Update README.md

README.md

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 # Dataset Card for "smallnorb"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+**NOTE:** This dataset is an unofficial port of small NORB based on a [repo from Andrea Palazzi](https://github.com/ndrplz/small_norb) using this [script](https://colab.research.google.com/drive/1Tx20uP1PrnyarsNCWf1dN9EQyr38BDIE?usp=sharing). For complete and accurate information, we highly recommend visiting the dataset's original homepage.
+
+- **Homepage:** https://cs.nyu.edu/~ylclab/data/norb-v1.0-small/
+- **Paper:** https://ieeexplore.ieee.org/document/1315150
+
+### Dataset Summary
+
+From the dataset's [homepage](https://cs.nyu.edu/~ylclab/data/norb-v1.0-small/):
+
+> This database is intended for experiments in 3D object reocgnition from shape. It contains images of 50 toys belonging to 5 generic categories: four-legged animals, human figures, airplanes, trucks, and cars. The objects were imaged by two cameras under 6 lighting conditions, 9 elevations (30 to 70 degrees every 5 degrees), and 18 azimuths (0 to 340 every 20 degrees).
+>
+> The training set is composed of 5 instances of each category (instances 4, 6, 7, 8 and 9), and the test set of the remaining 5 instances (instances 0, 1, 2, 3, and 5).
+
+## Dataset Structure
+
+### Data Instances
+
+An example of an instance in this dataset:
+
+```
+{
+  'image_lt': <PIL.PngImagePlugin.PngImageFile image mode=L size=96x96 at 0x...>,
+  'image_rt': <PIL.PngImagePlugin.PngImageFile image mode=L size=96x96 at 0x...>,
+  'category': 0,
+  'instance': 8,
+  'elevation': 6,
+  'azimuth': 4,
+  'lighting': 4
+}
+```
+
+### Data Fields
+
+Explanation of this dataset's fields:
+
+- `image_lt`: a PIL image of an object from the dataset taken with one of two cameras
+- `image_rt`: a PIL image of an object from the dataset taken with one of two cameras
+- `category`: the category of the object shown in the images
+- `instance`: the instance of the category of the object shown in the images
+- `elevation`: the label of the elevation of the cameras used in capturing a picture of the object
+- `azimuth`: the label of the azimuth of the cameras used in capturing a picture of the object
+- `lighting`: the label of the lighting condition used in capturing a picture of the object
+
+For more information on what these categories and labels pertain to, please see [Dataset Summary](#dataset-summary) or the [repo](https://github.com/ndrplz/small_norb) used in processing the dataset.
+
+### Data Splits
+
+Information on this dataset's splits:
+
+|      | train | test  |
+|------|------:|------:|
+| size | 24300 | 24300 |
+
+## Additional Information
+
+### Dataset Curators
+
+Credits from the dataset's [homepage](https://cs.nyu.edu/~ylclab/data/norb-v1.0-small/):
+
+> [Fu Jie Huang](http://www.cs.nyu.edu/jhuangfu/), [Yann LeCun](http://yann.lecun.com/)
+> 
+> Courant Institute, New York University
+> 
+> October, 2005
+
+### Licensing Information
+
+From the dataset's [homepage](https://cs.nyu.edu/~ylclab/data/norb-v1.0-small/):
+
+> This database is provided for research purposes. It cannot be sold. Publications that include results obtained with this database should reference the following paper:
+> 
+> Y. LeCun, F.J. Huang, L. Bottou, Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) 2004
+
+### Citation Information
+
+From the dataset's [homepage](https://cs.nyu.edu/~ylclab/data/norb-v1.0-small/):
+
+> Publications that include results obtained with this database should reference the following paper:
+> 
+> Y. LeCun, F.J. Huang, L. Bottou, Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) 2004
+
+```
+@inproceedings{lecun2004learning,
+  title={Learning methods for generic object recognition with invariance to pose and lighting},
+  author={LeCun, Yann and Huang, Fu Jie and Bottou, Leon},
+  booktitle={Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.},
+  volume={2},
+  pages={II--104},
+  year={2004},
+  organization={IEEE}
+}
+```
+
+DOI: [10.1109/CVPR.2004.1315150](https://doi.org/10.1109/CVPR.2004.1315150)
+
+### Contributions
+
+Code to process small NORB adapted from [Andrea Palazzi's repo](https://github.com/ndrplz/small_norb) with this [script](https://colab.research.google.com/drive/1Tx20uP1PrnyarsNCWf1dN9EQyr38BDIE?usp=sharing).