{ "cells": [ { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from PIL import Image\n", "image = np.load('pneumoniamnist.npz')\n", "x_train = image['train_images']\n", "x_label = image['train_labels']\n", "\n", "im1 = Image.fromarray(x_train[28])\n", "im0 = Image.fromarray(x_train[-20])\n", "\n", "im1.save('image_label_1.png')\n", "im0.save('image_label_0.png')" ] } ], "metadata": { "kernelspec": { "display_name": "modellib", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.15" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "dfa0523b1e359b8fd3ea126fa0459d0c86d49956d91b464930b80cba21582eac" } } }, "nbformat": 4, "nbformat_minor": 2 }