vehicle-detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/shubhra-rajan/miniconda3/envs/carnd-term1/lib/python3.5/site-packages/sklearn/cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "#!/usr/bin/env python3\n",
    "# -*- coding: utf-8 -*-\n",
    "\"\"\"\n",
    "Created on Tue Dec 12 23:57:01 2017\n",
    "@author: srajanku\n",
    "\"\"\"\n",
    "\n",
    "import matplotlib.image as mpimg\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import cv2\n",
    "import glob\n",
    "import os\n",
    "import time\n",
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from skimage.feature import hog\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from scipy.ndimage.measurements import label\n",
    "# Read in our vehicles and non-vehicles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cars = []\n",
    "notcars = []\n",
    "\n",
    "\n",
    "\n",
    "for imagelist in glob.glob('vehicles/**/*.png' , recursive=True):\n",
    "    cars.append(imagelist);\n",
    "\n",
    "for imagelist in glob.glob('non-vehicles/**/*.png' , recursive=True):\n",
    "    notcars.append(imagelist);\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8792\n",
      "8968\n"
     ]
    }
   ],
   "source": [
    "\n",
    "image = mpimg.imread(cars[0])\n",
    "print(len(cars))\n",
    "print(len(notcars))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/shubhra-rajan/miniconda3/envs/carnd-term1/lib/python3.5/site-packages/skimage/feature/_hog.py:119: skimage_deprecation: Default value of `block_norm`==`L1` is deprecated and will be changed to `L2-Hys` in v0.15\n",
      "  'be changed to `L2-Hys` in v0.15', skimage_deprecation)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "110.69 Seconds to extract HOG features...\n"
     ]
    }
   ],
   "source": [
    "   \n",
    "# Define a function to return HOG features and visualization\n",
    "def get_hog_features(img, orient, pix_per_cell, cell_per_block, \n",
    "                        vis=False, feature_vec=True):\n",
    "    # Call with two outputs if vis==True\n",
    "    if vis == True:\n",
    "        features, hog_image = hog(img, orientations=orient, pixels_per_cell=(pix_per_cell, pix_per_cell),\n",
    "                                  cells_per_block=(cell_per_block, cell_per_block), transform_sqrt=True, \n",
    "                                  visualise=vis, feature_vector=feature_vec)\n",
    "        return features, hog_image\n",
    "    # Otherwise call with one output\n",
    "    else:      \n",
    "        features = hog(img, orientations=orient, pixels_per_cell=(pix_per_cell, pix_per_cell),\n",
    "                       cells_per_block=(cell_per_block, cell_per_block), transform_sqrt=True, \n",
    "                       visualise=vis, feature_vector=feature_vec)\n",
    "        return features\n",
    "\n",
    "# Define a function to compute binned color features  \n",
    "def bin_spatial(img, size=(32, 32)):\n",
    "    # Use cv2.resize().ravel() to create the feature vector\n",
    "    features = cv2.resize(img, size).ravel() \n",
    "    # Return the feature vector\n",
    "    return features\n",
    "\n",
    "# Define a function to compute color histogram features  \n",
    "def color_hist(img, nbins=32, bins_range=(0, 256)):\n",
    "    # Compute the histogram of the color channels separately\n",
    "    channel1_hist = np.histogram(img[:,:,0], bins=nbins, range=bins_range)\n",
    "    channel2_hist = np.histogram(img[:,:,1], bins=nbins, range=bins_range)\n",
    "    channel3_hist = np.histogram(img[:,:,2], bins=nbins, range=bins_range)\n",
    "    # Concatenate the histograms into a single feature vector\n",
    "    hist_features = np.concatenate((channel1_hist[0], channel2_hist[0], channel3_hist[0]))\n",
    "    # Return the individual histograms, bin_centers and feature vector\n",
    "    return hist_features\n",
    "\n",
    "# Define a function to extract features from a list of images\n",
    "# Have this function call bin_spatial() and color_hist()\n",
    "def extract_features(imgs, cspace='RGB', orient=9, \n",
    "                        pix_per_cell=8, cell_per_block=2, hog_channel=0,spatial_size=(32, 32),\n",
    "                        hist_bins=32, hist_range=(0, 256)):\n",
    "    # Create a list to append feature vectors to\n",
    "    features = []\n",
    "    # Iterate through the list of images\n",
    "    for file in imgs:\n",
    "        # Read in each one by one\n",
    "        image = mpimg.imread(file)\n",
    "        # apply color conversion if other than 'RGB'\n",
    "        if cspace != 'RGB':\n",
    "            if cspace == 'HSV':\n",
    "                feature_image = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)\n",
    "            elif cspace == 'LUV':\n",
    "                feature_image = cv2.cvtColor(image, cv2.COLOR_RGB2LUV)\n",
    "            elif cspace == 'HLS':\n",
    "                feature_image = cv2.cvtColor(image, cv2.COLOR_RGB2HLS)\n",
    "            elif cspace == 'YUV':\n",
    "                feature_image = cv2.cvtColor(image, cv2.COLOR_RGB2YUV)\n",
    "            elif cspace == 'YCrCb':\n",
    "                feature_image = cv2.cvtColor(image, cv2.COLOR_RGB2YCrCb)\n",
    "            feature_image = feature_image/255.0\n",
    "        else: feature_image = np.copy(image)      \n",
    "\n",
    "        # Call get_hog_features() with vis=False, feature_vec=True\n",
    "        if hog_channel == 'ALL':\n",
    "            hog_features = []\n",
    "            for channel in range(feature_image.shape[2]):\n",
    "                hog_features.append(get_hog_features(feature_image[:,:,channel], \n",
    "                                    orient, pix_per_cell, cell_per_block, \n",
    "                                    vis=False, feature_vec=True))\n",
    "            hog_features = np.ravel(hog_features)        \n",
    "        else:\n",
    "            hog_features = get_hog_features(feature_image[:,:,hog_channel], orient, \n",
    "                        pix_per_cell, cell_per_block, vis=False, feature_vec=True)\n",
    "            \n",
    "        spatial_features = bin_spatial(feature_image, size=spatial_size)\n",
    "        # Apply color_hist() also with a color space option now\n",
    "        hist_features = color_hist(feature_image, nbins=hist_bins, bins_range=hist_range)\n",
    "        \n",
    "#        features.append(np.concatenate((spatial_features, hist_features,hog_features)))\n",
    "        features.append(hog_features)\n",
    "\n",
    "    # Return list of feature vectors\n",
    "    return features\n",
    "    \n",
    "### TODO: Tweak these parameters and see how the results change.\n",
    "colorspace = 'YCrCb' # Can be RGB, HSV, LUV, HLS, YUV, YCrCb\n",
    "orient = 9\n",
    "pix_per_cell = 4\n",
    "cell_per_block = 2\n",
    "hog_channel = \"ALL\" # Can be 0, 1, 2, or \"ALL\"\n",
    "spatial_size=(32, 32)\n",
    "hist_bins=32\n",
    "\n",
    "t=time.time()\n",
    "car_features = extract_features(cars, cspace=colorspace, orient=orient, \n",
    "                        pix_per_cell=pix_per_cell, cell_per_block=cell_per_block, \n",
    "                        hog_channel=hog_channel)\n",
    "notcar_features = extract_features(notcars, cspace=colorspace, orient=orient, \n",
    "                        pix_per_cell=pix_per_cell, cell_per_block=cell_per_block, \n",
    "                        hog_channel=hog_channel)\n",
    "t2 = time.time()\n",
    "print(round(t2-t, 2), 'Seconds to extract HOG features...')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(24300,)\n",
      "(24300,)\n"
     ]
    }
   ],
   "source": [
    "print(car_features[0].shape)\n",
    "print(notcar_features[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using: 9 orientations 4 pixels per cell and 2 cells per block\n",
