---
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