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- depth-estimation
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- computer-vision
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# ORB: Omni-directional Reconstruction Backbone
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**ORB
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##
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- **Zero-Shot Generalization**: Strong performance on unseen data
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- **End-to-End**: Single forward pass for complete panorama depth
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- **Easy Integration**: Simple Python API with HuggingFace support
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##
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- `README.md` - This file
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```bibtex
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@
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title={
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author={
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```
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##
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---
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- depth-estimation
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- computer-vision
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# ORB: Omni-directional Reconstruction Backbone
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**ORB** is a 360° panorama depth estimation model that predicts dense distance maps from equirectangular panoramas in a single forward pass.
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## Model Description
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This model takes a 360° equirectangular panorama (2:1 aspect ratio) as input and outputs a dense depth/distance map at the same resolution. It's designed for:
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- **Zero-shot depth estimation** from panoramic images
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- **Scale-invariant predictions** with geometric fidelity
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- **End-to-end processing** without post-processing
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## Quick Start
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```python
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from orb import predict_pano_depth
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# Predict depth from panorama
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distance = predict_pano_depth('panorama.png')
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```
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## Model Details
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- **Input**: RGB panorama (equirectangular, width = 2 × height)
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- **Output**: Dense depth/distance map (same resolution as input)
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- **Format**: SafeTensors (1.3 GB)
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- **Precision**: FP32 / FP16 supported
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- **Base Architecture**: Built upon [DA²: Depth Anything in Any Direction](https://arxiv.org/abs/2509.26618)
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## 📖 Full Documentation
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For complete installation instructions, advanced usage, API documentation, and examples, please visit:
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**[github.com/speridlabs/ORB](https://github.com/speridlabs/ORB)**
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## Citation
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```bibtex
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@misc{orb2024,
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title={ORB: Omni-directional Reconstruction Backbone},
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author={Sperid Labs and Del Pino, Javier and Garabito, Chema and Sanchez, Alejandro},
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year={2024},
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publisher={Sperid Labs},
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url={https://github.com/speridlabs/ORB}
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}
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```
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## License
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Apache 2.0 - See [LICENSE](https://github.com/speridlabs/ORB/blob/main/LICENSE)
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## Acknowledgements
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Built upon the foundational work of the [DA-2](https://arxiv.org/abs/2509.26618).
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---
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