samples/sun/Preprocess_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/envs/MaskRCNN/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n",
      "/anaconda3/envs/MaskRCNN/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import SUNRGBD\n",
    "import random as rand\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import json\n",
    "import os\n",
    "import shutil\n",
    "import sys\n",
    "import h5py\n",
    "import scipy.io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_to_sun = \"/scratch/datasets/SUNRGBD/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "store = []\n",
    "for f in os.listdir(path_to_sun):\n",
    "    if not f.startswith('.'):\n",
    "        store.append(f)\n",
    "        \n",
    "b = []\n",
    "for i in range(len(store)):\n",
    "    for f in os.listdir(path_to_sun + store[i]):\n",
    "        if not f.startswith('.'):\n",
    "            b.append(path_to_sun + store[i] + \"/\" + f + \"/\")\n",
    "store = []\n",
    "\n",
    "c = []\n",
    "for i in range(len(b)):\n",
    "    if b[i] != (path_to_sun + \"xtion/sun3ddata/\"):\n",
    "        for f in os.listdir(b[i]):\n",
    "            if not f.startswith('.'):\n",
    "                store.append(b[i]  + f + \"/\")\n",
    "    else:\n",
    "        for f in os.listdir(b[i]):\n",
    "            if not f.startswith('.'):\n",
    "                c.append(b[i]  + f + \"/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(c)):\n",
    "    for f in os.listdir(c[i]):\n",
    "        if not f.startswith('.'):\n",
    "            for r in os.listdir(c[i]  + f + \"/\"):\n",
    "                if not r.startswith('.'):\n",
    "                    store.append(c[i]  + f + \"/\" + r + \"/\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1449"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#just excluded\n",
    "#'/Users/ekaterina/Desktop/diploma/mask_rcnn/datasets/SUNRGBD/kv2/kinect2data/000667_2014-06-09_21-06-12_260595134347_rgbf000145-resize/'\n",
    "#checking that we collected all the pictures\n",
    "len(store)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The standdard trainval-test split uses the first 5050 images for testing and the rest for trainval.\n",
    "if not os.path.exists((path_to_sun + \"test\") or (path_to_sun + \"train\")):\n",
    "    os.makedirs(path_to_sun + \"test\")\n",
    "    os.makedirs(path_to_sun + \"train\")\n",
    "if not os.path.exists((path_to_sun + \"train\" + \"/train\") or (path_to_sun + \"train\"+ \"/val\")):\n",
    "    os.makedirs(path_to_sun + \"train\" + \"/train\")\n",
    "    os.makedirs(path_to_sun + \"train\"+ \"/val\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Work with a class mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import scipy.io\n",
    "\n",
    "mat = scipy.io.loadmat('classMapping40.mat')\n",
    "\n",
    "label_13 = [1,2,3,4,5,6,7,8,9,10,11,12,13]\n",
    "name_13 = [\"bed\", \"books\", \"ceiling\", \n",
    "                 \"chair\", \"floor\", \"furniture\", \n",
    "                 \"objects\", \"picture\", \"sofa\", \n",
    "                 \"table\", \"tv\", \"wall\", \"window\"]\n",
    "\n",
    "labels_13 = pd.DataFrame({\n",
    "     'label_13': label_13,\n",
    "     'name_13': name_13})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_40 = []\n",
    "for i in range(0, len(mat[\"className\"][0])):\n",
    "    list_of_40.append(mat[\"className\"][0][i][0]) \n",
    "    \n",
    "label_of_40 = list(range(1,41))\n",
    "merging = [12,5,6,1,4,9,10,12,13,6,8,6,13,10,6,13,6,7,7,5,7,3,2,6,11,7,7,7,7,7,7,6,7,7,7,7,7,7,6,7]\n",
    "\n",
    "labels_40 = pd.DataFrame({\n",
    "     'Label_40': label_of_40,\n",
    "     'Name_40': list_of_40,\n",
    "     \"label_13\": merging})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "allClassName_894 = []\n",
    "for i in range(0, len(mat[\"allClassName\"][0])):\n",
    "    allClassName_894.append(mat[\"allClassName\"][0][i][0])\n",
    "\n",
    "mapClass_894 = []\n",
    "for i in range(0, len(mat[\"mapClass\"][0])):\n",
    "    mapClass_894.append(mat[\"mapClass\"][0][i])\n",
    "    \n",
    "labels_894 = pd.DataFrame({\n",
    "     'Label_40': list(mapClass_894),\n",
    "     'Name_894': list(allClassName_894)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('name_mapping_from_toolbox')\n",
    "df = df.drop(['Unnamed: 0'], axis=1)\n",
    "df = pd.merge(df, labels_40, left_on=\"Label_37\", right_on=\"Label_40\").drop([ 'Label_37', 'Name_37'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Label_40 Name_894\n",
      "0        40     book\n"
     ]
    }
   ],
   "source": [
    "print(labels_894.loc[labels_894['Name_894'] == 'book'])\n",
    "df3 = pd.merge(labels_894, labels_40)\n",
    "final_dataset = pd.merge(df3, labels_13)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_needed = {}\n",
    "#Converting data to work with 13 classes\n",
    "for i in range(0, len(df)):\n",
    "    labels_needed[str(df.iloc[i]['Name_6585'])] = df.iloc[i]['label_13']\n",
    "    \n",
    "# Adding data for the dun from matlab file\n",
    "#Converting data to work with 13 classes\n",
    "for i in range(0, len(final_dataset)):\n",
    "    labels_needed[str(final_dataset.iloc[i]['Name_894'])] = final_dataset.iloc[i]['label_13']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Start the parsing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_labels = []\n",
    "for key in labels_needed.keys():\n",
    "    all_labels.append(key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import stringdist\n",
    "\n",
    "ufo = {}\n",
    "def transformation(image_root, number_of_image):\n",
    "    # Set the paths\n",
    "    image_root = image_root\n",
    "    path_to_image = image_root + \"image/\" + (os.listdir(image_root + \"/image/\")[0])\n",
    "    anotation = image_root + 'annotation2Dfinal'\n",
    "    \n",
    "    with open(anotation + \"/index.json\") as data_file:\n",
    "        data = json.load(data_file)\n",
    "    \n",
    "    numberOfAnot = len(data[\"frames\"][0][\"polygon\"])\n",
    "    element = {}\n",
    "\n",
    "    size =  os.path.getsize(path_to_image)\n",
    "    filename = os.listdir(image_root + \"/image\")\n",
    "    filename = filename[0]\n",
    "\n",
    "    element = {\"fileref\": '', \"size\": size, \n",
    "        \"filename\": str(number_of_image) + \".jpg\", 'base64_img_data': '', 'file_attributes': {}, 'regions': {}}\n",
    "    \n",
    "    anootation2D = []\n",
    "    labels2D = []\n",
    "    regions = {}\n",
    "    \n",
    "    for i in range(0, numberOfAnot):\n",
    "        x = data[\"frames\"][0][\"polygon\"][i][\"x\"]\n",
    "        y = data[\"frames\"][0][\"polygon\"][i][\"y\"]\n",
    "        idxObj = data[\"frames\"][0][\"polygon\"][i][\"object\"]\n",
    "        if idxObj <= len(data['objects']):\n",
    "            label = data['objects'][idxObj][\"name\"].lower()\n",
    "            label = ''.join(i for i in label if not i.isdigit())\n",
    "            if label in labels_needed:\n",
    "                label = labels_needed[label]\n",
    "            else:\n",
    "                leve = {}\n",
    "                for i in range(0,len(all_labels)):\n",
    "                    leve[all_labels[i]] = stringdist.levenshtein(label, all_labels[i])\n",
    "                label = labels_needed[min(leve, key=leve.get)]\n",
    "                ufo[min(leve, key=leve.get)] = label\n",
    "            if type(x) == list and type(y) == list:\n",
    "                all_points_x = list(map(round, x))\n",
    "                all_points_y = list(map(round, y))\n",
    "                if len(all_points_y) != 0 and len(all_points_x) != 0:\n",
    "                    shape_attributes = {'name':'polygon',\"all_points_x\":x,\"all_points_y\":y}\n",
    "                    region = {'shape_attributes': {'name': 'polygon',\n",
    "                    'all_points_x': x, 'all_points_y': y}, 'region_attributes': {\"class\": int(label)}}  \n",
    "                    element['regions'][str(i)] = region\n",
    "    return element"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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    }
   ],
   "source": [
    "# For the NYU dataset\n",
    "# 80% of train images - 1160 pics (0, 1160)\n",
    "   # 10% test - 145 pics (1160,1305)\n",
    "   # 10: validation - 144 pics (1305, 1449)\n",
    "# 20% of test images - 289\n",
    "\n",
    "# 5050 test images store[0 : 5049]\n",
    "# 5285 train-val images [5050 : 10334]\n",
    "   # 4226 train images [5050:9275]\n",
    "   # 1056 validation images [9276: 10333]\n",
    "d = {}\n",
    "fail = []\n",
    "# Working with a test dataset - 5050 images\n",
    "for i in range(0, 1160):\n",
    "    try:\n",
    "        element2 = {}\n",
    "        number_of_image = i\n",
    "        print(number_of_image)\n",
    "        element2 = transformation(store[i], number_of_image)\n",
    "    #except json.decoder.JSONDecodeError:\n",
    "    except ValueError:\n",
    "        print(\"Fuckup with \" + store[i])\n",
    "        fail.append(store[i])\n",
    "    #print(element2)\n",
    "    if element2:\n",
    "        file_name = os.listdir(store[i] + \"/image\")[0]\n",
    "        file_to_copy = store[i] + \"image/\" + file_name\n",