      "Feature vector length: 24300\n",
      "7.18 Seconds to train SVC...\n",
      "Test Accuracy of SVC =  0.9848\n",
      "My SVC predicts:  [ 0.  1.  0.  0.  0.  1.  0.  0.  0.  0.]\n",
      "For these 10 labels:  [ 0.  1.  0.  0.  0.  1.  0.  0.  0.  0.]\n",
      "0.00151 Seconds to predict 10 labels with SVC\n"
     ]
    }
   ],
   "source": [
    "# Create an array stack of feature vectors\n",
    "X = np.vstack((car_features, notcar_features)).astype(np.float64)                        \n",
    "# Fit a per-column scaler\n",
    "X_scaler = StandardScaler().fit(X)\n",
    "# Apply the scaler to X\n",
    "scaled_X = X_scaler.transform(X)\n",
    "\n",
    "# Define the labels vector\n",
    "y = np.hstack((np.ones(len(car_features)), np.zeros(len(notcar_features))))\n",
    "\n",
    "\n",
    "# Split up data into randomized training and test sets\n",
    "rand_state = np.random.randint(0, 100)\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    scaled_X, y, test_size=0.2, random_state=rand_state)\n",
    "\n",
    "print('Using:',orient,'orientations',pix_per_cell,\n",
    "    'pixels per cell and', cell_per_block,'cells per block')\n",
    "print('Feature vector length:', len(X_train[0]))\n",
    "# Use a linear SVC \n",
    "svc = LinearSVC()\n",
    "# Check the training time for the SVC\n",
    "t=time.time()\n",
    "svc.fit(X_train, y_train)\n",
    "t2 = time.time()\n",
    "print(round(t2-t, 2), 'Seconds to train SVC...')\n",
    "# Check the score of the SVC\n",
    "print('Test Accuracy of SVC = ', round(svc.score(X_test, y_test), 4))\n",
    "# Check the prediction time for a single sample\n",
    "t=time.time()\n",
    "n_predict = 10\n",
    "print('My SVC predicts: ', svc.predict(X_test[0:n_predict]))\n",
    "print('For these',n_predict, 'labels: ', y_test[0:n_predict])\n",
    "t2 = time.time()\n",
    "print(round(t2-t, 5), 'Seconds to predict', n_predict,'labels with SVC')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "POST TRAINING WORK \n",
    "\n",
    "model is trained using svc\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# POST TRAINIG OPERATIONS:\n",
    "def convert_color(img, conv='RGB2YCrCb'):\n",
    "    if conv == 'RGB2YCrCb':\n",
    "        return cv2.cvtColor(img, cv2.COLOR_RGB2YCrCb)/255\n",
    "    if conv == 'BGR2YCrCb':\n",
    "        return cv2.cvtColor(img, cv2.COLOR_BGR2YCrCb)/255\n",
    "    if conv == 'RGB2LUV':\n",
    "        return cv2.cvtColor(img, cv2.COLOR_RGB2LUV)/255\n",
    "\n",
    "\n",
    "def find_cars(img, ystart, ystop, scale, svc, X_scaler, orient, pix_per_cell, cell_per_block, spatial_size, hist_bins):\n",
    "    \n",
    "    draw_img = np.copy(img)\n",
    "    img = img.astype(np.float32)/255\n",
    "    box_list =[]\n",
    "    \n",
    "    img_tosearch = img[ystart:ystop,:,:] \n",
    "    ctrans_tosearch = convert_color(img_tosearch, conv='RGB2YCrCb')\n",
    "    if scale != 1:\n",
    "        imshape = ctrans_tosearch.shape\n",
    "        ctrans_tosearch = cv2.resize(ctrans_tosearch, (np.int(imshape[1]/scale), np.int(imshape[0]/scale)))\n",
    "        \n",
    "    ch1 = ctrans_tosearch[:,:,0]\n",
    "    ch2 = ctrans_tosearch[:,:,1]\n",
    "    ch3 = ctrans_tosearch[:,:,2]\n",
    "\n",
    "    # Define blocks and steps as above\n",
    "    nxblocks = (ch1.shape[1] // pix_per_cell) - cell_per_block + 1\n",
    "    nyblocks = (ch1.shape[0] // pix_per_cell) - cell_per_block + 1 \n",
    "    nfeat_per_block = orient*cell_per_block**2\n",
    "    \n",
    "    # 64 was the orginal sampling rate, with 8 cells and 8 pix per cell\n",
    "    window = 64\n",
    "    nblocks_per_window = (window // pix_per_cell) - cell_per_block + 1\n",
    "    cells_per_step = 2  # Instead of overlap, define how many cells to step\n",
    "    nxsteps = (nxblocks - nblocks_per_window) // cells_per_step\n",
    "    nysteps = (nyblocks - nblocks_per_window) // cells_per_step\n",
    "    \n",
    "    # Compute individual channel HOG features for the entire image\n",
    "    hog1 = get_hog_features(ch1, orient, pix_per_cell, cell_per_block, feature_vec=False)\n",
    "    hog2 = get_hog_features(ch2, orient, pix_per_cell, cell_per_block, feature_vec=False)\n",
    "    hog3 = get_hog_features(ch3, orient, pix_per_cell, cell_per_block, feature_vec=False)\n",
    "    \n",
    "    for xb in range(nxsteps):\n",
    "        for yb in range(nysteps):\n",
    "            ypos = yb*cells_per_step\n",
    "            xpos = xb*cells_per_step\n",
    "            # Extract HOG for this patch\n",
    "            hog_feat1 = hog1[ypos:ypos+nblocks_per_window, xpos:xpos+nblocks_per_window].ravel() \n",
    "            hog_feat2 = hog2[ypos:ypos+nblocks_per_window, xpos:xpos+nblocks_per_window].ravel() \n",
    "            hog_feat3 = hog3[ypos:ypos+nblocks_per_window, xpos:xpos+nblocks_per_window].ravel() \n",
    "            hog_features = np.hstack((hog_feat1, hog_feat2, hog_feat3))\n",
    "\n",
    "            xleft = xpos*pix_per_cell\n",
    "            ytop = ypos*pix_per_cell\n",
    "\n",
    "            # Extract the image patch\n",
    "            subimg = cv2.resize(ctrans_tosearch[ytop:ytop+window, xleft:xleft+window], (64,64))\n",
    "          \n",
    "            # Get color features\n",
    "            spatial_features = bin_spatial(subimg, size=spatial_size)\n",
    "            hist_features = color_hist(subimg, nbins=hist_bins)\n",
    "\n",
    "            # Scale features and make a prediction\n",
    "#            test_features = X_scaler.transform(np.hstack((spatial_features, hist_features, hog_features)).reshape(1, -1)) \n",
    "            test_features = X_scaler.transform(np.hstack((hog_features)).reshape(1, -1))\n",
    "            #test_features = X_scaler.transform(np.hstack((shape_feat, hist_feat)).reshape(1, -1))    \n",
    "            test_prediction = svc.predict(test_features)\n",
    "            \n",
    "            if test_prediction == 1:\n",
    "                xbox_left = np.int(xleft*scale)\n",
    "                ytop_draw = np.int(ytop*scale)\n",
    "                win_draw = np.int(window*scale)\n",
    "                box_list.append(((xbox_left, ytop_draw+ystart),(xbox_left+win_draw,ytop_draw+win_draw+ystart)))\n",
    "                cv2.rectangle(draw_img,(xbox_left, ytop_draw+ystart),(xbox_left+win_draw,ytop_draw+win_draw+ystart),(0,0,255),6) \n",
    "                \n",
    "    return draw_img, box_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_heat(heatmap, bbox_list):\n",
    "    \n",
    "    # Iterate through list of bboxes\n",
    "    for box in bbox_list:\n",
    "        # Add += 1 for all pixels inside each bbox\n",
    "        # Assuming each \"box\" takes the form ((x1, y1), (x2, y2))\n",
    "        heatmap[box[0][1]:box[1][1], box[0][0]:box[1][0]] += 1\n",
    "\n",
    "    # Return updated heatmap\n",
    "    return heatmap# Iterate through list of bboxes\n",
    "    \n",
    "def apply_threshold(heatmap, threshold):\n",
    "    # Zero out pixels below the threshold\n",
    "    heatmap[heatmap <= threshold] = 0\n",
    "    # Return thresholded map\n",
    "    return heatmap\n",
    "\n",
    "def draw_labeled_bboxes(img, labels):\n",
    "    # Iterate through all detected cars\n",
    "    for car_number in range(1, labels[1]+1):\n",
    "        # Find pixels with each car_number label value\n",
    "        nonzero = (labels[0] == car_number).nonzero()\n",
    "        # Identify x and y values of those pixels\n",
    "        nonzeroy = np.array(nonzero[0])\n",
    "        nonzerox = np.array(nonzero[1])\n",
    "        # Define a bounding box based on min/max x and y\n",
    "        bbox = ((np.min(nonzerox), np.min(nonzeroy)), (np.max(nonzerox), np.max(nonzeroy)))\n",
    "        # Draw the box on the image\n",
