saba99 / 3DSceneGeneration

3D Scene Generation from 2D Images

3D Scene Generation from 2D Images

Installation

You can setup the required environment by the following commands:

# install python dependencies
conda env create -f environment.yaml
conda activate scenedreamer

# compile third party libraries
export CUDA_VERSION=$(nvcc --version| grep -Po "(\d+\.)+\d+" | head -1)
CURRENT=$(pwd)
for p in correlation channelnorm resample2d bias_act upfirdn2d; do
    cd imaginaire/third_party/${p};
    rm -rf build dist *info;
    python setup.py install;
    cd ${CURRENT};
done

for p in gancraft/voxlib; do
  cd imaginaire/model_utils/${p};
  make all
  cd ${CURRENT};
done

cd gridencoder
python setup.py build_ext --inplace
python -m pip install .
cd ${CURRENT}

# Now, all done!

Inference

Download Pretrained Models

Please download our checkpoints from Google Drive to run the following inference scripts. You may store the checkpoint at the root directory of this repo:

├── ...
└── SceneDreamer
    ├── inference.py
    ├── README.md
    └── scenedreamer_released.pt

Render!

You can run the following command to generate your own 3D world!

python inference.py --config configs/scenedreamer_inference.yaml --output_dir ./test/ --seed 8888 --checkpoint ./scenedreamer_released.pt

The results will be saved under ./test as the following structures:

├── ...
└── test
    └── camera_{:02d} # camera mode for trajectory
        ├── rgb_render # per frame RGB renderings
            ├── 00000.png
            ├── 00001.png
            └── ...
        ├── rgb_render.mp4 # rendered video
        ├── height_map.png # height map
        ├── semantic_map.png # semantic map
        └── style.npy # sampled style code

Here is a sampled scene with my default rendering parameters:

rgb_render.2.mp4

Gradio Demo

You can also locally launch demo with gradio UI by:

python app_gradio.py