TableNet.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/KamaljeetSahoo/TableNet_PyTorch/blob/master/TableNet.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "__mgPzZacW_T"
      },
      "source": [
        "from IPython.display import clear_output\n",
        "!pip install pytorch_lightning\n",
        "!pip install pytesseract\n",
        "!pip install --upgrade --force-reinstall --no-deps albumentations\n",
        "!sudo apt install tesseract-ocr\n",
        "clear_output()"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k_VujWSdrUjf"
      },
      "source": [
        "!sudo apt install tesseract-ocr\n",
        "!pip install pytesseract\n",
        "import pytesseract\n",
        "import shutil\n",
        "import os\n",
        "import random\n",
        "try:\n",
        "    from PIL import Image\n",
        "except ImportError:\n",
        "    import Image\n",
        "clear_output()"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_VMraYR9dXds",
        "outputId": "2bdb3476-561e-4d78-8339-f429f82c7f6b"
      },
      "source": [
        "!gdown --id 19nNp42l0rN1epa9AwEQEqGX5fbImMV6s"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=19nNp42l0rN1epa9AwEQEqGX5fbImMV6s\n",
            "To: /content/best_model.ckpt\n",
            "252MB [00:03, 70.5MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EvC8x8ZipR6C"
      },
      "source": [
        "!gdown --id 1xiEUoeV_L8kpd2BwHyD8Grz2OCRMGjCn\n",
        "!unrar x /content/samples.rar\n",
        "clear_output()"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ySqemd3_cVBv"
      },
      "source": [
        "import pytorch_lightning as pl\n",
        "import torch\n",
        "from torch import nn, optim\n",
        "from torch.nn import functional as F\n",
        "from torchvision.models import vgg19, vgg19_bn\n",
        "from collections import OrderedDict\n",
        "from typing import List\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from albumentations import Compose\n",
        "from PIL import Image\n",
        "from pytesseract import image_to_string\n",
        "from skimage.filters import threshold_otsu\n",
        "from skimage.segmentation import clear_border\n",
        "from skimage.measure import label, regionprops\n",
        "from skimage.morphology import closing, square, convex_hull_image\n",
        "from skimage.transform import resize\n",
        "from skimage.util import invert\n",
        "import cv2\n",
        "#from tablenet import TableNetModule\n",
        "import matplotlib.pyplot as plt\n",
        "from google.colab.patches import cv2_imshow"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Mc30sLpVOyS"
      },
      "source": [
        "\"\"\"TableNet Module.\"\"\"\n",
        "\n",
        "EPSILON = 1e-15\n",
        "\n",
        "\n",
        "class TableNetModule(pl.LightningModule):\n",
        "    \"\"\"Pytorch Lightning Module for TableNet.\"\"\"\n",
        "\n",
        "    def __init__(self, num_class: int = 1, batch_norm: bool = False):\n",
        "        \"\"\"Initialize TableNet Module.\n",
        "\n",
        "        Args:\n",
        "            num_class (int): Number of classes per point.\n",
        "            batch_norm (bool): Select VGG with or without batch normalization.\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "        self.model = TableNet(num_class, batch_norm)\n",
        "        self.num_class = num_class\n",
        "        self.dice_loss = DiceLoss()\n",
        "\n",
        "    def forward(self, batch):\n",
        "        \"\"\"Perform forward-pass.\n",
        "\n",
        "        Args:\n",
        "            batch (tensor): Batch of images to perform forward-pass.\n",
        "\n",
        "        Returns (Tuple[tensor, tensor]): Table, Column prediction.\n",
        "        \"\"\"\n",
        "        return self.model(batch)\n",
        "\n",
        "    def training_step(self, batch, batch_idx):\n",
        "        \"\"\"Get training step.\n",
        "\n",
        "        Args:\n",
        "            batch (List[Tensor]): Data for training.\n",
        "            batch_idx (int): batch index.\n",
        "\n",
        "        Returns: Tensor\n",
        "        \"\"\"\n",
        "        samples, labels_table, labels_column = batch\n",
        "        output_table, output_column = self.forward(samples)\n",
        "\n",
        "        loss_table = self.dice_loss(output_table, labels_table)\n",
        "        loss_column = self.dice_loss(output_column, labels_column)\n",
        "\n",
        "        self.log('train_loss_table', loss_table)\n",
        "        self.log('train_loss_column', loss_column)\n",
        "        self.log('train_loss', loss_column + loss_table)\n",
        "        return loss_table + loss_column\n",
        "\n",
        "    def validation_step(self, batch, batch_idx):\n",
        "        \"\"\"Get validation step.\n",
        "\n",
        "        Args:\n",
        "            batch (List[Tensor]): Data for training.\n",
        "            batch_idx (int): batch index.\n",
        "\n",
        "        Returns: Tensor\n",
        "        \"\"\"\n",
        "        samples, labels_table, labels_column = batch\n",
        "        output_table, output_column = self.forward(samples)\n",
        "\n",
        "        loss_table = self.dice_loss(output_table, labels_table)\n",
        "        loss_column = self.dice_loss(output_column, labels_column)\n",
        "\n",
        "        if batch_idx == 0:\n",
        "            self._log_images(\"validation\", samples, labels_table, labels_column, output_table, output_column)\n",
        "\n",
        "        self.log('valid_loss_table', loss_table, on_epoch=True)\n",
        "        self.log('valid_loss_column', loss_column, on_epoch=True)\n",
        "        self.log('validation_loss', loss_column + loss_table, on_epoch=True)\n",
        "        self.log('validation_iou_table', binary_mean_iou(output_table, labels_table), on_epoch=True)\n",
        "        self.log('validation_iou_column', binary_mean_iou(output_column, labels_column), on_epoch=True)\n",
        "        return loss_table + loss_column\n",
        "\n",
        "    def test_step(self, batch, batch_idx):\n",
        "        \"\"\"Get test step.\n",
        "\n",
        "        Args:\n",
        "            batch (List[Tensor]): Data for training.\n",
        "            batch_idx (int): batch index.\n",
        "\n",
        "        Returns: Tensor\n",
        "        \"\"\"\n",
        "        samples, labels_table, labels_column = batch\n",
        "        output_table, output_column = self.forward(samples)\n",
        "\n",
        "        loss_table = self.dice_loss(output_table, labels_table)\n",
        "        loss_column = self.dice_loss(output_column, labels_column)\n",
        "\n",
        "        if batch_idx == 0:\n",
        "            self._log_images(\"test\", samples, labels_table, labels_column, output_table, output_column)\n",
        "\n",
        "        self.log('test_loss_table', loss_table, on_epoch=True)\n",
        "        self.log('test_loss_column', loss_column, on_epoch=True)\n",
        "        self.log('test_loss', loss_column + loss_table, on_epoch=True)\n",
        "        self.log('test_iou_table', binary_mean_iou(output_table, labels_table), on_epoch=True)\n",
        "        self.log('test_iou_column', binary_mean_iou(output_column, labels_column), on_epoch=True)\n",
        "        return loss_table + loss_column\n",
        "\n",
        "    def configure_optimizers(self):\n",
        "        \"\"\"Configure optimizer for pytorch lighting.\n",
        "\n",
        "        Returns: optimizer and scheduler for pytorch lighting.\n",
        "\n",
        "        \"\"\"\n",
        "        optimizer = optim.SGD(self.parameters(), lr=0.0001)\n",
        "        scheduler = {\n",
        "            'scheduler': optim.lr_scheduler.OneCycleLR(optimizer,\n",
        "                                                       max_lr=0.0001, steps_per_epoch=204, epochs=500, pct_start=0.1),\n",
        "            'interval': 'step',\n",
        "        }\n",
        "\n",
        "        return [optimizer], [scheduler]\n",
        "\n",
        "    def _log_images(self, mode, samples, labels_table, labels_column, output_table, output_column):\n",
        "        \"\"\"Log image on to logger.\"\"\"\n",
        "        self.logger.experiment.add_images(f'{mode}_generated_images', samples[0:4], self.current_epoch)\n",
        "        self.logger.experiment.add_images(f'{mode}_labels_table', labels_table[0:4], self.current_epoch)\n",
        "        self.logger.experiment.add_images(f'{mode}_labels_column', labels_column[0:4], self.current_epoch)\n",
        "        self.logger.experiment.add_images(f'{mode}_output_table', output_table[0:4], self.current_epoch)\n",
        "        self.logger.experiment.add_images(f'{mode}_output_column', output_column[0:4], self.current_epoch)\n",
        "\n",
        "\n",
        "class TableNet(nn.Module):\n",
        "    \"\"\"TableNet.\"\"\"\n",
        "\n",
        "    def __init__(self, num_class: int, batch_norm: bool = False):\n",
        "        \"\"\"Initialize TableNet.\n",
        "\n",
        "        Args:\n",
        "            num_class (int): Number of classes per point.\n",
        "            batch_norm (bool): Select VGG with or without batch normalization.\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "        self.vgg = vgg19(pretrained=True).features if not batch_norm else vgg19_bn(pretrained=True).features\n",
        "        self.layers = [18, 27] if not batch_norm else [26, 39]\n",
        "        self.model = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1),\n",
        "                                   nn.ReLU(inplace=True),\n",
        "                                   nn.Dropout(0.8),\n",
        "                                   nn.Conv2d(512, 512, kernel_size=1),\n",
        "                                   nn.ReLU(inplace=True),\n",
        "                                   nn.Dropout(0.8))\n",
        "        self.table_decoder = TableDecoder(num_class)\n",
        "        self.column_decoder = ColumnDecoder(num_class)\n",
        "\n",
        "    def forward(self, x):\n",
        "        \"\"\"Forward pass.\n",
        "\n",
        "        Args:\n",
        "            x (tensor): Batch of images to perform forward-pass.\n",
        "\n",
        "        Returns (Tuple[tensor, tensor]): Table, Column prediction.\n",
        "        \"\"\"\n",
        "        results = []\n",
        "        for i, layer in enumerate(self.vgg):\n",
        "            x = layer(x)\n",
        "            if i in self.layers:\n",
        "                results.append(x)\n",
        "        x_table = self.table_decoder(x, results)\n",
        "        x_column = self.column_decoder(x, results)\n",
        "        return torch.sigmoid(x_table), torch.sigmoid(x_column)\n",
        "\n",
        "\n",
        "class ColumnDecoder(nn.Module):\n",
        "    \"\"\"Column Decoder.\"\"\"\n",
        "\n",
        "    def __init__(self, num_classes: int):\n",
        "        \"\"\"Initialize Column Decoder.\n",
        "\n",
