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Hunyuan3d 1
Overview :
Hunyuan3D-1 is a unified framework introduced by Tencent for generating 3D models from text and images. The framework uses a two-stage approach: the first stage employs a multi-view diffusion model to quickly generate multi-view RGB images, while the second stage uses a feed-forward reconstruction model to swiftly construct 3D assets. Hunyuan3D-1.0 strikes an impressive balance between speed and quality, significantly reducing generation time while maintaining the quality and diversity of the generated assets.
Target Users :
The target audience includes 3D artists, game developers, VR/AR content creators, and anyone needing to quickly generate 3D models from text or images. Hunyuan3D-1's efficiency and user-friendliness make it an ideal choice for these users, significantly enhancing their productivity and creative flexibility.
Use Cases
3D artists quickly generate conceptual models from text descriptions using Hunyuan3D-1.
Game developers create game assets from existing images utilizing Hunyuan3D-1.
VR/AR content creators generate interactive 3D content with Hunyuan3D-1.
Features
Supports 3D generation conditioned on text and images: The framework facilitates generating 3D models from text descriptions and images.
Multi-view diffusion model: The first stage rapidly generates multi-view RGB images using a multi-view diffusion model.
Feed-forward reconstruction model: The second stage quickly reconstructs 3D assets from multi-view images using a feed-forward reconstruction model.
Bilingual support: Supports text-to-3D generation in both Chinese and English.
Optimized generation speed: The Lite model generates 3D meshes from a single image in about 10 seconds on an NVIDIA A100 GPU.
High-quality 3D output: The standard model produces high-quality 3D assets while maintaining diversity.
User-friendly interface: The Gradio interface provides easy access to and use of the generation models.
How to Use
1. Clone the repository: Use the git command to clone the Hunyuan3D-1 repository to your local machine.
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2. Set up the environment: Follow the provided env_install.sh script to set up the development environment.
3. Download the pre-trained model: Download the required pre-trained model from the Huggingface platform.
4. Run text-to-3D generation: Use the main.py script and provide text prompts to execute 3D generation.
5. Run image-to-3D generation: Use the main.py script and provide image prompts to execute 3D generation.
6. Use the Gradio interface: Run the app.py script to launch the Gradio interface for interactive 3D generation.
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