{"name":"image-blaster: Turn Images into 3D Environments and Assets","description":"image-blaster uses Claude skills and external generation services to turn an image into a 3D environment, object meshes, and sound effects. It is designed to quickly create starting points for game, 3D, and web projects.","github":"https://github.com/neilsonnn/image-blaster","url":"https://osrepos.com/repo/neilsonnn-image-blaster","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/neilsonnn-image-blaster","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/neilsonnn-image-blaster.md","json":"https://osrepos.com/repo/neilsonnn-image-blaster.json","topics":["typescript","ai-agents","generative-ai","agent-skills","3d-reconstruction","gaussian-splatting"],"keywords":["typescript","ai-agents","generative-ai","agent-skills","3d-reconstruction","gaussian-splatting"],"stars":null,"summary":"image-blaster uses Claude skills and external generation services to turn an image into a 3D environment, object meshes, and sound effects. It is designed to quickly create starting points for game, 3D, and web projects.","content":"## Overview\n\nimage-blaster is a Claude-driven workflow for turning a reference image into a collection of 3D and audio assets. It combines World Labs for an explorable environment, FAL for object meshes, and sound generation for ambient and object-specific effects.\n\nThe project is aimed at speeding up early 3D work, not replacing a full modeling or production pipeline. Its outputs can be used as starting assets in game engines, DCC tools, or web applications.\n\n## Key Features\n\n- Generates a Gaussian splat environment from a source image.\n- Creates meshes for dynamic objects in `.glb` or `.obj` formats.\n- Produces ambient loops and object-specific sound effects.\n- Uses Claude skills to coordinate the image-to-assets workflow.\n- Supports Hunyuan 3D options for face count, PBR materials, geometry style, and polygon type.\n- Supports image-editing preferences including nano-banana and gpt-image-2.\n- Designed for integration into engines and tools such as Unity, Unreal, Godot, Blender, and Three.js.\n\n## Use Cases\n\n- Game developers can turn a concept image into a rough level environment and object assets to begin prototyping.\n- 3D artists can use a photo or illustration as a jumpstart for environment blocking and asset creation.\n- Film and architecture teams can create quick spatial concepts from location or rendering references.\n- Web developers can generate scene assets to explore interactive 3D experiences in a Three.js or Electron project.\n\n## Project Facts\n\n- Language: TypeScript\n- License: MIT\n- Stars: 9.4k\n- Forks: 918\n- Archived: No\n\n## Getting Started\n\nClone the repository, install Claude, configure World Labs and FAL API keys, then place an image in `input/` and ask Claude to process it. See the [README](https://github.com/neilsonnn/image-blaster#readme) for the full setup and workflow.\n\n```bash\ngit clone https://github.com/neilsonnn/image-blaster\ncd image-blaster\n```\n\n## Alternatives\n\n- [GigaSLAM](https://osrepos.com/repo/dengkaicq-gigaslam): GigaSLAM reconstructs and tracks large outdoor scenes from RGB video, while image-blaster turns an image into 3D assets and sound effects.\n\n## Considerations\n\n- Using the workflow requires Claude and API access to World Labs and FAL; generated assets depend on these external services.\n- The outputs are intended to jumpstart 3D work, so they may need review and further editing before production use.\n- The README describes model choices and generation parameters, but does not specify a local-only or offline workflow.","metrics":{"detailViews":1,"githubClicks":1},"dates":{"published":null,"modified":"2026-10-05T15:28:22.000Z"}}