        "        Args:\n",
        "            num_classes (int): Number of classes per point.\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "        self.decoder = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "            nn.Dropout(0.8),\n",
        "            nn.Conv2d(512, 512, kernel_size=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "        )\n",
        "        self.layer = nn.ConvTranspose2d(1280, num_classes, kernel_size=2, stride=2, dilation=1)\n",
        "\n",
        "    def forward(self, x, pools):\n",
        "        \"\"\"Forward pass.\n",
        "\n",
        "        Args:\n",
        "            x (tensor): Batch of images to perform forward-pass.\n",
        "            pools (Tuple[tensor, tensor]): The 3 and 4 pooling layer from VGG-19.\n",
        "\n",
        "        Returns (tensor): Forward-pass result tensor.\n",
        "\n",
        "        \"\"\"\n",
        "        pool_3, pool_4 = pools\n",
        "        x = self.decoder(x)\n",
        "        x = F.interpolate(x, scale_factor=2)\n",
        "        x = torch.cat([x, pool_4], dim=1)\n",
        "        x = F.interpolate(x, scale_factor=2)\n",
        "        x = torch.cat([x, pool_3], dim=1)\n",
        "        x = F.interpolate(x, scale_factor=2)\n",
        "        x = F.interpolate(x, scale_factor=2)\n",
        "        return self.layer(x)\n",
        "\n",
        "\n",
        "class TableDecoder(ColumnDecoder):\n",
        "    \"\"\"Table Decoder.\"\"\"\n",
        "\n",
        "    def __init__(self, num_classes):\n",
        "        \"\"\"Initialize Table decoder.\n",
        "\n",
        "        Args:\n",
        "            num_classes (int): Number of classes per point.\n",
        "        \"\"\"\n",
        "        super().__init__(num_classes)\n",
        "        self.decoder = nn.Sequential(\n",
        "            nn.Conv2d(512, 512, kernel_size=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "        )\n",
        "\n",
        "\n",
        "class DiceLoss(nn.Module):\n",
        "    \"\"\"Dice loss.\"\"\"\n",
        "\n",
        "    def __init__(self):\n",
        "        \"\"\"Dice Loss.\"\"\"\n",
        "        super().__init__()\n",
        "\n",
        "    def forward(self, inputs, targets, smooth=1):\n",
        "        \"\"\"Calculate loss.\n",
        "\n",
        "        Args:\n",
        "            inputs (tensor): Output from the forward pass.\n",
        "            targets (tensor): Labels.\n",
        "            smooth (float): Value to smooth the loss.\n",
        "\n",
        "        Returns (tensor): Dice loss.\n",
        "\n",
        "        \"\"\"\n",
        "        inputs = inputs.view(-1)\n",
        "        targets = targets.view(-1)\n",
        "\n",
        "        intersection = (inputs * targets).sum()\n",
        "        dice = (2. * intersection + smooth) / (inputs.sum() + targets.sum() + smooth)\n",
        "\n",
        "        return 1 - dice\n",
        "\n",
        "\n",
        "def binary_mean_iou(inputs, targets):\n",
        "    \"\"\"Calculate binary mean intersection over union.\n",
        "\n",
        "    Args:\n",
        "        inputs (tensor): Output from the forward pass.\n",
        "        targets (tensor): Labels.\n",
        "\n",
        "    Returns (tensor): Intersection over union value.\n",
        "    \"\"\"\n",
        "    output = (inputs > 0).int()\n",
        "\n",
        "    if output.shape != targets.shape:\n",
        "        targets = torch.squeeze(targets, 1)\n",
        "\n",
        "    intersection = (targets * output).sum()\n",
        "\n",
        "    union = targets.sum() + output.sum() - intersection\n",
        "\n",
        "    result = (intersection + EPSILON) / (union + EPSILON)\n",
        "\n",
        "    return result\n"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YswXxRl2VXT-"
      },
      "source": [
        "\"\"\"Marmot Dataset Module.\"\"\"\n",
        "\n",
        "from pathlib import Path\n",
        "from typing import List\n",
        "\n",
        "import numpy as np\n",
        "import pytorch_lightning as pl\n",
        "from albumentations import Compose\n",
        "from PIL import Image\n",
        "from torch.utils.data import Dataset, DataLoader\n",
        "\n",
        "\n",
        "class MarmotDataset(Dataset):\n",
        "    \"\"\"Marmot Dataset.\"\"\"\n",
        "\n",
        "    def __init__(self, data: List[Path], transforms: Compose = None) -> None:\n",
        "        \"\"\"Marmot Dataset initialization.\n",
        "\n",
        "        Args:\n",
        "            data (List[Path]): A list of Path.\n",
        "            transforms (Optional[Compose]): Compose object from albumentations.\n",
        "        \"\"\"\n",
        "        self.data = data\n",
        "        self.transforms = transforms\n",
        "\n",
        "    def __len__(self):\n",
        "        \"\"\"Dataset Length.\"\"\"\n",
        "        return len(self.data)\n",
        "\n",
        "    def __getitem__(self, item):\n",
        "        \"\"\"Get sample data.\n",
        "\n",
        "        Args:\n",
        "            item (int): sample id.\n",
        "\n",
        "        Returns (Tuple[tensor, tensor, tensor]): Image, Table Mask, Column Mask\n",
        "        \"\"\"\n",
        "        sample_id = self.data[item].stem\n",
        "\n",
        "        image_path = self.data[item]\n",
        "        table_path = self.data[item].parent.parent.joinpath(\"table_mask\", sample_id + \".bmp\")\n",
        "        column_path = self.data[item].parent.parent.joinpath(\"column_mask\", sample_id + \".bmp\")\n",
        "\n",
        "        image = np.array(Image.open(image_path))\n",
        "        table_mask = np.expand_dims(np.array(Image.open(table_path)), axis=2)\n",
        "        column_mask = np.expand_dims(np.array(Image.open(column_path)), axis=2)\n",
        "        mask = np.concatenate([table_mask, column_mask], axis=2) / 255\n",
        "        sample = {\"image\": image, \"mask\": mask}\n",
        "        if self.transforms:\n",
        "            sample = self.transforms(image=image, mask=mask)\n",
        "\n",
        "        image = sample[\"image\"]\n",
        "        mask_table = sample[\"mask\"][:, :, 0].unsqueeze(0)\n",
        "        mask_column = sample[\"mask\"][:, :, 1].unsqueeze(0)\n",
        "        return image, mask_table, mask_column\n",
        "\n",
        "\n",
        "class MarmotDataModule(pl.LightningDataModule):\n",
        "    \"\"\"Pytorch Lightning Data Module for Marmot.\"\"\"\n",
        "\n",
        "    def __init__(self, data_dir: str = \"./data\", transforms_preprocessing: Compose = None,\n",
        "                 transforms_augmentation: Compose = None, batch_size: int = 8, num_workers: int = 4):\n",
        "        \"\"\"Marmot Data Module initialization.\n",
        "\n",
        "        Args:\n",
        "            data_dir (str): Dataset directory.\n",
        "            transforms_preprocessing (Optional[Compose]): Compose object from albumentations applied\n",
        "             on validation an test dataset.\n",
        "            transforms_augmentation (Optional[Compose]): Compose object from albumentations applied\n",
        "             on training dataset.\n",
        "            batch_size (int): Define batch size.\n",
        "            num_workers (int): Define number of workers to process data.\n",
        "        \"\"\"\n",
        "        super().__init__()\n",
        "        self.data = list(Path(data_dir).rglob(\"*.bmp\"))\n",
        "        self.transforms_preprocessing = transforms_preprocessing\n",
        "        self.transforms_augmentation = transforms_augmentation\n",
        "        self.batch_size = batch_size\n",
        "        self.num_workers = num_workers\n",
        "\n",
        "        self.setup()\n",
        "\n",
        "    def setup(self, stage: str = None) -> None:\n",
        "        \"\"\"Start training, validation and test datasets.\n",
        "\n",
        "        Args:\n",
        "            stage (Optional[str]): Used to separate setup logic for trainer.fit and trainer.test.\n",
        "        \"\"\"\n",
        "        n_samples = len(self.data)\n",
        "        self.data.sort()\n",
        "        train_slice = slice(0, int(n_samples * 0.8))\n",
        "        val_slice = slice(int(n_samples * 0.8), int(n_samples * 0.9))\n",
        "        test_slice = slice(int(n_samples * 0.9), n_samples)\n",
        "\n",
        "        self.complaint_train = MarmotDataset(self.data[train_slice], transforms=self.transforms_augmentation)\n",
        "        self.complaint_val = MarmotDataset(self.data[val_slice], transforms=self.transforms_preprocessing)\n",
        "        self.complaint_test = MarmotDataset(self.data[test_slice], transforms=self.transforms_preprocessing)\n",
        "\n",
        "    def train_dataloader(self, *args, **kwargs) -> DataLoader:\n",
        "        \"\"\"Create Dataloader.\n",
        "\n",
        "        Returns: DataLoader\n",
        "        \"\"\"\n",
        "        return DataLoader(self.complaint_train, batch_size=self.batch_size, shuffle=True, num_workers=self.num_workers)\n",
        "\n",
        "    def val_dataloader(self, *args, **kwargs) -> DataLoader:\n",
        "        \"\"\"Create Dataloader.\n",
        "\n",
        "        Returns: DataLoader\n",
        "        \"\"\"\n",
        "        return DataLoader(self.complaint_val, batch_size=self.batch_size, num_workers=self.num_workers)\n",
        "\n",
        "    def test_dataloader(self, *args, **kwargs) -> DataLoader:\n",
        "        \"\"\"Create Dataloader.\n",
        "\n",
        "        Returns: DataLoader\n",
        "        \"\"\"\n",
        "        return DataLoader(self.complaint_test, batch_size=self.batch_size, num_workers=self.num_workers)\n"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DpCIMtnpcx-P"
      },
      "source": [
        "class Predict:\n",
        "    \"\"\"Predict images using pre-trained model.\"\"\"\n",
        "\n",
        "    def __init__(self, checkpoint_path: str, transforms: Compose, threshold: float = 0.5, per: float = 0.005):\n",
        "        \"\"\"Predict images using pre-trained TableNet model.\n",
        "        Args:\n",
        "            checkpoint_path (str): model weights path.\n",
        "            transforms (Optional[Compose]): Compose object from albumentations used for pre-processing.\n",
        "            threshold (float): threshold to consider the value as correctly classified.\n",
        "            per (float): Minimum area for tables and columns to be considered.\n",
        "        \"\"\"\n",
        "        self.transforms = transforms\n",
        "        self.threshold = threshold\n",
        "        self.per = per\n",
        "\n",
        "        self.model = TableNetModule.load_from_checkpoint(checkpoint_path)\n",
        "        self.model.eval()\n",
        "        self.model.requires_grad_(False)\n",
        "        self.inp_img = \"\"\n",
        "\n",
        "    def predict(self, image: Image) -> List[pd.DataFrame]:\n",
        "        \"\"\"Predict a image table values.\n",
