- Multi-GPU training not work correctly
- GPUs do not have a consistent gaussian model after densification
- Slower than single GPU
Multi-GPU/Node training- Dynamic object mask
- Appearance variation support
- Load arbitrary number of images without OOM
- Interactive web viewer
- Load multiple models
- Model transform
- Scene editor
- Video camera path editor
- Video renderer
# clone repository
git clone --recursive https://github.com/yzslab/gaussian-splatting-lightning.git
cd gaussian-splatting-lightning
# if you forgot the `--recursive` options, you can run below git commands after cloning:
# git submodule sync --recursive
# git submodule update --init --recursive --force
# create virtual environment
conda create -yn gspl python=3.9 pip
conda activate gspl
# install the PyTorch first, you must install the one match to the version of your nvcc (nvcc --version)
# for cuda 11.7
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2
# for cuda 11.8
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
# install other requirements
pip install -r requirements.txt
# optional one, you can skip this one unless you want to train with appearance variation images
pip install ./submodules/tiny-cuda-nn-fp32/bindings/torch- Base
python main.py fit \
--data.path DATASET_PATH \
-n EXPERIMENT_NAME- With mask
--data.params.colmap.mask_dir MASK_DIR_PATH
- Load large dataset without OOM
--data.params.train_max_num_images_to_cache 1024
- Enable appearance model to train on appearance variation images
# 1. Generate appearance groups
python generate_image_apperance_groups.py PATH_TO_DATASET \
--camera \
--name appearance_group_by_camera
# 2. Enable appearance model
python main.py fit \
... \
--model.renderer AppearanceMLPRenderer \
--data.params.colmap.appearance_groups appearance_group_by_camera \
...
[IMPORTANT] Use config file configs/blender.yaml when training on blender dataset.
python main.py fit \
--config configs/blender.yaml \
--data.path DATASET_PATH \
-n EXPERIMENT_NAMEpython main.py fit \
--config configs/blender.yaml \
--trainer configs/ddp.yaml \
--data.path DATASET_PATH| Transform | Camera Path | Edit |
|---|---|---|
transform.mp4 |
animation.mp4 |
edit.mp4 |
- Base
python viewer.py TRAINING_OUTPUT_PATH
# e.g.:
# python viewer.py outputs/lego/
# python viewer.py outputs/lego/checkpoints/epoch=300-step=30000.ckpt
# python viewer.py outputs/lego/baseline/point_cloud/iteration_30000/point_cloud.ply # only works with VanillaRenderer- Load multiple models and enable transform options
python viewer.py \
outputs/garden \
outputs/lego \
outputs/Synthetic_NSVF/Palace/point_cloud/iteration_30000/point_cloud.ply \
--enable_transformThis repository is licensed under MIT license. Except some thirdparty dependencies (e.g. files in submodules directory), files and codes copied from other repositories, which are separately licensed.
MIT License
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