kishazi_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Az eredeti kepek:\n"
     ]
    },
    {
     "data": {
      "image/png": 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MgE+XHzcCeAPAtGofk8g8qnpMABiAhvLjGgCLABzb38djMO78MwGscPe33b0T\nwP0oFQNNBnd/FsCeHTWrXhCVzKPquPtad19SfrwNwHIAY1HlYxKZR1XxEgNeNHcwnH8sgFW7/L0a\ng3CAyziAhWa22MxmD9IcPmJfKoh6lZktLX8tGPCvH7tiZhNQqh8xqEVi95gHUOVjUo2iuakv+J3g\npcKkZwC4wsxOGuwJAfGCqFXgxyh9JZsBYC2AW6u1YzNrAPALANe6+9ZdtWoek8A8qn5MvA9Fcytl\nMJx/DYBdW7OMK49VHXdfU/5/PYBHUPpKMlhUVBB1oHH3deUTrxvAnajSMTGzGpQc7l53f7g8XPVj\nEprHYB2T8r73umhupQyG878AYIqZHWJmeQBfRakYaFUxs6Fm1vjRYwCnAVgWtxpQ9omCqB+dXGXO\nQxWOiZUKOM4FsNzdv7+LVNVjwuZR7WNStaK51VrB3GM180yUVlLfAvDfBmkOE1GKNLwM4NVqzgPA\nfSh9fOxCac3jMgCjUGp79iaAhQBGDtI87gHwCoCl5ZNtTBXmcQJKH2GXAnip/O/Mah+TyDyqekwA\nfArAi+X9LQPwN+Xxfj0e+oWfEImS+oKfEMki5xciUeT8QiSKnF+IRJHzC5Eocn4hEkXOL0SiyPmF\nSJT/BxlTfa4p1ULbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbce03400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbadfef98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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ZIvELkSkSvxCZIvELkSkSvxCZMtACnigKgBR2rAZZfSAuiQ1xuwbz3HapneIW28IJbnt9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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbab55470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AXhde5O67AFw2+6GEEMcT+oWfEIki5xciUeT8QiSKnF+IRJHzC5EoNv3jvC4N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\nipxfiESR8wuRKHJ+IRJFzi9Eovw/s4wkAwpSQjcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbb03c978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbce7bbe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[252 255 255]\n",
      "  [254 249 246]\n",
      "  [255 255 251]\n",
      "  ..., \n",
      "  [255 248 248]\n",
      "  [254 255 253]\n",
      "  [255 251 255]]\n",
      "\n",
      " [[252 255 255]\n",
      "  [255 254 250]\n",
      "  [254 255 251]\n",
      "  ..., \n",
      "  [211 212 206]\n",
      "  [242 255 253]\n",
      "  [252 253 255]]\n",
      "\n",
      " [[251 255 250]\n",
      "  [255 254 247]\n",
      "  [253 255 252]\n",
      "  ..., \n",
      "  [144 146 141]\n",
      "  [239 250 246]\n",
      "  [255 250 255]]\n",
      "\n",
      " ..., \n",
      " [[255 255 255]\n",
      "  [254 254 254]\n",
      "  [252 252 252]\n",
      "  ..., \n",
      "  [252 252 252]\n",
      "  [255 255 255]\n",
      "  [255 255 255]]\n",
      "\n",
      " [[255 255 255]\n",
      "  [254 254 254]\n",
      "  [252 252 252]\n",
      "  ..., \n",
      "  [255 255 255]\n",
      "  [255 255 255]\n",
      "  [253 253 253]]\n",
      "\n",
      " [[255 255 255]\n",
      "  [255 255 255]\n",
      "  [255 255 255]\n",
      "  ..., \n",
      "  [251 251 251]\n",
      "  [255 255 255]\n",
      "  [253 253 253]]]\n",
      "A cat.jpg kepen az atlag az R csatornan 208.585938, az szoras 60.950419\n",
      "A cat.jpg kepen az atlag az G csatornan 203.217773, az szoras 65.124224\n",
      "A cat.jpg kepen az atlag az B csatornan 198.659180, az szoras 71.312226\n",
      "[[[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]\n",
      "\n",
      " [[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]\n",
      "\n",
      " [[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]\n",
      "\n",
      " ..., \n",
      " [[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]\n",
      "\n",
      " [[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]\n",
      "\n",
      " [[252  15   0]\n",
      "  [255  38   0]\n",
      "  [255  69   0]\n",
      "  ..., \n",
      "  [  1  71 254]\n",
      "  [  1  40 255]\n",
      "  [  0  15 253]]]\n",
      "A gradient.jpg kepen az atlag az R csatornan 109.937500, az szoras 112.721431\n",
      "A gradient.jpg kepen az atlag az G csatornan 182.062500, az szoras 83.826062\n",
      "A gradient.jpg kepen az atlag az B csatornan 109.125000, az szoras 112.756305\n",
      "[[[241 255 255]\n",
      "  [255 230 236]\n",
      "  [255 240 245]\n",
      "  ..., \n",
      "  [255 240 245]\n",
      "  [255 230 236]\n",
      "  [241 255 255]]\n",
      "\n",
      " [[254 229 235]\n",
      "  [255 184 207]\n",
      "  [255 189 210]\n",
      "  ..., \n",
      "  [255 189 210]\n",
      "  [255 184 207]\n",
      "  [254 229 235]]\n",
      "\n",
      " [[255 241 243]\n",
      "  [255 189 208]\n",
      "  [254 190 207]\n",
      "  ..., \n",
      "  [254 190 207]\n",
      "  [255 189 208]\n",
      "  [255 241 243]]\n",
      "\n",
      " ..., \n",
      " [[255 241 243]\n",
      "  [255 189 208]\n",
      "  [254 190 207]\n",
      "  ..., \n",
      "  [254 190 207]\n",
      "  [255 189 208]\n",
      "  [255 241 243]]\n",
      "\n",
      " [[255 230 236]\n",
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      "  [255 190 211]\n",
      "  ..., \n",
      "  [255 190 211]\n",
      "  [255 185 208]\n",
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      "\n",
      " [[241 255 255]\n",
      "  [254 229 235]\n",
      "  [255 240 245]\n",
      "  ..., \n",
      "  [255 240 245]\n",
      "  [254 229 235]\n",
      "  [241 255 255]]]\n",
      "A heart.jpg kepen az atlag az R csatornan 236.253906, az szoras 42.173539\n",
      "A heart.jpg kepen az atlag az G csatornan 147.674805, az szoras 75.282260\n",
      "A heart.jpg kepen az atlag az B csatornan 158.375977, az szoras 80.557738\n",
      "[[[255 255 239]\n",
      "  [255 253 255]\n",
      "  [251 251 255]\n",
      "  ..., \n",
      "  [240 254 254]\n",
      "  [252 255 251]\n",
      "  [254 250 239]]\n",
      "\n",
      " [[255 247 255]\n",
      "  [244 247 255]\n",
      "  [136 144 219]\n",
      "  ..., \n",
      "  [177 117 213]\n",
      "  [255 230 255]\n",
      "  [255 254 255]]\n",
      "\n",
      " [[250 249 255]\n",
      "  [144 141 222]\n",
      "  [ 76  75 202]\n",
      "  ..., \n",
      "  [151  42 195]\n",
      "  [180 116 203]\n",
      "  [248 252 255]]\n",
      "\n",
      " ..., \n",
      " [[247 252 255]\n",
      "  [245 208 119]\n",
      "  [255 184  85]\n",
      "  ..., \n",
      "  [214  38 111]\n",
      "  [237 106 160]\n",
      "  [250 247 254]]\n",
      "\n",
      " [[249 254 250]\n",
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      "  [232 206 122]\n",
      "  ..., \n",
      "  [235 107 158]\n",
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      "\n",
      " [[249 255 251]\n",
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      "  [255 254 255]\n",
      "  ..., \n",
      "  [245 255 255]\n",
      "  [255 253 255]\n",
      "  [255 253 252]]]\n",
      "A insta.jpg kepen az atlag az R csatornan 214.225586, az szoras 46.072536\n",
      "A insta.jpg kepen az atlag az G csatornan 123.886719, az szoras 79.988298\n",
      "A insta.jpg kepen az atlag az B csatornan 154.431641, az szoras 67.819608\n",
