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GitHub · Robbyant/lingbot-map↑ +372 today

Create three-dimensional scenes from streaming data

Lingbot-map is a feed-forward 3D foundation model designed to reconstruct scenes from streaming data. The project optimizes visualization processes by processing complex environmental data, thanks to its architecture developed in Python language.

Updates

  • October 13, 2026: Stars 17,060 → 18,061.
  • September 16, 2026: Stars 16,054 → 17,060.
  • August 2, 2026: Stars 8,439 → 16,054.

What you get

  • Stable 3D reconstruction of long video sequences
  • Low latency streaming inference support
  • Artificial intelligence architecture that can process complex environmental data

Installation

Environment preparation and basic setup
conda create -n lingbot-map python=3.10 -y
conda activate lingbot-map
Installing the required libraries
pip install torch==2.8.0 torchvision==0.23.0 --index-url https://download.pytorch.org/whl/cu128

Running it

Starting the sample scene
python demo.py --model_path /path/to/lingbot-map-long.pt \
    --image_folder example/courthouse --mask_sky

If you don't write code

Paste this into your AI agent (Claude Code · Codex · Antigravity)

I want to create a 3D scene from streaming data using LingBot-Map. I completed the installation and my model file is ready. How can I launch the visualization interface in my local browser using the command required to run the Courthouse instance?

Repository: https://github.com/Robbyant/lingbot-map. Follow the official instructions in the README of this repository for setup and execution.

Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.

Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.

Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.

Related dictionary terms

Who it is forIt is suitable for researchers and developers interested in 3D computer vision and streaming data processing.
LicenseApache-2.0

Links

TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-29: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.