        "        Args:\n",
        "            image (Image): PIL.Image to\n",
        "        Returns (List[pd.DataFrame]): Tables in pandas DataFrame format.\n",
        "        \"\"\"\n",
        "        processed_image = self.transforms(image=np.array(image))[\"image\"]\n",
        "        self.inp_img = cv2.resize(np.array(image), (896, 896))\n",
        "        cv2_imshow(self.inp_img)\n",
        "\n",
        "        table_mask, column_mask = self.model.forward(processed_image.unsqueeze(0))\n",
        "\n",
        "        table_mask = self._apply_threshold(table_mask)\n",
        "        column_mask = self._apply_threshold(column_mask)\n",
        "        # print(type(table_mask))\n",
        "        # print(type(column_mask))\n",
        "        # print(table_mask.shape)\n",
        "        # print(np.unique(table_mask))\n",
        "        # print(column_mask.shape)\n",
        "        # print(np.unique(column_mask))\n",
        "        # cv2_imshow((table_mask*255).astype(np.uint8))\n",
        "        # cv2_imshow((column_mask*255).astype(np.uint8))\n",
        "\n",
        "        segmented_tables = self._process_tables(self._segment_image(table_mask))\n",
        "        # print(type(segmented_tables[0]))\n",
        "        # print(segmented_tables[0].shape)\n",
        "        # for i in range(len(segmented_tables)):\n",
        "        #     cv2_imshow((segmented_tables[i]*255).astype(np.uint8))\n",
        "\n",
        "        # for table in segmented_tables:\n",
        "        #     abc = self._segment_image(column_mask*table)\n",
        "        #     cv2_imshow(abc*255)\n",
        "        cv2_imshow(self.inp_img*cv2.merge((table_mask, table_mask, table_mask)))\n",
        "        cv2_imshow(self.inp_img*cv2.merge((column_mask, column_mask, column_mask)))\n",
        "        tables = []\n",
        "        for table in segmented_tables:\n",
        "            segmented_columns = self._process_columns(self._segment_image(column_mask * table))\n",
        "            if segmented_columns:\n",
        "                cols = []\n",
        "                for column in segmented_columns.values():\n",
        "                    #cv2_imshow(self.inp_img*cv2.merge((column, column, column)))\n",
        "                    cols.append(self._column_to_dataframe(column, image))\n",
        "                tables.append(pd.concat(cols, ignore_index=True, axis=1))\n",
        "        return tables\n",
        "\n",
        "    def _apply_threshold(self, mask):\n",
        "        mask = mask.squeeze(0).squeeze(0).numpy() > self.threshold\n",
        "        return mask.astype(int)\n",
        "\n",
        "    def _process_tables(self, segmented_tables):\n",
        "        width, height = segmented_tables.shape\n",
        "        tables = []\n",
        "        for i in np.unique(segmented_tables)[1:]:\n",
        "            table = np.where(segmented_tables == i, 1, 0)\n",
        "            if table.sum() > height * width * self.per:\n",
        "                tables.append(convex_hull_image(table))\n",
        "\n",
        "        return tables\n",
        "\n",
        "    def _process_columns(self, segmented_columns):\n",
        "        width, height = segmented_columns.shape\n",
        "        cols = {}\n",
        "        for j in np.unique(segmented_columns)[1:]:\n",
        "            column = np.where(segmented_columns == j, 1, 0)\n",
        "            column = column.astype(int)\n",
        "\n",
        "            if column.sum() > width * height * self.per:\n",
        "                position = regionprops(column)[0].centroid[1]\n",
        "                cols[position] = column\n",
        "        return OrderedDict(sorted(cols.items()))\n",
        "\n",
        "    @staticmethod\n",
        "    def _segment_image(image):\n",
        "        thresh = threshold_otsu(image)\n",
        "        bw = closing(image > thresh, square(2))\n",
        "        cleared = clear_border(bw)\n",
        "        label_image = label(cleared)\n",
        "        return label_image\n",
        "\n",
        "    @staticmethod\n",
        "    def _column_to_dataframe(column, image):\n",
        "        width, height = image.size\n",
        "        column = resize(np.expand_dims(column, axis=2), (height, width), preserve_range=True) > 0.01\n",
        "\n",
        "        crop = column * image\n",
        "        white = np.ones(column.shape) * invert(column) * 255\n",
        "        crop = crop + white\n",
        "        ocr = image_to_string(Image.fromarray(crop.astype(np.uint8)))\n",
        "        return pd.DataFrame({\"col\": [value for value in ocr.split(\"\\n\") if len(value) > 0]})"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XMg9Ng46dNHp"
      },
      "source": [
        "def predict(image_path: str, model_weights: str) -> List[pd.DataFrame]:\n",
        "    \"\"\"Predict table content.\n",
        "\n",
        "    Args:\n",
        "        image_path (str): image path.\n",
        "        model_weights (str): model weights path.\n",
        "\n",
        "    Returns (List[pd.DataFrame]): Tables in pandas DataFrame format.\n",
        "    \"\"\"\n",
        "    import albumentations as album\n",
        "    from albumentations.pytorch.transforms import ToTensorV2\n",
        "\n",
        "    transforms = album.Compose([\n",
        "        album.Resize(896, 896, always_apply=True),\n",
        "        album.Normalize(),\n",
        "        ToTensorV2()\n",
        "    ])\n",
        "    pred = Predict(model_weights, transforms)\n",
        "\n",
        "    image = Image.open(image_path)\n",
        "    print(pred.predict(image))"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "ba20cad16647413aa331ecb758712d7e",
            "8c9d696be4654287bcbcef81a3e896a9",
            "27b8e3df2e964b1cbb9675538de53a0d",
            "530f4cb93bba4fe998ff38ead9767b97",
            "7a49681c25e5403eb35dce395d8360b1",
            "61cac9f84f4c48be81183e2a58a78719",
            "201afe7df9854568ac61955df203dd99",
            "2a608f41044d466a9fc33300c0ee2f90"
          ]
        },
        "id": "L_UFcc1XdqsI",
        "outputId": "83dd8a53-facc-4342-d3de-ab3bbf86ae55"
      },
      "source": [
        "predict('/content/sample_images/10.1.1.1.2023_31.bmp', '/content/best_model.ckpt')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/vgg19-dcbb9e9d.pth\" to /root/.cache/torch/hub/checkpoints/vgg19-dcbb9e9d.pth\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ba20cad16647413aa331ecb758712d7e",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=574673361.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=896x896 at 0x7F1D872AFA10>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=896x896 at 0x7F1D89DDF5D0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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sNq1W6+HhwePxXFxcZDLZqlWrbr311o6Ojm+++YZ0hTQajT/hG/EqlaqpqUmv1y9fvpw8Q3IvZ2fnixaQLBbLyZMnT5065e7uHh8f39DQ4OTkJJfLu7q6hoaGSL83iqJGR0dJtvThhx92dHRERka6u7s7Ojqmp6fbew3azcHrt7e3t66uTiaTSaXS1tbWsbGx8d2gz549KxaLk5KSysvL//WvfxmNRoFAQA7cYDBkZWUdOnTIzc0tPT3d19eXz+cLhUKO4xYvXrx169bo6Gj7fkwm05dfftnY2BgREeHq6trX1yeTyQQCweSLS61WMwwzNDT09ttvq9VqcnGRIt/k/oXTh3xnCwgICA8P1+l0Y2Njra2ttbW1SqWyubl5y5Yt5CIaGBjo6+vT6/V6vZ7P5w8NDbEsq1AonJycMjIyNm/eHBoaWlRU9Pzzzy9btmzFihX2irKbmxt5IY7jjEbjhx9+2NnZGRsbK5VKh4eHHR0dBQKBRCKpra0lX2lYljWbzcPDw3V1dR988IFIJEpPTzebzTExMWFhYTPWe5thmKampjNnztxxxx32ruQURTU0NLS2toaFhUVGRopEIoZhtm7dun79eh8fn+rq6tra2sDAwNHRUZFINDw8rNPpvvrqq9zcXJvNRlGUxWIhZ0JnZ6fBYDAajYGBgfPnzx9/9+Y6zcHrDq7BT/bD6UZxqb4sN0ofl7nwh+DYsWPu7u4rV6685ZZb7r///v/6r/+SSCQURTk7O5eWlgYEBLi4uOTl5TU1Na1bt458PJw4ccLf33/RokUajUan0y1dulSr1ZKOg8nJyQKBIDc312q1ZmRk+Pn53XXXXV9//fW+ffuu/2buNejp6cnPz1+7dq1CoSDZpFqt1ul0ra2tDQ0N69atI5udPHkyODjYZrPl5+d3dXXRNM3n8++///5ly5Y5OTld86tzV2lqjvnK1NbW9vT0LFiwQKlUkmc6Ozvr6ur8/f1jYmIuun15ebmjo2NiYuLAwMDJkye3b98uEonOnj0rk8kyMjJ4PF57e/uaNWtsNtvRo0eHh4ejo6OdnZ0LCgp6enpWr149eZ9zoR0mOH78uIuLy4oVK9asWXPvvfdu2bJFpVKZTCaO41iWLSwslEgkrq6uZ8+ebWpqEgqFBoNh8+bNq1at6uvrKy8vd3Z2TkxMlEqlS5YsmTdvnkAgyM/Pd3FxiY+PH3/U58+fr6urCw8P9/X1raur6+vrW7t2Lbm4cnJyAgMDFy1apFar9Xr9kiVLtFptVlaWVqtNSUkRCASnTp1iGCYjI2Mmm8VkMh0/fjw1NTUuLk6v1585c6a5uTkkJMTT0zM7O/uuu+5ydnY2m83FxcVWq3XJkiVKpbKkpISkZRRF5efny+XymJgY0q/D29u7v7+/pKREq9Vu3LgxMzPTfpPBYrHk5eU1NDQkJCS4ublVVlbq9foVK1awLEv+yERHR6enp/f29tI07ePjc/bsWZqmFy9erNPp9u3bFxwcHBUVNWPNYjAYBgYGTCbT/Pnz7X+6yf0ftVr98MMPOzo6Go3Gw4cPp6WleXt7W63W6urqzs7OJUuWREVFZWVlrV69uq2trbCwkHxz8/LyuuuuuxYsWGCz2Y4dOxYUFJSWlrZ06dKkpKTJ399+1Fz++wPXDwno7LvRc9Bp9aMJLsMw+/fvDwgIIL2yZDKZj48PRVEcx5WWlpKqRk9PT11dndlsDg0NtVgs2dnZYWFhmZmZ9u/o3t7eWq326NGj4eHhfD7/+PHjzc3NMpmst7c3Ozt7/vz577zzzpEjR+wDF2YMy7Lt7e3nzp3btGkTTdMsy/b29ubl5Z0+fbqnp0ckEgkEAo7jOjs7tVptYGCgyWTSarXR0dHLly+Pj483mUw3yoR/V4u8v729vePLnwcPHlQqlaGhoRftyVdUVGS1WkNCQtrb2/fs2aPRaIKCgs6fP+/u7r58+XJyS3F0dDQgIMBmsx0+fNjDw0MikZw7d66iokIqlV5zf+KZxLLs/v37g4KCwsLCWJYVCAR9fX3PP/+8WCzm8XgVFRV8Pl8qlfb09PT394eGhmZmZi5YsIDH49lsts7OTqPRqFAoOI4zmUx1dXUsy5aWlkqlUqlUarFYxr9KVlaWn58f6fSSm5vLcZyPj4/ZbD527Fh4eHhmZqZMJuvo6DAYDD4+PhqN5tixYxERETRNZ2dnt7a2ymSyKelOeoU4jrNYLIODgxKJhJTuRkZGvL29FQpFUVGRQqFISEhwcHAoKipycHBYunRpSEhIT09Pd3d3SEgITdO9vb1qtdrb29vHx4fP54eGhj700EPDw8MREREvvvji+vXrXVxc7K9lMpn27dsXGRkpl8tzc3Pz8/P5fL6Xl5dOp8vNzU1KSlq1apVQKGxvb2cYxmw2V1RUhIeHG43Gb7/9Vq1Wy+Vy8v15Zjg5OQUFBbm4uJAZP8hXiP/85z/Dw8OPPfZYZmamwWAoKCgICgriOI5hmNraWp1Ot3jx4vnz5w8PD9fX13t7e3d0dNA0nZycvGTJkuDgYLPZTL6HhIaGZmRkeHp6ojwJF4U+oLPvon1ZLvM42/HOqMtk4WRU5okTJ2QyGZ/PN5vNk+fAl8vlnZ2dPj4+qampjY2NRqPRycmpvb19x44d/v7+arXazc1NoVAwDKNQKLZt23bw4EGGYaKiojIyMqRSaWdnZ0VFhaurq16v/+1vf+vv7z+Tx240Guvq6srKynx8fEpLSzs6OoaHhysqKjZs2EA+IENDQ8ldzoMHD956663kg0Sr1Z49e/b111+Pjo5OTEwcf1vtJ0On05WUlHR2dsrlcrPZTPoblJaW1tXVOTo6WiyW0dHR8TkBkZKScuTIkaysrNTU1PT09LGxsbGxsY6OjvXr18fExGi1WolEEhsba7PZhELh3XfffejQof3798fGxmZkZGi1WqPROCsHe1UOHjwoFot1Ol1eXt7JkydbWlrUavWyZcvIT0l+o1Qq4+LiRCLR999//6c//SkqKioxMZEM2zKbzaWlpVqt1t/fn4zrItPxODk5sSxrfxWapm+55ZaDBw8eOHCAtM/Q0JBarZZIJO3t7ffdd5+vr69KpXJ3d3d1dbXZbAqF4s477zx48CDLspGRkYsWLSLlxplpE4vF0tHRkZOTQ3oCeHl5PfDAA76+vn5+fufPn6+qqkpMTGxsbIyKiurv71+0aNH8+fMNBgNFUfPnzyfzSxw/fjwlJSU2NpbjOI1GU1RU9Omnn3p5eTU2Nvr4+KSnpwcHB9u/84jF4nXr1h04cIDP50dFRS1evNhms2k0GplM1t/f/9hjj7m6ug4MDPj5+SmVyqCgoAULFhw/ftxisSQlJbW3t0ulUvKiM2bRokVvvPHGoUOHyBeJlpaWmJiYnTt3kj93pKtAaGgon8/nOG50dDQsLCwxMZF0D128eDHDMOvXrzebzadOnWptbY2NjY2NjaVpurW19a677vL19Z3JY4Eby0/tk+mGc6MnlDOQ3FxPFm42mwUCAZ/Pt9lsHMdN6HNGvtNTFEV6XJEyCblPRJ4nUyAxDCMUCklqO0cmouc4jkwCSuYB/ctf/nLfffeFhYWRA2QYxmazXWZCmekzR9rnUshpQMrGNptt/D1BcoeaZVn7SUK6spFzgPzWlb/QbCX9l28fcjKT7hnkv/a5Qu1sNhvDMPaThzSU/VfGs1gsfD6fpmmGYa724iLj8SdHOEcmWifBG41Gg8Egk8n+8Y9/rFixIikpSa/X5+Xl1dfX/+xnP9Pr9d3d3R9//HF6evratWu9vb3H78FsNguFQh6PN74Rxu/fZrORWbFYliWnInmSNOmlApu+9iE9BPh8vkQimfDWsCxrtVonf5Ul54+DgwN5nuTNM9mvd7Kf3pftnza8W7Psqmqfc7ACOscTjik3d47XaDQ2NjYWFhbGxsb6+Pj4+PhcQxerKTd32md2zc0EdO6bIwkoRVFms7mjo+P48ePx8fG+vr4+Pj4SicRkMlVUVJw+fdrZ2dnDw4PjOAcHh7i4OF9f35lJvOZO+8xNSEBvLHi3ZtmN/odgjldApxwSrMtD+xBIQK8NEqzLQ/tcHhLQGwsGIc2+S42zmQsDzGcdRmIBAAD89GAQ0uzDKPjLuCH6IUw3m802PDxcW1trNpvJ1IzBwcEXnROKDHsXiUSz2xNrxphMpr6+vpaWFjLbq1AojIuLs8/IONnw8PDw8PDg4KBGo1mzZs2MzbY4wzQaTWtr68DAAOma6ejouHDhwmv++kpG5JApFyb/lGXZgYGBlpYWjUajUChsNpvZbE5MTHRzc5ubc9AyDNPe3t7R0WGz2RwdHa1WK8dx6enpDMMUFxcPDQ3FxMRcdBqvq3X5drsoo9FYWVnZ1dUVEhIyk7MOGwyGurq6jo4OpVIZHR3t5uZ2+ZhZlh0bGyPD