# Tutorials & Interface Usage
Welcome to the tutorials for `EmbodiedGen`. `EmbodiedGen` is a powerful toolset for generating 3D assets, textures, scenes, and interactive layouts ready for simulators and digital twin environments.
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## ⚙️ Prerequisites
!!! tip "Prerequisites"
Make sure to finish the [Installation Guide](../install.md) before starting tutorial. Missing dependencies will cause initialization errors. Model weights are automatically downloaded on first run.
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## [🖼️ Image-to-3D](image_to_3d.md)
Generate **physically plausible 3D assets** from a single input image, supporting digital twin and simulation environments.
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## [📝 Text-to-3D](text_to_3d.md)
Create **physically plausible 3D assets** from **text descriptions**, supporting a wide range of geometry, style, and material details.
"small bronze figurine of a lion"
"A globe with wooden base"
"wooden table with embroidery"
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## [🎨 Texture Generation](texture_gen.md)
Generate **high-quality textures** for 3D meshes using **text prompts**, supporting both Chinese and English, to enhance the visual appearance of existing 3D assets.
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## [🌍 3D Scene Generation](scene_gen.md)
Generate **physically consistent and visually coherent 3D environments** from text prompts. Typically used as **background** 3DGS scenes in simulators for efficient and photo-realistic rendering.
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## [🏞️ Layout Generation](layout_gen.md)
Generate diverse, physically realistic, and scalable **interactive 3D scenes** from natural language task descriptions, while also modeling the robot and manipulable objects.
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## [🏎️ Parallel Simulation](gym_env.md)
Generate multiple **parallel simulation environments** with `gym.make` and record sensor and trajectory data.
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## [🎮 Use in Any Simulator](any_simulators.md)
Seamlessly use EmbodiedGen-generated assets in major simulators like **IsaacSim**, **MuJoCo**, **Genesis**, **PyBullet**, **IsaacGym**, and **SAPIEN**, featuring **accurate physical collisions** and **consistent visual appearance**.
## [🔧 Real-to-Sim Digital Twin Creation](digital_twin.md)
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## [🏞️ Layout Generation](layout_gen.md)
Generate diverse, physically realistic, and scalable **interactive 3D scenes** from natural language task descriptions, while also modeling the robot and manipulable objects.
