Generation Method:
+- **Template-based synthesis** using realistic layouts
+- **Procedural generation** with Faker library for realistic data
+- **Professional document styling** with authentic typography
+- **Quality-controlled output** with automated validation
+- **Zero API costs** - fully synthetic generation pipeline
+
+### Data Fields:
+- **Driver's Licenses**: Name, address, license number, DOB, expiration, photo placeholder, state-specific designs
+- **Credit Cards**: Cardholder name, card number (synthetic), expiration date, CVV, brand-specific styling
+
+## 📝 Licensing & Usage Rights
+
+### License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
+
+**You are free to:**
+- ✅ Share — copy and redistribute in any medium or format
+- ✅ Adapt — remix, transform, and build upon the material for non-commercial purposes
+- ✅ Use for VLM training and research
+
+**Under the following terms:**
+- 📝 **Attribution** — Credit this dataset and its creators
+- 🚫 **NonCommercial** — Not for commercial document verification use
+- 🔄 **ShareAlike** — Distribute derived works under the same license
+
+## ⚖️ Ethical Considerations
+
+### Privacy & Safety:
+- ✅ All data is **100% synthetic** - no real personal information
+- ✅ Generated names, addresses, and numbers are **completely fictional**
+- ✅ Designed to **avoid harmful biases** in demographic representation
+- ✅ **Cannot be used to identify real individuals**
+
+### Responsible AI:
+- 🎯 Purpose-built for **legitimate AI research and development**
+- 🔒 **Not suitable for production identity systems**
+- 📚 Should be used alongside **proper data governance practices**
+- ⚡ Intended to **accelerate VLM research** while maintaining safety
+
+## 🚀 Recommended Use Cases
+
+### 1. Vision Language Model Training
+```python
+# Example: Fine-tuning for document understanding
+"What is the license number on this driver's license?"
+"Extract the cardholder name from this credit card"
+"What state issued this driver's license?"
+```
+
+### 2. Document AI Development
+- Layout understanding models
+- Multi-modal document processing
+- OCR enhancement for structured documents
+
+### 3. Research Applications
+- Academic studies on document AI
+- Comparative analysis of VLM architectures
+- Benchmarking document understanding capabilities
+
+## 📦 Dataset Loading
+
+```python
+from datasets import load_dataset
+
+# Load the complete dataset
+dataset = load_dataset("sugiv/synthetic_cards")
+
+# Access images and annotations
+for sample in dataset:
+    image = sample['image']  
+    annotations = sample['annotations']  # Document metadata
+```
+
+## 🔧 Technical Specifications
+
+- **Image Format**: PNG with transparency support
+- **Color Space**: RGB
+- **Quality**: Professional document rendering
+- **Annotations**: JSON metadata with document details
+- **File Naming**: Descriptive names indicating document type and region
+
+## 📈 Model Performance Expectations
+
+This dataset is optimized for:
+- **High-quality VLM fine-tuning** with realistic document layouts
+- **Robust OCR training** with varied text positioning
+- **Layout understanding** with authentic document structures
+- **Multi-class classification** across document types and regions
+
+## 🤝 Contributing & Feedback
+
+- **Issues**: Report problems or suggest improvements via GitHub issues
+- **Research Collaboration**: Open to academic partnerships
+- **Model Results**: Share your fine-tuning results with the community
+
+## 📚 Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{synthetic_identity_documents_2025,
+  title={Synthetic Identity Documents Dataset for Vision Language Model Training},
+  author={Sugiv},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/sugiv/synthetic_cards},
+  license={CC-BY-NC-4.0}
+}
+```
+
+## ⚠️ Disclaimer
+
+This dataset contains entirely synthetic data created for AI training purposes. It should not be used for real-world identity verification, fraud detection, or any production authentication systems. The creators are not responsible for misuse of this dataset.
+
+**Remember: This is a tool for advancing AI research responsibly.**
+
+---
+
+*Dataset created with ❤️ for the Vision Language Model research community*