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| title: PGPS Geometric Problem Solver | |
| emoji: ๐ | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 5.43.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| # PGPS: Neural Geometric Problem Solver Demo | |
| This Space demonstrates the PGPS (Plane Geometry Problem Solver) model, which uses multi-modal neural networks to solve geometry problems. | |
| ## How to Use | |
| 1. **Upload a Geometry Diagram**: Upload an image containing a geometric diagram (triangles, angles, lines, etc.) | |
| 2. **Enter Problem Text**: Provide the text description of the geometry problem | |
| 3. **Get Solution**: The model will analyze both the diagram and text to generate a solution | |
| ## Model Details | |
| - **Architecture**: Multi-modal neural network with visual encoder and text encoder | |
| - **Task**: Geometric problem solving | |
| - **Paper**: IJCAI 2023 | |
| - **Original Repository**: [GitHub](https://github.com/mingliangzhang2018/PGPS) | |
| ## Features | |
| - Visual diagram parsing | |
| - Text understanding for geometric problems | |
| - Expression generation for solutions | |
| - Support for various geometry problem types | |
| ## Limitations | |
| - Best performance with clear, simple geometric diagrams | |
| - Requires both image and text input for optimal results | |
| - Limited to plane geometry problems | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{zhang2023pgps, | |
| title={PGPS: A Neural Geometric Solver}, | |
| author={Zhang, Mingliang and others}, | |
| booktitle={IJCAI 2023}, | |
| year={2023} | |
| } | |
| ``` |