    "        cv2.rectangle(img, bbox[0], bbox[1], (0,0,255), 6)\n",
    "    # Return the image\n",
    "    return img\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test6.jpg\n",
      "288 648\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/shubhra-rajan/miniconda3/envs/carnd-term1/lib/python3.5/site-packages/skimage/feature/_hog.py:119: skimage_deprecation: Default value of `block_norm`==`L1` is deprecated and will be changed to `L2-Hys` in v0.15\n",
      "  'be changed to `L2-Hys` in v0.15', skimage_deprecation)\n"
     ]
    },
    {
     "data": {
      "image/png": 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naEda221uRofZUAPbj++ncJXGKI21Lc4yBB1RmaBf659T9n5E4RhDNkI2Glec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\nG9lsAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add8c05c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test5.jpg\n",
      "288 648\n"
     ]
    },
    {
     "data": {
      "image/png": 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OhVm3tp1sLk46lcfn62HHHb/Jgz+9m5bqBrbuuJTk1FF+ev/dCKuT+cU0TreT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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add0bddd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test4.jpg\n",
      "288 648\n"
     ]
    },
    {
     "data": {
      "image/png": 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OiBDEtApNNMIIHTbeO7IQwDtyCdAsWLlkJT6bIM+bdHUP0rNoJblbRe+Sddx7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qrwdazZZFmCkhIdBP1Bl8FwiEj0Yn3xrmlAjs4XJlHI4BE6NgfjZOzjUhIRbjYYCyGjMW2IhHyS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\n8f8BOmChokDAkCIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add304fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test2.jpg\n",
      "288 648\n"
     ]
    },
    {
     "data": {
      "image/png": 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OavputN9gRNAVBRSvnr+RGTNmXDJcFoSfdDo8V9alIBLgtXkjGWqaWGISsKYFjUx0G+lh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\n7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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add8ab1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test1.jpg\n",
      "288 648\n"
     ]
    },
    {
     "data": {
      "image/png": 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EzKNRJzRNQhsfleQ8hVofICe5o6rLzetMCgIffEeFAgSJJmFkjKw8uao19yt8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\nW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htVPYgwhkd33sBY3Us6SPEioi6DLbgxhnleknW60F7P66/hvedwNObypUssigW2DJDu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\nxwrPCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add74fa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_images/test3.jpg\n",
      "288 648\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ci7KxTOzDFBN91Q6rI4u8iFDnVoZHFRdYRUjVmxhm8RYco4BY1FDVEsW54kSS\nid3nhlnMjUZSnej5neA0bJRkZQo2+jkYYk5mEHFGpEbxULLCOtpxmAoLPG+lEseAIEcI2Tx8JlG8\nmyKsSZwDUYQMkNTQifgSEkmqWB0jN9aMkCtbmHiPMNLJOjkVV0TfiJ+DaMKKH9NFfRVL0ZI+Z1KE\nFmfMmHH1cE0ZKNeWgWAThC7c1hAAW7pxJMobDNvWtQhT1b8m90IAVzZQ1z4Impe/bk7ZVhVS8vAT\nRLdaE1QyFjTmNgYRQ8pWO3CS5qkWyXUL21rIplhWkrn8EU1NwRLY6CFLG+ki1Ccp7TTVq1G75Pmr\nagMqziLUmIituoEAqImJiajAQoRq7oFZkwWSNt17XZI22XVhop17Pym/TtWgi9+N5t35PlH17Ys3\ne7TwAlXFW9XTRHJ98q9UOnFjnBGX8VWNdimNqBEGKs6x4rqBGgoiWQWlUFRZWAoD0yM2IDsSVyti\n4UFlWYSSErUdMwghXbTccHagn7eZhw4lCB5O3jBmDt+MGVcX14SBEqerORmgFarGxNQKQ8fNcJLJ\nV22qVfF9nGTxSdC6Ae+JFMdxenIUh4ZnI3hdTanD5DE15JycURheQineiTfF5L5VWJfI7ThTrto4\n5bOsbuNGrcjVBxTNB4NGn0OyaKQ6ASFyHjlnD52JensP80LWcRy3VOpgF5biCuqi23aKKs5Za3ky\n06j3AUoZyXnpea3IWalUSnVGXjKg1kndu44lelgNTlKJadtalFNCPxDI0X3Xagu7hdHdqTvy66eR\nl/KQ6K5yhpmHK4fYdxLvYVUIpfTBSRRdUmpNJ/JESVuoVz2vOW7ouszGNOqzLAgvhTHyc9KOj7j+\nXiIkpnZr8mbMmHE1cMVCXRF5mYj8fyLyYRH5kIj81/H6GRH5NRH50/h5Y7wuIvKDInKniHxARD73\nyQxkP2c6lGwyFVJ24rkCgNx5DmCRFK0lJrTiLdvxCU/ZdpZtEj0iQury1Fdpl8rePtMmXmxLpsg5\ns9A8beNSS5W+750ZWIobSdXJ8xLxAmNNbP8W1xn017ZjUNWgfDujrq3Ote0PvA27wDhswll01pkn\n710UV7LneNo5dar0KdHFPp027a93muhTZiHCUpXW40hsIFPIWpwMId7hPWWZilaXqiwMv/5i9H1P\n1kSP56tS6tDqOnmd+OS/yAtMEtIZi6Ts5cSeKp0afd5qFBaroTuooIlOF3SiXlwryqIT9pKy6Hw9\n1aVMb5l7tD0rAAAgAElEQVRk0CVFMbDRA4Hak3RBkp49EvskektkVbrFHlkypySz1EyPklOC7EW/\nnQkLiXNC2O8X9JrIiP/UKz4u18SzNGPG8wVP5okbge81szcAXwh8t4i8Efg+4NfN7Hbg1+NvgK8F\nbo9/3wX88ysdQBCG8ExaWEsi/5BDxDOb51eaNJGXvZxsyQHb4sysOhkpYDIKu+E4EfEuscIkKPt4\nTely6j3UF59dLpfkvKNe0WKQOP29eU+ubCAR/tq2CtnWe9UTWoLNI9s1ZLtjaq81L2PSEdxRcNj9\nfPsddun2jkXK9CnTafKaqurae63cRyOUWes43Q8RIafeiROa/B7UEaXSJTeCKkKXM1TXy8v18hKA\nuDcJuuSLjkVS+uzGJqlr46kSzQabMGwNPbxK17s4bK+JRWj7JXEJ3ZxCSUQ1NBdrhGS3AsK+fw3a\nvjMOi0Yn5p3r18bRxvIM8Zw/SzNmPJ9wRQNlZvea2R/G7xeBDwMvAb4J+PHY7MeBb47fvwl4uzne\nDdwgIrdd6TgpZ1Sh6xKW2+o+wnmlei5JFZJPFlJLyAfFZJN2PJWm97bjJSniRAep0+RjZuxpJmua\ntslNBokdY7fTW2kShq0F0wrJPabGBut77w6bUqLrupNhSYyc01RArKr0fX/CaLXtm2RPO76IhyFd\naHZLh2/Gr1P14tzLjNnJfTP902jad7kB9zBfyP3E+y5hVL13kwRVXw3DPbBF17sHEtcxm7P2kgoW\n3m4ruhXVyKd5nVHCWX0pGINZzSnzWGS8Wl7KwnidNNCj1amg2r3SrdctIpTkgrxJlC4rC3GKYGMH\nGs5M1PAyUUE795JVDKyi4l7uMy2DulrP0owZzxc8pRyUiLwS+BzgPcCtZnYv+IMnIrfEZi8BPr3z\nsbvjtXsff8eG6+x5PiAZkzyPi6ZG7YvsiITGRFxrpRTQVD3PkNRFVLuWiyLUHKKYFHF2VkgkeVeM\nQk6dd3itTk2GsN6ybSWP+JRpAilqmJpWn4WH1FrFP1bPqmYI2TEknsRvVsPJBcl2NPumzsFeQGuM\n5E4pozcwFD5T/X23R1afwriqbzOEwSBycBDSQqWQO9+21+gNhatuVIwarD8NA0+QIRKeezNxiSUq\nVBVqdeWI3EKttUYez7voUi3ulV+rlofTIFJoC8fiOS215mH692RS5WiGHPN8ZFgRiTYcfm9sItlU\nMXLSqeBakOn7gQTVv4xTD64sW33EZzMH9Zw9SzNmPI/wpA2UiBwAPw38DTO78AQP62O98RkEXRH5\nLjxswQ1nX7Qz0TW5GZ0kaJAt80wlMwze6dYnyIHqVao+2dcURbZbskNKXv5qNkbjPoNcJiZaimJO\ncE8t0RoKymQkNYWSBUpV98SSCmruUaA1an/UGW26NTKtcNWadJIGg68xDeM8a/MKQqR01/Ck6B+F\nZKxakDe2iXvRYPKZnjBQjTghOUGpLHLHUEPtYYxQpxZg27rDzLYEDytI1JkRlw4kNBPdgIS9CkPk\nRbkklwo64RFSMYNaCp12jNWvmcU2C82sykDfuyK6i8a6EayhCOJeXwLKRJKx6t+RnDNjG1fzuOPY\n4zgiVqlVJq8wiWJjoaYCFp5pXKddrwzc0xvqtnD8meC5fJZmGseM5xOelIESkQ5/oN5hZj8TL98v\nIrfFiu824IF4/W7gZTsffynwZ5fv08x+GPhhgJff/kZr4aXRqrdml6h9aQ38SnhBaSRlCeVzL+pV\nCta609oYzfhcvmY375JCNEg1+4qYGjkesBoFpDgjTaL1hgiTYfEonXs1kltRcKy0zVtYiF8w7z5b\nq0+0UaglnYSH2DQCT+acWi5pkZycYbEvcLklMScDtm7A6TFyT3aZ0Wu/qyg1FCw6dTp+865SShQV\n6rihS9t9AQjeHr0ZGzEPD5Jc0661qZ+Kajvv5qsGlEruOlbDxtXZg0W47Jb+mQhXLjUxyhi0fqjj\nVpk8ERqKZhPrbzen1ogmmmAc6uQFmhkpvOQylihLSDTRexHvWWWqKL13PvY6biQlJO5rSYKOXuh8\nXX/5t/ip47l+lpLM1Voznj+4ooESnw3+JfBhM/uBnbf+NfDXgH8UP39+5/XvEZGfBN4KnG/hiyc8\njmoYBNeqE4nuteDxs9RCclEwKRYeVwultYleo7ypaac56aLWDUImJe/I21bnblFcIb20Lr315CTf\ntOUKThjoUud1QlYxLahmKpVcQyVbxOnoejLcVgnKeKmTMkZLAzaCRM6ZYVxHoeqWNq+m0U8pzrec\nJECg4jmhRv4YT3Yhpm6bD9aYw6pApyEYazYZjC113j3MtnggaqC81sgJDo1fvmvUmjxQF2PZ6xd+\n3KDem1VSFsa69dScSl+mvF2nCavuVSbxNiiAlwOEcfPrEl8R/LPW5LLYtkrRpnRfL7sfChrXpdbq\nPVECrTC7y8f86s/9CNfJEZ/70huv9DV+QlytZ2nGjOcLnowH9SXAXwU+KCLvi9f+Dv4w/V8i8p8A\nnwL+o3jvl4CvA+4EjoC//qRGEjmM5MG9kJmJ4U3Gymt3DJ9Qq+zkXqyFuqon1FWnxnmS3VBpeEmj\njBGTii7z1TAGvPXRdoKTUqYGdq3cN6kbvMI231NDoSGl3ltVjBv65OT3nDPDsA7DEN5Gm8yrN8Nz\nY+fsP1FI3a78UaiG55B7Cq+rdcGtTSiXbf7G8z861fiYlEmTDhSt4vur7rGauC5e8/omsVecqefK\nFS2EKohUhGA0aonQZkz+dQynz6bmhBApth1jJpFv8hfcK+oj3yQi0f7dBVybmoRfs3FSinD7k+J4\n4U1Gq3hXtxi3eUgDNCNibPB6qyxg6ursmgQrodsnhtZjfuHHf5C3vPYs/8FtmWW6jpyesXNydZ6l\nGTOeJ7iigTKzd/H4oe2vfIztDfjupzKI1gpBYrIVU7p0MsdSohV5lRCLkJABap6TT0N0Faoqg7ms\nkKeiLHIdlSKeP2rHkZDiSSIuGhpFwp6A9/0bMtHIWwDFQ3/gXgW4zOsYbcW9B5QTENdO4AB6vJUF\nEZpzx9Bbk7vX4ufbmYaSgh8racLCw9JoT+4cANfLM7PwoIi+St4Jt8Q10GjsN7EQk4EpSbyotwnN\nNhHaxtloIb1GMQf/rBmIlihqjQJiKcHqM8yECP5NfbvAWrRyun5h1wihKn/f/E6WKNpGXPw1B/Gk\n4uG/rK4o7/kzdU/ajBTjVsBse9+8lf2IVaHPQbSpO7lLM+ihPHqB9/ybf8lbXnaGr3/NPtdfD4me\ngco4Dk/la/0ZuBrP0owZzydcG0oSwAIYRDBJYD755VACKKNN6g8KoJ17HJoYhsFJDtU9kJphtDJN\n7t7l1kK3znX7BM/BZEkMDBOdOUTO/Z9uFc6V6E/VGvQlLy6dHAABqRs3oOoTY6e9h8fMvYIaBAHX\nAfQJXBlxo2aRH1JK2aCSvbGfKYXNlKivAJZ8lR/huC48phoFx6Zl663EZF2CYFBLJWeXBDIrUxuM\nat6p2GuMdKr38v5ZLgFV6oBKdsdGjJSyE0wmAkoLoxX8LhUk495aYyWmGh5dXNemB0gIx2qFCMOl\n6osRM9ffw20JXcvttZqlIJvUKDr21vaGmrfmgEa193xlFZf0SDlD8e6+giDHF9m7/+Oc//RH+bJX\nXMdyUaDroRaG4ouVGw5OP8vf/BkzZjwRrgkDdenSBVQK5Xgg7y2m8FvznrquY1Oa8ng0I0w+Ke73\nC8ZxpCZPptvU8iE8DtJUjGkha1QnPTlQy9hOqLDBzHYMkLiKd9QcgXtDIjKxvar6mJ1CLiBDc2ei\n82uEzarX1xRh0oCrdXAvBD8vag1ZwtHrgaSJ3ELzGGED5iEpVejCC/F3zT2a8ARTULRd+TUMiEBl\nRBVq9IlqrTyAiWadzPUIm45fSu32jKg40cQXA8F6VJnadbgR9/5LQy3hETuRQ0QmA5mQiVlYKIga\n3aQ04WHKakRIMIRlIUKRcbottzQRWgTdye81g7vt6WT0KOXc3ewf3slidT91fcyZzqWztBjL/QNU\nxikftdkcP/0v+YwZM54yrgkD1anwiTs/jKQFt7381SxzR7GRJC6aWuvoRaCqjGVDiwp5d9mNNwtU\nJz+IpqiViSQ+1RvCBvPNzOgkRxtvD/lYM151h5oNQX13o1fUOX6agslWQbNQi07kBjObSBxmJRoq\nbhUizIobXs2Itaya1wNJ9caMKuLq4dGGPtThToTHavVeRU4UcY+pNXVs9UlT7mUnhOVVXzaFvTTy\nNhkPtTnBg/DsXBG9TfxdiDE5o05isQB+Qt5vSkQ8hOrDIFsrBHbDoNZ0+7a1W946ReglIaKY1hCO\nNToqw/ElVsdrrrv5ZtcHbMSVFimTMMsGqmkKu06cRjP3CIkaOARsJF06j93/R9xm97M+/zCmI1mW\npKZmkZW+E89n1YG+2+PUqf1n82s/Y8aMK+CaMFCHhw/y8he9iE01zj90H+dVuPWWF7nCeOSnXB40\nWkOYh/wMg8hVAR76ssFrbGycQkk56naAUEdvxbiCZmVdtqw17zfrk3Px4h5EdJrEqW1iFYZS3RvL\nHjLUYK6p+GQ8msvmeHjSjSeEVxMMOZGmCJGoLfQVVOfRqqtoqOvfiSRKrZPCgxMavMFfxbUEsxSq\nyUTPBxA8TyQmk7dYa0WDGScxJtSlhFrYjIl0gNd3mRswE3ViA14E655cHGzK0cmOUfX+WyLVFxEW\neTIrExGkEVY6UfbryKc/+G7+6Pd/k89502u48677OHP75/Paz/kiLy7W+Mz2BGkkCbEBTd3278g9\nZoVcjNX9n2Rx9DFOrc+xObpA6RRNhaQLai0slgtySqw2x6QMhGEehg0XL158Ol/vGTNmPE1cEwZK\nVPnYxz7Ia17zWdx6800Mljh37hHO3HzTNPm1Jn8qS2e6ZaHU6kWrkt0YaELwOqhU0tROA1p7923X\nW7PoB1Vb7oVIrDtNvVZQqZOR26pCeX6r4qGrWhREySnqokwosU3Xut9KC8+FccAb8ElQrCcPpxXm\nCtRa2FPF0o4KefhcEHkycVahWGEzGiLehbfVQrUTKdaKacWLaGulagLZ7Vps3nxRvCgsAZqUcXRK\neIpI3hhMOAvFjNJaYEQn3V7zpBKvkjAqnQiDeVsLVQsFC3HRXXPl9iKKjWuGcw/xG7/yDm46bdxy\nUPnoh9/L0eEx5x/8OJ/4g1/my7/+r3L6pa9jYwViQeEG3+nnpG7yZlMRBklkW7P51EdZru/mzOoB\n1qsLjJJZLBN9v6DWDNZ5mNkKVbxRodBz6dIlFosFpRa/ZjNmzLhquCYM1I033sItZ85w3yc+wrv+\n4Hd57RvezBvf9Nk8cu4hzpw5g0iaQlkth1Rr2bYMx8h48W0SVzcgpZ2amDTlrnYlhtp8oxHaS8GQ\nMCt0KVNsy7ZrxsOiKHZSH0/urUiExTz3sVVW91KrVvDrPxOAZMRKGDA3KlWaJJLbFsW9moRRon6r\nCZY2tiFWEINlTpPHgGxDdkIr73EygllFk9cXFYp7Vh4jjOvjHuA4jijQ9QkhBckjrl8tTFSP1EXB\n8khrvT5p/NWC3zGjj3MTFXKEA0erU/FtVoXDNcOlP+O2W8/ywD0fZizCYm/J0aOPcub6M4gUfvsX\nf4xb7vhS3vK2r2EVnigCmoZg8CWKFTKCZsHu/hDXH92Fbs5xeHhIWu5z3XXXAU0my6noKW8QySRL\nDMPIUMCGkaFUjs9fYrTCpaOj5/pRmDFjxg6uCQNlliml4+LxEWeuP8OXfeGX8IlP3MmZl74yNOJ6\nVIyhDNgwoJ03zBPJtBZ02BhN5pRxXIF2gDAOheXS+x2N40jrSdSlzIhQBp+IvU+TkMTAli5yGpmM\nYi6d4zG4gtaKaKaKd5n1fFXHpm6QVJ0Hn8zp8igm3kakyfW0vNBggqZKthSSSym06capRkgsYRmS\nufdB1EFJtIKX4uzBUSoqCRcqcDq2Rii0yjiF0vLk1TnXblfeSMKYIi7a6/fG2XKty614x0fvbAxU\n84VCQUgYuXUQBq+/omWEIr8VuasWLsyl0GOsjx9k8+jdHD5yjlFGzBacv3CexXrk8PCYYXOO6w4O\n6Pueo3s/wK/8xAf54v/wr7N/5iyqyoDQ60BlJFWlPvgx9s5/BF0/wNHRMSJ77O8fYFZYr9fUWlns\n7XkbDpTNZsPxMLLZjByuXW7p6OFLbGwgS6aUAc3Lq/ZMzJgx4xoxUCLCIw8/zG/99rt43R2v5Rf/\n1Y/C/gF89OMesioVS70LfGoH5Zi+7xkxvuiL38pP/9RP8bav+Ar2T5/m9OkDfvYnf5Kbb3sZRxv3\njN7yBW/lPb/3u4gpb3nr53N8fMyrXvFK3vlzP48l4eYzN3Hrrbfxqte8GjRT6kiOepvBQKyg9Ahe\nY6Uk74pbB0Z1JQKC2p0leHYSyRbTkPjZafFRnLHmdVzubeTce92SbdUVADRIHobTvaXaFLk0K0i0\nMs8tjNdakNSW+xI68yrfUbZeZNP986KmnVogJhLlVLDTFBtExRXNTXz/qgzFAGfiJVXEjBReYRUl\netOfIDcU8Z9SR9732/8Pt+wnVqtHuOtPPkAnldX6iHHTsR4KfVrQyQJQLh6vePieP+Mvf9u38fZ3\nvJOv+0/PUqOYez/B5sjoHvgQp4d72RsvcbQ+ZE3H9dctWa/XlDKwWq1Y7vV+dmOhqLAZC4dr4/yF\nC+x3p0iWWK8G+n5JMlfZH4cFD58//1w/CjNmzNiB7GrV/Xnhpptutr/0TV/PhVUhpQOvZ1me5vTp\nUxxdPGKzHlgc7DNWWKQeWT3Mw488wI1nX8Tq8JiDZeWRBx/gaKiw6Ll+ueDhQ7jh1ldEq/MFVQ2L\n0JKVwli37TzGsmG5OGC9XpNCvXp/2VEERjJaNyxOn+b48Jg77riD229/XRS8ulOlNYNUj2ixQVM/\n5XbGcaTLe4CLjU7KFztGoRXyNkxsQmMKE8K279MuRit4mVDUSkWfozI2LUFBGMPLCvaeBRtPJNqu\nh1eVZTJYFh12LUgcEoSGKmA1PE2iHTtlKytUAZWtTFWNtu3SCpvxjsnApUfP8ZH3/Raf/uC7uen6\nA86vL5LKisNLAxcvbei6BYp7Ogenz/DeD7yfg9OnefFLXsVbv/wbuO1Nn+VF0iIsN+c4/Mhvsbd5\nCF0k1pdWWO5Z9Jn1ZqSMGxbL/WiNUlnu9QybyoMPXuTi8QbVjLFGrfPyJ1NKMXLuuXh4zDiOHB2u\n+YG3//QfmNnnP8Ov/HOGJGKznzfjWscKKLbN8D8erhEPCh556AH6xXVcPPdRar6efHoNssHGY+rm\nPEfnr0cXmW59H3V8hFRXHD/yIMcrsM0NDFXJ+9exd3BAysKBrjk13sN999zFja94M0Pd59J6BPGp\nNGnHZjSSjezlDtZrcoShBHOB0KGwWMDFo2M2R8f0ecGdH/gAf/L+9yGpi1boieNxwzCs6VOPiFHY\nekoi4p15VWkt43PfUcqAqbDsesC7x/bLjuPNmjvueD133303Z8+e5dLRIXe89nbuvfdeLj56nkcf\nfZRXvPbVnH/0AhceftjFdYeR5SJRh4pIYrUZSMtuor1vhoG95dIFYpcL3vjGN3LrrWcj9OahuS6p\nawuaYjUMTjUk1yl3JCKUIWq2wsDmbNhQt1T61DHRvK2gOQMVNcNqZb05Roc166FQjw5JIpw5c4bD\nRx/idJ+wfIqVXeCm605RamX/1B5J4eCg8CVvvYOLxys+9ck/5iO/D3d95D18xdd8Fbp6iNWn3s+Z\nvURZLhhrpd/fA/V7sFgs0L09RCvLfsFqtWZ1ZNx516epsu+tS+SYvQ6ywqXDDaAMw8Cih/XRynOD\n+Zp4XGbMeMHgmvCgzp49a1/x5V/Fol+GRNEC63sODw/ZP7iRVFesNgOL5R5LO8bGh0kiJB1YH6/Y\nO3gJ601myKdIUhlWF+i0cv6BT3FcCgev/CwqC4biRaReECqu1FAKp7OGLFDGTCglUWVkqR6i8gLQ\nxGb0iYrOW1UkUTbVC2LHccOiW3oLCfXcFuq5LivFK5DMQnnBa5Gkesit0+QtIXYo2ovFAmDSFKx1\npM8Lqo1gGvR2QSRRx8LesnejN3oR8FAqm3Fk2fcUMxgLmhMjRq3GZhy57mAPyR3jULCyieaJTneX\n6s0ex3Fk0XVsyoZGDdGcOFqteeOb3sArXvVyz/GNzqYbDe+mS6UWlwb60Pt/j/PnL/IVX/Y2ROAP\n3/Vr3HfXx+i6Ja9//e2kccO7f/vf0stAqbBareg7Ie13/OlH/4Q3veE1IGu6PtEv97HNyKMPPcLr\nXvUaPveNt7O6dJFub591SBFZdWX5xaJns9lgBkMZWHQ9OXc8fO4S9z90nrF6MW4Sw8rIhaM1dXCD\nthoLpQwcHw+c2luy7DOrzcg//tGfmj2oGTOeIf6d8qAqyv6Z29iUDXUwHn3kEtffeIp+eZrjS4cc\nnT/Hrbeepe8Sdgx1XTi46aXce88nufnGG7jvnrsY6sDZl30eq2Ggl8KwfpT+4ICc9hjWIzll9g1W\n48DxEMoOVdDccWG18sLZJDBuO+6WvZ46wDBE2/MEQocdVRZ7Pvl1KdEvModlpI4bMgkxWPQdxZyB\nV0NpPOUlddiQs7LeFE7tJVZjBauUUj3UuFyi0nPx6CLDMJBF6aOl+Xq9jhogyP2CdGzQG1Yq5y9c\n8nxTVo7WGwb1ZnulFHoUusTRMHq7C5S9bsH6aI3JwFhHn8TXo7c+jxqm6xYLShlZlUIxIyUP9W02\nHn782Ec+yof/6EOhkeehxdwlTGCRF7zhdXegdsx9H34vb3rdG3jXO38KGdasLj5EXh2yODjgd3/z\n37iw7rjCchRCq5G7RBoqb3j5q0lD5XAYOT7cILKCceDc3fdyx4tuRUxZHpxitdogKmzGgYP9U1QT\nxs3A/nKPaiN540SIS5cOATh70/Usl0suXbhIUaXUzCmDIVVKgmQdp06dYrHwRdDRauTKj9OMGTOe\nTVwTBgoz3vve93L2RWc5e9MNnLlxoGphtVqz6HwyrJs1n77/fm655RZET/PIIxc5fXCW84+eY7Ho\nkOMN4+oROhLl8JDjMjJaZr83Vufu5extt3Hf3few6fc5uPEstRbGYPwtkrJILtoq3VbCaLU6BOsY\nx5GD5YLVxsNy680xorFOLSO2LkgtFKv0vTKOA7UkNsOGPnJaKQvj+hKn+56NDZRxYByS69sJrDaH\nrlS+WWG25mBvwSAZrYKZM/wGq2AdVitHlw7Zx+h1wXpVuLQ+5uDggOPjQjGQjRvl1LuUE1XJePHx\nQMXGkWrV+X7VG0BWE4YyMBJK8GMhq/fWynlB2azp+56chToa43pDUiGrXy9FOb5wyP5ywWq95g9/\n/w/Q1UNceuBTvPfieepwzCIVOlFIwur4iL0F1Dpy6mCP9TBEc0ewmthsBg7Pn+PGm2/i4594gLGs\n+dx/7w7OX3qQ7/iPv539vYVTwq0wFiNn5WB/z70/gz4rVF84lGGkSwqLjCSlmnJ04QL7p5zhuRkr\ny+UB586dpxgskrBcdNTNmo14D7GhbP58n5MZM15guCYMVC0b3vDqM6RuH1s/zP33fJzrbnsTpXY8\n8OgjvPTmG8A2vPQlt7JaF5Ia4+ohNuOaS+ePODjYBxWGC5/g+HjNDQdnOH/xmBe9+JU8eu5hTnWF\nT9/1Ee685yHe/KbP5v5PfpxbXvoyNGUoIyqZUhJHm0KhsBRhXUc090gqaO64eLzyRollzV7Xszo+\nJmdlb7FHqSOy2WC1MNaRdakcdB2n+kQtFdXMOFa6BBdXhyCV/cWCwYzNZoUWYa/LVIxSKr0qZXMR\nBXrd49FLx6Qk9MsF69UlNPdghbLoGNcrFOH0XmZYHbIurtZwarlAxmNq7TgcR/YXGamFDGwscTSO\n9HtL6mqNKSyWS4aNUaWSEyCG2ujED83U9QaVMnlxQ/HC4mXuXaKoDGzKyMGyR+oaQdFsDLbi8PAY\nGQr7C0Wzy0wdHR6h6nVreZE5Xq1ZrQZOnz6A1DOMa86df5iDU5k/O3c3Z266nqNHH+ZNr3klr/7K\nL0GLeR2TjCwWC1JVDi8dM3ZuXF1EuKPve8pQJ7WRThPH62OqJU6dWtL1idVmpOt7Ll1Ys0yJlDuO\nj1b0ZcPB6QX9XsfqcE3u5kLdGTOuJq4JA5WTgT1EqgOr4/t48YtPI/0jdMOLOHXjGR5+4H76rnLh\n0Ye4/voDhuOHyJ0wlEPGesjeqetYrY1xXHHd9ae4//4HufHFr+NTn/oUMlzk4dWal7/2/2fvvaNs\nS8/yzt+Xdjihct18+3buVkJCEggRjAATBcYg0gxmAGkQLJaRCQ6LmfGMx2MWZnmWARONgcFgbIKN\nkGBArEEkg1BsSS2ppe6+rQ43VdWtdMI+O3xp/vh21dWwbCQhq2lp6vmnwj1n33127f293/u+z/s8\n9/OCjdtZVBVrayu963uyqbDW03lPtXDoTOCjY1CUNF2DMQYpFIezGeurS0hAEcilJFMG27UczueY\nvCBGj2tahoMRAk/dOHKpicLTdA25lMl4kcTu62wiWSAC0SdNvhACrW0ZjUbsHczJ8waEp8hKFk1D\nqTM619JZh4geGwNZVuC6DqkEWhm6rmNh66Rg4ZIZo43gg6fMcmLbIQiEZs6ozJk3He1skpxu8cyn\nLcsrY3CWtmsQxuAslCYx22SWJ81Dl5QXpJQEHwgx0DYdo6I8njdT+ZiiHGKrXToMRua0bZuIC70y\n+fbWTUajJWSM2KZjMa+QeVKkUEXOGMNqofjab/4OMi3wrmHeVUiTMTBLHEwmibovJDIqrE8itcF1\ndCHNNvVexCil0Crr73zHfF4xHK3Qti3FQKBNwZWtfQaDAVJ02M4TQ2BUKsb9gO8JTnCCpwfPiACl\nVIZrItf3LrO2MqSu91lfAz+5QdBLGOUZjTeYTz3z6SG+a9Fa0zQeIUv29qcYowjWQcxoI4jpjOXx\nErg04jkAACAASURBVIuDCjUccnAw4dSFdUqTcW13F9l4jMmJSFSR4VzybxoXBiEyuq5FaIVzgag6\nVlbHLBY1gyyjs5bMaJyzuOBZXU1Oqz64JL/kOxoEdWPJlwp8aFEysmgbyuGAyXRCluUMyiIpGQQg\n00mVPTgEmu2DGUWW9XYYYGPKAubVjNxk5CRrdKRgOp+xNB7QLipyEym0wkeL0pGm6fDRM5+1FJkh\ntmmc1hKo2479g4amc5w6dYZ5u0fXCYqswHUt1juiBNNYgox0zmBty7JWWNeihcC5dH4qQOilzg/3\n9rEhMhgadOg4d+Y8bq4IYUHEMR4MqOYN7XSB9Y6llTWs9bRNg7WOebPgttNnqWZ7mCj4uq/8CtaW\nhlTVjIOqTsSW5WWmsxnX5rsUWclgpJIrsvcYpag7WB+PWDQdrfBkWUnEU88rlpdXqaoKHyNlOWYx\nb9CZZDweMTmcc/7Mam9lb2kU5HqAbRvciZr5CU7wtOIZEaDazuOCwegBmRnjRU6Mkf2DXRB7lOWQ\nxWFFNW0YLy8xnU65eOl2JrM5bWtZXc0JztN2jqqekmcDovNkw4Lh6XPsbu8gpebmzg5L5ZjlYkDr\nWvJSkRclIBmPDXXbID20zQKtkoxPkBHvOnSQkCl8aDFZgZO9iKuFpq3x3pJpiQ0RI0BLQ5EZgu3o\nbIeWmmFZ0HY1S8OcGARN05AbgZIB39YYndP5PhMSHSoEmtYyGBbMD3aQSjDIB0BHkWkWi4pyWGCi\n4HB3m7zQ7B8esDwYE2XANRajNULnyMLTuSbpFrYTIhEXFBAYDTLa+T6rKxnbVUXnO7QoGOYZrpkR\nBRRW0PqUhVWhxsdE2Z5VcwaDAZ1PskYtEiUEbdcmVYy2YtYcoKkZjQa0i5roPIeHB2ysrlFVFdEm\n8oJShs3NDarHH2Pn6mW+8HM/hzwGVscjDmcTYlCYPMcgqOuGRdWSZQPo/b4igXrRoYVkfXO1Zy4a\npLRIqZjPF2itaduW9fVVFk1HVTWJ9RegrdMgbpEnXT9r0yyY9x5lMsIzgPF6ghP8/wnPiAAlhUAh\n2N3bpigG3Ny6ybnzp8nK09SLA7a2b7K+ehp6SZpFO+fqU4+zsrLCrq2ZTPcxUjCvIq3tWNscszRI\nQ5nTvX3OnjnFpGpQJqmiW1snwoMxiSLeKzuEkJTJx4VEhBatoOkctV1QmEjTzTDFMt63VAdTNlfX\naINDqQwvfApiQmCMQSlQncf5BcaAdC22FRgTcK0nUxodK+zhIboc0lnBwgpGgyHIDoKlDWCEQvvA\n2jhn3i5ouwVds8DkJUJ6qsmEcjDGdjVNF7GtJdhAiJ5MCp511x08ef0mu5MDlFLMnOXsRsmibpE+\nwwvJdHLIs+++k8PJTbSKCF/T1Q2iUzhbMyiGEBzDsqSzkr3ZPoPBiN2eqk0USK04PDykMAalTdLf\nU1Bkiv1ZnejyLuJCJHaQZQVBJHeqyWyK0RobIo9+4FFe8Jy72LnxEKdXSk6trQOSzAxomgbnO5xN\n5pQry6PkJBwB4almc2LQqEyxv3+IMhq8IIRI07VkWpPnqS8VRAARcKGjyMfYrmE4ylF9plpZS103\nZFkaurYh0Hb+w9zJJzjBCf5b4iMOUCL5QrwduBZj/HIhxB3ArwBrwAPAN8UYOyFEDvwi8CJgD/j6\nGOMTf9mxQ3BU8wMyJdm+fo3h0jJNZ1nUh+SZoigGTCdzZtWC0WiEFBkiSvZ39xiPRxT5kK2bOyg9\nwMiMTBtybcE5xqOc/ckWS6Nldic3ackYjMaUoxKhkpq3pENLQ1NXBBdpRMA3HVlhCNGj3YQbl3fp\noqeqLJfufBZnN1eo5zOiihwe7rI6HqAkECSuc7RRMcgLog90zuJtwIcIVmIbi9eeTFhicFy99hTO\nScrxCrPQJckkLRBG0DUdQg6w1qOUwNuO4UjT1jVtCAhZ4OteYzDCaFiQZRntvGF1WHJ6pWBy4wCV\nWe79lOfx3ofeQzudMBwOUD4yr2vWlkq2bzyFbR2jpSV8r1s4rxa4END5CKMNe4cTykKTm4LJvMVH\nqGZTVpaWOTg4YHV5mbZtkQLWl8eY7hARPOfPnWV/50Ziy7UBZMPe/i7z2QBjDNZHloZDpjdvsr6y\nTNfN+bZXfhMGyc7efq/QAcE5JIKlwQCEY15VSCOZVYtkl+EFZWnIswwVJdrkNIuasixROkNJaOs5\nnohrA0bnjEaJOz4shgwygXctdWsZFjlyVTNfLJBotJB0IvzXb+JnwHN0ghN8suGjyaD+HvB+4KhT\n/EPAD8cYf0UI8dPAq4Cf6r8exBjvFkJ8Q/+6r//LDuxcB1IwHq1hvcC5lr3pnNnkgDwTlNmA5ZUx\nK6tLzKuKe571XN765rcyWhohFgu6ztE4jwgLhFJMDq+zs7Xg7OlTaA1lkXNwuMOptVM8+MjjLA3u\noJQS79pk4Y7DLSKHe/uMBiWDMkdqibOWrj7EtxXVooWyIB+WzKYHKCzDpSFt4zm3PsS2HdVsgvfJ\n3FCbAfuLOYeTlmKQMdA52TBjNl+ghUeiaToPIVLokoO2YuCT4O1iUZMVhvn+jNFomf3pgrqqMCqy\nvDym6xzOdwyLMZPDCWQwzCTeJkPCegLD4YjdyTb/+e3bbI4HZCPN5Uffw8bYYFtP18755q/6W+Sq\nwUhFVuZcvXqjV7wQIFKZqw1A1Hzw2hXe8eB1Jm1GtbDcef4cX/tVL+dNb3+Qra0dNs+usj9b8Hu/\n99qP7g7s8cLnPZtutsurvuZLOXtmiYOdfYyWDFVBoKX1gWKQMyhz2q5jOBz1fiM6qWfUDl0YApF5\n3dG0C4bDZAuiFETR4YJEF4MUKG3H4nCG1pqV5RErRUZVHRAiZKZkVjtc8AzKEZ3z4AVLg+yv9Nn+\nAj5uz9EJPjlR/dxH/trhqz5+5/HXgY8oQAkhLgAvB34A+F6RBOU+H/jv+5f8W+CfkB6sr+y/B/iP\nwI8LIUT8SyQrlNIMh2NWljMevvwoGEk1O2A8HqC1R4RA085YGg05fWqdBx94G8MyQwXB6vopDg/3\nUQiarkFEsNIf28NXVcNBO6frHOWg5ezZM0zaObVv0VHROI9RgjIv2FxfI3pQ0TOt9hgOcvJMUHtF\nkJ7CFFzbvsnmimNeTdl0m8xmM86cWmU23WVjbZX5rKXqIhjJzckUoUpsFBzMa8bBMR5qJvuHNFXk\n8HBKkQ9obYeNger6Ve6++27WN5aY1S2z2lLZA2SAtZUlpIwIYVBB0tjAYXOIyTVdt2A+q8hkhsoN\ni9bjtSSgqF2k2qsZDw3LgwJrW1rbsT+t+Q+vfR2rZeS+20/xnHvuZX0gsc7jhWR/fsiVaze4545L\nqFjzwttWePaZFxOlRGcDZtWC3/hPv8nOpKHIFaX2nF1dA+AVr/hqsmjZn87o5nNGo4LhYEDbdVzf\nusmi9mycXsN1lnZR89YH38sXvuTZ3HP757G+ZJjs3GBpmDLS+WyCNrA8GmKUQSrQg4Jr124gs5wQ\n6qT8IDrybMRi0fREE0XTNJR5ASHgbK/MHiUxKmwnkBgyo9EyIKQjzwqCkOweTkBJRuWA4AWuakkM\nc/lfu4U/Iny8n6MTnOCTDR9pBvUjwD8Exv3P68BhjNH1P18FzvffnweuAMQYnRBi0r9+90MPKIR4\nNfBqgLLM2bqxDUCIikJIrBoxn7WYTFDN55w6dYqt/ZZTm0NWV04xW9TY4Hj0scfRWlMODFk/p9J6\ngRCepm5p246lpRVWNkZc2d4GBEJJhuvrrI6XeWpnF6kNlW1pDycMihztd3HOko83mSwq9vYOyJTG\nL/a57/az5JnG+YjEMcgk88M9cqOo247pokGZnMODLegCOhcsFyNGy2ngNzOaG4sapSSF0dx/3x08\n8O4PgNTYYDiYO0rfcTCdsrK2CtFyZnWDvZ0Dpm3H1et7jAYqae/5nDh3aAldCMgsEruWYDuyTrFo\nAjcPG4rBkFEx5vKjjzMqJePxkNZ7Ll/b4/bbznJBLPPa/+ctXLrzbqaTfTqR857LTyFNwdvf+0Ge\nddcZYoyc2tjEusCT13eI1vKab38l//xHf4HP+vQXcGGzJBst8W/+HSg8gzBjZXmPw+XTVE3L7u42\nNkZOnx4yb2qMqChN5O47Vnjrg/Ci+y9iSgnOsrYyBB/oXEthICAwypDlhqtXnwKZI40m+kBelFjb\nMh4ts3dwgFZZosJLSTJcTkFFAdbZZLYoBEjBcFxQqMhyaWg7S+eh9R3FcEDnLF3rcc4xyHOUkSjv\n+Bjx3/w5+ovP0onYxSchXvnpH/lrX/XWj995/DXgwwYoIcSXAzsxxncIIV529Ov/wkvjR/Bvt34R\n488APwMwHg3iwra4ruPFn/483vWudwGKphWsLC0haGibQJbl2A6q2lJ3gdF4QObg7NmzHBwcUJQ5\n+7t7NF3NmbUNhuUI6xVlWXLtxha333aJ6fyQ5XLI7uGEvdazvryEjx1KgwyG8UCwu9XiIkynM1ZW\nVyiGA1xr6WyF9RXNgrTDHg0odGRYjrm5e0i1aKmbliBqtM54/j0X+NKXvZRf/PXXM60849GQbuG5\nePEC169eJcsVVx7/IJvLy1x+aotYlFy5scWlcxfACm5c3SZXlnp3i7EZcceZFbbzBfvzCTvbc86d\nv0RTVWQKVtcHdG0kSkkzO+SLP+1TWV8/xVvfd5nZ3HJqo2B1cJa2bTGmZO9gi0FeMJsumLWKNl/h\nvU/eSBkoNYMip8xzxmfv4rHdGS5GHtu5Qa6gto557fiHP/DjLC8v88Y/eRNGQ2c98L3YaUvQ+0xl\noC48T16/wTDPWF4a8MTlD/DVX/5FPOe+e7nywafYXF3h/3oddKElLsCIkBTSXUSgmM0mbG5uYtuG\ntZUxp86cxgaF6p1zb+7usrS0RNvWLI/H5GVJVc0RMqJILr/Od3iffMFiSISccpihYhoe1gJchHJg\n0J1kWs1xrWU8XCIOMxazOTpqBoX58E/U0/wc/cVnSQlxkmF9kuBWae8tH8W7Prm2KB9JBvVZwN8S\nQnwZUJBq5z8CrAghdL/7uwBc719/FbgIXBVCaGAZ2P/L/gPrOsajnMZa3v+Bd3Px9k1u7kyZNxaV\njdE+DZ/Ws4rd3X2ClNx5xwUKbTjc3eOpJx9HqpwL586zubnJ3vYOK6tDnOt48ae+kCtPXebs5hqL\nxYxmOqc6OGA8WmU6O2Q2m7C8OWZre5e1tRHVtMIUhul+hTGG6bUtjBJph77fsLm+xP5Bwyu+5uv5\n+Z/712SZ4u67zicTPi8p8jE39yuiqNgazHjjn78FozMuXrzEY088TqYDRgROn97kxs42i84yLDLW\n1gacXh/w7V/9xdR1RR0tv//mt4M3fPHf+Cyu3dghX1rhF371dzicN9igeeLh9/Opz72L59x1hrvu\nvJfXvvEPQQUunj/Fgw8/wsbmNhGDbfY52Nnj1Nk1nFvQNPuc2shRquTm3pyD6QGT2ZTJwYx/+UP/\nFCNA5oKmgW/7ru/hzG0XaeuaUmtErnFNQ4iRYjBgERzWegyR3KQFvCFybT5kt1nw/PvP8ZOv/1k2\n1lcxSmDrBc10wrvf9TYO5xWCJPDqF3N2DidcOLtGOVzhcLYLSIbLY6q2pq5rDiZTltfGOB8R/fBx\nEJJFNQPAKMW8miT1eJPU3GWAYpBRVwsyGTG5xPmWedWwvrRCn2AhTYToGRSC8XCDCFjX4lzHeH3E\nfFphPjbDwo/7c3SCE3yy4cMGqBjj9wPfD9Dv/P5+jPEbhRC/DnwNiYH0zcDr+re8vv/5z/t//4MP\nVzc3xrC9tcfZ82eYzyY89ugNlDIURcFkMiHEjrauWFs9xfasohgO8J3liavX0FqyurrO4WTGvDrE\n7Xec3TxN1c3ZWFkjE2modnlpwKOXL7OxscH29k32qynBR1rXsRxzGlezs1uxlGcQFVIN2durOX1q\nja6ZEdDJeVZJvIA3vfltbJw5y2Ix58bunGaxYFiWEB0q8wzHA7Z2d7HBsrY05OFH3sfFi5d44vGn\nuLR2nmk1oSxLtInkg5LM1+xtPUFb72GQHDQVjo6N1TEfePQRHnz0KWxQzOqGlfEKT1zZIQTHw09c\nx8jkmTQsJJ1XVLVj1tTMg0dGmRQtBmOeunbAV3zFy/n9N/wOWZYxXXTk4wHXdvaYTKYUWc4//xf/\ngpsHO5is5MbWIZPpgttuH/HGt7yD599/O1llmE72uXDhHLuHU5qm4+zGKWxTJft1YPvmHi60fPbL\nXs7myianz93FV33Fl3Dutks89eSTBKVpqoYX3neeF92buAJZrnnOfXexvrHM/sEEMSqYziqqhWeo\nFU5EpFE0vaVI27SIPEeVJdP9GUFIbFPhvWdpOOD06gaPPPIwFy9epG4qlldOMZ3uJ08or1kaF0wX\nlswI5ouWwWBE5xt2b+yS5yXWeobDkuBaBMmavuuaj/4JexqfoxOc4JMNH8sc1D8CfkUI8c+AdwJH\nCenPAb8khLhM2vF9w4c7UAiR9fUN2tZi9ADnBZNZw8Zaxvvee5nbbjvH8qohMGM8Kjlz5izWtpw7\nd47J/gH7BzPKvGBvbw/XdhRGsbS0RPCC933gA8znE86ePc/tly6xc/MmnbO4fqjTiwZPiREB7yzZ\nMGNvv2IylZTjyP7hDmvLQ4SMFKXA2ZZBPuBtb3kT49UVTC5p53Dtyh7rKzmbm0NWxgV50SGdANGy\nfWOPPBvx2GOP0bY1Tz1lue2OOxmOJCYfMBiOEdKTZ4on5vDkB68yr1sW85LHDxpirFnYZKh454X7\ncV5SZKvE4Ohcy/XDwNU/epDWeqLMUELjQ2Q+64jOgvTc3K/QWvNTP/1rdK5DG0lnA8YYvA1olTEV\nDTtbM+b1lPFIEGPJHXdcwjrD+vptnNq4gwfe/RayzLC1NUUIwT2XnkVWZCyNxmyujHnDG+GlL/oU\nrm1v8dVf+XK+4GWfQ5Twut/+bR556CGqzvLQQ49w/uwFJgc3OLjyfiAZIx7OF1zZ2uWP3/yfedmX\nvZwPbl1j+8YWF86cRRNAG25cu8ELnvs8rt24Rp4XzKqapbV11lfWmbY129e3+bRPfQFPXnmSrMh5\n93sepMwLlpdX0JnmbX/8Zzz3vmcRpaCzkSzTKAkfvPIU46WSyJgb2/sUpqBJQoSMBobWeW7e3P4Y\nHpeP/3N0ghN8suEZ4Qc1Hpbx/nvuYNHUeAfDpRE7N69yZnOFmzdrPJ7oF5w7f4qDA8FwWHJza5uN\n1SXy3DCp5rRty+n1DebzOac212i6lnZhOX36NNa2bG6s8573vZdT585xsD9jbzLD6BKdB+66e4Ot\n69fJhGJ1JWMysZhizM7OFqOlEcO8ZHNzk9tuO8+ZM+fJzIjxaI2d3X32Dw/Y2dlhZ3ePGzdu0DQ1\na2trBK+oqoqiGGBMjnOOKDQuJnv0GBUipnmjI2O9GBPz0AuBtR2eSHQ+DRCTFA0kHDvxHtm3i3jL\nIkRpQdtYbrt0gXvuuhMjPTiLVIZyNGT/YELdJn06naUy2IVzZ9nbO6AohxxMDhmUOUbnvPBFL+Ad\n73grbeepase4LKnm+3zmZ38mjzzyKG3bkhlNXhQsLy/zyEPv5z++7tf4vu98Nf/g+/4+JhsyXh6x\n9/D7+Y5X/h2qco3/9Yd+lD9789tQmWFtnPO/fNer2Gojf/Bz/xueltlsho9ATBYjmTaYvEAayWI2\npyw0ShlkhMViwWh5hI3QVgtCcPggsW0HMiafKp8U0m1juXTpEoumQymV1OW9xznQuWZpkFNPJiwt\nrzNvWgpTYIPHBUsIjiLPmc/nfP63/NMTP6gTPC047kG98iNfo4fiE6MH9QnlByWkpPWBKBTVYo9y\noDm1OWJvbw8RC0al4cLtd3LliQNWVk7RLiqUlgzLAmTk4rlNJpMJQkTKPCMTmvHaEve85D5WVseU\nwwEXz1/gG/7ON5CZIdZ63v/Qwzx59UkeeOd7efzhfYp8mQ7DzZugVI6rJEV5ibaWxFBycLnhiaeu\nEdhCKoF3AW1UL+5qiULQNAVRjLk5c2ghiGLIYm4Rog8yoSYgiN7hrQeSoGpUEiEjsfd2V0iCT8O3\nxIgkmSZG7wkKtNb4nlF2z513cO7MqaQKLgNRg69r6vk1vvil9/Nbv/NGdLFOG+H63