{ "cells": [ { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false }, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/plain": [ "Dataset({\n", " features: ['id', 'gender', 'masterCategory', 'subCategory', 'articleType', 'baseColour', 'season', 'year', 'usage', 'productDisplayName', 'image'],\n", " num_rows: 44072\n", "})" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load dataset\n", "import numpy\n", "\n", "# Load the dataset from huggingface datasets hub\n", "'''\n", "from datasets import load_dataset\n", "fashion = load_dataset(\n", " \"ashraq/fashion-product-images-small\",\n", " split=\"train\"\n", ")\n", "'''\n", "\n", "# Load from local path\n", "from datasets import load_from_disk\n", "dataset = load_from_disk(\"../fashion-product-images-small/dataset/\")\n", "dataset" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false }, "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "
\n", " | gender | \n", "masterCategory | \n", "subCategory | \n", "articleType | \n", "baseColour | \n", "season | \n", "year | \n", "usage | \n", "
---|---|---|---|---|---|---|---|---|
0 | \n", "Men | \n", "Apparel | \n", "Topwear | \n", "Shirts | \n", "Navy Blue | \n", "Fall | \n", "2011.0 | \n", "Casual | \n", "
1 | \n", "Men | \n", "Apparel | \n", "Bottomwear | \n", "Jeans | \n", "Blue | \n", "Summer | \n", "2012.0 | \n", "Casual | \n", "
2 | \n", "Women | \n", "Accessories | \n", "Watches | \n", "Watches | \n", "Silver | \n", "Winter | \n", "2016.0 | \n", "Casual | \n", "
3 | \n", "Men | \n", "Apparel | \n", "Bottomwear | \n", "Track Pants | \n", "Black | \n", "Fall | \n", "2011.0 | \n", "Casual | \n", "
4 | \n", "Men | \n", "Apparel | \n", "Topwear | \n", "Tshirts | \n", "Grey | \n", "Summer | \n", "2012.0 | \n", "Casual | \n", "