Dollar street 10 - 64x64x3

<p>The MLCommons Dollar Street Dataset is a collection of images of everyday household items from homes around the world that visually captures socioeconomic diversity of traditionally underrepresented populations. It consists of public domain data, licensed for academic, commercial and non-commercial usage, under CC-BY and CC-BY-SA 4.0. The dataset was developed because similar datasets lack socioeconomic metadata and are not representative of global diversity.</p> <p>This is a subset of the original dataset that can be used for multiclass classification with 10 categories. It is designed to be used in teaching, similar to the widely used, but unlicensed CIFAR-10 dataset.</p> <p>These are the preprocessing steps that were performed:</p> <ol> <li>Only take examples with one imagenet_synonym label</li> <li>Use only examples with the 10 most frequently occuring labels</li> <li>Downscale images to 64 x 64 pixels</li> <li>Split data in train and test</li> <li>Store as numpy array</li> </ol> <p>This is the label mapping:</p> <table> <tbody> <tr> <td><strong>Category</strong></td> <td><strong>label</strong></td> </tr> <tr> <td>day bed</td> <td>0</td> </tr> <tr> <td>dishrag</td> <td>1</td> </tr> <tr> <td>plate</td> <td>2</td> </tr> <tr> <td>running shoe</td> <td>3</td> </tr> <tr> <td>soap dispenser</td> <td>4</td> </tr> <tr> <td>street sign</td> <td>5</td> </tr> <tr> <td>table lamp</td> <td>6</td> </tr> <tr> <td>tile roof</td> <td>7</td> </tr> <tr> <td>toilet seat</td> <td>8</td> </tr> <tr> <td>washing machine</td> <td>9</td> </tr> </tbody> </table> <p>Checkout <a title="data preparation notebook" href="https://github.com/carpentries-lab/deep-learning-intro/blob/main/instructors/prepare-dollar-street-data.ipynb" target="_blank" rel="noopener">this notebook</a> to see how the subset was created.</p> <p>The original dataset was downloaded from https://www.kaggle.com/datasets/mlcommons/the-dollar-street-dataset. See https://mlcommons.org/datasets/dollar-street/ for more information.</p>