notebook/CIFAR10_Web_params.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# CIFAR-10 Webアプリのテスト用パラメータを作る"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 必要ライブラリ\n",
    "from keras.datasets import cifar10\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "from scipy.misc import toimage\n",
    "import numpy as np\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ラベル定義\n",
    "labels = ['airplane','automobile','bird','cat','deer','dog','frog','horse','ship','truck']\n",
    "# イメージデータ読み込み\n",
    "(x_train, y_train), (x_test, y_test) = cifar10.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Indexのシャフル\n",
    "indexes = list(range(len(y_test)))\n",
    "np.random.shuffle(indexes)\n",
    "indexes_sub = indexes[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4286, 3507, 8714, 1834, 4155, 824, 3565, 318, 5859, 7037]\n"
     ]
    }
   ],
   "source": [
    "print(indexes_sub)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 表示関数定義\n",
    "# Index番目のテストデータの画面表示と正解データ\n",
    "def disp_image(index):\n",
    "    a_ind = y_test[index].flat[0]\n",
    "    answer = labels[a_ind]\n",
    "    title = 'index:%d  %s  (%d)' % (index, answer, a_ind)\n",
    "    img = Image.fromarray(x_test[index])\n",
    "    plt.figure(figsize=(2,2))\n",
    "    plt.imshow(img)\n",
    "    plt.axis('off')\n",
    "    plt.title(title, fontsize=16)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Deep Learing WEBサービス\n",
    "# パラメータ作成関数\n",
    "#\n",
    "def get_param(index):\n",
    "    x_param1 = x_test[index].astype(\"float32\") / 255.0\n",
    "    x_param2 = x_param1.reshape( (1,) + x_param1.shape).tolist()\n",
    "    # print(x_param2.shape)\n",
    "    # print(x_param2)\n",
    "    params = {}\n",
    "    params['values'] = x_param2\n",
    "    return params    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471694fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"values\": [[[[0.24705882370471954, 0.42352941632270813, 0.545098066329956], [0.24313725531101227, 0.41960784792900085, 0.5411764979362488], [0.24705882370471954, 0.41960784792900085, 0.5411764979362488], [0.250980406999588, 0.42352941632270813, 0.545098066329956], [0.250980406999588, 0.4274509847164154, 0.5490196347236633], [0.250980406999588, 0.4274509847164154, 0.5490196347236633], [0.2549019753932953, 0.4274509847164154, 0.5490196347236633], [0.2549019753932953, 0.4274509847164154, 0.5490196347236633], [0.2549019753932953, 0.4274509847164154, 0.5490196347236633], [0.2549019753932953, 0.4313725531101227, 0.5529412031173706], [0.250980406999588, 0.43529412150382996, 0.5529412031173706], [0.2549019753932953, 0.43529412150382996, 0.5529412031173706], [0.2549019753932953, 0.43921568989753723, 0.5568627715110779], [0.2549019753932953, 0.43921568989753723, 0.5568627715110779], [0.25882354378700256, 0.43921568989753723, 0.5568627715110779], [0.25882354378700256, 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471648390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae4717a1be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"values\": [[[[0.4117647111415863, 