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3D building model edit with generative AI

Thesis

Overview

Two methods for 3D model edit with generative AI are presented here, including Image Control X-Mesh (XMeshimg) and Combination of X-Mesh and Text2Tex (Combination). They can produce high-quality 3D model edit results with geometric changes and texture creation. The proposed methods are especially suitable for low-fidelity inputs.

Image Control X-Mesh is modified from X-Mesh. Instead of text prompts, the method allows the user to use image prompts to guide the edit. The results can better follow the user control and be more realistic.

Combination of X-Mesh and Text2Tex takes advantage of both X-Mesh and Text2Tex. The edited geometry from X-Mesh is used as input for Text2Tex to provide richer depth information. It can generate smoother and more detailed textures.

Setup

The code is tested on Ubuntu 20.04.6 LTS with an NVIDIA GPU with 24 GB RAM.

To run Image Control X-Mesh:

# download the repository
git clone https://github.com/fengyingxin/MSc-Thesis.git

# setup the conda environment
conda env create --file environment.yml

# install other packages
pip install git+https://github.com/openai/CLIP.git
pip install kaolin==0.15.0 -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-1.12.1_cu113.html
pip install einops

# install gradio (if needed)
pip install gradio

To run Combination of X-Mesh and Text2Tex, first download the ControlNet Depth2img model (control_sd15_depth.pth) from the hugging face page, and put it under Combination/Text2Tex/models/ControlNet/models/.

Then follow the further steps:

# install PyTorch3D
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -c bottler nvidiacub
conda install pytorch3d -c pytorch3d

# install xformers
conda install xformers -c xformers

# install other packages
pip install -r requirements.txt

For further information about setup, see X-Mesh and Text2Tex.

Inputs

Mesh

The open-source tool MeshLab can be used for mesh preprocessing. The input mesh for both methods should meet the below requirements and example meshes used in the thesis are provided in Data:

  1. The Y-axis is up and the mesh should face towards +X. The Rotate function of MeshLab can be used.
  2. The mesh should be represented by small triangle faces. The Subdivision Surfaces function can be used.

The input mesh should look like the below image:

Image prompt (Image control X-Mesh)

Here are suggestions for image prompts and example images can be found in XMeshimg/prompt_image:

  1. The object should be complete and take up the majority of the image.
  2. Choose the image from a representative angle (e.g. the front view of a building) to give more useful control.
  3. Avoid the presence of barriers or irrelevant features.
  4. The image should be high enough in resolution and square (512*512 is ideal).

Text prompt (Combination of X-Mesh and Text2Tex)

Here are suggestions for text prompts and example texts can be found in Combination/prompt_text.txt:

  1. Specify details, like the type of the building, size, colour and material of key parts, additional features and the overall style.
  2. If needed, add keywords for more realistic style images, like 'unreal engine' or 'DSLR photo'.
  3. If needed, add keywords to get the complete architecture from the outside, like 'zoom-out' or 'exterior'.

Usage

Method 1: Image control X-Mesh

Run with command line

First check the XMeshimg/image_xmesh.py for all tunable parameters. You can change XMeshimg/bash/example.sh to meet your demand and use it for editing:

cd XMeshimg
./bash/example.sh

The final mesh result is named as ..._final.obj in the result folder.

Use gradio

To start a local gradio demo, run:

cd XMeshimg
python image_xmesh_gradio.py

Only major parameters are provided for tuning and the process results are automatically stored in outputs/xmeshimg folder. Below is a successful sample:

Method 2: Combination of X-Mesh and Text2Tex

Run with command line

First check the Combination/combination.py for all tunable parameters. You can change Combination/bash/example.sh to meet your demand and use it for editing:

cd Combination
./bash/example.sh

The final mesh result is named as ..._post.obj in the result folder.

Outputs

Complete results in the thesis can be found in Output folder. To transform the generated Obj files to GIF, this simple Obj2Gif tool can be used.

Below are examples from the Image Control X-Mesh and Combination of X-Mesh and Text2Tex methods:

Acknowledgement

The codes are based on X-Mesh and Text2Tex. Thanks for their excellent work!