      "[[[238 250 236]\n",
      "  [237 245 234]\n",
      "  [244 249 242]\n",
      "  ..., \n",
      "  [255 252 236]\n",
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      "\n",
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      "  ..., \n",
      "  [231 255 237]\n",
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      "\n",
      " [[254 245 248]\n",
      "  [251 255 255]\n",
      "  [252 247 254]\n",
      "  ..., \n",
      "  [255 252 255]\n",
      "  [255 245 255]\n",
      "  [234 244 220]]\n",
      "\n",
      " ..., \n",
      " [[234 251 255]\n",
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      "  ..., \n",
      "  [177  38 105]\n",
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      "\n",
      " [[248 250 237]\n",
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      "  ..., \n",
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      "\n",
      " [[232 237 240]\n",
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      "  [254 243 247]\n",
      "  ..., \n",
      "  [190  40 127]\n",
      "  [140  41  96]\n",
      "  [255 251 244]]]\n",
      "A pinkie.jpg kepen az atlag az R csatornan 225.541992, az szoras 45.525300\n",
      "A pinkie.jpg kepen az atlag az G csatornan 161.206055, az szoras 88.313570\n",
      "A pinkie.jpg kepen az atlag az B csatornan 194.791992, az szoras 59.403486\n",
      "A cat.jpg kep atalakitva:\n",
      "A kep R csatornajan a szoras 1.000000, a varhatoertek -0.000000\n",
      "A kep G csatornajan a szoras 1.000000, a varhatoertek 0.000000\n",
      "A kep B csatornajan a szoras 1.000000, a varhatoertek -0.000000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fbenedek/anaconda3/lib/python3.5/site-packages/sklearn/utils/validation.py:444: DataConversionWarning: Data with input dtype uint8 was converted to float64 by StandardScaler.\n",
      "  warnings.warn(msg, DataConversionWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbb406160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A gradient.jpg kep atalakitva:\n",
      "A kep R csatornajan a szoras 0.000000, a varhatoertek 0.000000\n",
      "A kep G csatornajan a szoras 0.000000, a varhatoertek 0.000000\n",
      "A kep B csatornajan a szoras 0.000000, a varhatoertek 0.000000\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbb3c7438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A heart.jpg kep atalakitva:\n",
      "A kep R csatornajan a szoras 1.000000, a varhatoertek 0.000000\n",
      "A kep G csatornajan a szoras 1.000000, a varhatoertek 0.000000\n",
      "A kep B csatornajan a szoras 1.000000, a varhatoertek 0.000000\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbadebf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A insta.jpg kep atalakitva:\n",
      "A kep R csatornajan a szoras 1.000000, a varhatoertek -0.000000\n",
      "A kep G csatornajan a szoras 1.000000, a varhatoertek 0.000000\n",
      "A kep B csatornajan a szoras 1.000000, a varhatoertek 0.000000\n"
     ]
    },
    {
     "data": {
      "image/png": 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XR8Z2Uu1JPXj6Kvx8PiQvuNt8qiV07km1qM71VG51IDMPK/g6th/i94D03BKq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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbacf71d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A pinkie.jpg kep atalakitva:\n",
      "A kep R csatornajan a szoras 1.000000, a varhatoertek -0.000000\n",
      "A kep G csatornajan a szoras 1.000000, a varhatoertek -0.000000\n",
      "A kep B csatornajan a szoras 1.000000, a varhatoertek 0.000000\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbcc94470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "#képek beolvasása\n",
    "\n",
    "imgname=['cat.jpg','gradient.jpg','heart.jpg','insta.jpg','pinkie.jpg']\n",
    "print(\"Az eredeti kepek:\") #eredeti képek megjelítése matplotlibbel és beolvasása az images[] tömbbe\n",
    "images=[]\n",
    "for i in range (5):\n",
    "    images.append((mpimg.imread(imgname[i]))) #hozzádom a tömkbhöz\n",
    "    plt.imshow(images[i]) #megjelenítés\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "\n",
    "mean=np.zeros((5,3)) #átlagok tárolására \n",
    "deviation=np.zeros((5,3)) #szórások tárolására\n",
    "rgb=['R','G','B'] \n",
    "for j in range (5):\n",
    "    print(images[j]) #j-edik kép nyomtatása np arrayként\n",
    "    for i in range (3):\n",
    "        mean[j][i]=images[j][:,:,i].mean() #pixelek átlaga a j-edik kép i-edik csatornáján\n",
    "        deviation[j][i]=np.std(images[j][:,:,i]) #pixelek szórása a j-edik kép i-edik csatornáján\n",
    "        print(\"A %s kepen az atlag az %s csatornan %f, az szoras %f\" %(imgname[j],rgb[i], mean[j][i], deviation[j][i]))\n",
    "\n",
    "#átalakítás 0 várhatóértékű, 1 szórású adathalmazzá\n",
    "scaler=StandardScaler()\n",
    "img_scaled=np.zeros((32,32,3,5), dtype=np.float) #scaled kép mátrixának feltöltése \n",
    "for j in range (5):\n",
    "    print(\"A %s kep atalakitva:\" %(imgname[j]))\n",
    "    for i in range (3):\n",
    "        scaler.fit(images[j][:,:,i]) #eredeti átlag és szórás kiszámítása a .transform()-hoz\n",
    "        img_scaled[:,:,i,j]=scaler.transform(images[j][:,:,i]) #scaler alkalmazása a j-edik kép i-edik csatornájára\n",
    "        print(\"A kep %s csatornajan a szoras %f, a varhatoertek %f\" %(rgb[i], np.std(img_scaled[:,:,i,j]), img_scaled[:,:,i,j].mean()))\n",
    "    plt.imshow(img_scaled[:,:,:,j]) #átalakított kép megjelenítése\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fbenedek/anaconda3/lib/python3.5/site-packages/scipy/io/wavfile.py:273: WavFileWarning: Chunk (non-data) not understood, skipping it.\n",
      "  WavFileWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A spektrogram:\n"
     ]
    },
    {
     "data": {
