{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Image Browser" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This example shows how to browse through a set of images with a slider." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from ipywidgets import interact" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn import datasets" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use the digits dataset from [scikit-learn](http://scikit-learn.org/stable/)." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ "digits = datasets.load_digits()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def browse_images(digits):\n", " n = len(digits.images)\n", " def view_image(i):\n", " plt.imshow(digits.images[i], cmap=plt.cm.gray_r, interpolation='nearest')\n", " plt.title('Training: %s' % digits.target[i])\n", " plt.show()\n", " interact(view_image, i=(0,n-1))" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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