    "        target_dir = path_to_sun + \"train/train/\"\n",
    "        shutil.copyfile(file_to_copy, target_dir + str(i) + \".jpg\")\n",
    "        d[str(i) + \".jpg\" + str(os.path.getsize(file_to_copy))] = element2\n",
    "\n",
    "jsonname2 =  path_to_sun + \"train/train/\" + \"via_region_data.json\"\n",
    "with open(jsonname2, 'w') as fp:\n",
    "        json.dump(d, fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pictures failed:0\n",
      "Pictures parsed:1160\n"
     ]
    }
   ],
   "source": [
    "print(\"Pictures failed:\" + str(len(fail)))\n",
    "print(\"Pictures parsed:\" + str(len(d)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'air conditioner': 7,\n",
       " 'air duct': 7,\n",
       " 'air vent': 7,\n",
       " 'aluminium foil': 7,\n",
       " 'american flag': 7,\n",
       " 'baby gate': 7,\n",
       " 'back scrubber': 7,\n",
       " 'baking dish': 7,\n",
       " 'banana peel': 7,\n",
       " 'basketball hoop': 7,\n",
       " 'bedding package': 7,\n",
       " 'bicycle helmet': 7,\n",
       " 'binder': 7,\n",
       " 'book': 7,\n",
       " 'book holder': 7,\n",
       " 'bottle of comet': 7,\n",
       " 'bottle of liquid': 7,\n",
       " 'bottle of listerine': 7,\n",
       " 'bottle of perfume': 7,\n",
       " 'bottle of soap': 7,\n",
       " 'bread': 7,\n",
       " 'business cards': 7,\n",
       " 'cable modem': 7,\n",
       " 'cables': 7,\n",
       " 'can of food': 7,\n",
       " 'can opener': 7,\n",
       " 'cap stand': 7,\n",
       " 'cardboard sheet': 7,\n",
       " 'cardboard tube': 7,\n",
       " 'carton': 7,\n",
       " 'casserole dish': 7,\n",
       " 'cat cage': 6,\n",
       " 'cat house': 7,\n",
       " 'cd disc': 7,\n",
       " 'cell phone': 7,\n",
       " 'cell phone charger': 7,\n",
       " 'chair': 4,\n",
       " 'charger and wire': 7,\n",
       " 'chart roll': 7,\n",
       " 'chart stand': 6,\n",
       " 'child carrier': 7,\n",
       " 'cleaning wipes': 7,\n",
       " 'clothing detergent': 7,\n",
       " 'clothing dryer': 6,\n",
       " 'clothing hamper': 6,\n",
       " 'clothing iron': 7,\n",
       " 'clothing washer': 6,\n",
       " 'coat hanger': 7,\n",
       " 'coffee grinder': 7,\n",
       " 'coffee machine': 7,\n",
       " 'coins': 7,\n",
       " 'console controller': 7,\n",
       " 'console system': 7,\n",
       " 'contact lens solution bottle': 7,\n",
       " 'container of skin cream': 7,\n",
       " 'cooking pan': 7,\n",
       " 'cooking pot cover': 7,\n",
       " 'cordless phone': 7,\n",
       " 'crayon': 7,\n",
       " 'cream': 7,\n",
       " 'cream tube': 7,\n",
       " 'crock pot': 7,\n",
       " 'curtain rod': 7,\n",
       " 'cutting board': 7,\n",
       " 'decanter': 7,\n",
       " 'decoration item': 7,\n",
       " 'decorative bowl': 7,\n",
       " 'decorative dish': 7,\n",
       " 'decorative egg': 7,\n",
       " 'decorative item': 7,\n",
       " 'decorative plate': 7,\n",
       " 'decorative platter': 7,\n",
       " 'deoderant': 7,\n",
       " 'dish brush': 7,\n",
       " 'dish cover': 7,\n",
       " 'dish rack': 7,\n",
       " 'dish scrubber': 7,\n",
       " 'dishes': 7,\n",
       " 'display case': 6,\n",
       " 'display platter': 7,\n",
       " 'dog bowl': 7,\n",
       " 'dog cage': 6,\n",
       " 'doll house': 6,\n",
       " 'dollar bill': 7,\n",
       " 'door  window  reflection': 7,\n",
       " 'door facing trimreflection': 7,\n",
       " 'door way': 7,\n",
       " 'door way arch': 7,\n",
       " 'drawer': 6,\n",
       " 'drawer knob': 7,\n",
       " 'drum': 7,\n",
       " 'drying rack': 6,\n",
       " 'drying stand': 6,\n",
       " 'dvd': 7,\n",
       " 'dvd player': 7,\n",
       " 'educational display': 6,\n",
       " 'electric mixer': 7,\n",
       " 'electric toothbrush base': 7,\n",
       " 'electrical outlet': 7,\n",
       " 'ethernet jack': 7,\n",
       " 'excercise ball': 7,\n",
       " 'excercise equipment': 6,\n",
       " 'excercise machine': 6,\n",
       " 'exit sign': 7,\n",
       " 'face wash cream': 7,\n",
       " 'fax machine': 7,\n",
       " 'fiberglass case': 7,\n",
       " 'file container': 7,\n",
       " 'file holder': 7,\n",
       " 'file pad': 7,\n",
       " 'filing shelves': 6,\n",
       " 'fire alarm': 7,\n",
       " 'fireplace': 7,\n",
       " 'fish tank': 7,\n",
       " 'flask set': 7,\n",
       " 'floor_mats': 5,\n",
       " 'flower': 7,\n",
       " 'flower basket': 7,\n",
       " 'flower pot': 7,\n",
       " 'food processor': 7,\n",
       " 'food wrapped on a tray': 7,\n",
       " 'foosball table': 6,\n",
       " 'framed certificate': 7,\n",
       " 'fruit platter': 7,\n",
       " 'fruit stand': 7,\n",
       " 'frying pan': 7,\n",
       " 'game table': 7,\n",
       " 'garbage bin': 6,\n",
       " 'gift wrapping': 7,\n",
       " 'glass': 7,\n",
       " 'glass container': 7,\n",
       " 'glass dish': 7,\n",
       " 'glass set': 7,\n",
       " 'glass ware': 7,\n",
       " 'globe stand': 7,\n",
       " 'gold piece': 7,\n",
       " 'grandfather clock': 6,\n",
       " 'guitar case': 7,\n",
       " 'hair brush': 7,\n",
       " 'hair dryer': 7,\n",
       " 'hamburger bun': 7,\n",
       " 'hand blender': 7,\n",
       " 'hand fan': 7,\n",
       " 'hand sanitizer': 7,\n",
       " 'hand sanitizer dispenser': 7,\n",
       " 'hand sculpture': 7,\n",
       " 'heating tray': 7,\n",
       " 'hockey glove': 7,\n",
       " 'hockey stick': 7,\n",
       " 'hole puncher': 7,\n",
       " 'hooks': 7,\n",
       " 'hoola hoop': 7,\n",
       " 'horse toy': 7,\n",
       " 'hot dogs': 7,\n",
       " 'hot water heater': 7,\n",
       " 'id card': 7,\n",
       " 'incense candle': 7,\n",
       " 'incense holder': 7,\n",
       " 'indoor fountain': 6,\n",
       " 'ipod dock': 7,\n",
       " 'iron grill': 7,\n",
       " 'ironing board': 6,\n",
       " 'karate belts': 7,\n",
       " 'kitchen utensil': 7,\n",
       " 'kitchen utensils': 7,\n",
       " 'knife rack': 7,\n",
       " 'ladel': 7,\n",
       " 'laundry basket': 7,\n",
       " 'laundry detergent jug': 7,\n",
       " 'lazy susan': 7,\n",
       " 'leg of a girl': 7,\n",
       " 'letter stand': 7,\n",
       " 'lid of jar': 7,\n",
       " 'life jacket': 7,\n",
       " 'light bulb': 7,\n",
       " 'light switch': 7,\n",
       " 'light switchreflection': 7,\n",
       " 'lighting track': 7,\n",
       " 'lint roller': 7,\n",
       " 'litter box': 7,\n",
       " 'luggage rack': 6,\n",
       " 'magazine': 7,\n",
       " 'mail tray': 7,\n",
       " 'mask': 7,\n",
       " 'measuring cup': 7,\n",
       " 'medicine tube': 7,\n",
       " 'mens suit': 7,\n",
       " 'mens tie': 7,\n",
       " 'mortar and pestle': 7,\n",
       " 'mouse pad': 7,\n",
       " 'mug hanger': 7,\n",
       " 'mug holder': 7,\n",
       " 'napkin dispenser': 7,\n",
       " 'napkin holder': 7,\n",
       " 'napkin ring': 7,\n",
       " 'necklace holder': 7,\n",
       " 'newspapers': 7,\n",
       " 'night_syand': 6,\n",
       " 'oil container': 7,\n",
       " 'orange': 7,\n",
       " 'orange juicer': 7,\n",
       " 'orange plastic cap': 7,\n",
       " 'ornamental plant': 7,\n",
       " 'ornamental pot': 7,\n",
       " 'oven handle': 7,\n",
       " 'oven mitt': 7,\n",
       " 'package of water': 7,\n",
       " 'paper rack': 7,\n",
       " 'paper towel': 7,\n",
       " 'paper towel dispenser': 7,\n",
       " 'paper towel holder': 7,\n",
       " 'paper tray': 7,\n",
       " 'pen holder': 7,\n",
       " 'pen stand': 7,\n",
       " 'pencil holder': 7,\n",
       " 'pepper grinder': 7,\n",
       " 'pepper shaker': 7,\n",
       " 'personal care liquid': 7,\n",
       " 'phone jack': 7,\n",
       " 'photo album': 7,\n",
       " 'piano bench': 6,\n",
       " 'ping pong ball': 7,\n",
       " 'ping pong racket': 7,\n",
       " 'ping pong racquet': 7,\n",
       " 'ping pong table': 6,\n",
       " 'plant pot': 7,\n",
       " 'plastic bowl': 7,\n",
       " 'plastic cup of coffee': 7,\n",
       " 'plastic dish': 7,\n",
       " 'plastic toy container': 7,\n",
       " 'plastic tray': 7,\n",
       " 'pool ball': 7,\n",
       " 'pool sticks': 7,\n",
       " 'pool table': 6,\n",
       " 'poster board': 7,\n",
       " 'poster case': 7,\n",
       " 'projector screen': 7,\n",
       " 'puppy toy': 7,\n",
       " 'range hood': 7,\n",
       " 'remote control': 7,\n",
       " 'rolled up rug': 7,\n",
       " 'salt and pepper': 7,\n",
       " 'salt container': 7,\n",
       " 'salt shaker': 7,\n",
       " 'scenary': 7,\n",
       " 'serving dish': 7,\n",
       " 'serving platter': 7,\n",
       " 'serving spoon': 7,\n",
       " 'sewing machine': 7,\n",
       " 'shaving cream': 7,\n",
       " 'sheet': 7,\n",
       " 'sheet of metal': 7,\n",
       " 'shelf frame': 7,\n",
       " 'shoe': 7,\n",
       " 'shoe hanger': 7,\n",
       " 'shopping cart': 7,\n",
       " 'show piece': 7,\n",
       " 'shower base': 7,\n",
       " 'shower curtain': 7,\n",
       " 'shower hose': 7,\n",
       " 'shower tube': 7,\n",
       " 'sleeping bag': 7,\n",
       " 'soap dish': 7,\n",
       " 'soap holder': 7,\n",
       " 'soap tray': 7,\n",
       " 'soft toy': 7,\n",
       " 'soft toy group': 7,\n",
       " 'spice bottle': 7,\n",
       " 'spice rack': 7,\n",
       " 'spoon sets': 7,\n",
       " 'spoon stand': 7,\n",
