metadata

license: cc-by-4.0
pretty_name: IPD

Industrial Plenoptic Dataset (IPD)

To download the data and extract it into BOP format simply execute:

export SRC=https://huggingface.co/datasets/bop-benchmark/
wget $SRC/ipd/resolve/main/ipd_base.zip         # Base archive with camera parameters, etc.
wget $SRC/ipd/resolve/main/ipd_models.zip       # 3D object models.
wget $SRC/ipd/resolve/main/ipd_test_all.zip     # All test images part 1 
wget $SRC/ipd/resolve/main/ipd_test_all.z01     # All test  images part 2
wget $SRC/ipd/resolve/main/ipd_train_pbr.zip    # PBR training images

7z x ipd_base.zip             # Contains folder "ipd".
7z x ipd_models.zip -oipd     # Unpacks to "ipd".
7z x ipd_test_all.zip -oipd    # Unpacks to "ipd".
7z x ipd_test_all.zip -oipd   # Unpacks to "ipd".
7z x ipd_train_pbr.zip -oipd  # Unpacks to "ipd".

Dataset parameters

Objects: 10
Object models: Mesh models
Modalities: Three cameras are placed in each scene. Image, depth, angle of linear polarization (AOLP), and degree of linear polarization (DOLP) data are rendered for each camera.

Training PBR images splits

Scenes 000000–000004 contain objects 0, 8, 18, 19, 20.
Scenes 000005–000009 contain objects 1, 4, 10, 11, 14.

Dataset format

General information about the dataset format can be found in: https://github.com/thodan/bop_toolkit/blob/master/docs/bop_datasets_format.md

References

[1] Agastya Kalra, Guy Stoppi, Dmitrii Marin, Vage Taamazyan, Aarrushi Shandilya, Rishav Agarwal, Anton Boykov, Tze Hao Chong, Michael Stark; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 22691-22701