0.5098039507865906, 0.34117648005485535], [0.3803921639919281, 0.5098039507865906, 0.32549020648002625], [0.35686275362968445, 0.47843137383461, 0.2862745225429535], [0.4274509847164154, 0.5098039507865906, 0.32549020648002625], [0.47843137383461, 0.5568627715110779, 0.3686274588108063], [0.38823530077934265, 0.49803921580314636, 0.2980392277240753], [0.3764705955982208, 0.47843137383461, 0.2862745225429535], [0.3921568691730499, 0.4901960790157318, 0.3019607961177826], [0.37254902720451355, 0.4627451002597809, 0.27843138575553894], [0.3686274588108063, 0.45490196347236633, 0.27843138575553894], [0.364705890417099, 0.46666666865348816, 0.30588236451148987], [0.19607843458652496, 0.2823529541492462, 0.16470588743686676], [0.13725490868091583, 0.20392157137393951, 0.12156862765550613], [0.3764705955982208, 0.45098039507865906, 0.3450980484485626], [0.4431372582912445, 0.545098066329956, 0.3764705955982208], [0.4156862795352936, 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae47179f518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471616f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471605588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471605cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471813630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"values\": [[[[0.29411765933036804, 0.25882354378700256, 0.1764705926179886], [0.3294117748737335, 0.2823529541492462, 0.18431372940540314], [0.3019607961177826, 0.239215686917305, 0.16470588743686676], [0.239215686917305, 0.16862745583057404, 0.13333334028720856], [0.18039216101169586, 0.10196078568696976, 0.09019608050584793], [0.18431372940540314, 0.10588235408067703, 0.09019608050584793], [0.16470588743686676, 0.0941176488995552, 0.0784313753247261], [0.13725490868091583, 0.07450980693101883, 0.054901961237192154], [0.12941177189350128, 0.0784313753247261, 0.054901961237192154], [0.1568627506494522, 0.10980392247438431, 0.08235294371843338], [0.21568627655506134, 0.14901961386203766, 0.12156862765550613], [0.1921568661928177, 0.12156862765550613, 0.09019608050584793], [0.1882352977991104, 0.10588235408067703, 0.0784313753247261], [0.21176470816135406, 0.11764705926179886, 0.09803921729326248], [0.23529411852359772, 0.13333334028720856, 0.11372549086809158], 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae471ffeeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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EnLd5QKQ9+cye+nZhQXLq/l7vnrCauQ9ccflFIl+RyaUHxqdE2to1PfXtITY5/5wtUqbsH/S8v7dHxijlk+m5t6lT36A862/wOKGAnJhSczKtVvZpC3N+0k6xOC/ytXf550gkXz8PGV9lHg09fWtFvm1Xvra+vevZ50Ta/j17kCVYC2AIGmYAhqCRGQrEZb9xNZGjf5WX9h7/X9kET3f7Zn1gjaclo+ecJ/K9/vv8t2D9c7tFWu8qf96W8/1o7Oi5cm5yV7evB6cygJxvy8dq9Rxavq8noohRVkWB2tt93nLRT/wpz0sK5Ga9TNnZ0SnL5wuJs3nWfAUeQHrOVlUYSRsJNhgyBDMAQ9DIDAU6eOhofftwTvKGwSHvhDZ1TEZ9rvR66nHypB+5LbP5wQAwPOzL6OraKtK6e7yD2gCbYNK3ql/ka2/3tEEvmCfWCXaJsZxB4NGn1aQdNmpcLsvxaj63uMLSqhU15zjv90/Nq5FgpgJ1962ubxdzek6wpznlklTdWlxf8IyBtQCGoGEGYAgaZgCGoJGZPsA4mwTT2SVDmxfLbNUTRUILbKLLiy96+XR4WMb+GRhgXpg9XSKtl01Saev0127Lyck35ZKXJrV0CHiuLFeZkbn4qi3VqkyssPCHJcXfq3zEl/UxnFpmhkur0p8UKC6wMtjEmapabHu+7PcrKmxiw+o6ZzisBTAEDTMAQ9DIDAUSwqGSGKcmvfOaHofk8uPhIz7038HDMiZOH3N4o5RmnI/o6gjNlZIfZc1BluFEvBy20ktJyrFVNsqqFUy+CkytKuVH7vTG5dJqTdKoHKNEbe2KwrHzZuc8xepUcux0weebn9cTYGwk2GDIDMwADEHDDMAQNDLTB6hWPHedPTUrE1kaX2URkDJjkcmUh8dk7M6tF/qYOJ3Kk5N7duaZTKkl13LZ8+GqctfgsmKJ8f5KqSCy8ThBOeWt2c72uSQKAIWCvzYvo61dSsY58hIv5ZK/f0XmReqUpHvsmJekdVygjHUBrAUwhA0zAEPQyA4FYnGB9PApXzxOt8FiETo2ojlzUo6kzjBP0ZFBudg28e8EG52tKo9M7qHZMCLKKFCx4ClcpSInrCyw0VgqqbCDPd5Ds6Q0Uh67qDDraVVHh/LWZOjslvOWqeafT4nJm05JqRNjXkKultVKNYlXOzNhLYAhaJgBGIKGGYAhaGSmD5Bjk8DJtbYIdWOa3z41I+XHY0eP17f7+yQ37lnd3DWipjwti0Vf5sJCsgyKCp+xpSKRMk/RqoobOl/xZdYU225v9xLpqVnuCiH7GKuZZNw2L90w2OKPIsZnQbk7TIx7GVT3D8wb1GDIEMwADEEjMxSI+CQSLba5ZPEtiR4tLEjqMT7uKdDIoAwF2MVCjBdXe9rQqVajmZvz8ma78rSssDCHxYIPXViak1Sso82fVyNJJ0olL9Xm2+QIb5mVPzntac8cC5MIACPOy5YdapS4xMJDgnmvLpTkMzx50t9nxubAN8BaAEPQMAMwBI3MUCDHaY4Kv0cin1NpLAwha7BrSr04eNhPlhlat0qk9fT6/fYu70zW19sr8h3ee6C+3dvbI9LyHf5bMzXlrzU7JVeZ6V/LrtUrneHE3GcV2Xl8wk8K2nPQx1CCkyO1bXl/3z3K2Y7PR+5h86CnZmQdC/OFpucAatQ8A8hWbQ2G0wwzAEPQMAMwBI3M9AFqjNunTXxvAMvMeb8O482lvRf2T4i0C7b6UOonJn3a9KQs49DefYnVyHf6R81HWUtqRZsii1m6uiJXeCyxPsDMKSmfPrvbe2hOHfcy6JpVUo5dWPB9gsKclIK7u32fIMdiLx1kwQQAoFr19chaOHQNawEMQcMMwBA0MkOBWnd4W1l5XGadm1cL0DEela95CnHipJQH9x7xo8lzBeloxuXCdjaC3KHewDxzVjt6XDqyzc15ujR5fFqkTR7n0qSvb7EoKdZCia38omIXtbFYQydm/ISh4yfkaLKUPtVzzNiUGGsBDEHDDMAQNMwADEHjVdEHaDVfWhpX8wpzcsL8sUnPt0fYgt2rVq8W+aaZrHj0mIxdlM/7C4j+QF7WKcfyVdXckhKbgF4uqdij3FWEyb3FknSFqLBJ/ZtGpMzayaTa/ePMY1XFIOrM8++m9szNln+otQCGoGEGYAgamaFAaeJarZY8D7XVkUqebW5Wyo97XjxU3x4e3lbf7u6VE0q6uvxC2c5J6ZATgzKjFHqyiVw9Rt4XD/tIDSEgXdPtmiqjymTcIba6JiBp2vMHvHdpA63J+Ogvh7UAhqBhBmAIGpmhQKIh19QAnBq0HjJFQIgo8pwjR3wk6bkFNie4Sy6m18EW0NP0hdgEFl5HIlU/RkOopl4PU3o07asJ6tScDgHAPFs0cHpaUr0upgJVKs3Le7XBWgBD0DADMAQNMwBD0MhMH6DKhMRcgyyXfF4Sf23sK7DJ82p1l+lZPzI8NeU9Ptf2yYnvxMVO0t6mCbxcxzRqHskxPi+Zl8vyk/MV5v1o9QRbfBwA+tgk/CKbqJNDchCCrMNaAEPQMAMwBI3sUCAW+q+RATFHszQZVMiPqiHni1Ar7lFk0ueRwz7mzrrVMn5QhYVXbpy3nEBLUijQctRHfj/8NFI14fLm9LR0+quy+cg19rwb6CK7gi4/a5KptQCGoGEGYAgaZgCGoJGZPkA3i7XZlpMLN3PPSO0iwCefcB6ezyeXUVUrv/BFqQ8c8nGBepQrBI+Xk1fh0WX80lrzBCj+3iClIhmiXyEKkXUUfRFZRKXKJ+Mw2bkhFuurRwi1FsAQNMwADEGDsiZbGQynE9YCGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGIKGGYAhaJgBGILG/wFbAJUGPdOhPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ae4717e6780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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0.16862745583057404], [0.35686275362968445, 0.33725491166114807, 0.3137255012989044], [0.5333333611488342, 0.49803921580314636, 0.45490196347236633], [0.27843138575553894, 0.26274511218070984, 0.26274511218070984], [0.1411764770746231, 0.13333334028720856, 0.16470588743686676], [0.14901961386203766, 0.14509804546833038, 0.1725490242242813], [0.1411764770746231, 0.13725490868091583, 0.16862745583057404], [0.13725490868091583, 0.12941177189350128, 0.1725490242242813], [0.13333334028720856, 0.125490203499794, 0.16862745583057404], [0.12941177189350128, 0.12156862765550613, 0.16862745583057404], [0.12941177189350128, 0.12156862765550613, 0.16470588743686676], [0.125490203499794, 0.11764705926179886, 0.16078431904315948], [0.12156862765550613, 