Update README.md

README.md

@@ -1,86 +1,93 @@
-# AutoMat Benchmark: STEM Image to Crystal Structure
-
-The **AutoMat Benchmark** is a multimodal dataset designed to evaluate deep‑learning systems for iDPC-STEM‑based crystal‑structure reconstruction and property prediction.
-
----
-
-## 📁 Dataset Structure
-
-The dataset is organized into three tiers of increasing difficulty:
-
-```text
-benchmark/
-├── tier1/
-│   ├── img/          # STEM images (e.g., PNG, TIFF)
-│   ├── label/        # Atomic position labels (e.g., TXT, JSON)
-│   └── cif_file/     # Reconstructed or ground‑truth CIF files
-├── tier2/
-│   └── ...           # Same sub‑folders as tier1
-├── tier3/
-│   └── ...
-└── property.csv      # Material properties for all samples
-````
-
----
-
-## 🔬 Tier Descriptions
-
-| Tier   | Characteristics                                                |
-|--------|----------------------------------------------------------------|
-| Tier 1 | Simulated low-noise STEM images, light elements, low complexity |
-| Tier 2 | Moderate noise or multiple elements, more realistic patterns   |
-| Tier 3 | Low dose, multi-elements, complex symmetry                     |
-
-Each sample in the dataset includes:
-- A STEM image (`img/`)
-- Labeled atomic coordinates (`label/`)
-- A reconstructed or reference CIF file (`cif_file/`)
-- Associated material properties in `property.csv`
-
----
-
-## 📊 Tasks Supported
-
-- STEM-to-structure inference
-- CIF generation and comparison
-- Atomic position prediction
-- Property prediction (formation energy, energy_per_atom, bandgap, etc.)
-
----
-
-## 🔗 Files Description
-
-| File / Folder      | Description                                                |
-|--------------------|------------------------------------------------------------|
-| `img/`             | STEM input images (grayscale microscopy)                   |
-| `label/`           | Atomic position data (format: .txt / .json per sample)     |
-| `cif_file/`        | .cif crystal structure files for each sample               |
-| `property.csv`     | Global material properties table with `material_id` match  |
-
----
-
-## 📄 License
-
-This dataset is released under the **MIT License**. You are free to use, modify, and distribute with attribution.
-
----
-
-## ✉️ Citation
-
-If you use this benchmark, please cite:
-
-```bibtex
-@dataset{yang2025automat,
-  author    = {Yaotian Yang et al.},
-  title     = {AutoMat Benchmark for STEM Image-Based Crystal Structure Reconstruction},
-  year      = {2025},
-  url       = {https://huggingface.co/datasets/yaotianvector/STEM2Mat}
-}
-```
-
----
-
-## 🙋 Contact
-
-For questions or collaborations, please contact: `yangyt22@gmail.com`
-
+---
+license: mit
+tags:
+- chemistry
+pretty_name: STEM2Mat
+size_categories:
+- 1K<n<10K
+---
+# AutoMat Benchmark: STEM Image to Crystal Structure
+
+The **AutoMat Benchmark** is a multimodal dataset designed to evaluate deep‑learning systems for iDPC-STEM‑based crystal‑structure reconstruction and property prediction.
+
+---
+
+## 📁 Dataset Structure
+
+The dataset is organized into three tiers of increasing difficulty:
+
+```text
+benchmark/
+├── tier1/
+│   ├── img/          # STEM images (e.g., PNG, TIFF)
+│   ├── label/        # Atomic position labels (e.g., TXT, JSON)
+│   └── cif_file/     # Reconstructed or ground‑truth CIF files
+├── tier2/
+│   └── ...           # Same sub‑folders as tier1
+├── tier3/
+│   └── ...
+└── property.csv      # Material properties for all samples
+````
+
+---
+
+## 🔬 Tier Descriptions
+
+| Tier   | Characteristics                                                |
+|--------|----------------------------------------------------------------|
+| Tier 1 | Simulated low-noise STEM images, light elements, low complexity |
+| Tier 2 | Moderate noise or multiple elements, more realistic patterns   |
+| Tier 3 | Low dose, multi-elements, complex symmetry                     |
+
+Each sample in the dataset includes:
+- A STEM image (`img/`)
+- Labeled atomic coordinates (`label/`)
+- A reconstructed or reference CIF file (`cif_file/`)
+- Associated material properties in `property.csv`
+
+---
+
+## 📊 Tasks Supported
+
+- STEM-to-structure inference
+- CIF generation and comparison
+- Atomic position prediction
+- Property prediction (formation energy, energy_per_atom, bandgap, etc.)
+
+---
+
+## 🔗 Files Description
+
+| File / Folder      | Description                                                |
+|--------------------|------------------------------------------------------------|
+| `img/`             | STEM input images (grayscale microscopy)                   |
+| `label/`           | Atomic position data (format: .txt / .json per sample)     |
+| `cif_file/`        | .cif crystal structure files for each sample               |
+| `property.csv`     | Global material properties table with `material_id` match  |
+
+---
+
+## 📄 License
+
+This dataset is released under the **MIT License**. You are free to use, modify, and distribute with attribution.
+
+---
+
+## ✉️ Citation
+
+If you use this benchmark, please cite:
+
+```bibtex
+@dataset{yang2025automat,
+  author    = {Yaotian Yang et al.},
+  title     = {AutoMat Benchmark for STEM Image-Based Crystal Structure Reconstruction},
+  year      = {2025},
+  url       = {https://huggingface.co/datasets/yaotianvector/STEM2Mat}
+}
+```
+
+---
+
+## 🙋 Contact
+
+For questions or collaborations, please contact: `yangyt22@gmail.com`