tobacoo-industry/02_feature_design&training.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 特征设计与模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from utils import visualization_evaluation,visualization_y\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# some parameters\n",
    "tran_size = 20000\n",
    "\n",
    "blk_sz, sensitivity = 8, 32\n",
    "selected_bands = [127, 201, 202, 294]\n",
    "tree_num = 185\n",
    "pic_row, pic_col= 600, 1024\n",
    "\n",
    "dataset_file = f'./dataset/data_{blk_sz}x{blk_sz}_c{len(selected_bands)}_sen{sensitivity}_4.p'\n",
    "model_file = f'./models/rf_{blk_sz}x{blk_sz}_c{len(selected_bands)}_{tree_num}_sen{sensitivity}_4.model'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 数据集与样本平衡"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据量：  19564\n",
      "x train (13694, 8, 8, 4), y train (13694,)\n",
      "x test (5870, 8, 8, 4), y test (5870,)\n"
     ]
    }
   ],
   "source": [
    "# 读取数据\n",
    "with open(dataset_file, 'rb') as f:\n",
    "    x_list, y_list = pickle.load(f)\n",
    "# 确保数据当中x和y数量对得上\n",
    "assert len(x_list) == len(y_list)\n",
    "print(\"数据量： \", len(x_list))\n",
    "x, y = np.asarray(x_list), np.asarray(y_list, dtype=int)\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=5,\n",
    "                                                    shuffle=True, stratify=y)\n",
    "print(f\"x train {x_train.shape}, y train {y_train.shape}\\n\"\n",
    "      f\"x test {x_test.shape}, y test {y_test.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total (array([18474.,   762.,    75.,     0.,    62.,    91.,   100.]), array([0, 1, 2, 3, 4, 5, 6, 7]), <BarContainer object of 7 artists>) \n",
      "train (array([12931.,   533.,    53.,     0.,    43.,    64.,    70.]), array([0, 1, 2, 3, 4, 5, 6, 7]), <BarContainer object of 7 artists>) \n",
      "test (array([5543.,  229.,   22.,    0.,   19.,   27.,   30.]), array([0, 1, 2, 3, 4, 5, 6, 7]), <BarContainer object of 7 artists>)\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 864x432 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 3, figsize=(12, 6))\n",
    "hist_res_total = axs[0].hist(y,[0, 1, 2, 3, 4, 5, 6, 7], align='mid')\n",
    "hist_res_train = axs[1].hist(y_train,[0, 1, 2, 3, 4, 5, 6, 7], align='mid')\n",
    "hist_res_test = axs[2].hist(y_test,[0, 1, 2, 3, 4, 5, 6, 7], align='mid')\n",
    "print(f'total {hist_res_total} \\n'\n",
    "      f'train {hist_res_train} \\n'\n",
    "      f'test {hist_res_test}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train (array([12931., 12931., 12931.,     0., 12931., 12931., 12931.]), array([0, 1, 2, 3, 4, 5, 6, 7]), <BarContainer object of 7 artists>) \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 720x432 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train (array([3333., 3333., 3334.,    0., 3333., 3333., 3334.]), array([0, 1, 2, 3, 4, 5, 6, 7]), <BarContainer object of 7 artists>) \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 720x432 with 1 Axes>",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20000\n"
     ]
    }
   ],
   "source": [
    "# 发现样本实在是不平衡\n",
    "from imblearn.over_sampling import RandomOverSampler\n",
    "ros = RandomOverSampler(random_state=0)\n",
    "x_train_shape = x_train.shape\n",
    "x_train = x_train.reshape((x_train.shape[0], -1))\n",
    "x_resampled, y_resampled = ros.fit_resample(x_train, y_train)\n",
    "# 画图\n",
    "fig, axs = plt.subplots(figsize=(10, 6))\n",
    "hist_res_train = axs.hist(y_resampled, [0, 1, 2, 3, 4, 5, 6, 7], align='mid')\n",
