---
license: apache-2.0
task_categories:
- image-feature-extraction
- image-classification
- image-to-3d
- image-segmentation
size_categories:
- 1M<n<10M
---


## Dataset Details

This dataset derives from [Coil100](https://huggingface.co/datasets/Voxel51/COIL-100). 
There are more than 1,1M images of 100 objects. Each object was turned on a turnable through 360 degrees to vary object pose with respect to a fixed color camera. Images of the objects were taken at pose intervals of 5 degrees. This corresponds to 72 poses per object. 

*In addition* to the original dataset, planar rotation (9 angles) and  18 scaling factors have been applied so that there are no dependencies between factors.
Objects have a wide variety of complex geometric and reflectance characteristics.

 
This augmented version of Coil100 has been designed especially for Disentangled Representation Learning for real images, the Factors of Variations are:

| Factors  | # values |
|----------|----------|
| Object   | 100      |
| 3D Pose  | 72       |
| Rotation | 9        |
| Scale    | 18       |


The binarized version is also available.


## How to download

With Python > 3.0 install 
  ```
pip install huggingface_hub
```

Then to download the RGB dataset run 
```
python download_coil100.py
```

And if you want the binary version run
```
python download_coil100_binary.py
```


## Citation

if you use the dataset, please cite us:

**BibTeX:**
```bibtex
@article{dapueto2024transferring,
  title={Transferring disentangled representations: bridging the gap between synthetic and real images},
  author={Dapueto, Jacopo and Noceti, Nicoletta and Odone, Francesca},
  journal={arXiv preprint arXiv:2409.18017},
  year={2024}
}
```

## Uses

This dataset is intended for non-commercial research purposes only. 

## Dataset Card Authors

[Jacopo Dapueto](https://huggingface.co/dappu97)