/shUTdcfA8uyOp1OJBKJRKK5eebAlMPbPMt4V2m2451pyMIZhmloaHj00UdlMll0dLREIsnOzr5w4cJFN87Nzf3888/LyspmOMhZYbVas7OzX3/9dU9Pz9jYWIqivvjii7a2tkttPzg4mJOTU11d7evr6+bmxnHcyMjINE1TNd3zFF5m/2az+S9/+cu5c+cCAwN9fX27uro++uij6/nTcfDgwa+++qq+vn7yj8iiYl9++SXDMHFxccHBwZ6enp988klvb+/c/GNlNBrfeuutkydPOjk5xcTEBAYGWq3W9957j6IokUhUVlZWX1+v1+un5LV++OGHb775prm5+cp/RSQSNTQ01NTUqFSqKYnhymm12qeeespqtUql0h/N/8j0CPX19WVlZePn57o8juOsViuZLnTyT9Vq9bvvvrt//361Wn3V0cON6adZAPhpQOUPKIoymUytra3FxcVkGsKgoCCRSOTo6EgSDpZl7V9OWJZduXLl+AHLZPg2y7I0TdM0Tcb2kgHIZM0SMsqb+r8x4OQ04/F45BPI/hIURZFnyDYURV1+rO7M0Gq19fX1zc3NZEabwMBAhmF8fHzsx0LiJBeOzWZ79913ZTLZ9u3b/f39eTzeH/7whx07dojFYrFYTNO0fbQ7GdZNGoH8rn1vLMuS0cpk3Le9TcYPlre39mxlYAMDA6WlpUql0t/f39HR0cvLyz4j1eQ3lOTffD7ffsj2QyDT7rAse/vtt/P5/MmD1jUazf/+7/9KpdLt27fb50739va+++67fXx85loCyrKsSqV66KGH1q9fv27dOvugdUdHR71eT0asFxcXr1y5Mioqymq1Tr6OyDkwod3IFAGT241hmG3btgkEAvuPJl9cE84rsvPKysrg4OCkpCRyjpHfIqfx9DWOwWCora0lMyiRKbesVisJlZwY9oKoPeyRkZHS0tK77rpLKBRardbx8yGQjcmcEvbLkOO4mpqa/fv333PPPXK5nBya/QqiadrJyemZZ54hbwQ16VwlsyDbd3jRaRnghoMEdO66aB9Q5KA3G0dHx4SEhFtuuWXnzp3PPvtsRkZGamqqXq+vq6vr6enh8/m9vb0hISFRUVElJSXnzp1LTEy8/fbbbTbb0NBQdXW1m5vbhQsXXF1dExMTx8bGzpw5IxQKMzMzT548qVKp7rvvvpCQEL1e39HRMX5v5POvubnZaDSq1erW1taIiAiDwcBxnMlk0mg0qampSUlJs9sySqUyPT29rKzskUce+d3vfhcfH3/rrbeOjo4WFBTo9XqapoeHhxUKxerVq1Uq1ZdffpmXl7do0SKLxVJVVfX++++XlpZGR0e/++67GzZsSE9PN5lMVVVVNptt6dKl+fn5g4ODt912m0gkqqurGxkZ4Tiuvb29rq7uzTffNBgMhw4damlpIVP9DwwMbNmyRSAQVFVVubq6FhUVyeXyhQsXzsq6WRRF+fv7r127NicnR6fT7dy5MyQkZMOGDRRFqVSq2tpagUDQ3t6u1+sTEhIUCsUPP/xgNptXrVqVlZWlVCqTkpJGR0erqqqSkpI2btxoMpmys7MLCgrWrl27dOnSCS/02muvNTc3P/DAAxNW7lm/fv3MHe0VGx0dffzxx8maQ+OnTFIqlZs3b6YoqrCw0MnJiabpU6dO1dXV+fj47Ny5k+M4lUpVU1Pj4ODQ1NRktVoTExPFYvGBAwesVuvq1av37t3r4+OTkJDQ39/f0NCQkpJy2223mUymI0eOXLhw4Y477oiLi+vo6Ojt7SUXV2hoaFJSEsuy9vOqra2toaHhzTffpGm6ubnZYrF4enqOjo6eOXOGTAVFrlP7SkvTYWRk5NChQ9u3b3dycjIajbm5uRUVFT4+PiEhIRcuXDCZTL/+9a8lEolWq21ublapVEajsaioqKOjIyUl5eOPP7ZYLBs2bAgICMjOzu7o6PjFL35hs9mys7PJHKJqtToxMZFhmA8//LCnp2fVqlWurq4HDx5sb29PSUkZGxtTqVRpaWmlpaWVlZWvvvqqs7OzTqdraWnR6XQ6na6xsTE5OTkjI+PEiRN6vd5sNmu12vDwcPvstnDjwi34uQt3n4Hw8/P7y1/+snLlyv/93//96quvmpubs7KyDh8+7OXllZaWFhwcLJVKJRLJ6OioQCAg/fDq6+tff/11UjAwmUx8Pl8mk2m12tbWVrPZbDAYhEKhRqOx2Ww6ne7w4cNHjhzx9va2781sNn/00UcXLlwgtRDSTy4rK6umpmbevHlpaWnu7u6z3SoUj8dbuHDh7373O39//0ceeSQrK6u7u/v9998vKSkJCgqaP3++SCT661//SlGUUqmUSCTLli1bt25deHg4j8dzdnZ+9NFH77nnnsDAwKampubm5uLi4uzs7Pr6epqm5XK5r68vy7J79uypqakJDQ318fHp7u5WKpV8Pt/Jyam7u1ur1dpstsDAwPT09JGRkVdffdVms7EsS1p7FnuX8ni8n/3sZw8++GBDQ8Mf//jH0tJSiqL0ev2f//znjo4OjuPMZjPLso6Ojjwer7y8nFT7DAZDc3NzV1cX+dQ3m808Hk8ikfT395OFHkhf29bW1t7eXoqiDAbDmTNnvLy8ZivPvioMw5AcKz093b5w6wT79++XSCRSqdRms1mtVp1OR4qmr7zySl9fH8dxFouF4zhHR0eWZauqqsiyF3q9vrGxsaenZ0K79fX1kaWzDh8+fPToUW9v74ULFwYHB0skErPZvHv37tra2tDQUG9vb3JekVpgVlZWUFBQVFRUW1tbXl6eVqtdu3YtWU5i+hpHr9e3tLR0dnauXr3a0dFRKpX29fX19vaazWaLxcLj8VQqFcdxWq3266+/rq2tDQkJ8ff3ZxhmxYoVHMe1tLSQjullZWXFxcXkhoDFYjl27Fh1dXVCQsKiRYtIxu/l5fXggw+mp6crFIrOzk69Xk9WJluyZIlcLieT8/P5fJPJ9Omnn547d47cuLBarWSqWpIWh4aGLl68GPPb/zQgAZ27MAoeent7q6uraZr28PB45plnVq9enZOT88UXX1RWVioUivj4eIlEkp6enpiYKJFI8vLy5HJ5YmJif39/Xl5eS0sL6XS1adOmW2+91dXVtaGhoaOjIzMzMzIy8tChQ8uXL/fw8CgvL6+qqlIoFHFxcfa9lZeXl5eXj42NMQwTEhJyzz33LFu27JlnnsnNzd2zZ499vdNZ1NDQ0N7eLhQKY2Nj//u//3vhwoW7du3as2fPwMBAeHh4aGgoWeXIHufp06d9fX3Dw8NZlu3u7q6srNy4cSNN0+Hh4RqNpri4WCAQ+Pv79/T0kIFKaWlpNTU1jY2N/v7+AQEBTU1N9fX1pFRmsVhOnTrl6emZnp6+cOFCX1/f8+fPt7S0kPn/169fv2bNmln5gGQYJj8/X6vVSqXS9evX33fffRRFffPNNyaTKScnp7a21mAw2Gy21NTUO+64Izg4uK+vr7CwcP369WFhYTU1NaSiTNN0d3d3ZmYm2SdZWpOm6QMHDnzwwQdffvnluXPnKIoi6zsoFAqpVDrzR3q1yE1kPp/v5uY2eXwex3FGozE7O9vPzy89PV2j0eh0uqVLl+r1+hMnTtTV1RmNRpvNtmjRos2bNwcEBPT09JSXl2/atCkkJKSiosLT0zMtLY0ss2Qvyx0+fDg+Pn5sbKyqqoosPSWVStPT05OSkiorK8efV42NjZs2baIoimGY3NzcwMDAsLCw1NTUefPm7dmz59ixY+np6dO6qERPT09BQcGyZcvc3NzIknIlJSUMwyxZssTZ2bm4uHjLli0ikejUqVMDAwMhISHu7u7l5eWlpaVbtmyRyWTnzp1LSkoSCATZ2dkajYYsjevo6Pib3/zm/Pnze/bsEYlEPj4+LS0tHR0dq1evpijKYrHk5OT4+/unpaWRPzjk5sz27dvFYnFhYWFZWdno6Cj5grdjx46UlBQej/eLX/yiubl5z549JpMpJCRk+hoEZgwS0LkLFVBoa2s7cuTI+fPnSZlKqVQGBATodDqTyUTqlHq9vra2lmGY+vp6sioSRVEajaanp8fPz2/ZsmVJSUmkeFNXVzc2NrZ06dKkpKT+/v7m5may1nlvb6/RaHR0dDSbzTqdjqwA3traKhAIEhMTFy5cSJYc/OKLLwIDA//61782NTV1d3fP+nehioqKrKwsUogSCoWurq5BQUF6vd7T01OpVJpMpsrKyoqKiueee46iKLIoub+/v7u7e09PT2dnJ2lGiqIUCkVpaalMJps3b56Tk1NNTU1hYeFtt90mFovJfOMuLi6lpaU5OTk2m83Ly4tl2VOnTvn7+6enp5OejhqNpru729fXl7Q2j8cjpbKZbxOGYY4dO3bs2LHe3l6WZaVSqZeXl7e3N3n3FQpFamrq/PnzyW3W3t7esrKy1atXJyUl5efnKxSKjIwMgUAwMjLi6elJplOorKzkOI7P58fGxj766KN//vOfX3zxxa1bt1IUJRKJ1q1b19raWl5ebjKZLBaL0WgcGBg4fvy40Wg0m80ajcZkMs18I1wUuXZ27tx56NChrq4uUtvT6/Wtra0FBQWkXBcREbFy5Uq5XN7d3a3T6dzc3Mxmc2Njo6ura1pa2rx586RSqclk6uzsrK2tveWWW+Lj43Nzc93d3TMyMsidejc3N5PJZLVay8rKSMfN3t5e+6VKLi6SZcrlcvt5xTCMt7c3y7IFBQWkFJqdnV1eXn7LLbc89NBDBw4cmL7+xKTE2NLSkpeXt379elKFvXDhgkQiWb58eVBQUG9vb19fX0BAAE3TZ8+e5fP5YrG4tLS0oKBAKpWKRKILFy6QsmVbWxsphfr6+vb393/00Uc+Pj6vvvpqd3d3R0dHe3v70NCQt7c3qXqSZeIXLVrk5eXF4/FGRkZaWlrEYjE5zNbWVj6fHx8fn5aW5uPjo9PpNBrNO++84+jo+Lvf/Y78rZv1DugwJdAHdO5CH1AQiUQWi+Xs2bMdHR0syxoMhocfftjFxeX06dP19fXffvutn58fWXlZo9GEhoZ6enpyHBcSErJp06avvvrqzTffjIyMjI2NdXBw0Ov1YWFh8fHxNptNq9WuWrVKLBZzHLdixQqr1drQ0PDtt9/6+/vHxsbyeLxNmzbp9fr8/Pzu7u7IyEiKourr64uLi/V6/c9//vMJff5mhUQiGR4ePnXqVE1NjclkkkgkTzzxBJ/Pz83NHRgYUKvVIpHoD3/4Q2BgIMdxR44cWb58eVhYGEVRLMvKZLKwsDAyvsHLy+uxxx4jU89ERkaSESrkJTIzM7Oysk6dOhUXF7d06dLm5matVuvh4TEwMLB582ayN4qigoKCbr/99s8///ytt96KiIiIi4vz8PCYlQ9I0rWgrq5OpVJJpdKxsbHk5OT169eLxeIHHnjg3Xff/f7774ODg2NjY0NDQw0Gg0gkevDBB/l8/tjY2Pbt2xMSEvR6PWkcMsJDpVLFx8crFIqL/tn59a9/ffjw4Zqamr6+Pm9vb5FIJJfLV61axePxyHqViYmJqampM94MF6dUKt9+++2PP/740KFDxcXFSqVSLBb7+vqmpaUZjcbBwUGy+rlarfb09JTL5Var1dXVdceOHe++++7XX38dEhJC2m1sbEwmk+3YsYOiqLGxsZ07d0ZHR4+OjsrlcmdnZzLaRqVSJSUlyWSyFStWiMXi+vr63bt32y9Vcl6dPHkyPj5+6dKlra2tWq3W3d1dp9MFBAQ4Ozu3trZ2dHSQpPnZZ5+dvi97JpOpqamprq4uODiYfE0Vi8X2r6lGo1EgECxatIhcKZs2bTp69OjJkycTEhKWLVvW1NRE1qr19fXt6OhISkrKyMiwWq1kfeDa2tqioiKTyXT//fdHRkaOjY0pFAqRSEQ6BfX392/dujUgIICEQdZ0TUlJIUO7NmzYoNfrCwsL+/r6oqOjIyMjrVZrXV1dcXExn8/fvHkzyp8/GbilO3fdEKPgp7sSNtcOeYaPl2EYMkRUp9Px+fzxM6SQHof2zmFk4C0ZLmp/xmw221dqnvAqVqvVPuB08t4IMhLWPhqaYRgyqvcyjTBj7UNiI30uBQLB+BvB9gG8ZACETCZ7/fXXt27dGhkZKRQKuf93zXcyyNc+jQDpwTZ+V2S8LXkjLjO76mVae7ypap9LXRdms1kkEhmNRrKe+4Q3lHzSX2b4sH2Ms30B9x9dnZwsCM4wzPjJIO3zM1xtIj7d7UNRFMuyJLW66H1t7v9dwp4gC7tf5li4SQvf22w2+xQTky+ui55X5PQjv2J/Fya86Ay0z3jkqref9mT9ej6fP/5KMZlMZOZOMrHGRf9cTDivJgdDGnD89UWu4vED6kmn28tPCDDrd2bgquDdmmUXzTLnZq55VWb4D+WMudkS7kuZrT/0V94+RqOxubk5Ly8vPj4+KCjI09NzOkZyzP12uLH8VP9uTBW0z+UhAb2x4Bb8LOPxeC+99NLkx5dffnm2Q5sTbrZ2uNmO92pdQ/ucPHlyOiKZXW+88QYpc852IHMUrqPL+wm0z0sXM9tBwdVBAjrLvvnmm7vuuuuij7Md2pwwF7obzqSb7XivFtqHCA8PJ7MpzXYgcxTOk8v7CbQP+Yic8HjXXXfNclhwNVCvnn0/vfvv1E/3VhFuwRO49UygHabWT/XvxlRB+9hdtOvabAcFVwcV0Fl2hX1ANRpNVVVVe3s7mRmYLGK2detWiUSCq+4yGhoaLly4EB0dvWDBAvIMwzD9/f1k6LRQKIyMjCRLAVVXVx88eFCn023bti0hIUEmk81u5HYsyw4NDWVlZfF4vMDAwKSkJIVCMWGDlpaWrKyszs7OpKSkZcuW+fv7UxRlsViqq6vPnj175513jp+202w2NzU1ffbZZ88++6ybm5v9eYPBUFNTs2/fvhdeeEEikczU8V07hmGampr+v/buPD6q+vof/72z75mZ7Mtk3xNICFsgQCDsi6K4VXFBbd231k+11Y+1trbW2qpt1bpUFBUpWhREhLCEPUAWsu8Jkz2TTLbZ93t/f9zfZ74phEggk5mE1/OPecDkzp3zfs9dzj33fe89e/Ysj8eLjY2dPXv2RRcJmc3m+vr677//fnBwcOXKlQsWLFAqlUNDQyUlJUePHqUo6p577klISPDoXb4nn9PpPHbsWGdnp1KpTE5OTkxMHHWy4eHhioqK6urqhx9+eOSlIUNDQ01NTV1dXZGRkRkZGV68o/7EYi682717t9lsDg0NTU9PH/VerT09PadPnz5//rxMJlu/fv2MGTMIglCr1fn5+S0tLenp6StXrvT6TXAn1kVbmFmzZjG30L9IXV3d2bNnZ82a5X4Eml6v3759e19fH1OJFwgECxYsYO4DOglGvU0h9oZTC26m5WVXkn22t7e/9NJL9fX1K1asuP/++zdv3jx79uxt27Z1d3djENgYNBrNsWPHduzYUVNT435Tr9c/9NBD8fHxGzZsMJlMhw4dKikpaW9vV6vVd9xxB4vFevbZZ8vKyrwY9kg0TVdWVr711lvh4eF33333V1999cMPP/T19bknoChKp9N9/vnnkZGRwcHBf//731999dX29na73a5Wq/ft2/f5559rtVr33E6cOLFly5ba2lq9Xv/KK6/8/e9/b2pqoihq7969TzzxRENDQ39///PPP//ee+91dHR4qdFXhKKoH3744ZtvvklJSVmyZMkbb7xx4sQJk8nknsDpdLa2tn777bc5OTlSqfSJJ5749NNP29raWlpazGbz2rVrBwcHN2/erNFovNiKCedyuV5//fX29valS5c6HI6tW7dWV1dfOpnRaKytrd2zZ8/OnTvd5/GdTufhw4ffffddtVq9cePG2bNnT6fsc2Bg4Omnn2az2Rs3bqysrPzqq6/UavVFk1ksloKCgsHBwaSkpLKysjvuuKO6urq/v//8+fOZmZnx8fHffPPNO++845UmeAhN0xUVFe4tzM6dOy/awjDT9PT0FBQU7Nixo6GhgXnTYrE0NDScPHlSLpdHRETweDyNRnPRBz0KD2qZBqbJ9mXqGrsCSlHU4ODgfffdd9NNN61ZsyY4OJggCKZu9+677wqFQmYynU43ODhoMpmcTqdSqWSe1dHc3Ozv7282m+12u1AoNJlMzLNPhoaGmAFAPT09NpstPDw8Pj7e5XI1NDTw+fzh4WHmOTcsFqujo6O7uzs1NbW1tVWv1ycnJ4eFhRkMBuZZ0gkJCUFBQRaLhblXc0hIyBg3qfGKkJCQnJycM2fOuN9h7sDS3t5+5MiRpUuX2mw2FovF5/MTExNTUlJcLhczhMijj10el/7+/rNnz5aVlf3hD39gs9lLly7dvXu3QqFYu3YtMwFzc9D//d//ZTrfbrd3dXX19fVFRkZGR0cvX7784MGDI2fIPH3k2LFjra2tM2bMmDVrVnBwMEmS8fHx6enpJ0+e7OjoyMzMnDt3rlKp9EKDr1hnZyfzsOy5c+fq9foVK1b85S9/+cc//uG+Pafdbvf393/55Zc5HE5eXp5arTaZTFarNSsra86cOUaj0eFwMPcq8m5DJhBFUTU1Nfn5+S+88EJUVJROpysrK/voo4/+9re/XTSlRCJJTk6eN29eSUmJ+7O7d+8uKipKTk5evHjx8PCwjy8A42Iymc6fP793794XX3xRLpdnZWV9880333///ZNPPjlyMqPReOONN4rFYhaLFRcX95vf/Ka1tTUuLm7Tpk0kSQYFBTG3FvJWKzyB2cKUl5czW5hly5Z9++23CoVizZo17mlIkgwNDV20aBHzECwGi8WKjIzcvn07k/Z98cUXMTExCxYsmLTIUQGdBlAB9bKxK6DMQyMuXLiQnJzMPE6XOV1y4sSJY8eOFRUVDQ8PDw4OHj9+vLi42GAwlJaW/upXv9Lr9RaL5be//e327dsrKira29uPHz/+3HPPnT9/Xq/X79y586233jp37pxWq927d+8bb7wxNDTU0tLy9ttvd3V1FRUVbdu2rbCw0OVylZeXP/HEE+fPnx8aGtq2bdvOnTtbW1sdDkdRUdEf//jHyspKgiB0Ot3hw4dbW1unxKAiFovl7+//xhtvfPPNNz//+c9bWlpmz56dlpbGZrMNBsP+/ft/97vfKZVKmUzmI83p7e1tb28PCQlh7t0YGRnZ0dHR39/vDo+5ETSPxyNJ0mw2BwQEzJkzx32FwaibY+Zu4UFBQWlpaTwez11EDwgIYB7OmZ6eztwUc1KaeJVaWloMBkNAQACLxeLxeNHR0ZWVlWaz2T2BSCQKDg5m0gWDwRAVFZWdnc0806W3t/ebb755880309PTeTyej/zW146iqNLSUqlUyjznXS6Xc7nc+vr6yzVw5OLR29v73XffDQ0NhYeHHz169LXXXjt37hxzZ8dpwGAwVFZWRkZGMmtKSEiI0Wjs6Oi4qGcCAwOlUimLxbLb7SwWKzMzc+HChcyDyM+fP//Pf/6zqqqKebSBl9ox8TQaTUdHR2ho6OW2MG4XbUz4fD5z7EoQhF6v7+7ulslkERERkxY5KqDTwLQ6mJuixnjiEZNuMvfTZh7pRpKkVCoViUQvvfTS22+/zeFwSktLT548KRaLmVsrL1iwYHh4ODo6ms1mR0ZG3nzzzXK5fP/+/SwWixkQptFojh8/HhgYmJubq9Ppdu3aNTg4GBER8dxzz7W1tQ0PDzc3N8fFxclksrCwMIqiUlNTVSpVS0tLZ2enRqOJj4/Py8vr6+vbsWNHXl5eQUHBL3/5S51Ox+fzp8RgcJqmmYGeDQ0Nx44dY7PZERERQUFBIpFo3rx5LBbr1VdfDQ0N3bhx48jxkSM/PpmD3x0OB/P8bua/LBZLLBaPvIH8SAcOHIiJiZk9e/blBrCSJBkdHa1Sqcxmc2xsbHJyMlP/I0kyOTk5Pj7eaDSmpqYyGfnYgV1JTuNRNptt5H2I2Gy2VCodNWyapr/44ouNGzempqYyY1sVCkVubi6Hw/nNb36TlJS0ZMmSqx7yO95cxKP9Q9O0yWRyPwiUJEkej8dsNH70s7W1tQ6HY86cOYsWLWpra6usrHz99dc/++wz3xkMfS0oimIeAunuGYFAMMZTA+rq6hobG3/+85+7y8Dx8fG33Xbb559//uWXX8bGxiYkJExe9J406haGSdOvfCbHjh2LiIhITEyczC0/KqDTACqg3jfqisT8icfjrVy50t/fnxmnyKxgAoFAqVSazWalUsnj8Uwmk1arDQoKuvHGG++6666f/exnMpmMef4Ej8fj8/nMAznYbDZzsQWPx+NwOMzTTRg2m629vf23v/2tWCxesGBBSEgI82gK5kEmzCN6mUyFqYrFx8ffcMMN9fX1e/bsaWlpIXzpnPXYXC5Xd3f3yy+/nJeX96c//enRRx/t7+8/dOgQQRBsNjsoKGjdunXLly9nnmQ96hwm+bA7MDAwODi4ra2NybS6u7tjY2ODgoKYR4Mw09A0bbFYdu3aFRoaOnfuXOYpgu4/XZQhMQ8XkclkmZmZzC/rbgWXy1UoFMx1J+73x+DdCkRUVBSPx+vp6aEoyuFwdHV1ZWVliUQi5oErzDQURfX392/dujUnJ2fGjBl8Pp/pRh6PFxUVtWHDhry8PK1WO7JuOqWxWKyZM2f29fXp9XqappllOD09nfmry+W6aGEYubVRKpV8Pp/NZguFwrCwsOzs7M7OTh+vgl85sViclJTU2Nhos9lomu7v71coFDExMcSIhxgx7Hb7uXPnOjo6li9fHhERwUxPEIRMJps3b96aNWtUKlVXV5fXWjLRAgMDg4KCWltbR25hAgMDif97nNWPzsHlcp08eVKlUrlHvwBcIVRAvW+MCiibzU5OTv7DH/6we/fuPXv2LFq0KDQ0lMPhqNXqoKAgiUTCYrFmz5594sSJgoICh8PBXJ65bNkyjUZjsVi6u7uHhoZYLNbQ0JDRaOzs7AwKCtJqtUNDQzqdbmBgYHh4WK/XNzc39/X1DQ8PM5/SarUajaazs7Ovr48ZMSkUCgcHB/v7+/V6vd1u5/F4MTExP//5z1944YX33nvPq503FpvN1t3dPTg4ODAwoNfrZTIZk0lHRUXV1dURBBEWFjZjxgyxWFxfX9/e3h4eHu50OgUCwbx580a9QpaY9ApoeHj4ihUrurq6CgoK4uLiKisrV61alZ6eXlJSMjAwsHDhQqFQ2Nzc/PHHH/v5+RkMho6ODofDoVKpFi9ebDab29vbDQZDX1+f1WplziROIO9WIJKSklavXl1VVXX69GmxWFxTU/Pwww8HBgYeOHBAqVTOmDGDOR/9zTffhIWF1dbW1tfX22y2+Ph4sVg8ODgYFBRkNBqVSuXixYunzWBHNpudk5Ozbt06jUZTXl7e0tIiEAhuuOEGgiAoitq+ffu8efNiYmKYRFyn03V1dRkMBo1GEx4enpqampWVZTQaS0tL2Wy2RqN5+umnJ3yZ8RY/P7+8vLwNGzaUlJQwt7xITk7Ozc0lCIIZibRhw4aAgICenp49e/Z0dnYyZwmcTqfL5VqyZElLS4tMJmOGyCcmJs6ZM8fbDZowERERK1as6OnpOXr0aGxsbEVFxerVq9PS0miarqurq6+vX7ZsmUKhsNlsXV1dQ0ND/f39BoNBKpUyH6dpury8XKVSMYNhvNsWmHJQr/a+K7kPaFtbG1MGY06o2Ww2k8mUnZ3NFDtbW1vPnz/P3HglMzMzPT29q6ursLBQoVCkpaVJJJKmpqb6+vqZM2fGxMRUVFT09fUlJiYGBASo1er29vakpKSAgIDDhw/7+/sHBARoNBqpVBoXFzc4OFhVVTV79uyIiIjKysrh4eH4+Pi4uDgej+dwODo7O//xj3+8+OKLAQEBnkvIrmW4ldVqbWpqamxsDAkJSUtLY+5e5HQ66+rqhoeHFQoFQRB+fn5CobCjo6O+vl6lUnG53LCwsKCgoMtdmzL59wG12+29vb2tra0ymczhcCQmJkql0qKiIq1Wm5OTIxKJGhsbS0tLmadIUxQVEBCQnp4eExPDXOnc3NycmZkZGxs78mnpE8Ir9+Eb2T9ms7mrq0ur1YrFYqfTmZGRwWaz9+3bx9RxXS5XXV1ddXU1c17e5XJFRkaqVKqhoaHu7u7Q0FA+nx8REREYGPij4w0m0CTcx3FoaKi1tZV5hrufn19cXBxBEBRFbdu2bf78+bGxsQKBwOl0DgwM1NXVdXV1LV68OCwsjMPhDA8Pd3V1mc1mDodDUVRaWtqPPtp+wnmufyiKGhgYaGpqEggENE2Hh4eHhIQQBNHb27tnz54NGzYEBwd3dHRUVFT09/ezWCyaprlcbnJycmBgYElJiVQqlclkCoUiNDR01LsUTQ5P9I/NZuvr62O2MHa7PSkpiRkEX1NTU1dXl5eX5+/vb7VaGxoaGhsbVSpVSkqKuwdomi4qKvL39w8LC5vwLcxVwCn4qQW/lo8adQfDnC2iaZo5gX7Rn5gU5KoPQ92jo9z/GHWy/v7+xsbGlpaW7u7uzZs3MxVZ30xAx54tEycTKv1/riQX8Wjidbn2MuG5f9yL/us7Jj9Bv6grmLVgjDCufU25FpOQgDIu7Ycf7Rn3nL24aHm6fy5a8Yn/Wx7GXvGZcR3MuKYJCe+qea5/Lv3dr3BJYA51vN4zDB8JA64QTsF735VUQBnMAL7L/ekaCznuVXfsdZi5JX5XV9e9994bHh4+RVf4i/bEV7Jjdk856qunXXXAnuOVCuioYYz83h/dX177mjIlXNoPV5hT+sKi5TmXtu5KlgcfPNKbcKP2zJUsCdPsvlQwmabthmaq81DlzxO8UhH0ouutveMy+RXQqWXSKqBTFPpnbOifsU3jY6dpafof2Pm+US/m8HJMcBneqoD6IHQFAABcNRTPvW/UHTlyUPBlo5aBvXUW/jp0uX7GdgMApgpUQOGaoAw27V3uAAnZ59g8vWrgzAkATGlIQOGaYC847V3ufp9XfvHc9cnTqwaO/QBgSkMCCtcEe8FpDxXQq4MKKADAGJCAwjXBXnDaQwX06qACCgAwBiSgcE2wF5z2UAG9OqiAAgCMAQkoXBPsBac9VECvDiqgAABjQAIK1wR7wWkPFdCrgwooAMAYsMPwUVNoX+KVRMRb/YMn/YwN/TM2PMlmbOifsaF/xoZj4KkFFVC4Vp6uxKDS45tQ/B4b+odxuX5A/8CVwHIyjeGH9FFTKMdCBXQCTaHffVTon7GhgjU29M/Y0D9jQ246taACCtcKFdDrEyoTY0P/MFABhWuB5WQaww/po3wnx6IoisUa60AFFdAJ5Du/+9VB/4wNFayxoX/Ghv4ZG3LTqYXj7QDgWnV3dx8+fLioqEgul99www3z58+fkNkaDIaTJ09+8MEHGzZs2Lx5s0gkutyUl7tNz4SE4Z7btdzuR61Wl5eXd3R00DQdEBBw4403isViFotFUVRJScnhw4c7OzulUunq1auXLFnC4fjWSmGxWFpaWo4ePSqRSPh8/uLFi8PCwthstnsCp9N59uzZo0ePNjU1xcXFrV27Nisra2QrLly48K9//Wvu3Lk333yzyWTSaDR9fX3vvvvu888/HxYWxszWYDBoNJr29vYvvvjiN7/5jZ+fn1Qq5XK5YwTm9avg9Xp9ZWVlRUWFRCIRiUSrV6+WSCQjD5Zomtbr9Tt27Kirq3M4HHPnzl22bFlkZKRGozlx4kRpaelrr73m7qihoSGtVltTU3PixInnn3+ex+P5+fmxWKyBgYGBgYHS0tK6uronnnjC/f6Phuet/unt7T1x4sTQ0JBQKIyJiZk3bx6Px7toGoqimE4oKSl57bXX3D+02Wzu6upSq9VGozEyMjIzM/PaV4cx7pkwmf3jcrl6enr2799PkqRQKJw5c2ZycvKlS/jg4GBJSUlLS4tYLPb391++fDmfz6+srOzu7rbb7Xa7PSgoaN68eUKhkKbpjo4OvV6/a9eupKSk5cuXC4VCiUTidDo7OzsNBsMXX3yxePHi+fPni8XiMbafXvejWxhmaTl48KDD4RAKhampqTNmzOByuTRNOxyO06dPHzx48LbbbsvKymKmt9lsXV1dBoPhgw8+uOuuu5KTk8ViscPh6O3tbWtr+/LLL3/zm9/IZLIf3cIwcMe3aQyn4Ke8sLCw0NBQvV7vdDonKvskCEIqlUZFRcnl8h9d1T19iuQa5z80NLRz5061Wv3YY4/dcMMNBw8e/PDDD/V6PUEQzc3NdXV1crl848aNGzZsyMrKGrnZ9QV2u/3s2bNvvfVWbm7ufffdV19f//XXX7e0tLgncDqdfX19XV1da9euveOOO8rKyj744IPGxkb3BC0tLd9///3Jkyf7+vpomlar1du2bTt16pTNZtuxYweTqdA0XVtbu3379nPnzplMpq1btxYWFjJdNAbvDo2wWq3/+c9/8vPzV69evXr16oKCgh07dgwNDY2cxmAwFBcXazSaFStW3HTTTUuWLAkJCbHb7UNDQy0tLefOnaMoyt2W4uLif//73+Xl5X19fR999FFpaanFYiEI4tSpU19//XVNTU17e/snn3xSWVnpcDiuJMLJ7x+apg0GwyuvvOJwOG6++ebAwMB9+/YdPHjw0imZTrhw4UJRUZE7Kq1W++23337zzTd+fn4333zznDlzJuRg7HL9MJn943K52traHnrooYSEhDvvvNNsNu/Zs6ekpOSiycxm80cffVRVVbV+/frZs2cfPHjwq6++MpvNf/zjH9ls9rp160JCQsrKys6ePcvMc/v27QcOHOjp6Tl16tSePXtaW1tpmjaZTP/6178OHjzY399/+PDhH374oaOjw0PtunZ2u72wsPDtt99eunTpfffdV1dX95///OfChQvuCSiK6u/vf/rpp4OCgm6//XaSJL/77rvCwkKCIGiaNhqNXV1dxcXF/f39zPQ0Tff29m7duvXo0aN6vX7Pnj2HDx/u7e1ltjBFRUVGo3Hr1q1nzpwxGAxXEiGGYE1jSECnAzabLRQK+Xw+81+Koo4cOZKfn//BBx8cPHiwtrZ2586dr7zyyuHDh5966qmzZ8/u3bv3hx9++OKLL7788svm5maCIFwuV1lZ2b59+z755JNdu3Yxb7JYrCs5QvXxMaD19fVqtdrpdHI4HLlcvnTp0m3btun1epqm8/Pzd+zYkZ+fX15eHh4eLpfLfe0Mjlarraio6O/vT09PZ7FY8+bNO378eG1trXsCFoslkUhuvfXW2bNnr1+/PicnJzAwkGkFU/I5depUWlpaaGgoM73FYunu7jYYDHw+v62tzWQyMZ1pMpl6enpMJhOXy71w4YLVavX6gcfYWltbq6urnU5nXFycSCTKzs7+5JNPtFqtewKapjs7O999990jR4589913XC43MDBQIBAIBILQ0NC4uLiLZqjT6Xp7e61WK0EQFy5ccDqdzEwGBwf7+vpsNpvT6WxtbXW5XFcY4eT3D0VRFRUVDQ0NQUFBAQEBkZGRbDb7P//5z6VTMp0QGxvrfsflcn366adFRUUxMTEcDmfkQc418oUxoEajsaysrLm5OTExUSwWp6amtre3nzhx4qLJGhsba2tr+Xy+SqVSKpXx8fHvv/++3W4Xi8X//ve/d+/e3draymazmX6jabq7u3twcJD4v/I5s8q4XK7Ozs7h4WGSJLVa7cDAgC8nTH19fZWVlf39/WlpacwW5tixYyO3MBaLpbS0tLGxMSYmRiaTJSYmDg4O5ufnEwTBYrEUCkVKSopQKBw5T7vd3tnZqdPpOBxOd3e3Tqdj8nL3FqalpeVKtjAMjAGdxpCA+qjxrnXuldlms505c+b48eOxsbEzZswQCARSqZTFYn399ddGo/Gee+5xOBwHDhxgs9kxMTG1tbVfffWV3W5vamr66quv0tLSbrzxxoKCgk8++eRHC2BXHep4XeP8ExMT2Wx2dXV1W1uby+XS6XROp5M5j/Pggw9u27Zty5Ytp0+f3rJlS3d3t7sk5iN6e3s7OjoCAwOZc77h4eFarZapWTITsFgsmUzGZrNJkhwaGlIqlXPnzk1MTKRpenh4+IMPPlizZk1MTAxzIEGSZFpa2vPPP5+bm2u1Wl988cUNGzb4+/uTJDl37txf/OIXCxYsoCjqtddeW7FihVwuHzs271Ym1Gq1Xq9XKBQkSXK5XJVK1dzczKSPDJIkExMTt27dun37drFY/OSTT37zzTeXK7qQJLly5connngiIyPDz8/vjTfeWLhwoVAoZLFYGzdufPjhh5OTkyMiIl599dXZs2dfyVEZ4Y3+oSjq/PnzYrFYKBSSJOnn58fn85my3KjTj1yP1Gp1SUmJ0WhUKBRlZWWPPPIIs2W49qh8oQJqMBiqqqrCwsKYmm5gYKDVatVoNBd9Y319vdPplEqlzGl6f3//+vp6giD++te/SiSSF1544fTp0ytWrIiMjCQIgsPhPP/887fccotcLt+wYcPDDz8cFxfHdPsrr7xy4403ikSin/zkJ1u2bImKivJQu64ds4UJCgpyb2F6e3uHh4fdE1it1vPnzwcGBvJ4PJIk/f39XS5XV1eXu+tIkhy5IJEkqVKpfvOb36xevZokyccee+z2228PCwubN2/eL37xi+zsbJqm//SnPy1fvtzPz+9KIkQFdBrzreFucNXcmwAOhxMXF1dWVlZdXb1q1aq8vLzg4GCBQODn5zdv3rzQ0FCXyxUVFaVWq8vKyrq7uwMDAw0Gw/79+5uamo4dO6ZQKFatWhUSEsJUgK7wez16eHqNA4D8/f0feeSRAwcOvPfeexERETt37ly3bp1YLCYIQiQSiUSim2++OSYm5p133tm/f/8999xz6YA5L2L2l+79gcViCQwMlMlkl3ayTqfbv39/amrq7Nmz2Wx2e3v7559/HhsbW1ZW1t/fr9Fo6urq6urqkpKS4uPjY2JiMjIyFAqFe8iBVCpNTEyMiYnJzs5mUtIfjc27Y0B5PJ7D4WASSoqiLBZLVFSU+yQAg8PhKBQKhULx9ttv/+Y3v2lvb29pacnMzCRGW0rlcrmfn19MTMzatWsVCoX7fX9/f6VSGRsba7PZfjQpH8mj/TPqzB0Oh0gk0ul0TOLocDg4HE5YWNiVHLuq1WoOhzN//vyVK1d2dnYODQ29++67a9euvfbVwRfGgLLZbD6f39/fzxxhWq1WqVR66XIuEAgsFgsz9MLlcrlcrujoaIIgdu3atXTp0uzs7B9++OGVV1759a9/nZGRQZJkREREWFhYfHw8j8dzVwHZbHZUVJRKpUpISGAq7h5q1ITgcDjMsSvzX4vFEhQUJJVK3RMwufjg4CCzR7DZbMxmc4wfi8/nx8bGRkVFJSYmugd68vl8ZguzcOFCpVJ55b81xoBOY6iATgc0TVMU5T46NJlM77333ubNm0+ePPnxxx/X1NSMnLi0tPRvf/ub0WjMzs6OioqiKIokSYlEwpyfWrNmTU5OTkREhO+Uea49x505c+Yvf/nLp556SiQSZWRkPPXUU8zYVqfTyZxRFYvFCQkJKSkpV3JxyWQKDw9PTEzs6+szGo00TTc2Nqanp6tUKpvN5q72URTV2Nh46tSpjIyMmTNnWiwWrVYrEoni4uL0en1zczNTLOzt7WWGgZIkyeFwAgICLhrwSpIkj8cLCAi4wu71bmUiOTk5MDBwYGDAYrHYbLb6+vrly5fLZDKLxeKu21EU5R6vqVKpUlJSAgIC3H+6NFqSJAUCwcjs0/2+UCgcV/ZJeLh/Rp05i8VatGiRzWYbHh52OBxarZaiqJycHOYjRqPxovEDIzshNjZWJBIZjUabzSYUCqOiopjqsodCHePVE5jDb41GYzAYXC4Xc1YhPT2dIAiXy8WsXARBZGZmikSiwcFBq9VqMBh6enrWrFnDjDaWy+V33nnnz3/+8/T09JHDalkslp+f30XnoJn35XK5j2efBEFEREQkJCRotVqTyUQQRGNj44wZM1QqFUEQDofDbDaLRKLFixcPDg4ylxl0d3dLpdJZs2a558AsRZf+dmw2W6lUjtyPMFuYKzy+dUMFdBpDBXTKYwbx1NTUmEym+vp6lUpVWlpaVlaWm5s7Z84cuVxus9kaGxv7+/uPHz++adMmm82mVqt/+OGH+Pj4tra2wcHBjo6ONWvWHD169KWXXvL3909KSlq5cmVGRkZ3d3dzczOzRebz+aNeoOP7FVCXy8XU/9ra2vz8/F599VVmC9jZ2fnll18ODQ1FRUUJBIJZs2bNmTPH1y5CUiqVK1eudDgcn376aVpaWltb2/r161NTU3ft2nXhwoX77rtPqVQeOXLkzTff5HK5fn5+bDY7ODh41apVGzZs+MlPfsLMpK2trb6+fsmSJbm5uRMYm3croGFhYbfddltRUdGXX34ZEhIyMDDw0EMPBQQEvPHGG+Hh4Rs2bBAIBOfOnfvyyy/nzJnD5XJlMtncuXNDQ0OZAWplZWV9fX3l5eUZGRkX1U0nyuRXQGmaTkpK+vnPf97e3r5nzx69Xh8cHLxx40aCIFwu11NPPfWTn/wkOztbJpON7ISKioqMjIyoqKibb765oaHh22+/lUgkbW1tL7zwwoTkT75QARWJRHPnzv3tb3+7b9++hISExsbGrKysJUuW0DR94cKFl19++YUXXkhMTIyKitqyZUttbe3XX38tFAopinr88ceVSuWiRYvKysqYmmhsbOylA4inLvcW5pNPPklLS2tvb9+wYUNqaipN0wUFBYcPH37sscdmzpz54osvFhYW9vT0tLe3Jycnr1ixgiAIiqL0en1JSUlHR0dDQ8OsWbOCgoImPEJUQKcxDOb1XVe41lEUZbPZHA4Hi8USCAQsFstsNjudTr1eL5FImAGgzA1E+Hw+n8+nKIoZFc782+VySaVSNptttVr7+/udTqefnx8zrNDpdFosFuYKpzFKg15JRK58A2SxWAwGA1Pl5XK57gt7XS6XwWCwWCw8Hk8sFnO53CvJPj3dtEvbxVRqrVYrU5pifouhoSGHw+Hv78/8uMxJQwZztnHkmVPmDDWHw/FQpjXSZPYPU+C0Wq1Op1MsFvP5fJIke3t7+Xw+M0qBqQXSNC2VSvl8PnO2kaZpl8vFXFQkEomYNz0a80gT9V1jLP9M62w2G4vFEgqFzJJA03RnZ6e/vz8zPHTUTnC5XMwq73Q6mTvyTGbPMDzaPy6Xi6mXM2fMmU2BzWbTaDTM8FCSJCmKstvtzCUyIpGIWWWYVczhcHC5XOaD3jpV4on+GXULQxCEwWAwGo1BQUFsNtvlcjETcLlcgUDgrmsy3WW323k8Ho/H8/oZpMlfYuFa4NfyXVPisG9yck3f6YfJT0B9lo8feHidp/vHp9aLMXilAuqbXXHtJuEAxteMqwKKBHRqwa/lu6b0DsbTX+qtrkACOjb0z9iuwwRiXNA/Y0P/jA0J6NTiW5dcwJQzOWNAR30F75qEn35K82j/TKHOv1yoU6gJ4EVYTqYxJKDeN2qCNVWyrkmIc0psgKbK7zVRpsSPMjlG7QpP98/1trxNY0jQJxA9Tt6O93qHBBSuCbaS1yckQG7oirGhfwBgVEhA4Zpg73J9woGHG7pibOgfABgVElC4Jti7XJ9w4OGGrhgb+gcARoUEFK4J9i7XJxx4uKErxob+AYBRIQGFa4K9y/UJBx5u6IqxoX8AYFRIQOGaYO9yfcKBhxu6YmzoHwAYFRJQuCbYu1yfcODhhq4YG/oHAEaFBNT7pnQOd73tXa639sKPmtLr7yRA/1wFdJobNrnTGBJQ78MKNoVgxwAXwfo7tlH7B+sRXCEsKtMYElDvwwo2hSDbgItg/R3bqP2D9QiuEBaVaQwJqPdhBZtCkG3ARbD+jg0VULgWWFSmMSSg3ocVbApBtgEXwfo7NlRA4VpgUZnGON4OAP7/esBFr+Oag81m0+l0BoOBxWLJ5XKFQuGhUKcus9k8NDRkMplYLJZCoZDL5Ww2m/mTw+EwmUxWq1UoFMpksrGzh8nPNmiattvtWq2WIAgmQi6Xe9EEZrNZq9VaLBaZTObv7y8QCNx/NZlMJpOJzWZLJBI+n08QBEVRJpOpq6srNjaWx+O5p3S5XEajUaPRxMfHuzvHl9E0bTKZhoeHWSyWSCTy8/O73G/hcDg6Ozv9/f1lMhnTzOHhYZqmpVLpyCXB6XTqdDqdThcbG3vRx4eHh81mc1RU1KhhXPrqxRyUpumBgQGr1crlciUSiVgsHnUai8UyODhIkqRIJJLJZEwnmEymoaEhs9nMZrMVCoVCoWAaYrfbBwYGaJoOCwsbOR+bzdbf38/hcIKDg8eI59JXb2XtNE1rtVq73c7j8SQSiUgkunQCvV5vMBjYbLZYLJbJZO4/2Ww2k8nkdDpFIpFEImHetFqtvb29UqlUqVSOnI/FYtFoNEql0s/Pz9ONukY/uoVhMGuNTCYb2ScMp9PZ09MjFosv6oQJcenO8Sp2keCbkIB63xgVgitks9mKi4v37dvHZrOffvppJKAXcTqdZWVl+fn5VquVz+evX78+MzOT2eO2trbW1dXZ7XaVSuXv7y+VSsfeEY66KfTovrOvr+/s2bNDQ0Px8fFnz55dtmxZamqqUCh0x2O1Wr/99tvBwcHGxkaTyZSXl3fTTTdJpVKr1VpcXNzd3R0aGhoUFMThcHg8Xmtra2FhYWho6Pbt21evXh0REZGYmOjv719fX19RUSGTyb799tv169cHBwenpKTI5XLPtevaNTc3V1ZWOhwOf3//4uLizZs3h4WFXbrvpGl63759n3322WOPPbZ8+fKysrLS0tLY2Fi73X7s2LG77747KSmJz+eXlpa2tbW5XK5Tp06tXbvW398/PT1dKBSePn26v79fr9dXVVUtX748ICAgIyNj5LdM8vLwo06fPt3W1iaXy3U6HUEQa9asuTQtaGtrO3/+vMViCQ8PP3Xq1G233RYTE0OS5JkzZ44fP26z2WQy2dq1a/38/Fgs1sGDB51OZ1tbW29v76JFi4KDg2fOnElR1N69ewUCQU1NjdVqnT9/fmhoaGpq6qXxXC6BmPx+o2n66NGjXV1dgYGBTNa4bNmyi7aWVVVVdXV17pXl9ttvDwwMZLFYNTU1LS0tXC43PDw8MDBQIpG4XK6dO3eGhIScOnVKJpNlZGSoVKq4uDiz2bxz5864uLj8/PyIiIi0tLTo6OhRD118xNhbGIIgaJo2GAwFBQUHDhzYuHHj2rVrL5pDQUHB559/vm7dujvvvHPCw0MFdBrDKXjvu/YVTCaTMbUKiqLi4+M9EeSUVlZWVl9fn5WV9dhjjz388MOZmZlMLbCxsXHXrl319fXz58+fNWtWVFQUi/Uja8QkV25MJtOpU6c+/vjjdevW5eTk8Hi8nTt3VlVVuSdgag+zZs264447nn32WZFIdOTIkbq6Or1ef/To0X/+85/Jycnz5s1LTk5mCoR8Pp+iqG+//VatVjc3N/N4PKZcKhQKzWbz3r17W1tbW1pa3OVSn6XT6Xbt2lVYWLhq1apZs2ZZLJZ33nmnr6/vosksFsvBgwd7e3u7urqYotS5c+e6urqWL1+em5srEonef//91tZWgiDEYnFfX19+fn5ra6tarVYqlRwOhyAIiUTS3t5eUFDQ2tra2dnJpCMjv8J3dpA0Tff29v75z38WCoXLli1TqVTV1dU7duy4aDK9Xv/DDz8cOHBgzZo1c+fOpSjqX//6V1tb27lz59ra2hYsWPD444/ff//96enpTEtlMlltbe2pU6fUanVfX5+/vz9BECRJyuXy0tLSs2fPqtXqoaGhyx33+kgF1OVy9fT0vPLKK2FhYUuXLg0JCSkpKdmzZ8/IaQYHBz/55JP29vYVK1YkJyf39vb+/e9/t9lsZWVlX3zxhdlsnj9//syZM0NDQ5mAlUrlsWPHysrKLly4YDabmVWMzWYHBAQcOHCgqqrqwoULdrvdXS71QSaT6eTJk5988gmzheFyuTt37qyurh45DbPdUCgUzJHYyD/RNH3s2LGOjo6enh6DweCJCDHEZRpDAup9o65gl3O5mbBYLDabzVT1aJp+/fXX33vvvSeeeOL111+vra1ta2v705/+tGDBgoMHDy5evDg9Pf29995j9taNjY2vvPLKhx9+ePvtt3/xxRd9fX0lJSWPPfbYPffcw2yV0tPTKyoq7Hb7lQc/sf1zjTt4mqbPnTv32muv3XvvvQ888EBnZyePxyNJ0uFwvPXWW83NzYmJicXFxcXFxRMb9oTo7e1tamoSCoVBQUEkSaalpZWVlanVavcEXC43NjY2LS0tODg4JiYmMTExISEhKCiooqLi5z//+X333adWq0+ePMn81jRNV1RUvPPOO4mJiTNnzjx8+HB+fr5Go6Fp+vTp059//nliYmJSUtLu3bsPHjw4MDAwRmBe3yu0tLT09PRIJBKlUikQCGbOnLl3797h4eGR01gslubm5ubm5uzsbOZMaEdHR1VVVV9fH4vF4nK52dnZRUVFzMnl77//fv/+/cnJySEhITt37jxy5IjJZKJp+quvviosLExOTpZKpf/5z3+OHTtms9lGfovXu8KNoqiSkhKbzaZUKkUiUUhICJvNPnLkyEWTtbe3t7e3i8Vif39/Docza9asI0eO9Pb2Hj9+/Pe///1dd9315JNPajQaPp/PHNN+8MEHjY2NKSkpFEV98803Z86cYb7rzTff7O3tTU1N1ev13377bUlJyaUhjXc75jk2m+3s2bMURQUEBAgEgoiICIvFcurUqZHT1NbWDg4OymQyPz8/Pz+/iIiIXbt2GY3Gp556ys/PTywWnz17tra2liAImqadTudLL71EUVRaWlpnZ+d3331XXV1N0/Tw8PAvfvELqVSanp7e0NDw/fffNzQ0XC4qry88Go2mqalJIBAwW5j09PTz58+P3MIwmAR05IgdgiAcDgezfqWnpwcFBXkownFt/8fYdfrIcggj4RT8dONwOFpaWiwWy+rVq4ODgw8fPnzy5MkHHnhg/vz5b7zxhkAg2LNnzz//+c+vvvqKzWbfcccdHR0dAoFg/fr1drv9u+++S0pKmj179qFDh06dOpWVlbV+/frnn3/+22+/DQwMvGj416QZdRt95TkoSZJPPPHEo48+2tDQsG3btoceeuijjz7KzMysq6sbGBgIDw8PCQlRq9W/+93vcnNzn3zyyZEDKK8xyKuYz0WGhoZ6e3vdw/gUCoXVarXZbKOer2xsbAwKCsrKyhIKhTU1NRwORyqVhoeHv/nmm999993mzZuzs7NXrlyZnZ3d1tbW1dW1Y8cOhULB4XBYLNbtt9++Zs2apqamgYGB/fv383g8pv5H+N4pZoZGozEYDEwtis1m+/v763Q6p9PpnsBoNNbU1BQXF993332tra0ul8tqtSYnJ2dlZR04cGDfvn0pKSklJSUymYzP57NYrKeffvree+9lqsvvvfceRVFcLpckyZdffnlwcLC0tFQmkz300EPM++5v8VYCMeqPYrfbm5qaOBwO89uJRCI+n6/X6y/6yfr6+oaGhgICAgiCYLFYAQEBRqPR6XS+8MILzz//fGVl5aeffvrUU0+999576enpbDb7/fff7+/vP336dFxc3G233cbMhM1m//vf/9ZqtUePHp01a9a6desmodXXwuFwNDQ0CAQC5ihdLBZzuVyj0Tiyczo6Oux2O1P75/F4fn5+/f39586ds1qtYrFYpVIdPXr0888/X7t27b333svj8Y4fP67RaA4cOLBixYqcnBwmpwkODq6oqOjp6fnuu+9+85vfZGZm+sL6cjnMFsZdox17CzOS1WptbGz84YcftmzZMjg46HQ67Xa7zWbz8TMn4FOQgE4TNE2z2WymDhoeHp6Wltbf328ymRwOh91uZ7FYTEoxZ84coVC4fv36M2fODAwMiESi6OhorVbb3NxMEITVanW5XCwWi8PhKBQKlUpFEERkZKTJZHK5XF5s2qW72/HOhM1mp6amPvHEExRFVVZWpqSk6HQ6Ho+XkpIye/bsiIiIgYGBTz/99JFHHrm6BNRDY9rEYrFQKHRXUHQ6XXh4uPvSkJFqamqam5szMzMTEhK6u7vNZnN4ePjChQsJgrjvvvs++OCDhoaG7Oxs5peVyWTx8fEikch9NpnL5SqVyrlz56anp4vF4pHz97WLbBhyuZyiKKZM63K5hoeHk5KSRg5ca25u3r17N5fLff/99wcGBjo6On744QeVSnXDDTckJCRoNJqGhoYdO3Zs2bKFObLi8XhBQUG5ubkLFy50J98EQfD5/JCQkFWrVrlcrpHvM7wylpG4zI/idDpDQ0MHBgYsFgtBEBaLhcPhxMbGXhQPM7KTueiEoqjBwcHY2FiJREKSJIfDycrKEolEn376aXl5eUpKCpvNFggE4eHhN910E03TI5NvoVCoUqnuuOMOkiRHvWzFp3A4nLCwMI1GwxSwzWazQCCIjIwc2Tn+/v4Wi4UZO2u325kjluHhYT8/v4yMjMzMTJFIxAxuuffeewmCEIlEMTEx999/P5vNdvcASZJisTguLu6RRx7hcrk+3jPMFqapqYn57/Dw8OW2MBfp6enZsWMHm83etm2bTqdramqiKCo5OXnp0qWXriYAo8Ip+Cmvo6Ojra3NaDRKpdLIyEiz2fzNN9/k5+eHhYXFxMQIhUKXy0VRFDOx1WqladpoNKpUKpVK1draumfPnrKysqysrNDQUBaLxUxM/x/mmJ75t7caeI1FJpqmbTYbM4SApmkWi7V48WKhUJiamiqVSoeGhoxGI0mSEokkKyvrqq/+9lAlLCoqihng2N/fT9N0eXn5nDlz4uLijEajTqdjfhSXy3XkyBGNRjNnzpz4+Pje3t6hoaHk5GS9Xt/f309RFJvNjo+PDwkJcc+WuSj+orGMJEky718UudfPEo5qxowZsbGxzFXwFoultLT05ptvVigUzOXqBEHExcXdf//9t91225o1a5YsWRIQEJCVlRUbGxsSErJ06dLFixcXFxczQ03cV3AzidSlV0aTJMnj8UZmtyP/NOqrp436vWw2e8WKFSKRaGhoyGKxdHd3OxyOVatWMR9hrv4mCCI5OTk5OdlkMg0ODjocjnPnzq1evTooKMhmszkcDoIgaJrm8/mLFi0aWQXn8/mXHpuRJCkQCKZE0UsgEKxbt47D4QwODlqt1ra2Nj6fn5ub63A4+vr6mFVp/vz5ISEhBoPBYDAMDw+r1erNmzfn5OQQBMHcWIAkycDAwOTkZPdsSZIUCoUXnZtm3heJRD6efRIEER0dPWvWLKvV6t7CzJ07Ny4ujiAIi8UyNDTk3vJTFMXsGpj/hoSEPPDAA3fccce6detyc3NDQ0PT0tJSU1N/dBg9gJv3dyQwLpcmgh9//PG+ffs4HM66des2bdokEAiqqqruv//+qKio9PT0srIyf3//Z555xm63r169+vHHH581a1ZhYeHSpUuXL1/ucDh279795z//OTs7Oykp6Ysvvrj33nvT09O//vrrpqamp556KjEx8aWXXjKbza+88sq8efMu3QdPTrHnWiqgLS0tb7zxRkVFRWZmZmho6C233JKamsqEXV9fX1BQoNfrAwMDu7u7H3vsMaVSOXaLLvfXiaqEXdq04eHhoqKiH374ISsrq7W19a677oqNjX3ttdfKy8t/97vfhYSEfPbZZ7/73e8cDgeLxXI6nbNmzXr88cfXrl1bWFh44MCBhQsXVlVVrVy5ctSf76p5Kwcd2T/d3d3Hjx+vrq6Oi4vr6Oj45S9/yefz77zzzvj4+EceeSQyMtI9ZUtLyxNPPPH444+vWbOms7PzzJkzjY2Nubm5S5Ysufb9pRcroKOqra3du3cvU5MLDQ29/fbbCYJwOp3p6enPPffcxo0b/f39+/r6Tp06de7cudTU1Obm5meeeUar1f7+97/v7OxMTU2NiYm58cYbR6ZZV80XlpORKisrv/32W7lc7nK5kpKS1q1bd/78+Ztuumn79u3z5s0TCAStra2HDh3q7u4OCQmx2WxPPfUUQRAlJSWHDh2SyWQOh0MsFt9+++0TdXMlX+if4eHhc+fO7d+/n9nCbN68OS4ujqKobdu2ffbZZ2+//fbMmTMHBwe3bt36xRdfrFq16qGHHkpISBg5t7a2tv/93//Nzc396U9/OulN+S++cGwMVw6/1hQz6obVYDAwNTz3O3a7nTmh5q59njlz5pZbbqmvr3c6nTKZjLkQhyAIiqKcTidz2p35x7h2yb6wAf1RTqfT4XAw1ZpL/2q325n9ypXMytPtHbVdNE1TFMXcqZT5dZhBWlcyWsBgMIhEomu5r6dPjQG9qH+Y885Op9OdW1ssFjabfWlFiuFwOJjT0z96v60r5N2uuNyBGUVR7oE37umNRqNQKHQvCTRNu1wuu90uFAqZVjCrCYvFmsCKpg9uH5jOcZ80d7lcFotl5LATmqYdDgdFURetXxaL5XLbkKvmI/1z6RaGIAiHw+FwOC49IeDLkIBOLfi1ppirOBVO0/Tg4OCBAwf+9Kc/ffjhh7NmzZrAbajvV0An1uRXQH2Tj+w4fYGvVUB9CpaTsaF/JhYS0KkFv9YUc3UbDpvNNjAwMDQ0FBgY6O/vP4HPubneNqBeqYB6ly9XQL3ONyugvuN62z6MF/pnYiEBnVrwa00xvrbhQAWUgQro5PC1/kE/jA39Mzb0z8RCAjq14II1gAngm5eKT4hp3DQAAPAWJKAAE2DU+zJ6OaYJMo2bBgAA3oIEFGACTOMy4TRuGgAAeAsSUIAJMI3LhNO4aQAA4C1IQAEmwDQuE07jpgEAgLcgAQWYANO4TDiNmwYAAN6CBBRgAkzjMuE0bhoAAHgLElDwaSi/eZe3sk/87gAwXpfbbmB74puQgAKAz0HZFQCuAnLQKQQJKAD4HOwtAOAqXO7YFce0PggJKAD4HOwtAOAqoAI6hSABBQCfg70FAFwFVECnECSgAOBzsLcAgKuACugUwvF2ADDBHA5HU1NTXV2dy+WKjY2Nj4+Xy+Umk0mtVjc2Nvr5+WVlZVmt1sbGRq1Wq1AoUlJSAgICLly4UFFRIZPJ0tLSQkJCeDyet9sxMbq6uhoaGlQqVUJCwsj3zWZzQUFBcnJyfHw8QRA0TRsMhuLiYpIkAwMDY2JiJBKJl0K+GE3TOp2utLSUJMmgoKCYmBixWHzpZJ2dnQ0NDTExMbGxsQRBDA0NFRYW6nQ65q98Pj8jI4Np7JRA0zRJkpe+jpyGoqju7u6GhgYulxscHBwfH89ms0dOYLPZOjs7i4uLjUZjZmZmUlKSVCpl/mS327u7u7u6upRKZVRUlEgkmry2eZjL5aqurh4YGJBIJBEREWFhYZdOo9PpLly4MDw8vGzZspHvd3V11dXV9fX1CQSC5OTkpKSki7p0SnM6nWfPnrXb7QqFIioqSqlUXjrN0NBQXV1dS0uLSCSaM2dOVFSU+082m62ystJsNufm5k5i1B43ri1MbGxsTEwM8w5FUUNDQ2VlZRaLJTAwMD4+PiAgYHJjH8Wo240r2Z7A5EMFdLphs9kRERE7d+7cu3evzWZjNiUCgYDNZhcUFERERAiFQoVC0dLSsmfPntraWqVSabfbm5qajhw5EhISEhAQwOFMk8OSvr6+gwcPvvvuu8XFxRf96b333nvttdeqqqqY/6rV6n/961/Dw8Opqamff/75sWPHhoeHJzvcy2hubv7kk090Ol1aWtrWrVtPnDjhTisZNE339fUdOHDgnXfeOX/+PEEQJpOpoqJi+/btbW1tXV1d1dXVhw8fbmlp8VILrsaVVEALCwv37NlDUVRAQMCf/vSnyspKq9Xq/qvL5Wpvb//8889ZLFZ5efkjjzyya9cu5mdtbW39+OOPv//++4SEBJVKxefzJ61dk+Czzz47f/68UqlUq9WfffZZW1vbRRMYDIaysrJt27Zt27Zt5Ps2m+3cuXMHDhxobm5ub2/n8XjTaQ+t1+v/+te/trW1RUVFFRQUfPfdd729vRdNY7fbDx06VFpa2t/f/+WXX/70pz9tbW2lKIr56/79+//4xz/u3bt30mP3rKamJmYLk56e/vHHH588efLSLUxvb+/+/fv/8Y9/lJWVud/s6+t78MEHQ0JC5syZs2/fvu3bt3d0dHijBf8FFdApZJqkGuDGYrEkEolcLufz+RKJhMvlEgTBZrOZN6Oiovh8PkmSIpGIx+NxOBy9Xl9cXFxZWfm3v/1NKBR6O/yJFBQUNHfu3OPHj9vtduYdmqbNZvOuXbtUKhWXy3U6nQRB6HS606dP79q169ixY1wuNzMzc/fu3Vwud/Xq1V4NnyAIYnh4+OTJk999992hQ4c4HM6sWbO+/vprHo+3fPly9zRM3WLevHlHjx51OBwEQVAUFRcX98UXX7BYLIIgPvvsMz6fn5SU5LVmjN+PVix6e3u///57k8n08MMPGwyGjIyMP/7xj3/+85/d5RmTycTj8V544QUej3fbbbfdcccd9fX1XV1dGo3mu+++02q1r776KovF4nA40ybNoiiqtbX1o48+evHFF2fOnOlyuSorK99///3XXntt5GRSqTQpKSkxMfHYsWMj3//hhx/a2trWrVuXlZUlkUimzYEoQRAWi6WiouIvf/lLaWmpSqVKS0vbv3+/0+n86U9/OnKy3t7e5cuXy+VyFos1e/bsX/3qV2fPng0LC2OO3s1mc1BQkHtjMiX86HrEbGH27t178OBBDoeTlZX11Vdf8Xi8vLw89zQkSQYHB4/cwhAEodfri4qKrFZraGiov7//4sWLv/322++///7RRx+d7Eb+N1RApxBUQK8Xlx7t2e32s2fP/utf/+rv73/hhRemWfZ5KZqm9Xr96dOng4KCUlNT3SfZe3t71Wp1REQEk6xHRUW1trb29PR4Ndj/n0ajaW9vDw8PZ7KBmJgYtVqt0WjG/pRUKlWpVEz2abFYqqurw8LCIiMjJyPiCfKjFdCWlhaDwRAUFMThcHg8XmxsbElJidFodE8gk8mioqKYwSQ2my0qKio7O1uhUOzbt+/w4cN5eXmHDh3629/+Vl1dbbFYJrVtHkNRVFFRkVwul0qlLBZLqVRyOJyqqqpL132SJC/qT5qmaZpubGz8y1/+cu+993788cdms3nalIgMBkNFRUVMTAxz+B0aGjo8PHzpOQGVSuXv789ms10uF4/HmzFjRk5ODpvNPnfuHEVRCQkJISEhXon/Woxd+evp6Rm5hYmOjm5pabm0NkxcsgK6XC6dTldVVdXf3+90OqVSqclk6u/v92hbYJpBAjo9McnHRUiSHPk+RVEajaaoqKisrKytrc19pmm66uvrO3bsmEajSUtLMxqNNpttaGjIYDCYzebh4WH3WDdmuIJ3Q3VjYnP/agKBYNRf9nJomj558mRCQkJoaOi4Puh1P3q+TKfTmc1mplFMRX+MWe3fv3/ZsmULFiwYGhrq6ekJDQ1NS0tLTU1taWl5++23W1tbPdqWScOcFXW5XEyuwOFw+Hz+FSaRJElu2rTp3Xff/fDDD9evX7979+4TJ04wpwimAbvd3t/fz2azmZ7h8XjM0ebltLa2dnR03HfffaGhoQUFBU1NTcHBwTwez2AwMGnWFErNxz6WM5vNOp3OvcUTCoVXuPWTy+VLly7Ny8v717/+dfDgwUOHDpnN5uDg4IlvAExf0+ckC4wkEolMJtPI/QebzRaJRCwWy731EQgEa9eunTdv3ocffnjrrbe+/fbbs2fPnsZ10N7e3vz8/P7+/gMHDphMptra2s8//1ypVGZmZioUirNnzzKTDQwMRERE+MJoeoIg5HK5XC53j7saGBhgijRXPofdu3f/7Gc/G3ktxZTwoxVQphbFlGpcLpdWq01LS7s0DTWZTN9//31oaGhGRoZMJhscHORyuX5+fpGRkXa7ffPmzb/+9a8vGvE2dbFYrPj4+N7eXqYSzCToiYmJV36qkcViRURErFy50mg0DgwMTKE0a2xCoVClUjU2NrpH3cjl8oiIiFEnrqqqamtrS01NTUlJcTgcR44caW9vP3DggM1ma2pqstvt77777q9//eupcqXm2MdyCoVCJpNVVFQw/+3v74+MjBz18qyLsFis8PDwf/zjHwaDweFwfPHFF7GxsSOHBgH8KCSg0xBJkqtWrfrHP/7R2tqakJDAZrMtFktHR4e7AOB0Oi0Wi8ViYbFYc+fOTUhIeOeddzZu3PjrX//6pptuioiI4PF4U6tgNiqKoiwWi91ut9vtTqdz5syZ7733HvOnCxcuPPXUU/fdd9+tt95K03Rubu7Zs2cbGhoiIiKKi4sXLlyYnp7u3eAZ0dHRixcvLisra2xsjIiIOHfuXG5ubmpqand3t9VqZUayEpe0lDmb5nA4WltbmRR27HqPD/rRMVsZGRlz5sxpbGxsbW1lsVjnzp3bsmVLQEBAc3OzWCwODAwkCKK9vT0/Pz8mJiYmJoYZBahUKhMSEgoLC9VqtVKp7OjoWLdu3bQp27DZ7NWrV3/66acDAwN9fX0XLlxwuVy33HILQRA0TVdVValUKj8/P5Ik7Xa7xWJxOBx2u51JpBwOB3P+VCQSDQ4OGo3G9evXT7nF5nKUSuXq1av//ve/X7hwQSQSVVdXR0ZGLlmyhCAIk8nU1NSUnJzM5/NtNtuxY8cGBgYSExP9/f1bW1tramp+//vfM/2g0Wjee++94eHhl19+2dsNGofLjYBk/hodHb1kyZLKysqRW5iUlBSCILRa7eDgYExMDI/HG3ULQxAEU7B49913169fv3Tp0vDwcG81E6YiJKDTEEmSa9asoSiqtrZ2x44d/v7+DodDIBA8+eSTzOkVjUbjdDpDQkK4XC5zRvKuu+7q7u4uLy9nsViLFy9OTk5237Bm6jKbzVqtNioqisvl9vX1jbwfjVgszs3NZYZFkiQ5Z86cP/3pT6dPn46MjExKSlq4cOGoN6+ZfCwWKzs7OyAggIktNTV10aJFwcHBu3btUqvVd911V3h4OE3TJpOpr68vJiaGxWJptdrQ0FCCIBwOR1VV1a233joVE6wfrYCyWKy77rqrtraWGdS7aNGiG264gcvlfvTRR6GhoatXr3Y4HIWFhYWFhUVFRQRBOJ3OzMzMdevW3XTTTUlJSczFJTabbcuWLUy2Oj2w2ew333yzpKSksLCQw+Hk5eUtWLCAIAiKoj788MNNmzbNnTuXy+UODQ2xWKzk5OTm5ubk5GRmsfn666+1Wq1KpQoNDf3Zz34ml8u93ZoJQ5JkSEjIt99+W1hYqNfrAwICkpOTk5OTaZrWaDTvvPPOs88+GxcXV11dffbsWbVaffjwYZqmhUJhXl6eO1cTCAQzZ840mUzebct4jV0BZbFYCxYsCAwMZLYwaWlpixcvDg4Opmm6srLy2LFjP/3pTyMjI5ktTGxsLEmS/f39ISEhFEUZDIbGxsbm5ua8vLzU1FQ/Pz9vtRGmKFwFNsWM66SYw+Gw2WwkSQqFQg9VND19IeFkngSkadrhcHC53DEa5a32UhTldDrdsTFnEse+Tpm55P8af3pvXSg6xrWrF03pcrkoinLX6hwOB4vF+tFxbBRFORyOa78Bkxf7Z+y/MiNBR/aD3W7ncDhjLAwURTGfmsDr332tf2iadjqdbDbb3Q80Tdvtdm/dimsStidXuB5dtIUhLlmzLp2zw+FwOBwikcinLifHVfBTCH6AKcbXRmVNpwT0SqC93oX+YfhaP1wO+mds19v2ZBIgAZ1Cpvw4PwDwHHqcrmL+l3udkPl72hjxj/o6UfMHxvXWP55e3qa6yw3duZIHW8Dkw28wxfjaZuV6O4JHeyeHr/XD5aB/xna9rS/jhf6ZcKh0TiGogALAZXmrAjpVoALqdddVcQsV0LFdVwvDNIDfZorxtc3K9XYEj/ZODl/rh8tB/4zteltfxgv9M+FQAZ1CUAEFgMtCBXRsqIB63XVV9EIFdGzX1cIwDeC3mWJ8bbNyvR3Bo72Tw9f64XLQP2O73taX8UL/TDhUQKcQVEAB4LJQAR0bKqBed10VvVABHdt1tTBMA/htphhf26xcb0fwaO/k8LV+uBz0z9iut/VlvNA/Ew4V0CkEj+IEgMsa7w5svNv6qb6DRP943RU+6Wd6uIp2XVf9gwro1IIEFADgKmH35nXX1dnncT3m5zo8O3+5pmE99U1IQAEArpKnK6Dwo66rCt9VjAG9rvoH69fUggQUAOAqYYfndddVhQ8V0LGhAjq14FeZYubNm+ftEP5LUVGRR+eP9k4t4+2fMdrb29vL4/FUKhWfzx8YGLjm0HzCtfcPRVFdXV1yuTwmJsZqtRqNxomLbuJNwvpSVFTEvM6cObOyspJ5XbRokd1u9+hXT4gJXF/G+Irk5OT6+vqMjIyKigp3j413PlOCp5c3mFiogE4xwcHB3g5hUqG909sY7ZVIJGw2OygoiMPhcDg+uqXau3evR+d/af/QNC0WiwUCQUhIiMViEYvFHg3AxwUHB99www0EQdxwww1Op1OpVAqFwpycnL6+vimRgI5XUVHRDTfcsHfv3it8JQjihhtusNlsYWFhfD4/MjKSecfb7fCUyzXN0+spXB1UQKeY3t5eb4fwXzydMKG9U8t4+2eM9prNZjabzePxWCzWtDlpeO39Q9O0yWTi8Xg8Hm/i4vKUSVhfgoODmdeurq7w8HDmdaqsRxO4vozxFR0dHSqVqru7OywszN1j453PlHC9HcBPdUhApxhf2xNfb/exu97aO17X222GsDyMDf0ztqvon/GOAQUCY0ABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAArhXp7QAA4P956aWXvB3Cf/n973/v0flPVHsnKk5P97+vxelr8XiLp5dzALgUElAAH5KYmOjtEP5LY2OjR+c/Ue2dqDg93f/jjdPX4rkcX1tux8vTyzkAXAoJKIAP6ejo8HYI/0WlUnl0/hPV3omK09P972tx+lo83uLp5RwALoUEFMCH0DTt7RD+C0l6dhMxUe2dqDg93f/jjdPX4rkcX1tux8vTyzkAXIrj7QAAAEY3MDDQ09PDYrHCwsLkcrm3w/l/rFZre3v74OCgXC5XqVRisdhDX3S5xOhyCZ/L5Wpubh4cHAwMDAwLCxOJRB4KbGwDAwMkSYrFYj6f75UAAMD3IQEFAB9lt9v//e9/2+32X/ziF96O5f+hKOrMmTNdXV01NTW9vb05OTkPPvigh75rXJVFiqJaWlqMRmNJSUl3d/fixYvXrVvnocDG0Nra+t577+Xm5i5btmzyvx0ApgqWtwMAABid1WolCMLf3z8oKMjbsfw/JEnOnTv35ptvfuKJJ8LCwg4fPuxwODz3XaMadWIWixUVFTVr1qykpCSapo1Go4eiuhyn01lfX//BBx/U1tZyuVyhUDjJAQDAFIIKKAD4qMLCQh6PN3fuXBbLhw6VSZKUSCQEQXR0dISGhkZFRXG5XA9917gqoDRN6/X6Q4cOdXR0bNy4ce7cuR6KatSvNhqNdXV1paWlJEmuXr06NjZ2ZKJM07TZbK6srDSbzQMDA0KhMC0tLTIysru7e8+ePQMDA5s2bTpx4kRYWNjSpUuVSqXT6ezp6fnPf/5js9ny8vJOnDhBkmROTo7Vaj1y5MjcuXPXrVvH4XCsVmtTU1NfX5/BYLDZbCkpKTNmzNDr9d9//71arZ4/f77RaOzu7r7ppptkMll9fb3T6SwrK4uIiJgzZ05YWNik9Q8AXMqHNusA1w/6Mrwd18W8GKfNZistLRWJRJmZmT868eTH2dnZWVtbm5iYePfdd3vuW8aFoqi6urqampojR440NDR4oi47aic7nc7u7u7Tp0/39fXdd999lZWVqampERERIwPTarWvvvpqXV1dampqbm5uTU3Ntm3bOByOSCTq6OhwOp3t7e3BwcFxcXFMcs/hcCQSSW1trcFg6O/vN5vNbW1tZWVl7e3tFoulq6uLSXk//vjjY8eOBQUFLVu2jM1m//a3vyVJ0s/Pj/lIX18fm81OTEzU6XTvvvtuU1OTUqkkSVKn0zHFdQDwIiSgAOCLqqqqXC6XSqVSKpVXMj1Tb7v01RNqa2vr6+sTExNzcnJ850Qzm81esmTJSy+9FBwc3NfXZzKZJvwrRu3kzs7OPXv2bN269ezZs88++6xara6srOzv73d/ymAwHDp0qL6+ftmyZSEhIRqNRqfT8Xg8mqZ1Ot33