    "print(f'train {hist_res_train} \\n')\n",
    "plt.show()\n",
    "# 抽样\n",
    "x_train, _, y_train, _ =  train_test_split(x_resampled, y_resampled, train_size=tran_size, random_state=0,\n",
    "                                           shuffle=True, stratify=y_resampled)\n",
    "# 画图\n",
    "fig, axs = plt.subplots(figsize=(10, 6))\n",
    "hist_res_train = axs.hist(y_train, [0, 1, 2, 3, 4, 5, 6, 7], align='mid')\n",
    "print(f'train {hist_res_train} \\n')\n",
    "plt.show()\n",
    "x_train = x_train.reshape(x_train.shape[0], x_train_shape[1], x_train_shape[2], x_train_shape[3])\n",
    "print(len(x_train))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 特征设计\n",
    "设计特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "from models import feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5870, 256)\n"
     ]
    }
   ],
   "source": [
    "features_train = feature(x_train)\n",
    "features_test = feature(x_test)\n",
    "print(features_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 进行训练，验证特征好坏"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "预测时间： 0.2433488368988037\n",
      "RFC训练模型评分：1.0\n",
      "RFC待测模型评分：0.977918626047843\n",
      "RFC预测结果：[0 0 0 ... 1 5 5]\n",
      "---------------------------------------------------------------------------------------------------\n",
      "RFC分类报告\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.98      0.99     18474\n",
      "           1       0.68      0.99      0.80       762\n",
      "           2       0.79      0.85      0.82        75\n",
      "           4       0.85      0.81      0.83        62\n",
      "           5       0.82      0.84      0.83        91\n",
      "           6       0.82      0.97      0.89       100\n",
      "\n",
      "    accuracy                           0.98     19564\n",
      "   macro avg       0.82      0.91      0.86     19564\n",
      "weighted avg       0.98      0.98      0.98     19564\n",
      "\n",
      "RFC混淆矩阵：\n",
      "[[18092   343     9     3    15    12]\n",
      " [    5   753     3     1     0     0]\n",
      " [    0     1    64     5     1     4]\n",
      " [    1     9     2    50     0     0]\n",
      " [    0     8     1     0    76     6]\n",
      " [    0     0     2     0     1    97]]\n",
      "rfc分类报告：\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00     19236\n",
      "           2       0.88      0.94      0.91       328\n",
      "\n",
      "    accuracy                           1.00     19564\n",
      "   macro avg       0.94      0.97      0.95     19564\n",
      "weighted avg       1.00      1.00      1.00     19564\n",
      "\n",
      "rfc混淆矩阵：\n",
      "[[19193    43]\n",
      " [   19   309]]\n"
     ]
    }
   ],
   "source": [
    "from models import train_rf_and_report, SpecDetector\n",
    "feature_x = feature(x)\n",
    "clf = train_rf_and_report(features_train, y_train, feature_x, y, tree_num, save_path=model_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 3 Axes>",
      "image/png": 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caZ0E3q7LQ5MXVPXvgHFWDzd+seh8lzdgfndute9yuz0e5afTCNyFMwKbxpeBG8WE7X058AuY1kP1HPcl+TBml6oXWY/3DZjumC/b898CfsR67y/DVFzEe4GfsPd6IrJHlm+GshYlm8Y05gcsjhapZieoDwNvF5GSmEHQ/87yWTj/Qtv4/QPmB+cOm8dXYzzAL0Hc6shh+iM9MaGN0yzntcCXVXU1LzOZ1pqhk21aKZuWD/g2rc4fmzuA/2sNzEZ5hZjB0gwmmubXVPWkqk5ifuh+zL7nT7KOUbYe8p8DfyAiozbPe0TkpedIfwLYJiIDiWN/h4m4ul3MgP9vsHKT+f8pZnri8zAzr/7eHi8BM6paE5FnYZyCiL8BXixmam9KzB7Ot9i8vw/4fTED076I3CZmMHpdGVbVk8CCiDwJ+DrmR/MdIlK0dfScRL7KwJyI7OH8Z8u82XrFNwE/gdnRbC1KmLDVZasznftMdIb5/nPgZ20rSmzev1dESpgtTluYcOMpEfl+zHhdjJiB/GiwOGPfW+w5z55Lm6+Sk/bucBuhhHEu5sRse/o/Os5/GWMkngV8Xc2uefsx4xufpxvY6v6oNfrVjrFyYPiTwJs6jn0IsyvV+zEedDnx96f2mjux/cT2++uwg4v2+3/ChCKex1jmmxLnngE8iBms+2uM8r+t49777fnHgZeeK01Mt9A/2XuOY7pH4j5QYAjzgzKJ8YB+A/ASz+rH/Pim7ffnAd+273w38LyOdLXj7/0dZfgIiQHgjnM3Ag8nvn+/fc8F+47JsnrLKmm9JXE+hxmveNF5yMH7MZ7yZ+37fZ7EgDLGwz1qn/t7tv6SYwJf7HheDmN0j9h3eBj4hQ3k430Yoz2HacnkMNtKjtu/d2P7ibFjCMCv2Xo6Abw28axX23pfxEx2+GNs/3qiPr9m83cSuMMejwa2T2Nk9fNA/lwybM//DnacDOMl/6N9nyng3fb4TZjxtDLG+XkDibEQzj0m8HraYcN/uUMuPtCRn9sxclfG9Jm/leU6+bO2XOeAH7THXoaZ+DBnz/09UEro6b22TD9k/97WkfdO2TyQqK/Oc3cm7n0Q+NFk3Xa8y26MLpQxkzh+hpVjVV8BPpf4/hESerXVf5d17CARuQP4blW9Y6vzcikRkc9h9oz93CVI6wjmh/voxU5rlbTfj1G69fbTdZwDMRvtvFVVn3/Oix09x+W+2OHjmOZYr/E2TMvnUvBLmKl/jsuXL7HGrmYOx2XdEnBc/ohI1Efayc9g5q1f9JaAiLwJMzjZyRdU9eWrHHc4rhicEXA4HI4e5nKeHeRwOByOC8QZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhnBFwOByOHsYZAYfD4ehhLpoREJGXicghEXlcRN54sdJxXFpcvV6ZuHrtXURVN/+hIj7wKPAS4BTwDeCHVfWhTU/Mcclw9Xpl4uq1t7lYLYFnAY+r6hFVbQAfBF55kdJyXDpcvV6ZuHrtYVIX6bl7gJOJ76eAW5MXiMjrgdcD+PD0bQiCUgEC+5cCFGgCoT0GApJ4zhoZSLZvsimflO/RCkLqrQAPSPtCPVCIWkKy/Glp3yPte+QzKRaqDZpBuO4LZ1M+rTAkCFdvWYnNk+8JYaioPZb2hZTnkfE9Wqq0gpBaK1z13tXwBNZIElTxMJY+eqIAaaBlP+fs5yCTpW/bdmbGT02p6vY1nnie9eo/vUD/Go9yXEoWmb2gegWns92os+L71CpLaxXphrhYRmC1TC17bVV9D/AegF1eWn+VEtNUeFAanACuBqaAWYRFYE6EOlAXIRAPT4RQBBFBUcQmKWJkRDWM0rEVZSrR8312lLIs1gOajdaKXEfPUaCukFIhl8sQ1JqArRyRxEuaf0ulHBnf48xs2WQieqQInueZfIYht16/kyAI+MbjZ1FVAmB/f5ZnXjPKXLXBvafmOLtQNwInkEl5KEIrVKKuO7HP11BBICWyvMhVCTXEUyWnygCwAGSAflVyEP89TZUZEb5+1T6e/WP/hb95638/vln12i/Dequ8aJ3HOS4V/6ofuaB6Baez3aizs9XqmpW6US5Wd9ApYG/i+1XA2FoXBygLLCKEzAOjChmFvD1fwljCDJGFVethAKoJEdBYmNR8iItZbKELUGsGVJsBiPkukRgpSORlmMdRrTep1FtIJLz2//afyVS52mSp1ozT8LDnE89Kp3wGcmn+481Xcf2ugThvxxcbHJqukE6nWKgHeF77+Xv7sxTSvsmnCJ54sSCLJ3gr8iMggmffrCrCWSuAPsaDaAAFlCEV+iTpcZxzfOi86tVx2XDe9ep0tjt0djO4WC2BbwDXichB4DTwGuBH1rq4hXJK0qS1xS4VTgChKBlgDlgQUzAB0BLPNpeUVvyblWx8aSxMCsY0iyCehxeGiCoLtVZ8tfFKQKwZ9z0hUCO0sLKwI8GMHo0I+UyKWr3JUj1EvFg8EZS+fIbR/jwnpss0WyF3PTJOtd7kxp0DLNWanJ5ZIgiVB07PoTLM7pF+Tp6dJ7TNy4V6QKUZRK+GSluBonQSLxALcSiC2mIJVKmJIKqEwDY8ygRkCJkC6qr4cTmuy3nVq+Oy4bzr1elst+jshXNRjICqtkTk54FPY4zZ+1T1wbWu9xAGUEJS3C91zgJ5hBLgixA1AI3FtF2CaoQKQONjbU9WbQeeqIIIqorn+8bAJ7yN0GYwtM/uy6bwRZittVBV+0iN+x9V1bYcjSB6Ily3o59jU2UWKw1byVYcVdg9kGd7KcfJ6SVAqTcCvnBogkzKI5uywizCjqE+GqFyemqBZssIkCJMVZqI57Xz0fFDHfdUatSsjvpLZZmahbYZ2w8EhBQxXluggopHX6SAm1ivjsuD76Renc52h85OrVuzG+NitQRQ1U8An9jItR7CQa+PxWCRAwo7gXGBGoqvUBJhFoy1t8KQFtNMMsImeHbwBusRpFCCqJPO5Mf8xc0921eH9Rzs8flai8F8mtFSlonFOoN5n5QnLDVCqsv6I21aYcjxqTLX7ejnWyemTR4wFlwFHptY4LGJReLEbLr1Zot6wx4WYXqhwvhMgIZqPB01z8cz/ZOBBok+VIklJRYviZ5lvwigghASWq+hCpRF8BN9jiDUCI3Xce6WwHnVq+Py4Xzr1elsd+jsZtAVK4ZVQhpBk7qmaSFMAHlVlhCamILwMV5E2nbW1TD9ZCGYZqTappYty5aYvjfEWH7f8+ImZ9L7sN1wccUosNQKuWHvdkb6c+ztz/GcvQM8cXsxHjtKeswKLFTqlOtNRvtz9mBbWE1zL2rhSjxAFF3g+x6DhTStIETwYgWI+y4VwiBY4+c5mZOor9HD8zzTD2mbzYgQ2LQXgHkRhhT6gD2ElFACiZN2OM6J09nu0NnNoDuMADAriuBzENgFDAGjwDYgi/EeCvH0qWhwyBCqEoZhPLgUNcDCxPnk2NGKxK23Ep1rNgN8gWdft4dDMzU+9sgk944ttJttHU9R4PhUmV39Oes4aPwXNzOtp60dd+czKb7vafsoFdrCeK71e4mn2mfbZiXEHkmoifJQJWX/0vaeeStsOTscVQhDwnAzh5scVzJOZ7tDZzeDrjACLeARYNALmEGo4nFWYB4wvXKQU6jbawNvFRMYOQtRk0zV9C1aYQk16Jh9sLzWrAMSC+n0QoUjZ+fZOVwi6ksUiax+0vKbv0Yz5IHT8+2BreT/yXTadwNQrbd48MQMYRgQhkF8myZuiAazkl5JPKNATBWqnY4WhiEahisEM+pH3WU/P47woAhjhBwWoUyHx+NwrIPT2e7Q2c3goo0JnA++CntRjlNnkpCjAsMAKFmEPGY2QgNiqx1NNxOMJQsSz4umOiYXW8TD7rRlrrNJGV2rwLdPToMIu4f7EZHlXrK0RdIIiHlQMwjj8ajEPIBlgtrG+AZBqNx7YoZWGD3NNkulLXbRAFPUYFVVm3cz33pZ3iNPJuFGReUjAkGoDAEVzBS+HHCTwrEV+XM41sbpbHfo7PSKPJ4/XWEEBNOHOEtIGtiOKYARYBYYwHgUGYyQhLSbjp3C1H6i6Y8M4++JYhdFIufDDhaJPR4JQqhAGHJ6an7FzARRRTyPAyNFsimfIAghVBbqTeaqLRpB9OTlYjRcTFNvhdRbIUEQ0mqZQatWEBJ3JnawPLaTyWPirDmaHHQS8+ZoaJXGeBcpjADNiDCoynZgUJUCHouYVZ8Ox0ZxOnvl6GxXGIEayhGpUlS1S6I9FlCawLSYaWeKyWwNY2WjpmByeXWyOQbtsaS4ahN1ptEFy+pcln9KNOOi65OXz5QbeJ5Qb4WkPGEw4zOcTzGx1FyWH1+EG3YN8ISRIoV8htLIIF944DTfPjpuFSJyb9qeSORjRDMglpFoeipJGVNQMzilZu7ZMlXqV6N8HtBEKQuUNaSM4LuuIMd54HT2ytHZrjACgcAONSsPpzHexQxmoUkF0y9WwcyRjZpEgulrDAFfIUxY8biRlmiemf9NxSWm5bKsfZloEMbLvFcdWDLNu/lqM27iiUC53uq4x5DL+PRlPD53eJrbrtvBgw+f5tHT04BQyvgUi1lGSzlaQcDhySVqzWCZYGmUn0iTaAtRpwBqR16jMjHTzZScGi/tDGZGx6JAEY8KncrlcKyN09ku0dlNoCuMQFohRYYcIT4tPIURUeYQKkAZUyDzmAyHmOZSSGdjLHIZ2gW/GmsPgK4lTGbK2rZCiqmKERrP8+KkTAfiClcmltVKPeDu47MAfOq+E/FzRYTBYobhYobxhRqjxTSDhTTj822BKubSBEFIvZno37SzIrxl/ZyJd7L9kZHnpUTzs4UQpaYmwJcAC3jkUDwEb3NkytEDOJ3tDp3dDL+tK4yAeZk817LIJEaAJvHYg1lAMoaQw2ZWzcKMJRHSapqfcZ0SWeHl3oRdlndedjMpTGqlpphJgQhTS02u2zXA2GyFsg1SFVWiRil39AOqRpUfXwHAybka80sNFlohZ+aq8dxkT2D3UIFbdg/w5aPT1Jt1rP8CAqV8huFChlq9xUS51n5m9E/Hy4aoifAoMIaQQUkp7AZmxQzinV8JOXoZp7PdorMXTldMEfUFCoTMIzTxCYAFlEWgodhgxDYOCdGouQkMlUHA9v91ehntbrfE0c6FJwligVTF94TrhrIMZn17m3J6oc6OvgwDxSz5tG+CTyX79lZ9qJDNpOIE8pmUScf2/fm+WRTSn/bjpm4pl+ZlT9zJcw9u4+6Tc8wuNaJHgYCf8nnpk3Zz47YCS41W3LQ109E8PE8SAa2IzwVWERcE5hEqAmMSshQ1qd24gGODOJ3tEp3dBLrCCLRUqVDnKCEPoDZynnKGKHoe5NE4PnkT8FUJVWmhKwZ/IJpv3GEpV4zatyP4JUl5wlOGc/SnPMotNQGmbJCq0wt19gzmOTmzZJebRwNYQhQxMJvxiYJClQpZXv7U/fi+SeOq4QJX7+gn5Xvs7M/yvP1D7CzlqETxyAVyKY9d27cxsVBHbUz0ZERFX4Sz8zXuOjZDpRnayIReew40SWGS+F6VKDSE0BKoIlTstb6NbuhwbASns92hs1dMdxAIZXw8AkYl5DRmLqxHNA/WLEdPAxWReOMKtddEBeHT9izavXGauCJKTogmHqv9npzju7cvQyNUFsXjSVcN0lfIkkmnqDYCvv7YGR4/u2imiNH2JQTwPOG60RI5X7jv9DwAB3YMUchk4kkNZxdq/Kdb9lGrB5yZX2Ky3CBQGChm2T1Y5MjZBWYqTR6dbzFZh0ojIOV7doWleZcgCLn7+AzNQPF9v90Mlui/TvUC8Wi/L+b1AzGxWupAepO8Ckev4HT2StHZrjACPoqPkMesmmsCNRGyCH12BkEWMy9ZMELUwtjzAF0mMlHzMEaJQ7lGPXvS2bS03kckVHsKaQ4tNugrpFiqB0wvLVJtmHjmYWgWi4gIkmhHeSI8a/8w2/MpHhw385RzuQz5TIovPDyG7wk7h/tZrNR48MwC4gmhml2LDgwXuH7HAPsHC8wu1ag2WkxMz/HMg6MElSX682kOT1dZqDbiqW/1ZtAeLLNN0rgMRKLpCSihOW7fOVlWivHaqgh5WSmIDsdaOJ3tDp1dYSy/A7rCCDSBMerk8WkR4IlSVCUjZmpZWZW6CDmkHVuEyDkQfDELRQLbzLMGFCEKVmUHfexAUNSU7MtnqbcCmq1We0xI4Ew9YDjr89j0Etv6ssxXGmYxiUaj95EHYpqcAHuG8jxhMMMjk0ucnK+jqngiVFsBp2cWuX7XELuLabzhPOl0CtGQbMbnxFSZUiHD6fkKZ8tVnr63n2q9RZOQgXyKW6/eRrVS5+hMNZ7dQCQwFi8h2ZFiKLp8nEuiGOxGeXzMXGdfTOREj+UK4nCsh9PZ7tDZzfDbusIIKHAtHlVa9KGEClWBOZQcwpKYPsYJ1BSCfXMTUzw5uCTxeLlpMi6ztdblUNIpj2YroJTPILUmrWarbW0VFgLlufsHKSNU6y0aQYgg+L5HqO1ZCJFRz6V9dpRyfOXUAo9PVeK9TeuNJuVKHYAzCzUen5iPrfvebQVefMMIX/KEnf05wlAZW6wzU1MeP1shCAIWm8oTd/Tx70fnWKobLyJeCSnGT4r6EKMFKmG8PN2uvdSkD7GShu1vFKtzDsdGcDrbHTq7GXSF72cEJMUEcFJgTkzTcV6EYyJURKjbQlOEUNpLz9vCpHho7FGYIxLPHIgCUQ0Ustx+7XYTphZI+WIqgbagHBjKs28oz0y5wcxSAxQKaY9bdhTIesTPMlEQlZGhEkG2wHgloBW2PY8gCDl+ZtYsUilXCMOQbX1ZnnVgiAPDBWrNgOceGGSmHjJTC9iRT1MQpVxrMldtslBtcmxqiXK9xZ7BHLsGcvHep9GsgmXb1HmC7/v4no/v+2bgyQ6QmQGw9rWBmF2MzPiTgOchXleIg+MywOlsl+jsJtRl12j9NtIUSVNTjxpQQ+hXGFazJd0c7eZkkpSRGPMZYuEAMxshakpFbO/LcOhsmVYQUq03SaeMCEZCF2rI8bkanp+mlPHI+saSVxoB94yXqTRb8bVq065Vajx09Azz5RqxOK8Y1xJKfQUO7hvlmdfvYqSUp9qCEwsNXnvbDYwOl6iEHteNDrCjP89gMcv+oQIPnSkjIjRCuGGk0J5GZqeUeZ6dXiaC5/n4nofn++ZYJFRW+JC2cEUzEjSakZDwyBybgOdz5he/C7+/f9Oe121TeHtXZ1u89rYfZHR4eJN0NnUBOnvhdEV3ECg+TXyaTNg+wtMCJTWDIFE1RTE0WrStV5gohga0W5C0g1SJTQOEo5Nl44moUqk38LwM7dpXUGGuUufU7BIjhTTleouMnSrWCDTRZwliAz3NlKv0Z3zqNrVI6OMJALYCB4tZriqmODVV5q5HJ9nRl2agv8gjE7MMZYS6F/L1k9M8bVeRclP55tg8S3bD7Eoz4KZd/dwzvkSlYUqgPZ3Mi2dLRD2fCpglwIqEQkgAoaB4hNKe2oba5rd03W/M5Y2G7PriAmG1timPm33ts+gbb5L+zN2b8rwLp9d19gGGMuEm6ewTgDLKyfPX2QuvyO4wAlmEEin6SOHZzZQHMD9KU5iVh5FwtGgLjGD2GTX9gol+xQRRsCq1Y0vt/jczWt9oVhNPM0+u1gO+cHiKVmiiB27LmTnEZ5aatJdoaNy0U4S9fWnqofE+lk9ksFcrjE8t8Km5MvtGS8xX6swsVinN1Xjg5AxBEHJgIMv+/gzHZ2s8PFlhsJSnhFCuNghCmCq34p2IknOJIy9jhUgs+4EX090ThtHonPUqTMF4ImxO49IBmNkrdz9wwY/xcjkqL74Zr6XUB3yyxSLh0tImZPDCcDr71U3Q2RRwlX2XLJAGbZyXzm4GXWEEWgJnFIoE7MLjAUJSwCBmt6ImEFiJaEHssiaXiYsdVol29Wz3Mdrz0T3RP7HXbO5m2WdlbKEaP6cV+nhiLHR0LyKogu9BzhcmawEHS2kemjH7g3bO6xJRWoHZvWuomCGd8ghaAeVqw1SoJxyerTFeaTFSSLN/tMR1Owf4ymMTCEKjFfKxh8/SCsNl+Y26B2PBssISqu3giQtDYqUTSEQsbPdVOroPb+cov/nu93BrtsnxVoP/9uhPw30Pb3W2nM5uis4WEPkhRIqgdUL9U4SpS66z3aH5Cj4Bg8BeWhxQoajKokKD9mYUcfjZqGDUTEfzSTYll/cnnqvPLLmlXHS153lctXMYz/cRhPlmyHQ9ESAqn7bW3QjqQNZsbD2U8blhKEdf2ot9FBT68mnSKd/UqcBipUnG9+0MAUj7ws5Shj0DWW4/OMTOnMeTd/dTrdVp2rnFgolhHv/QJ3TAyPjyQSQRM9AbX5tsKES3x03TWEcc3YTn89CbR3lKpkpW0uxPZTj6aykkm93qnDmdvWCd9RB5Lp4UbCshi8jtiJc+L53dDLrCCCjQokSLAn1ADqUIlFAyagSlnnhjL7pJjMdhPI1IJJYPliyLPigrXzgq0KjERcwS72c/YQ/7dw4hnnDtSB9XDRbA9uM9ac8gg0WjiK1AGV9qcnKhwX3TNVIo1ZYJkjtcyHDz7n5e/oRR9gzkSHvCzmKasF6nmDE/0KVcmmfvHeDZe/rZ1Zfhqv4886FH2vcZn12i3gqTrgO2gydu4LaFoi0V8SBUYjBJWO5FRcejJwripoh2Gf51B3ndM77MgJcHICtp3nTzJ5Ebr9ninDmdvXCd7UfkIEjKvoOPeAfwZPC8dHYz6AojEKKkvTIVQiYQipgesrx9yRLQBxSJMmz7zJDYCwYjCPFgS9JURj+O0J6CS1LYJPGf0AoCPvm1R9ndn6Mvn+GxqTK5lHDNSBERYWKhxkh/btmtCCw2ApZaIX2ZFPlsmmor5OxSg5PzNQRhV5+x8kdma2wrpClmU9w0kufR6Sr3nSnz0GSVI7M1lgKYWKhSrgWECn3FHIP9eXLZFIVMilDtRt3JGQ8JoYiaz8n/oxihnb/zisbPctvMX1r8668hfO4ta56feP52Xlh6KP5eDmv8yZEXMPbCwYufuXPgdPZcOjvKYP+BdXT2KqCU6H0KQM+g7Dsvnd0MumZMYDL0qFCj5SmHQ7Marg8jSAuYWBlNlu9Bqtg5xrYwoi0/l20QEfUjiiw/njgf9bt5aoRbgHqlzreOnqWQTbEYBDw2WWbfQA5fYGy2wt5tfXbuMeAZ4Uz7HlnPI5sWnjTax+HpCsP5FPeemiMMIUjseTq+UKMv47NQbTK11GDCLmv/6vFpWiH059PM11uUChluuXonjUaTiel5lmotFqvtAFWB2LjiEtg+Q1sGYWhjl5hNrKN50vF8aVXQ0Ly6Z7673qBLzDna9CN//lX+W/rn+O6f/CpfmriaibFBbvyVIwTTj1/CTK6O09mN6GyaienJNXT224j4qNwKugCygIb/Tqi189LZzaArjICncJoy+/EYD80+pYsoE5gNKrKYqIXxIBPE5lESHqwRruXPVntf3Hpctnn18ouTW94FQLnaMINA5mJOz1ZN+qFyZGKhPY5kkmBvIcVYpcF8PWSyXEcEdpcG2D5QoFxtMr9Ut3lQZpea7B3MIWIWvqQ8Yd9AjtFSloZCLTCVffVIgcMnJzg1vWRlP9GkVLtptRWUOKCWyDIjEIZBLFhhaPwLDcPIJ7PHQwLXFLikBIcexzu0zgWq7HjP3Tx01/VsK1cYXjpOMD1zyfK3Hk5nz6Wzj21AZ+9H5DjQNE5cWDlvnd0MusIIhECOPFWEg1QY84RWGLIkygDCvCqaFCY09npNT4jxDDThIUAkP+2eM1G74o7oemLBTO57GuUpCvxkZEBpRU1WiKevRQ8fyvjUgpD5enu6WagwXWny9Ku387lHzprrChkUZbZcJ5MywpTzhVor5MRcleNzVZ65d4Az80ssLNW452idbNqPVzqaQST7mjYdVUUTExAEEs3O0AqVEajYswCyqtQxcdg1CDfNs3BsHtpsoA880nVddU5nN0NnGyCT8Xt/Jzq7GRrbFUZAgD5qpPBYQiiHMI2JQjiDCTbVROIZB+1OvUhgJNHPZ6TETD8zAaqSv47JxnfyvsRVUbvVDkolvOuExy124CcS14VmwEzd3CQS/Q+n5mqER6ZYrDYApdoM2FbMMCd1+nNpFhsht+zOcrYe8tj4HKHCPafnyXieFSKh1J8n47eYW6qjGhL1+sQSoBAmRnXjvIZh2+sIQ0QVT5WcmpjufcCwQk2xU8+cEXBsDKez3aGzm0FXDAyDWTnoEVJDCQkZwDQZ85h4IWFUiEiHULSJ45Rre9ei9UbQVZNDL4kCTVRUPpOimPHbqSX6cI1MGelr2qagqUDzP7Zpd3q2QhgYr6BSa3BiusxoX5az5Qb7h4u0REh7gu95oEojUBbqTTI22mF/LsVSrWkFrO0lYIUlDEPCIIiPh0FAEAQE9jNBgIRmOX5g+/4HFXaosgcYUiVH0HXepqO7cTq79Tq7GXRFSwCBhvocJqAiZsWhDyyJEbJIJjyMYEUGNBKDyINNBqZC283KRAtyRbrxcFXSrYj6LgWuGSlweq5Kud6yt6wmoLa5Gbd12+mbplz7SiPE0AxCbt5ZYnqxypN29vHoTI2b9w6xWG3wnKtH+OTDE+zNwv1TVRaXarSCqMlq2rSjAwX2jPRRqTZ55PRM3G8Zl4vtR0SVlM1DDvN5EDNgNwikVfBRZkOzMNHh2BBOZ7tCZzej8d4VLQFfhT12k+p9+PSjbEe5XpVBVdKqFKw1TCU71hJERyT+N6rM9l90XXJpSqIeELVb3NEO95rxPRZqiZ5Nbd8d9d+t6bjE6Wq7iWcTm1ys86VjM5yYWeL0QpNtOZ9HxufYlfd59Mw804tVys2A4WIG7KYYseCrsn2gwO5tJQbzmSgpI8Ta9mpU23O2BSWNmbmRAXajZNRjB8I2IKPq2gKODeN0tjt0Vlcp1/OlK1oCaZRh0ng0qeNzUAOamCiEJTGrCxewTUU1Gz+0VO0PV9ubSDoGKzapwBS2JK5FlwvXsj5GIJXyzB6pYUdBW6GKBqGIzne4MEkhj5qhIpjRflUarYAbRvJ848Q0KRFazZAHJ8rmXDNgvhEy2pfl22cWE56JEZjFRotiJsO/HJ5ov5dE76hx4iGKr0aIQkxgrxFbPouE7AXq6hNo4j0cjnPgdLZLdHYT6IqWQA3hjIRUgHkNaJKiiFIW5Swwi9AU6Vhqbv7PYCyZR3spOiT2Le2w+MtWI3Zi+zCjQhnMZ/BFKGRS7aXc7QfFQrnes9vyJQz3ZTkw0hdfW8ikyPo++4YLtIBcxieV8rh2pMiO/hy+71HyhZS3vHGsqkxML3L3o2N22liy39MEx4ry2rJlECBUMQJVASbxmBM4CfQhbFunH9bh6MTp7JWjs13REhCUgCYzpJmkiaJMidlBJ1ps0g5DK7HHkMUUTjSqHyQ68jwkvq9zIlU0Er88D+0mJp6H7wmD+RQzlSZP2lVisd7i0ETZbIcnwu6hArNLDaqNlu3yM9Loe0Ixm6ZSb5H1PZYarbgb0/c9BotZdvU3SHtCpaXMVpsstUKu3V40S+99qIRw044iD08s8eB0Bc/6PinPI5P2qdabVGtNHh+fte+z7C2SEyVQjFBlaSvfMFBR5SA+JTy202JMw03pX3T0Bk5nu0RnN4GuMAIecJYmaTx24uPRYhKJY5EPYqxhGZZZ9mrUm5g0urZiQ8zKxDBZssBoX8bsEzpdWfGbF1X8cF+O264fpSCKBiG5tI94Hkdna9TqTZN2I+Da7UUeGl8ksNO6AHYNl7j16mHuemCcpg0ehQiFtMe+UpprBzP4tTTHFhoM9uUgDFiqtzgyWSanIa0QmiKMFDOEqszXArNJNpBN+zxt3zD3nZo1G1jDsiZnXBbYgTh7LovaPkZz6ASQF1jUgCJCBs8oqWsMODaI09nu0NnNoCuMQAhkNE0JCGlxHGUh0RRaBOrYWNqYTLfALiJJDhy1ZxaEJBaSJLr/pipNnlzKUh/IMbFQiyvE9BeazzPlKnc9PM7BkRIahowU0ijCVQNZTs2G1Fohc0t1FqqNFTNqfE8YzKXpz/kcm22Y5yqkPWG60kBF+ObEEruG+rhmRz9jE3PM11sM59OE4lEopmkEii9Qa4WkPGiFxmupNFp89chkLGDRsJlp4soy7yIaDEsDLTWK2YfZ9zXyKhrA9RSoeXVCcTuLOTaO09nu0NnNoCuMgIcwSj/XU2GeFvMoFSBjBaiG2dM0DdTVxC1JYwSmZb0GHzuinvAoVgwyiRkweniyws6+DJ54ttnZHpQxlQHlapNvn5qNnZiUb5qbYucBK2awKJ7bIKYfcGKuwoMn55goNxLjrMp8rUVTYfdQkWt3DLC9mOELh86goZLzPc6W66jCjaU8c5Uq9QbUWxrvjBS9TCu5SlBNfmOpxWuvjrQS18AE8crYyxu2nEaAfQh5DRDNkseP38XhOBdOZ7tFZy+crhgY9oGraFHVFHlgEGGPeuzGzI/1aXsJIibTZi1fu+8wipoQ2vZhNFgUYm6Kw7CK0AhCTszXCDUZ4TDyR0h22IFNp9kKaAYhT9lVIuUnik0gl0nxXVdv43nXjqCq3HN8miU7Rznte+wYyPGUPQPcdmCYq0f6yHrw9SOTLNWalDIpXnr1Nnb050CgmPaoNgMmy3XqrQA/3jFMY9dH4ny1/akkXvQuVvECjFJ6mBkbPkbI0qRYFBjVkJa2NmsBoqMHcDrbJTp7vhW3Cl1hBELrMZSlxnGURYQ6yiTCJEZ4otkExmtoD55EKw7Nn8YvpCJtYbLHRIR8ylwRLeJYbWglFqdofrEt6TBUaq2Q0VI2fl4u7TPal2H/cJ5WGJISoRmHRoTdAzl29+eYXmrwrdPzHJkq89D4PE0brS3lwVwz4DlXD+OJcHquSr1p5lJ4Ak/f3c9gIbVMdDzr2URvlkp5FPNZdgwWGLBxTsSWTWDLaQAzCDdk7zoOzNCkQZ2y10DQTj1yrIOkM3i53FZnY8u4snW2wO7+4uWhs+dXbavSFUaghXIfdaYJaOJRQ5kRpQ4siinYJhDYKV/RbANf1XgcmvAqEn2JqxXQUCba7JmE96DJ0Zpli0vi8/b4sdka+20kwcFClqftHeL0XI0P3zPGFx+fZqnRioVVBG44sIug2M/4Yp3pstnWOumVjC3W+fyxWQrZNP35NGNzlTh8bRAqJxdq3DzaZzwFhUzKZ9dgIb7f8zwOjg5wzY4BfBEq9aZZeWgXoHjWGVm071RFmcOUZwWYIsVc6FPFbSqzUSSbZfznn8Fjb7sFf3Bgq7OzJVy5Outzw4GXEhRfzviidr3ObgYbGhMQkWOYsZ4AaKnqM0RkGPgQcAA4Bvygqs7a638V+Cl7/S+o6qfXe34W5QmEnCQDNCkAY5g+sQGFlpg5x0G8pLwd6iwZBz/aqi5qWiY9CjACEYRq5UfbUmelcbVpaMll3YIyX2kwX83ge0Ih41NrBjbOt3lue/DHlp3n8bRr93B6bJqp+SVChP58mslGi0zKp5BLM1eu8dWjs6S9lZU6Nl9jaqlhFpQIZNI+0cZFiBCGyuHxWXRFytbDEuOJFYHdwBLKHoUhPD6hAUWqpBEq46d4hbnRF5HPsgn1eqXibx9h8ZYaqWyL8Jqr4JvzW52lZXxRP4FPCtOZ4nGrvAg2uV6vXJ3NIt5VPO3anZwe+wJT88e7SmebKMO0KJKm71IaAcsLVXUq8f2NwL+p6jtE5I32+6+IyBOB1wA32Xf4VxG5XlXXjHbkiRCQQbRi5vRi+sU8zBQzUSUD1G3lenbRR7TqTmjHEWkPwGhiyqMRweieyItI+T7DxQy1ZkC53rKDRjZPasPcQty8NPeHVFohOwppGo0mj5ypo2EkdIkKtcvNP333owiPxYJ6Zr7KSDHL5HyFQJXrdg3yyOlZjk6VaSUC+rdXFAr1VtjuU1S7O5FNg+jdzWvGBaCYaIy+KgXMlL0+lBKmmTlmPbPXeEWup4/P7C5FTtYu4EObUa9XKq1Tp7nujtPAchXuJp7O88nIsr2IN7Ver1ydLfPpu//QqFIX6uwB0qiXJq+FFYvqvlMupDvolcBf2s9/CbwqcfyDqlpX1aPA48Cz1ntQoFDXBtvwmRefowJLmKZPzvaHDaqyzUpN0xaab/sQrYjg2xfyrFCKRn+m0AXB89qeSSsImS7XCVXJ+O3NHiAZ2ApQxRMo5VLctLOfvdv6uW3/IDdvL1JtBvFgjyfC3oFcXPl7tpfYs61kvA578PhUmaNTi4AQBCHHzi6wb1uRq3f0x+VRyqXIpDyKuTS+tBVGFar1JovVRhwvJcqjAsWs2f4uIlqROYoyYt+5DAwB1xDiIewLszTVJ9PWvsHNqldHVzHIJtbrla2zfV2rs0MIB1bq7AWxUSOgwGdE5Jsi8np7bIeqjgPY/0ft8T2Ylc0Rp+yxZYjI60XkbhG5u0HIFBnOAscIqCI0RFjA9INts8VmZhyY+bhmqpmtSttfGE2piqxsPOAUv4WSst9DMfe2gpDFapNqI0heSOR5RLHIr93ex3Ou6mdbzufBsVkk5UPaj1unCmwbLHJwuICIsK0/x61Xj7BgdznaOZAnm/ZpBSG1RtvJmpyvcGhsjiAIUFVGB/I848AIL75uO9eNltgzkKMvm4rzFIZKPpsmlTbTw6L0PU949jWj9OfT0DFgtKTtlYdXq5BHGCaDD/wJc/wRZ5koz0d9s6nNqtcm9c7TjkvEvXyBr+m/ckqPRIcuqF7B6WzEVursDkkz7DfZkW4xlGxFXQAb7Q56jqqOicgo8FkReWSda1czTyvyqqrvAd4DMOKldBc5lAaewjGE44RkEEKi+ccwQTTbwAhD1n6vWimKFqOYBKPR+HbiniwPUrViGfqyQm2/RtoTnjpS5K