      "image/png": 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SWavU2UvVvdO1X93TvI8QA91TqcQVDR/dgMclPVUOquHRwsuX9Iz8zT8Q+qdL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LvB841Fx3vFg6+mTnTeHZZmFGb46ALCV+GBd0Moe8MLjuAsqlitxhHVBLhU/i/wsqgrMRuKUL\nWugujJWoYYM3nqJfk+tIyfRecGs6Z5KWzJuctogK0dmsRzGsSI2lNo5+VnP0aAczrtHGYSvNxhl6\nusb6qJrcS5YY4Vi5jEI1GOGovOF35m9Re8Wv73+PNmjup6dUIeGTap/DZMbLesR+skAR+NH6Brey\nWRyJBMNYlByYBa5LdMpky8YZLmyPu8k5n9V7rFzKWTvgoFhgg6J2mjd7x+zqJfM857P1Du9NnqGF\nZ90mvDgZk41qKhVQieds0WOmc76wd0wiHYmKo5l5mTMalZwtemjjaBpNUdR4J/nR5T7LTUaetExG\naz4638M5SS9rKJKWo+WAECI3f1bl1FZzsurTSxusl1zWBWerHk+Op7x75wU+CL5/dMiN8QKjPI2N\nG8jpRaRwrqqUECDkDlXE8VJuWgrdsJ8u+a3nb/LF3Ze8lp1x0g7ZNwtO2iGHxuKCjJuubDFiiUPS\nBsW99IyZi340V5x9h0QJz29cfpFvjD/kvd4Tvre5TRsU99NT/q39P8EhO1D+fGvFfGqHrDpr4wfZ\nKVJ4vjb4jDM7ZOky1jrl7ew5bdDMXMENPedxE8H3XbNE4XnW7jLRa74x/Yg2aD6sDjkw0QiuCZod\ntUIRqILBpZK1T5maaMR2d3pJ7aIVNkQ7ayFATSuq0zxSWyWgPGqmsSOHkIEQZAfeC2Ri8Y1EbuIq\n3kxcp9qFTHmKXk3r1JbzjwngQ1SvqzjmILxaJEXoxq6ve1TqcKki7MQgoHKeI+eakMeFLuiOMt3R\nIpFxpFQYR+MTZOo6s0NQC40bOEQdGzwCNMPY4OlSvBqNqMihJ0RSB7KzbR55cOAGjk165S3UjYU2\nsnudopQ3mLhp0W+xwcR15QoENnGhDkaQXCpc5tEXBpfFhd1OLAhJ2+ucAPL4PIMX2LElPTLUexZM\nwJzpuC5+jroe6VzXdV3Xdf2c1M9uwZfQeybBRGAnJAG5UtugAVVB8djEoxmg1x2tK4vCKpdHHxwB\ncacl7tD6UiO6bqIdx2OXK3x05TTxxKCXMnYInTWsk38c2QAAIABJREFUcOIVENNK8n6NUY51m3C3\nf8mgiN1+5SLAVlnNfrHk3bsvyJIWrTw3RkuUCPRvrEhSy+5gzd7BHE+Mn5s3Gd+fH+I7xKqvKh6m\nxyji87NB8kujzzhrB3xS7TF3MTv11wY/xAfJ+4MnPK2m/LA85J3+C55sJryWnQHwop3QBsXzekIq\nLZ/W+7RekckWJTx303O+1H9GoWpuZzO+0n/E0qZbsdDLasS7wxdMTIkQgXG24WBvTt5l+tJlzB4M\nl6zalPOqx2VVcLEpWM9yGquj35BVhI6a11aaRZnRtgofoG51FFxVhtmi4GTWZ1JsSBJHZTWniz7r\nNqFuNYsqpUhaLtYF60XG64dnHJfx9lEvWv7WbTycJtoyHGzQ0hMCpMZuOy8eFexka3LV8rvHr/NL\nB4+5lc22CtodteJ+espYlSx9jhJhC9AqPDsq+g4Z4Rirkn21ZEev+ObiPlJ4vjH+kDvmnLFac2hm\n/ErvYwpZU8iasVrzXvYkunGaS/b0gjYoHqbH/PH6AYWseTd7ynvZE741v8dIl/yDo69yQ8/JZEMV\nDD1Zczs5R+K5ZS5Z+Jxv9H7ELXPBVK/4UX3IB71PuZecctSOeJAcc2TH/P7yIZlo+cXiMY+qXd7I\nj1m2GbXT7OZR2dvLGqoyzkeMsYjCxY7cCVTqsNMWkXpCpciOdCRTJB4hiSeBvZowbRFOIDIXxVGN\nJjMxszh0DbTOLGKjkBsZRxJDix35rUBSrySyih202+g4PuxXWKsweRvHQomPzpSNeGWprrpTuoD1\nRY6axfeDW8XwnishU/5CRfB5LbGDgGi6cVXmYmfeSuzYxknAWqLnCpdA8Ux2AHMkg6i1jM6fTuAH\ntlvD4tolvEDUMp6GEk/2Useoxw6sjZ8hKO+4jjJOZxnd3eYFbuDiicoTxW0XGbJn49fd/2l37VZA\n9jmW3eu6ruu6ruv6eaif3YLvYX3PIZI4T5S1wI8tru9pdqP4qny9wVxoQmG3u3QEO7quPPW40yx2\nGGsNqcfut4haEDIHHRAT8ui8dzXDbycuUj+J8zX81uIeZgnOSbTyDJIaGyT9tOZ4FUFEgFFa0XhN\nplsO+it2izVGOgKw219zOFrQesntwYypWXPa9LnVm1M7zW88f5uVS5mqNVJ4fn/+kN+8fIcfXhww\ntwW7Zsm8zRmpkjfSIxyCby/uMnc5r+envChHFLLhq8PHnLRDCtkghccheCM/5nZyiRGO5+sRB2a+\nnT9DnEE/q8ZksmWgY1Tei3bMl4dPGaiKF/WYsk22LperMkVqjz9PEQLK1jCrcmyQkZ7pJb3xBmtl\n9NEXgeFgQ/ACnToS7UjTlro1LC56rJYZeRcFKUT0yk9Ny6LM4uwdGBYVqXYsNykuCCbT2JFOstjF\nD9KaVZ0yLjaslxl7vTW7/TXWS1JjGeUVKnV4K+D+mp10zWnd585gxlBvGOkSJcKWginxNEGxo1bc\n0rETv2Fm3DKXjFXJWK25a84xwrLwGU+bHf7l8Q8oXcqLZkIbNN/b3OGGibYLx+2Yx80eR+24e5vL\nTpwVO9A9vWCgKtqgUHiM8Pyt/W9yQ8/52ze+ubV0+M76LlUw+CDJRNuB+g1ZRx/tyZo9vWQgK8aq\nZKpXtEHzB4uH/I3Rd9nTS4ywfLX/abyWNmWarTnb9JnXGYm2SBWojwuaRiMTh+pbZG5xa4MqLKGO\nYqbm4QY9rRCVIngQJvpIhUohpw2hiY6bzcbQSxqGWcW4t8H04mscMh9JFmm0wAjaE3p2C0LKLkwd\nILu3xDlJnjYxm6JW0Mhol9DEThgZ4rrQnRIIAtfzJKlFWLn9bKM9mwOPL+IJAaJ/VzvqsIo0EjSQ\n4dUEII1+96svNBHEDgIS33nZdL9XEj2EVDdv1z765ngBOjr3Bt1RUkM8lcTHGacIdsdGfLK7PTuL\nPl7o+Fq4gYPOG78demRh4wlLx+fyeepnBtoKH49VIrwKM8F1C7UM2GF8Y7W7FiqFnVhEJbcmaXot\naROPPihxVkEjQCjkpMaNiF4e0kMroOfjG22t0XOFHTnkWkUPnrHFyYAeNNyaLHh5OaSX1zyYnJGr\nFkngV/c+pfYaI9zWjvZRuUOuWnTqyVXLQbrg905fJ5GO270ZT5jwbDnmg/ETjushX+gfsZuu2DUr\n/snxW7hdyf30lL8y+pgL1yNXLSftgNfTE35t/EM8knPX58fVIVJ4Ds2MNijeGb6MGayy4qPNPreT\nC2oMj+oJtYmq0Mu22AZ5nLUD2qBY2oyvDWqM8DyudxmbkvM2ctAPkzknbZ8fzg5onGLVpFSNiQAY\nIMYNedLSTxrmVRbBUN2ihefJZsKN8ZKLMsetDDZvuDFdkOuWu/3LbfrW97Mb5KYlVRY5CayalKYD\n98rTHsmkYl7mjIsNo7SitgO8lwx7URE8TUtmTc40jZvry8WQ9+8/obQJI1N3z7WHlp5hf9MBupCr\nlrvFJb/99CH37l9QupQfuxuULtle0+N6yF+f/oCPqwM+6H1G5Q1rH5k8S59RyIazdhDHKyKw9ike\ngRKeR80ubVDMXA+F52UzovQJf234A37UHALgOs+eby/ucmN3zr3kjE/rfc5dn0dtDkAmWo7aEXtq\nQeUN7/cecW77PGum3EvP+Kze4xeLxzyxEzwSFyIg+wfrNxipcsvfv5ef8cJOcCECy0Y4/sHzDzhZ\n9Hn3xkvWTULVam6N5pwAozvzaAhYGYKLG7EZ1PEz5ToV6lVzVFgEECqFNTGmSUqPA+xey439Oa2X\nXJQ5dW2wTfTXwQnc2EZfIy9Ae4QK0Mhogz6KG8F4d8XhcMGz+QijPG6lEXlMGWmIXjt0Nud24CPb\nRcUxlNxIhOgWZePxWWTWqEoQrESvov1yENETR64UYdLGxdXHkZI5U1S3WpoA2HhfInPdWEeC8egT\nQ9uNk6LluiSMW+zEIs8TwtiSv1TRh2gcH6Ncqbg5uai6RQZw0bxOVpJm5LfW7XbQ0Xok+ErDwGGU\np818NHCsPh9qez3Sua7ruq7r+jmpn1mHH0wHrBHP8nolaCcReBMqclRDt8sCcTesJZ4IkrQ7Fqxg\n0Ku4OB1C4bdUsSuXR3lu4LDCtxKpA06H7ewmSAjDlryoGe1UXK5z9oslmW5JlKOnGrR0vFUcM1Il\nn1T71F7TBsUo2fBG/4RdveJ/fPY+X5y+JJMtz8/GvH/3KWmXebqXrThve9zKZ1sPnX2z4N3JC3bN\nkioYLmyfP7y8zy9PosfLuetjhON761v85qO3+Dcf/BmH2YKB2uCD5EwN+Lg8oKdrctXSBL0d58Ts\nWsO+WfDD9U2WLmeq15y1fd4sjjhuR7w/fEwmWka65NL2cEFy1vZ5WY14ODzjj1/eZeVTmkZhjGPU\n3yBFYJDGLvrNySm76YqjasjQVDx47YxFm3GzNye9YVm20dpYC8/t7JL7+RmmO09vnCFVlo0zDJOK\nF6sRm8bw5bejH8xetqL2io9me+z0SkZJBFB30jVtkJyVPV7vnzFrCn797g9Y2JwXmxgykuuWcREB\nXec7bYSAT1e7FLpBXGW+6mgj/Gg9ZWgqtIyZuac22hD/b7Mvcj8/5Xk9QeG32omxiSeNTLZc2B4r\nl7KbrXhS7/B/HD/kP3rtd6mCIZWWkd7wuNlj7nKMcLggeT09IVct39vc5m5yxqUt+N7mDgcm+iGl\nssUHyfeqO6Sy7cZJi6gHcDlPNlNuJZe8bMbcT0/41uo+X+49xQjHNxf3eVCc8km5R65afBavaRsU\n358d8v70Kb9VvklpE0SnhK6siUzLINisUkIrwUpCANVrsJWkOFhTlQnOSoIT2w5TzTUtoPqWJLXY\nViFk4J3JMXfzCz5a7/Pjyz1604azVQ9R1DSNpqkMzA1yaPFtJGG4no+fcRVwnfr67njGuk1IxtGr\nSSnPZmbwvQgst/vtVhkfCkcx2VB/NiA1lirvxrVNFyqiowp3k0QVMTZ2/iFxUVegAqKOo+J6L+p+\n4njFI0oFiSNsdASsVyqGmKwkbmLjKQUiRbywsXtvJeXDBrFWkMX78OMWWom+0PiU6PNVWMR5QnEk\nWT1skSsVH1vi44nj6v5yT7sxiFLhxCtL9/+ndd3hX9d1Xdd1/ZzUz9RLBxEIAeSgxQ4C0nS7mxOI\njjIltEdmFnTATVtkHZ0sRam24IxYalBhS5cStUKkDr0WSOljd19qsAK734VfjBt0GhW0PdPQ1IbV\ntjt1vNwMMZ1T4dwVfLze4w9PX+PReofHmx3Kzv3wq7uPqZ3m8WaHd24e4YNg0WaMTEVPN2gZfdGf\nVlNSafmT5T32kyW1Nzytppx0EXqlTyhkvcUJljbjV+98xmkzIJMtx+2YJigOzYx7+Rlv5y/4Su8z\nPixv8HpywoPkhJ6suZOcc8ec88XeMxyCQtaM9AYjHA/TY15LTiNwKDdU3lD6hJHe8P7wCT1d82B6\nhpKeUb8i0VFg5bykbA172Yov9I/4Qv6SLw5eME3W3ExnEZtIV+wmKybJhsoaGq9Y2IxMttTecJjN\nAWi9oqcaKmt4MDpjkNXc7V2wl624l58zNhsejM6ZlTnDZMMwiV17XzeUXbxhoRtGerONeBzoGklg\n08avW6tIEkeWtiyblMeLCR8cPqWna26ll3ww+Ix/4+Cf8a/ufJ9vjH/MvzT5cQdyOu5l5/xodchE\nl9xK48nsfn7GYTLno3KfkSqpveakGmCEZdes+OreE767vs1n9V58rB0oe9b2mduodnZIfJB8Z36b\nYzviVnpJ6RMuXI97yRmFbKi84duLu7RB8fdffg2A3zt/iBGW/XRJGxQrl/Lj6pA72QVzV3DTXG7x\nn56u+drgEw7MnMfllJNqwDf2PuJPzu8yyGpeLoecPp1QN5rjeXzf+SBIixZdWPLdEtGzSOlJioYi\nbcmKSM1NipZer0KsFX6/joJJ5UhNS96rETLwoDhloCp20xWTbEOqLNUmoUhaiqzBpBa9t0Epv/Wr\nCVkHjNrofHq6jh5SIQick7SNxntJ6MXum8QjMwdWILRnerDg9nhO9vqScbGJytxaodcSmTjcyCJy\n25EzBHrcQOpIXhpE6hCpI8hAdqSjYG+ucZNXCuHQKPqf6K1fjis8bmrRuUUmbgvGhkWCWBiSU43K\nHAw7zCKIiFuYCPyKVsS1yTh87lnfc8jc4sc2AsG6Y5DUkpB55DpiJWqvQhhPKOznWnZ/pjx8Ndfo\n44SsaPC5IwRIjkxUr7UxDevKfleogNgo3G6DnXYXxAQ2dULoW0TiSAYNxrjI620lzb0aIdjKxzEe\nlUWettQBW2rqKmFeR/Xj09mYWZXzcj2kbBNO6j5/OLvPb529xYdn+3xx+pK+rjmuBvzR6Wv82foO\nUgTaIFnbBBskH1/s8s+Ob/K8HHFcDfBBUPqEtUs4MAu+2HsBgAsSh2TXrPirOx91bJuAD2LL/17a\nlGkSOd7fWd4hEY5/cvE2Rjgy0TKUFV/uPWEoK5qgeNGOmaoV+2rJnl5SupTfvnwLgJXLGKs1M9ej\nCoYzO+SD3mcY4Tg0M/qqQuHJlKWf1eSmZfHZmItVwfnZACUCPR0zVJc+o3TRrO2kGfBiM+Ki6XHW\n9HlejgCY1zn/8Jsf8PFmn988+gJPNhPOq96WAVQ5za1sxjQv8d3rV7qEF5sRjVfcn5zz6XyX0ia8\n3AypneYrN56xtimrNuXjcp9Plzv86Sd3ebSaclEVJMqxahKU8rStom40ldV8de8Jr+XnHCYzbuh5\n92fGnl5wy1xyJzlnTy/Y1QvuJWdMkzUPs2NuJ+e813vM6+lJTMNKl+zpBXfTC6ZJyX//9GsxQ7b/\nCRufsGuW7JolY1VyL4mbxH6yoPQJz5optVe8N3pGIRtu6DlTveammfHD6iY9WUdzvHTFVK341/f/\njNKn/Ct7P+C4HTFQFbU3vFtERtVNMyOVLVUwfDD4jMNkzmvZOZ/UB6x9ivWSN/onGOG43Z8xzUrO\nL/rkuyVJYmkqjevsvet1smWpSe3xXuKsYl0lW+D+KmhG7jQo45GNxDZ6q8EgiE7N3WfZZlxsCso2\nIS9q1nWC9ZJmkaK1J1w1dblF1ArSyNbb7ccQmh+9OGBZJ7g6juXqjSF5acB4RGesKBIfA1eMjVqX\nTvld9GvERtLuWIQkhrEAmM4GwcfRVHPYEloZmUaDlnrXIZY6bhBVBKyvOPOr1y2i1F0YkIBWREII\n0WKBeWw0zI0Se7ciSdvIXOq3yF4brSNSF1O4mvjcfRcME4yPquQ2bgziMonq31GDzG0Eho3HLk20\nbk/d5112r+u6ruu6ruvnoX6GC37AjSx2YrFWQRAo5aP9aWZjRz6IRmTBSUITbY+pFbqwhCIe8ewV\n7zYIpAzUL3qIwyp2AR2o4r1AD5u4cyqP7rW4tUYXMQv1bNbHe8GmTFlUKReLHss64elyzKLJGCcb\n8qSN+aF1QSIthWn4cL7Pdy5v87vffJuLumDdJkyKDUY5ns9HSDqr4K5/6quKZ82Es7ZP6RP2zZLb\nyQUjtWGqV8xdTulTHje7HKZzdpM1Ux27nn9795vs6QW/OHrCHXOxtcBNhMMh+L3Vm7yfP6L0KVJ4\njLBM9Yq/c/A7HJpLvpg/pQqGUzvg4+oGU72iEHUEde2As3bAjXTOi/WIw96C81VBfndJXRlCpWic\n4rwu+NPZHX60OuTj9R6fzHf5xx9+keerEaebPsebAYVueLoYYZTjrTefc9EU3B+e03hNz0Rdw3E1\nIFOWlUvRwrF2CYs24zuz22TKkqmW43LAW+MTLuuCz852uGxyLuuC07qPFp5HqymjpCLrN7y4HLFu\nDKYbP9W1pj3JSRLLG+MYKzjVax5Vu5zaAVUw/M7yLdY+5R9d/uKWgvlJfYAUnq/0HrH2KZU32xNR\nE2J27KmNIHFP1/ztO9/iprkkky17yZKzNobRXNg+f//4axjheCM9YqAqXjYjfmn0GV/Kn/DD9U0A\n0s6s7e0snvoOkxnvFC8ofYoRjqftlAfJCX8yu0tfVXy82efMRu3FQG74sLzBd9Z3eSd9zh9cvM6u\nXvB29oKB3HC3d8n99BQXJKebPlo6bu7P0NphlGM6WZMULYm2pL0GV2k2ZwVp2tK2Cm0cm/McKT2h\njKeBxTrDbVTsNncjoOp9VNj6VvI/ffIlZrag9ppUW3Ldsjzv4ZzEWkV/d83mrCCESP8MpUaOG1Ti\nkV2nG4Jgd7yil7TgBEWvimPeByVZvyEE8CuDyeNodl0nnK16zC97nK16GOUi7z3x6I9z2nUSx8de\noPqW4KOanlYguvhOoQIhi7bQqt8SOvBV5Ba1UuhRgxw3yMwi9mtE7rCnMQ5Ujdr4f4uoLvZ1l3nd\nb+M4R0DSi6cMsVMTDmoG30txi2RrE83cgApkk4owaRDa4xuFSS2hbwkXSVTdikCS/P91pHNd13Vd\n13Vd/5/Wz84t03dgBuCsQjQiOkxO2ojnpg6pPa6MnbgtFWQeoT1KOywaakm20+JahThJqazA7G9o\nZyl61GwpXdHnRaISj1KeZpEiEo8/ypD7NQJwpcYMa5YXPSa7S6bFhoGpeLqYoKXn7HLAH29SBnnN\n6bqHUZ7dYs1etuKNXznltx8/5M5kxiCpaJ2i9ZJEWb7S+4zfuHiXnmrYUSvqxFB0trpX9SA53v77\nk+aAu+actU/5/eVD/uDidf7Ozd/hneScNsDN/nd54Qb8zcm3qbzhprnkj8oHnZti4KNml0G2oSdr\n3sue8Lqp+FRWNChmruCd9DkeyViWrEPCSJWc2QFf73/I/zJ/j6/vf8LLakR5mfPm/SPmWUYzVGTa\n0njNYb5g2AGmw7TiaaViyImOHdfIbKgGhmm6prQJPdXQhmhRnCdRyPZ0OeagWPHD2Q12sjUjs+Gy\nLrBIpsmapc3Yy9fM24xJWjI62FDolou6oHaas1WPB9Mz9rIVw9sbvv3yDkbFmEQpAnvjFYvUkmqH\nEoGb6azrtDdbr5xf/T/be/NYWZPzvO9XVd/ee5/93P3OcmflkENSQy20ZJrUBsNCAgERY1vyBkMw\nDGQBkkgwEDB/BHCC7HFgW3Fk2ImjKJadmJEdMZJoEVYiDtfZt7vM3c9+ev32r6ryR/WcuSJEkebQ\ncy3efoCD0139dff3Vne/X9W7PE/nMhLDh9vXFwLgHo9Hd+nLDIMkks4eZSy+aFiTU0xHoJH0VMow\nmZ90vPpCE4qG7XDEy+lpfrL/Ihe39rhcbtKRBR+Ib2JiyT89foa1wZTtRTJ405vgi4YCn8f8XV6w\nZ9j0JvRlxgvFWZdPUHO+b3CdJ8I7PBtfpyUqLlcbBEKzHsxoq4KWaPgrpz5PVxakNuB/3P1hfmb9\nS9ypByhhuNTb43q6Qtl4tMKKdlCR1b5jKR23HJ13x63YO3HpYvha4PdKIr8h69RYC3XuOzZJzzhm\n1MzHUy7mb7XgiY1dcu1jrKBsHCtn1C2pK49BL2Weh07eL2iQytB4hqRVULzWR58tuHvUo9POySsf\nFRn8Vk0S1NieKw0uSreyF0lNUyuCsEG/sytYmzKZxzSVwnQb/LChOocr+fY1deYhkxqpLPpugtx0\n3wNtIQgacs87WVmrVoM5DKEKkJVA+RrdSJpRRLiZUsxDvNUCrSVRXJFlHn5c0xRufsxBBP3KlZUb\nAb6myTz8doWuFbNLtcspnK4g97AtjR/XREFNmfn4UUM1DU98greeO54qLdH6va3R75/Dl7i608gg\nhEUMK4o0wBYKM/Ogs6jV1YIgrDEdgfJc0qYuPVdD63ZM7sMNA5CgG0m8liGlpSo9mlqhtcTMfWSr\nJh9Hrm3cguk3CCOIWiXFO6cVaEf0hWVUJmx1pmxEM262+nzizGX3ZTYeR2WLxKvYybqcSiYM2hmd\noEAKyzDKOJ2MkcLQlQXPdm/w/OQCX03P86cHzwNQW0mFZKwT1lSKsYKxiblZrvBQsEdtE0LZ8G9u\nfJWng318oAZa0uAbTYDmrh5wqxjyTHSTdTVnX7fZ9kdc8nN+ZXqB55IrAAxVQWY8ul5JR9b82vRD\nXIp22FQTNv0xfeVqzC+EBwBMm4hPPv06aRNgEHTazq7GKA6KNiYU3E17CGE5deqYtAm4O++y3Z6S\nNQEPdw7YLboMghxjBUpYPti5yUxHZCbA2k1OJ2MeTlzvwIqaM/Bc9UvPy/lyfo6zrWNXw47k+nzF\nfTbCcrY9wpea7XiKQTAMMj6wcZcXd7eR0nJpdZ+scd2ko2nC6rYLlX0tO8+f7L5IYRUt0SCxlFbx\nZLDPkXFqZHfsgOv1Gh+OrlNbxfV6lVPeiESWHOgOz8bXWZElErjW9DjjTTnWETebIR9JrnHeH3O3\nGjjVMplzsXXM57NLfCy+SmE9Pt57k9p6DL05HZlzxnOVS7+VPs5HwztcDPYJ0ESi4aPx20RC4wvD\no9EOKyplbGLO+DVjM+WZYHpCDzE2IetqjhSW/brDz2/+Dhtqzn7T5Zn4JhfCfaR4hFkVMggzEq+G\nGDpBSeJVvLqzxVp3zu6xC1etdecnFU/WCob9OXnlu67o223aZ6dYK2jFJWke4vuaoF3x5uE6l1b3\naYxLBt856oEVrA+nJ8l61auwVpw4bAGY8zkCOLd+zFYyoTGKnax74vzbkVsgVbVHMQmJ+wX1Xox3\npkQJS20kdaNoJwWyBZNZjG4kfuwuVEGgqQkXJICWOjYkYU1+u0NyeoanDE1c0xxFThMjsNjEVc80\nfYEwwvUi+Ib8OEaEGq2lu3BJi99ZFIcog609xEqJST38XkmzlxCt1VgjqOcuIesfe4gLKdYI/KSm\nKT2CsHF60lpijUAlDU3t/FzdhIS9grIKHX3De3S7SyyxxBJLPAC4jyEdCFdzPM+QpwHtTsFsnLia\nVn9Bezz18Vbc1VP5GqMVpnTbR5RFBJr5LMIaQbiR0VxrozcNVeURhrXb/hyETtXGgkl9VMd116az\nyNW6CouvNK3+nIu9I2JVk+qAWNWsBnNC2dBRBQcD1wHrS1cWNQhyHm/tsBd1OR2MeCg5YOjNeX56\nkXPJMY/EewSi4Wq1zqhp8dHuDZ6N3yYRmhpBuhC5uNsMqFHMdMytesiPdl8GHNFZv5PRkTmRgD3t\nMzaxE7bAqR5dKTb42cEXGZuAba9hV0vW1QwDnAsOiITmehNw3qvoy4YXyj6hmPDH2685cQ8vp2dK\nbjU9LpebbPsjblSulrzllZRGkdU+p1tj7qY9zrZHhNKVwUVezWO9PRqj2A7HGASJrPja9Cxnw2Ou\nzNa41H43VPVwuMtYJ0x0i+9bv0EoGxSWeqHoYHDlqwORMqsijlXD+cSpUN1VPYZBSt93Nfnr8Yzt\ncMxR3eK4bmEQPL6+x83pwCWD65Djgy6dYUqiKn6w9Rbn/TEbSpIIiSREiXfWOiHnrSG3FU8FuwDU\n1hAJw1PBzrvfV3/MsWnoCMnMGp4OpowNXPJLTnt3uN3ErEnBR5JraCSP+zC3lg9GNxibmG0141xy\nncwKCqu41fQprUIj+GTrdTKrWJE5kdB8tTzFp+Idjo1BAqe8EV9IH+OT7deYGSduArDtzdjVLdZU\nTmY8NpVmTe6TWSis4snwNgB9mXEjHHHcTmiMIpSN6zAOBZ7UrPXmJzrEQljaQenKiSufvAxY6aRM\nqpheO6dYqWi9Q5sNZEVAut8iWsn5gVNvcy46PuktWWu51y21h7GC1HOdvvksYmV1RlF7eEqjpwF+\nvyBUjVMC80rupj2UtER+SdU4N9Vr5RQTF+qwgaWqPC5s7tP1C+6kPYrGYzRLiOMKYwXzcUzYcmR9\nwaDAWugkBc2sjVmVtM5OCbyGNA8R0iIHFX7QUNcK3qmHF04oprYeQb9Ea4kApwonoCz8k+eIvRD6\nTiGvEgvX2quRwuIHi/HSp9kuofTAQtIpkW+1sE8VVLWHihqa0sM2i5C3Z+mvzkmzEOEZep38vXjd\n5Qp/iSWWWOJBwX3ttA2DBmMEpnFNHVG7RBhcdkTXAAAgAElEQVSXLLJaIPoV/W5GkQeuYcPiyrEs\nIC29fkbSLml1C3y/wZwqSDola4MZTaOQ0qK2MuJBDsrSWk/ptPMTvVlCJ6s2SHLWW3O2oglb0YSO\nV/JE+y4DL8MXmv2qQ6E9buUDvrD3MNfTFe5kPQrj01M5Z4IjnopvselPOBWNndCJFWgr2an6jGpH\nUbzb9Hm5WudyvcLz2cMU1uexYIcVmfJIsMfT0W3WZEZLVPRlgS8axibhlg7Z1V1u1kOuV6u8WWzz\nRHiHDyQ32dWuM3FsQC/EVi4vGBgvV+vMTMSBlsyMpUZRIznQncVzJEpYLleb7r5O2Kl65DrgdtYn\nlNoltK3gfOeIC/EhK8GcoZ/ycOeQtiqJVXXClSOFoe/naAQX206c5UJ4QGF8DpouMxNz2LQXzWqK\n3xtf5Eq2wW+OnuRqusakjhnVLU63xpyKx+R6oTcbu51FyyvZL9uEUjPXIdMmRmK5O+85Xd6gojLK\nMUWGmmghXaiEQVvBzGhKW1PahsxUZKZibgpK21Dbd2lnJ8aiF6W0tTVo3P3LdY9bWrKrQ1JjeaHc\nJl08Ty9q7E55U+7WAwBuNT4XvYw1lVJahQL6i1+cS5r7fD59HCUsRyamsIrUenw0vMPYGHwBkXAC\nLJ9sv4bCUi3okt+sY8Ym4PfSR/CxXK3XmBmLWnRKvVCeZlNlHOgukWgwVrIWzAmV+6yMla6sUFiG\nccZqPOfUcEK4KG2VwjpumlFE6DV0WwVKGjZXJjRaUTWO6bSch8SrGb1WTqxqSusxqyMK7ZF4bqU9\nK92q3BhJv5XjhQ2ecl3uo6MO0UoOVnBz3Of6bIXdouO4j4qA0TzheNximkZklaNtVso4SvQ3XR6t\n5ZVsJDPWkpROUiKFJfAaVGAIgoYy90miiqZ0q+6m31CmAXFQk5cB5dydX5yUVKWHzj234lcWWyh8\nTxNENVXmo1MfIQ2tuHT5wUYiBLTiCt1vCLslTeU0f+ssoN13+TGlXMGIuh4RxjVBVBPENUUeYB5N\nyY4SxzogXYmqd+QazYJ2RRK6c7eVxLw3/RPUZz7zmff2Ct8h/tP//r/8TO9TH0FrRdxyRk3nMaaR\neLGrjw+6lVPmKX2q0gctiVsVWghs7tEbpmjjJnw+Tmh3c5pGuS/LQdtRpQpBKyld6GCRtNFG0miF\nLRWtXkErrJhXIe2gQlvFuI45Fx9zpxpQG8VO0ePR7j7nomM+tfo65+JjxqbF+eiI3z1+mPPJkat4\n0C0KG2CE40DveQUaSYPiuG4xMu7xm9Uqa/6Mc/6R65qVmhvNCm1Z8lJ5mo7KKaxHS1ac9WZUVjGz\nEc+EO1hheSTYY6BKAuGEsMc64XezRzjnHzE3IWe9GZsqJZQlY5NwoDsMZMaqyrjd9DBIfKH5vexh\nzvlHvFKc4geSK5z3R9zSAx6J9wg9zao/d/zzTYQQ0PUK3ppvIIRLOkssDYpXp9sMgpyjus28ibhT\nDFgL5uyVPQobMG8i3ki3+PXrT3Oxf0Qsa7SVPNO5zZnwmIvxPoMgQ+MEtl+bbHGhdcSNbIW2X3JY\ntbmVDXh9tMHj/T2mdcyt3FEAZ02ARVAaF+aYljGhajiatpCeYaM1p+2V3Gn6/Nrog/T8Q75eDdjX\ngptNwIvlChklMwtKNBxrQY0kt4axgatNG01NZTUbquTr5RZ9lXG76fOwf4jA8nfHz/GB6A6g+RuH\nP8InOq9zW3usqoJ0oR0wtSE3mi4tmfOV4iwb3pRYaDoqZ03laEBh8YSlIy2v1wMOdQxoOrJmR3dY\nVzlWgI/GIJmYmB9K3mZHJ1zwR4xMyK6OuKu7PBvukFvFru6yq3vEsmKn7rMapBTGZxBkzJqIeR3S\nWLXo8pZMiphJEdGLCwZhjtdqqLSi1opGK3pxQVoFlLVPYxTtjiP1m6cRcVyzk/fZyXpMipjKeDRG\ncTRr0VhJngdMJy2QEIU1eRGwuTqlqH2UZ1DSOj0GJP6CfsFYV+cvlYuvSOkq7wzAak2FAiGojMfL\nb56hkYJGS7Iswo4C/G6F8gxR0NBYeULpoAuPIG6oaufgVaTJJxFy0cE7HKTU2tEzeJ4hCmqXjB4F\nDDZdohdpiaMaISDwNXkZECU1xgr8pEHXimHf+aiidHTjddtSpz6DQYY2jqyuqTyCdg0I6kmIF9fY\nriZpO8qXINDYRXWURXD4q1/Y+cxnPvNL34nfXYZ0llhiiSUeENy3pK2UBq0l7aRAvSOwcE83nOzW\ndJKSSRoz7KXklU/duASfTn06mzOmWURTK7eFkm57it9graC/NSVdhII8ZQjCGiGsK+2ahsS9gnwa\nkKUhh8IyPWoxSmMeX99jP+twKxqSNiFrwYwP9W6iFlv8jszxRcOoTOj1U3587RVSE3K7GtJTOT2V\n8/Hem0SyJhI116p12gselIfDPWqrSIJ9Nr0JHVFTI4mE5tlwl0QIngkcj04oPELhAQlzWzKUhwyV\nIjNTHvUFe9qy7eUMpcdYjejKgtNezo0moSMFiVBEomJXw7PhLrWFRMB5f0wiLAbot97k5XKbn+19\nnZerAZeiGReDAyJZ8aXZBS4lewz8jNcnrl4e4KnOXTb8CR2Vo7Ac6TZPJ7dRwjDWCZ40bPhTpDDU\nVvHh1nX+62uf5FJ/n595+KtcCA/wRcOX5xepraKvMlrSldcN1Zzb1Qo/tHqVVX9GnSh6Xs6sifhw\n/yb0oedlrPpztJXsVV1eOtrmUn+fVAeMy5hiUYvf76c8NDgilDUHTYehctq2/9f4g3yi9xrHun3S\nD3G1WudTyXVmixLSFWkZG8isx4aaUyMprCIRmo9Hdzg2ikBN2VaWGsFPdF7i6cDnyDT8xxu/Q2Et\nr1UtQi9jV0c84uc8LCy1zdDAT7fv8noNv5k+wae7LzKUAVBx2ov5vVJxwat4NhxTWMuNJuFJz+Pv\nj57gudUvMzYNj4YhXy0rfihKSWSbymY85MVcbzI6siIRBTMDb9Z9zvuHvFae4onwDq9mp+iogqmM\nMFZQaI+78x6rifts235Ju1dybbRC7NUkXkU/ksyrkEGU8/qVU0RBjZKuXh9YaAkLhq2Mnl/Q8Qua\nxP1Or8xWCZRmFgUEnka0c6JBw+5Bj1ZQYVuCxkjXLW8FaysT9qdtVMtwvn3MTQYcvbJG+9ExUliq\nRhH6DY2RWCMRynA0bpP4NS2/or8xc7/RqCStfNRgzvGkxaCb0WhJOQtJ1iq6rYIqrJmnEZ12Tl14\ntOLSdernPu1ujpIuBFMet/BWDUpYmkrhbWbMspAwaCgKn5VeSlH5HNwaEK9mrkvZM4S+K9mcFyHt\nqGQyTQjaBYNeytSLiP2aycyFXr1A04pLprPEcfgYSRTV+EpTKeOS257bgYj2uwnz78jvvqdnL7HE\nEkss8UcG99Xhx6FbLeSV7xJF0pK0CsQiTgcwaGcnog1V5VEWPt21OaGnacclvU6OHzV4QcPkdo/Q\n0/iepp/k2IXOqbWCfBJRFgH9dkZnJcX3NH6vpN9LKUqfwdqM0/0JkyrmUn+faRNjrOCobpHpkNfT\nLd7MNngpP8vb5ToGwU49IDMhpfFZ9WYL9kKPwgYcN+2TxxSWVW/GGf+IG9UqkXAshwcm4fPpY3xu\n/gRD6dGTEaHwaEuXRCptw9QUzIzmWtPjSq244Lt5+Sfzp/hn80vU1nBsPM55OYEQHOk2l+uYG43b\nkaypGdrC5XqFRCoiYelLD21dzPhisI8vBNeqdW41ho7MGesWN+ZDXp6fYlQnNEYSyObd7lPxbqLS\nsYGGpIvmpURWaASHdYdUh+w2PbphcUJl/A5HzXHV4nqxynHT5nq1ypViw8WlF6IhkyZBL3INsayY\n65DMBBzWHe6WfUZNgsSy2ZoSLkoxszpgmkccZi2KynV8Pte5ynPJVT4Wv82fHnyRnxp8jWiR++jK\ngo7K2fQmZBbGJgDgQEteKB3fTY1kt+lQWEVhOUmKrqoaKQRHWqARlLbhjbqFQlBaqFEcG48zXobE\nJX9rLAda4AvFGa/m090XaQnJ3NYcm4DS1mQmZG5rCmuJhCASDZmt+FO9rzE2DV/Iz5GZirGJUUIw\nNwUHJmFqCq7WAySgsbxcDXi5OE1roYFrrOTl8TbaStqq5O10hd20S+S9k3C3J3+DJKcxkkJ7pHVA\nqZVb7a/P0EaijVjkzlwJ53rb7Upr6z6vaeP4nNp+iSc0sd+QlQFV48ozzYKlsx/npGVAK3b6tcdZ\nzGon5ThN8KXj/Fl9ep9TvQnzNKJplOtGLXzMrivHHvbSE76qU70JxgqksLSCmsSvWe3PUdIwncd0\nVlKmswRtBEnoyjWtFXhh4zp6LXiBawZzOsuCaMdDa8lkktDrZ4ShSxrrxSq80QopDcma68D1fY1Y\nJLy7SYEnDb50erutsCLwHCdObVzjlpCWKK4YHbWJkxIkNIVHehwzm8es9Oc0jSJLI+SC8vu9YLnC\nX2KJJZZ4QHDfYvhaS6pGkZc+5XEMG3P8wPGfWCvI5iHVouKmrD1mk5ggrhl0MhqtODpqc3pzRFr5\nGO34KOPNOY2W+J4rLfODhqwIft9VsdEKgWvTNkby5Ooue1mXR7oHtLySWRPR8QpK47Huz+iogqE3\n57nWVTrSxa0L63Mp2mGsXbnlXt1DI+nLOaXx6auU52cPsR7MWPVmHDYdLoV3qa1iw59QWJ9xk5CZ\nkKejW6zIjBuNxRcFYxNgLEgh2G16ZCZ0jIyixheGzGjuasWPJG9y2mu40Xic8zQHRlAYxSP+IXd1\nhztNyDAY0RINX8gvcsY/wliLDxTWNX/5wtCi4Uod8cPJZT6fXWKn6qOE48WXuMqNh7uHTOqIK9k6\n29GY29WQUZ0Qq5pc+2yGE7Awqlucjw6Zayd88n2da6x5U/7iqd9FI5jpmIlOyETAx/tvLfhkxo7z\nBctb+SYvj7f50fXXmCxYF4ETmcHtaMztfEBtJX1fE6uKQGpy7ZM3Polf0R/m7My6hH7D7VmfaLN2\nPP8LiclaVKQEdKRrYHmHniC1HgGGY+20ER4L9qitWw+d8qZoBBPj82bd5aJ/zG9lF3k2usmxbtGX\nOV+vfAI0qTUUVnGt3GBNzfBpONCCzDp5zNQGZDbHF4qOaLihFXd0jzv1kJnZZU3NONKCG82QbW/C\nzES8UjX0ZcmVusspb8QrtaC2Hl8pFZ+dfJRP95/n5TphbBKu1AXJQiLxo/HbpNYjkSWF9Xlu5Tpf\nGZ9lLZqzHTtah520i7GCt47W6McFseeqTKZlxM1swEZ3hhKWyngkYcWsCOlGJbMiRAiLJ50MZG00\nH+3eOBHU+dLoPIFs6AUFjVVstqYcFS1u7g5JBjlpFRB5DXke0EpKOu2cP/vQl9xnZBU7VY9xEfPY\nYJ8X9k7x9Ok7XB8PGc0S/KBBr5e0WwXPrt2m1B6jKqZufOKgJvHd9+KtgzUG7YxpHoEVeNLl8kZ3\newy2J9hG0hhJK64oG48gaDBGUlYenmfIbrfxn5gThfVJxGF+lNBddVQoReETtt33KhvFhF3HR1TX\nHiYSpEVAXatFPN89/3jWohWXZKXbTRotMUYyXJ3RaEUwKOi2CpoFZ05aBlSFhykVndWUOHhvK/z7\n12lrhatBLRWdzRl5FiKVQUlDkbvO27pRzKYxSbvEakm8cNzGgvQss8JdFHQjwYJKDGnuRBtGWhJG\nNfnETawMNEFYM8tCmsbptW6sTPCFwVeaUNZEsmZsXUjhydZtWrLCF43b+suCRDQoYdG2JJElQzUn\nQDNUcza9CQqXeIxkzRPJXU75Iwrrk5mQzIZE1CfkXXt1n1DW7DZ9UhmSmZCOyklNyFnvmMyEFNbH\nF5qWqPCFobaSF6sV/uHhR/m3Vp+nI0dcrdcYqru8XG7ji4ZAaKYmYtObMDaSIxOz7Y2YmZiXa01f\nFhSL7tbaKr6cX+SxcIc1lXPKH9GROa/mp/GkJlSNI/qSzQklrxKOTIyIk07ZSNYUxmfDm7DizSlU\nQCSrxXk3zHi3eLijcrqyWNjW4AtNX2XU1uPReJeDyvUIbPgTel7GmucScW1V0vMyZGzpqOJEI3gr\nmFBbx/FzsX1IrgNHuVyHnG2P+I3xB/hw+zozf8Ru06OyHpkJmOuIVW/GTt3nbHBE4Tsq5LFOuFmu\n8IPtt9ht+kSioqsKxjqhsh4PBXu8Vm1w3j/kWr3K5XKDH269QWpCIllzu3Hd0BfDPQ60o2K+Ww+4\nVq7zTHIDvbiI1NZDYqhRrMiUy2YTXzTUVnFNd7lTDxnrhL7K2G16KP+QF4qzPBtf51q1zkHTpaNy\nvr/t+JJmJuJKsQmRo8zuy4ypiZiaiMyE3K0HzJuQh9qHvDrZYl6FdMOCqvE4aNpsdObcOupzajjh\nOE1Iwoqq9JgWEcbCTIVUjUcnKslrjzSNMElJGgRYKzict3j6wq2T91tdm7FX9/CFpuN18YUmkJp6\nTbmEZRFRG4me+0xTF6YdenN8oVEY2qqgWVF0vZxgq8EXBk8ark+GBEqzV/oEnubRZJfS+OjEhQO/\ndHiOM60RvjDkA7cQkAtlPVc6WqE25tRa0erlVJVH3M4pao/Ib044g3ylaZ2ZUVXORbaiiqpxTreq\nPeKwopYKJQ2jcZuw65LYde0RRzXTNCIIGrSWzPKQbBqdXDTSPCSJKuZzF5YqCx+1uCBEYU3oNSjp\nFsTCCsRuhFQWtWap3yN52jKks8QSSyzxgOD+rfCF5cz66ERbs9vJ6EYlaRVwanXMzqiL72u21seM\n5gndYYoQlkkaE4cVcVIySyPWBjPWOin707bTwJyFrG5N6EYF0yIi2ayYZRHDQcrhQYftrRGzIqQV\nVvTCgsuTNUaZEzPo+gWVUawFcwyS1ATUNiGTIUeiTUuWSAwGSbVYJbcWpX21VWTWI7Mh4yZhZiIK\n65MuBEluVSsQwEHToa+yxWq8YaYjbldDTgfHjHWLSNQcmRapcav+g6ZDR+Yc6C61VbyQnuWh5IBX\nijMc6zapCblc97hWrTFpXIjpbHhEIDTH2iVEXRjKY6jadFTO704f5ZF4n8wEPB7dYb/pkJqQI+2E\nWQDuzHt0/HdpnBWGwgZgIRDqZKWqkRTWdcRqJCyamGurSEWIsZLdpoexksL4dFQB/piDpktmAiLR\nUFiPTIes+jN8qblTDpDCkmufTqtgpiOOatdRPNchiSrJtOuyjWRNKGs84UIL5YKpcSVKKY3iXHzE\nXt3jsOmQyIrnJxfYiia0VcnlfIOuV5yE5EZNi57K+MH2W7yUnyWRFRNiblcrJKo8YRVNTchr+Sme\nSW7QkQUvF2fY9Mcc1F1uV0MuhPvOXuvzZrPN7xw9ylo454n4DvtNlw+Et3ip2uBmucKF8IDa89j0\nJtTW49VF13NfuQap59OHeDy+w5fziwAUxidaCKc8EuyikbxUnuKUPzr5Ps50zNfK87RV4UR1dMhB\n1aG2koOize6s45KyjUejXWFDXvsEQUPLr/C7mtoootUxtVZoKzhOE5Q0RJ5LwK4OZq7MWSsOxm2e\n2t5xoUqdUNgAX2hK42GkoLGK0njMm5DNlmNUrRvFsJNhT49ISyccdKNcxReaRJUnyd/aOi3g3Ljm\nsM32DE9o7u71OdsdkemQuQ4JF7vQe6GkIfHdWC8u2J+0AdjuTrl+OCQMXYhYG+m6sher7ZX+nMhr\nXII6FhxO2rSjkmYRht7ozaiNZDpLqLWk285PpFizIqQTlfTigqLx8KShqHyidsUwydmftvE8w3Z3\nSlH5NLXiwvoRb13bYrg5odYKX2lGacxax4WOOk/vES7O5yhN3pPbXa7wl1hiiSUeEHxbK3whxI8D\n/y2ggL9jrf3r3/C4WDz+k0AG/Dlr7df+sNd0Qgwl29sueTStI7fCjpRrye5JWn5FL8yptWIYZ+xM\nuzy65jjb0yYgi33W4pS88YmCms3OjGhtn7QOafklvSCnsYr11pxANoRew+nOmF3ZJfJq9uZtlLSs\nd+bMqpCjPGGrNeWt+To7RQ+DcO/TBDzZ26Gncr42OcOdeY8L3WP28g6P9/boejm+1BTGZ7/sUBvF\nlfEqz645tsKb6YAnezvcLIcniciu5+LQHVVwvFhZvpSe4cPt69RNh+Omzd97/Tn+whO/x68cfoxn\nOrfoyIKtYMIz8U1eLk6z2/QojU9LllwMDrjGGnMdcbNcoStzIllzPjhkt+5xsxwyjFNeys5yKnQC\n2Ht1l69mF5g0Lm8x8DJ+Y+cJNltTNpI5R2WLUm+ffDYtryLXPvM6JPJqsibgbOJWlldmq0zKiFPt\nCYnnVlVfvHGei+tHdIOCjlcyqmKuHK/yY2ff4PXpJhvRjFEVc2MywFrBM+t3eXu6QjsomVchwyjl\nuHJt+XtZhyf7u7w+2WAQupX2rIoYFTHPrN5lLZpzXLlE8uXxGu2gIlQNV8Ua6+EMheHVYouP9K6z\nU/VJVIkShpemp/hY/226Mscowe1qCIDEsupNOdZtItUQypq38k0khn9w52P82MZrbne12CW8kW+x\nFUzYrzqcCw6ZmpjMuJXuj629ytem53glP83VbI3uIOeV9BSvTzYpBx6l8Xi2fYOxSRg1Lc4Fh4x1\ni9L43C4GnA6OuZyvcyY65pf3Ps6/vf5F3si32PZdbqYlK65WG7w0O8XQm7tdl/GZ6Yhz4SFjoZk2\nES1puDEf8rGtG0jsyer5t155nEsXduhHOWeTEdMm5LBosxVPOSjbBLJh5LuVpTaSTlSynsyY1yHa\nSh7b2uft0Qq/0XqatFnw0qiKm+mQtl9ye97n5u6Qp87dxVvEqjc6MxKvotsteHu8wmo855/efpJB\nlFNqjw8M7zCuEg6NZHfWYa2VUmqP7ZbzFw+dPqDlVbyRbnBzNkQIy1YyZSVK2cu7TosiKMiaACnK\nk7Lvc4MRXb/gml4l9DSeNJztjqi0R2Ml1gq6QUknKNjPOuwd9WA35Mzp2zx/9yKnto/phzl7WZuH\nNg8YRBkv726x2ZuxN+1waX2fxkrafknWuHzS7ZnbjRTaZ8922OzO6Ac5D68dcu1ohe3WhIONFlud\nGdcOV9hIZoyzmNPtMTtZl0GYnegJvBMR+U7xLR2+EEIB/wPwKeA28GUhxGetta/dc9hPAI8s/p4D\n/ubi/zeFxDIuYjai2YkTnDchsypkkkeECzV6YwWHV4f4j2p6cUFjJZGqCVWDLzWNlUxKd3xtFN2g\nYD8LuHx7nQ9euEU/yJjXIVJYssqnMZJb+wPa7YKy8pDSEnkN3bDAkx5ZExCpmlEVkzUBl++ss7Yy\n43XhRDtmlaviuDxa4/CggycM0ypkI5nz1sEa6905We1zPGnxotxmqzUl8SpeOD7N2wdDVnopTw0d\nDa+zu8dO3uNDmzeY1tFJiGhmIv7Y+ats+BMGvZSb5Qq/NX6cw6zFhx69TqbdD+vXrn2Qn7/0Lzjj\nH3GrGHImOqY0/gnHzqY3Ya92hGgap+3qC00gGv757iMYK1hLUj6+chljJR9cue0I2ObrpHXA28dD\nnl7fwZOaK9NVPGkwVvD2//EQ9kdGtD13volXoa1kVCa8fHeb1d6chzcO2Zu3eevWBo+c3kcIS+Q3\nXJ2vkjc+oyrmxa89xMNP3yatA94arxEozTBM2Zl1OM5intu6yawJ0UaS6gApLC/d2eaJrT12Zx2S\nsGIn7zqHX7Zo+yV7Bz1GUY251ubVYUN3fc6wlXHjrU2e++NvM/RSFJaeyqm0x0xHaF/yRr7FQ9EB\nv3HwFJ9ae41I1vTJXHLVevzmncd4oXUag+Bze0/wb2x9nb2yy3Hd4iPd6/yL0SMcFS2ebt1mriOG\n3pzC+Ex0wmroEpItVXGtXOfV8RYfWblJrn0uxgdU1mOqI24UK2z4EyY65v89epjtZML/N3mYFw62\neW5Tcam9x7FuY6zgP/jaT/ND567xqcGrvDQ/w7wO+Uc7z3Kpu8+lZJffPnyMjbUJfZVRBj6HdRtP\nGmJZIYUlxoXehG/uqcM3NEa5enkEu/MOB/tdnrxwl715h1OdCS+9eJ7VD86JFkRsntSMj1u83Npm\nWkRsdabcmXbxlaEX+tw+7LOxNiFSNTemAwaRU7CqjIcUNbFfc5i3Gc9ijict7H5E8ajH6c6Ya0cb\ndOKCaRVyNGlhrKAf5cReTak9Xj/cAKBqFNffXueZSzcBeHVniw+fvsVxnjArQqbHLeTEw6weMa9D\n4qQk8BqO5wmnO06sSCIoa49re6s8srXP7nF30RmrHT9O7KiOd9MOeeUziJzAT1n6pFVAElZu/rTH\nqEhorFu0WisIpHP8xXHErudCap2gpK4VtVF4yjAuYrpJgbGCWisqo7g76mH6glC5fqKqeG9R+G8n\npPN9wBVr7TVrbQX8b8BPfcMxPwX8fevwRaAvhNh6T2e2xBJLLLHEdxXC2j+cb1MI8dPAj1tr/9Li\n/p8FnrPW/tV7jvl14K9ba393cf+3gf/IWvuVb3itvwz85cXdp4BXvluG/BHFKnB4v0/iPmM5B8s5\ngOUc/MvYf85au/advMn7WqVjrf0l4JcAhBBfsdZ+5P18/3/dsJyD5RzAcg5gOQfvl/3fTkjnDnDm\nnvunF2P/sscsscQSSyxxH/HtOPwvA48IIS4IIQLgZ4DPfsMxnwV+Vjh8DJhYa3e+8YWWWGKJJZa4\nf/iWIR1rbSOE+KvA53Blmb9srX1VCPHzi8f/FvDPcCWZV3BlmX/+23jv70ix5XsMyzlYzgEs5wCW\nc/C+2P8tk7ZLLLHEEkt8b2DZabvEEkss8YBg6fCXWGKJJR4Q3BeHL4T4cSHEm0KIK0KIX7gf5/Dd\nghDijBDinwshXhNCvCqE+HcW40MhxG8KIS4v/g/uec4vLmx/UwjxY/eMf1gI8fLisf9uQVmBECIU\nQvzqYvx5IcT599vObwUhhBJCfH3Rk/Eg2t8XQvyaEOINIcTrQojvfwDn4N9b/AZeEUL8ihAi+l6f\nAyHELwsh9oUQr9wz9r7YLIT4ucV7XCgy34YAAAOnSURBVBZC/Ny3dcLW2vf1D5f4vQpcBALgReCJ\n9/s8vov2bAHPLm53gLeAJ4D/HPiFxfgvAP/Z4vYTC5tD4MJiLtTisS8BHwME8H8DP7EY/yvA31rc\n/hngV++33X/APPz7wP8K/Pri/oNm/98D/tLidgD0H6Q5AE4BbwPx4v7/Dvy57/U5AP4Y8Czwyj1j\n/8ptBobAtcX/weL24Fue732YoO8HPnfP/V8EfvF+f3DfRfv+CY536E1gazG2Bbz5B9mLq376/sUx\nb9wz/mngb997zOK2h+vIE/fb1nvO9TTw28AneNfhP0j293DOTnzD+IM0B6eAWwsH5AG/DvzogzAH\nwHl+v8P/V27zvccsHvvbwKe/1bnej5DOO1+Md3B7MfZHHovt1oeA54EN+24vwi6wsbj9zew/tbj9\njeO/7znW2gaYACvfdQO+c/w3wH8ImHvGHiT7LwAHwN9dhLX+jhCixQM0B9baO8B/AdwEdnC9OP8P\nD9Ac3IP3w+bvyI8uk7bfJQgh2sA/Av5da+303sesuwR/T9a/CiH+JLBvrf3qNzvme9n+BTzctv5v\nWms/BKS4rfwJvtfnYBGn/incxW8baAkh/sy9x3yvz8EfhH/dbL4fDv97joZBCOHjnP0/sNb+48Xw\nnlgwhi7+7y/Gv5n9dxa3v3H89z1HCOE4leHou2/Jd4QfBP6UEOI6jkn1E0KI/4UHx35wq6vb1trn\nF/d/DXcBeJDm4JPA29baA2ttDfxj4Ad4sObgHbwfNn9HfvR+OPxvh6rhjwwW2fT/CXjdWvtf3fPQ\nZ4F3Muc/h4vtvzP+M4vs+wWchsCXFlvAqRDiY4vX/NlveM47r/XTwOcXK4f7DmvtL1prT1trz+M+\ny89ba/8MD4j9ANbaXeCWEOLSYuhPAK/xAM0BLpTzMSFEsjj3PwG8zoM1B+/g/bD5c8CPCiEGi93V\njy7G/nDcpyTHT+KqWa4Cf+1+nMN30ZYfwm3ZXgJeWPz9JC7O9tvAZeC3gOE9z/lrC9vfZJGNX4x/\nBEcZfRX4G7zbCR0B/xBHXfEl4OL9tvubzMWP8G7S9oGyH/gg8JXF9+D/xFVOPGhz8J8AbyzO/3/G\nVaN8T88B8Cu4nEWN2+n9xffLZuAvLMavAH/+2znfJbXCEkssscQDgmXSdokllljiAcHS4S+xxBJL\nPCBYOvwlllhiiQcES4e/xBJLLPGAYOnwl1hiiSUeECwd/hJLLLHEA4Klw19iiSWWeEDw/wMvQRro\nASxkOgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbaba8438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.io.wavfile import read #wav beolvasáshoz\n",
    "\n",
    "audio_name='sikoly.wav'\n",
    "audio=read(audio_name) # hangfájl beolvasása\n",
    "sound=np.array(audio[1], dtype=float) #átalakítás np array-ba\n",
    "print(\"A spektrogram:\")\n",
    "plt.specgram(sound, 256, 2,0) #spektogram sound-ból\n",
    "plt.show() #hibaüzenet a metadata miatt\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "collapsed": true
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        Connect with Snopes      TOP TAGS:   ASP Article donald trump barack obama hillary clinton Not Necessarily The News animals election 2016 fake news politics music hoaxes facebook Movies something for nothing Radio & TV Television           What’s New  Hot 50  Fact Check  News  Video  Archive  About  FAQ  Contact  Random                                        What's New    Hot 50    Fact Check    News    Video      Archive    Automobiles    Business    Cokelore    College    Computers    Crime    Critter Country    Disney    Embarrassments    Fauxtography    Food    Fraud & Scams    Glurge Gallery    History    Holidays    Horrors    Inboxer Rebellion    Language    Legal Affairs    Lost Legends    Love    Media Matters    Medical    Military    Questionable Quotes    Racial Rumors    Radio & TV    Religion    Risqué Business    Science    September 11th    Sports    Travel    Weddings      About    FAQ    Contact    Random                 Automobiles  Business  Cokelore  College  Computers  Crime  Critter Country  Disney  Embarrassments  Fauxtography  Food  Fraud & Scams  Glurge Gallery  History  Holidays  Horrors  Inboxer Rebellion  Language  Legal Affairs  Lost Legends  Love  Media Matters  Medical  Military  Questionable Quotes  Racial Rumors  Radio & TV  Religion  Risqué Business  Science  September 11th  Sports  Travel  Weddings                   Get the Newsletter  Contact Us      Thank you for signing up: User@email.com   Sign up for the Snopes.com newsletter and get daily updates on all the best rumors, news and legends delivered straight to your inbox.                   cancel      Know of a rumor you want investigated? Press related inquiry? Lonely and just want to chat?  Select from one of these options to get in touch with us:    Submit a Rumor   Website Feedback   Advertising Inquiry  cancel                5K                         Fact Check  Technology              Did Facebook Shut Down an AI Experiment Because Chatbots Developed Their Own Language?  Facebook's artificial intelligence scientists were purportedly dismayed when the bots they created began conversing in their own private language.             5K                CLAIM  Concerned artificial intelligence researchers hurriedly abandoned an experimental chatbot program after they realized that the bots were inventing their own language.       