Datasets:
Tasks:
Image-to-3D
Modalities:
Image
Formats:
imagefolder
Size:
1K - 10K
ArXiv:
Tags:
chemistry
License:
Upload README.md with huggingface_hub
Browse files
README.md
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---
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---
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# AutoMat Benchmark: STEM Image to Crystal Structure
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The **AutoMat Benchmark** is a multimodal dataset designed to evaluate deep‑learning systems for iDPC-STEM‑based crystal‑structure reconstruction and property prediction.
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---
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## 📁 Dataset Structure
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The dataset is organized into three tiers of increasing difficulty:
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```text
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benchmark/
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├── tier1/
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│ ├── img/ # STEM images (e.g., PNG, TIFF)
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│ ├── label/ # Atomic position labels (e.g., TXT, JSON)
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│ └── cif_file/ # Reconstructed or ground‑truth CIF files
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├── tier2/
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│ └── ... # Same sub‑folders as tier1
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├── tier3/
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│ └── ...
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└── property.csv # Material properties for all samples
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````
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---
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## 🔬 Tier Descriptions
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| Tier | Characteristics |
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|--------|----------------------------------------------------------------|
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| Tier 1 | Simulated low-noise STEM images, light elements, low complexity |
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| Tier 2 | Moderate noise or multiple elements, more realistic patterns |
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| Tier 3 | Low dose, multi-elements, complex symmetry |
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Each sample in the dataset includes:
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- A STEM image (`img/`)
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- Labeled atomic coordinates (`label/`)
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- A reconstructed or reference CIF file (`cif_file/`)
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- Associated material properties in `property.csv`
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---
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## 📊 Tasks Supported
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- STEM-to-structure inference
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- CIF generation and comparison
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- Atomic position prediction
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- Property prediction (formation energy, energy_per_atom, bandgap, etc.)
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---
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## 🔗 Files Description
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| File / Folder | Description |
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|--------------------|------------------------------------------------------------|
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| `img/` | STEM input images (grayscale microscopy) |
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| `label/` | Atomic position data (format: .txt / .json per sample) |
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| `cif_file/` | .cif crystal structure files for each sample |
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| `property.csv` | Global material properties table with `material_id` match |
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---
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## 📄 License
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This dataset is released under the **MIT License**. You are free to use, modify, and distribute with attribution.
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---
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## ✉️ Citation
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If you use this benchmark, please cite:
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```bibtex
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@dataset{yang2025automat,
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author = {Yaotian Yang et al.},
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title = {AutoMat Benchmark for STEM Image-Based Crystal Structure Reconstruction},
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year = {2025},
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url = {https://huggingface.co/datasets/yaotianvector/STEM2Mat}
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}
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```
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---
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## 🙋 Contact
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For questions or collaborations, please contact: `yangyt22@gmail.com`
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