6TcwxmhO1Z4SvHZ0mp0pfxmKuaDr9rd4+wuz+Nf2KeQtqn2jKWfmGpRsoTitkU9cgLSSQ9VMpRbQQMDRR5yS37adVrnJxeYmapgecJg/m0iYpo83tge4lKPc8jp2YAM1vCU+Xbp2eZWqgtK+wQs9drCtMXeyaK9U7Iq+nnWeIxqco7F+bInzi8Wn2uLJBENa44kKjXfhnu1t6SK5pn8kKykqehNe7hCxS1tN7lG6pXcDrbDTrrqc9CALWgxSKXcHaQqo7Z/88C/4BpLk6IyC4A+/9Ze/kpYG/i9qswY0Zr0sIuJpEiTyfFjXhcpbAXZTdQVNPUrNt+xSimhgc01UQmTGH6JCMZiQZh1LOzikVQEcZqUYzvlcUX3WuacdajUBM58EsnZqjUmzwyXaEZhAymhDOLdVKe7blU5RuPnODI6SlCDTk5vcTsQpWn7R9BEDKex1P3DrF9qBinLSL0F7LsHswzuVjntoPbmJpdIK0t0imfs+U6s5Vm3L8odi7x4bPz7BsutJebm7rh7NwSYah2QNC6WiIsicfXRHjQE46IckZgWpoc8cococ5xqdBXLDI9dhKgtVn16tgaspIHICM5trObBWZgk+vV6ezW6Oz9ssAR6jxAmRObNCZwzpaAiBQBT1UX7efvAd4KfAy4A3iH/f+f7C0fA/5WRH4fM9B0HfD19dIIEY5riyGqTNLARwjxmLITyxYI24Gl1MxBFiHevzSak1w1OcbOSrN75rY3YFe1qxXjl2O5z2OkMA7+ZKyvabaVQyg3jTAenqnRl/GptUJT2fb5YahMLtbMsnQR7j85Q9o3TUDPE27eO0xfX4EvPXya3X0Zzi412DZY5PDEIo1mi7seGSflCTft6GO62qLWaFFVjQUpymO52mSmXMP3PFpBkJg2116GbnYkMl6ZCjTUbPc3jJJXZRyhj5BjNDmryly1yvWjO8FEA96UenVcegJtoSgpSRNoixkmOMgTYZPr1enspdfZCfEooRyjyQxsWijpjXQH7QD+wRZaCvhbVf2UiHwD+LCI/BQmvtF/BlDVB0Xkw8BDmDr/f8410yBEKcsCZTXNyQmgIWYO2DwhJRHG7dSxaKeiAmYQKrTHAxJNRhHQlROwDG3XwXgapvCTK6WM02Gem0757N3Wx4FSmvvGFpiuNECEcjMk5XsU8xkK2TQp36Nab3JsthI/v1JvItLC84QgVA6Nz3JqeonrhnJsL+U4Mlvl7KmZOPZ5pd5CVbn31LyJrmjdHFUzgOV5QitUwiDk3uMzBEEU+dO+uShq45GoPZ7HeF4poE+VPbZZvoRyVOExWjRR+vL97L7mRoBx4CWbUa+OS0+dGvfzFTszRtnJXkZkJ+jm1qvT2Uuvs3WUPoUiHhVC6psyIrABI6CqR4CnrHJ8GnjRGve8HXj7RjMhhJRIkUKZR0kJzGOWTadtJgtqgic1ROIl1ZEAJQMpxfZXZFk42rhPLxK2RFMqFsDYJNumn+dx1bY+phZreEGLPaWMESjM0vKnHBjB830qjYD9u0eYnp5ner7S7rdUJeUJ144UmK8HfOXwNDNLZrD0+tESewbzHDqzEA9kRQteKo3Etng2S5mUx46+DMfnTP9hEO1XirJsZnU8q0LJqtnVKQD6Ubsa0ccj4ADCiHh8NyP4lPn00JAtUQJV3ZR6dVx6CtLHs3nJaqc2tV6dzl56nd2tUMZjG4OMUubUJnUHdcWKYROONsW1pLkRYQRII2Qx82MVs3AiEo8AMwMBe8wjcTIxTziaWBYJnrlueVMt+hSFjxX7FwneqekyC9UGE+UGI7lUvAqwFYTce3SKe45Mks6kOXV2nrsfP2Nltv38QJWDg3k0DJmtRLmG47NV9gzkOLC9tGyKWHLVrpn+Bn35DH25NCnTkRjPgAATyCuaexy/qJhBtgDTL+sDTTUTxWcJqGKiE+4DPC3TEmFIXRRRx8ZxOtsdOrsZdEUU0SYwp8oYAQ2UhzADSSlgEiNMZYxHAaYQU2L6D028EUGkHTNkRZchduZB20jbk5FQmZrYu62PpiqT81UCG/mvFYSgylKjxUSlie97eGpWMYahcnBHP+WlGkfGZwnD9gIR28ZFEHxP8FIpoI7nCbtKWZ57cJh7JircdvUIswsVvnx8lvlKY1mfpxmEyvCUqwY5dGaRRqAk2o1x8xERxPPbXhGKhkrLvlfUV3pWlboIs5jl37sIqVLB0wxZTLPU4dgITme7Q2c3g65oCYgoc6I0Ec4gzCO0gBnMjII6pi9RsQNLYrZeQ6KAU8T9gR0Pbn8kIUzRcU1OSoPtpTw/+4In8MIn7sbzvPh60+yDk+UGtx8c5Bl7B41gecL0/BKHrTBFsxPCMETDkIwv7C2lmak0GS6k8T2PJ23v44nb8ozP1xibXeLTD5+hvy/Pc67Zzvb+HL5nQsumfJ+U71FI+9x3ao7JxRrj5Uacn8h3sruTYgbToC2Nbe/GA7ZhmuAh7ZWdVUwTXkjhOwPgOA+czl45OtsVLQFfhScR8gCteDCpLO1Y44LxKKL+NrGeRBSu1lhOjYVq2ezZhPBo8vsq3HdymnoYMjZbIUxs3Rb1/9WaId8aL1NphgwWMtx2zQj1ZsDhyTJHJsuxtY+sezHj8ZTRIouhZ3Y8EuHR2SoPToZk0j71RotKrck/33+KQibFtcMFnrxrgMdmquwd7ccPlS8dGo+bka0w2XxcGWPFLKGP+hfbNIEzIqTsc+YwSrqEsAOfAnUqKCUXQc6xQZzOdofObgayIvjSFiAii8Chrc7HBTACTJ3zqu4meof9qrp9Mx4oIpOYLs7LuWwu97rd9HoFp7NdwKbVa1e0BIBDqvqMrc7Ed4qI3H055x8uzjuo6vbLvWxc/tfE6ewWspn574oxAYfD4XBsDc4IOBwORw/TLUbgPVudgQvkcs8/XLx3uNzLxuX/0j73UuHyb+mKgWGHw+FwbA3d0hJwOBwOxxbgjIDD4XD0MFtuBETkZSJySEQet3ufdiUickxEvi0i3xKRu+2xYRH5rIg8Zv8fSlz/q/adDonIS7cgv+8TkbMi8kDi2HnnV0Sebt/7cRF5t8g6K3eWp+/q9eLk19XrBnD1eh71Gi2b3oo/TJykw8DVmNXm9wFP3Mo8rZPXY8BIx7F3Am+0n98I/I79/ET7LlngoH1H/xLn93bgacADF5JfTGz52zALGj8JvNzVq6tXV69XTr1udUvgWcDjqnpEVRvABzEbX18uvJIu3ZRdVT+PCeWS5LzyK2YHqn5V/YoaCfurxD3r4er1IuHq9YJw9boKW20ENrzJdRegwGdE5Jsi8np7bIde4Obdl5jzze8e+7nz+Lno1vdfDVevrl679b0uSb1uddiI1fqrunXO6nNUdUxERoHPisgj61x7Ob0XrJ3f7/Q9Lqf3d/XaPv6dPq8bcfXaPr4uW90SuGw2L1fVMfv/WeAfMM3FCbm8NmU/3/yesp87j5+Lbn3/Fbh6XXb8XHTr+6/A1euy4+uy1UbgG8B1InJQRDLAazAbX3cVIlIUkVL0Gfge4AFMXu+wl93B8s27XyMiWRE5SPdsyn5e+bVN0EURebadZfDjiXvWw9XrpcXVawJXr+dZr1sxct8xKv4K4FHMCPevbXV+1sjj1ZjR+PuAB6N8YvZ9+DfgMfv/cOKeX7PvdIgNjNBfhDz/HWbT+CbGQ/ip7yS/wDMwCnQY+GPsKnNXr65eXb1eGfXqwkY4HA5HD7PV3UEOh8Ph2EKcEXA4HI4exhkBh8Ph6GGcEXA4HI4exhkBh8Ph6GGcEXA4HI4exhkBh8Ph6GH+fxDkjrjcp2sxAAAAAElFTkSuQmCC\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mKeyboardInterrupt\u001B[0m                         Traceback (most recent call last)",
