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---
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.z01 -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 |