GPT-Based Blender 3D Modeling-Blender 3D AI model generator

Example

A user provides a detailed text prompt describing a car model with specific features, such as 'Create a futuristic sports car with angular bodywork and large tires.'

Scenario

The system generates Python code that breaks down the components of the car, such as wheels,JSON Code Correction chassis, and windows, translating these into Blender's scripting interface. It uses predefined geometric shapes (like cubes, spheres, and cylinders) and modifiers (like bevels, subdivisions, and extrusions) to assemble a detailed vehicle model.

Example

For a highly detailed, organic object such as a tree or a human figure, the user requests 'Generate a 3D human model with lifelike proportions and a realistic posture.'

Scenario

The tool generates point cloud data with a density of 200 points, distributing points across the surface of a base mesh. It then connects these points using Blender's algorithm to form a smooth and detailed mesh. The code also ensures that the points are properly scaled and aligned, resulting in a high-quality 3D model that can be further refined in Blender's sculpting tools.

Example

A user requests an architectural model of a building but is concerned about polygon count for performance purposes, saying 'Create a minimalistic house design with fewer polygons but still detailed enough for rendering.'

Scenario

The system generates an optimized mesh by using decimation techniques and applying LOD (Level of Detail) adjustments. It breaks down the structure into modular components (walls, windows, doors), simplifying geometry where needed while maintaining visual fidelity. The Python code also provides options for controlling the polygon count based on specific requirements, ensuring the model performs well in real-time applications.