i5RpzmfcqTw\n1tF2LTt7W3gnETYpJ0ynU5Q0/Nmf/RmZVjTVgqHJWDQV5XDEW976Ttq2RkTJaLTEfD7l2c9+No8/\ncQWAwzncuHaINAc0T1hecP99/Obb38m1p3ZYWMtXvPxvUlUV08N9fvCnfpZvfSWwfI6Dm0/iZcn7\n3vMessxw5vR5pFiQmRm2qbl44QwiRnANSmuWxwUyRoyIjJYy5vPAeLTEomsYlCMyIxnmBW1IJImu\ndZS5R0nJ1aeusLaxhpEGu6jYnQFIZovrKAkTn3yyqllFlhm8h6rvdZ3gBCd4evCMCFCRwHiguH7j\nBloHtq9d5uy5U7zkRS/k8z73S+g6x2CsKYsVXOex1vLu9zzAu9/9PmzjeOqJmwQM43GGNCvcmFjE\nbMEHrz+AMTkhRgaDEXW1SAEipsAQpMCTky/flnTWOkvrPQhFlmUsKkfXWvxsAVJS5oHWO7Tu7d77\nTCaEZIsOIKXHtR5Hm1S+QwB6uwchcSImO3UJIiabdCGAKCAGohB4EUFJXLBIqfG2RQu4cP40ly5e\nSErgUiZFdgkei/SCrpvz2c8/y5VrEx515/itP3wXttwgCE1Tt8mvSmg0ST09CtBasrK0wvb2dlL6\n1ppBmcqJs2mdfh4MkVJSREdVzfju7/5ufvzHfxytBnQhDRv//hv/lCOdhaWVNaz0tIuaB9/1AHff\neYkH/+RdfOCRJ3jyynXquqVtW7oQsTaRJH7nTY9xdnODpprz5OEIESLXpzNGg4KlQcHm+mlauUme\naUTsUrA0Gbt7+1jrCDiMhr35DYp8gM6HxM5jY8v0cJ9r165x6dIlVlZWaLqOc7ddwHcdg+GArhXM\nZjOi1GR58tfSuUEBMUjKosC5jtXVEzXzE5zg6cQzI0BFzdZOi8nPo7VG6paqy3jn+/Z44L3/Hik0\njbcopUCkWSeda3wXyfSAbO12nHPUCIQHZUokycW2dRGd5Sw6h40K1y7w3nM4nZJlGVmW0WhFnufJ\n1bZpcCGidVIrlyQSBzIpZQsf6FyTbDdUOpcYUgBSSiFdIABeBgghSeT4gIjgCfgYiVKTyMAxWb2n\nbwFF1zbkSnHnpbOcO3sKh6DMTLLO6FUeUmYc8DHQ+UDp9/i7/8MX8dP/7vW88Z0aJ0oyqQgqA9fR\ndi1egFEaESWIgJASFdNM0NbWIS9+wafwrvd8IBn7ScWoyAlZTuta5rNZUn1Xmjwb8jM/87OUxZi2\nbbGdQ2vNfffeziOXHwFgZ/cmn/k3Po8v+KIv5NXf9irWz9/O6upp7rrrPiSRt739TZw7fzvz6pDZ\n9AD4MS4/fJnd7TTi08UhXYDF3HOzqhkV8PC1GeI9W9x22wUunLvIwW7HBx9/fyqjloY808ToE/1c\nzTh3WrC8NOCOu86jV0/xvEsvpllM2ZnvEyxkOufshdt47LHHWMzrtMmwC9ZPj3ASjM4xxrCyuklu\nND60xN7C/gQnOMHTg2dEgHI+gBn2ZSuJlxkemRZZD1IbiixLQacvx2plsFLgrWV/exelDMFHpErW\n4zEkz6XRaIRc1Ljgb/VuAozKIYhkuhc6S+uSYKyIASMUETCil/2Jgug91qWymlIK6z1ICYhkN9Fn\nS1Iqgk8SOxGBJRCEQsS+jxQ84EBCjALXeaSMnFlf49677iREi9GgiOS5JkqFEL2dOpHGSzLhqF2N\nrad8+1fewx/96ZP84M/9CQ0XkAoybRBK9q69YH3o3ZAEIThi1McZn5LgfeBt73oQEeF5z3seDz30\nEMJGdFagM4POkh+UtZa6z8Ryo8myjOGwRBDYunoV3VeUv+1bv4nQNSAVr3vt6/nqv/0K2rZlZ/sm\nHsE999yLwJBpw/mz53jo/dA4x+FsyuFkwvLyMqAQQoIUVHWLyTOEEDz6+BU+cPmJZFgYHUqWdC7H\ne1CZJDjP5uY6p2+7H+c6Xv+GN3H9ylXGowE600gFwUZMprA2ZYilMVw4f5az587gBmtoATNvEcGz\nf9gSQ5PchM3HpiRxghP81fCSv+4T+GvDMyJAQeqrRNP3WqTAdh2zakrXOaTUaC0Z5AUhQGs9xaAk\n+oiWgmE5SDbtLhBImUaUHm0MIVoEGhEFgoCSEndUkusDFpC+hkggBa30u/T7EB0m0yiV7NuD82gl\nETHi+0X5iLRgYwTS8T0x+QqF0FfwIl3ToKXk1MYm9957N5mKydpDQp7nxJj15AeNUukrQIiCYB3e\ndyzslGetbvP5X/R8fvg/XYbsIo6I0RqpBfTn7ZwjxrSoeh96GnjEu0iUySBRSEHUEu+T8vc73vF+\njOooioLWJukopQxSaooiS4OvIeKto6pS5qEzgxagdA7Ay77wZcDLPqq/v8DQdVAWS3QWMq1BgOwz\n5nrR4pxLChEkwkiWZTgk3rfJWNJD8Ior1/d4/MofpoxXCMhGNGgKUSKFwCtP23RIOeL2u+7h/rvv\nYTKZ8Ht/9Kfs7u5QljlZUZJlut/sOMyRRuEJTnCCpw3PCBafNllcWk3lvYSAVgq8I0pFDIJhnqGV\noLUdShp8DFgv0aSgdFTewYXEipMBGWXybCIt9D46tEpeUzZ48IHkFpiYcULJJIXjQUiFDw5rLcYY\ntFS955AgBo+PiaId5IcEOR+OS4Hee7RUWGsJBHKT8Zxn3cN4WFAoAyKVBPPcYKTAOYfQJpUKEanU\nKSVRClzwuNqysBXDOOOH/u6n87//2K+z6+6gFUsQM4xKgf0o2wJobLI+99YRYzwuSRpjiFiUzpAi\nQkyKCzE4QpTk2vGrv/ZvecUrvpYQy5RZCtEHy1RalELjnaPzAe9TH0ooiVEaKcFkCtnLSilBi30M\nNgAAIABJREFUsspwDiEE1qe5Iu/SZkIrhTKS6CFEiXMtzqXe3ZFskdTJkPCop3d0rzjnjq+3Ugot\nk14fpGrwIDNIrfvj9YE7eEL/tyVqlI4YIXHRYkzev1n0mXXL6c11XvjCF7K8POYbv/lbTlh8JzjB\nx4iPlMX3jAhQWVbEU6duTwsdR+bcpIW2L50ZlRY8HwPWJgKCzkqidyBVypSCQMaQVK6BKORx30ZL\nRWsbMlMm+nC/Gxc9MUEphYREWojiODOy1qK1xoh+5x7SQudiCjBR8CFMPmjrBiUEuVLccek27r3z\nDtp2hpFHPlEKIWLqa5EkdiD0vkNHRAvdl+IizoVkYREsL7tvyl0XCn7mDxzzekCOwPdZi+rLT0dl\nTIlg0aZjHAUopDh+jZbqOKAomXpozkcCIhFBouPihU2apmNyuOjJHKI/v5TxJmq7Sbp5ISbxV9vd\nOgeZjq+NRKmeBq8U0VustXS+J4kQiFGwMiq4sX2d5bV1lEhZsY+p7BtFchD2NqmM/0VIKdM5RZGE\ngvEE1yC1xgfHwcEeL33pS/gfv+2VzGcLfuEXfpHHH3+cEGBpOEIaDT1pxbkUhKNPKhk+JnNKHwJv\neMNvngSoE5zgY8QnWIAq4+bpO5LlOYEY6Rd52S+MCi0VToIPNi2wfcAIAhTquMQWEEgiIvb07X6x\nFDERFWKvVdV5h1Ep24lK9f0niM6D8EShEf3/7627ldHE5N7auQ4QtNYie4m0TBvuu/8uLm5uYFtL\nnmcoEQkioHWG1mkRjS7N5kSZ/l/T09WPCBA+BlxnCa6hxTOyW/yr730R/+Qn/4Cri7uonEGoRLTQ\nOgU2pXWiqsdI9Cl4VosuZRyhZxqKDyF2xIjq+3VKHWnMCVxwdMGjQ7KZFz1LMddHmZnsS50erSUy\nSoIApEAisF0qLaa5L44/V8qCBDLSX8uU4UiZ+kbWWnxwDIucpq74xV/6eSaHM771ld/B6vopZtWc\nMh+gpCHg8a5DSol1pGBiUybto0eKdD21SffNLQuRlMEdlf7aZkaWZezv7/IZL/10vv3V38Xdd9/J\na77re3j8iaspI0MQpYD+2v7m6371JECd4AQfIz6hApQxRVw7dQkROQ4KhIDu54RA4n0qvxx9JCFE\nH4r6sloMKYgFSwwBQXLITaWgeDzg6o/6SiEQnE07/Sw7DlBCSbx1CJWyN0I4pkK3bYuNqb9UFjmi\n6/jSL/oC2qrCCEkUAXSGkjFlckqidfb/oaNrLY+DxNFCf/Q3EP3CWrcLmi6wLB2v+hLFPWdzvuNH\ndoiyIEgFoiDIiO6zkhiTEzBREmIy9ZNSUs1bokj9mkA8LpEdDfVKma4J8tZCHqPHR/A2EUJCOCKP\np1LecFAkO4sgkCYFeCl1oqxLdTxgG0IgxL78FtI5+OjQQiKDwpNKsUoptOmzOpUdl+66tsK2TQp+\noiNXgp/4iZ/k6rUb/IN/9D9TDsZIkmCsDwEtDRF/zPJ0Ls2ZeZsCpXMfokQujkq/PgXdfsCZaJAy\nAhLXWTpnIUSQMZVCfeD3/vD/PglQJzjBx4hPqACVF4O4cfp2tMzw3hKIEAJGJKsFoRQEdxysIJUB\nE7U7Q6jk9ZOUFkSaNQqCGANKCEK/gxYuLc5BQOfsccnwaFGMMR73Rnyw1F2Ds74nLCiyTLM8Kvm0\nT/0UbNcie8sNpRRSZEgFLqZs66iXYa09fq9z6bXOdZRlSQgQo0eI1ONpFhPqEMHmLLUP8qP/02fw\nA//6DTxw5V6y0QoxJiVuSFlLdpQhSsHy8jJCCA4m+0QfMCYpH8Sg+nknfbxIJ3v70M+DpQX5VvlO\nHgeYI6JFmudyaJ3x8//mX/HLv/zL/P4f/HF/rBwIRCnIhcKFFKidc5RFQRqTcqnd5yPWu+TLFCJB\nkjYFRxmWvPW90oJMq+N7pG1bXPDI/ry6EPpgpFP/S9wqjwol0UgILvUBRewz33hcRk7KHSmTcr7r\nyRC3enhKSqQy6U6TEfrr+Lu/++snAeoEJ/gY8QmlJBFjRBpN8B6pJd5aBKl0EwJkSuFFWprzPE89\nGa0gCEymkwkdSa0BkQTnpZS0bYfKc6IQhBhRWhJDysqOgpK34bjsU7VNCnCAioJSaUZrQz7zM16C\n62pCdBA82BoVQRmFUiWKSJSQZRk6ZH0fIy3sxpjj0l2el8cL4FEAiFHQdf18jS9Q9VW+/+s2GC3f\ny7f+4APsdc8mN0mfUGlB5yKagDQa21PntdQc7M/S+cm+vOk8qboXiCEel7ViTP0v51xPi5dA6AOE\nPB5iPiplHiH0meQ3fsurU0CNAqM1zjUpKKBx0eH7rFebFKgCiS0ppUDInu4uEuEE7/Gksl/XdR8S\nZFKQbKVEqETq0DrDKDA6vVc1ga5riER8jGnqzXtkpvHW0XmbGJs6Hn9OpSRCpIBW5gUhOpz3ZELj\nbJoNO7oXOmuRNiBkxMdkgBjFCc38BCd4OvGMCFBSSsqyxFqLCBEVQWpN11mMkQgpkf0iU7cdxmR0\nITHqpJQ9k8sRgkdHiVYpM1J5jiMN0kop00ImBUqA7xyddxAFTb0g0zlLxYhBDs+6+3aKIiOKdG62\nmUHfByMqpE5stpTBpcUXZJq16k3ypFQURUFdJ9uOEI609lLPJ4SOaB0OQUdETFqK6n380v9xnp//\nI/jtP58zm49YGa0QRIcXJC8jKdKQrVLEKG9lBsFDzzA0UuGJx4SOo6xT9jNPbdselxWdc0itCMEj\nQ8rwBGC0RElwPpXKUvBKGY8USZapsx4pFZnWtLbB+4DJh8gYiC7gXJ0MBGXqKUYBuc6wrSMrDNEr\n2q7vOap07MTIBKLDhbSBsF3KMrMso46WoswAR1mWKCMRUbJo5hirsT71KEWUaYZOhkQtdx3pChmE\njHRdRIkIUSBE7/UUHD61qjBSEqwAEZDREIIjhBOa+QlO8HTiGRGgjkpJIQREmnolHw2QtUMrQV3X\nxyWq0dKYruvITQZAnptkoXFzD6U6YoSiKOi6LgWkvt9irT0usXXBo7McJUrWl4fcce4Mq8tL1Isp\nxiS5n7puiTH1RehJCDEEpE6ZRq4VLgZCSCyzo+xDKtlLBkmc69A6w/uA1oYsy2jbNrH+WtvPWEmY\nX+cnv+c8g+JeXvNj+zyxt8AKxWh8Gmc7VHZr9kcrBTLivEfA8eeL0SGEQvVBW5scIepjAdo0J+aO\nGX5CiJTdQF8iS6lnClwOISQxOpQWfSYl+kArjmefjjKspmnS/JiQYC2ZupVpeO9TBqN1T1zoZZoE\nIDVF7vE+EkPfOyJA8DibMifXdQThIATq2h5vSDIjAEtrU29NkuFEx2g0AlJGdpSlBtvhCMQgkKKB\noPoA38+reYm1lkxLWp9KyUoItEnkm0xn+CD4L5AHT3CCE3wc8YwIUJAWxtFoRD2vUEJSzyt8lBhd\nsrG6Russh4eHx6WqzqbFarGwNE1zvIgGIagXLRGHDf54dsl7T5mn6vyZlXU+93M+m4OtD/LffePX\n8Ju/8bu0zpNrRRSGEJJ2XyRlGFmWguF4vETdtfjO9v0LKMtkjGhM3hMGJB/a18uyrFcvj33m4nEu\nzVDNqkPuUDv8s+/b5Lf+9M38xjvuYKcZ4KNnZWmd2tZkpSEKifAeYzRaKQIeISS+P7e08Ets5yjK\npJxubZoLcz7RuGU/n6W15qj0Kz9ElzDRwkVfyvMfUvLTKKmJ8qgHmOC9P854iKKfNXLonu3nvU9D\nwCFitCR4D1LQ2YYiH9LZhthnY1ondmAMgjxXNE2Tsp7+ehJTGVLIdO2kTHNNUoFAITOBFkkFvus6\nlBKE0CXaeZDowRJN0ySyhA3Hw9cShfeOXAqEloQQj9mg0UWsCygj6WxLKoP+1R11T3CCE3z0eMYE\nKBHANm1PBY8YpQltBzJwWE2JQpIXg55Rlxr7mdL9gtriYxIe9d5TliUxKqRI8zO5iDz3Oc/l1MYq\ni3mFxHHzxhMopfjl//BraDRBSFAZzrZ9tpZ24MPhsO+PCOouOaxKEei8oCzzftHPjlUmIAXbXKk0\nOEtk3jSpVOhd6pfFmqKa8FPfeYHCSL7z/3yExxfnCUGwOl6iFl3KvqQhREfoMz/6PpuUEKMlkQFT\n4AgepBC40CFkoG09znVAEpUlpGsWAqkkGeIxIzJG3/fF6DMnCEH0mU5P2daa+CG2HlpJ3LH9hz7O\nzJz3tF3H0niIbevUS7I9McN5pFYs6nkKgCIFS53UcnHC4rvUZ3IxvSeRGWJiAgafyrfeEWKkrjvy\nPMd2HVongoQPt4ggR9mbIaAkSW5KCvJBEsP1/b3jVEQ4R+sDKkKZRWJW4dR6YvIBvpc+OsEJTvD0\n4ZkRoCK4zlIUBYTEfIuRpMNWVX1/ytF1vp/1CUQR2T/YRWuNMobOWXKTkRuD7TpkcLzg+c9DCSiy\npATRNoukWBCSYgRSEoNG5jmhs+R5Tp6nXfJRFtA0yYLCWo+zAaUVWiiiP1qsQ58VpY+SKY3QaQcf\nQji2xXDOoYl07Ywz8f38wHffxVPXtvnHv17T2DuZH+6xsbF0PJQMR3R4gZAQRT/BFemb/rovXXYo\nZW5R1aNAKo1z7fExBLf8owIRGQTWu+Nh2yNJp+OvIiCjAAdCphmlPDfHZIMjNQe4RY0H0bMRExNy\na2uL1aWSoiiw8YjNaAhHeoveE0hagIGjQWJ63cMA0SOVQspE6CBKpIrIKBEikSuyLGkhxuhwLiKE\nJUQFJIq7Erqfd/LHYrsAfrFIrwlQliVllqOEZNHUOOdooye0Cu9u0fTTcPUJSeIEJ3g68YwIUJG0\ncFazeWJo5VlPA+/nZ3yFt4kVt3Ady8vLVLMFUSh8FNB5Cq2597bzbGysJVWJXoInUbwzYnCkzEug\ndJZmW1AolUpTSdkhlX/aziGAwmQM8l7nTziKMiNGj5ECrSNKKtpesTzGQFlkNC7irEXGQNvVKdC5\nmCjl7RY/8ZpNyuI8f++HH+VG8xw6p5hMDllfX0dKRd12KCHwURzPFgkpU8aDTIkQktAHFFBEL4gh\nKV6EAMZonKsJRLRK3lFHfSd8wEuLFGnmq7UWLSXe+ePgo5RIZdEAIvo0G+Z7rUEfiAg6nwKU7Oe7\nUglMQ0zB5uz6mF977b+Hes6Xf9U3UIxPEX1yqHWu18iTvdqU9MQgIaSAKEXq4YXgcT5ghMQbcM4Q\nRUALjRQB6SUhCiBlmokk0qtnhIAXt3qQQQiE9xAlytxiKEYhmTcpmPtgEVIgpWGQLdF1HV3fkyII\nnD1RMz/BCZ5OfEQBSgixAvws8FzSKv9K4GHgV4HbgSeAr4sxHojUqPhR4MuABfAtMcYH/rLjh17p\nwMe0aHR1ndQB+sXPWts3rhNtez6doQSsDAa8+MUvxtZzjIiY0tC0LcJ5RJYsFUJIRIYj6nna8TuC\nDQgteyuNVH6q67onOKQBUC369wrJqMjJjaRxEUj0cO8jmdIUeY6PjtXVFZ64upUWbJ9IC9Z2RBrO\nx/fyj19znpkTvOYH9tj3d+NCx2RyyOrmabyPfX8ElNFE12GMJtKTGSKIGECkDE/IQPCpjyIIhBjT\nucaI9f0sTzzKRkOaN9Xq+Jp67xPbTiaRXXGcRUW8ByFulfOQgkjv4BsFII69n0IMx3/HGD0qSjyR\nxmr+9ld+I7455Ld+6zeYThb/b3tnHmtZdpX339r7THd49w01dFV1t40NxgkYAY0FlghDwDadEEEI\nECAgHBPhiEgQDIncBJGEiIQhyBEGDEHCYCexMQSBrYjBFoiQgME0StoDtqFpOlRX9eCqN93pTHvv\n/LH2Oe+VsbHb5e73qut80tO7dereeufsevuss9b61vfxrd/27TQtJEYDhA/x35dUZ6PwSkSxFuf0\nYaKTQQpe///FKIXeGLAktFEXyx2j0mugFeiDZzy/qH/YlETaucW1OkNljEGwEMC1gTIomcUgpHmK\nNSllefMsvqd6Lw0Y8EzCx5pB/RjwGyGErxGRDBgD/wr4rRDCD4nIfcB9wKuAvwM8L359HvBTfDS9\neAFnhXJVxgZ/w3g8Jcm0rJSZDBNaZkXGS77ki1jO5+A9vq1x1a422a2qIGRpSpLleCNkqShRoG0x\nARrfDc2OqOsagLatCaLMv07hwfuWJE3wte/7UKuqpoxZBj6QpjaqWfi+BHb16qOxf+NxicXWDc7v\n87pX3olb38HP/MoTvOMvR2xxlaz2PD4v2D57Dt+0UZOPI3v4YAk+UfFaTXyQYDASFR60HocXwTuP\niQy8AFSrErzqBRIVJIRA6xokGMRYnUsKQoJSzEWE4LVn1ZEBlH1nVZlDVOIwSLzhB12HRAQf1Rd8\nCOgtHVwI+EYw6Rm+4qu+ie/+jlfw5jf+LK9+zWv5X79/vypO+AYfS3ZdabNxokK+3fCwWNoQoqwS\nYC2lcwiC2CNSgzVpPw/XwYeAiO2HoaGJw9wW73ROTH/9Sg1sNo2CwRL7cVZ7Ty1441Vt4ubx1O6l\nAQOeQfioShIiMgMeAJ4bjr1ZRD4AfHEI4VERuQj8Tgjh+SLyn+PrN33o+z7SzxhPZuH8nZ/CYrWk\nLEsSY1ksFmzNNsizhC9/yUvY371GXa2Uadc2OGvxBPI8780C8UH7Ma0jJIAPZFmi/Q8JJNm4L1WF\nY7YYSZZG6ZtIADAeTKK5SbyL1U4FXTsdQGu1r7Oq6v49Rz2aFr9asuHfzWu+65OpTcN3/NCSJ+Qc\nVekovaetF+xMz+G8qoTXPiBxFih4z2ikQTSJ9GzicGti4/xSE9Uh4vyTMQGbSFy7FT4cySt1Mj3B\nJggtrZMblCN6zTxaxCQ9e06C6QVmQ1DiSjdMK2JvUIMgqjIEjpQoJK6vMYbMBAwVv/yWX6JeLfiH\n3/CPMSajbqKjcLfWJomq6dojc7XDiSEzQotg4tC1Cy0m/jx8UFFGjnqHzjkwWlp1QanrPd0+svXS\nSIc3ousk1vTkDedCVAjRfhdoRvm2t73141aSeDr20qAkMeBWwCdSSeK5wAeBnxORzwT+GPjnwB3d\nRokb63x8/53A5WOffyQe+4ibqmpqrh8cYBCmecoL/ubf4O47L7A42CfPMnYfvUqSos6yaULIUkY2\nMNk4w2JxqGoN8ebiYioyyXXmKB+PdM7KN6pKgSXLk6harmyv6XRKkiQc7u0DKleUZRllWce+U0DW\nK2zMItrgacqGxncDrCGW4Rx1uULCkp/5FzskVcH/fu8BP/1rU9bhTqp1yaJuya1QZFsENEN04pUh\n5xw2SWi9p4rMwV5yyLdkidpkhKBmia2P0k6R3dZUDSbP1efKH5EivAtKSHANkXuC9w6PZhfQOc4b\nBO2peS94iSK7IkjU8TOJxQYNEupcr/NTNsmV4m08BLBGtJyX6JDrqvGIZHz1V38zi4PH+M1ffwsk\nOV/zVf+IdLLJfD5HrMWFQGLjQ0jT9MogTUgjdV3PtyM8hCgOG8wREaRTTffokHGSJDgnOmAcAmlc\nV+c8xsCqbFSKqqoiG7OKQUoHsHutQ26axfeU76UBA55J+FhoSQlwD/BTIYTPBpZoCeIj4cNFxb+S\nponIK0TkfhG5H+/41Gdf4qVf9EK+8PM+na1pymL/OhmGpqw0KCUGb7UfkyQJP/bjP8zh4T7Wara1\nWCyYz+es6zXOOearNfN1iRPD3sE+ZVnr8KZzHOzts1qtqNuGxWLBBz/4Qa5cucKyLjlcL6nrmuVy\nSQiBsixpmoYiTyE4vOigqJeYRWAIQZC2JTeeM+ED/Py35yCP8q9fd8Brf/0uFj7D+Yatc2cYJRnF\neEI2ntBQQ+owoSFPosNuqyQFH1p8aPu+idASaPqAGHB6PihDTSREod2oUSgxI+y07jxYk5KK6vgF\nIxir/aUuWPcKDLE3JEHJATbKAx3vX/XzQvFY3TY3zEl12WT396oob1iWgWR0B1/9dd8CxvL6n3st\nn/+5L0CoydOE4FrKakXtA7VT25MQ1KvKdtka4NvQn5sRzXDgKHB1r490BA1WlJVhrb1B2inJtKSZ\n2EzNHL301+lcoxlx6yJV/6bwlO+lk1fWHDDgE4ePpcR3AfiDEMInxT9/AbqpPoVPUFlie2srvPRL\nX8yqLEnTHLFGLSOCJ43ucy6a+CVJtMhwFTYdRdkg9YCSRICEplqq622W9pp7TdOAF7a3t6nXC7Xp\niJ890qSLMDokOskKGu9i2UhlmKrIQAuClrhCjWstE67xH7/7IhvV+3hicYZX/XTFghmhbqmCsLt/\nwObWDBP06b71MRDgEekync6K4niZrOuldGU5Pc+2qTAdHR1Hno1om4ambZVFaNMb9Pe667IhEhxC\n25cNuzmnDt6rMrwy4wBRcoW1FoxEm48j2/hjvyt9BnPDz/VB9YOiMYlm9p6iMHz+Cz+Nf/l99+FX\nFd/9nd/DI4/vEkRYLbUvpJlRR6awPT3DRVV2KwltqOLaZRjR3pL+HD0XFzX0EmN6ZXpxIdpzaDBv\nvaNxDumysKCsxCaOCQRR48Xf//233UyJ7ynfS0OJb8CtgI+1xPdRM6gQwmPAZRF5fjz0pcCfAG8F\nXhaPvQx4S3z9VuCbRfEi4OCv21Adjt9MDcK0GJGPCtrINBNjaKJ7qvceGyVzQlQg996zXmj2ZCVR\n4dZ4E1V1b8t4nOFchbcWjKWNfYlO1NUYQ1EUJEnSkyZSY496F+F4aSkowSIELro/4rWvzEmX7+TH\n33zIK3/Ks+v0hl8FYW9vn+3ZNjb2Z5pOSTuKDYUgEAzbZ7ZuyDj62SZRAz4VxPW9ZJD3IM6TJWnv\n/Asc9a3iuoKa/UmAsq1xoYk09dAb/XXXJAFIrPaWsJHGTU9B7+nZx8/t2IByH1glmku6VkV/nSpF\n1HWNDxCwVJXwO3/wbv7el389f3H5EX7oB7+PX/rvr6ctD8mLJEpJdWvhaNo1TRw4O57BgQqbe9/S\nuLZz3NDr9l7NL+nU79VWxcWHAis3ZlydqWSeRyNIa3vLlo/2MPfR8HTtpQEDnin4mOw2ROSzUGps\nBjwEvBzd878IPAv4S+BrQwi7kRr7E8C9KDX25SGE+/+6f39neyf87S/4YtIowio2Bh6rMj42UoJ9\nvKGq/E3Det1gTUrrSvJc2W95PsIEjxePR/XnxkUeh1qj+nckF6RpGuV+9KYrXv+uk5KrnO/16/Jc\neyzihdJV1C2ckQP+3T+7i21/Pz49x8t/4GEO5ZP0id9ZvMAjV69y6dIlCDErEmW7WVpCpIybYPBA\nagNOkv58gN6EUOV+iMw9dPmjjFDbltpbSUcsV6UGGfFKlBAIvo69Iv15QaIPlDuSLwohHHkpETBe\nPZBCzGCP6/eFEHQ+K372OOHCG4EYDDuCRVcS7Kzj67aJ7rc6UBuA1AgbE+HNv/AGwqrk3e9/iO//\n9z+CTXJWZU3dVv01W2uxWNrQou7DmoVq6TM6C4OumREaV2PSBOOOCB61dySowaUE7YPmadLb0vuo\nYN7EeS9VwRB+7/feflN2G0/1XhoyqAG3Am4pP6id7Z1w74u/TINRIlSNiyoHsamdplgs4/GY+Xyu\nGYSVqJNX9HMsdV1jTEJqhDa0iE2ixbhmUB7p3WW7PoTqxxmyrKBcrsjznLKJbq1NQ5KlVNUxVYbg\nwcFk/S5+4r5ng/tL3v6uDf7bb+TstQaY4pw+9T/88MM85znP0Rt4DDAdsUJE5XsADHou93zOC/g/\n73ovwd1YduwyE1A5Iy/Rit6kiASKPGe5PKAopiyWa80KxFM3LjIijnpGWZpStUquIOggc38eXX9L\n1LBQbdrtDVmRTZPed6uTd+qyKGttH9wSY5U9F6HsOf15bbPWcp0ocQHUxcRYyLNAbhre+MY3UJcV\n3/iN30rtNaMp64amU/A4pqihJIiG2WzGcrnWdW5VSUJFbP9qhodRxqNHlSuOZ67ee4z12o+SI6He\nNrS88x2/PfhBDRhwk7ilAtR0Ogv33PMiRtMJWZbhakddrQHHxQvnWSwWuLphNBr1ZTiA1tWq2eeh\n8zTqyzgi6orLUXkqiJBa29O31RAvlt2ahiLNqKo1lTtWysPhXcWqrpilBVT7/OC3nuHM5L14X/Bd\nP/oQf9F8BgTN0pxXeaaD+ZqzZ3e0pxSg8dobyWwspxmJVhaK42W5Lih3N0s4Kk+54PVp3oKRpFdu\nx1Wk+Yh12WqgRq/fEwiuhXB0o25dIEvy3qjPRYo1UX+P4Kid9qE6yw2TpL1+n/Eg6ZEckzGGJJZC\nvRFCDGDHy38iUcLISN/z6T4baKLSuAaPNE1B1nznt72Ml37Jl1C5wD/42m9CKCh9C/4oYHYBVEt8\nWu70Xn2orAeHMjitTUFSEgGPwzudKwuiIrCtW6vnUzxf56NqROho+Kpk8ru/+/H3oJ4ODAFqwK2A\nT1gP6umBqgAc7u0zzgvKcsVsNiXLE1arFcbAeDyOMyrSU5vUB6rpb3TQmdslag3Rul51OzG2b5IH\np+Ok3U2uc5otm1p7XM7h2laDU+uiHxGki/fxmu8oOJO8h1K2+Kev9vxF/VmQZIgxlFXFuqpYlSVn\nz53T8pMzOkcjtidAdLZCXeDsMjkbMxh13W2P7NQjsQKOSm3d9XY2InmeU7cNzjV9gD7OuOuGT8GQ\nWIvz2ocCSFITyQc39r60z6Ylr+7f6VyI++DjtW/lmo7p5vvsqlvf4/0iK4a6bfqf0dmshNAJwmoA\nbVrh1a95Pf/2P/ww6Tjjf/zqm/jVX/4vHOzvkWXJMYZgS9vWR6Ky0d7eOdfLFKVpDK6u7Xt43XuD\n96pbGEwsi6rFSPeA4IL+jrnGK3NwwIABTxtORQY1Hk/CubMXuXTn3azXa6qqIktTJpMJANPplK1p\nQZYKIilFUVCWJeBJUvDOYOPQbtXqjaooiv5mdDwbMcaQWQ0Mav0wZllW1HVJVowIzpPgKEkQL1Dv\nkyY13/91woU7LiPrwL/5pYQ/efgcSbpFIxVV2SBJSr0uOVzWzDbHGNQi3DtIRZ/k1SapbqYCAAAQ\nXUlEQVSiprM2F0nx6OyTNvMt2n7SXo8Yg5g47Bpp4E0MCP0QbJqpgnuRKCU+mvt1duYdEzAANhgV\nyHWaHXg0OxCOAomWt2KvKvbCNNDYPrNzztFGh+OEo5KbqjFEBp1o3yZJEpWqR0kX0MkvBTCCMbFc\nmWTK9ovzTLgakyihoSgKXvWqb+PBP38fT1xf8D9/+x2sVzWz2RaHh/uq5GEyxBoa3/TB26Q6w+ab\nFhUAcXgX+uHk1FtCog8HeZLTBs2sy7Imi5lZVa/Js5EOSWcpb/udXxsyqAEDbhK3VIlvtrkZXvCZ\n97A8WJGmKaOioHUOawKLxYIsy7jrzoskBlKb6ABunpOn0ZwvG+Pqqn/id9Fcr2Oo6SyL7zOYEG+c\nzjlWlUoedQQAgyhzrW3wxjJuHuQnX3mONFxl6XK+5yccf364TWFzZYxlhioO7TZlRTGdRtkeVSPw\nQciM9o0skTYtHbuss7RQV1wkxYqWvJrWY5KUxGrQ8JHeLlbZjBZhPB732UhqE+q6pqkDLt6kuyzG\nxt6b9tuSKBgLNs213xStRYj0cJNogGqao95bt17B6Tq2Rnt7SZyj6tTdrdio3UccWrqxlwbRxben\n0reI8RBSxAeaSF4JbdWPG7Rti01i0Ik0+S4DSrMEguBqF2fTQn++YpP4+ZrUdmVbQxrLunmSMZ5M\nGOVjvDccHh4ymUwIHtq60gzXNYzHBVWlc17/9dfeOASoAQNuEp9IJYmnHL5xFHUgm05i+UrYmW6q\n4sKFi1q2sYEsK0hwpJJjEqFtG4SEqpxz5uwmy+WSLMtog48WGU3U4QtYBCuBqlwhWFarVdSqM/3N\nFyOUZUWSWerFLq9+xUUuba9pDz7A/Y+P+YE3pYib4hOn9u4iLNdrqqphMtnAIri2QtDB3NZrJtGG\nOEZqDCFYDOqjFAIkdoQRtZcIVOAMm2Mhm0yoW8edl86TpinjLCWxGUlqSMT0Ja1RXui1NJWWBBOr\nJa1gevfetlGzviTNMGmCFe15lXWt17xaMxqNSLq+UTR4TLOE4KMBoxc1R0QDYhu0NzWZbfTU/2vX\n99i7fsgTTzzBqlwzmUxom0BpdZbMGj2njhKfBCFPEpzzWlZVLxFMcLQSaOqaPC3Ud6tuCGi51rUN\naa5eXE3TIBhSK3gfyLOcxWJBmmZ88sXzTEcJTb3CBsd6VVJkozjTZFgtKyQLeDfHh5Q7tgrAEbzg\nYgAtRlPaxrO1cYb1en2i+2TAgNsNpyJAZUnGXWeeRes0m8EEtcgIgZQcLx4xllQswdXkUVIgydV/\naHfvGtceuaoU8qIgMQaxButasiShtfrEXdc1aZKzWJfYJMXEG2sIgca1WCx1s2InPMZPfu8nI9U7\nEJPxvT97mQcO/pY+nUtQirNof2vv2h7T6ZTQlAhgMUBDEiy+XuPrNZ/5ws/m3Jmz+LZSCZ+6unGA\nOGgZUmKWU/n6iNjBEmqhWbZUAvl0zHq9JjXKanzioARgcbAgBGF2ZpN16Xp1cu9bZjP1mVouD1lc\nXwDaq5tOpxpcWse8XpGhDsFVzMqW87afAwohUFUWa5VQEkQzoXL+OKloeTER4e6dMXfv3M25c+do\nfEMIwrqsub57wNbWFqAD0lmWUbtaA5Ut9AHBatCvqoqmdqp9aDSDXCwWWJOyjpnNbDJlPp9jLMxm\nM4Jz+LZFotNy0zRRQSJhaVtyqw8uIThm07EyQPOM5XKJt4GigHJ1iHOOnZ2zXNvdZTwa49yC+f4e\ndbkB9pS0bAcMuE1wKkp853bOhq998VfEkpRaKXjvqeolZbnSrAqriglxGNVKwKQJIkpd7ijP+WiM\nD4FxkuGtkGaZ9kVCQGzam/Tt7u73SgyrqmSSF0w2ZyRhxWdcfD+L3X0an7JKPoelm9KGjNy0NFUk\nDQT1lwou9Fbq3ntC7anruu9n+NZh43yNkgeUlFG3Dkki1Trozf5wsSS3lqLIIn1eVPQWsA1UbUNd\nqyI3QefBklGqrL2gQ6a1axmPx1SrKpInUkJUxphNphpIYtkzBFWSKBt9MEjEIDaldTWz2Uz9t1Yr\nmqahKbU3uLNzljzP2Tw7o8hyrl27xrXdPVKbcHh4SJZlffkOYGNjk7quCW1DJ9YRnJZUndFyYd06\niqJgVS77zxVZHoPIiM6+xFrt69V1TVVVsdeo/b4qGjT6NhypXJgQvboCrq6QTAPSZKJs0FGqa7du\nHMvlHCsZ0+lYiSbeqBagBdMRPoLhP735F4cS34ABN4lbqsSXZymHh48yLkba0M4daZKRiSMfqxr5\ndDqmKArNNERoUWv3+fyA0WjUM9s6C4U0U7HY4PVpXxvxDfNFRZbkjBIdghUxbOQTqqpicf1RsnTC\nHx4+C8yzydOMtq0IsmY0nrJsWqqqir2cjLat2d3dxznHxniCYCgyPZf5csXe3h7jcYExho3ZlOA1\nUG5sbLIu57RNw7Vr1zi3s63n74Qky0EsVd1w9uxZ1us1e3t72MSQZwWf9Jy7qOua+cGCsixJTcpk\nNmKxWLFcrimKgsO9Q+0HmZTlouL5n/48Ll++wt7hXMtzyxXee3Kba1DPcrIs4/LVKyyXS9I0o65c\n38cSMYyKDdJkhJEEkyZcefgqjz32GOPpTBmGmWVUbOCbliTNmc/npJkwn88JGJqqjuutpcL5fM7m\nbMyVK48zmU6xJuX5n/JpvPOd79RzdDU7OzvgNbjOFyuK8Yjlcs409o3yPGfv2nWe2N0jz3OmG2OK\nfAzQsyCXXpVFjBFM6zULW9a0zuE3NvDe4oMnywrauqGtatIipw0em01o6pLFes1sutmrWAwYMODp\nwanIoM7v7ISvu/fF8ck3qhBIgCB9qS/QIiRRVVot4q1VfwqR2OiJZbdgLFmas1ovj+SOPNjE9KWz\nru+UZwU+6OfSNGVdqqJ1U68ZJZmSNiZTluUSnOfgYA5A7VpGWU5i02PeUl3vq+pp8bu7u0zHG9Rt\nRVtrCSsrRuzu7vb2HaM8Y71ekxUa3MZj7Ssp6cAwmUxIspSyrHn/nz6odG0v5HlOoOX8hTtomkqz\niWg3sb+/j3fCxYsX1KXWJDQu6NCxr6M9SZTxicOotWt6Np+LpIckSchz7esAbG5uUpZrHn/8cWaz\nWU/JXi60P6Mlsh22Z5sEI5y/cIH5/JAHH3yQxWKBQdjb2+PcHefJxIJVn6cQAvkk1fcYQ5LmXLp0\niYceeojDw0O8h8nGlK3ZBnVV4WpVo1gu1oQENqZTVqsFNv6fFUWBR3RMoKkIvqVpfU+5V13HJMpm\nZdRlRVmu2JhOCaBivXFMrRMonk03+NGff/2QQQ0YcJO4pTIodXwNqg9HIHjH5uYm29s7GGO4cuUK\n63VNCBXnzp3lcP8Q8QFXN5SupihGJMHy+O41JqMxs80N6rru9dTEWNpWLSxSK4gVqrohzQyPX3uU\nsztnKMsVz7rzU1mv16yqkkVoqcoKm2Y88MADeIQL586zv3egQ75pSuUqdhf7VE3NdDqNM1Uem1kO\n9g6j8eKYw8NDEE9qUpz3LOeH5GlCYlX9Ih2PCEVB3dbx5jnDt3OVXUqFvf3rJGnK9et7POuuSxwe\nLCjynLwocARsporuZbnP3Xc9m+VqzvbmjLKsefjhh2ldzcbGBhsbE9I0xwUdUE4SQ5paDuaHrJYl\nWSq9Fp3FEIJBfGBxcAhAEi1M1osl48zSrBdIllHWTW/LUUwmGmzGIyS1tI3n8uVHeP7zPhWxhoO9\nfcbjMU1wXP/gdeqyJEs8YqAsl2SJZn6urbjy/x4iscLO9ibeQ9WUPHHtcba2dkhHBdW65uyFsySJ\n4X3v/1MSk5IXNZcuXeL67j4bm1NWqyWJVU3B8Xis5UaBUTFC8NR1iErvMNuY4L06G7dxnsxYNWwM\nzvdCswMGDHh6cEoyqO3wDffei/OeJD1SnO6M85QBlqq6dmgp8hGuVquMJLWkRU5qLOs6EEJFkY/w\neCSy3UQshJayqmjqmjNnz2IsZEatxM9fvMDly5dZHCy0D9YeZVRJklBWOgiapRpgrLXUVcX29jZV\n2fTswccee4yLFy9SVRWjPD8SWA2BYjzhcH8PmyZqp9GG6MSbM54UzA+XJFlKWzckmSXPNBNYrQ8g\nJKRpxmK5JMnHlOWKIp/im5amXjGZTDCxtLher1X01LQYSciygqapSNIR1nhWqxUu6Nrmqap113VL\nno3wpmZSbJClui7FeMKVRx5Ver7Vz1hrWS8XlPU6ZntT6rolTfI4Q6UqGWmaUmxscuHcBWYbE6r1\nmr2DAxaH814hPDGW5XyfbGwxqN8VeHxw1HXNJB+zbqM317JiPMlwAazJWS72qeqW2WyL+XwOJpZ+\nKw3yF+68xLpu2Lt2nSRJOHPmDC60LJdLru/uU2Q5i+UhVdmQZQXnz5/l4HCPLC0Yj8dsbW0x25yy\nv3vAfLFQRQ6b8NNvfNOQQQ0YcJO4peagRGQOfOCkz+OU4Cxw7aRP4hTgtK7Ds0MI5076JD4Shr3U\n47T+/pwETuNafEz76FSU+IAPnOan0qcTInL/sBbDOtwEhr3E8PtzHLfyWgyDHQMGDBgw4FRiCFAD\nBgwYMOBU4rQEqJ856RM4RRjWQjGsw8eHYd0Uwzoc4ZZdi1NBkhgwYMCAAQM+FKclgxowYMCAAQNu\nwIkHKBG5V0Q+ICIPish9J30+TzVE5GERebeI/F8RuT8e2xGRt4vIn8Xv2/G4iMhr4tq8S0TuOdmz\nvzmIyOtE5AkRec+xY0/62kXkZfH9fyYiLzuJazltuN32Edy+e+m22kfH3U6f7i/AAn8OPBfIgAeA\nTzvJc3oarvlh4OyHHPsR4L74+j7gh+Prvwv8OiDAi4A/POnzv8lr/0LgHuA9H++1AzvAQ/H7dny9\nfdLXdsLretvto3jdt+Veup320UlnUJ8LPBhCeCiEUAO/AHzlCZ/TSeArgdfH168H/v6x428Iij8A\ntkTk4kmc4CcCIYTfBXY/5PCTvfYvA94eQtgNIewBbwfuferP/lRj2EdHeMbvpdtpH510gLoTuHzs\nz4/EY89kBOBtIvLHIvKKeOyOEMKjAPH7+Xj8dlifJ3vtt8OaPFncrmsy7KUjPCP30UkrSXw4LaZn\nOq3w80MIV0XkPPB2EXn/X/Pe23F9Onyka7+d1+Qj4XZdk2EvfXTc0vvopDOoR4C7j/35LuDqCZ3L\n04IQwtX4/QngV9DyzONduSF+fyK+/XZYnyd77bfDmjxZ3JZrMuylG/CM3EcnHaD+CHieiDxHRDLg\n64G3nvA5PWUQkYmIbHSvgZcC70GvuWPRvAx4S3z9VuCbIxPnRcBBl8Y/g/Bkr/03gZeKyHZkKr00\nHrudcVvtIxj20ofBM3MfnTRLA2WZ/CnKQvrekz6fp/han4syrB4A3ttdL3AG+C3gz+L3nXhcgJ+M\na/Nu4IUnfQ03ef1vAh4FGvQJ7p98PNcOfAvwYPx6+Ulf12n4up32Ubze23Yv3U77aFCSGDBgwIAB\npxInXeIbMGDAgAEDPiyGADVgwIABA04lhgA1YMCAAQNOJYYANWDAgAEDTiWGADVgwIABA04lhgA1\nYMCAAQNOJYYANWDAgAEDTiWGADVgwIABA04l/j/pYiQaM6j67gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1add205710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    " \n",
    "for image in glob.glob('test_images/*.jpg'):\n",
    "    print(image)\n",
    "    img = mpimg.imread(image)\n",
    "\n",
    "    ystart = int(img.shape[0]*0.4)\n",
    "    ystop = int(img.shape[0]*0.9)\n",
    "    scale = 1.5\n",
    "\n",
    "    print(ystart, ystop)\n",
    "\n",
    "    out_img, bbox_list = find_cars(img, ystart, ystop, scale, svc, X_scaler, orient, pix_per_cell, cell_per_block, spatial_size, hist_bins)\n",
    "#     plt.imshow(out_img)\n",
    "#     plt.show()\n",
    "    heat = np.zeros_like(img[:,:,0]).astype(np.float)\n",
    "\n",
    "    # Add heat to each box in box list\n",
    "    heat = add_heat(heat,bbox_list)\n",
    "\n",
    "    # Apply threshold to help remove false positives\n",
    "    heat = apply_threshold(heat,2)\n",
    "\n",
    "    # Visualize the heatmap when displaying    \n",
    "    heatmap = np.clip(heat, 0, 255)\n",
    "\n",
    "    # Find final boxes from heatmap using label function\n",
    "    labels = label(heatmap)\n",
    "    draw_img = draw_labeled_bboxes(np.copy(img), labels)\n",
    "    \n",
    "    mpimg.imsave('output_images/'+image.split('/')[-1], draw_img)\n",
    "#     cv2.imwrite('output_images/'+image.split('/')[-1], draw_img)\n",
    "\n",
    "\n",
    "    fig = plt.figure()\n",
    "    plt.subplot(121)\n",
    "    plt.imshow(draw_img)\n",
    "    plt.title('Car Positions')\n",
    "    plt.subplot(122)\n",
    "    plt.imshow(heatmap, cmap='hot')\n",
    "    plt.title('Heat Map')\n",
    "    fig.tight_layout()\n",
    "    plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def process_image(img):\n",
    "    ystart = int(img.shape[0]*0.4)\n",
    "    ystop = int(img.shape[0]*0.9)\n",
    "    scale = 1.5\n",
    "\n",
    "    print(ystart, ystop)\n",
    "\n",
    "    out_img, bbox_list = find_cars(img, ystart, ystop, scale, svc, X_scaler, orient, pix_per_cell, cell_per_block, spatial_size, hist_bins)\n",
    "#     plt.imshow(out_img)\n",
    "#     plt.show()\n",
    "    heat = np.zeros_like(img[:,:,0]).astype(np.float)\n",
    "\n",
    "    # Add heat to each box in box list\n",
    "    heat = add_heat(heat,bbox_list)\n",
    "\n",
    "    # Apply threshold to help remove false positives\n",
    "    heat = apply_threshold(heat,2)\n",
    "\n",
    "    # Visualize the heatmap when displaying    \n",
    "    heatmap = np.clip(heat, 0, 255)\n",
    "\n",
    "    # Find final boxes from heatmap using label function\n",
    "    labels = label(heatmap)\n",
    "    draw_img = draw_labeled_bboxes(np.copy(img), labels)\n",
    "    \n",
    "    return draw_img"
   ]
  },
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   ],
   "source": [
    "from moviepy.editor import VideoFileClip\n",
    "from IPython.display import HTML\n",
    "\n",
    "white_output = 'output_videos/project_video.mp4'\n",
    "## To speed up the testing process you may want to try your pipeline on a shorter subclip of the video\n",
    "## To do so add .subclip(start_second,end_second) to the end of the line below\n",
    "## Where start_second and end_second are integer values representing the start and end of the subclip\n",
    "## You may also uncomment the following line for a subclip of the first 5 seconds\n",
    "clip1 = VideoFileClip(\"project_video.mp4\")#.subclip(0,3)\n",
    "\n",
    "#clip1 = VideoFileClip(\"test_videos/solidWhiteRight.mp4\")\n",
    "white_clip = clip1.fl_image(process_image)\n",
    "\n",
    "#NOTE: this function expects color images!!\n",
    "%time white_clip.write_videofile(white_output, audio=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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