part3_load_own_images.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# python notebook for Make Your Own Neural Network\n",
    "# code for a 3-layer neural network, and code for learning the MNIST dataset\n",
    "# (c) Tariq Rashid, 2016\n",
    "# license is GPLv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# helper to load data from PNG image files\n",
    "import imageio.v3\n",
    "# glob helps select multiple files using patterns\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy\n",
    "# library for plotting arrays\n",
    "import matplotlib.pyplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# our own image test data set\n",
    "our_own_dataset = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...  my_own_images/2828_my_own_3.png\n",
      "0.01\n",
      "0.97282356\n",
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      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.02164706 0.05270588 0.08376471 0.09541176\n",
      " 0.07600001 0.03329412 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.03329412 0.14200002 0.29729411\n",
      " 0.44870588 0.57682353 0.63505882 0.63894117 0.62341177 0.4875294\n",
      " 0.22352943 0.04882353 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.16529413 0.43705884 0.61952943 0.70105886 0.70494121 0.64282358\n",
      " 0.55741179 0.52247059 0.60011768 0.75929415 0.67000002 0.27011764\n",
      " 0.03717647 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.26623529 0.62341177\n",
      " 0.62341177 0.43705884 0.29729411 0.17305884 0.09541176 0.07211765\n",
      " 0.13423531 0.36329412 0.73211765 0.60788238 0.17305884 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.11482353 0.23517647 0.16141178 0.04494118\n",
      " 0.01       0.01       0.01       0.01       0.01       0.04494118\n",
      " 0.39435294 0.73988235 0.42152941 0.06435294 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.11482353 0.63505882\n",
      " 0.62341177 0.16917649 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.07988235 0.61564708 0.67000002 0.20023531\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01776471 0.02552941 0.03329412 0.09929412\n",
      " 0.37105882 0.7554118  0.5069412  0.09929412 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.1264706  0.31670588\n",
      " 0.43705884 0.472      0.49529412 0.58070588 0.73211765 0.62341177\n",
      " 0.22352943 0.01776471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.32835296 0.72435296 0.87576473 0.91458821\n",
      " 0.94952941 0.97282356 0.76705885 0.30894119 0.04494118 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.20411766 0.42541176 0.47588235 0.51858824 0.61952943 0.7709412\n",
      " 0.78258824 0.49917647 0.14200002 0.01       0.01       0.01\n",
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      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01388235 0.02552941\n",
      " 0.03717647 0.06047059 0.13811766 0.27400002 0.55352944 0.7709412\n",
      " 0.44870588 0.08376471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.1264706  0.60011768 0.71658826 0.26235294\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.30117649 0.7515294  0.4875294  0.04105882 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.08376471\n",
      " 0.60011768 0.66223532 0.09152941 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.04882353 0.04105882 0.01388235 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01776471 0.51858824 0.72047061\n",
      " 0.11482353 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.02941176 0.35164705\n",
      " 0.34388235 0.08764706 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.02164706 0.22741178 0.70882356 0.64282358 0.08376471 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.02941176 0.53023529 0.70882356 0.25847059\n",
      " 0.01388235 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.06823529 0.31282353 0.68552941\n",
      " 0.7437647  0.35164705 0.02941176 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.30505884 0.7515294  0.60788238 0.23517647 0.07211765\n",
      " 0.02164706 0.01       0.01       0.01       0.01776471 0.07211765\n",
      " 0.22741178 0.49141178 0.7554118  0.70494121 0.35552943 0.07988235\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.07988235\n",
      " 0.44482353 0.7554118  0.70882356 0.56517649 0.45647058 0.37882352\n",
      " 0.3477647  0.36329412 0.43705884 0.55741179 0.70882356 0.7631765\n",
      " 0.57682353 0.25458825 0.05270588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.11094118 0.34388235\n",
