Update README.md

README.md

@@ -1,3 +1,47 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+# SweepNet Dataset
+This repository contains three datasets used in SweepNet. One dataset comprised of 20,000 sweep surfaces for neural sweeper training and two datasets used in quantitative evaluations. All datasets are preprocessed.
+
+## Neural Sweeper Dataset
+We created 20,000 sweep surface samples to train the neural sweeper, please refer to the supplementary material for the training details. 
+We provided sweep surfaces with 3, 4 and 5 control points, structured as follows:
+```
+neuralSweeperData/
+├── control_point_i/
+│ ├── sweep_surface_index/
+│ │ ├── parameterse.txt # sweep surface parameters
+│ │ ├── bspline.ply #visualized sweeping axis
+│ │ ├── sample_profile.obj #visualized profile
+│ │ ├── result_sweep.ply # sweep surface
+│ │ ├── manifold_points.npy # key points on the sweep surface
+│ │ ├── sweep_occupancy_v1.npy # Occupancy field of the sweep surface
+```
+
+## GC-Object Dataset
+We sampled 50 generalised cylinder featured objects from internet and prior works [OreX](https://arxiv.org/abs/2211.12886), [GCD](https://vcc.tech/research/2015/GCD#:~:text=Our%20decomposition%20algorithm%20progressively%20builds,on%20decomposition%20to%20global%20optimization.).
+We provide processed 3D models here. Please consider cite us and the prior works if you find the dataset useful.
+```
+GC_objects/
+├── model name/
+│ ├── oracle.obj # Oracle 3D model (not the input)
+│ ├── voxel_64_mc.off # 3D model reconstructed from input voxel
+│ ├── skeletal_prior.ply # Model skeletons 
+│ ├── model_surface_point_cloud.ply # Surface point cloud for point cloud input modality
+├── test_names.npz # List of all model names
+├── voxel2pc.hdf5 # Model voxels and occupancy field used for training
+├── ae_voxel_points_samples.hdf5 # Model voxels and occupancy field used *only* for testing
+```
+## Quadrupeds Dataset
+We use quadrupeds dataset from [Tulsiani et al.](https://github.com/shubhtuls/volumetricPrimitives/issues/7) to benchmark SweepNet. We provide the processed data here, please cite us if you used our processed data.
+```
+quadrupeds/
+├── model name/
+│ ├── oracle.obj # Oracle 3D model (not the input)
+│ ├── skeletal_prior.ply # Model skeletons 
+│ ├── model_surface_point_cloud.ply # Surface point cloud for point cloud input modality
+├── test_names.npz # List of all model names
+├── voxel2pc.hdf5 # Model voxels and occupancy field used for training
+├── ae_voxel_points_samples.hdf5 # Model voxels and occupancy field used *only* for testing
+```