File size: 3,507 Bytes
25d7df0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | # Break4Models Dataset
Break4Models is a small-scale 4-shape dataset for deepfracture paper. It contains simulation data of various 3D objects undergoing impact and breaking fracture pattern, designed for training and evaluating neural networks that can predict object fracture patterns for specific one target shape. It was created by [FractureRB](https://github.com/david-hahn/FractureRB).
📖 **For more details, please visit:**
- [GitHub Repository](https://github.com/nikoloside/TEBP)
- [Project Page](https://nikoloside.graphics/deepfracture/)
## Overview
This dataset contains simulation data of 4-shape 3D objects undergoing impact and breaking fracture pattern. Each target shape includes multiple simulation runs with different impact conditions, providing a small-scale dataset for learning relationship between impact collision condition and physics-based fracture patterns.
## Dataset Structure
```
break4models/
├── _out_base/ # Base object simulations
├── _out_pot/ # Pot object simulations
├── _out_squirrel/ # Squirrel object simulations
├── _out_bunny/ # Bunny object simulations
└── README.md # This file
```
Each object category directory contains:
- `meta.json` - Metadata with simulation statistics
- `obj/` - 3D mesh files (.obj format) for each simulation step
- `info/` - Collision information files
- `impact/` - Detailed impact data in JSON format
- `initial_cond/` - Initial conditions for simulations
- `nii/` - NIfTI format data (if applicable)
- `gif/` - Animation files showing breaking process
## Data Format
### Meta Information (`meta.json`)
```json
{
"target_shape": "base",
"max_gssdf_val": 0.128913,
"avg_max_gssdf_val": 0.127481,
"min_gssdf_val": -1.045852,
"avg_min_gssdf_val": -1.045852,
"start_time": "2024-03-30T08:58:40",
"stop_time": "2024-03-30T10:40:07",
"total_valid": 277
}
```
### Impact Data (`impact/*.txt`)
JSON format containing collision information:
- `collElems`: Collision element IDs
- `collPoints`: Collision point coordinates [x, y, z]
- `collDirections`: Collision direction vectors
- `collVels`: Collision velocities
- `collImpulse`: Collision impulse values
- `collForce`: Collision force magnitudes
### Info Files (`info/*.txt`)
Simple format: `directory/,frame_number`
## Usage
This dataset is designed for:
- Training neural networks for physics-based fracture pattern
- Evaluating fracture prediction models
- Research in computational physics and computer graphics
- Development of real-time simulation systems
## Citation
If you use this dataset in your research, please cite:
```bibtex
@article{huang2025deepfracture,
author = {Huang, Yuhang and Kanai, Takashi},
title = {DeepFracture: A Generative Approach for Predicting Brittle Fractures with Neural Discrete Representation Learning},
journal = {Computer Graphics Forum},
pages = {e70002},
year = {2025},
keywords = {animation, brittle fracture, neural networks, physically based animation},
doi = {https://doi.org/10.1111/cgf.70002},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.70002},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.70002}
}
```
## License
This dataset is licensed under the **Public Domain Dedication and License (PDDL)**.
## Contact
For questions or issues, please open an issue on the Hugging Face dataset page.
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