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Turn one photo into a flyable 3D video scene

Guangyu Zaojing (光域造景) turns a single photo and short prompt into a 3D scene you can fly through like a video — no 3D modeling skills needed.

A system that takes one image and a description, then builds a scene out of a point cloud (millions of colored dots) you can watch as a flythrough video.

When it helps

Good for quickly showing a look-around of a room or landscape for a review or a class. Building your own custom scenes needs a strong NVIDIA GPU.

Pros

  • View a ready-made 3D scene in a browser, no GPU needed
  • Comes with finished example scenes: anime cabin, a girl, more
  • Download the point cloud as a PLY file for SuperSplat or MeshLab
  • Depth estimation, scene generation, and rendering are already wired together

Cons

  • Making your own scenes needs an NVIDIA GPU with 16+ GB VRAM
  • Interface is in Chinese, so you'll need to translate as you go
  • Full mode downloads about 30 GB of model weights on startup

How to set it up — step by step

  1. 1Clone the deepopen-com/deepopen-3d-webs repository (download the project code) to your computer.
  2. 2Open your AI agent (Claude Code, Codex) in the project folder.
  3. 3Send the agent the text from the block below.
  4. 4Wait for the agent to run demo mode via docker compose up -d --build (container build command) — no GPU required.
  5. 5Open http://localhost:8090 in your browser and check the result.
  6. 6Look at the Example Gallery section with ready-made scenes.

Text for your agent

Copy this and send it to your agent — Claude Code, Codex, any of them:

Set up Guangyu Zaojing from https://github.com/deepopen-com/deepopen-3d-webs — bring up the no-GPU demo mode with docker compose following the README, open http://localhost:8090, and show me what's in the Example Gallery tab.

Browsing the ready examples and spinning the point cloud in the browser works on a regular laptop with Docker and 8 GB of memory — no graphics card needed. Generating your own scenes needs an NVIDIA GPU with 16 GB or more, which a laptop cannot do; you would need to rent a server.

Open on GitHub