       " 'spot light': 7,\n",
       " 'stack of plates': 7,\n",
       " 'stacked plastic racks': 6,\n",
       " 'stand': 6,\n",
       " 'staple remover': 7,\n",
       " 'step stool': 7,\n",
       " 'storage bin': 7,\n",
       " 'storage chest': 6,\n",
       " 'storage space': 7,\n",
       " 'stove burner': 7,\n",
       " 'styrofoam object': 7,\n",
       " 'suitcase': 7,\n",
       " 'surge protector': 7,\n",
       " 'tape': 7,\n",
       " 'tape dispenser': 7,\n",
       " 'tea cannister': 7,\n",
       " 'tea coaster': 7,\n",
       " 'tea kettle': 7,\n",
       " 'tea pot': 7,\n",
       " 'telephone cord': 7,\n",
       " 'tennis racket': 7,\n",
       " 'throw': 7,\n",
       " 'tissue roll': 7,\n",
       " 'toaster oven': 7,\n",
       " 'toilet bowl brush': 7,\n",
       " 'toilet paper': 7,\n",
       " 'toilet paper holder': 7,\n",
       " 'toilet plunger': 7,\n",
       " 'toothbrush holder': 7,\n",
       " 'toothpaste holder': 7,\n",
       " 'towel rod': 7,\n",
       " 'toy apple': 7,\n",
       " 'toy bin': 7,\n",
       " 'toy boat': 7,\n",
       " 'toy bottle': 7,\n",
       " 'toy car': 7,\n",
       " 'toy cash register': 7,\n",
       " 'toy chest': 7,\n",
       " 'toy cube': 7,\n",
       " 'toy cuboid': 7,\n",
       " 'toy cylinder': 7,\n",
       " 'toy doll': 7,\n",
       " 'toy house': 7,\n",
       " 'toy kitchen': 7,\n",
       " 'toy phone': 7,\n",
       " 'toy plane': 7,\n",
       " 'toy pyramid': 7,\n",
       " 'toy rectangle': 7,\n",
       " 'toy sofa': 7,\n",
       " 'toy stroller': 7,\n",
       " 'toy tree': 7,\n",
       " 'toy triangle': 7,\n",
       " 'toy trucks': 7,\n",
       " 'toyhouse': 7,\n",
       " 'toys basket': 7,\n",
       " 'toys rack': 6,\n",
       " 'tree sculpture': 7,\n",
       " 'tv stand': 6,\n",
       " 'utensil container': 7,\n",
       " 'vacuum cleaner': 7,\n",
       " 'vegetable peeler': 7,\n",
       " 'vessel set': 7,\n",
       " 'vhs tapes': 7,\n",
       " 'video game': 7,\n",
       " 'waffle maker': 7,\n",
       " 'walkie talkie': 7,\n",
       " 'wall decoration': 7,\n",
       " 'wall hand sanitizer dispenser': 7,\n",
       " 'washing machine': 6,\n",
       " 'water cooler': 6,\n",
       " 'water dispenser': 7,\n",
       " 'water filter': 7,\n",
       " 'water fountain': 7,\n",
       " 'water heater': 7,\n",
       " 'water purifier': 7,\n",
       " 'watermellon': 7,\n",
       " 'whiteboard eraser': 7,\n",
       " 'window cover': 7,\n",
       " 'window frame': 7,\n",
       " 'window seat': 7,\n",
       " 'window shelf': 7,\n",
       " 'wine accessory': 7,\n",
       " 'wine bottle': 7,\n",
       " 'wine glass': 7,\n",
       " 'wine rack': 7,\n",
       " 'wire basket': 7,\n",
       " 'wire board': 7,\n",
       " 'wire rack': 7,\n",
       " 'wire tray': 7,\n",
       " 'wooden container': 7,\n",
       " 'wooden kitchen utensils': 7,\n",
       " 'wooden pillar': 7,\n",
       " 'wooden plank': 7,\n",
       " 'wooden planks': 7,\n",
       " 'wooden toy': 7,\n",
       " 'wooden utensil': 7,\n",
       " 'wooden utensils': 7,\n",
       " 'yellow pepper': 7,\n",
       " 'yoga mat': 7}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ufo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "d2 = {}\n",
    "fail2 = []\n",
    "# Working with a train dataset - 4226 images\n",
    "for i in range(1160,1305):\n",
    "    try:\n",
    "        element2 = {}\n",
    "        number_of_image = i\n",
    "        print(number_of_image)\n",
    "        element2 = transformation(store[i], number_of_image)\n",
    "        #print(element2)\n",
    "        if element2:\n",
    "            file_name = os.listdir(store[i] + \"/image\")[0]\n",
    "            file_to_copy = store[i] + \"image/\" + file_name\n",
    "            target_dir = path_to_sun + \"test/\"\n",
    "            shutil.copyfile(file_to_copy, target_dir + str(i) + \".jpg\")\n",
    "            d2[str(i) + \".jpg\" + str(os.path.getsize(file_to_copy))] = element2\n",
    "    #except json.decoder.JSONDecodeError:\n",
    "    except ValueError:\n",
    "        print(\"Fuckup with \" + store[i])\n",
    "        fail2.append(store[i])\n",
    "\n",
    "jsonname2 =  path_to_sun + \"test/\" + \"via_region_data.json\"\n",
    "with open(jsonname2, 'w') as fp:\n",
    "        json.dump(d2, fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pictures failed:0\n",
      "Pictures parsed:145\n"
     ]
    }
   ],
   "source": [
    "print(\"Pictures failed:\" + str(len(fail2)))\n",
    "print(\"Pictures parsed:\" + str(len(d2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "1448\n"
     ]
    }
   ],
   "source": [
    "d3 = {}\n",
    "fail3 = []\n",
    "# Working with a train dataset - 4226 images\n",
    "for i in range(1305, 1449):\n",
    "    try:\n",
    "        element2 = {}\n",
    "        number_of_image = i\n",
    "        print(number_of_image)\n",
    "        element2 = transformation(store[i], number_of_image)\n",
    "    except json.decoder.JSONDecodeError:\n",
    "        print(\"Fuckup with \" + store[i])\n",
    "        fail3.append(store[i])\n",
    "    #print(element2)\n",
    "    if element2:\n",
    "        file_name = os.listdir(store[i] + \"/image\")[0]\n",
    "        file_to_copy = store[i] + \"image/\" + file_name\n",
    "        target_dir = path_to_sun + \"train/val/\"\n",
    "        shutil.copyfile(file_to_copy, target_dir + str(i) + \".jpg\")\n",
    "        d3[str(i) + \".jpg\" + str(os.path.getsize(file_to_copy))] = element2\n",
    "\n",
    "jsonname2 =  path_to_sun + \"train/val/\" + \"via_region_data.json\"\n",
    "with open(jsonname2, 'w') as fp:\n",
    "        json.dump(d3, fp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pictures failed:0\n",
      "Pictures parsed:144\n"
     ]
    }
   ],
   "source": [
    "print(\"Pictures failed:\" + str(len(fail3)))\n",
    "print(\"Pictures parsed:\" + str(len(d3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_root = store[100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "frameData = SUNRGBD.readFrame(image_root, True )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "imgRGBWithAnnotations = np.array(frameData.imgRGB, copy=True)\n",
    "\n",
    "for i in range(0, len(frameData.annotation2D)):\n",
    "    color = [rand.randint(0,255), rand.randint(0,255), rand.randint(0,255)]\n",
    "    cv2.fillPoly(imgRGBWithAnnotations, [frameData.annotation2D[i]], color)\n",
    "    \n",
    "for i in range(0, len(frameData.annotation2D)):\n",
    "    data = frameData.annotation2D[i];\n",
    "    centroid = np.mean(data,axis=0)\n",
    "    cv2.putText(imgRGBWithAnnotations, frameData.labels2D[i], (int(centroid[0]), int(centroid[1])), cv2.FONT_HERSHEY_SIMPLEX, 0.7, [0,0,0],2)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = frameData.annotation2D\n",
    "data2 = frameData.labels2D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "anotation2D = image_root + \"/annotation2Dfinal/index.json\"\n",
    "\n",
    "with open(anotation2D) as data_file:    \n",
    "    data = json.load(data_file)\n",
    "\n",
    "    numberOfAnot = len(data[\"frames\"][0][\"polygon\"]);\n",
    "    anootation2D = [];\n",
    "    labels2D = [];\n",
    "    for i in range(0,numberOfAnot):\n",
    "        x = data[\"frames\"][0][\"polygon\"][i][\"x\"]\n",
    "        y = data[\"frames\"][0][\"polygon\"][i][\"y\"]\n",
    "\n",
    "        idxObj = data[\"frames\"][0][\"polygon\"][i][\"object\"];\n",
    "        pts2 = np.array([x,y], np.int32)\n",
    "        pts2 = np.transpose(pts2);\n",
    "        anootation2D.append(pts2);\n",
    "        labels2D.append(data['objects'][idxObj][\"name\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth data\n"
     ]
    },
    {
     "data": {
      "image/png": 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Xsb4uFinwabdpYvYhFEgn2+rq6gbZTbbXUMjl6vpWmLJWV1fBzFhbWwMRYTQaYW1tbUM5pvJ9MJMkGTNJc0zsGojBVwZbe1MHVg390BZsJhbdxDYFYuuOtwkXmenaNjc3t47EBARJiXNWV1en56gkBgBzc3NTwpXLEWWLcuTzVHmFLKYQrJR+nSmSTOmMVALoGzGUIMhSfVDDNlDVbELOcaW5kKvttn6UCWY0Gk2JzUcWnZ3V9K0SJABjXbrydZA1TR1pizyxqMZxk4ouPco1EaTvhPL1aLbRn7XFmgLm8dTVtc7RByYta35+ft0xsYX1Qcn+SCl7JoPJ+4CayDAVPm2Jjd+bBXStuZZCDe2qQYYQOEmSiD5GRMeI6Ckp7deI6AgRPdF8bpaOfYiIDhHRN4joX5QSXKov+fwQO17tmCWyUjXZ83mHUApEhJWVlen/knGzoXcLpcqR6/r5aJIfB3CTJv0jzHxN83mgEeoqALcB+MHmnP9BRHNZJNXgfPWkpiJ3f+UoT+fEUFHa3pyrvtqhOo9ig6xD6knJo+YNkVdeaNWPL5wkycyfB/CyZ3m3ALiXmZeY+R8xeSHYdd7SRKBNu8UskHFf25BiGw2d/H3toxisra05A9x1SO2jnIH0toiBHEixSX6QiJ5stuM7m7TLADwv5TncpG0AEe0jooNEdPDMmTNRAqRuDWZVU4iFjzZXqi6RJj413KanxgDWgjZuJZXh47iyjRU1rKdviCXJjwK4EsA1AI4C+N3QAph5PzNfy8zXLi4uRoqRhlwkUMuFz726l2yXSkQqagq1aqtO3+1pVs/tKF5P8rEV29pUy7xxIaqHmPlFZl5l5jUAf4xzW+ojAPZIWXc3aUXR1sra9gpeAqHy52izaascO9l1tqUuQr+6QG4nlthuq+Xb6jsf+llGFEkS0S7p708AEJ7v+wHcRkQLRHQFgL0AvpQmYjmEhrjYJmLX5BkycLuSNcZw7pO31m1xm0hZcMS3bz+r5/nI0YVTKBecd9wQ0Z8BuB7AxUR0GMCvArieiK4BwACeA/BzAMDMTxPRfQC+DmAM4E5mtofTZ0LMIDnfVkSBvjis1EnpmhiqnKkTSb17o3Q/hNhic7TNVK+66Kh9YPqdQ64a4SRJZv6AJvluS/4PA/hwilC+aMOzHbK6zipsdrBZbX8X20tfB0dOz7ANJhLUkWpX5NhGvefdHTc5bVc1EUSu0A3TrWtto6a+bROlA6xN5ZnMIC4bZcx1asMhmBO9IcnaJuqsTmJVg0rtg67DeULRtQOohnEVSpTidw2yl0BvSDLXUz1yalw5J3+q19KXsHyP5zAz5PTExnjlY+vp0rHVRX2myAMdCeo0SV+y7GtQf/WPSuuyo9q85TGlrpoJsiukOBLakN3kAAHasbOZnDMmJ46a11Qm8+QBuPJzI0vaS9vYqVRFkiaDcO5B61NmF/eEizpDLnzbBJlLphznhJYvX9NcO5OQ+n3SRHrbd9TIhKMjRpFPTjdFH8ivR9A9P7JvqIokdXd8lBi8vmV24dXt0n7XFUG2Bd2k1pFmzjaERFG4vNalNTJdva5FRUeWKjHq2tYnO3VVJGnqzJonXg7oVmifQTRL/WK6zrkmk6kcEzGZZJmVPpfbYtJyZfusi0RliK22uOWxT4SoQ1UkCdhXndQBGnJ+V55teeDaBleIhuJzrIbJb9vqxZZng22bacqvk9OVvy3EbtN17bKZJuRzdPULk5F4DQQzO1/RUDOqI8lS6ANBloBpQoe2I4czx3Zu7u1YSU+qa3x0oXH6Lq7qOT5mBnUh0W29VXuk0CLn5uawsLCAAwcOBLepFlRFkqaLm2PA1br6A91v49pcFHxtvCneaVv5OhtaTphsiG1eXx+itJG5qY9sjh2TvbdvSoUOVZGkCakkkutC5Tbom7Y3PigdMuSTL7c2ajrHtfWznafW29akzUHuIWXE9JEJan899NBDSeX1Hb0IJs+lSabWEzL4TBNTXl1dk9dHnlJGcZ8+byvA29R/vuep2p36yQmdfKF9mRIIPyA/qtQkS4Rg5CgzdrveJZG5tlM1aOi6MnNuswUZygQm29d8HROh9foiZ5iPLs54QBqqIskSky6nvc9VVkn7VkhdXTkPXMilnYZuQ2POC0Hu8ZXioQ6ta4Abvdhutw3T1td3O15yGyzXFRL7VwtyyDZMbn8MfZWOakiypotpursg9NzS3r2a+qxthCxapvNN5XQVvgOUexSarc4BdjhJkoj2ENEBIvo6ET1NRD/fpF9ERA8S0Teb751NOhHRHxDRIZq8TfGHfQQpdctVLk9uTN0xcsSUrztmC7XpaoKU2OL5tFX3EfLYyvFx8AxkM/vw0STHAH6Rma8C8DYAdxLRVQDuAvAQM+8F8FDzHwDeh8m7bfYC2IfJmxWdyBmmE0qObQ302iaUjVxmGbY7uFQCZZ481UZ8cge9D6gfTpJk5qPM/JXm96sAnsHkXdq3ALinyXYPgPc3v28B8Ame4G8B7KD1Lw7LjpwebLXckDJDCdqnvBi0dbdKSMyiS+NT86mauG89PrL6lre2tobV1dXpx/REm1whRSUXp4HM4xFkkySiywG8CcBjAC5l5qPNoRcAXNr8vgzA89Jph5s0tax9RHSQiA6eOXMmy0DLcStaLNGV1r5CSMNHQ6xFW9R54mVNT0egpnJc9aiQtUU1XdUgZU3S9FHLLYmB9NqDN0kS0TYAfwHgF5j5FfkYT65Y0FVj5v3MfC0zX7u4uKg77k2asQO0DwNNRxSu/K501+LQph1XDXvxsVuaCM/m7dcdd+1AdOQnHtgg/svHhKZZYgFqm4QHnINXnCQRzWNCkH/KzH/ZJL9IRLuY+WiznT7WpB8BsEc6fXeTZoXr4ZwuR4UMm83JBV2sms12pZ7XJXzq92lLaj0xcvgQls7hop4feswEXV6ZJIkmT7kRi8ry8vL0v60dvnUORFgPfN67TZi8QvYZZv496dD9AG4H8FvN96el9A8S0b0A3grgpLQt18J3i20Kti05aUW9PuelOkJsdfqUYSLqnDbSHF5eWz+Ztt6m/yHw7UOR1/QKAkGU8/Pz2LRpE8bjMebn56Pl8pWplnLON/hoku8A8NMAvkZETzRpv4wJOd5HRHcA+DaAW5tjDwC4GcAhAK8B+NkcgprsR6Y0IEyDkCenmKw+2qFLwzHJFaN5+pCwTotWZVSJ3ZeQUyeZSUNX+96EELOLLY9P++bm5tZpjTLW1tawadMmMDOWl5c3jBtxvrw7stldbXLn7nPfegecg5MkmfkLAEwj90ZNfgZwZ6JcWRC67dZpqj5e0bYcTSFanE0z9vmvpoUsFiK/3J/ywqM7R+3nkltP00Ii/x6Px8bzbYucrg9sC7wLMaaCLsudRVR173ZOxGwx27IpmgjBd3U32WB1ZZrO99W6bPldGqmcx7XwuDRr24KXc5FSF0r5pVYCptcSyOQ5Ho+n2maoDDF5QmDq/wF6zARJqkQTW0bK8ZQ6fW2mPlt0X8eHD9GajrnK90nXld0GYfiaUNQP0cYXXKlYW1tbd03H47H1PS9dOPpEnbKsIn0gSj1mgiQFcjgPUvOmnmfTlFKIPPeEDJEzxv4aglxmC4FNmzZN38li07pWV1exaZN9CunskiYHpG5bnmNR0KW5TAUDYZ5DNSQZqwmGaGMh5aXKkxO+mqZvemkNpjQpyvXEHBPQkcJoNMLy8rKWwFQSE9rl/Pw8xuMxmBmbN2+eamm2hcQkn40gVZtuLEyyqXk+97nPJdc1C6jmKUDy1qY0fLZbPvlqQS6CFJPHVZ5PGab/OeGSVf34nLe0tOTtaCE6FyYkfo/HY+N93qEo0W8+5g/x+dEf/dHs9fcR1ZCkCbaJW8I5EzqwQzzAOeFLaK600HpM5ap5SpKjq35XPtMx4FzojvjYwMxaQhQkk0qUJRQGVXtWP+qxG2/cEMBy3qE6klQnmul4bpgGi895tcHmvAmFy0uu1tW19h1L0CHXXl0wTLZEF8nmQK7FKHb8nw+ojiRDEHNBTYZs8d3nl6i7EOvY8bGf1QYfclcJRmd3tJWhq08dk/K93qEIdS6G5DfJO2AjekeStlAVH7jIYDweY3l5OViutrfaA8KQagIIDU/qioRC2pnq+DpfUBVJhqzkOSEGlFj1U+ySbaBE3+SazDVOrtTrkyMMJ7epwzdvqOll0Cw3ohqSVL1uLgdBqFbgm1/k2bx5s3fZJQdVDgIObbsOvm2sRcvN6TzyLaOrtoeOP5uttJbrVxOqIUngXEhFiXJN6fKxubm56e+zZ89uyN/FKuta8X23gaXkngWtw+UszFGmzsGVg8hdAekx12cgyvWohiRtnsLY8nxDZMRvOQhYV7/pWMlBZWqHjvhKh934kG2uYOfcCHXE5PLa+1wTmzPRt3xbiJbpvGFr7YdqSFKghosmBlAIwZaCbiCX1Ap9NFSdPDqnhS9MnuIc0MX++cqSem1NxNV12JQ8vget0Y1qbkuUNUnbxbORVy7YiEKVsy24wnBkDdfHWO/Ko2ufGi6jputkUaErs5QjSvdb/h8qi2+7bNt328LbloLQZl2zgGpIUkB+BL4M3aAX+eTHWdkmuQp1sIg7JORtte5RWX0ZYGoYis45ZiI+X01al2bb+qWYKkpM7tCFzmcxEsfU/s1pe0xFSe191lANSRLRhqc5qxqKDuIc8WABce+sXIZtYorjp0+fXvd/NBphdXV1+oTq+fn56atFxXG1LB+kBhari4GJiOT8cmiTi/hMpCnn0/VnLPmF2tJyQiYx0T8+d8n4yCq//8YHOcOvYvpy0C7N8HnHzR4An8DklbEMYD8z/z4R/RqAfw/gu03WX2bmB5pzPgTgDgCrAP4TM3/WRxj1sVKbN2+ePl1FB+ZJ8DfR5GksQuvTbf/Ef5Eme9FVTVR+aIEILBfvYJbrjiHIGMeHz6pvmiCq6cC3ftd2XCXTGM0kdGL69HeIyUH89zGh2EwJNo3Zt3wbcttofWQYSPMcfDTJMYBfZOavENF2AF8mogebYx9h5t+RMxPRVQBuA/CDAP4JgL8ion/GzM77/YhoSkREhKWlJczPz2M0GmFlZWWaT73QzDw97nIqCKjPAlxYWJg+AUZ9+RMRrSs/ZaC3PfB869MtKDrojvtMKJ+tt6+MJfPGLGK6vpMfaiubkGLGj0//hrTBt8wBE/i84+YogKPN71eJ6BkAl1lOuQXAvcy8BOAfiegQgOsAfNFV18rKyoYBJDQ59aLaJrVLGxPHZS0RmASQ6+xy8/Pz60i6baRso0LgY8PVpcUuHDmQWxNNgWmBlrfdMY4bX9IznWMjdt1v2fTAzHjHO96xId+jjz7qlGlWEBQCRESXA3gTgMeapA8S0ZNE9DEi2tmkXQbgeem0w9CQKhHtI6KDRHTwzJkzWFlZWffYKVUDdF1I3UcuT378lfxx3Yq4sLCwQbOMWYG7IhFfxBCk77m1oE1tXh6HoQ+5yCGfjYx15ifdvJEfF3c+a53ejhsi2gbgLwD8AjO/QkQfBfAbmNgpfwPA7wL4d77lMfN+APsB4OKLL+alpSUQ0fR2wBDtRLeCiztmFhYWtFrn8vKy9l3J6op+6tQpLCwsrDsWYpB3lS/LZWpTX0ioC/g492TobIWloJafaqbRKQ+u83SQHaRy+apCsbq6uo4smSc+gJWVFezduze4LSFwtfHQoUNF65fhRZJENI8JQf4pM/8lADDzi9LxPwbwmebvEQB7pNN3N2lWiIt/9uxZjEajKbmZCOS1116bktXi4qK2LGDypGmiye2OwgYpnEHLy8tTD7YgZ3lbJG//S62kLm+z6VhOeWZBS3R55XX5StUfU2eMlhuykKpkKH6rOzITQQptOOXRb76oTWt1brdp0vt3A3iGmX9PSt8lZfsJAE81v+8HcBsRLRDRFQD2AviSRz3Tj80GxzzxPs/NzU3zq/dZq04ecfEFKcrkK+7XFuE9IoRILqPUw1O7mLBqvlQZahvQwPp2yeOqC8J32SLVfDJCnGEh10E1UemIUd12q6atUvAt+8orr8SVV15ZTA4ZPprkOwD8NICvEdETTdovA/gAEV2DyXb7OQA/BwDM/DQR3Qfg65h4xu9kh2dMS5+4AAAfkUlEQVR7NBrhda97HVZXV9d5AgU5zc3NYWVlZRqaw8xYXFychu6cPn16SpqbN2/WPjh3fn5+eoHF2/Dm5ubWEebmzZunpDkajXD69Olp/GXTtml5OSZc7JZPZ14oQQB90SJNaEN+eVHvwoEV6whSSc/Xdl/yaes1LriAn3f7CwB0V+IByzkfBvBhXyHEBZXfUSyvWCIWUh2E4oJt3bp13XZ9fn5+w4vhxfk6TVTWMmRC3LJlyzS/bgXNRZQh5fnao+T26jALW+zaEGM66QLquNA5bGStUvwOsYnGyBSTT2iTzz77bHaZBKq540ZANVQD8dsKneHctP0xOWREmvried/tkzoY5e2+TPo+j4jTtV0uS65brbcUUrzitcJmh5avm80sVDvkXZn6UbVKeS7WRJBtoSqS1BmXxX/dwHUN5hCYSErWckNWUVVOosndO4Js5fbJdwr5aH4uQhQmC5u8tq2h7+SfRYIE3IH0cp5cW+zcBGBaUGW5xTgRjktxa26p+nOWpZL25Zdfbi3jueeei66/GpLUrWTAeiJUtS+fie4D1zZJpz2E4rXXXtsgm/gWK7bwwptkEsSqMznIMsvHXbYp2wT3OS7X03f4OA27cgDlhG67vba2Ng11A4BXXnllekyGaw7kIkefOkpqtzKqIEnVJmKz/YVOWltHmgZ8KPGaBs7Zs2e9NI4cF1tur7C3htgvbcfl8mPLiUXKwhQKtR61TaXIMfT6h1xb13FdmwFg+/btYJ7c7nv69GnvXZRtd+cDXwI29ZlJ6/z+7//+dWnf+c53vGWqgiQBrDMO67Y18vYxxMHhMwB9wjRCtKYzZ85Ytwg26O4b94FsFhBe+zahs+XmLDtVkw9Fznpyk2sbfSDm2qZNm/C6171u+n80GuHEiRPTCBLT/Ar1I4SSo+23rdyYxbwqkjRpe7rtgXzMh9xsWqYvTPLJ36+++uo6mUIviM3e6DpPdTC1hVL1temAMtV/vkM3Hrdv3w4A03jipaUl6627LpOPT902jdGnbPX37t27ve2UVZCkiQRNeXV2SsA/IFclWdO5ujJs+U+ePLmhXNsK64Jte2/KL7/MzKeu1Dw+polYsmmbFE31p5ClMOl0sXDplAlTm0zxjzqCm5ubw3g8BjCJPxbPXB2Px+uehSDPa105qdqjrYyYc0yogiRtcG1bYwhP1fJCOk0d8KK8EydOeJ0fWpdch08ZsvHdt/zY4znq6ANK2Vtddep+6zA3Nzd9FoGwI6rKhPjWfeR65EgLsaUWJChjfn5+enuv8JKLc4XpTCZMscOxmb9cZJaiPfqer0P1JOmLkEaLQSACzmNjFAVUgozRgHTEG3pRR6PRNAC+NAHOAvnVihATC4ApgZ09e3bDbbfAxrFlI0mhIcpkpmqZLvnkCA3dk4TU8e2j6bnmQgjBhmJmSFKG7zZpPB6ve/CuL3y39T4ymM53XVSTDLaVOgS5vNk5tqw5oWpX6mKU2+Hka87wteHpzmM+d6ut2PYeP34cO3fuBBFNTTAq8anXRqSrxCbLoyoUPlqq3A/q+MxNfjEE60I1JFliS+MqM7ROU34f20obW1fbxE8lTVN9bWzZTeXGtElnbvFxAKYgpVzfscU8eZ7BeDyeboNfeuklMDN27NixLuLhpZdempaxffv2dTcfnD59GvPz81haWlr32EIA2gdP627/lc8xaa1qHp92pxJm7ByohiS70jRWVlbW2fFSiFCHWjQoFSVJoTRyLThd9YGL4H0ns875cuzYsQ35Tpw4gbW1NezcuXOaJto+Ho83vKFUaJLi9SnAuccLqoSoEqfYmeXSFGPPy0mY1ZBkCZgmgJwuBoF6MX28tqIs25NR5FU6dUK6toViWxOzVe8DVLl9nFk+nvkSZGm6Prq6c0FHTHJY2MmTJzeYZM6cOYP5+fl140aOgRSvOPGtT30Fi+7NpbFEqEsLzdPr7XZuhIS26CaJmiYurmyTISLtyi0fF29xLGFKEHXI9alpXSI1dEag9La+ZH/lKNt3You7SExOQB1Bieesqgus+JY1Q50dUyerSV6TLD4k5qsJ5iZIoMckmWPwyV449YKZtJQchOcTruR7QWUCkQehrW4f+VIRW4ZrsTpfIJNIik1ZHhvqGLeNeQHdy/lsddhgI1DT+TnI0Uc2G6olSdvWKga6TpLf1S3y6FYesYrmhA8ZxGydTXfctEWOAjHkFit37cjVhtCJrluMTWPdpwwfWeT5ZMtn23rr4EuOurRUwvR5fcMWIvoSEf0dET1NRL/epF9BRI8R0SEi+nMi2tykLzT/DzXHLw+SCOvvUhCfkLw2e526PVUHje0lSKW1GlV7CIWvTTInStvUQiZSrdC1y5VXN45dY8KXDNSy5bGvboWFycj2VlIZaj6dzCGka2qnrm6dkpNjLPm8UnYJwA3M/EMArgFwExG9DcBvA/gIM78RwHEAdzT57wBwvEn/SJMvCCbis5GhbkD5GO1NNhKZMHOQpMte6LMg6PKr5attCpUvFKVsrakLRi3Q7RhMpJlzi6iTwzVnAKwb8+rrluVXOMhzxvTKB1nZ0LXddl3n5ubW3WIrYCLY0L4M6VsnSfIEp5q/882HAdwA4JNN+j0A3t/8vqX5j+b4jRQwykVW+dmJphXBpNb7rNypGkrIxA0lQFM9PuXEbMlitsU+5/VdAywJV9+4xntqffL109kUxW8R+qO+DMykXepewUI0ucVRZxoSmJub2/B+K5eJK1SbjO1H31fKzgH4MoA3AvhDAM8COMHM4ybLYQCXNb8vA/B8I9SYiE4C+D4A31PK3AdgHwBs27ZN2yjdsyXlfOJeVfEOHPnp4aY7A9RthrBLlkQMCalEb9t6qXlDty6+9soaSC9Fm28bvnKW1CBd5equqzz/dGXoxp5IE7c1imNijslEqSMq9d5wcVx337hv+2Lmgw5eJMmTtx1eQ0Q7AHwKwA8k1Topcz+A/QBwySWXsNwQ23ZRvigikFVeCcWFlZ0y6kXVEaVpQKtyqITqQx4hE1s1A6jpPueUILSYrXsuGeRr3heClJFTZpvSEAvbgqv+lseYutvTlSN+mxZ7Oa/OVioIUihB6r3l6m/XMVOaDUHebWY+QUQHALwdwA4i2tRok7sBHGmyHQGwB8BhItoE4EIAL2kLVOAiK4tcG4hBqOu6B9DKA0HeOoZ23ve+9z3jOTpblCmfPEhs+VzPitTZcErARfpyv+auF+i3jbI22BZjnaKie11IKHGb3hflIjTxymnbNtykPaYsIj7e7UsaDRJEtAjgvQCeAXAAwE822W4H8Onm9/3NfzTHH2ZPCVMGv9rpOkeJyXnCfO6VB6PRyBoLqXsvuEkeAZthezweTw3c4r5bkSZ+iwebigcYqAZ1uc4Ysg/N3yVJ1UqQOrlCZE3VEA8fPuxdlwmuuWIiMXlbbbP7ibEp8slkqfuoLwOUz9XJZNKC29hu7wJwT2OXHAG4j5k/Q0RfB3AvEf0mgK8CuLvJfzeAPyGiQwBeBnCbqwK1IT6NcmkVKmHIdYhvQXhENH0ikExcum06M+PFF190yifXo9O8bIMI2EjA6tZDELqaJ2ZA1Eg8NcpkgmnxdR0Dyju3YseDa8E1jV/dy+pM58j2S1nxUOetyR4v6hqNRhteJ6GrL7avnSTJzE8CeJMm/VsArtOknwXwU1HSZITa6cDGTlpdXZ0+xUQOVRCamu4RU74EKaASs2ubavsvYzweT++5FbjwwguN2w0dYhxKrmOurXhOeWpGirOuFpiUBBW+aer5Ns3UdI4Orvrb0CSLg4iwdevWDelnzpwBAGzdulX7TuCtW7dOO1E9vm3btnVpYpUTZW3btm2DvUNAkGWIZ80XMonYfseWLSDbWtXyTYghKdMqH3NuH1GqT2skTB1RqmYl245JN77VNB1BujRakcf2nh2TTD6ogiRNHuPFxcVpJ6okqnaE7vgFF1ygrW/r1q0bLob88F35pn7V1pIKnd1H99u3Lpn8Tp48iR07dkzTZIeUSwtsW/ubBYK0oYTjyoacmpMKHVmZyNJWt0njM9k95TpdcyLGPOCLKkgScMcBpmgsvnXqIB5A2kZdan7bhdUNHvUp6/LiYyJ5eTL7yJhD24yFOkmB8jY9FT71CedfyMNQfEkut5aZarPUlVFCPtPYVY/p8qcuINWQZNvwJQSfVSy2Hh8iDDkmv5bXpUGqxOgKqPfRSH3kTkWJxTIGputmc6r5OO9yoI3tumnBCiHMHOYl+Q4fefckO3JmwiYJhMXAmWx5JesTeU0D0DR5bXYYNZ+v00VMQt92u8jetO035cupGQr4tNkHNvJKhe/2z1SXz2T1cWyElFGaMNX+CBnHOeSSb3dU681lIquGJAV8nRltbLPUOkajES6++OKpTCKY3LZltZGkiUhdE8Vm7/KxP8YcC8njC1lWG/m4TC+uBa+Etplr/JUex22aI3zshrnrMZGyKov6WMQQVEeSgJ4kTFpH6EoZqpHI9cudTERTwjx+/HgQOflugXXy2M711TK6dpr4tj9GVhehloZtS51ju226zm2Roa8GbdMqY9stzg1tv+r1DkU1JBlLfKEEycx49NFHtXfLvPvd795Qtmznk2/7Y2Z84QtfWCcDEeHqq68Okkec77LPuCb7k08+iauvvnoDGdu0shiEmCl0CCEx3THfNFt6WwixueXYGrapNdqgjutUgrSdZ0pXiTFlLFRDkjJMK8Wjjz7qtf0MIVg57yOPPLLO+BsqJzPjiSeeWCdXKehW1q9+9avrZL/++uuNcvrIJxaBd77znfibv/kbvOtd7/I6z4auJnJurTJkIc+9DW3DMZMDpm2xQJttSFEWqiBJXWeZtD3f81XYtrBqmmori62/tBPBlC6OPfzww8H2Ox3++q//GsyMRx55JOhclaxVGdqCvOVrQ7vULbIh9fqOZ/Va1kqesr0ZsLcvh+anqyNFo62CJE+dOjXVWkwIWbVDz2/DCB+j6abANSBTZAg998CBA+sm8rvf/e5WyCq3qcGFHBNbZ8Oz1Zdjmx6C2LpcRFlay7RptC6UfdpsAMTFNn1CywnJb0v3Lc+VJ7Y9sUjpw5IyrK2tTTXTUjJ12d7Y82LOrVFrDEGbNuOUeVCFJlkCOQZQyurjW3ZbaHsrZtvmi627bP9VnWaxKGXi8NF0SphRbBNb9KX6mLRat90COm0yZTtc2kFWDUnmNF7nHKw624/rnBLypKKtSWMasK5t1iOPPILRaIT3vOc92ny5oU5QF0ptbXU7llTtv2aCVJHDqVW6vdVst0Ph6ljXQPPd3psGb8h21nVel5/cMNXh07dra2tTsvSNMFAha6e+kQqhE9E2psS3z7hqAzUs0CpMC2hJh2YKqiHJkhM5R5mlSKUEQtrZBvmaCFM+LqcfOHBgXXoJhJBoTtgWCls+G3bv3p1NPh1yXwdd22SiNF0T33GXW0FwbreJaAuAzwNYaPJ/kpl/lYg+DuA9AE42Wf8tMz9Bk9b9PoCbAbzWpH/FWyINYi5SiVWplK3HJmtqfbX0nSjXJ9039KtGiAloethzbEiZLe3555835pFRg61SJjIZMjEymx+f1gV8bJJLAG5g5lNENA/gC0T0f5tj/4WZP6nkfx+Avc3nrQA+2ny3CtPATOlwcW5uzaPrQaAilzwm5404Jk8YdYIcOHAAN954o/G1wrpzTHl0eU1krUNof5iIQCerq2zTcV+ZclzLNsjVdT10162teePcbvMEp5q/883HJt0tAD7RnPe3mLxVcZejjiiV2DdvjIrtW28b8N0+xHzalls9pvvPPLkd9MEHH1z3Cg3TtspWlymvr7wxBOn6COJXX5xlqi/nuK0RtrZ3YRJR4eXdpslLwL4M4I0A/pCZHyOi/wjgw0T0KwAeAnAXMy8BuAzA89Lph5u0o7Y6RAfZtA8X5Ly+xvpUj3WtA88XJeT3MR+o/Wfamo7H43WTyDeqIaRdOnlTtCef81xtyV1f1zAtUK7/Aj7X1qcfYuatl+OGmVeZ+RpM3q99HRH9cwAfAvADAN4C4CIAv+Rd60TYfUR0kIgOyu+R8V29fVZfHw0qVtNqSxtz1a0bZF3KppPBJqfpv0h7+OGHp+9atmlf4pj4+Gh0Ptqea+yE9oGtjpC+rRkp8tn6W9UqYxbFmP4LipNk5hNEdADATcz8O03yEhH9LwD/ufl/BMAe6bTdTZpa1n4A+wFgcXFxg9ShDVHzm2xUrjy+5ctl6I75ll1ak+hqQrn636VJyv36wgsvYOfOncW2XD7aS+i5pny+OxfTwq9COG1i4aPNxo6h1LFnO99FkDnHvY93+xIAKw1BLgJ4L4DfJqJdzHy08Wa/H8BTzSn3A/ggEd2LicPmJDNbt9ol4KuN5q6njW14aNk5ySV0spvkUAnT9v+73/0uLrroomBCMtWf0gZdOSa5XWWGOIps/eNbRtcIkdlXYwfKzzkfTXIXgHsau+QIwH3M/BkierghUALwBID/0OR/AJPwn0OYhAD9rI8guQZu1+jj4CxZpo0Y5XTb/+PHjwfVqdZnmkS5NaTU3Y/uuCvPnj178J3vfCeo3hAZUpDTK27iBx8fRqoMTpJk5icBvEmTfoMhPwO4M1Yg25bM9zwXSobw1ELWtcBH05Ynk+74ysqKtixbPa5jXVwnncZsQowyUEMcpA9SFhPTtfQxr8Wimnu3dSh1wUNsk7m1A1d9OcoPrbtEP/tuJVWC1JHleDzWEkCqg8Ala264NFtTfjXNR96+EGYMdAus7NQJ2ar7oGqSVFFqq932YOpy8LZVt++1MhGkOhG++MUv4s1vfrNXvaEEIROPj3MpFbZF2iSL6XzZcTOrpGiD7OiS+9Hm2Antp2pIsm9aQU1I2U62baZwbb9lzUA+5+zZsyCiDbcs6rSKmLHkY8vKTZauekRdNu2xDWKsXSs1jSl5Gx47LoCKSDIXYjoiZ6hHLejSWSMjNKjfRaK2rVTfrpEPTJrSLLY1FWpfif4ajSbh4CKGNhS9IcmSXu1hwJWDr5arI0tVg/n85z+Pd73rXeveYNkFYjTK0DAVH9uxzb57viAk0oDo3GuhQ/qpGpKMvbjn+1ZbIPfkCAnFCu1327k2GyU1tymayqoZsSaAnE7F8wG6nYa8/Zbv3vJFNSTpgo9HOnbQpEzyWhAqU2w8amjeWLI1OTCeffZZvOENb4iSMzdCoiR8oNtOh2iebUWDdIlUe7MgSrEF90EVJCmrv7HhEV2G1XSBVJlTnD2l6jGNATn/yy+/jCuuuCLKi50DpsU5hyylHEM2dLlFN9mXc8ljMk+EECRQCUnKyLHtjkENYUQ5tbsYlCjfpfHbSEeXf3l5GY899hje8pa3bDhWEiFhOSnlx5ZVsh9KEWkXBC2cN73TJGuAS+Np42L61pFi/G8bLoebbbutSxP/xZO/25hoJesIdegMSIPo5xAvdy9Isq2toU+9XSPWVlgDYcpwkaApTfVMhtjuYvsgxebaZtkxW9Y2x7irrbXIoqJKkvRpQK4OrY08ZOQcNDFl5QhbcUElcl/yXFpawsLCQnRdOaALbhfpqeUCbnlrHrs1Ivb6V0OSNRiPBboafLVprqHypE5qU/iPWjbz5A6chYWFVvvMFK6kIkWmWY117HObqiHJmlDLBU3R/mqEyz6p5rNplkePHsWOHTt6/WbF1DC2mq+1jNJe7NKoliRLeYtzx7blRI42p2oxXcDHeaPGTZ48eRKnT5/Gli1bjGWpZaaG2OSOw0293vJrT0qiDftmzYRZDUmW6KQU2+b56Bhqw0vsI4PJeaOS3AUXXLCBKEzn2/6XQgnPte923JVPdyzWKVgSNcyRsKjK8wjCiyp/cpd7vsG3P10TWPx+/PHH15UrvyxMfiFY6svBbG1IyRtat6lvBGraFc0SvDVJmry+4SCAI8z840R0BYB7AXwfJq+b/WlmXiaiBQCfAPBmAC8B+NfM/Fx2yTtAzcSm06Bqh2mbLR+zebmZJ+/n9r2/Ofb6hTikcpuJco85F8l2Pca7rl+HEE3y5wE8I/3/bQAfYeY3AjgO4I4m/Q4Ax5v0jzT5ghC7ytaOHJqFrS9yaiy55fct25WulnnkyJEsr5BNGV+56w1pj00mHdpcSIUMIuhffnxZn+BFkkS0G8C/BPA/m/8E4AYAn2yy3IPJGxMB4JbmP5rjN5JHz9QwOHNNGpNsNSN3+13lu/Lp0nX5Tp065S1/aFu6Gju+db/yyivB5brqbOOcvsF3u/3fAfxXANub/98H4AQzi+dWHQZwWfP7MgDPAwAzj4noZJP/e3KBRLQPwD4A2LSpGv+RFaUGUR9XVx10bfXx7NqiEExbT7E1FGnM5vu9cz4xKhRt3nboU4fcr3LfhZYTA53ppA8k6/Pe7R8HcIyZv0xE1+eqmJn3A9gPAFu2bOHUzqqBaGLb0IeBEgu1baEPvNCRpZx+5swZY12u9BC0ETakkkbMA09MaW0RoQ/6dr+6jwr3DgD/iohuBrAFwOsA/D6AHUS0qdEmdwM40uQ/AmAPgMNEtAnAhZg4cIoid4d3/USeWUWMBmlKVzXJVLTxQBNfJ1NJGXxRevvdF7J02iSZ+UPMvJuZLwdwG4CHmfnfADgA4CebbLcD+HTz+/7mP5rjDyeriR2gpH1uwAS2/rRphfKxtbU1HD582Nsu6KrT51jKJ9XJZOubviLWodNWP6QYA38JwL1E9JsAvgrg7ib9bgB/QkSHALyMCbHOHGwXqIatf0mEDk7fIHI1v0mrVI+98sor2LVr1zq7pGqj1Mmdc5KFXPPYem12xJBzY1GClFz36YdAPi+nrEEkycyPAHik+f0tANdp8pwF8FOxArkaV8Otcznzlm5PDVqHTgafbafv7YTLy8s4e/YsNm/e7Kw3BqEkX6J83zpqdIaEyp3rrqJcqMKtHLKFDZ1wsWhroNU2oNuC2m4f+6TJLrm2toalpSVs3ry5iIZfmgDbGAN9GWchxNeH7XY18F11UssYUA6urbXpwRfi/4svvoitW7da7Vultos25KjT9xFttvPbHt8x9ekeZJJiYsiFmSBJH8R0cFtaa83IsQDF1ueKe5Qn0WuvvYaVlRWnNpmKVMIylWNDDltiLFGanFilUZPn+7whSRe6UPFn5UlDJRw5crmmpwKpdR89ehSXX3551mdM5tDidEjRtHKhBgLygaxhdiFzNSTZldbW5UDxrbtGY3wKQu2GPp5vZsbp06exvLyc9Q6uVE0xlgx9ZBmNRtpHxfmcGwrX+bGOTZ+x0CVBAhWRpA6mrVdqWX1Dn2UPhcuhY3PmrK6u4tSpU7jwwguTZMixOKdonD7nhjg7a9m6htZvUpzabkfVJCnDFQZiO2dAe2jLhmmKg3zppZeCXutQ6r7u0DbmIJC+wyf877zebvvCx7A/IAylHC+uunLWK8paWVnBeDz2fvl8KUKMjZXVkb+u7NCYwlibe9f2QBVdbMGpkoa/CuAbXcuRCRdDeeJRjzG0pU4MbcmDf8rMl7gy1aJJfoOZr+1aiBwgooNDW+rD0JY60Ye2DO+4GTBgwAALBpIcMGDAAAtqIcn9XQuQEUNb6sTQljpRfVuqcNwMGDBgQK2oRZMcMGDAgCrROUkS0U1E9A0iOkREd3UtjwtE9DEiOkZET0lpFxHRg0T0zeZ7Z5NORPQHTdueJKIf7k7yjSCiPUR0gIi+TkRPE9HPN+m9aw8RbSGiLxHR3zVt+fUm/QoieqyR+c+JaHOTvtD8P9Qcv7xL+VUQ0RwRfZWIPtP872s7niOirxHRE0R0sEnr1fjqlCSJaA7AHwJ4H4CrAHyAiK7qUiYPfBzATUraXQAeYua9AB5q/gOTdu1tPvsAfLQlGX0xBvCLzHwVgLcBuLPp/z62ZwnADcz8QwCuAXATEb0NBd8PXxitvee+BfwIM18jhfr0a3yJ6P0uPgDeDuCz0v8PAfhQlzJ5yn05gKek/98AsKv5vQuTuE8A+CMAH9Dlq/GDyXuK3tv39gC4AMBXALwVk0DlTep4A/BZAG9vfm9q8lHXsjfy7MaEPG4A8BkA1Md2NDI9B+BiJa1X46vr7fb0Hd0N5Pd39wmXMvPR5vcLAC5tfvemfc027U0AHkNP29NsUZ8AcAzAgwCehef74QGI98PXAPGee3EDuvd77lFXOwCAAXyOiL5MRPuatF6Nr1ruuJkZMDMTUa9CBohoG4C/APALzPyKci9xb9rDzKsAriGiHQA+BeAHOhYpGFToPfcd4p3MfISIXg/gQSL6e/lgH8ZX15qkeEe3gPz+7j7hRSLaBQDN97Emvfr2EdE8JgT5p8z8l01yb9sDAMx8ApNXHr8dzfvhm0O698ODWnw/vAfEe+6fA3AvJlvu6Xvumzx9aAcAgJmPNN/HMFm4rkPPxlfXJPk4gL2N524zJq+fvb9jmWIgv2v8dqx/B/nPNF67twE4KW0zOgdNVMa7ATzDzL8nHepde4jokkaDBBEtYmJbfQY9ez88z9B77oloKxFtF78B/BiAp9C38dW1URTAzQD+ARP70X/rWh4Pef8MwFEAK5jYTO7AxAb0EIBvAvgrABc1eQkT7/2zAL4G4Nqu5Vfa8k5MbEZPAnii+dzcx/YAuBqT978/iclE/JUm/Q0AvgTgEID/A2ChSd/S/D/UHH9D123QtOl6AJ/pazsamf+u+Twt5nffxtdwx82AAQMGWND1dnvAgAEDqsZAkgMGDBhgwUCSAwYMGGDBQJIDBgwYYMFAkgMGDBhgwUCSAwYMGGDBQJIDBgwYYMFAkgMGDBhgwf8HIqLe3P5IkYwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Depth data\")\n",
    "plt.imshow(frameData.imgD);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RGB Image\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"RGB Image\")\n",
    "plt.imshow(frameData.imgRGB);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Annotated Image\n"
     ]
    },
    {
     "data": {
      "image/png": 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BiLRE5CzgfsB/DXBESo3N7UgE6hkqI2Rfdw61USSXY1VLUkT+EXgMcLyI7AJeBjxGRM6mam7fDDwLQFWvE5EPAdcDDrhk1ZFt6rzbWfySIhGANqMNG9hRXYikEzmcVUVSVX9ridXvXqH8q4FXr6USQZR5jXm3IxEAM58DYyM7XzFVQIhGynI04s4YEUz0QIhEKjag6fuwXzr25lwPi0aIpACT7fUKdBSJbC5sNuIUCLGlvSKNEEmAfK670VWIRBpBx40unexN138LfJztthLNEEmFVqu10bWIRBqBG2Fze2rvboiO5CvSDJEEtDlViUQ2lFunRzexIrgyTklchUYokyLRmTUS2QDUe4j5pVakIcqkqDSkKpHIPQjnenFK4io0RpmU+DaLREbNvrvvAhNFciWaI5Ih+iFEIqNmampqo6vQeJojki6+zSKRUTO1f3rkUYc2G40QScEgsU8yEhk5ea8AOxzn9as/+mSu/uiTD1ve7DRGmYKLze1I5Md/sX2k5yvLGKJwNRoR6VYVjMREYJGIxzPKn6U7xP2nb/097MkfXXZ5cbk+/fXHIo2wJEUEHXEMvUikibgw2r55Vzge9kuvXfg8iNgdKpjHOo0QSdXYcRyJQDN/C0uJYn/5niCUjRBJUcHNFxtdjUhkw2m3RhtwV8zS/snLDbocK4Mxa2FVkRSRM0Tk8yJyvYhcJyLPrdfvFJHPiMgP6v876vUiIm8RkRtF5Fsics6qtdDAiJ+NSKSR9DrzIz2fGTC4xT3JcjyUQSxJR5Uy9oHAI4FLROSBwIuBq1T1fsBV9WeAX6bKbXM/qpSxb1+9FsLE1hgFKBJJ09EOYPre4RkBBhHEvovPPcGyHCR9wx3AHfXyrIjcQJVL+3yq3DcA7wO+ALyoXn+FVp0rXxWR7SJySn2cZenGgZtIhDDiYBPpKj+7pYRy8Wj3cmWPJYtzTb4GInIm8FDgP4GTFgnfncBJ9fJpwK2LdttVrztIJEXkYipLk8mtx3HNd38EPGJttY9ERsAvvH/PYeue//FJgit5yr9sGeq5khGHCc+SpRuTq4ncsSSCqzGwSIrIJPAR4HmqOrM47aWqqsjagtKp6mXAZQDbTzhD53sxOnKkeSwlkABvfNJctfDkg5/bh/6/H+HN8qwjPt8oR1Kv/pfLY777ARjoOxGRlEog/0FV/6VefVc//3b9/+56/W3AGYt2P71etyw7tm/jz5//h2updySyrvzB/r/h0um/XPN+3/j7pywrrINgRjiPet/sHIWP0bdWY5C820KVQvYGVX3Dok1XAs8EXlP//9ii9c8WkQ9StZ+nV+uPJJS86oTfgNcevPoN8/9EywjHvTRamZHRYicSTPvI07r+wvv38MWnH7/m/VppyqiiBu7ZPwNhdPl0NiuDNLd/Dng68G0RubZe9xIqcfyQiFwE3AL8Zr3tk8CvADcCHeB3VzuB2KX9f14w8bRq4bVLbj4i3iSfBSqn3VNeeOfwDhw5ZnjK/rdxQpbz2X868mYzHJlQGjnQ/L30wrO59PJrVyhdlQEOKrd4v5WOMT09RTYRs5SuxiCj219m+aST5y1RXoFL1lKJTre3luJHxfP08Qc+DEl83zvxNXINkFiKEPDec8qzbxzOwSMjZzw1TGYr/zTSn3oqAOV1H16x3AvH38trO6vaCQt0isqM7IvfUiwljIduW+0YAEVR4Bs4w6dpNCLABZvc/ed353/m8JVHKcCfuPcP8N7jnENEKDVgxWIUiqdffXQHjyzLxelH2daC1AxnBth/vvNJfPHpg5fXVgvc0gK4FEsKZd+KXOUYefB4okiuRiNEMrWW2Ot4ML92y/2W31gL8O7zdnHCVacftrwSn7rvzRACIoJXJRjBi8Gp4FQIv/6Fo6/8JubkHRmFK7nPqScMVL5vUcIBqzL9qaceZGGed81jAbjqnM8vLC/LUytxO9RaXM4qXGp9v4m92jEmTns0dH54j4rocyQ0QiQzK1Ek18ju83Yd0X6/eOOZKxc4Agv4I6ffhIgQbIoC6qvklyaBXgmlKq0L/uNIqjtSbrr0DE7+YIvpDlzxml8feL/yug8fJJaDcNU5nwcGE9DFYresWK7SB7nUMXrlwdZyFMelaYRIzk1PAVV05N//p9/hXU/7h42tUGRNPGXXfVYvtEbx/dv212inKVY940lKqoqIYMbHcUWBBCUxBmsts8/4zyOr+CH4zl62jXnGdk4MvM9qfZJL0RfIQz8PYmmuJJSDsHhff/dXFpajQC5PM0RydpoJTuC33/ZovnrDZ3lG+ttc8esf2OhqjYSlmsx9K3Hx+sUM0qze7Dy79zOw1HjeUnmrBhTg18z+K+PjCRhLt9fDq2CtZW56lpB78r1TzE7tY1t7fVy6r3k28Hvw1ReCakKWteA34NoXTtKyhswKPGVdTg0c3kf58uf8Ljr7jfU74TFCI0Sy1W5x9guPY1d2M5NbxzhxwP6gY4WVms6LBfNIm9iRihdv+dUDHxa5QL4o/wiWhD1778YVBW9/xZOGds7FzXA7PwtA2Z0BFZKyqoTvzpAHpVzngLuHugZFBqMRImnSFt/4wW2cODHBlq0TZLYR1doQlhLFvuUYhXJ92LGlTWotu348z8zscEa1l+qj3NudAWB2qoeRhJ6tRHGu20NWcMXpN7GPqpm9xDGSbQ/BTX/ziI95T0GaEAl52/bjtG0nmRTP9PRefvXXn8ojHvOLXPqAF6++85B55R2XMzYxjkEIzpGJ4fjjj+e3/WEuoUNjKeFbSiT7ZZdrkt8TmuHrwf/xn0e9o91uk05kPH7i/67Led745W2ISenisNZircUYQ6gtSFUlZ3SJwF713GfykMddOrLzNY2rP/rkq1X13NXKNcJk0+BRHCpKKxsjSVP27NvHn33zr