Labels with Coordinates 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pillow is installed but import PIL due to backward dependency\n",
    "from PIL import Image\n",
    "from tesserocr import PyTessBaseAPI, RIL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "base = '/Users/macbook/Desktop/images/'\n",
    "index = 28559\n",
    "path = str(index) + '.png'\n",
    "image = Image.open(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------\n",
      "Found 8 text labels.\n",
      "-----------------------\n",
      "[0]: x=129, y=103, w=183, h= 25, confidence:  0, text: \n",
      "[1]: x=129, y=145, w=176, h= 32, confidence: 81, text: containing\n",
      "\n",
      "\n",
      "[2]: x=129, y=178, w=961, h= 39, confidence: 88, text:  \n",
      "\n",
      " \n",
      "\n",
      " \n",
      "\n",
      "copper power - Wire gauze\n",
      "\n",
      " \n",
      "\n",
      " \n",
      "\n",
      "\n",
      "[3]: x=906, y=277, w=217, h= 32, confidence: 86, text: Tripod stand\n",
      "\n",
      "\n",
      "[4]: x=907, y=384, w=120, h= 23, confidence: 84, text: Burner\n",
      "\n",
      "\n",
      "[5]: x=116, y=691, w=251, h= 41, confidence: 87, text: Figure 1.10\n",
      "\n",
      "\n",
      "[6]: x=118, y=734, w=1026, h= 57, confidence: 82, text: Oxidation of copper to 2Cu + 02 ﬂ\n",
      "\n",
      "\n",
      "[7]: x=118, y=793, w=240, h= 39, confidence: 86, text: copper oxide\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "api = PyTessBaseAPI()\n",
    "api.SetImage(image)\n",
    "boxes = api.GetComponentImages(RIL.TEXTLINE, True)\n",
    "print '-----------------------'\n",
    "print 'Found {} text labels.'.format(len(boxes))\n",
    "print '-----------------------'\n",
    "# im is a PIL image object\n",
    "# box is a dict with keys x, y, w and h\n",
    "for i, (im, box, _, _) in enumerate(boxes):\n",
    "    api.SetRectangle(box['x'], box['y'], box['w'], box['h'])\n",
    "    ocrResult = api.GetUTF8Text()\n",
    "    conf = api.MeanTextConf()\n",
    "#     if conf < 70: continue\n",
    "    print (u\"[{0}]: x={x:3}, y={y:3}, w={w:3}, h={h:3}, \"\n",
    "           \"confidence: {1:2}, text: {2}\").format(i, conf, ocrResult, **box)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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ARt7/0LmSqMbgQTaMcX9mX8RNfSg1ri2W+vuCeiaovcRS/wlB3YW6C/VPQf1b\nQX1C1B8J6kOpcWmxqb8vqGeC2kss9Z8Q6iHUQ6h/COrfCuoTov5IUB9KjUuLTf19QT0T1F5iqf+E\nqBehXkT9U9S/FtTvhfojQX0oNS4tNvX3BfVMUHuJTf0HRC2hXkR9s6B+K6g/EtSHUuPSYqkdBPVM\nUHuJTf23hPpI1IdCvRPqvVAE9YFQS9zVW6E+EvVOKIL6UGpcWiy1g6CeCWovsan/llCv4q7irSLu\nGkstsakllgb1s3jRKPGq7mJTD3FXsdQSS4P6UGpcWiy1g6CeCWo3sdR/S6hX8U7jroilxE09BEVQ\nD3FTxF39JNRNUHdBLaFugrqLuwYVN/UQN0Xc1YdS49JiqR0E9UxQu4mlXkVdXqi34qaEIqi7uKmH\nUHdB3QV1E9SLoN4L9RDqLqgXoR6Ceoi7ugvqLqgXQX0oNa4sNrWDoJ4Jajex1BLU5YV6K6hXQd0F\n9SIognoR6ibUEtR7oV5E3QX1ItSLUA9BLaHuQi1BfSg1riw2tYOgnglqN7HUQ9zV5YV6K9QPQd0F\ntYQiqBdBCWoJ6r2gXqTugnoR6kWoh6CWUDdBLUF9KDWuLDa1g6CeCWo3sSniRV1eqLdC/RDUXVBL\nUEItQQlqCeq9uKs3gvqHUA9BLaFuglqC+lBqXFkstYegnglqN7GpuLJ6J9RboX4I6i6oJaigNqGE\n2gT1k1hqCepnQT0EtYS6CWoJ6kOpcWWx1B6Ceiao3cR/Rb0T6q1QPwR1F9QSVFCbUEJtgvpZvKq7\noN6IpR6CWkLdhNoE9aHUuLJYag9BPRPUfmJpXFq9E+qtUD8EdRfUElRQm1BCbYL6p9jUTVCbuClC\nPQS1hLoJtQnqQ6lxZbHUHoJ6Jqj9xFLiwuqdUG+F+iGou6CWoILahBJqE9TH4q5ugnoR1EOoh6CW\nUDdBLUF9KDUuLDa1h6CeCWo/sdRNPNTlhXor1A9B3QW1BCXUEpSglqDeiVripgjqIagXoR6CWkLd\nBLUE9aHUuLDY1B6Ceiao/cRSD3FTlxfqrVA/BHUX1BKKoF4EJaglqHeiXoUiqIegXoR6CGoJdRPU\nEtSHUuPCYlN7COqZoPYTm3oR6vJCvRXUq6DugnoRFEG9CHUTagnqvahNKIJ6COpFqIegllB3oZag\nPpQaFxZL7SKoZ4LaT2xqk7q6oN4K6lVQd9qX2PIAACAASURBVEG9CHUX1F1QN0E9xE29F+pFqJug\nHoK6i5t6CGoJ6iaoh7ipD6XGhcVSuwjqmaD2E5v6D4mb+iFuahM3dRd3RVAvgiKoh7gp8VDvxU3d\nhHoISlTcVGhQd3FTD3FTd3FT4qE+lBoXFkvtIqhngtpRLPVfEa/qIZa6i6UIGi9qE0tt4kXFXb0V\njaVexIsiXpS4aywllrqJFxV39YHUuLBYahdBPRPUjmKp/09BEfWTqPeifinUW1FL1BL1a1G/lhrX\nFZvaRVDPBLWjWOr/U1AXlBrXFZvaRVDPBLWjWOr/U1AXlBrXFZvaRVDPBLWj2NT/paAuKDWuK5ba\nR1DPBLWj2NT/paAuKDWuK5baR1DPBLWj2NT/paAuKDWuK5baR1DPBLWnWOr/UdzV9aTGdcVS+wjq\nmVC7iqX+D8VSV5MalxWb2kdQz4TaVSw1riQ1Lis2tY+gngm1q1hqXElqXFZsah9BPRNqV7GpcSGp\ncVmx1E6CeibUrmJT40JS47JiqZ0E9UyoXcWmxoWkxmXFUjsJ6plQ+4qlxoWkxmXFUjsJ6plQ+4ql\nxoWkxlXFpnYS1DOh9hVLjQtJjauKTe0kqGdC7SuWGheSGlcVm9pJUM+E2ldsalxHalxVLLWXoJ4J\nta/Y1LiO1LiqWGovQT0Tal+xqXEdqXFVsdRegnom1M5iqXEdqXFVsdRegnom1M5iqXEdqXFRsam9\nhHoq1M5iqXEdqXFRsam9hHoq1M5iqXEdqXFRsam9hHoq1M5iU+MyUuOiYqndhHoq1M5iU+MyUuOi\nYqndhHoq1M5iU+MyUuOiYqndhHoq1N5iqXEZqXFRsdRuQj0Vam+x1LiM1Lim2NRuQj0Vam+x1LiM\n1Lim2NRuQj0Vam+x1LiM1Lim2NRuQj0Vam+xqXEVqXFNsdR+Qj0Vam+xqXEVqXFNsdR+Qj0Vam+x\nqXEVqXFNsdR+Qj0Vanex1LiK1LimWGo/oZ4KtbtYalxFalxSbGo/oZ4KtbtYalxFalxSbGo/oZ4K\ntbtYalxFalxSbGo/oZ4KtbvY1LiI1LikWGpHoZ4KtbvY1LiI1LikWGpHoZ4KtbvY1LiI1LikWGpH\noZ4Ktb9YalxEalxSLLWjUE+F2l8sNS4iNa4oNrWjUE+F2l8sNS4iNa4oNrWjUE+F2l8sNS4iNa4o\nNrWjUE+F2l9salxDalxRLLWnUE+F2l9salxDalxRLLWnUE+F2l9salxDalxRLLWnUE+FOkAsNa4h\nNa4oltpTqKdCHSCWGteQGhcUm9pTqKdCHSCWGteQGhcUm9pTqKdCHSCWGteQGhcUm9pTqKdCHSA2\nNS4hNS4oltpVqKdCHSA2NS4hNS4oltpVqKdCHSA2NS4hNS4oltpVqKdCHSGWGpeQGhcUS+0q1FOh\njhBLjUtIjeuJTe0q1FOhjhBLjUtIjeuJTe0q1FOhjhBLjUtIjeuJTe0q1FOhjhCbGleQGtcTS+0r\n1FOhjhCbGleQGtcTS+0r1FOhjhCbGleQGtcTS+0r1FOhDhFLjStIjeuJpfYV6qlQh4ilxhWkxuXE\npvYV6qlQh4ilxhWkxuXEpvYV6qlQh4ilxhWkxuXEpvYV6qlQh4hNjQtIjcuJpXYW6qlQh4hNjQtI\njcuJpXYW6qlQh4hNjQtIjcuJpXYW6qlQx4ilxgWkxuXEUjsL9VSoY8RS4wJS42piUzsL9VSoY8RS\n4wJS42piUzsL9VSoY8RS4wJS42piUzsL9VSoY8SmxvmlxtXEUnsL9VSoY8SmxvmlxtXEUnsL9VSo\nY8SmxvmlxtXEUnsL9VSog8RS4/xS42piqb2FeirUQWKpcX6pcTGxqb2FeirUQWKpcX6pcTGxqb2F\neirUQWKpcX6pcTGxqb2FeirUQWJT4/RS42Jiqd2FeirUQWJT4/RS42Jiqd2FeirUQWJT4/RS42Ji\nqd2FeirUUWKpi4qf1X9ValxMLLW7UE+FOkosdVlxV3dxV/9NqXEtsandhXoq1FFiqcsKahM39Z+U\nGtcSm9pdqKdCHSWWuq5Qr4L6T0qNa4lN7S7UU6GOEpu6rFA/hPpPSo1riaX2F+qpUEeJTV1WqB9C\n/SelxrXEUvsL9VSom6jdxaYuK9QPoV5EvUotUQT1kLoL6o24qVdRBHWA1LiWWGp/oZ4KJaj9xVKX\nFepVUMRd3cVDEXcVD42HiqWWWOom7iru6gCpcS2x1P5CPRUad7W/WOqyQm2Cuoubeoi7uom3KjYl\nqBehboIi3qgDpMalxKb2F+qpGP9KLaFu4qGWoJagHuKmiLqJm3oI6i7UQ6ibuCuiDpAalxKb2l+o\np2L8K7XEO7UEtQT1ENQPQb0I6iaoh6BuQh0oNS4lNrW/UM/E+HdqCbXETb0ItQT1EOqNoJZQN0E9\nBHUT6kCpcSmx1AFCPRXjX6kl1KugHkItQT2EeiOoJdRNvFM3oQ6UGpcSSx0g1FMx/pVaQv0Q1F2o\nJaiHUG8EtYQiqJ+EOlBqXEosdYBQT4XGXR0glrqqUD8EdRdqCeoh1BtBLaEI6iehDpQalxJLHSDU\nU6EEdYBY6qpCvRHUTaglqIdQbwS1hCKon4Q6UGpcSWzqAKGeCnUTdYBY6qpCvRHUTaglqIdQbwS1\nhLoJ9ZNQB0qNK4lNHSDUU6GOE0tdVag3groJtQT1EOqNoJZQN0G9F+pAqXElsakDhHoq1HFiUxcV\n6oeg7kItQT2EeiOoJdRNUO+FOlBqXEksdYRQT4U6TmzqmoJ6FTd1F+pF3NRDqDeCWkLdBfUi6ibU\ngVLjSmKpI4R6KtRxYlPXFDe1xE09hHqIu3oI6oegXgT1EOoh6i6o46TGlcRSRwj1VKgDxVKXFEtj\nqRdx16BB3cVdbeKu7uKu7uKugrqJuzpMalxJLHWEUE+FOlAsdUHxs/ohXpS4q9jUXWxKLHUXL+om\nljpKalxIbOoIoZ4KdaBYapxbalxIbOoIoZ4J6kCx1Di31LiQ2NQRQj0T1IFiU+PUUuNCYqlDhHom\nqAPFpsappcaFxFKHCPVMUAeKTY1TS40LiaUOEeqZoI4US41TS40LiaUOEeqZoI4US41TS43riE0d\nItQzQR0plhqnlhrXEZs6RKhngjpSLDVOLTWuIzZ1iFDPBHWk2NQ4s9S4jljqGKGeCepIsalxZqlx\nHbHUMUI9E9SRYlPjzFLjOmKpY4R6JqhDxVLjzFLjOmKpY4R6JqhDxVLjzFLjMmJTxwj1TFCHiqXG\nmaXGZcSmjhHqmaAOFUuNM0uNy4hNHSKoZ4I6VGxqnFhqXEYsdYygngnqULGpcWKpcRmx1DGCeiao\nQ8WmxomlxmXEUscI6pmgjhVLjRNLjcuIpY4R1DNBHSuWGieWGlcRmzpGUM8EdaxYapxYalxFbOoY\nQT0T1LFiqXFiqXEVsaljBPVMUMeKTY3zSo2riKUOEtQzQR0rNjXOKzWuIpY6SFDPBHWs2NQ4r9S4\niljqIEE9E9TBYqlxXqlxFbHUQYJ6JqiDxVLjvFLjImJTBwnqmaAOFkuN80qNi4hNHSSoZ4I6WGxq\nnFZqXERs6iBBPRPUwWJT47RS4yJiqaME9UxQB4tNjdNKjYuIpY4S1DNBHSw2NU4rNS4iljpKUM8E\ndbRYapxWalxELHWUoJ4J6mix1Dit1LiG2NRRgnomqKPFUuO0UuMaYlNHCeqZoI4WmxpnlRrXEJs6\nSlDPBHW02NQ4q9S4hljqMEE9E9TRYlPjrFLjGmKpwwT1TFBHi02Ns0qNa4ilDhPUM0EdLpYaZ5Ua\n1xBLHSaoZ4I6XCw1zio1LiE2dZigngnqcLHUOKvUuITY1GGCeiaow8WmxkmlxiXEpg4T1DNBHS42\nNU4qNS4hljpOUM8EdbjY1Dip1LiEWOo4QT0T1OFiU+OkUuMSYqnjBPVMUMeLpcZJpcYlxFLHCeqZ\noI4XS42TSo0riE0dJm7qmbipw8VS46RS4wpiU0eJu3oiHuposalxTqlxBbGpg8RS/xSv6mCxqXFO\nqXEFsdRR4nPqYLGpcU6pcQWx1FGCxq80qKPFUuOcUuMKYqmjBCU+VjdBHS2WGueUGhcQmzpKUA/x\nk3oR1NFiqXFOqXEBsamjBPVrQR0tlhrnlBoXEJs6SlC/FtTRYlPjlFLjAmKpwwT1a0EdLTY1Tik1\nLiCWOkxQvxbU0WJT45RS4wJiqcME9WtBHS6WGqeUGhcQSx0mqF8L6nCx1Dil1Di/2NRhgvq1oA4X\nS41TSo3zi00dJqhfC+pwsdQ4pdQ4v9jUYYL6taAOF5saZ5Qa5xdLHSeoXwvqcLGpcUapcX6x1HGC\n+rWgDhebGmeUGucXSx0nqF8L6nix1Dij1Di/WOo4Qf1aUMeLpcYZpcbpxaaOE1Q81Kt4qJugjhdL\njTNKjdOLTR0n3qolliKo48VS44xS4/RiU8eJd+ohXpWgjhebGieUGqcXSx0o3qmH+KGCOl5sapxQ\napxeLHWgeK/u4ocK6nixqXFCqXF6sdSB4r26ix8qqBOIpcYJpcbpxVIHivfqLn6ooE4glhonlBpn\nF5s6ULxXd/FDBXUCsdQ4odQ4u9jUgeK9uosfKqgTiKXGCaXG2cWmDhTv1V38UEGdQGxqnE9qnF0s\ndaR4r+7ihwrqBGJT43xS4+xiqSPFe3UXP1RQJxCbGueTGmcXSx0p3qu7+KGCOoNYapxPapxdLHWk\neK/u4ocK6gxiqXE+qXFysakjxXt1Fz9UUGcQS43zSY2Ti00dKd6ru/ihgjqDWGqcT2qcXGzqSPFe\n3cQbFdQZxKbG6aTGycVSh4r36ibeqKDOIDY1Tic1Ti6WOlS8VzfxRgV1BrGpcTqpcXKx1KHivbqJ\nNyqoU4ilxumkxsnFUoeK9+om3qigTiGWGqeTGucWmzpUvFc38UYFdQqx1Did1Di32NSh4r26iTcq\n1DnEUuN0UuPcYlOHivfqJt6oUOcQmxpnkxrnFksdK96rm3ijQp1DbGqcTWqcWyx1rHivbuKNCnUO\nsalxNqlxbrHUseK9uok3KtRJxFLjbFLj3GKpY8V7dRNvVKiTiKXG2aTGqcWmjhXv1U28UaFOIpYa\nZ5MapxabOla8U3fxRoU6iVhqnE1qnFps6ljxTt3FGxXqJGJT42RS49RiqYPFO3UXb1Sok4hNjZNJ\njVOLpQ4W79RdvFGhTiI2NU4mNU4tljpYvFN38UaFOotYapxMapxaLHWweKfu4o0KdRax1DiZ1Diz\n2NTB4p26izcq1FnEUuNkUuPMYlMHi3fqIX6oUGcRS42TSY0zi00dLN6ph/ihQp1FbGqcS2qcWSx1\ntNDY1It4VUKdRWxqnEtqnFksdbRQ8aI2sRShziI2Nc4lNc4sljpaqJtQb8VN3YU6jVhqnEtqnFks\ndbRQvxHqNGKpcS6pcWKxqaOF+o1QpxFLjXNJjROLTR0t1G+EOo1YapxLapxYbOpooX4j1GnEpsap\npMaJxVKHC/UboU4jNjVOJTVOLJY6XKjfCOosYlPjVFLjxGKpw8VdPRUPdRqx1DiV1DixWOpw8U69\nirfqNGKpcSqpcV6xqaPFJ9VpxFLjVFLjvGJTR4tPqtOIpcappMZ5xaaOFjclnilBnUZsapxJapxX\nLHW0+LQ6i9jUOJPUOK9Y6lDxNXUOsalxJqlxXrHUoeKL6hxiqXEmqXFesdSh4ovqHGKpcSapcVqx\nqUPFF9U5xFLjTFLjtGJThwqK+KQ6h1hqnElqnFZs6lChXsQv1E1Q5xCbGieSGqcVSx0r1It4rh5C\nnUNsapxIapxWLHWsUK/iI7UJ9S/FU/V1salxIqlxWrHUsUJ9WqgPxR+pL4ulxomkxmnFUscK9Vnx\n19RXxVLjRFLjrGJTxwr1WfGt6iHu6otiqXEiqXFWsaljhfqs+Ir6rLipr4mlxomkxlnFpo4V6rPi\nh/pGQX1NbGqcR2qcVSx1sFCfFdTfENSXxKbGeaTGWcVSBwv1WUH9FaG+JDY1ziM1ziqWOliozwrq\nrwjqS2KpcR6pcVax1MFCfVZQf0VQXxJLjfNIjZOKTR0s1GcF9XeE+pJYapxHapxUbOpgoT4rqL8j\n1JfEUuM8UuOkYlMHC/VZQf0dob4kNjVOIzVOKpY6WqjPCurvCPUlsalxGqlxUrHU0UJ9VlB/R6gv\niU2N00iNk4qljhbqs4L6K4L6mlhqnEZqnFQsdbRQnxXUXxHU18RS4zRS45xiU0cL9VlBfVXq90J9\nUSw1TiM1zik2dbRQnxXUF0U9RD2Eugv1ENQXxVLjNFLjnGJTRwv1WUF9Tai7UMQz9UWxqXEWqXFO\nsdThQn1WUE/Fn6ivik2Ns0iNc4qlDhfqs+Ivqq+KTY2zSI1ziqUOF+qz4i+ofy2WGmeRGucUSx0u\n1GfF19TfFUuNs0iNU4pNHS7UZ8UPdbxYapxFapxSbOpwoT4rqPOIpcZZpMYpxaYOF+qzgjqP2NQ4\nidQ4pVjqeKE+K6jziE2Nk0iNU4qljhdqEx+oV0GdR2xqnERqnFIsdbS4qRfxXN0FdSKx