What do you want to do?
3 use cases
-
Render a first-person walkthrough MP4 from one image
Run the Preview v1 pipeline on a first-frame image to get a clean MP4 with motion-driven video and sound.
- Helix World
- Content
- Advanced
View prompt
In the HelixWorld repo (NoizAI/HelixWorld), set up the Preview v1 environment as described in the README, then run ./run.sh with --image <path to first-frame PNG> and --output-dir outputs/demo. Expect a clean MP4 under outputs/demo, and verify that the file exists and that ffprobe reports a video stream and an audio stream.
-
Score whether generated sound follows camera motion
Use the HelixBench dataset to test if synthesized sound fields track dynamic viewpoint motion.
- Helix World
- Content
- Advanced
View prompt
Using the NoizAI/Helixbench dataset on Hugging Face and the HelixWorld repo (NoizAI/HelixWorld), generate outputs for the dataset items into <output folder> and compare stereo panning with camera motion for each clip. Expect a results table with one row per clip; verify that the row count matches the number of dataset items.
-
Walk through a Helix World scene in the browser
Open the hosted demo to hear how sound changes as you move and turn, with no local setup.
- Helix World
- Content
- Beginner
View prompt
Open https://helixworld.org/ in a browser, move forward and turn in one scene from the HelixWorld project (NoizAI/HelixWorld), and report whether the sound changes with the viewpoint. Expect a short written note; verify that the note states the scene name and the observed sound changes.
How to use Helix World
- Check you have what it needs: Linux with Python 3.11 and CUDA 12.x; NVIDIA GPU, 80 GB VRAM recommended (a reviewed BF16 single-GPU run uses about 70 GB); System ffmpeg and ffprobe installed.
- Open NoizAI/HelixWorld on GitHub and read the README and license.
git clone https://github.com/NoizAI/HelixWorld.gitcd HelixWorldconda create -n helixworld-preview python=3.11 -yconda activate helixworld-preview
These steps come from our top use case, Render a first-person walkthrough MP4 from one image, which also has a copy-paste agent prompt.
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Get them freeAbout this repo
- Who it is forBuilt for ML researchers and creative technologists with a CUDA GPU who want to generate or evaluate interactive audio-visual scenes from a single image.
- Why it is hot
- LanguagePython
- Sourcegithub.com/NoizAI/HelixWorld · Back to Hot repos
Requirements
- Linux with Python 3.11 and CUDA 12.x
- NVIDIA GPU, 80 GB VRAM recommended (a reviewed BF16 single-GPU run uses about 70 GB)
- System ffmpeg and ffprobe installed
- A first-frame image file (PNG) and a text prompt
- Access to Hugging Face to download the Preview v1 model files
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Questions about Helix World
What is Helix World?
HelixWorld is a Python research repo for a real-time interactive audio-visual world model that generates video and camera-aligned spatial sound from a starting image, a prompt, and movement or camera actions. It is an open-source project on GitHub: https://github.com/NoizAI/HelixWorld.
Who is Helix World for?
Built for ML researchers and creative technologists with a CUDA GPU who want to generate or evaluate interactive audio-visual scenes from a single image.
What can I do with Helix World?
3 use cases so far, for example: Render a first-person walkthrough MP4 from one image; Score whether generated sound follows camera motion; Walk through a Helix World scene in the browser. Each has steps and a copy-paste agent prompt.
What do I need to run Helix World?
Linux with Python 3.11 and CUDA 12.x; NVIDIA GPU, 80 GB VRAM recommended (a reviewed BF16 single-GPU run uses about 70 GB); System ffmpeg and ffprobe installed; A first-frame image file (PNG) and a text prompt.
What are alternatives to Helix World?
Other hot AI repos in Content: Voice Studio, Anatomy, Comfy UI, Hyperframes, Earshot.
Is Helix World safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.