      " 0.55741179 0.67000002 0.72047061 0.7282353  0.72435296 0.7282353\n",
      " 0.7282353  0.68164706 0.55741179 0.35552943 0.1264706  0.02164706\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01388235 0.05270588 0.09929412\n",
      " 0.14588237 0.17694119 0.18858825 0.18082353 0.15752943 0.10705882\n",
      " 0.04882353 0.01776471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01      ]\n",
      "loading ...  my_own_images/2828_my_own_4.png\n",
      "0.01\n",
      "1.0\n",
      "[4.         0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.03717647\n",
      " 0.22741178 0.22741178 0.03717647 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.55352944 1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.27011764 1.         1.         1.         0.11870588 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.07988235 0.89517647 1.\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01388235 0.67000002 1.         1.         1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.37494117 1.\n",
      " 0.97282356 0.69717646 1.         1.         0.11870588 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.13811766 0.94952941 1.         0.44482353 0.53023529\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.02164706 0.7709412\n",
      " 1.         0.7437647  0.01776471 0.53023529 1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.4875294  1.         0.94176471 0.1264706\n",
      " 0.01       0.53023529 1.         1.         0.11870588 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.21576472\n",
      " 0.98447061 1.         0.36329412 0.01       0.01       0.53023529\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.05270588 0.85247058 1.         0.66611767\n",
      " 0.01388235 0.01       0.01       0.53023529 1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.60011768 1.         0.90294117 0.07988235 0.01       0.01\n",
      " 0.01       0.53023529 1.         1.         0.11870588 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.30894119 1.         1.\n",
      " 0.28564706 0.01       0.01       0.01       0.01       0.53023529\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.09929412 0.91847062 1.         0.58458823 0.01       0.01\n",
      " 0.01       0.01       0.01       0.53023529 1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.67388237 1.\n",
      " 0.9650588  0.37494117 0.33611766 0.33611766 0.33611766 0.33611766\n",
      " 0.33611766 0.68941176 1.         1.         0.40988237 0.33611766\n",
      " 0.33611766 0.01388235 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.82917649 1.         1.         1.\n",
      " 1.         1.         1.         1.         1.         1.\n",
      " 1.         1.         1.         1.         1.         0.01388235\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.82917649 1.         1.         1.         1.         1.\n",
      " 1.         1.         1.         1.         1.         1.\n",
      " 1.         1.         1.         0.01388235 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.08376471 0.09541176\n",
      " 0.09541176 0.09541176 0.09541176 0.09541176 0.09541176 0.09541176\n",
      " 0.09541176 0.57294118 1.         1.         0.19635296 0.09541176\n",
      " 0.09541176 0.01388235 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.53023529\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.53023529 1.         1.\n",
      " 0.11870588 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.53023529 1.         1.         0.11870588 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.53023529\n",
      " 1.         1.         0.11870588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.1264706  0.22741178 0.22741178\n",
      " 0.03717647 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01      ]\n"
     ]
    }
   ],
   "source": [
    "for image_file_name in glob.glob('my_own_images/2828_my_own_?.png'):\n",
    "    print (\"loading ... \", image_file_name)\n",
    "    # use the filename to set the correct label\n",
    "    label = int(image_file_name[-5:-4])\n",
    "    # load image data from png files into an array\n",
    "    img_array = imageio.v3.imread(image_file_name, mode='F')\n",
    "    # reshape from 28x28 to list of 784 values, invert values\n",
    "    img_data  = 255.0 - img_array.reshape(784)\n",
    "    # then scale data to range from 0.01 to 1.0\n",
    "    img_data = (img_data / 255.0 * 0.99) + 0.01\n",
    "    print(numpy.min(img_data))\n",
    "    print(numpy.max(img_data))\n",
    "    # append label and image data  to test data set\n",