1DiJ1Dil\nWOo48apexHN1F3d1GrHUOInUOKPY1CHivXojbho/qbt4VWcQS42TSI0zik3tLj5WT6Ue4h/qYLHU\nOInUOKPY1K7ic+qH+J06UGxqnENqnFEstZ/4NiXeq4PEpsY5pMYZxVI7ie9VN/FOHSE2Nc4hNc4o\nltpF/F7jS+ou3qn9xVLjHFLjjGKpvy8+od6Id4r4p3qId2pnsdQ4h9Q4odjU3xafUb8TH6iHeKd2\nFUuNc0iNE4pN/V3xGfV78aF6iPdqP7HUOIfUOKHY1N8Un1GfEh+rF/FO7SU2NU4hNU4olvqL4lPq\nk+KJehHv1D5iU+MUUuOEYqm/Jj6lPi2eqiXeqj3EpsYppMYJxVJ/S3xGfUU8V5t4o3YQS41TSI0T\niqX+hvik+pL4lXoVr+rvi6XGKaTG+cSmvld8QX1V/FK9irfqr4qlximkxvnEpr5NfFF9XfxavYqf\n1N8SS41TSI3ziU19i/iy+lfiN+qH+Fn9DbGpcQapcT6x1DeIr6t/KX6r3oh/qO8WmxpnkBrnE0v9\nsfi6+vfi9+qH+EB9q9jUOIPUOJ9Y6g/F19UfiU+oV/Gh+kax1DiD1DifWOqPxL9QfyY+pTbxsfo2\nsdQ4g9Q4ndjUn4ivqz8Wn1Mv4pn6JrHUOIPUOJ3Y1B+IL6vvEJ9Ud/FUfY/Y1DiB1DidWOoPxFfV\n94hPK/EL9S1iU+MEUuNsYlP/XnxVfZf4NvUtYqlxAqlxNrGpfy++pr5RfJf6FrGpcbzUOJvY1L8X\nX1HfKr5LfYvY1DheapxMbOpPxKfVd4tvUt8iNjWOlxonE5v6E/EF9c3ie9T3iE2Nw6XGycSm/kR8\nUX2j+B71PWJT43CpcS6xqT8S/0Z9k/gW9T3iVY2jpca5xKb+SPyB+mPxHeqbxKbG0VLjVGJTfya+\nQf1r8QuNz6lvEq9qHCw1ziRe1Z+Jb1afFL9SL+Iz6rvEpsbBUuNMYlN/KM6n3orfq+8Sr2ocKzVO\nJF7VH4pTqX+K36pvE5sax0qNE4lN/aH4Y41vVK/i0+rbxKsah0qN84hX9YfiQ3UTn1Gv4u+rm/hJ\nfZ94VeNIqXEa8ar+VHyofohzqFfxk/o+8UONA6XGWcQP9cfiI/WBOET9Q/ykvlH8UOM4qXES8UP9\nufhI/Ur8dfUL8bP6TvGqxnFS4xzih/oG8ZH6nPhW9Snxk/pW8UONw6TGKcQb9Q3iI/Ul8Wfqa+Kd\n+mbxRo2DpMYZxBv1HeIj9SXxC5X6QLyqr4l36rvFGzWOkRonEG/Ut4iP1JfEM009Ea/qS+K9+nbx\nRo1DpMbx4o36HvFMfVo8Vc/Eq/q0+Kf6dvFWjSOkxtHirfom8aKIf6jPiKcq9aF4VZ8RP6u4q28X\nb9U4QGocLN6q7xIPtcQH6tfiqZL6SLyq34h/qru4qe8X79TYXWocKt6p7xN39UY8Ux+K5+qJeFVP\nxIfqh6D+gnivxs5S40DxXn2jeKifxO/UJn6lPhSv6q34hfpZUH9BvFdjX6lxmPhJfatY6q2gbuKP\nNOoj8VX1kaD+hvhJjT2lxkHiZ/XN4o1agnojjlF3oT4SN/V3xE9q7Cc1DhH/UN8vflZBfSh2UO+E\n+qd4qL8k/qHGTlLjAPFP9XfEB+q34vvUc6F+Fi/qr4l/qrGL1NhbfKD+pvhJ/Yn4SP0rod6LF/VX\nxQdq/H2psaf4WO0gXtVphHojNvWXxYdq/GWpsZt4ov6PhXqIt2oH8USNvyg19hDP1f+1+EDtJZ6r\n8Xekxl8Xv1D/7+Intaf4hRp/Q2r8bfFcjXij9he/UOP7pcZfFk/VuAt1qHimxvdLjb8snqhxHvFE\njW+XGn9ZfKTGycSHany71PjL4h9qnFL8U41vlxp/WbxX48zinRrfLzX+tnhV4wriVY3vlxp/X9zU\nuJK4qfE3pMYYY1+pMcbYV2qMMfaVGmOMfaXGGGNfqTHG2FdqjDH2lRpjjH2lxhhjX6kxxthXaowx\n9pUaY4x9pcYYY1+pMcbYV2qMMfaVGmOMfaXGGGNfqTHG2FdqjDH2lRpjjH2lxhhjX6kxxthXaowx\n9pUaY4x9pcYYY1+pMcbYV2qMMfaVGmOMfaXGGGNfqTHG2FdqjDH2lRpjjH2lxhhjX6kxxthXaowx\n9pUaY4x9pcYYY1+pMcbYV2qMMfaVGmOMfaXGGGNfqTHG2FdqjDH2lRpjjH2lxhhjX6kxxthXaowx\n9pUaY4x9pcYYY1+pMcbYV2qMMfaVGmOMfaXGGGNfqTHG2FdqjDH2lRpjjH2lxhhjX6mTCjXG+C9K\nnVLc1RjjPyh1RvGixhj/PaljxMfqLl7UwUJ9Sqh/ik2NMV6kjhFP1E28qAPFi/qdeFE/iTdqjPGQ\nOkY8UTfxog4Rb9QvxBv1XrxXY4y71DHiibqJhzpGvFG/EG/UO/GzGmPcpI4SmyI2RdzVQeKN+oV4\no96KF0W8qDEGqcPEi3oRD3UX6jDxQ/1K/FBvxIu6i4caY5A6TLyoJe7qHOJF