ORB: Omni-directional Reconstruction Backbone

ORB Banner

ORB is a 360Β° panorama depth estimation model that predicts dense distance maps from equirectangular panoramas in a single forward pass.

Model Description

This model takes a 360Β° equirectangular panorama (2:1 aspect ratio) as input and outputs a dense depth/distance map at the same resolution. It's designed for:

  • Zero-shot depth estimation from panoramic images
  • Scale-invariant predictions with geometric fidelity
  • End-to-end processing without post-processing

Quick Start

from orb import predict_pano_depth

# Predict depth from panorama
distance = predict_pano_depth('panorama.png')

Model Details

  • Input: RGB panorama (equirectangular, width = 2 Γ— height)
  • Output: Dense depth/distance map (same resolution as input)
  • Format: SafeTensors (1.3 GB)
  • Precision: FP32 / FP16 supported
  • Base Architecture: Built upon DAΒ²: Depth Anything in Any Direction

πŸ“– Full Documentation

For complete installation instructions, advanced usage, API documentation, and examples, please visit:

github.com/speridlabs/ORB

License

Apache 2.0 - See LICENSE

Acknowledgements

Built upon the foundational work of the DA-2.


Made with ❀️ by Sperid Labs

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Paper for speridlabs/orb