Create README.md

README.md

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+---
+license: mit
+language:
+- en
+tags:
+- blockchain
+- defi-security
+- depin
+- graph
+- vision
+- transaction-analysis
+- ethereum
+- arbitrum
+- polygon
+- attack-detection
+pretty_name: Sigui DePIN 1M — Multichain Transaction Graph Dataset
+size_categories:
+- 1M<n<10M
+task_categories:
+- image-classification
+- image-text-to-text
+---
+# Sigui DePIN 1M — Multichain Transaction Graph Dataset
+> The largest open dataset of annotated blockchain transaction graph visualizations for AI security research.
+---
+## 📋 Dataset Description
+**sigui-depin-1m** contains 1,000,000 visual transaction graph images generated from 1.87 million real on-chain transactions across Ethereum, Arbitrum, and Polygon. Each image is annotated with an attack topology label designed to train Vision-Language Models to detect DeFi threats.
+This dataset is the training foundation for **Imina-Na V2**, the vision brain of the Sigui Protocol — a DePIN security oracle for the agentic economy.
+---
+## 📊 Dataset Statistics
+| Property | Value |
+|---|---|
+| **Total images** | 1,000,000 |
+| **Source transactions** | 1,870,000+ real on-chain txs |
+| **Chains covered** | Ethereum, Arbitrum, Polygon |
+| **Label classes** | 3 (DRAIN_STAR, MIXING_CHAIN, NORMAL) |
+| **Image format** | PNG (dark background) |
+| **Total size** | ~10.8 GB (images.tar) |
+| **Annotation file** | qwen2_vl_real_data.jsonl (260 MB) |
+| **License** | MIT |
+---
+## 🏷️ Label Classes
+### DRAIN_STAR
+Multiple wallets converging simultaneously into a single target address. This topology is the signature of coordinated rug pulls, flash loan attacks, and fund aggregation schemes.
+### MIXING_CHAIN
+Funds routed through a sequential chain of intermediate wallets to obscure the origin. This is the on-chain fingerprint of mixer evasion, layering attacks, and money laundering.
+### NORMAL
+Organic transaction topologies with no anomalous structure. Standard user-to-user and contract interactions.
+---
+## 📁 Dataset Structure
+sigui-depin-1m/ ├── images.tar # 1,000,000 PNG graph images └── qwen2_vl_real_data.jsonl # Annotations in ShareGPT format
+
+Each line in the JSONL file follows this format:
+```json
+{
+  "messages": [
+    {"role": "user", "content": "<image>Analyze this DePIN transaction graph."},
+    {"role": "assistant", "content": "DRAIN_STAR detected."}
+  ],
+  "images": ["/path/to/graph_000001_drain_star.png"]
+}
+⚙️ Generation Process
+Generated using a custom multiprocessing pipeline on AMD MI300X (ROCm 7.0):
+
+Source: 1.87M real transactions from Ethereum, Arbitrum, and Polygon via public APIs
+Graph construction: NetworkX DiGraph built from from/to transaction pairs
+Attack injection: Deterministic injection of DRAIN_STAR and MIXING_CHAIN patterns
+Rendering: Matplotlib (Agg backend), dark background, DPI=50
+Speed: ~225 images/second using 20 parallel CPU cores
+Total generation time: ~1 hour 15 minutes
+🔧 How to Use
+python
+from datasets import load_dataset
+dataset = load_dataset(
+    "json",
+    data_files="qwen2_vl_real_data.jsonl",
+    split="train"
+)
+print(dataset[0])
+🔗 Related Resources
+Sigui Protocol (GitHub): https://github.com/ibonon/ERCs
+ERC-8259 Standard: https://ethereum-magicians.org/t/erc-8259-ai-agent-identity-threat-registry/28473
+Imina-Na V1 Model: https://huggingface.co/Ibonon/imina_na_lora
+Imina-Na V2 Model: https://huggingface.co/Ibonon/imina_na_v2_lora
+✍️ Citation
+bibtex
+@dataset{sigui_depin_1m_2026,
+  author    = {Ibonon},
+  title     = {Sigui DePIN 1M — Multichain Transaction Graph Dataset},
+  year      = {2026},
+  publisher = {Hugging Face},
+  url       = {https://huggingface.co/datasets/Ibonon/sigui-depin-1m}
+}
+⚖️ License
+MIT — Open for research and commercial use.