This dataset contains randomly placed shapes with procedural textures for the purpose of measuring the correlation of texture frequency and solid structure in NeRF reconstructions.
The dataset is available at gs://kubric-public/data/texture_structure_nerf
sudo docker run --rm --interactive \
--user $(id -u):$(id -g) \
--volume "$(pwd):/kubric" \
kubricdockerhub/kubruntu \
/usr/bin/python3 \
examples/nerf_texture.py
Parameters:
num_objectsHow many objects to generate.num_frequency_bandsHow many discrete frequency bands to use.min_log_frequencyMinimum frequency value in log-scale (base 10).max_log_frequencyMaximum frequency value in log-scale (base 10).num_train_framesHow many frames to render in the training split.num_validation_framesHow many frames to render in the validation split.num_test_framesHow many frames to render in the testing split.
The script directly generates output that can be used as input by JAXNeRF with the 'blender' configuration. The resulting folder structure is:
[train|val|test]/*.pngRGB color images.[train|val|test]/*_segmentation.pngSegmentation maps indicating which frequency band a pixel belongs to.transforms_[train|val|test].jsonCamera information for each data split.