0.11372549086809158, 0.1568627506494522], [0.11372549086809158, 0.10980392247438431, 0.14509804546833038], [0.10980392247438431, 0.10588235408067703, 0.13725490868091583], [0.12156862765550613, 0.10980392247438431, 0.14509804546833038], [0.21176470816135406, 0.1882352977991104, 0.1921568661928177], [0.25882354378700256, 0.22745098173618317, 0.2078431397676468], [0.16078431904315948, 0.14901961386203766, 0.16470588743686676], [0.07450980693101883, 0.0784313753247261, 0.11764705926179886], [0.0941176488995552, 0.09803921729326248, 0.125490203499794], [0.09803921729326248, 0.09803921729326248, 0.12941177189350128], [0.0941176488995552, 0.09019608050584793, 0.12156862765550613]], [[0.16470588743686676, 0.16078431904315948, 0.18431372940540314], [0.18039216101169586, 0.16862745583057404, 0.19607843458652496], [0.18431372940540314, 0.1725490242242813, 0.20392157137393951], [0.1764705926179886, 0.16470588743686676, 0.19607843458652496], [0.18431372940540314, 0.1725490242242813, 0.20392157137393951], [0.18039216101169586, 0.16862745583057404, 0.19607843458652496], [0.1921568661928177, 0.18039216101169586, 0.2078431397676468], [0.19607843458652496, 0.18431372940540314, 0.21568627655506134], [0.18431372940540314, 0.1764705926179886, 0.20392157137393951], [0.16862745583057404, 0.16078431904315948, 0.1882352977991104], [0.239215686917305, 0.22745098173618317, 0.22745098173618317], [0.3960784375667572, 0.3686274588108063, 0.3450980484485626], [0.2666666805744171, 0.250980406999588, 0.2549019753932953], [0.15294118225574493, 0.15294118225574493, 0.18431372940540314], [0.1568627506494522, 0.15294118225574493, 0.18431372940540314], [0.14509804546833038, 0.1411764770746231, 0.1764705926179886], [0.1411764770746231, 0.13333334028720856, 0.1764705926179886], [0.13333334028720856, 0.12941177189350128, 0.1725490242242813], [0.13333334028720856, 0.12941177189350128, 0.16862745583057404], [0.12941177189350128, 0.125490203499794, 0.16470588743686676], [0.125490203499794, 0.12156862765550613, 0.16078431904315948], [0.12156862765550613, 0.11372549086809158, 0.15294118225574493], [0.11372549086809158, 0.10588235408067703, 0.14509804546833038], [0.10980392247438431, 0.10980392247438431, 0.1411764770746231], [0.10980392247438431, 0.10588235408067703, 0.13725490868091583], [0.2078431397676468, 0.18431372940540314, 0.1921568661928177], [0.24313725531101227, 0.21568627655506134, 0.21176470816135406], [0.14901961386203766, 0.1411764770746231, 0.16078431904315948], [0.08235294371843338, 0.08235294371843338, 0.12156862765550613], [0.09803921729326248, 0.09803921729326248, 0.12941177189350128], [0.09803921729326248, 0.09803921729326248, 0.12941177189350128], [0.0941176488995552, 0.09019608050584793, 0.12156862765550613]]]]}\n"
     ]
    }
   ],
   "source": [
    "for index in indexes_sub:\n",
    "    disp_image(index)\n",
    "    print(json.dumps(get_param(index)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.5",
   "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": "3.5.4"
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 },
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}