This is an implementation of Instant NGP using Pytorch Lightning.
Currently, the supported tasks are Neural gigapixel images and Neural SDF. NeRF is in progress.
conda env update -f environment.yml
conda activate ngp
git lfs install && git lfs pull # to get sample data
Additionally, you may want to build the SDFGen tool if you wish to train Neural SDFs. This is not required, but the resulting SDFs are of higher quality, with fewer artifacts.
For gigapixel images, the script accepts either standard PNG/JPG images or uncompressed EXR images. For SDFs, the script accepts either the output of the SDFGen tool (above) or an OBJ file. If an OBJ file is provided, the SDF is directly sampled from the mesh.
Usage: main.py [OPTIONS]
Options:
--input-data PATH Path to input data [required]
--task [sdf|gigapixel] Task to perform [required]
--batch-size INTEGER Batch size
--output-path PATH Output path for generated artifacts
--model-path PATH Path of pretrained model to run inference with
--help Show this message and exit.
SDF:
python3 main.py --input-data data/sdf/dragon.obj --task sdf --batch-size 4096
Gigapixel:
python3 main.py --input-data data/image/yosemite.jpg --task gigapixel --batch-size 32768