FALSE     RATING   FALSE  ORIGIN It is probably not a coincidence that two of the top-trending news stories of July 2017 were, in the first case, a warning from billionaire tech entrepreneur Elon Musk that artificial intelligence (AI) poses an “existential threat” to human civilization, and, in the second case, the announcement that an AI experiment sponsored by Facebook was, according to some sources, “shut down” after researchers discovered that the chatbots they programmed had begun communicating with one another in a private language of their own invention. Musk, who has previously warned that the development of autonomous weaponry could lead to an “AI arms race”, told the National Governors Association on 15 July 2017 that the risks posed by artificial intelligence are so great that it needs to be proactively regulated before it’s too late. “Once there is awareness,” Musk said, “people will be extremely afraid, as they should be.” Whether he meant it to or not, in some people’s minds Musk’s warning conjured up images of Skynet , the fictional AI network in the Terminator film series that became self-aware and set out to destroy the human race in the interests of self-preservation. Cue the “creepy chatbot” stories. Albeit prompted by a somewhat dry 14 June blog post by Facebook’s Artificial Intelligence Research team ( FAIR ) describing an inroad in the development of dialog agents (AI systems designed to communicate with humans), the news that chatbots were found to be communicating with each other via a private language received more and more sensationalized treatment in the press as the summer wore on. In a report published the day before Musk gave his speech to the governors, Fast Co. Design delivered a fascinating account of the FAIR team’s experiment with nary a hint of dystopian fear-mongering: Bob: “I can can I I everything else.”  Alice: “Balls have zero to me to me to me to me to me to me to me to me to.”  To you and I, that passage looks like nonsense. But what if I told you this nonsense was the discussion of what might be the most sophisticated negotiation software on the planet? Negotiation software that had learned, and evolved, to get the best deal possible with more speed and efficiency — and perhaps, hidden nuance — than you or I ever could? Because it is.  This conversation occurred between two AI agents developed inside Facebook. At first, they were speaking to each other in plain old English. But then researchers realized they’d made a mistake in programming.  “There was no reward to sticking to English language,” says Dhruv Batra, visiting research scientist from Georgia Tech at Facebook AI Research (FAIR). As these two agents competed to get the best deal — a very effective bit of AI vs. AI dogfighting researchers have dubbed a “generative adversarial network” — neither was offered any sort of incentive for speaking as a normal person would. So they began to diverge, eventually rearranging legible words into seemingly nonsensical sentences. The key word is “seemingly,” for in this instance the agents’ neologisms were simple, straightforward, and easily decipherable: “Agents will drift off understandable language and invent codewords for themselves,” says Batra, speaking to a now-predictable phenomenon that’s been observed again, and again, and again. “Like if I say ‘the’ five times, you interpret that to mean I want five copies of this item. This isn’t so different from the way communities of humans create shorthands.” The article notes that the researchers chose not to let the bots continue developing a private language in favor of programming them to stick to plain English, given that the whole point of the research is to improve AI-to-human communication. That decision took on a more and more sinister vibe as more and more venues reported the story, however, as exemplified in this small sampling of the dozens of blurbs shared via social media: Among other misrepresentations, some articles claimed that the scientists were “shocked” or “surprised” when the chatbots invented new forms of expression. Not so, the study’s lead author, Michael Lewis, told us via e-mail: We gave some AI systems a goal to achieve, which required them to communicate with each other. While they were initially trained to communicate in English, in some initial experiments we only reward them for achieving their goal, not for using good English. This meant that after thousands of conversations with each other, they started using words in ways that people wouldn’t. In some sense, they had a simple language that they could use to communicate with each other, but was hard for people to understand. This was not important or particularly surprising, and in future experiments we used some established techniques to reward them for using English correctly. There have also been a number of papers from other research groups on methods for making AIs invent simple languages from scratch. As to the claim that the project was “shut down” because the bots’ deviation from English caused concern, Lewis said that, too, misrepresents the facts: There was no panic, and the project hasn’t been shut down. Our goal was to build bots that could communicate with people. In some experiments, we found that they weren’t using English words as people do — so we stopped those experiments, and used some additional techniques to get the bots to work as we wanted. Analyzing the reward function and changing the parameters of an experiment is NOT the same as “unplugging” or “shutting down AI.” If that were the case, every AI researcher has been “shutting down AI” every time they stop a job on a machine. The main thing lost in all the hubbub about dialog agents inventing their own language, Lewis said, is that the study produced significant results in terms of its core mission: training bots to negotiate with people, a task that requires both linguistic and reasoning skills: We introduced a new technique for having bots simulate possible future conversations before deciding what to say (“If I say this, you might say that, then I’ll say this”), and found that this significantly improved their ability on the negotiation task. We asked, finally, if Lewis and his colleagues see anything inherently dangerous in letting AI systems develop their own languages. He said no. “While it is often the case that modern AI systems solve problems in ways that are hard for people to interpret, they are always trying to achieve the goals that were given to them by people.” William Wisher, who wrote the Terminator  films (among others) and who was part of a panel about artificial intelligence and its future at the 2017 San Diego Comic-Con, weighed in on the Skynet scenario, telling us: Right now, everyone is terrified of AI and project nightmarish scenarios around it, assuming that we are creating our own new overlords. I’ve been part of that in the Terminator films. It makes for a good movie.  But what everyone fails to appreciate in these fever dreams is that human beings are the most adaptable, clever, and aggressive predators in the known universe. That really helps me sleep at night. Because I don’t believe AI will ever fully develop as a separate thing from people. I don’t think we’d allow it to. We are in infant stages now, but I think we will subsume AI and make it part of ourselves; better to control it. Implanting neural nets, within our brains that are connected to it, etc. Now that raises all kinds of as yet unseen “have and have not” issues. But that’s another subject for another time. 1 August 2017, 5:54 P.M.: Added quote from William Wisher.    