      "Input \u001B[1;32mIn [27]\u001B[0m, in \u001B[0;36m<cell line: 3>\u001B[1;34m()\u001B[0m\n\u001B[0;32m      1\u001B[0m model \u001B[38;5;241m=\u001B[39m SpecDetector(model_path\u001B[38;5;241m=\u001B[39mmodel_file, blk_sz\u001B[38;5;241m=\u001B[39mblk_sz, channel_num\u001B[38;5;241m=\u001B[39m\u001B[38;5;28mlen\u001B[39m(selected_bands))\n\u001B[0;32m      2\u001B[0m \u001B[38;5;66;03m# 画图验证效果\u001B[39;00m\n\u001B[1;32m----> 3\u001B[0m \u001B[43mvisualization_evaluation\u001B[49m\u001B[43m(\u001B[49m\u001B[43mdetector\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mmodel\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mdata_path\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43mr\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mF:\u001B[39;49m\u001B[38;5;124;43m\\\u001B[39;49m\u001B[38;5;124;43mzhouchao\u001B[39;49m\u001B[38;5;124;43m\\\u001B[39;49m\u001B[38;5;124;43m617\u001B[39;49m\u001B[38;5;124;43m\\\u001B[39;49m\u001B[38;5;124;43m617_pure_tobacco\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mselected_bands\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mselected_bands\u001B[49m\u001B[43m)\u001B[49m\n",
      "File \u001B[1;32m~\\PycharmProjects\\tobacco-industry\\utils.py:112\u001B[0m, in \u001B[0;36mvisualization_evaluation\u001B[1;34m(detector, data_path, selected_bands)\u001B[0m\n\u001B[0;32m    110\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m idx, image_path \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28menumerate\u001B[39m(image_paths):\n\u001B[0;32m    111\u001B[0m     \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28mopen\u001B[39m(image_path, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mrb\u001B[39m\u001B[38;5;124m'\u001B[39m) \u001B[38;5;28;01mas\u001B[39;00m f:\n\u001B[1;32m--> 112\u001B[0m         data \u001B[38;5;241m=\u001B[39m \u001B[43mf\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mread\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m    113\u001B[0m     img \u001B[38;5;241m=\u001B[39m np\u001B[38;5;241m.\u001B[39mfrombuffer(data, dtype\u001B[38;5;241m=\u001B[39mnp\u001B[38;5;241m.\u001B[39mfloat32)\u001B[38;5;241m.\u001B[39mreshape((nrows, \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m, ncols))\u001B[38;5;241m.\u001B[39mtranspose(\u001B[38;5;241m0\u001B[39m, \u001B[38;5;241m2\u001B[39m, \u001B[38;5;241m1\u001B[39m)\n\u001B[0;32m    114\u001B[0m     nbands \u001B[38;5;241m=\u001B[39m img\u001B[38;5;241m.\u001B[39mshape[\u001B[38;5;241m2\u001B[39m]\n",
      "\u001B[1;31mKeyboardInterrupt\u001B[0m: "
     ]
    }
   ],
   "source": [
    "model = SpecDetector(model_path=model_file, blk_sz=blk_sz, channel_num=len(selected_bands))\n",
    "# 画图验证效果\n",
    "visualization_evaluation(detector=model, data_path=r'F:\\zhouchao\\617\\617_pure_tobacco', selected_bands=selected_bands)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "visualization_y(y_list, blk_sz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.7 ('base')",
   "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": "3.9.7"
  },
  "vscode": {
   "interpreter": {
    "hash": "7f619fc91ee8bdab81d49e7c14228037474662e3f2d607687ae505108922fa06"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}