/U68qDfioR7iRY0x\npA4TD3UXJW7qY3FXXxc39Ubc1a/Ei/qdeFE/xIt6EQ81xpA6TDzUTSjipsRDvYqf1U3c1V28qBdx\nV/GiXsQP9VQ81G/FQ70RD7XEQ40xpI4SL4qgiLfqVfxDY1N38VA38U91F+/UE/Gifide1A/xopZ4\nqDGG1FHiRRHUTbxRS/xTxabu4qFu4p+K+Fl9LF7U78SL+iEeahMPNcaQOkq8KHFTD/GqXsRSYmm8\nqrt4KOIDJV4U8VAfixf1O/GiXsWL2sRDjTGkjhLv1UO8qhfxou7iobGph3go4gMVL+omHupj8aJ+\nJ17Uq3hRm3ioMYbUUeK92sSLeogX9RAPRTzUQzzUQywlbipe1F081MfiRf1OvKhX8aI28VBjDKmj\nxDv1Kl7UXbyoF/FQxEPdxUO9iBf1Kh7qLl7Ux+Khfise6od4qE28qDGG1EHivXoVD/UQL+ohXhTx\nUHfxUC/iRW3iRRFLfSxe1O/Ei/oh/tcevCA0cm1JAIzc/6Jzzq2PEEgN9nPbapiK2NQpdnW5XKRe\nJHYlRt3Epjaxq01sasSmltjULjZ1E4/qF2JXX4ldvYlNnWJXl8tF6kViVwR1E5taYle72NSITS2x\nqU3s6iYe1K/Err4Su3oTmzrFri6Xi9SLxKZGUDexqSV2tYtNjVhqE5vaxK5O8VH9WuzqK7GrN7Gp\nU2zqcrmQepHY1Ah1E7taYleb2BWxqU1sahObuok79YXY1JdiU3diU4fY1eVyIfUasasR6iZ2tcSu\nNrErYlNLbGoXm7qJXf0VsakvxabexK4OsanL5TJSrxG7ehCb2sSuljgUsaklNrWLTd3Erm5SvxC7\nei+oe7GrO7GpXezqcrmM1GvErh7EpjaxqyV2NWJTS2xqF5u6iV2dQj0Xu3onlroTu7oTm9rFpi6X\ny5J6jdjVg9jULjY14lAjNjViV5vY1J3Y1SaWeip2dS82dSd2dSd2tcSuLpfLknqJONSDeFPiUHGq\nEc+V2NSdOBSxq2fiUHfiUDdxqHuxqRG7ulwum9R/L96p9+JNiSdqxC9UbOpefFSP4qPaxa528VEd\n4tA41OVy2aX+e/FOvRdvinhUI36hYlPvxHv1KD6qQ+xqEx/VTXxQl8vlkPrvxTv1XtzUEqfGppZ4\n07gpsan34k49Ex/VITa1i4/qTbxTl8vllPrvxb16EJs6xaZiU7vY1YhNjdjUR3Go5+KjOsWoQ3xU\n9+KmLpfLm9R3Erv6HoK6XC7vpf5sMeoQu7pcLt9X6o8WS+1iV5fL5RtL/dFiU0vs6nK5fGepP1oc\nGjd1uVy+s9QfLR7V5XL51lJ/tvigLpfLN5f6w8W9ulwu317qG4hNXS6XnyB1uVwu/63U5XK5/LdS\nl8vlsksdUv+i1OVyuWziTW3iTf19oR6kLpfL5RRL3Yml/iehHqQul8vlJkbdi1H/k1APUpfL5XIT\n1DtB/W9CPUhdLpfLTVDvBPW/CfUgdbn8cLGrX4lDvUAc6g8Q1DtB/U+CepC6XH60uFNPxJ0i6r8S\n79SrBfVOUP+LGPUgdbn8YLGp2NUHsSuxNNR/Iw4Vu3qtoN4J6l6Mei9G3cSuHqR+jKD+UHGoy38o\nRm1iU/diU4fY1H8iljrEpl4pqHeCuombOsSb2sWdupd6tbip/1Xs6s8Up7r8d4K6iaXexFJvYqn/\nQoy6E0u9UFDvBHUKihi1CWrEUocY9SD1WvFOfSnUR7Grr0XdhPrXhSKo7yHq2wvqTSx1E0u9E6P+\nfTHqnRj1QkG9E9QhqE1QI6hdUKegHqReKTY1YqnPxahHsdSXQh1i1L8tqBHqWwj17QV1J5Y6xaj3\nYtS/LkZ9EKNeJ0bdC2oX1C5GEeoQow6hHqVeKJY6xKhPxagngvpa1ClG/cuC+l6ivr+g7sRShxj1\nUVD/tljqg1jqZeKp2gV1CIpQp6AOMACKQQAAD+ZJREFUoR6lXieWuolRn4lRTwT1tahTjPqXBfW9\nRH1/Qd2JpXax1INQ/7YY9SCWepUYdS+oTVCnoAh1CuoQ6lHqZWLUvRj1iRj1RFBfCnWKUf+yoL6V\nUN9eLPUmltrFqCei/pmgPhFLPYilXiWod4LaxEf1QVCHUI9SrxJL3YtRn0o9FdRXgnqT+rfFqO8k\nqO8vRr2JpTax1BOhTqHeCfW5UJ+JUU/EqFcJ6p2gNvFRfRDUIdSj1IvEUu/FqP9BjPpCjPpPBfWd\nxKjvL0a9iaU2sdQzUcShDnGoz4X6RCz1RCz1IkG9E9QmqF+JQx1CPUq9SIz6IEYdUqegltSb2JQY\ndRObEk2N2BWpTepNbOpeasRSn4tN3aSxVOqXYqk3sal3UiOWepMasdR7sak7KYJ6ELsitYtNfS8x\n6k0stYmlnokiDnWIQ30u1CdiqSdiqRcJ6p2gNkE9E5vGqEOoR6nXiKU+iFHEUod4U6e4aVCnuGlQ\nI+40NnWKNzViU+JUvxZvahNv6rm4qV28qSV2FYcasas41J24qRGbik