Update README.md

README.md

@@ -33,4 +33,116 @@ configs:
     path: data/train-*
   - split: test
     path: data/test-*
+license: unknown
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+
+# Dataset Card for USPS
+
+USPS is a digit dataset automatically scanned from envelopes by the U.S. Postal Service containing a total of 9,298 16×16 pixel grayscale samples.
+
+## Dataset Details
+
+The images are centered and normalized. They show a broad range of font styles.
+
+
+### Dataset Sources
+
+- **Repository:** train set https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/usps.bz2, test set: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/multiclass/usps.t.bz2
+- **Paper:** https://ieeexplore.ieee.org/abstract/document/291440
+
+## Uses
+
+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/usps",
+    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.PngImagePlugin.PngImageFile image mode=L size=16x16 at 0x133B4BA90>,
+  'label': 6
+}
+```
+### Data Split
+
+```
+DatasetDict({
+    train: Dataset({
+        features: ['image', 'label'],
+        num_rows: 7291
+    })
+    test: Dataset({
+        features: ['image', 'label'],
+        num_rows: 2007
+    })
+})
+```
+
+## Citation
+
+When working with the USPS dataset, please cite the original paper. 
+If you're using this dataset with Flower Datasets and Flower, cite Flower.
+
+**BibTeX:**
+
+Original paper:
+```
+@article{hull1994database,
+  title={A database for handwritten text recognition research},
+  journal={IEEE Transactions on pattern analysis and machine intelligence},
+  volume={16},
+  number={5},
+  pages={550--554},
+  year={1994},
+  publisher={IEEE}
+}
+````
+
+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
+
+In case of any doubts about the dataset preprocessing and preparation, please contact [Flower Labs](https://flower.ai/).