HLOC + GLOMAP Repo

A GitHub repo from Pablo Vela has integrated GLOMAP with HLOC.

A GitHub repo from Pablo Vela has integrated GLOMAP with HLOC.

Michael Rubloff

Michael Rubloff

Michael is the Founder and Managing Editor of Radiancefields.com

Tags

GLOMAP HLOC

The repository, created by developer Pablo Vela, aimed at optimizing the Structure-from-Motion (SfM) pipeline for Radiance Fields introduces a combination of speed and usability. By integrating the high-performing GLOMAP mapper with the advanced Hierarchical Localization (hloc) toolbox, 

For many Radiance field creators and businesses, using COLMAP has been the standard, due to its robust performance, albeit slow processing time. Fortunately, with companies like Epic Games relaxing their RealityCapture license, Agisoft Metashape doing the same as well, and then there was the announcement of GLOMAP, which tremendously speeds up the SfM pipeline compared to COLMAP.

This repository leverages GLOMAP’s remarkable ability to process data up to ten times faster than traditional tools like COLMAP, while also incorporating hloc’s state-of-the-art feature detection and matching capabilities. Together, they offer a versatile and user-friendly platform tailored for modern SfM needs.

Visualization plays a pivotal role in this tool, offering detailed insights into critical stages such as feature detection, pair generation, matching, and reconstruction. This level of transparency helps users identify potential bottlenecks and refine their workflows effectively. Furthermore, the repository’s integration of both COLMAP and GLOMAP ensures that users can compare the performance of these two mappers, with detailed logs capturing the runtime of every stage.

For environments where graphical user interfaces are impractical, the repository includes a dataloader powered by Rerun, specifically designed for remote server workflows. This functionality is complemented by an intuitive, interactive interface created with Gradio, enabling users to customize feature detectors, matchers, and other parameters with ease.

The output of this repo can be used in locally training platforms, such as Postshot and Nerfstudio, though you will have to modify the CLI code in Nerfstudio to have it skip the SfM step. The repo is Apache 2.0 licensed, meaning that you can use it for commercial purposes. Additionally, PRs are welcome to continue to build out functionality for the community!

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