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IDesign

This is the official Github Repo for I-Design: Personalized LLM Interior Designer

Requirements

Install the requirements

bash

conda create -n idesign python=3.9
conda activate idesign
pip install -r requirements.txt
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch
pip install -U git+https://github.com/NVIDIA/MinkowskiEngine
conda install -c dglteam/label/cu113 dgl

Create the "OAI_CONFIG_LIST.json" file

json

[
    {
        "model": "gpt-4",
        "api_key": "YOUR_API_KEY"
    },
    {
        "model": "gpt-4-1106-preview",
        "api_key": "YOUR_API_KEY"
    },
    {
        "model": "gpt-3.5-turbo-1106",
        "api_key": "YOUR_API_KEY",
        "api_version": "2023-03-01-preview"
    }
]

Inference

Create the scene graph and allocate coordinate positions

python

from IDesign import IDesign

i_design = IDesign(no_of_objects = 15, 
                   user_input = "A creative livingroom", 
                   room_dimensions = [4.0, 4.0, 2.5])

# Interior Designer, Interior Architect and Engineer 
i_design.create_initial_design()
# Layout Corrector
i_design.correct_design()
# Layout Refiner
i_design.refine_design()
# Backtracking Algorithm
i_design.create_object_clusters(verbose=False)
i_design.backtrack(verbose=True)
i_design.to_json()

Retrieve the 3D assets from Objaverse using OpenShape

bash

git clone https://huggingface.co/OpenShape/openshape-demo-support
cd openshape-demo-support
pip install -e .
cd ..
python retrieve.py

Place the assets using the Blender Scripting Module using the script in the place_in_blender.py file

Evaluation

After creating scene renders in Blender, you can use the GPT-V evaluator to generate grades for evaluation. Fill in the necessary variables denoted with TODO and run the script

python gpt_v_as_evaluator.py

Results

MSheng-Lee/code