    "    record = numpy.append(label,img_data)\n",
    "    print(record)\n",
    "    our_own_dataset.append(record)\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x130ae01a0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "matplotlib.pyplot.imshow(our_own_dataset[0][1:].reshape(28,28), cmap='Greys', interpolation='None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3.         0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.02164706 0.05270588 0.08376471 0.09541176\n",
      " 0.07600001 0.03329412 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.03329412 0.14200002 0.29729411\n",
      " 0.44870588 0.57682353 0.63505882 0.63894117 0.62341177 0.4875294\n",
      " 0.22352943 0.04882353 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.16529413 0.43705884 0.61952943 0.70105886 0.70494121 0.64282358\n",
      " 0.55741179 0.52247059 0.60011768 0.75929415 0.67000002 0.27011764\n",
      " 0.03717647 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.26623529 0.62341177\n",
      " 0.62341177 0.43705884 0.29729411 0.17305884 0.09541176 0.07211765\n",
      " 0.13423531 0.36329412 0.73211765 0.60788238 0.17305884 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.11482353 0.23517647 0.16141178 0.04494118\n",
      " 0.01       0.01       0.01       0.01       0.01       0.04494118\n",
      " 0.39435294 0.73988235 0.42152941 0.06435294 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.11482353 0.63505882\n",
      " 0.62341177 0.16917649 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.07988235 0.61564708 0.67000002 0.20023531\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01776471 0.02552941 0.03329412 0.09929412\n",
      " 0.37105882 0.7554118  0.5069412  0.09929412 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.1264706  0.31670588\n",
      " 0.43705884 0.472      0.49529412 0.58070588 0.73211765 0.62341177\n",
      " 0.22352943 0.01776471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.32835296 0.72435296 0.87576473 0.91458821\n",
      " 0.94952941 0.97282356 0.76705885 0.30894119 0.04494118 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.20411766 0.42541176 0.47588235 0.51858824 0.61952943 0.7709412\n",
      " 0.78258824 0.49917647 0.14200002 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01388235 0.02552941\n",
      " 0.03717647 0.06047059 0.13811766 0.27400002 0.55352944 0.7709412\n",
      " 0.44870588 0.08376471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.1264706  0.60011768 0.71658826 0.26235294\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.30117649 0.7515294  0.4875294  0.04105882 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.08376471\n",
      " 0.60011768 0.66223532 0.09152941 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.04882353 0.04105882 0.01388235 0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01776471 0.51858824 0.72047061\n",
      " 0.11482353 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.02941176 0.35164705\n",
      " 0.34388235 0.08764706 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.02164706 0.22741178 0.70882356 0.64282358 0.08376471 0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.02941176 0.53023529 0.70882356 0.25847059\n",
      " 0.01388235 0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.06823529 0.31282353 0.68552941\n",
      " 0.7437647  0.35164705 0.02941176 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.30505884 0.7515294  0.60788238 0.23517647 0.07211765\n",
      " 0.02164706 0.01       0.01       0.01       0.01776471 0.07211765\n",
      " 0.22741178 0.49141178 0.7554118  0.70494121 0.35552943 0.07988235\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.07988235\n",
      " 0.44482353 0.7554118  0.70882356 0.56517649 0.45647058 0.37882352\n",
      " 0.3477647  0.36329412 0.43705884 0.55741179 0.70882356 0.7631765\n",
      " 0.57682353 0.25458825 0.05270588 0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.11094118 0.34388235\n",
      " 0.55741179 0.67000002 0.72047061 0.7282353  0.72435296 0.7282353\n",
      " 0.7282353  0.68164706 0.55741179 0.35552943 0.1264706  0.02164706\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01388235 0.05270588 0.09929412\n",
      " 0.14588237 0.17694119 0.18858825 0.18082353 0.15752943 0.10705882\n",
      " 0.04882353 0.01776471 0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01       0.01\n",
      " 0.01       0.01       0.01       0.01       0.01      ]\n"
     ]
    }
   ],
   "source": [
    "print(our_own_dataset[0])"
   ]
  }
 ],
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