9g2fhxmMgMrJElCO22BhxACUrdOfJqgqhgNiCrP3/mbK59wBZK0hceSFwXqPSExFBiuaH8BUUixXJA/akhXfjCHWor9z4cKY2S4ZGkbpz28C5iJ8XU5xxu+shOfe7Ixi8jBQSXSNMVaSwiBPLp5NI5GiKRzjm07J0hcyXHHHUd7fJLCO3y3g9WMhAyTGtK0he/lWJMcEEqA0hIAK4Ih8Ne3vRdjBEnAGIOYdOGtbespkMYc6JwXDEZS7tizmxwHCuPj48zNzHDCzuPo5j2KmS5jY2OEpMX7zedoJRnGpjjnuKD8uaHej6UswiiQ60ee52SJxXvPWKF9R4vhnkMDQQLd+VmyySrAdD+Slqou/I0SHyMADUQjRDJLU579wZ9dtGYKOHgkLgB5/Tf71ccjGBJj0FCNUIoEEKkePFHSzJIklYVpkxYhBIwxtNttvPcLIikiCAYkJaiSe0dihNnZWVxZ0ul0uOnG77Pnrjt4+MMfTrbjeLCWfVNTnHD8iYy1Wrx75t/odLtk7TbPGv+VNV//YlE8VCCXa0IPWg7g/zv5etIsIbUlrXalAMYIxhiU6ociBhKtmn4/+50VHNmPQS5JH8Nl+gUQJZ+agROHf465fI40S8mSFuiBhF9JklQ+piEsNLtHhUazdSAaIZLGrs3lYssjP7tqGQX68U0WB1VZ7bEwVILcX94DbPsZ2Abs5Rvs7RfcDp1dl9BOM2644QbSdovTTz+dt8sn+aOxtQvlWvjn7P8ylgd++P0f8NWvfZ29ecFjfu1XOOUnTsXWL4p2lvGUvQ/h46fcgDGGlrGI8YgK1hqyLMUHj6qAVDNwEixY+PqDbyZJLM55QggLVk7IHMbKYRZQ/4Uz23GIGIyp/h79zfuu630YJklqcM6zr5hbl+MH9QRjCUnAuoQ0TTHGLEw7FZGDWjcjYdTn26Q0QiRlk35ZU70ut333u+zZvZvJLVvYsn07XpU3uyt57pb/Z13O+bbwae6c2s/n/uXjfPO/riaf6zKxbTvv/8DL+MSXb0FESNMUdXVTynlCKOnlOa869/kHHevj5fsAeFL6zIE+93nrnr/De4/31evEJJUo7hxrV2IaAh7l2kfeSlF4rLWoKokI3dzhqIQ1AMYHgvck/ZamsZTeE4zgnCNNUx593QDO6keLcZS+R1fXJ07ZhLQhWCRXsAe6e7z31fc14ub2W1/xF40Qyc2Qw7sRIskmnWS/Z98+9s5MQ2IxaVI1mdbxYf87PkMu4FC6paOb5+TzHU47tWpq95trSVLV5SPbrsGXJeo8MsTfw3OO/4M1lX/zXe8CQKRq3osq3nvGx9tIsNiQLKQtcArWWdQacmNIreWrD74FQiC1FueFXvB0NTBXlGRZRuLhV75/1lFdkxiwicHm69PkNZpgg6mmbZrqRSIbGNilKIpGiORmoBEi2bdINhu79+0lWENZlpRG2NfrYMbaeDf8h//v/aexYy060zOMt8Y5+5xz2NaepHf3Pj48/lPwlXcheY43gtoEp4pIIPiAU4dko83Ct5jnnvT763r8V/zocr70k7fSEkhC1V3iAA8UpScAZai6DqZ781V0pTLnwun/vnCMmdn9ANh8ffK/GyekJsWLI3cOYwxJkmBM9fyktUvQqJjrzo88M+NKXP3RJy8kGGuaVdkIkUxNI6qxZqbu3sf45BbS9jidxJAGR1LmtBie6L+NL+PyAmcdYa5L1oPQKxhnnHPPeSTP/eItC2Wf9IT/trD8sU//iPOfeBaf/cyPefwTzjzomE9Kn7nQlAYOWu5/XtzE7n8+tNyhzfCN4qVnXXhE+z1yUTjUf+T/8LA3/iJtm/De+W387tkzQ6odXPqphLTlcKmAMSQkGEDq/lwrghUhGaVll6U8+JEvGt351sBioWxCc7wZ6rRJ40nundrP5I7tGGsxYkiCIs6zfIziw/nfU/+CGiGxGRKg1WqRZdnCgElRdijznH1GGB+boEwTbvzBj3j91/cuebwP/fs3+M1feijnP7Fqfj7+CfcCDu5nPFT0Du2DHJRDxXSzc/XzP8W9X/4I7tq/G84e3hC3QzEiGBEskPXFMARc7XWBVH2wo0J73ZGdaxBWEsGNtiwHyXFzBnAFVcpYBS5T1TeLyKXAHwC766IvUdVP1vv8BXARVYvnT1T1Uyudw4fN6a/VnmjjvGfL+DgtMYxRCaUJyl/uuoJXnf6MJfd708zHyLtdkiyr4jkGpSzmUe+ZaO/E+gJ1joBiUcgM84WjKEryouS2/fuWPO5r3/z3gPJPn/4OT3viTx/VtS1lXa5W9lgQzFte9p884cO/T5UleWV+7X9/m+xDt6xars+D3/I0EjFkSUoA1FQ/qEIDxjv8KF2A8vnRnWsN9JvcS+X13igGsSQd8Keqeo2IbAGuFpHP1NveqKqvW1xYRB4IXAD8FHAq8FkRub+qLquEa3UBagrWWmxSuW5YVUwI4Fw1kju2fBIpLUpcXlRuICp08hzxjtmZGVIjTI6Nk2UZGgJlCAQUrKPwcwR1bN3WYqkQOe0sY4sRstbh3tArid5aLMK+BbqU9XmsiOVnnvouPrN6sTX7nCdJi9QY8G5hdF9rH8nCe9QIdlSNqnJ0KVM2O6uqk6reoarX1MuzwA3AaSvscj7wQVXNVfVHVAnBHr7SOTpzzXyrrUZqDa1WC2qH7BBC1X9Y/y3FK3/4HnbfeSd7d+/m5ptv5uabb2bv3r3sm5pCRJjavYfZ/fuZm5khz3PK4ClV6UztZ9x4elN3k+rsksd+zh/9Jrbb5bxH33/N13KoUB4qdIeKYr/ZHhmcbpFT+ur7LL2n9B7vPVrHyhzpjJthujscBYf2PS5ed+jyRrGmOyUiZwIPBfpRTp8tIt8SkfeIyI563WnArYt228USoioiF4vI10Xk60W5PiOK601qDYlUTtWFQBECPe/oeUfulk7Vmfd6dDodoPKRcxrAGIyxiCZ05nPyTkmRe/Kuo9MtmesWJJIghcc4j/aWf6k88fxqxPajF98MwFvf8bElyz0pfeaKFt+RCuBmtyLXE++qJHEOxRmpLMlaGEUVGWHObRqUSXYpIXzYkz/aCIGENYikiEwCHwGep6ozwNuB+wBnA3cAr1/LiVX1MlU9V1XPHfFsrKHRTpLKCTp4SoFSwBvBG6G7zJSvoiiYmJxkfHKStNVCRVAjSNJmvtMlzdqkWYux9jit9hg2a0GaQRjHFS327+uIze8PAAAgAElEQVQxNXV4p/v2C/6B7Rf8A497xK8uCCRAD88VH/rKgnit5ijeZykRXbzuUKtzNdGNVEKIGAqUIBAEnB6Y0bRSuLRhc+ZPPWhk5xqEpgjiUgw0ui0iKZVA/oOq/guAqt61aPvfAZ+oP94GnLFo99PrdcsysWXrGqrcHHzpCAIYszD/Nvceawy5D1zyzTfwtoe8AIAXfOet+LJkPu9x0tbJypHXdXFlgRYGYwM2MSRZSjYxBq0Em6SMJxntxDLfm6GVZZQdj+8t/2OaOcQqf+EfLp+rZbXBmL7wLW5aHyqOSzW7o1gujWg106YMDqGeAqtauQMBRkc3reJBD3oot8duyYEYZHRbgHcDN6jqGxatP0VV76g/Phn4Tr18JfABEXkD1cDN/YD/WukctiFBdp/3qCsWlt/0paVHpheX/a0/fjUdlEBgqwPw9SwKj0qgNMJF1/5vjDHkQGIylB5z89NMTraZyDxplqEWslBQaIFpKWGixG7fStELGAJtaTFvS1BPq+ixY4Wvbe/80hbsUv2NKwnfofsuJ6hLuRJFlsFAUXaxxhCcw9eubx4wqjDCqDzT810Yne/6pmYQdfo54OnAt0WkH5rnJcBvicjZVC+/m4FnAajqdSLyIeB6qpHxS1Ya2QYIDQnZ9KYvPYPnPeqKVQWyj4TKGdhYgyscIlqNeCOAQBFoJxZXOpK8w3hrDFpt8J47d+1ibKxNuz1G2csRB5kq++/cw+zuPdzrPvdlbHwrrcxgXA+Xz5IbQ1nOMzO9l+VC1czNHuiv/OjFN/OtE67kzAc9hH9++nsOK7tSU3uldcsN6kRWQRWhanEkaYqvp2f257Ub1TV42B4deZ7D+oTOPOZYVSRV9css7R39yRX2eTXw6kErYcz6Pxp9K3EpAVxuW18wD93e//yBd/wlf/Tyd+JLJSHlLZdetLDvn7/iPRhr8E6QEPjL//U7ADzjd/4nd0zvIWlbyEtaCqmHpFc5Et+x7y7O/Mn7cfoJJ9Ian8C6Ht53aKWBzuwMc51prrv+2/DffnLJ63zkIw6Obbln912cVnbWdrMi60MIGDVVf2QIC03rxVGVRiWS88HRGtG5NjvNaOeuY4f14ib04s+LxW/Q/ZeyMl1RElDe8uo/PGj937z093jJK97LK1964UHrP3XN10i2T2ISQ0sD42qxnYLJnmey3ea4E05hy47juHPffm7ft5cTTz6FrVu2c+uuW5jfu48yOMa3Ld+He+ZZ94FF0b7uuvtOpqaWnp0TGS2psaRpSu7KyoKsw6NZa5EQMBMredYNl9/4neqF/vGP/Whk59ysNEMkR/D6PNQKXGrbSvse2l/5vEddwdMveQUJgbe/+k+W3G//9IH5v2e84ksHbbv18j+D0kGpQMKDtp/C3pk5itl9bH3AmYydcAI7jz+eLdu2IWK465pZ8rkOO7Zs5eQz771sYMy54uAN+/fvx7tN6j5wjFEGjy/yOjB01ez2ta9kasza/PGGxJPOPxA9KQrm0jRCJEcZKG1QC3Jx+eVwztGdX95n8fSzlo+DeMaFB01UOiid9GeBz94K3FpShf0F0nMOdEPuhC1LHPOh3/8kPbby8fEP0Aqeu2++mfleSTG6KcGRFcidI7N1UDg54CfZj6C/0UTBXJpmiOTGPx9HRJJYzCKJf9YL3sDcXIfCBT78npfyjn3bRlqfb9z/kIjox8Op//o6fDO+5ns8ppVhEoOEKtVIXxi99xsaW3Ip+oIZxbIhIhlGoJJrsR4H5f1vexm//Ycv48Ln/BWXv/UveOcbXjD0cxwte/bupygKLvrCq3n3Y/7nRlfnHo1XJXclmRiERekvYOT5bQZlsXUJ90zRbIZIjvAlurj5PKirz1Jl+8324ASngadc/HI+ctnLFrb3+yAP7YscJadd+TZm7BhpAOti0qeNxvuA1oEtrDVYQFEqB7lmWZJ9fiKdwyUWn1g8yu9ccAKFc3z4n/dvdNVGRiNE0oygqTGoIK5FRH/74pcSSoco7JhMecnL38X75QFHVc9hUhQ5wTmcc4RRzguOLI0P4APBVLElTT1Y0w9wMUyu//QH6PZKvCSoSQgWipDj1bOFhG1JRisRct8jtCy5V2zhyQpFpY5vKfCN4JF2i25R4NEFB/gdqaE91mKilXHj7ocMte5NoxEiaTdprg0blAQhM8IpO7ZzeYMEEqo85N57TJJQ5Mfm6M2wA/+u5+yhVASCYus/qedtW2PQIbzEPvG3r+PUE0/ihNO2Mzk5yZZtCfNFiTdCiYKDoI6J0GLMWiyKw9LTgFqLaSekqSF3JSqCNYYxW6VjljTBWBBr6fYKREDzHjO9OY5PPlulCgmevf6Xh3CnmkUjRFLW0chZS5N6rYQykCqI9VxuHrxu5zlSnC9IkoQka7Fn39KBeiOjo52k1YurLKpgFqr4EKqI5NYctXP3rz37z3jva1/JKZ0JTjnlZJJWVsUjTYRgFDFKkqQkZTULrHQ5pXEEKzgREjE4DaTjKa52T5LgSJOEsshRH7BJQuIdNk1BqhF7kwhlbSFv0Y9XyUuMZd6tb2rlUdEIkRxFc3s9CN6jBP79Xr+07ue69aWPWlP/5kkffwMiyvz8HEVRoA2ZH79eLGcBrmQZLp6PvprleCTHP5TgHAFIagfy0nuwBl8L0jD43Rf+Ly5/8yvYO3MjJ55yIpNbxknTFkEDwTlS26Jb5MxMT5MY6GpOmVlCmtAtAzN37GZ6foqyLBERLEIrywjOYRHGx8dJ05QgVWR1Yy1iLZpYbJKgRgjBkXcKstZHkMSQm+ZEGT8Sju1fznojghth6olBhPLWlz4KgMkHPp7JeoZH6RTdpMnWBmG5KOuDrF/LsRcf50jibXrvMcbglcqKRPEKwQjlEPuMt510L/bc8WN23bUbuw9OP/1ktm7dSpZkGCfsn5nhzh/fQiszSMsQWgm21Ua7BXfe8mNmOvsJIZAmCRahzPMq3qVUfaeuLNH6epxU2Smp46KSpdg0JRGDSROwFjv2TVoT40gi3PuMFw7tOkdFIzoDm+BIeyQEYaT+bWuxJJPULvR39cO4HcusZOGtJZDHoMc/kuMEKjcgXRDIern+GxZPvuBC5ktPt3Tsm5piz549zExNUfZKQunpdrtMz88zMzfH/Pw8nU6Hbq+DKwqCOoIv0eAgOFCHsWCtYBNTBTQXpdVKabUzxloZ42MtkjRDjKkCB/tA3p2nOztDd98e5vbuZu/NP2LPTTdx9eefxTe+/JyhXesoaIZ5sTlb25R19JYjpW/1wdIC2N9+2JTG2qJcbjvAt7/5Kc55wGMBSNOU5zztXODomotNZdAI60s1rwe1ClcKFTcwxhC8xxuDqBJUcQLOB0od7ktsrueYNAlFqezZu5/ObIeTd57A5NgEe6an6JRdej0HHUXGWzAFJnfMT0+joQSUgHL/89461HptRhohkkY3p0oacsZ0OKPGiwVvsXiuVr6/vJRQZibh+zd/hlf9z/9YWHc0zcXNyHIvhaM5xpFiXagikbuq2WpEIHisKm0/3NZUS8HPdSnm5yjLjFnbQcscsZZOt0Q0odsrMAJJr8CXJS0xmCIhScYptYRg+e5nXoArA0mSEIAHPvF1q577WKMZIrkJB24+9IYxTprQo+6v6IvbUsK4WvN6pX3P+ekn4IvV+0s3swW5FhZbzItzjw+67zCDCy/kszHVwIgy/PgFVgNGoW0zunNdctdjtjPL5LYtjKUTaJpRmoK81wMxuKKEJMGLQdRjtIqX6lUQkXoQB67/tz8lWEMu8LAnvHbItW4mzeiTHGmIi+FgJCF3ga4O5xaudWbOauXLEChHmOy+aSwepDlU3JbadiiH7jMMy3vxt+E0VP6HtYEw9B5jCQT1JEk1kt5utxER5ufn6c13aCUpO3bsYGJykhKl0MC8d/QIaGIxdV+2FUV9eeAvFASfYxLlG1c9n29e9Xy+fdXzhl37RjFI+oY28EWgVZf/Z1V9mYicBXwQOA64Gni6qhYi0gKuAB4G7AWepqo3r3iOEQTdHTaiSrd0fOGBv7XRVVmSIihpPVjzN6/7MNtOOZ1PXPiOY66ZfaQR0480Kvsgx14Oj1atJlMFt3AhoPXysKO8GCN41xfhQJolFL56cXbyOXLTI2lltMbHyMbazHe7VZrb2VlccIiGyrwNlZvbARn3CFL3W0JQTwiBb3/mj0mtkBgDarjvY9881OvZSAZpbufA41R1rk4I9mUR+TfgBcAbVfWDIvIO4CKqDIoXAftV9b4icgHw18DTVjrBKAJcDJu8V5BMHn38+0H6H4+E7333c9z/rJ8H4M//7Knrco7I2nCqWAPiPcHWXgf1CPewvQ9aYwk9nxOcx1hZcD/KkhYmr86X51Ue8DRNGZ+cpAyeaQ2EzizqK88NRbDWQr/JbRI0BAjuQCR1DSiK91UfKwjXffqSao56K+OBj37jUK9t1AySvkE5EOs6rf8UeBzw2/X69wGXUonk+fUywD8Dfysioiv5+WzCPsnZzhy2NbzeisXN56MJirF44CfHc/ZDfplrv/lvC9uXSgkbGQ1BKkcOTz3bRljIczPsJGAheMQEQp2crvqJGRAlSSwaKj/HMs8pigJbFCStrPKnHB+nNzNL3u0AHheqPDym7iJw6lGt557bKuK6UTASMLWrii99db0h8O0vPG8h4tFDHveWoV7nKBg0paylalLfF3gbcBMwpbowtLsL6MeePw24FUBVnYhMUzXJ9xxyzIuBiwHGJpYKIdtsRAT1R9/nN6ggriSih31+2K8heZdybo5S4K/fcSUyPsmXLjq2mtqbicmXnEfuPbiSicRWgzV1U1tEUDvc4QEXcoJ6qh7/gNbpajUIXpXEVP2O6gXnHK7Xo8xzTJJgxyZpb9mOJG163Vl8maPqEBRrLKmxONVqPnEAHwJiDCFUZ6sEU7BCNZUxTShDgBC47nPPhRDwAgbLT5/3pqFe93owkEjW2Q7PFpHtwEeB/3a0J1bVy4DLACa2Hb/p2tutdkpim1ftE656F/tEyL2vfO/aKTKWUgzZDy+yNrxWo9mhth5FlRAUV8eTHPaEirIs8a4grYOcBEBFUBXwQqhniokI7TRb2CfvdNnfDbTHx7FJQmtyG0nZRcsC5wpKV6DBV3l5kDovqEDfhal2jE/SlCSx9JyrLOUQFroVVJXSQ5pYrrvqz0lsChp4wGP/aqj3YFisyQVIVadE5PPAzwLbRSSprcnTgdvqYrcBZwC7RCQBtlEN4CxLoBkpZQflNc+6le0nHoe6o3v7r0esybQlTBSmCjrgCsgLWoUjSWKS5Y2kRcAGB8FTWoORSrTEGnxeIG54v4G/ecWfk5oMDSVFr0Mrs+S9klZ7jF4vhzSjDB5jpEqLXM+madsUa8HljtCdQzPDeCtjR3sLZVHg1THV7VDOTuFNAhpIjMFVJiRGBFEBCXhRvC+xpt+vmVQvBl91N6RWMFRBN4J3+LLk2n99NhpKVJW2Gh54/juGdk8Arv38Rdg0wxhDQjrwfoOMbp8AlLVAjgFPoBqM+TzwG1Qj3M8EPlbvcmX9+Sv19s+t2B8JI03KPgwe95jHkE2M0UrT5fPqbhCCQ12BlgVowEgVlkuH+COMrB0DJArG2GpUW7Wa6xwqay5JhueynCYZPp9jfGyS/XOz9GanaY9NVPEsa7/HJElIEltPRfSoCyABSYRt2SSdXs583mW2yJEsI0WQxDK5dQvdyXF6U1NQljivEAJBoG0SqmhwAa+usloBkYCxtm7yV9feF4TgFLxU6XatEFRQPAHh+//+HIyFoih44K++86juydWfeiakCRAIUr0cBmWQb+YU4H11v6QBPqSqnxCR64EPisirgG8A767Lvxt4v4jcCOwDLljtBJstHmzemaeTd2m1WnDyRtfmYIyxtNKU0iRIgESSyu1kyDM6Imuj39S09ZRErTMmighFUXDaTzx0aOcyQLcouP9PnMW9TzuJ8bGUvXv288ObfgS1k7gRwWLwIqRJthCv0CYCDrJ2m5BYim6HznyXljVIYnFk2JZl287j6M7PVyHUimo4KhiLEnBOMGZRF4KAU1f3jgbAUMlJXUarmLImEQJK0KoJn4ec4AJC4NufuJBEqoEnX5b89Pl/v6Z7kk2MoyIEqb4H74qB9x1kdPtbwGHfoKr+EHj4