19FHdqiTf1jcVSuxj1uVjq\nJjb1uVCfiFFPxagXCeqdoDZBPYillqAOoR6lXiNGfRSjxK6WuFeH2FTs6hCbil3tgtrEpg6xVCwl\ndo3RWOqXYqlY6hCjfimWxlJLLBVLjdhU3BSxqbipU4wiRokP6omgbmKpWOr7iqU2sdQXYtSbWOpz\noX4tlnoqRr1IUO8EtQnqoxi1C+oQ6lHqJWKpj2IUsakRu8ZSm1hqE0vtYqklltoFtYulNrHUEtSI\nQy1B/UIstQR1iFG/EqNGjBJLLUFtYjTUiFEjRkONGLWJUZsYRewaSz0R1CGWWoL6tmKpXSz1hRh1\nJ0Z9LtSvxVJPxagXCeqdoDZBfRCjDkEdQj1KvUQs9VGMWmLUiKWIUUssdYhRmxh1iFGbGHWIUUuM\n2sWoEUvtYtRTMWoXo3Yx6hdi1CaoGLWLUZvY1CaoJTa1CWqJUYegRixF1DMxahejdjHqu4qldrHU\nF2LUnRj1uVC/Fks9FUu9RlDvBLWJUe8FdQrqEOpR6iVi1IMYtYlRQu1i1BKjTjFqiVGnoHYx6hCj\nlhh1CGrEqENQz8WoQ1C7oH4hRu2CilGHoDax1C5GjVhqF6OIUYcYNWLUJ2LULkYdgvqmYqlDLPWF\nGHUnRn0u1K/FUk/FUq8R1DtB7YJ6kxLUKahDqEepl4hRD2LUJkaFOsSoEUudglpiqVNQu6BOMWrE\nqFOMIqhTUE/FqFOM2gT1XIw6hIpRpxg1YqlDjCKWOsQoYtQhRo0Y9YmgdjHqFKO+pVjqFEt9IUbd\niVGfC+qXYqmnYqnXCOqdoHYx6hQlqEOMOgT1IPUKsdRHsdQuaKhTUEuMuglqiVE3Qe2COgW1xKhT\njCKoU1BPxahTjNoE9VyMuhejTjFqxFKHGEUsdYhRYtQhRi1BfSaoXYw6xahvKUbdxFJfiFF3YtQz\n8Vx9EEs9FUu9Roy6F6N2MWoXSozaxFKHoB6kXiJGfRRL7WJTN0GNWOomqCVGnWLULqhTUCNG3cQo\ngjoF9UyMuolRm6CeilH3YtRNjBox6hSjiFGnGBVLbWKpTVCfCWoTo25i1HcUS72JUV+IUXdi1DPx\nXH0Uo56KpV4ilroTSx1i1BKKWIo41C5GEfUm9RIx6qMYdYhN3QQ1YtRNjBox6iZG7YI6BTVi1E2M\nIqhDjHomRt3EqCVGPRWj7sWomxg1YtQpRhGjTjEqRhG7OgT1maA2MeomRn1DMepejPpCjLoTo56J\n5+qjGPVUjHqBeFO7uKlNvKklbip2NeJUd1IvEaM+iKUOsdSboEaMuolRI0bdxKhNjDoFNWLUTYwS\now4x6pkYdROjlhj1VIy6F6NuYtQI6iZGEdRNjIp36hSjPhGjNjHqJkZ9PzHqnVjqczHqTox6Jp6r\nj2KpJ2KpF4g3tYk3dYhdnWJTS4zaxabupV4iRn0QSx1iqZsYNWLUTYwaMeomqF2MOsQoYtSbGCVG\nHYJ6Jka9iVFLUM8FdS9GvYlRxKhTLCVGnWKpONU7QX0mRi0x6k2M+nZi1Hux1Odi1J0Y9blQn4il\nnoilfrLUS8SoD2LUITZ1E9QS1E2MWmLUKUbtgjoFtQR1E6MI6hTUU0HdxKhNUM8F9U5QNzFqxKhT\njCJGnWJUjHoiqM8EtQvqJkZ9N7HUKWqJUZ+LUXdi1OdCfSZGPRGjfrTUS8So92KpQzRGnYJagrqJ\nUUtQNzFqF9QpqBGjbmIUQZ2CeiZG3cSoTVDPBXUvRt3EqBGjTjGKGHWKUYJ6IqjPBLWJUTcx6puJ\nUTehlljqiahdjLoToz4X6jOx1INY6kdLvUQsdS+WOoTGqFNQS1CnWGoJ6hRL7YI6BbUEdROjCOoU\n1FNB3cSoTVDPBfVOUDcxagR1ilEjqFOMIqgngvpMULugbmLU9xKj3kRtYqknQm1i1J0Y9blQn4pR\nD2LUz5Z6jRh1J5Y6hBKjDkEtQR1iU0tQh9jULqhTUEtQpxg1gjrEqKeCOsWoTYx6LkbdC+oUo5ag\nTjFqBHWKUcSoBzHqM0HtgjrFqG8lRt0JtYulHoTaxag7MepzoT4VS30QS/1sqdeIpW5iqV1QxFKb\nGLXEqF1saolRu9jULqhDjFpi1C5GjRh1iFFPxahdjNrFqOdi1Ck0Ru1i1CaoQ4xagjrEqBGjbkKN\nGPWZoHYxahejvpUYdSeoQyz1QahTUG9iqc+F+lws9U4s9cOlXiSWOsRSI3Y1YhQpQZHGqE1oUESD\nWuJQpGLUiBIUqaA2sdQI6hSjngtqE0vtgvqVGLULJahNLLXEUpsYtcRSmxi1iVGHoEZQn4lRIyqo\nTSz1jcRSb2KpUyz1TlCnoG5iU58L9YVY6k4s9dOlXiWWWmJTI3a1xKnEqTGKoGI0aCwlaJwqlhJK\nnBpLEaM2QZ1iaagHsRQx6hTUr8SmxChiKWLULjZFLLWJTRFL7WJTxKhNUJ+JpYSKpYhR30k8V29i\nqTcx6iZG7eJQnwv1lVjqJpb68VIvE+/VJja1i10RhxI3JQ4lbkrsijgVcShxp3ZB3cSunog7dRPU\nL8WdWuJOHeK92sV7dRN3ahfUp+JUxJ36VuK5uhO72sRSb2JTYlQs9alQX4pNbWJT78RSP0rqheJN\nnYK6iaWWWGqJXS2x1BK7WmKpJTa1iaU2cahTUG9iqefiUHeC+kTs6iYOdROU2NQpKLGpe3Gom6A+\nF5vaxaG+mXiu7sVH9U68KWJXnwj1F8QH9U6c6i+J7yD1YkH9VDHqnwvqUVCXp+K5+iDu1IPY1RKH\n+h3iTr0XagT1V8R3kLr8i4L6DYJ6FNTlNwj1KkE9CLUJ9VfEd5C6/IuC+udi1IMYdfmhQm2C+jFS\nl39RUP9cjHoQoy4/VKhNUD9G6vKbBbUJ6jcI6lFQl58qqCWoHyN1+c1i1BLUPxejHsSoy08VahPU\nj5G6/GaxlBj1z8WmPohNXX66oH6O1OV3i5v65+Km7sRNXX62oH6O1OX3i039DnFTd+KmLj9aUD9I\n6nK5/NmC+klSl8vljxbUj5K6XC5/sqB+ltTlcvmDBTWiforU5XL5c4XaRP0Uqcvl8qcKahP1Y6Qu\nl8sfKu7Vj5G6XC5/qLhXP0bqcrn8oeJe/Ripy+Vy+W+lLpfL5b+VuvwmQV0uly+lLr9B7OpyuXwp\ndfl7Qn0Uu7pcLl9KXf6OGPUolrpcLl9KXf6OGPVEUJfL5Wupy98Ro54I6nK5fC11+Tti1BNBXS6X\nr6Uuf0/qqaAul8vXUpffIkZdLpevpV4qlnoTm7qXGrHUndSIpd6JTb1JEdRHsal7qVNQS+pNbEqM\nuhObulwu76VeJ25qF29qxK7iUEvsKg71Jm6K2FRs6p14U0ssdYg3dYqbBvUmbupyudxLvUwsjaWW\nWCqWIjYVNzViU3FThxhFjIoP6l4sFUsRu1riXh1iU7GrU4wiRl0ulzupV4lRI0aJpZaglhgNNWLU\nEqOhRoxaYtQmRoldY6k3sdQS1IhNjdg1ltrEUptYahejNjHqcrm8Sb1IjNoEFaN2MWqJTW2C2sSm\nNkGNGHUIiliKqDsxahejlhg1Yili1BJLHWLUJkYdgrpcLm9SrxGjdkHFqENQSyy1i1FLLLWLUWLU\nIUYRox7FqENQmxgl1C5GLTHqFKOWGHWIUZfL5U3qJWLUIVSMOsUoYqlDjBqx1CFGiVGHGEWMehCj\nTjFqiVGhDjFqxFKnoDYx6hCjLpfLm9RLxKh7MeoUo4ilDjFqxFKHGBWjDjFqBPUoRp1i1CZoqFNQ\nS4y6CWqJUYcYdblc7qReIUbdi1E3MYoYdYpRI0adYjSW2sRSS1APYtRNjNrEpm6CGrHUTVAjltrE\nUpfL5V7qFWLUvRh1E6OIUacYNWLUKUZjFLGrXVAPYtRNjNrEpm6CGjHqJkaNGEXs6nK5vJd6hRh1\nL0bdxCiCuolRI6ibGI136hCjHsSomxi1iaXeBDVi1E2MGvFOXS6Xj1KvENS9GPUmRolRp1iKGHWK\npXGqe0E9iFFvYtQmlrqJUSNG3cSoEae6XC5PpV4hqHeCuolRxKhTjBox6hSjMepRUI+CuolRm9jU\nTVBLUDcxasSoy+XyidQrBHUvRt3EKGLUKUaNGHWKUUE9CupBjLqJUZtojDoFtQR1E6OWoC6XyydS\nrxDUO0HdxCiCOsWoJahTjBLUo6AeBXUTo5bQGHUKagnqFEstQV0ul0+kXiFG3QvqFKNGUKcYtQR1\nilFi1Ecx6lFQpxi1hBKjDkEtQR1iU0uMulwuv5Z6hRh1Co1Ruxi1BHWIUZugDjGKGHUTihj1KEbt\nYtQIilhqE6OWGLWLTS0x6ibU5XK5l3qJGLULJahNLDViqU2M2sRSmxi1xKhDUAT1TFCbWBq7GjGK\nlKBIY9QmNCiiMeoQ1OVyuZd6idiUGEUsRYzaxKaIpXaxKWKpTWyKGLUE9UwsRYyKXS1xKnFqjCKo\nGA0amyJGXS6X91KvEXdqiTu1i/fqEO/VKe7UJqin4k6JTe1iV8ShxE2JQxF36nK5fJB6ldjVTRzq\nFJTY1E1QYlN34lCnoH4hDrUEdRNLLbHUErtaYqlNHOryR4qlLi+S+rMF9URQl8vfF6e6E9Q/F9Tl\nM6k/W1BPBHW5/F3xpnZxqH8mDnX5ROqPFqMexajL5ZfiXu2CIkbt4lD/SJzq8onUHy1GPYpRl8uv\nxZvaxagR1CF29Q/Frv6/CeovSv3RgnoiqMvlU7GrU1BPxFL/VGzq/5lY6q9J/cli1KMYdbl8LpY6\nxahnYtQ/Fkv9PxNL/TWpP1hs6qPY1OXyqVjqFKOeiVH/WCz1/0ws9dek/lhxU/fipi6Xz8SoU4x6\nJkb9czHqNwnq3xLU7xBL/TWpP1bc1L24qcvlMzHqFKOeiVH/XIz6PWKpf0cs9TsE9Rf9Hx/PqqjS\neYbuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(path) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}