README.md

---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: domain
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': Alarm_Clock
          '1': Backpack
          '2': Batteries
          '3': Bed
          '4': Bike
          '5': Bottle
          '6': Bucket
          '7': Calculator
          '8': Calendar
          '9': Candles
          '10': Chair
          '11': Clipboards
          '12': Computer
          '13': Couch
          '14': Curtains
          '15': Desk_Lamp
          '16': Drill
          '17': Eraser
          '18': Exit_Sign
          '19': Fan
          '20': File_Cabinet
          '21': Flipflops
          '22': Flowers
          '23': Folder
          '24': Fork
          '25': Glasses
          '26': Hammer
          '27': Helmet
          '28': Kettle
          '29': Keyboard
          '30': Knives
          '31': Lamp_Shade
          '32': Laptop
          '33': Marker
          '34': Monitor
          '35': Mop
          '36': Mouse
          '37': Mug
          '38': Notebook
          '39': Oven
          '40': Pan
          '41': Paper_Clip
          '42': Pen
          '43': Pencil
          '44': Postit_Notes
          '45': Printer
          '46': Push_Pin
          '47': Radio
          '48': Refrigerator
          '49': Ruler
          '50': Scissors
          '51': Screwdriver
          '52': Shelf
          '53': Sink
          '54': Sneakers
          '55': Soda
          '56': Speaker
          '57': Spoon
          '58': TV
          '59': Table
          '60': Telephone
          '61': ToothBrush
          '62': Toys
          '63': Trash_Can
          '64': Webcam
  splits:
  - name: train
    num_bytes: 1300903275.02
    num_examples: 15588
  download_size: 1158984115
  dataset_size: 1300903275.02
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: other
license_name: fair-use-notice
license_link: https://www.hemanthdv.org/officeHomeDataset.html#:~:text=Fair%20Use%20Notice,Christopher%20Thomas)
size_categories:
- 10K<n<100K
---
# Dataset Card for Office-Home

The Office-Home dataset has been created to evaluate domain adaptation algorithms for object recognition using deep learning. It consists of images from 4 different domains: Artistic images, Clip Art, Product images and Real-World images. For each domain, the dataset contains images of 65 object categories found typically in Office and Home settings.

## Dataset Details

The dataset information is based on the original dataset website: https://www.hemanthdv.org/officeHomeDataset.html. 
This implementation is based on the shared data (images + a CSV file).

### Dataset Sources

- **Website:** https://www.hemanthdv.org/officeHomeDataset.html
- **Paper:** https://openaccess.thecvf.com/content_cvpr_2017/papers/Venkateswara_Deep_Hashing_Network_CVPR_2017_paper.pdf
- **Original Code:** https://github.com/hemanthdv/da-hash

## Use in FL

In order to prepare the dataset for the FL settings, we recommend using [Flower Dataset](https://flower.ai/docs/datasets/) (flwr-datasets) for the dataset download and partitioning and [Flower](https://flower.ai/docs/framework/) (flwr) for conducting FL experiments.

To partition the dataset, do the following. 
1. Install the package.
```bash
pip install flwr-datasets[vision]
```
2. Use the HF Dataset under the hood in Flower Datasets.
```python
from flwr_datasets import FederatedDataset
from flwr_datasets.partitioner import IidPartitioner

fds = FederatedDataset(
    dataset="flwrlabs/office-home",
    partitioners={"train": IidPartitioner(num_partitions=10)}
)
partition = fds.load_partition(partition_id=0)
```

## Dataset Structure

### Data Instances

The first instance of the train split is presented below:
```
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640>,
 'domain': 'Real World',
 'label': 0
}
```
### Data Split

```
DatasetDict({
    train: Dataset({
        features: ['image', 'domain', 'label'],
        num_rows: 15588
    })
})
```

## Implementation details
The CSV file from the original source contains paths to samples with a subfolder named "Clock"; 
however, such data does not exist. However, if counting this category, there would be 66 classes. 
I believe this class was forgotten to be edited because there's a different class present in the 
dataset named "Alarm-Clock". This state better reflects the number of samples specified in the paper.

## Citation

When working with the Office-Home dataset, please cite the original paper. 
If you're using this dataset with Flower Datasets and Flower, cite Flower.

**BibTeX:**

Original paper:
```
@inproceedings{venkateswara2017deep,
  title={Deep hashing network for unsupervised domain adaptation},
  author={Venkateswara, Hemanth and Eusebio, Jose and Chakraborty, Shayok and Panchanathan, Sethuraman},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={5018--5027},
  year={2017}
}
````

Flower:

```
@article{DBLP:journals/corr/abs-2007-14390,
  author       = {Daniel J. Beutel and
                  Taner Topal and
                  Akhil Mathur and
                  Xinchi Qiu and
                  Titouan Parcollet and
                  Nicholas D. Lane},
  title        = {Flower: {A} Friendly Federated Learning Research Framework},
  journal      = {CoRR},
  volume       = {abs/2007.14390},
  year         = {2020},
  url          = {https://arxiv.org/abs/2007.14390},
  eprinttype    = {arXiv},
  eprint       = {2007.14390},
  timestamp    = {Mon, 03 Aug 2020 14:32:13 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2007-14390.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
```

## Dataset Card Contact

If you have any questions about the dataset preprocessing and preparation, please contact [Flower Labs](https://flower.ai/).