Eut7wJp8TlpjY2spvuH4TpfpssQJjRNJXzrKwi84A6dpSmIzihFGK4ocTmosqFbNU+fQACrVKLcZ8vvLFQXqPWNjY6gTZuZmmJ6epigKsqwFQXDe1yltA7nmYKrgFT73pMHgMXg8RizWKokYSq+UeUGajBNUyVrjJElCLj2CL3Had+cTJCxy/ZSqCd4f4VZ14OvmOQfE0jlXxdkEci1QAsZAIgaLAa2DFYvhW5+8kGx8jFbW5qz/vrqLUdYaR0zVteBVSb2hGDDEaiOmJUpebnQV1oQrSgQljDI5z4DkhcNpwAcQkzLf7TE332Gmu7nu8bFGnue005Tu3Dzj7TZBq8AWwNAdyX3pEBG++93vMje7H+e6hFIr9xwfUDyiii8ry06SFFSrpjMCkhC8o/CBlhXGsjYJiqFKZDa3b4p2bdgYEVrZGHlRTbDAV32QqoFQO78YAdTgQ1n5WFI5u4sIwQeCqwavxAZsHVlLrAUVUEUQfFASlTosm0HUUhQBcHzvP/6k6ufMMu73s68/7H5c/bk/wkggzSytVkZiq5H1QWmESAa/+UZeQwhgB+/8HRVdH0hbbZxztCcn2L1vive+//2Y1jj3WsODERkupg5gmyQJVmvXYK18J5Mhpy8REVppysz8HKUrydIUi2IDZDYhqKmC5lI5gxdFUTWCraAiJAQQW6W/pXZ0NwaLkFqLFyi6DiNhoW9zcmwS6mPlRRfvHaoGpEqfG7QEDNh6ymPoN8f7TuqGQOWHqXhCcBgxiFQDQxIMTgQrUlm8PoARChcwFvKioNcrueazf4wGEKrznP34NyNBUQ149RShmqqZpIPf80aIZLme+RvWAe89QUP9imwWjtoiMJYCCImlkxecdPzJwPxGV+8eS1L3RWbGYlXRWihFh59O1hUFUGATS0k1oVBq1yMNAbPQH1gH1lCDGEUxYAx5z1U+nCJ4DRRlPRJuK1dxgyEFvAs47/BFSdZKabVatJIMo4I3vgrK60tCUVBZqAK2OueBlLogUnUNVdMdtYrl4MEkBmtsPYyjiCQgFkyVLygkgrGKSYS2MSRZG8HQ65a4vLJar/n3Syp/ZvEE5ylLMJlhvju4j3MjRFI2UUDJj73KYa3F1/5nTeK4//pH7i5LUpRWq4XmOSRV1rt0bIwokhuHMaZqMRmLBF2YZKaAHfLzX82wMQsBTtQIipIs9AkGfBA81ayYxBqchKo/MQS0GocB8YixiFQirqqV1qnSsimSpJShysbp85LcaxWUN0CatEkT8KHAh4ygJc4XaH8kPZGDLMmFY0vleZnZFEEwahGboFKJqWrltO4J+OAwVqtISqrgHEqC84qRBCPVS8EHKkd4azAoWlZdUoPSCJG0m0cj8caiLUvuPELOqV96B7c/6g83uloATI6PM2MNiSkpfIkbE+yWCeZ7nmxre6Ord49l8oU/T0dLEmsotCAVraw5Y1CxlEPubjIWxHm07GE10FaLF4OxgpCQikVFKbAU6hcGR0Ldogu2DuMmtlpvLd362E4Vp4IXrfo2EyFrp3Q6HXoux9oqIr4pHGNjYxhrsWooCkj7TXwLpTjE1iHj1CMakOCQug7GpPgAzlcvFGvrriKpBl9SyQghQfGoA4zB9wIh5CBgWkKWWMpSq4AddUT16hgpsoa4S40QSb+JmtvduS7GBXxioHSkheMBX3wnwSb84Ocu2tC6ZaRMSoYVgxFPoQaDoZVYdk5so8OuDa3fPZFtL350NWoLSGIXMg6KCIEqQYwZcp+keg/qsVJZkFrP6glUM36CVnOxA0rA43yd1MsYEiOYtLZ2NdT9AdU888riq7oZS6lDvQESBFIDDrx6cA6bpThfOYan1tYiV7W+NCg2NYQQCJSYxaESaz/OUE91NFKV8+Hg5rEJblH6FFM16/tTJaspTNT+TtS9CKhAqDuD7Ross0aIpG6igZu5qRm0lTHd7SAiTGAIY+OIbXPqv70DJAVjuf2JF468biYZx4eE0Mspy0BqkioKdhFoa0Zn5DWK2KAYMaSJpZW1KIuiypZoEkIIVT7sIUd1VTwq1UCMD/XMKyeV25FVEtvCo6gEBEvw1aCKmv7UxYBqNde6isVR+XWqHMjTA7YSJaWKXUnVDy6JQZIEV7iFeJmJMdVgTT/4hfeor5x/xLaxKBpKxCR1wjGhk3cx9cvEe79gofZ9L6U+tiQWwVfCX8/cM2rABYw1JICvhbHfJ7ug9APSCJG0m0gk756eQ9OEwlROwLvnOpx64smM7dzC1q3bmdo/z/zsLP6f3ko2Mc58d55WO6XnS5JWSifvMbd/P2f87iuGXrfv3HYnd/7wx5jQRaTEFwXVV5xy5779ZEM/Y2Q1evNVP7AvDDhPZ24O126TppVnRHCumpQwRJKkinfuvCJaEhRU6v5QEUqp5nL7aho3mBQxtd+iKKEsK7ECjDX1QExt4RkhCZX49mfQVFhIDEmaYoBWK6EsS3q9Hp1Oh1arVWVQNKa2LhOoY1GGoKha8LLwvkiyFv141tYe2K8/95tEqsRjUlvKBlQNdYo1xHusr5PhIZjEgvqqL9L7yrQc9H4O7Zs5CjZTtsR9vuqLoduBHTv4jadewMMf9jNsPfU0xie2snffDJ35HnfdvZvv/fAmbvjB9aStlJN3buPkk09ibLzNzp072bljEmPbjGVb2H33Pu7ct5e8LOsv3DA+Ps74eOWs284ytollvDWON5apTpd907PMz89z1113450i4uk9/Gwe8QvnctJYwpYtLeaLLt28JPEJ977XmXztI+/d6Nt3j6Ps5UxMTKDq8WVJlmV4VVyeQwiUeT705z/NLIhBC4dXU2U8TCypyQhBq+cM8JbaFymASTEWTACVpHLcCFWfoVJZZ4qgLlSh07BVs96YOp1sFWvSO8WFErtoxk2SJNVIdz3LxRgDUg2ASm25em8QzEIUh2q0PSyIYpqmC0JZlmXdx1hFNwoa6ticDg0BsUJiLWVZ1i+MeuqnTRC0SsQmOnDECGmCQJlkXN/4heYEhr1z6oXcccuPuc9ppzGZpXR6PbqJQec7FHPzBFXunp/ljHvfmzNPO72KfJImFIUHSetk8ELhHWk7Y2LLGBPB0xJBQ1H5yqUJopAXsGvXHPMiOK1jDdZYhFCW4ANjSQvnhTwoziwKr68BvMOkjrGdjgedfhwnjkFiIA8BSQxFDtvGoXBUc4UTKBVmcvjG9/cx28soy8D2zCyaFaEHRh2pZ++4UOWIxmM1cPx4i9OPn6A1BndOOTpFl7F2yonHtwmlsm/vXvZPzzPf9XQLz1fOf/WGfacbxY7nPhLvPWKULMsqCw4DePCBsughQXnAOecN5Xwvf+5FjG3JGGunuJCTd/uWbBUMl2DRECqRNLUPUh0XMjNSzfEPSfWcqJL0XZRM1RwPRuq84dXMIWOr7cZUwXmVgHpPZmwVe9I5rFTh2KpR/coiTdtplcPbObzXqs+ynuttVPBSLszzro5/sOUXTB0nUyu/SkKoIhvVz+2WzFYj9QZ6vR6lL6qUuLUwO3WEubmrVfXc1e5pIyzJE047fcXtreyvme526Gngvmfei3vtzJjbW9JzPbw1WJPS8TCviijssJYxa5gp5ihSw1lnTuI6VXSTnWMJ3SnH9N37mWiPV7MFgrK/ZfEKe/d12B5mOfHBJ2G1pOjOMbFjBwIcd/zJSK/AC5xUFphWRl54MoTM5YwlLRRD6JXYVkawCRNjYyQCE9YgRZdW9v+39+7Bst1Xfednrd9v793nvnT1sl5+yJYU2Y7xAwzYgRDhlCnscSUzVGYKZlLgDBkTAgECNuCiEmaS8qQcCDbkNSY8jCsBwpgww7iGOAQspsgwgJ3Yxi8h2bJsybaeV/dxTnfv/futNX+sX/e9ukhX50pXOuda/a3qOt27d3f/9rl911m/tdb3+1WGPihW80k4eWwOO9v0eUaXe6ZaQ+bfwWuhN6eXxDgVXBRNiQ4YxzlDVmbJGHLl4Fbikply/UG4Yog6+ogyAQzwN77xQ0/Dv+SfxY/96kspdCwr3Hz7u5nPF/zbl+6PaYCnA6eWCyA6zm7xx210i0arG6MZ/QWsSbpPTAXKfIG40Q09irMww8vp7bFABBgHKE3irJmUkXFTkq+41UKLP+BKToq5obT6nxvq0volgjnr8biUUgTbnPFSg5LpBcmFpF1s5zWaM4hiHvzqlIZ1kERs/X4iIfZrTR8kPjWG1nPbwrs788USFRi2BmazGZ0lzOLzS63Rat8l9kWQ7PqB8dSPs10LlmJ+6+glh7n04EFOHjtGOXUS5nOuuOxSrpj1+DboYpstjJ2xMvSHKK6MZlHQXYx0SdmykYNbh7BTcKiHUjO2BC3xV/wnvutTe33pX/Z427d+FIC/+56vQsXYOtjzHbf9K37p5v9pj1f29ODsLMjOCEa4R/J0IQV39XRzBKt0fdtxNBWelZYlgDULvgh28TOJYp5W097rzM9bAmJIdKBbI1m8Bdx2W2G1Q00ptuWrz48aZNTzU6po6ts2GsDXDE0RAVfcDUHXvI3V71JaM0Ya/7t6XQ+mu5do+ritOeHWxowU6HJmUXdP090XQRJzPvD2Y2cdfLTB5/vabYOLDe/49tOZ7Pe++2b+9qf/BcOwxYEDwtsue+PeLewpxmxrqwXKEIlwFQY0OsTilKqh2n2hoErXdTiJUkeWozF0HSl1qMLkE7Xaut0iVLrUI4T4RqeJxVLWQWg1wrMSzV1Vg8RlnT3+WQRTByCLYC3IapeZpYR5ptR5BDgtoGktk3nweqIAACAASURBVHam2IdJDMKbOZJjjEglUUqJgqrGSI/gdP2M3DQqrU5MdcJswoozjhNJQJt0oKgyGwZ2Wpb/eNgXQXLvq6IbPJ34Z2+8bX3/J9/3Vbx98W62FxP/4OiXX3aZtjqYT1yydYCZxtaTBJMbp4qwqIX5tORTn/pPvPCFX/ekPy9vtRnMInS6xWIs7IyFw1szUirkoTDXxDguWXEjJyv0fU8BJg93RPGYsVSBamWtR6qqsIScO2jbXtFurbpubhRW6aUwuSFJKdVCIs4qg2YO6gxPhstEYR5yiU5ksa6IhO1DrRMiRs59s4QI7nmvMxpHkiqFQkGShNKPgukWxlY0yFLMebqNrUwgDNLteiRuXwTJDZ65ePMbzqiVft3f4a//yldx74Mn+MArvm/vFnUB8Scfvz042w7XPusqjt1/P12nDAcOkA9vceTSo4xzxacL45HeiVKnCZWESKLvlTo5y+WSJJXZkNmaBXtlHEfMjJwUsaazWCuJWZMwi0FyVY3xIW3bZ7GYOXQPt0ca/7pGcNSYJ4r6YeNfimoMtGuIa4zWstLGCV8s5jGaIxnVjGF0NhBtLsfGBbOtQ3g1OnHQjKaOqh7THQpewS1qlCknElAMJGWSG15i6z9NFuIbu8S+CJJmF+YLssHFj3/9bR/iW951E6/90M/wyT/6E+7+7n+110t6Uvji/cfpUkKsYNKx/fApThy/n34249DlR7mpG7ji6BFYLDj+2Q9zyfUvf1Kf11vImUkWbCoYjmpmGhe4OPP5Ek0dOXe4h6/NNBXMVnTAhBcldssCDovFGLOGqnhySqmQTgtzeBPyNbF1DXNVQ1zVMoH1cHmZKkkHxuUOxoioN3VygIJJhVJZdmGHm5py0GK+jZDpuxkquUkVOkmG5tkTthEZp1rTVCWzZsdLB15wj0C5W+zGvmEG/D/A0M5/r7v/uIi8G/hLwPF26hvd/cMSxYyfBl4P7LTj//lcn3GhaVkbXNz4d991O//9z72M666+lod+6PXofIdT/+LWvV7WE8Lv/ZXffZwzfot/cuqtPOvyy+mnitz7SfyqFz3hz9NqZE3klFhMEdBEQzosdx11XLIc5xw8eJCsKQJSyxjNDEkEK6W2BknrbosoKqllqJVCY9kQzRtvNEAHkkqoZK2eW71PoxrWWkl5xuzQEaaxYxp3QtwiCV4KVCMPAymlYNLUQs4DtYZX07jcZmuYNYpjzGFO7piHLYMhrV4ZDSFF0OZz7lSKVNwuoDI5sARe4+6nRKQDfl9EVkbOb3H39551/uuAm9rtawkv7q891wd03b5IaDfYR7Dlgq0Dh/jCF+/HTm3Tf8sLQ29wGKjAZDHIXGtleWqbbM7QdZQ6stV1ZHGYyto7proH28J1TbPLfYc47OzsoMCz3v+FPbnWHzr0j/i5+g+5/LJLWG7v8GTkkRViZrBWvDpWCjS9xmk0vEbAXMzHNgurdDnYMbhiFaxWxFrm19rNTviD1xo1S9fYQq840it1IViXOqMeqEpSZWsYIvOsxjAMFGpYW0mm6w4iPjFNI+gIEnOT0YBS5ottFmOJLrcqLs72/DgiHdJ3iAqKoppjtrgYqakgeYnguKxOlzokJVQdtcxuHRx2Y9/gwKn2sGu3c/Va/irwnva6/09EjorINe7+xcdcxMbJb4Oz8Kvfcxtv+Ecv4urnPZ+7PvEp+r5nyDFsX1SoVhkFkEQ+EGNd1cGTYn2PqJD6VeNhQoBBM9Wia2qqeJepgHeZZSnc8y03MjKtmSC0IHHo0CEObR0IrvW0ZCt3vOiGG7ntR3/tgl3v35S/x6/bOzh05BAnT34GO/yCJ/Q+2/M5Xa+YhX6lqmKaw4PbIaUuDMHMqCX+iKSU6GYz5vN5C64rWTRZS7qFglltozm+3p7HCE7gtHiwU93o+p6UEoudHRgGbCpM0xR10K0ZWRKiCZdM1oHUVablglJHxupIMvpZRy8DuQlijMsltYRiumgE5vl8geSOoTtISrmJY3SoKVVqNHdKaTqeMXe5dfAAi1Nn//YeHbtK4ZoJ2IeAG4F/7u5/KCLfDbxNRP4+8DvAj7r7ErgO+PwZL7+7HXvMIFk3Tn4bPAre99ZPcs1/cwUMB9jxyi+++Kf3dD3f95kfAO154OGT3Hb7nRz6W3+RablkNGfEsdQx/MIfPOI1r731v+O3b9ldMP3IbZ/iVV/5Cg7KQU4cuwO59MbzXqNBY/YEIwZXcs6IxRhPsYkhdWFta4VxObUMrcm3iYTWY2s3r2cfZTUzSYjrSGojQTHrKURTRz1UhkqpSM4sTp4kDwOL7RCE6XImZUGzoCTEO6pFMyepU4dMVyvTdILFNCK9koZgrR05coSHjx3n/vseYKpzskxImtEPPWOZKLYkZaHbysiUsGTgkZnmPqiIpUxhY5susMCFu1fg5SJyFPgNEXkJ8FbgS0AP/CzwI8CuVRtE5E3AmwAuv+q68GTcYIOzcNlzriHdfpjlqRN7vRR+5gXvBOB77vxBtheFnVMnSIS9wChAgge+49Wc2D5FWcypU+HQ1u4tPv7Bte/inXe8ma94wY1cdvQSzp4c3g1Gq2wvJ0QTxYiSRPNd106RmijTnE7bdrZWrBSKxTa4iqAaikFmTQkIcI2ucWN6k/qM10otFtzt1rARCZuIZ11xGd/wDbfwB7//n/j8nXdy4Mglax52rRAsxEq8PHQ1RcMKQjL0hzq2Tz3MfDnCYmJ7e5ssiZtvvpkrr7ySOz/96Si1TAsoQbkcS8Fr4cjBw3SzLXQ0SvImCBcZZcpDsH/OY+7wvLnbLXPccfefPOPYLcCb3f0NIvIu4FZ3/5X23G3ALefabv+5r/hKv/GKi7uLucFTh2PfdA8nbv881wwz/ukNb9/r5azxXZ/4QRQoZiynCVR4z8v+GQAvfsvtAHziJ2467/d9z/LHuOHP3ciJ7ROclGt3/br/+W+/kX5wpi7hFbr+AEmVMl9gZUSzkxMsy5IkQu9C56FEZAQvO7jNKR7XaPw46TQThgTqmCyDa2kpJBtFyCnMwoTCTdc/j1e+8pV8/COfQHPHi17ycn7xX/8bXDtyTuQ0RXaqq+ZPjk60B4d7mSqlLunN8GmO2IikylXXXs0VV13BlDvu+cKXOPnwScbteYw7pR4vEYizHGDYOkB3aAtTZcJZLivLxcSQt+iScuoL//HCcLdF5EpgcveHRWQLeC3w9lWdsXWz/2vgY+0lvwl8r4j8KtGwOX6uAAmb7vZTgd+69ZW87pYP7vUyLggu/Q/X8eBzPs2Y9leD710v/qlHPb4KkGc/3m3A/PbhbfzyPW/juuc+m76c4MH5kd0tKObUsZzRWc947BSTSAx+m0ExBFnXDo1grKTZgJfSMj1jSAl3aZqLDj6tN94iwZkO8z5tXGppLEYDgaQd9z/wEA/e/zAnt3dYLpdcfv+Xghoo2ho+CRFHVh1yBbeK1VWQSygdkiquW1gRyrjDXZ/5PGU5sXXZJTz/umfzBb+bEwinTm0z0bjoFaZ6imVZ0vuC/tABNHcMQ8JqJXcwaGKXJcldbbevAX6p1SUV+DV3f5+I/G4LoAJ8GFipFvzfxPjPHcQI0N94vA+40EZIGzx5/Nat8Qd2vwTaq6+7msWXHtzrZewaTySDPBMf+/RnGVW5/rnP4VI/wX333k93yQ2P8yphkExV5fk33MDi1JKDsxmfu/0OxjohtSLFIAct0gEzJ4uAJFyEUo1aF2gTys1d0AB17Qkz4iEJ3kQyVjM+jeMt0VybLwqfvetudrbnPHziBP/+/e8npIWUcZyY5YNRz/S6zibNQ+cSgb5mDGFuhZoSaThIzh1b7hz7wkM8+OCD6PMrV15ylEsOHuKuz93NfBnWDWnIMAmaofqSEye26bdmHD5yGV3uw5JivIBGYO7+UeAVj3L8NY9xvgPfs+sVAFY2QXKDc+O6517DB+/8/OOfuMdYZY3nyh7PzjTPPOf0cz/MG77vJ7ny6mt5y7d+w595j3f+4vvBjGHrKONSOSYDnXYMAg9vb2NmLHZ22EqZcRwpy5FEIfep2SaE2Ia4U8aQ70M1BHfFVsOPqBldEmqjFa4SGs191CCr4+ZUM6RfaUNWutnAJ//0DpIqXidKnThy6aWcmu+Qug4rjqjByglRm0uihIAGy4J2GZUO7ztqWSDSM40jR7aOYv3E7R//FJddeQWHjhzhwFZ0wIsZO/M54kopbZgqC+POku0ENhoHhgNk2b3Q8b7Yv9g+0LT8csQqG4RHZoRnHj/zubOP7ycc/7XDzJ9l/M2PvZmfe8lPPv4L9gif+ImbePFbbn/MTPLM4HmubfmL33I77/uZNzOOj7zWH/6pX0M1sz2fQyncd/820yT8xq//XyEDVkJN/HOf/gzLnZF77/pcsGW6TJawjhWP7LGGA040SyQGsbvUQRLKOGI4SYysypBz2DpUohnEqgPeRCZkJYoRP+d1Se47vFQkJ4Y8MJ/P16W1nDNOwcXIObUxrSbCS9AMp6lCH4GbHNYO/aBYMWqdOHzkMk6dmLO9syQPPf2BAamVyw4cYH58h1InJptii5+VaXkCqjCJ0e2+n7Y/guR5tZo2OC+87pYP8lu3vnJdozx7G/1ogfHM8/YVDm4x7p4osW+xCqCrYHhmsDz7uXfe8C5e3J77lh/4p3zy9rtQFFucZNzeYbmE3B/gi/ffF1miTBwaZuzMF6gJmjPqzcRLBVenqx5KQI2X3eWeMk1QjE6UqXrMGQJWgraYh9R42AoGUy0RfFyb7YOsVfUla0sGR7IIs75v40hOscbkyWfY1BINIXewGoHWuxzWszjUxtbJCdPMUivFMpIUHRLmhVMPn4T5AlVhGAYOHzoEIjx04kHKYgfPGvJpFWo1tpcXlnHzlGMTIp8arALhowW9Mx8/Vsa533DpNVezuP2BvV7GnuFzX3yAIwcP0YtyyaFLOXzoKNMIJ07OKWZMtUbnWoXsgkhiKgVJbf5RBFOQYmQP0y9zp5aClIqY0WliNA0FoKTr7n0dS2g7upOykGgakB7Nl9X/4Upsyc1LqzkqvafWFEoIiolRfcSsUq1g7TieGtcapuRUDBVhZivytzOpscSCPaPQD5kkQkozxmkZ8nA7C7byjMOXHOZZs2fx0IkHWZw6HgPw1VGt1PPgNe2LILnB04+zg+G+zBzPwnP+3xu577nbfPdtf49/efM/3OvlPGGcvR1f3V9llY+2FQd4zyt/+THf86s/cCOWEm4ryw0JL5iW4Vk41ESQq5UkiU6UsUZXO6uSU0JF8WWJHgtKyt26ruhuVDOSDIjoivId9UiJ4fBaC1ZG6FjTCKs7Y2lMb42B9LRyvvY2k+mVLEpqWelEpWqlIyMKOfWMVhlrGH2VnPAxAp0KJM3MBgXvOXX8OA/d/xDz+ZxDRw4wSEd3+BLKNDLtLMLn+zxEdfbF7I3rJpd8KrAKfOcKgGduxR/v3P2Azo2d81Bw2W84OyA+Gh7r+LlwYJqTpxHtOsYU29Uq4JpQTWGpszRsNLCmi1MryRyvlRFnR+GEGH2XONhlpIbQxdAdQFKH9gOWlCWFokpRoahhWsOO1h0q5LSF1kymQ1KmquC94J1heUKS46VHfYuuO4zTkdPAcmeO1DmZEW3vucCYa+akCGPKEZzNsDLRDUpSoXfoXellIOkB+oOX0c+2qMslOw8+zDAZl+cZhwU6KVjdptruBHdhnxiB3fCil/nNV//CXi/jywqP1Zw513OPVZ/cT7CvvpPPf/FB3vuyf7LXS9lXePXbrmKatqm5IDkjqWMxD8qhlYKqxOy3T+RS6XKOrbZGRqcpUSQGy1MNYVyrMSLUdV10ihOUOpGyMk4hRbbifpc2Z2lmdF23lkVb1UJtpT9Js1jQGUwTlz3nWhDnoTs/DcMsNCWt0g0d5kIlsdrwJk2oWKgGeaGbdfTSkdypiwlN0aEvzRzMxgU2jWSp5AwqlUKh2oSaMl8cu3iMwFbCnBtcOJwruD3Wc/stID4a9I+fz0OX3c5f+/iP8N4/v3/YN3uNUkookptBKXSaSeIIgq+CFWGSVVUQ9+bMKZATk8coT3C3naJTuCKKUkooBiVPbYsc1hNmhVIb7c+n6JWLU02aU6HG9t2F2hhJmhKeJLxrDx/i0muv4sYbb+T9Jx7iltd8Iw/dex+fv+sujt97LypKlkRB1/YR0ny0q0cGbJroUmKU03Jtqsr2VOiHA3TDFj7OGadFTKybMllCzyM53Bfb7TDR3WCD3aHbSizqcq+Xsa8wXy4ZS2EaR6xMiBWk2S/0XQ63Rq9BBUyJqkJxpxCycaEhGfJzqUu4NhHdlB5xQ1PYJ+Qc297lnGm+jZUJxcEqtSyopYQvtzXzrb4naVP7sgrjnANDx8MPPcC42KEfZtzw3Ofxl//SLbziJS/D2usj6Me6VnOaqko/DCRpJmfDEDOeEpJ41R26gZHE6IKnGak/DDpjosO9R+h3/bvdF5nk3m/4N7iYcP3zr+Huzzxzu9yPBpOgJGrXkQVsKnSSonuMQgozLbczJu6aS2Odptg2930EJfcQ6U2KN/Fdb/JoQ7+F1RGshohvVbw1QYZZh1liuVzSN41KEyeJg648cxTRBCmzfOhhjnQDJ+69D51P/Pv3/iZq8OB994dQroaFsmmwgUS9BSzHbQr5N+2YLxfUZhuxlm5bqWiYhjp77lBRum7GuNyhngfjZl+kcPuhLrrBxYOv++qX4osFf+u2t+71UvYPpim2zyL0OaFuIWoBMUC+1jhrs4wiMWTu4YuTHKQayYFJ0TGhRdEi6CR0npoXfEXMoQhSEplM1o6EMi2m8NdpwsYiQlrZ0Zqvs8okykw6BlPmx05x/51fgp3CA3fdy/13fRF2WrlAzwjQLbMMu4n4HLGwi12MI1MtLMsUt3EkzMfrOhsVUXToSUOPzA6Qtw7t+le7LzJJ3ZQkNzgPfOQdhXylbGrZZ8I9utjKeuxnpfco4d8Q9cnGlBFYB0txX/tmuzvqoeyDSbgmRiKIS1g7qCvFQ54MDxaP1ZAjWyU8WWOrz0rEQpSUFMSjPmnRMFqO2+xsL6lTYdBMn/uoPzLHWWWwtjYdi0Ab0w0pJUwVcTvj1xDXTBI68fDjNkOHHiP0hskdSYXp0VyrHwX7IkhuvuobnC8ODB3bJ07u9TL2D7qOvu+YCKvYJILhsSWtEWBCPiICjhLWC+KNIuiOm4VPtmcwCSELoFolieJNtFdSQr3RFFtgTJJwHPNQElLVdaA2syaGEU2isGAIXmAt4VPTdVtYMZbLSt/NSDqFdJsLBei6UDIKYSInOc0GVylWW81udU1GQsjS/HYQxnEkDT1FYohe00XH3b5459422Bscec7zuOcz9+71MvYPOmX0HbqZUekBYdZ1jGVip85BM1tZSTU8qGvz+6kuUIUqYRhWUiUJGEZKEeg0w7TqcKeEJqhpCiqjNxdFAB8YZh3z5TbzOo8B85xJKeqTXh0lkTrBfBkJX84IwliXpCTkITHJBOS1TuWQK6IjU50oNbr4oomdedRS+6Qo4ZYY3XmFSakG/bDF5GNY2uZML8pYjDLt3g1hX9QkNwIXG5wvDv/B89m2if/x9h/b66XsD7hRvVK9UnBS14WSTxLoFMSoVhgQcpL1VhtVJitUCzaNAZVKEcOyhzCEhTUtKusxHrIjOcaFSLF1dpVoEkmCJDEatK4JCpoj3JRScCuIGzlFDbXPiZxTUB47IoBXi+BqRpkm3CqqQs6p8dBDpKPWupZ2U23K6iq4JGrbppsHBVKtkq2EQdousS8ySdkUJTd4ArjkkoGT880oEBB0v5SwLiGTQlKsRJMmS6aUEk6H0uqI0oxpWG2ZIQR2W8CDMElr2aC3bW4xoywrllr90RVzC79ud8ybQ2XqKI2/XWtkbapRGzWv5NzjNeY6nZFawqCrWJzX5w6qYCakpMy6GaVOLJcLxnFkmG2tbRlXnfcz4eJockafEImA6Ga4ptiK59jG7+pXeyH+fZ4s8j5TnN7g4sBrv+kv8tD28cc/8ZmAVq+TqqSUGMexieDGjaQhquu2rhOaBw+663MzyoqAUy1C52SVsUyN3ihrdk4xw03W0marLXe83khZEZS+G8i5D352jWApIgy5w0pttdOwtE0pttaKIBjVJpCobVqFcVmw6uTc0fc9VcGS4FmRPqiPVYUqGjd1LDuVCZOKJEOkkqjk7HR594nZ/giSm0xygyeAV3/NSzhw+CB//U9/fK+Xsqf4C7/0chDhQD/jSH+IlDJd3zPWst6KkhIpxTC3u+NUECNlwSkRkFKTLFNBWtDLOZ8W2lVFuxz2vv2MnDqE08FVFFLWFtikKfooXTc0I+62niR0fTR+xmnBYjFv7x+sIDNjKstQEhILnx0HlbwO8JON1OTQazCIug7p+vDh7ga6WQ9JyH0md4nVNLa7M+t6Zv3uE7NdB0kRSSLyX0Tkfe3x80XkD0XkDhH5tyLSt+NDe3xHe/76x13Epia5wRPAL7/xQ1x77dUhQPsMxmJ7h6HvmRYTZVkopTDV6GXXNf0wwoSLMJaoEaasVCtRuzwjiIg56oQO5epmcTxZUAMhRoPOzEpjOx11SK9KqF6cIcgrEmIa48i0XCIET7tOE7KSYRNQHJeyDpjuzjSGTa3VFitKhTKFiVmbofRS8eJ4MWyqIf/WOv0iCipMVjm1XLA4D2HS88kkvx/45BmP3w68w91vBI4B39mOfydwrB1/RzvvnJDNvNsGTxB/4VVfHYPDz2B0VimLJYJSXJhqXXO5RQRr9MAw7dLw5TaLLbk6SGSVq5EdBVjNWLq3fDAaGOKOVaeW1fxirMHdm3EYmJd4uRHSba3OSEoxJ1lGap3WIr2aWGtQqiqiYcQYAm+GkCijUSbDYpeOphDsSMJ6yD0CpcXAe3EoFuNP1XGLGcmxOstxYnEeljG7CpIi8mzgvwJ+rj0W4DXAe9spv0Q4JgL81faY9vxflseJgqclOzfY4PzwguufQ/8Md9uU+Q6KU1BGTVjL8FJKSNJ1wIPIJOOOtiww+NyrAOn1jODokCwEJZIT4pHmSOs6W2UdeIHoZLeMUiUD0mxpy3rrLm3LTynUMmJeYyjcy5qlA5BSBE8RiesQCWHeWHyMCzX9ySTSMl9d/0wtZtvklMkYpxoW4pIwyZR6gYMk8E7gh4HVO18OPOzuqz/hdwPXtfvXAZ8HaM8fb+c/AiLyJhH5oIh88IEHNzzcDZ4Y/o/v/xBXPf8Af+dTz1yK4skTx5kdGuhmwmymdMNAzZltK1gCppEuKVkzxWGsMFWwkqnLRF1mytxJ5MjMskECQ6kF6lKQqnQkhgx9D64FpK7VyrMpqSTylEljRl0Y59E86oaBKkBO4WSYEkl6GCu5TAwUZlro04j5DtUX0TAyw7XiaaQ/CNo7mhMimboEn5S68Jin9AihKh6SaCq4ZlQ71DsGerpl5WA1Ls/K0bT73etufLffANzn7h8SkVue6D/k2XD3nwV+FuDml37lJpXc4AnjiquOcM9FZDd7obG1tYVmYTluc3TrKFc+6zIOHT7MsWP38/k7PgmaCXZ1GHghkLqhqeoUIBg4XQrZsUIEKDMh0bHaSZsYSSquTu4TeNg7uDU2TY3GT0ph7NV1HZLbdlsyVmvMRI+VnAdUhIRjNTrZrkrWDk2Jnalg6fSokq/mklDMaTVMCVELBEmnM2QAcowkYQXVRMbJQ4eK4LWQ8u53H7tp8Xwd8FdE5PXADDgC/DRwVERyyxafDdzTzr8HeA5wt4hk4BLgnN/gurGU3eBJ4PDhQ/jwzB0F2tnZ5mDaQiUh7ozzJXcfO4nbCBPRAS4efOvqGIoqa+9sd8daHTOJnHYKkBguz50CHtxtUWj2r44TokGOuqyGd4L8KJXUXBirO3UK/jaSQE4LYEyrpgs1DMSIcaMu9cEzL04pI0n74IK3YKwICUg4IkQDilb7dME8RopcFccoEA0rDRFhXcm27QKPG07d/a3u/mx3vx74VuB33f1/AD4A/LV22ncA/2e7/5vtMe353/XHkfnxDXt7gyeBu99zCV86dj9/9wvv2Oul7A1yotRKUuXEwyc49sAxHrr3fo4/9DDdgUNkiazPiuBVUWKI20rUD4ccGVadJpbLJV6MRIrxH68YxmSFySbGYtRirSkTDRevoeHonWIJlhYSacUrldYwkgw1g2XwkD5bhQXVmO30ZkpWx4mynGJovYTdRBknrETNtE71dKOmVtxW2pVxEypeJjQJqc8UM8ZqLN2YO2xXY/spqEk+Gn4E+EERuYOoOf58O/7zwOXt+A8CP/p4b+Sb7vYGTxI1OScWu5R1+TLCq/+3m6OL68o0NimxxchWP4Raz/J0lzuYME14olrbjhp9zsxmM8QcmwrTWKklusmiIYxRcKobxR1zyJpbI0WjGeNOtUKtEyTHpOAabJ6u60irOU0D2ixmynm9tkT4fkdDqGLTiJqtm0e9KmoFqYXkRp8yOWc0SaM9suaVm5fw7S4jy3FBcaPUEsmYJKo58/MIkudFdXH3W4Fb2/3PAF/zKOcsgP/2fN53gw2eLG646QWcePCZNwo0n89j2yzSLF4FdUOqkDAkCTmtmDEAihlrncckEZiUUNoREUqj+IUOZWxL1cKGARFcoY51LdDrUmMWB2KAu4tRJLdCdWWxmJNSRs1oZg/hwy0KInQphTCvRb3Qpgi0bsH/Vkmo1LVDowDFjeRCvOy0oa0AppVaHXMhaces75gvmvgF7fdwHonZvpid2BBuNniy6G59Lg/tbPPj9/6ve72UpxU2VSAhoiEsq4piqFSQSsqC+US1kclGio/r7G0lClGnmFnMKYWtbBQsIwhKmHtZoyaaEPRAF3qU3LbKCaHLCUWYphEvIz4ucJvQjmD1aEF1RFJFuhzv2YbRSykhyIuQRMENKwumcYdSFkzTnGlaUMqCWpfBtzZpkQAACFBJREFUIbfmCe5OpVIlNC0rBmk1wB7rT6J0KJ0nxJVUL2B3++mA2Ka5vcGTx5TguDyzmoBWK5RCGQWjUF3Y6sK/RYqh4hHYzDB3VDNiFW8jM6sZ5VpD1xEgobGtrpUCoR/ZWCtuEXiyV5rsbmSyGv7bB7e2OHDJAe6957NsXXopi8WCadpBVjONvZBcqDEtjraOuhUHYusP4FlZTIvgeKtGB10bc8Yds9CbVA8xC4isWBRqNcQLXR5QTdRibZ4yckJtBKPd7jv2R5DcNG42uAC4ftax3N493ezLAV2XWYboDloKyWFZFU8Zl4zWEInACtliwLyqMNUJPDq90oKq1aAU5iRsJaUmw60y6wdqMXJOlKVQqlPFSDlRbGKcJlxBh0SaJa5+7rXcu3MfX/UNX09dTPzB7/0+lIrVMczJVEmuWC2AYB4iuLVWWpOahNDbFpIjgNfaKIa5BUu6qD16ZI3TuCDng8EZr0Id5zBLzLJwQDKuoaM5ibEUR/wCdrefDmxoiRtcCBz46As5/sCDvPVL/3ivl/K0QWXl7OVk1RjXUW3qP4pLwl1IxHZcVrYORHY5TdNpy1kVpCmHrwy13I1xscO4WDAtF4iNpOaZs1L1yX1P7ntEhOVUMGB29CjLJtTLYsTHERsnEqEClFXpui5U0ZsOpbEqGaRoGpHIqWvmZU61KTyzExFgLQInVhAa42cykvagmZSUhEANTco6TY39E7TG3WJfZJK2oSVucIFw6dEDqO1edfpihzfJMfGwhqVZHoTP9krxJ7AyA1uN3EBsl2VlKUvzvTFte7uMiDHVEqK3GEkzOXVRM7SKipJSjnGf4sy3tzn2wDFknPjjW38PPLU16VrgwkphMl/PNLoFJzuGLoNmmHNoYE5T0BZTVkodQ7DXHZeOJF1QF1UpEvOUeJiT0UaKik3UGu6PkxvFQjYua5QLdoN9kUluQuQGFwqvfMWf56EHn0G2DmZR26NlhlZDjdtsvU1dDW6vJM1KKWu18NWx1fkQeiHVQhNStYvxoKyYVMwnvNER3eM14zhSq8WIEYl7v/AllsfnMFa0FFjOyQmGrkMlUaZKMWM5TfGZK5WgFrylBbhVxisij1hvWc1S1jE66DW23eEzZpQ6As40LVgsFhiGN23KlKP0wLTY9a94EyQ3+LLCV7z0hWv2xTMBshKFqEbXdY+wZ85tDtHM1pJjq9LWyqjrEc6KNDWfFEK3tR0vVhmGgZQSk1UW44hjj9RpnKaQMatOWRYYC+qQ3OlnAzkpqeuQnJCuJ/UxO1mbEtBqJKc29fMz179SC1qJdvR9D0wIhWmlKETFa8GlUMYdKEuoRupT+Oz0GRK4TTDFrOVusT+C5EZPcoMLhF/5sTs59vADfO9tzwzvmzpFMFrB4BEBUXepkLTWfGzvYlqx1hmPLXtQ/VbqQSGD3gKNnPn/N5TKew/7G8VBKy7eLCGEJsYWXXc5rZpzPlFgRUW0aQz9I4m5zi4pqXnxpBy11eKFpYVCkYsgu+/ZtMvbBwFKRE4Ct+31Oi4QrgC+XGSNNteyP7G5lguD57n7lY930r5o3AC3ufsr93oRFwIi8sHNtew/bK5lf+JiuJZ9sd3eYIMNNtiv2ATJDTbYYINzYL8EyZ/d6wVcQGyuZX9icy37E/v+WvZF42aDDTbYYL9iv2SSG2ywwQb7EnseJEXkm0XktubT/bgCvXsNEfkFEblPRD52xrHLROS3ReT29vPSdlxE5GfatX1URL5y71b+ZyEizxGRD4jIJ0Tk4yLy/e34RXc9IjITkT8SkY+0a/lf2vEL5g//dEKeQp/7pxMi8lkR+RMR+bCIfLAdu6i+X3saJCUUPf858DrgxcC3iciL93JNu8C7gW8+69iPAr/j7jcBv8NpNfbXATe125uAf/k0rXG3KMAPufuLgVcB39N+/xfj9SyB17j7y4CXA98sIq/iAvrDP814ynzu9wDf6O4vP2PU5+L6fq39dvfgBrwaeP8Zj98KvHUv17TLdV8PfOyMx7cB17T71xBznwDvAr7t0c7bjzfCp+i1F/v1AAeA/wx8LTGonM/+vgHvB17d7ud2nuz12tt6nk0Ej9cA7yN0KC6662hr+ixwxVnHLqrv115vt9ce3Q1n+ndfTLjK3b/Y7n8JuKrdv2iur23TXgH8IRfp9bQt6oeB+4DfBj7Nk/SH3yNccJ/7PYQD/0FEPiQib2rHLqrv135h3HzZwN1dRC6qkQEROQT8OvAD7n7iTH3Pi+l63L0CLxeRo8BvAC/c4yWdN+Qp8rnfQ3y9u98jIs8CfltEPnXmkxfD92uvM8mVR/cKZ/p3X0y4V0SuAWg/72vH9/31iUhHBMh/4+7/rh2+aK8HwN0fJiyPX03zh29PPZo/PLJLf/inCSuf+88Cv0psudc+9+2ci+E6AHD3e9rP+4g/XF/DRfb92usg+cfATa1z1xO+3r+5x2t6IjjTa/xsD/Jvb127VwHHz9hm7DkkUsafBz7p7j91xlMX3fWIyJUtg0REtoja6ie5gP7wTwf8afC5f7ogIgdF5PDqPvBNwMe42L5fe10UBV4P/ClRP/qxvV7PLtb7K8AXgYmomXwnUQP6HeB24D8Cl7Vzhejefxr4E+CVe73+s67l64ma0UeBD7fb6y/G6wFeCvyXdi0fA/5+O/4C4I+AO4D/HRja8Vl7fEd7/gV7fQ2Pck23AO+7WK+jrfkj7fbx1f/vi+37tWHcbLDBBhucA3u93d5ggw022NfYBMkNNthgg3NgEyQ32GCDDc6BTZDcYIMNNjgHNkFygw022OAc2ATJDTbYYINzYBMkN9hggw3OgU2Q3GCDDTY4B/5/4DJRwjXC/tsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Annotated Image\")\n",
    "plt.imshow(imgRGBWithAnnotations);"
   ]
  },
  {
   "cell_type": "code",
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