Got a tip or a rumor? Contact us here .    Snopes Delivered to Your Inbox:                     Feedback  Sources   Filed Under:  AI  artificial intelligence  chatbots  +2 more  facebook  robots    Fact Checker:  David Emery   Featured Image:  Palto / Shutterstock.com   Published:  Aug 1st, 2017   Updated:  Aug 1st, 2017     Sources:  Domonoske, Camila.   “Elon Musk Warns Governors: Artificial Intelligence Poses ‘Existential Risk.'” NPR.   17 July 2017.  Lewis, Michael, et al.   “Deal or No Deal? Training AI Bots to Negotiate.” Facebook Engineering Blog.   14 June 2017.  Wilson, Mark.   “AI Is Inventing Languages Humans Can’t Understand. Should We Stop It?”  Fast Co. Design .   14 July 2017.   View All Featured Video    Did Jennifer Lawrence Say Hurricanes Are ‘Nature’s Wrath’ Against Trump?     Fact Check   Sep 11th, 2017 Right-wing web sites misrepresented Lawrence's assertion that climate change is caused by human activity.    Ask. Chat. Poke. Snopes Facebook Group   View All Most Searched     25K  Reese’s Peanut Butter Cups to be Discontinued?  Fact Check Fake News   Sep 14th, 2017 A prank-generating website churns out a hoax about the demise of the iconic candy.       9K  Pepsi/Frooti Contaminated with HIV?  Fact Check Food   Updated Rumors that a worker at a Pepsi or Frooti plant contaminated those beverage products by injecting HIV-infected blood into them were false.       52K  Trump Saved Two Cats After Hurricane Harvey?  Fact Check Fauxtography   Sep 5th, 2017 A photograph that purportedly shows President Trump rescuing two cats from a flooded area in Texas was digitally manipulated.       4K  Red Cross Instructed to Throw Away Donated Supplies in Texas?  Fact Check Viral Phenomena   Sep 13th, 2017 A viral video from Houston, Texas makes claims about the Red Cross' treatment of food and other items in the aftermath of Hurricane Harvey.       371K  Fabrizio Brambilla — Social Media Hacker Warning  Fact Check Computers   Updated Accepting a Facebook friend request from a stranger will not provide hackers with access to your computer and online accounts.      View All Most Shared     11K  Lowe’s Coupon Scam  Fact Check Inboxer Rebellion   Updated What appears to be a $100 (or $50) coupon giveaway by Lowe's is actually a scam.       8K  Was a Protester Throwing Explosives Into a Berkeley Crowd Before She Was Punched?  Fact Check Crime   Apr 20th, 2017 There's no evidence Louise Rosealma was using a glass bottle she appeared to be holding as an incendiary device.       79K  Did a 1950s TV Episode Feature a Character Named Trump Who Offered to Build a Protective Wall?  Fact Check Entertainment   Jan 9th, 2017 An episode of the 1950s western TV series 'Trackdown' featured a character named Walter Trump who claimed he would build a wall in order to protect a town from the end of the world.       4K  Did Jeff Sessions Say He’s Amazed a Judge ‘On an Island in the Pacific’ Can Block Executive Orders?  Fact Check Politics   Apr 20th, 2017 The Trump administration's Attorney General expressed his amazement on a radio talk show.       17K  Ted Nugent Dodged the Draft?  Fact Check Political News   Updated Rumor holds that conservative rocker Ted Nugent evaded the Vietnam-era draft by taking drugs and acting crazy during his pre-induction physical.       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' ', 'w', 'o', 'r', 'k', 'i', 'n', 'g', ' ', 'o', 'n', ' ', 'a', ' ', 's', 'o', 'l', 'u', 't', 'i', 'o', 'n', '.', ' ', ' ', ' ', ' ', 'Y', 'o', 'u', 'r', ' ', 'N', 'a', 'm', 'e', ' ', ' ', ' ', ' ', 'Y', 'o', 'u', 'r', ' ', 'E', 'm', 'a', 'i', 'l', ' ', 'A', 'd', 'd', 'r', 'e', 's', 's', ' ', ' ', ' ', ' ', 'Y', 'o', 'u', 'r', ' ', 'F', 'r', 'i', 'e', 'n', 'd', \"'\", 's', ' ', 'A', 'd', 'd', 'r', 'e', 's', 's', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', 'O', 'K', ' ', ' ', ' ', ' ', 'C', 'o', 'p', 'y', ' ', 't', 'h', 'i', 's', ' ', ' ', 'h', 't', 't', 'p', ':', '/', '/', 'w', 'w', 'w', '.', 's', 'n', 'o', 'p', 'e', 's', '.', 'c', 'o', 'm', '/', 'f', 'a', 'c', 'e', 'b', 'o', 'o', 'k', '-', 'a', 'i', '-', 'd', 'e', 'v', 'e', 'l', 'o', 'p', 'e', 'd', '-', 'o', 'w', 'n', '-', 'l', 'a', 'n', 'g', 'u', 'a', 'g', 'e', '/', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '×', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ']\n"
     ]
    }
   ],
   "source": [
    "#web scrap\n",
    "from urllib.request import urlopen #html lekérdezéshez\n",
    "from bs4 import BeautifulSoup #html felbontásához\n",
    "from bs4.element import Comment #html szűrésére\n",
    "from collections import OrderedDict\n",
    "import string\n",
    "\n",
    "page='http://www.snopes.com/facebook-ai-developed-own-language/' #oldal címe\n",
    "html=urlopen(page).read() #oldal html kódjának beolvasása\n",
    "\n",
    "#szöveges tartalom: stack overflow-ról eltulajdonítva\n",
    "def tag_visible(element): #függvény a látható tartalom megtalálására\n",
    "    #ezek nem láthatóak:\n",
    "    if element.parent.name in ['style', 'script', 'head', 'title', 'meta', '[document]']: \n",
    "        return False\n",
    "    if isinstance(element, Comment):\n",
    "        return False\n",
    "    #többi tartalom látható\n",
    "    return True\n",
    "\n",
    "def text_from_html(body): #függvény a html->string átalakításhoz\n",
    "    soup = BeautifulSoup(body, 'html.parser') #felbontás\n",
    "    texts = soup.findAll(text=True) #összes szöveges tartalom\n",
    "    visible_texts = filter(tag_visible, texts)   #látható tartalom szűrése a tag_visible fg-el\n",
    "    return u\" \".join(t.strip() for t in visible_texts)\n",
    "\n",
    "#szöveges tartalom megjelenítése\n",
    "only_text=text_from_html(html)\n",
    "print(only_text)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SpDWTwZ0kSZIkjQCDO0mSJEkaAQZ3kiRJkjQCDO4kSZIkaQQY3EmSJEnSCDC4kyRJkqQR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\nJEmSJGkEGNxJkiRJ0gj4fz+LKS8iGsRCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efdbaafa3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from collections import Counter\n",
    "\n",
    "#hisztogram a betűk gyakoriságáról\n",
    "only_text=only_text.lower() #lowercase-ben \n",
    "list_text=[]\n",
    "for c in only_text:\n",
    "    list_text.append(c) #only_text-ből list\n",
    "letter_counts = Counter(list_text) #betűk megszámlálása\n",
    "\n",
    "\n",
    "df = pandas.DataFrame.from_dict(letter_counts, orient='index') #dataframe készítése a list-ből\n",
    "df.plot(kind='bar', figsize=(15,3), title='Hisztogram a betuk gyakorisagarol', legend=False) #plottolás\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}