338/c+bMRYsW3XrrrRkZGTwejyAIl8s1ODiYn5+flZU1e/bsrq4uu90+b9680NDQhoaGNWvWsNnsU6dOVVRUJCYmpqWl6XS6np4e5rdwOBwFBQVyuTwnJ+eGG26YOXPmuXPnjh8/rlKptFrt7Nmz16xZEx0dPeGdAwDjglPwAOCL9u3bFxQUlJKScoXTM/XOi14nPAelafrAgQMKhSIzM3NoaKizszMqKsrr13rTNO1yuSiK4vF4drs9NDQ0Pj7+ChP38X7Rpa8Oh+Ouu+7atGmTTqd7/vnnf/nLXy5dujQ4ONj9KZvN1trampWVJZFInE7noUOH+Hz+LbfcMjw8XF5eHhsbm5eX5+fnN/LH0ul0Z86cycrKWrhwYVNTk81mW7JkSVhYWHV1tUKh4HK5JEm2trZGRkYGBwdTFFVRUVFZWfn000+7XK6zZ8/6+fktXLgwMjKSJMn+/v6WlpbY2NjZs2dzOByNRuO5IRMAcOWQgAKAD6Fp2mq1Hjt2rLCwMD4+3mKxuFwuNpv9ox8kSZLJOEe+Tmxser1+27ZtX3zxBXN2W6VS3X333b7wEKDe3t5du3Z98cUXN998M5fL3bJlS0JCgicGzo7ayTRNy+VyJh/t6+tbtmwZk/m5P6VQKO66666PP/64uLhYq9WmpqZmZmaGhYWp1er6+vqHHnpIKpVe9GMZDIa6urpHH31ULpfX1NQsWLBg4cKFBoNhYGBAoVDYbDaapjdt2vTVV1/V1NQ0NTXRNP3cc88lJCQ4HI7Tp0+vWbMmLi6O6YGYmJjly5e/9dZbv/zlL9PT0+fNm6dUKn1qVDHA9Ql33wXwAh8c7jkuU+UG5lP9xu9XHg9FUVarlcPhMNXByY+HGQyq1+vlcvnlDhgsFguPx7uSw4lRURTlcrlommZO0zNsNhtJkiPfudxnLRaLSCQatcm4ET3A5MNaB+AFSEAZE9gPE1IBnboJ6NW5ui66tKs9EdtkQgIKMPmw1gF4wVS/BUx3d/eEzMfT/TDeOBHP2Kb6cns5E7U8A8CVQwIK4AVTvWiECujVQQXUN6ECCjD5sNYBeMFU32f7YAI6qqme8PlaPOPla8s5Ek0A34Gr4AF8BUVRRqOxoqJCr9e773ETFBTka48CmnBGo7GpqampqYnH48XGxs6cOZN5v6KioqOjQyqVxsXFuW9sbrVaq6urw8LCRp4OntjEgnmoemVlZXZ2dnh4+Mg/0TTd0dHR1tYmEomio6P9/f17e3vPnz/vcrni4uLi4+OZW/w4HI7Ozk6dTncld9Efw6hl3YaGhsrKypycnNDQUGay4eHh0tLSlpYWgiBSU1NnzJjh5+enVqvr6uo4HE5sbGx8fDwzpd1ub2lpYbFYSUlJ1xLYhLBare3t7cwt6OPj44VCIdPzDQ0NfD4/IiLCfROuysrK9vb2K1kSAGCqmM57NYApxOl0Xrhw4Z577rFarfPmzVu2bFl2drZGo9m+fbtOp/N2dB5E0/TWrVuPHTu2cuXKsLCwF154obCw0GazFRUVHTx4kCCIrq6uDz/80D39Z599xmKxFArFRTOZqCchORyO9vb2b7/99p133lGr1SP/pNPp/va3v33xxRdhYWFpaWlyuby1tTU/P7+mpiY5OfmZZ55x3329sLCwvLw8KirqKgK4qF3Ef99xs6Wl5ZtvvvnHP/7R1tbmDrilpWXXrl1arVar1QqFQi6XW1dXl5+f39PTIxaLX375ZfcMf/jhh66uLnfm6kW1tbXvvvvuoUOHFixYkJSUJBAICII4cODA/v37FQpFUFDQn//856qqKofDUVRUlJ+fTxBEV1fXBx984J7DqEsCAEwVqIACeJ/T6SwuLn722WefeeaZnJwckUhEEIRYLN64ceO8efMsFguzlzWZTDabzeFwsFgsLpfrdDqNRqNcLh8YGAgICGCxWAaDgSRJPp9vMplcLldISIjZbDYYDGw2W6FQiMVim82m1+s5HI7JZJLJZGKx2G63Dw8P0zQtEon0er3T6QwPD+fxeEajUafTcTgcuVzO5/NtNptWqw0MDOTz+RNbbqyuru7u7o6JiVEoFFFRUcuXL3/xxRf//e9/NzY2Wq1WpnXt7e02m83lch04cCAlJSU2Nvai5w9NYEhcLlelUi1btqygoICiKPf7XV1dX331VXl5+R/+8AeFQsHhcNhstlar7ejoCAoKkkqlTU1NRqPR4XCUlpbabLaMjIxrz40urYDGxcWdPXv28OHD7vS6vLz8+++/nz179pIlS0JDQ0UiEYvF6ujo6O/vT0lJ4XK5LS0tFouFy+UeP35cJpMlJyfLZLJrDOxa0DRdWlq6b98+Fov10EMPkSTJ3Dqqs7Pz+++/DwgIyM7O1mq16enpv/71r7du3TpySejo6LBarTRN79+/f9QlAQCmCiSgAN6n0WiOHz/e3d29YcMGZodKUVRvb29ra6vRaCRJMiAgwGKx7N27VyqV2my26upqHo8nl8u3bt36y1/+sqSk5KabbpLJZP/85z/tdvuaNWva2tpOnz69fPnyyMjIxsbGoqKijRs33nDDDWVlZQcPHly5cuX333/v7+9/9913u1yuv/3tbxqN5o477mhsbMzPz3/22Wdzc3NbWlref/99Ho93//33p6amNjY2vvfee7/61a8iIiI4nAnebnR3d9M0rdfr2Wy2WCxua2tzOp3z5s0zGAxdXV0ikWjJkiV2u/3s2bNcLjczM5O5p6NAIHDnnZcrdk5UYmqxWEpLS99///233nqrpqamsrIyIyNjzpw5UVFRM2bMaGxsbGtru+WWW5RKZWVl5eDgYHx8fGhoqE6nk0ql1zJ84tInDzkcjvPnz498UyAQcLncwsLCzz//fPbs2Y8++mh0dHRKSsrAwEB/f79cLr/hhhuEQuHJkyetVmtmZqafn5/RaGTy1AnpnPHS6/V79+4tLy9/5JFHCgoKysvLb7zxxpSUlIaGBpvN5u/vz2azBQJBeHj42bNnbTabe0kQi8VLlixxOBxjLAkAMFUgAQXwPpPJ1NPTQ1GUyWRy701ZLNaxY8eOHDnyi1/8Ii4urqCg4NSpU4sXLw4JCQkODubxeFKp1G63p6enr1u3TigUcjgcqVRqNBrnzp2bk5PjdDoLCgr++c9/rl+//tFHH1Wr1QaDISoqauXKlQRBiESiwsLCdevWMYU65hnZCxYs0Gg0p0+fnj17dkZGxtq1a48dO3b+/Pnw8PDGxsYHHnggLCxswrPP5OTkNWvWnDp16r333ouOji4oKJgxYwaXy01MTJRIJGazWSgUusuKq1at+uyzz1QqVV9fX3R0dE5ODnNXc0/nH1qttrGxMSQkZNasWTwer7y8fMeOHS6Xa+3atcuWLUtOTubz+c8//3xzc3NfX9+MGTNaW1uLior8/f27u7vvvffeq37246UVUC6Xe+7cOWLEo9hnzJiRnp5uNpsrKyv/93//9/Dhwxs3blSpVKtWrRocHBQIBGlpaadOnRoYGFi4cOGZM2eYCjpN0xs3bpzIPrpiLS0t/f39UVFRs2bNMhgMhw8f/utf//q73/1Or9dbrVb3ws/n85mFLSEhYewlISoqatGiRVd9f3sA8AqMAQXwvsDAwMzMTIvFcuLECavVShAEi8ViTuxardbQ0FAWi9Xa2qrRaOLi4nJych588MG77rpLIpFwuVylUimVSnk8HovFYrFYAoFAJBKx2WyJRCIQCHg8HofD4fF4NE3b7Xa1Wn3gwIHg4GDmudhMWsN8iqnVyWQyh8PBvL927dqYmJjjx4+fOXOmubl5zpw5P/q8mavA5XJvu+22N95446c//alUKq2srHzhhRf8/PwIgggLC4uPj5fL5f39/R0dHStXruzo6MjPz5fL5QaDoaioiLnshpjQMaCjYmpyfD4/NDTU399/3bp1NptNo9EQBCGVShMTE1UqlcPhqKiomDFjBp/PP3PmTHd3d0BAQElJSXFxscvlurrvHbUCOvJPDJIkxWLx3Llzb731Vh6P53Q6CYLw9/dPSEgIDg42Go1FRUW5ublWq/X48eNWq5XH4xUXF1dVVV1br1wlHo/H5/PFYnFISIhKpbr99tvr6upMJhPTh319fUwzh4eHmXSfJElmSVAoFP39/e3t7e4lganmFhcXu5cEAJgqUAEF8D6lUrlq1arW1tbXXntNKpWmpqZKpVKXy2W1WkUiEZfL5XK5S5cu3b59+759++x2O/NMwsHBQYfDMTg4GBQUxGKxrFar1Wq12WxGo5HL5ZpMJuYdk8lkt9uZCllFRYXNZuPxeDqdzmg0Dg8P63Q6i8VitVoNBgOLxTKbzcz0FEXxeLyVK1d2d3d/8MEHr732mofO2NI0zZxILS8vP3/+/Pbt22fNmuX+q9lsPn/+vEajufPOO0mSJEmSzWYz0xMEwVy5QkxoBZR5pOTw8LDFYjGZTA6Hg8vlMin7wYMHy8vLIyMjL1y4kJ2d7b5a3+l0MpeLPfjgg/7+/n19fSwWiyRJu91utVqlUulVB3NRBZSiKC6Xe+DAAavVajabmUOFvr6+wcFBpVLpcrm6u7vvvvvukJAQ5uN2u725ufno0aNPPvkkM/CX+RGZkcTMUOPJl5CQkJycXF9fX19fL5PJmpub77rrrsDAwKCgoIULFw4ODjY0NNjt9rq6uqeffto9XJUZBdHT03PXXXe5lwSapi9aEgBgqkACCuAFl55ajYiIsFqtK1eurKurM5vNCoXC4XCEhYU99thjkZGRHA5n1qxZr7/+ekFBwX/+85+kpKSZM2cGBwdv3Lixp6cnPj6ew+EMDg7OmDHDYrHo9Xo/P7+goKD58+czyeWsWbNYLFZoaKhcLj927Njp06dDQ0NzcnJcLld7e3tCQkJgYGB/f79CoYiNjbXb7S6Xy+VysVismJiY5cuXKxSKjIwMD3WF3W7v6elpbW0lCOKee+6Jjo4e+dfW1lYul7t8+XLmbGxsbOz69evNZnNYWFhMTIxKpWImm8AxoExOY7PZli1bxuFwjEYjc8lRZmbma6+9xvw6BEGsW7fOfZG7wWCoqqq6++675XI5SZJBQUGLFi3q7Ow0mUx5eXnp6elXnR9fVAGlKGpwcPDUqVPLly8nSdJkMhEEUV1dfe7cuZiYGIlE8uCDD4aHh7vP+Gu1Wo1Gc+uttzLvhIeHL1++3G63EwSRm5ubmJg43n6bkKIyn8+/9dZbm5ubm5qalEqlTCbbuHGjn58fi8W67777GhoaGhoa/Pz8Vq1axTST+ZRareZyuStWrBi5JJhMptDQ0JFLwthGvYs+xo8CeAVWPAAvGHtH7nQ6bTYbm81mTqxf9CeKoths9tWNeGOSGOa0O/OPy+19u7u7Ozs71Wo1i8WaO3fuRXnhBN6I3uVyOZ1O5rr+Sydg6lsjr3R2uVx6vZ7P5wuFwh8NwxM3frfb7cxV2yNDMhqNzLABBlOjdTgcMpls5C/oiXiYPiQI4tLhuXa73W63SySSkaGaTCaSJCUSiXsU6ZUnZBN7Y3mmkH/p705RFEVRFzXnGpcEt1Hbi8QUYPJhBQPwDh9/pOGpU6f27dsXFBR00003RUdHX7QzxpOQro6vxXM5Hq2AehcSTQAfgRUPwAum+o4cCejV8bV4CK9WQL0CFVAAH4Gr4AG8wH3286JXgEl26YX20yDLHC+sjwCTDwkogBdgrw8+ArkXgfURwBuQgAJ4Afb64COQexFYHwG8AQkogBdgrw8+ArkXgfURwBtwH1AAL5jGVxkD+KzLZdvIwgEmHyqgADAZUGQCn4WFE2DyIQEFgMmAIhP4LCycAJMPCSgATAYUmcBnYeEEmHxIQAFgMqDIBD4LCyfA5EMCCgCTAUUm8FlYOAEmHxJQAJgMKDKBz8LCCTD5kIACwGRAkQl8FhZOgMmHgzwAHzJVdnvjrQ95q12+FqevxXM5VxEnSZKjvnoowquDuiaA70AFFMA7fKroQtO0R78dpzinN/y+ADBe2EYA+JDLZYFOp7OhoeG7777r6upKSEhYsWJFWlrahHxjV1fX9u3bm5qaNm3atHbt2iv81LVX8iiKqq2t3b59u1qtzsvL27BhQ1hYmM1mu3Dhwtdff22z2VJTU5cuXRoeHk4QhFqt3rt3r91unzNnzrx580QiEUEQNputrq6uq6tr/fr1Exin1Wqtqqravn17d3f32rVrV69eHRYWRhCE0Wg8f/78tm3bdDrdAw88sHDhQrlcThBEc3Pzvn37XC7X7Nmz58+fLxAImNhqamr6+vrWrFlzjfFc9I7D4SgpKTl48OCdd96ZmJhIEER5efnXX3/d19fHTODn5/fAAw+kpqaeP3/+xIkTPB6P6TTmrxaLpbi4mMPhLFy4cIzv9XQFtLe39/jx4/n5+RRFbdmyZcGCBTwej/lTV1fXqVOn+vr6nnzySff0Bw8erK6uViqVc+fOdS/5RqOxoKAgMTExOTn5CuNEWgzgO1ABBfCOcVVAORxOWlqav79/fX29SqWaqOyTIIjw8PDIyEixWExR1ETN81IX1cYoimKz2W1tbffcc8+qVav279+/Y8cOu91eWlr6P//zP88///zvf//7srKyTz75pKamprGx8cCBAw6H49577/3Vr36l0WhomjYajadOners7MzLy5vAOB0OR3d396lTp26//fa8vLx33nnnn//8Z0dHh91u7+/vNxqNL7744ty5c19//fXi4mKCIOrr6w8ePEjT9B133PHss8/29fUxsZ04cUKj0eTm5k5gbARBOJ1OjUbDJKD9/f0EQQwODnZ2dgqFwpUrV65evToiIoLFYtE0XVJScvz4caVSOWfOnJdfftnlchEEodPpfvjhBzabPXv27IkNbFwVULPZXFtba7PZ7rjjjrCwsE2bNh09etRkMhEEYTAYmpubT58+ffbsWff0hw4dKikpmTFjBpfL/eCDDyiKoml6cHBwx44diYmJcXFxE9sWAJgceBY8gHeMus8e+zw4n8+XSCRcLpcgiL6+PrVa7XK5Ojo6Fi1aZDAYysvLFQqF0+m02WxMfa6wsNDPz6+rqyskJCQhIUGhUBiNxra2tsHBweHh4aCgoNTUVKlUyuFwOBzPbgouzbOdTiebzWb+YbVaY2JitFpteXk5SZI8Ho8kyVWrVn366acRERGzZ882m81cLpfNZtvtdpfLZbVai4qKaJqeP3++UCic2DjlcvlTTz3FZrMXLlxYW1vL4XAsFguXy42MjIyOjqZpeuHChTRNh4aGEgRhs9ksFotAIGCz2TabjYnt7NmzbDZ71qxZExsbQRAcDic0NHT+/Pl79uxh3hEIBLm5uevXrydJ0m63FxUV3XDDDZGRkeXl5Xa7ncvlkiRps9koirLZbAUFBWFhYSkpKXw+f2IDu1wFdNSJXS7XnDlzcnNzWSxWcnLyoUOHjEaj0+kkCEIqlSYkJCQkJAwMDLinNxqNLpeLw+HQNO1wOJxOp8lk2rNnT3Z2dlRUFLM6AMCUgwoogHdcyxhQjUZz+vTp8+fPBwQEGI1GrVYrkUi++uqr7777zmKx+Pv7O53OioqKDz74QCwW9/f3//vf/y4pKTEajeXl5QUFBZGRkZGRkS+++OK5c+dsNpvn2uh2abbN5BMHDhx45ZVXzpw5w+FwJBKJv79/bW1tY2Mjk2eYzWa73R4fH7948WKbzXbmzJmf//znQUFBhw4dIkkyIyODx+N1dXUx5b0JwePxlEolkxkPDw+Hh4fPnz8/OjqaJEkWi2UwGLZv3/7cc89pNBqm0JiQkJCTk8Oc137uuecCAwPz8/O5XO7MmTM5HE53d/cExnYRphtFIpFUKiVJ0uVyabVanU4XEREhkUgyMzMzMzP7+/u7uroef/xxDofz9ddfh4eHp6amOp3Ovr6+iQ1sXBVQqVQqlUpZLJbD4TCbzTNnzly4cKFUKh05q5GWLl0aFxd34cIFoVB4++236/X6r7/+ev78+QkJCUNDQ8PDwx4t3gOAh6ACCuAdV1EBdROJRN3d3e+8805dXd3TTz8dHR3NZrP5fH50dPTKlSv9/PwIgggPD9+6devhw4ebm5tbWloGBwcvXLhw+PDh9vZ2Zmd/9913+/v7OxwODzby/1wu216zZk1KSsqrr766c+fOqKiopUuXPvXUUz/96U9vv/32o0ePcjgclUolFArnzZvnHsW4b98+qVSalpZ25MiR2tra5OTk06dP//Wvf+Xz+RM7wu/TTz9dtWpVWlqae3iiVCrdvHnz7Nmzf/rTn0ZERCgUitDQ0Ozs7OzsbGaCvXv3yuXy1NTUAwcOtLS0xMXFFRcXv/766xMe26V0Ot3XX3994403+vv7kyQplUpXr169evVqgiBMJtO///3vuLi45OTkDz/8kKkl63S6//mf/5moUui4KqBubW1te/bseeuttyQSyRgTKxSKu+66i/l3V1fX8ePHs7KyEhMTn3nmmYULF9bX1ycmJt5xxx0ohQJMLaiAAnjHVVRA3deqs9nsW2+9ddu2bVwu96abbvrmm2/0ev3IKU0m08mTJ++///7ExMS8vLygoCDmg1ar1Wq1btq06b777tu4cWNkZOTk7LbHqJBFRUUtWbIkNjbWZDIFBwc/88wzJ06cWLBggUQiueWWWxYsWOCeidPpLC4utlqtKSkpLperra1NKBSmpaXZbLbi4mLmHO61czqdnZ2dO3fuXLlyZVJSkt1uN5vNIxuSkpKycuVKqVRqtVrd79vtdqacnJqa6nA42traRCJRSkqKxWIpKSmZ2BLdpUsLRVE6na6oqCgnJ8ddSmQwYzNYLFZWVhYzYDQwMDA2NnZ4eLi6unqiQhrvVfBGo7GsrKy+vn7z5s0SiWRoaMj9841xQ4be3t7GxkaJRDJr1qyWlpaenp74+PiQkJCurq6WlpaJagsATA5UQAG8Y1wVUIqitFotc9G3Wq0uLS29cOECi8W67bbbSJLkcDitra3Dw8Nqtbq9vT0tLc1isbS0tHR3d589e5a5sEatVjNXQ5eWlj777LMxMTFKpXL58uVsNruvr6+jo6Orq8tisUz4sEXGRXm23W6vq6t7//33o6OjuVyuw+GYM2dOcnKy2Wzu7OxsampqaWl56qmnkpOTJRIJMwez2VxdXd3S0rJmzRq5XG4wGKRS6cDAwMDAgM1mi4mJYc6bXyOdTnfq1KmPP/44MDCwtraWJEmJRLJo0aLU1NTa2try8vLU1FSbzRYQEJCdnR0REcF8ymQyVVdXX7hwYd26dTKZjInNZDINDAzY7XbmDP61x0YQBEVRBoOhtra2v7+/vb09PT1dJpMRBDE0NFRdXb1o0SKBQDDyuwYHB5mJb731VhaLJZPJxGKx1WodGBggSZK5w8CEGNc9vNRq9e7du4uLi4OCgsrKylwul7+//x133BEUFGS323t6ei5cuKDValtbW6Ojo92f6urqqq+vZ7PZK1asIElSoVAIhUKDwTA0NCSTyYKCgiaqLQAwOXBPCgAfcrkdOU3TZrO5vb3dYDAEBgaKxWKj0Wg0Gnk8Hp/PDwkJsdlsbW1tHA4nLCxMLpczJbGamhq5XM4kalKpNCIigqbp9vb21tZWNpsdFxcXHh7OZrN7enqGh4flcnlYWNgVXo10FRnVyDOzTqeTw+GcOnVKIpGIxWKZTCaTyTgcjsFgYHIjuVzu5+c3Mhij0VhRUTFz5kyxWMxisQiC6Orq6ujocLlczFnvUUMab5xWq1Wj0XR2djIfZK5JCgsLE4lEfX19bW1tCoVCJBL5+flJpVJ38dhgMFRXV8+YMUMkEjGxdXZ2dnR0MB9PSUlxh3GNt2Ficveenh6tVhsaGhoYGMicQzcYDO3t7aGhoXK5nAmA0dfX19nZmZKS4j6uaGlp6e3tJUkyKChojOvHJypjHnV51ul0XV1dQ0ND7k4OCQmJiIjg8/kul0un0/X29jIHFcxgEoZarWYuVmNudEXTdHV1tV6vZ8ZpMLfK+lG4DROA78DaCOBDfO3JMZczjZ/o46FIGL4Wz+VMlTjHCwkogO/AKXgA8Lgp8ZxGuGqXS+zwEwPA5SABBQCP86nnjsKEw68JAOOFBBQAPA4V0OkNFVAAGC8koADgcaiATm/4NQFgvJCAAoDHoQI6vaECCgDjhRvRA4DHoQIKAAAjIQEFAI8b75NyAABgekMCCgAehwooAACMhAQUADwOFVAAABgJCSgAeBwqoAAAMBISUADwOFRAAQBgJCSgAOBxqIACAMBISEABwONQAQUAgJGQgAIAAADApEICCgAAAACTCo/iBJgympqa9u3b19jYGBMTs2rVqoyMDG9HNAFomu7o6Dhy5MjJkydFItF99903Z84ckiSdTmd+fn5jY6NCoZg5c2ZWVhYz/cDAQGFhYXJyckJCgoficTqdZ8+ezc/Pv/POO9PS0pj39Xp9cXHx7t27e3p61q5du3r16vDwcIqimpqaDhw4wGaz4+Pjc3NzRSIRQRBGo7Gurk6n061YscITQXZ3d//9739fuXJlXl6eVqstLCzMz8/v7++//fbbV6xYIZfLKYoqKSk5c+aMQCBISUnJzc1lPqjT6crLywUCwfz58z0R2LhYrdaampo///nPH374oZ+fH03TbW1tR48ePX36NJvNvuWWW5YvX85isVwu18GDBxsaGkZdEpKSkhITE73bEAC4CqiAAkwZCQkJAQEBGo3Gz89vemSfBEFYLJahoaEZM2Y8+OCDQqHwhRdeYN4/fPhweXn5jBkzOBzOJ5984nK5KIrSaDR79uxJSkqKiYnxUDwURQ0MDNTX1588eXJgYIB502azdXV1tbe333///evXr3/77be//PLLnp6ehoaGw4cPs1isW2655YUXXtBqtTRNDw8PFxYWDg0NLVq0yBPhtbe3f/bZZ0eOHNFqtRaLpb293WKx3Hvvvbm5uU8//fTevXuHhoZKS0tPnToVEBCQlZX1xz/+0eVyEQQxMDBw5MgRPp8/a9asCQ9svIxG4/nz5z/++OPi4mKHw0EQhMFgaG5uViqVd955Z0BAwKOPPlpYWGi32w8fPlxWVjZjxgwulztySfjuu++SkpJiY2O93RQAuBqogAJMJRwORyQS8Xg8giC0Wm1xcbGfn19jY2NaWlpKSsrAwMC5c+fsdntsbGxBQQGHw7ntttsiIyOrqqp0Op3ZbLbb7ZmZmSqVqqqq6tixY3PmzBkaGmppaYmOjl61apVEIpn8FgkEgpkzZ5Ik2dPTM3/+/MjISOZ9u91OURSLxSJJkqIol8tlMBj27t27aNGiyMhIDsdT2y42mx0YGJiZmblr1y73myRJhoeH33vvvWw2Oysr69ixYzwez+l0ulwuu93O5XJZLBZN0zRNWyyWc+fO8Xi8zMxMgUAwsbE5nc7e3t5Dhw7NnTv3+PHjTGDJyclZWVksFiszM3P37t0kSbpcLofD4XK5WCwWi8WiKIqiKKvVevToUZVKlZqayiw/XmQ2mxsaGi5cuJCXl3fgwAHmTRaLlZOTw+fzWSxWYGDg2bNnrVYrTdPuJYEgCGZJMBqNk7AkAIBHoQIKMCUNDQ0VFhbu27cvMTHRYrFs3bq1ublZKpVWVlZ+9tlnFotl4cKFhw8f/tWvflVQULBnz56+vj6FQlFRUbFt2zY2mx0TE/Pxxx+fOXMmOjpaIBAcOXKESWgmH5NYVFVV/eUvf3n99dfNZjNzh6a8vLykpKTm5maBQHD33XcPDw9/+eWXK1asiI2N1Wq1g4ODFEVNWpA8Hk8mk7HZbIIg+vv7Y2JisrOzw8LCEhMTc3NzbTbb6dOnX3rppcDAwL1794pEIuY0cUdHB1N6nBA0Tff19X311Vfr16+PjIxkkkihUCiRSJjz1IODg6mpqQsWLFAqlVlZWXPmzOnv729ra/vFL37B4XC++OKLuLi4tLQ0s9ms0WgmMLDxoijq/Pnzra2ty5cvVygU7vclEolQKGSxWDabzW63z5o1a9GiRXw+f/ny5cySIBQKN2/ePDw8vH37dm8tCQAwUXDsCDD1kCQpl8tXr149c+bMY8eOtba2trW1WSwWmUwmFAoDAgKWLVtmtVp/9rOfPf30088888wzzzzT2NhYUlLS0dHBlOsUCgWHw0lMTExMTOzv7+/s7Ozp6fFic2bMmPHyyy8fPHjwt7/97cKFC+fNmyeRSG6//Xbi/waJnjhxYvHixeHh4c8880xubm5dXV1sbOztt98+4VXGMdA0bTabP/nkk82bN8fExHA4HA6HM3v27NmzZxMEQVHUd999FxYWlpycvHv37tbW1sTExDNnzvzxj38Ui8XXftuppqamPXv2xMXFqdXq7u7uoaGhpqamjo6O8PBwmqY1Gs3WrVtfeuklf39/FoslFArz8vLy8vJomjYajV9++WVGRkZsbOx7770nEAi4XO7AwMAvfvELZsTqJNu/f397e3tUVFRDQ0NdXZ3NZispKcnJyZFIJMzY35qamtLS0ldeeUUoFBIEIRaLfW1JAIBrhwoowBRAUdTg4KDRaHS5XAqFQiqV9vf3f/fdd2+99daiRYsWL14sFovddSCapl0uF4fDiYyMVKlUarX6rbfeUqvVixYtSklJYU7IEiNuBU+SJEmSXr8zvEwmy8jIWLhwIXPi1f1+d3d3Q0NDQEDAjBkzLly40NvbGxsbGxgY2NPT09bW5qFgmPPpI9+xWq2NjY379u3btGlTVFSUwWAwmUzuv9rt9pMnT7LZ7JSUFIfD0dnZKRKJEhMTrVZreXn5hJToBAKBVCqtqak5fPjw6dOntVptVVVVc3OzXq+vrq4uLS29//77lUrlwMCA1Wp1f4q5dkoikWRkZAwNDXV3dwcEBERGRup0urq6umuP6irI5XK73V5aWlpQUHD+/HmLxXL8+PGhoSGapgcHB4uLiwcHB2+66SaBQNDT0zOyUnvpkhATE+PpJQEAPAQVUIApwG63f/XVV729vQ6HY/78+bNmzbJYLN3d3fX19T/88IPZbO7o6Kivr4+PjycIorOzMz8/X6lU7t69+8knn5RKpR0dHTqdTqfTdXZ2trW1VVVVEQRhMBjq6+tTUlK6u7vVajWHw9Hr9TKZbOT3TuDt4ke9Fz1N0+3t7SdOnDCbzeHh4UajMTs7e+HChXw+n/lUW1tbY2OjWCzOzs4mCCIoKEgkEg0PDw8MDPj7+4eEhExUeG4URen1+oqKCo1G09LSMmPGDIVC0dvbm5+fv337dn9//5MnT9I0HRISsn79euZqHoPBUF5ePjAwsHLlSolEYjKZ/Pz89Hp9X1+f3W5PSEhghhlco8jIyEceeYT594ULF1paWjZt2hQTE7Nt27b8/Hx/f/+CggKHwxEZGXnbbbcxl+ZotdqamhqbzbZhwwY2m80culgsFofDwWKxoqKiLvddNE0zv85Fr9feCoIgcnJycnJyCIIwm81nzpw5duzYs88+GxAQUFNTs3379urqan9/f2Y5jImJeeCBB5h/j1wSSJJklgSdTjc4OKhUKoODg68xKo82GQAuhbULwIdcrgxJUVR/HnSTwwAAEJpJREFUf39HR0dAQEBgYKBQKKQoSqfTaTQaiUQiEokGBgaUSqVYLH7zzTdLSkreeusth8MhEokCAwMJgujp6XE6nSKRiDmJHBoaShCERqORSqUymcxqtRqNRh6P5+/vf9ElHRO4Ax51B08QhNVq7e3tNZvNIpFIIpGIxeKR51JbW1sdDkd0dDSXy2XeUavVGo1GLBZHREQolcqxv3S88TOFT5fLNTQ0pNfr5XK5TCbjcrl2u314eHhoaIiZIU3TEolEqVQy54gNBkNdXd3MmTP5fD4zgVar7ezstNls4eHhKpXqWuIZ9X2Hw9Hb2yuTyXg8HhOqOzCZTKZUKpkMXqvV9vT0JCcnu6866u7u7urqIkkyIiJijPR9on73scvqzKVRPT090dHRbDbbZDINDg6azWb38Ymfn5+/vz8z9Latrc1ut1+6JIhEIpVK9aNLAgMJJYDvwNoI4EOu8Ty40Wj861//Wl9f/9FHH03IJe2e3mF7+rz/RCV8E8XX4hnDhJQDvT6u4yJjNAEVUIBJhjGgANMETdM9PT0xMTGLFy9uaWnxdjgXY3KRS1/BB406XsLLMXnYddhkAO/CCgbgQ3wtJ0MFdGL5WjxjQAUUFVAAj0IFFAAmAyqgU8h1WA68DpsM4F1IQAFgMmAHP4Vch0cL12GTAbwLCSgATAbs4KeQ6/Bo4TpsMoB3IQEFgMmAHTz4MhwgAUwyJKAAMBmwgwdfhgMkgEmGBBQAJgN28ODLcIAEMMmQgALAZMAOHnwZDpAAJhkSUACYDNjBgy/DARLAJEMCCgCTATt48GU4QAKYZEhAAWAyYAcPvgwHSACTDAkoAEwG7ODBl+EACWCSIQEFAID/gqMFAPA0JKAAAPBfUA4EAE/jeDsAALgaTqfTbDZbLBaSJCUSiUAgYLFYDofDbDbb7XY+ny8Wix0Oh9FodLlcQqFQKBSSJMl8hMfjSaVSNpvt9azCZrOZTCYmPOYdmqatVqvJZPLz8+NyucybTENomhYIBExLmSntdrvD4ZBIJJ6L0GQymc1ml8tFEARJkiwWy9/f32QyORwOLpcrEAjcQVIUZTQaRSIRhzMZ21W9Xm+1WimKYgLjcrlKpZJ53+l0XmNsNE2TJHnp60QFb7FYmCWT+S+bzVYoFExsdrvdZDLZbDYWiyUSiUQiEYvFYt5hs9kCgYDP57sbZTabeTwej8ebqMAAYNIgAQWYkgwGw8mTJ3fs2BEQEPDwww8nJCTw+XydTnfo0KHm5ualS5fOmjVLq9V+9NFHPT09GzduzM3NNRqNhw8frq6uXrNmzdy5c2UymXcTUJPJdOLEifz8/NWrV69du5YgCJfLNTQ0dPjw4QMHDvzqV79KTk5mWlpRUVFUVBQXF9fU1PTAAw8wmVZ7e7tarZbJZFlZWR6K0Gw279q16/z58zwej6Ioq9XKZrMfeuihkydPSqVSq9UaExOTl5dHEITdbi8qKrLZbFlZWQqFwkPxuBmNxq1bt7a1tXG5XJfLZbPZgoOD//d//7ezs3Pv3r1yudxsNickJOTm5hIEYbPZzp0753A45syZ4+fndyXz92gF1GKx5OfnHz16lMfjMQdFBEE899xzkZGRLperpKTk0KFDOp1OKBSuX79+9uzZQ0NDR44csdlsXC5XLBZv2rSJmc/58+f1en1ycnJYWNhExQYAkwYJKMCUpFAoVCqV1Wrl8/kxMTFMWSggIMDf399oNM6bN48pgvJ4PIvFEhgY6HK5ampqKIrasmVLWloaU0T0LhaLxeVyu7q6BgcHmXeYEiOPx2tubmbyEoIg1Gr1mTNnRCLRokWLXnzxxQ0bNsjl8o6OjoaGBqlUOnPmTM9FODQ0lJKSkpqaKpPJ+vv7T5w44efnd+TIkaGhoZycnN27d3d1dS1ZssRms1VXV3d0dKxZs+YKM7xrpNVq58+fn5ubKxaLW1tby8vLIyMjnU7n/v37tVrt0qVLd+7cqdVqc3JyrFZrTU1NV1fXunXrZDLZFc7foxVQvV6vUqk2b97s5+dnNpv3798vl8uZEnhlZWVDQ0NycvKMGTM4HE5ERASPxzt16pRarV68eHFbW9sPP/xwww03kCRZVVXV2tqanZ0dEhIyIVEBwCRDAgowVbFYLIFAcNH5RzabzePx3Gda2Ww2m81ubGysra1VKpV33XWX+2S31wmFwuDgYIFA4H6HxWJJJJKwsLCR+bFQKJRIJAaDgaZpf39/gUBgNBpLS0uVSuXcuXM9er47JCQkNDSUCcZut7e0tPz1r389cuRIX1+f3W5nzg67XK6Ojo5z58499NBDfD5/corKkZGR0dHRzHe1t7frdLobb7yRJMnAwMC2tjYmNrFY7HK52tvbS0pKfvazn3G53CuPzaMV0MDAwMDAQKZXe3p6zp8//7e//U2pVNI0ferUqQ8//FCv18+fP/9Xv/oVM26EqSjbbDY+ny+Xy0mS7OvrO3z48D333BMUFOQLh1IAcBWQgAJMeWMnBz09PX/84x9XrFixZcuWqbK3Htmi+Ph4Ho9XUFBw6tSpN998UyKR7NmzJyUlJTo6+sKFCzabTaFQhIeHeyLzY7PZzD+Gh4c1Gk1UVJRMJrvppptYLFZTU9Ps2bMjIyNramrKy8sffPDB3t7e4eFhkUgUEhIikUg8mom6A+vr69Pr9RERESKRiCCIm266iabp+vr67OzsyMjIqqqqmpqaLVu29PT0MLGFhoaKxeIfjc2jFVD3QmgymVpbW2NiYmQyGdOiJ5988tFHH62qqvrwww/vu+++HTt2JCUl5eXlsVis7u7u4ODgn/3sZ21tbXv27HnkkUd0Ol1tbS2Xyw0KCmIS0wkJDwAmx9TYGwHApZiz1Xa7feQtcpjz2iMTzdDQ0CeffFIoFL755puff/55f3+/N4K9eiRJRkVF3X///Rs3bkxOTj5y5EhqaqpKpfr222937NjR1dX1hz/8ob29nbkcx0NaWlrKyspuv/12Jp6NGzf+5Cc/Wbhw4dDQUGdn58qVK3t7ex999FGbzfbhhx8ePHhQp9N5LpiRysvLtVotM4KWiW3Tpk0/+clPsrOz+/v7e3p68vLyurq6Hn74YafT+c9//vPw4cN6vf5HZzs5V8H39PQcPHhwy5YtI6vyHA5n1qxZzz333PLlywsLC202G0mSy5Yt27x5c25uLkmSxcXFmzZtcjgcL730Ultb2+7du7/66quBgYEJDw8APAoJKMBU5efnl5CQUF5e7nA4mHfMZrPVaiVJ0p0uuFwuiqJmz5793HPPrVmz5sCBA7/+9a+rq6t95LaO9P8Z+SZFUaNmkzab7auvvoqPj09OTna5XAMDA3w+PyQkxGq1dnV1uS+pnnAWi6W/v99utyckJIx8//z58xqNZtasWQEBARqNxmQyRUREcLnc/v5+g8HgoWBGMhqNWq2WzWZHRUVd9KeSkhKtVpuVleXv79/b22symVQqFZfL1Wq1VxLbJNwH1GazMR2VmprKjKNw39aAIAjm3g4LFy50X/NOEERTU1NVVdW8efNUKlVvb6/BYAgKChKJRMPDw+5hxAAwVeAUPMBUFRERcd9993V1dT300EM5OTkkSWq12rS0NKYeZrPZysvLjx8/3t3dfe7cuejo6LVr1w4MDLz00kv79u3bsmXLrbfempKS4sUhoYODg0ePHq2trQ0ODs7Ozo6Pj3c4HN3d3fv27WttbT1z5kx4eHhwcLB74vz8/LS0tNTUVKFQKBAIQkJC1Gp1a2src3235waD1tXV9fb25uXljawCnjhxwmq1zpw5U6VS0TQdFxcnEolaW1u1Wu2iRYsm57rskpISkiTnzZt3UXny2LFjDodj5syZ4eHhNE3Hxsa6Y1u+fHloaOiPznkSKqCtra11dXXr1693z1mtVr/99tsNDQ1paWnBwcE333xzamqqu5ZfVlbW3d2dkZERGxtL03R8fLyfn19PT49Go4mJiYmNjZ3Y8ADA0zBoBsCHXEWdiaZpo9E4MDAgl8uZu3tOYDwTmHaMOqzwyj9utVrb2toSEhLcGYnD4ejt7dXr9YmJiZfLPscb/6ghmUwmp9MplUpHDmzo7OwUCoX+/v7uD1oslvr6+ujoaLlcfrmxthMSj5terydJUiwWX/R1HR0dYrGYuVmVO7a6urrY2Fg/P78rHAc8IWNAx4jfarVaLJaL4nE6nXa7nSTJS4+Lent7KYoamT1bLJaWlhZ/f/+goKArXOwxThTAd2BtBPAhPnJm3M13EtCrM7EJ37XztXguZ6J+92m8PAPANcIYUAAA+C94FjwAeBoSUAAA+C94FjwAeBoSUAAA+C+ogAKApyEBBQCA/4IKKAB4GhJQAJgM481pkANNDvQzAHgFElAA8Dmj3gMIZ4EBAKYNJKAA4HM8+ixyAADwOiSgAOBzUAEFAJjekIACgM9BBRQAYHpDAgoAPgcVUACA6Q0JKAD4HFRAAQCmNySgAOBzUAEFAJjeON4OAAD+n8rKSm+HMKkqKyszMjIqKioufSVJctRXb8VzuVePxjPeou+4Is/IyBj5LZ64Caiv9ScA+A6c0gLwLRwOx+l0+s7rVG+vR+MZ78w93Z/jDcnXfl9PBzMJ7QWAK4QKKIAPefzxx70dwn959913PTr/xx9//N133x3X67jmP974fS2e8Xr44YfHFb9HgyE835/jNQlNBoArhAoogG+53PU33nqd6u31aDzjnbmn+3O8Ifna7+vpYHAdG4DvwNoI4EN87TqbSUiYxptTjmv+443f1+IZr2lwdOHReJCAAvgOXAUP4EMuvRzEu6+T0N6ryJk8F79PZUtXh4nqyl89ahr0JwB4CA4HAXyIr+2Dfa1ihwro2FABHRsqoAC+AxVQAB/iC1VPVEB9JFu6OqiAAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAXKf+P5UrI7EE4Th0AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=896x896 at 0x7F1D87787350>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[         0      1              2      3        4\n",
            "0  Germany                               Average\n",
            "1   Israel  Funds                  Tate    Stage\n",
            "2    Japan         Early “Midale     B)     2.0\"\n",
            "3       UK    187             We   0.74       14\n",
            "4        \f     98    0.68\" 0.89\"             2s\"\n",
            "5      NaN     37   0.934% 0.499  0.284       24\n",
            "6      NaN    140   0.15% 0.199%  0.65\"        \f\n",
            "7      NaN      \f       048 0.84   0.80      NaN\n",
            "8      NaN    NaN              \f      \f      NaN,          0      1         2         3         4          5           6\n",
            "0  Germany                             Electand   “Mnf and       Other\n",
            "1   Israel  Funds      Life      Wand   Semi-C.  Chemicals  Industries\n",
            "2    Japan   Ts3-  Sciences  Software      0.16       0.23         O17\n",
            "3       UK     95       021      0.23      0.16     0.08\"*          oo\n",
            "4              56    0.249%       sie    0.05**     0.06¢*          od\n",
            "5        \f    140    0.267%     0.499       ous       0.24        0.19\n",
            "6      NaN               oT      0.26         \f          \f           \f\n",
            "7      NaN      \f         \f         \f       NaN        NaN         NaN,          0    1    2         3\n",
            "0             \f       ‘Formore\n",
            "1  Germany  NaN  11%       60%\n",
            "2   Israel  NaN   2%       21%\n",
            "3    Japan  NaN   ™%       42%\n",
            "4       UK  NaN    \f       75%\n",
            "5           NaN  NaN          \n",
            "6        \f  NaN  NaN         \f]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yyDKDvDKGsAb"
      },
      "source": [
        "# Upper Table Detection"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aOGqpULmqn77"
      },
      "source": [
        "\n",
        "import cv2\n",
        "import numpy as np\n",
        "import os\n",
        "import matplotlib.pyplot as plt\n",
        "from PIL import Image\n",
        "import pytesseract \n",
        "import pandas as pd\n",
        "\n",
        "def table_detection(img_path):\n",
        "    img = cv2.imread(img_path)\n",
        "    img_s= cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
        "    img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
        "    #plt.imshow(img_gray)\n",
        "    #plt.show()\n",
        "    #(thresh, img_bin) = cv2.threshold(img_gray, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)\n",
        "    (thresh, img_bin) = cv2.threshold(img_gray, 180, 255, cv2.THRESH_BINARY)\n",
        "    img_bin = cv2.bitwise_not(img_bin)\n",
        "    #plt.imshow(img_bin )\n",
        "    #cv2.imwrite('img.jpg',img_bin)\n",
        "    #plt.show()\n",
        "    kernel_length_v = (np.array(img_gray).shape[1])//200\n",
        "    vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, kernel_length_v)) \n",
        "    im_temp1 = cv2.erode(img_bin, vertical_kernel, iterations=5)\n",
        "    vertical_lines_img = cv2.dilate(im_temp1, vertical_kernel, iterations=5)\n",
        "\n",
        "    kernel_length_h = (np.array(img_gray).shape[1])//100\n",
        "    horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_length_h, 1))\n",
        "    im_temp2 = cv2.erode(img_bin, horizontal_kernel, iterations=5)\n",
        "    horizontal_lines_img = cv2.dilate(im_temp2, horizontal_kernel, iterations=5)\n",
        "\n",
        "    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))\n",
        "    table_segment = cv2.addWeighted(vertical_lines_img, 0.5, horizontal_lines_img, 0.5, 0.0)\n",
        "    table_segment = cv2.erode(cv2.bitwise_not(table_segment), kernel, iterations=2)\n",
        "    thresh, table_segment = cv2.threshold(table_segment, 0, 255, cv2.THRESH_OTSU)\n",
        "   \n",
        "    contours, hierarchy = cv2.findContours(table_segment, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
        "    count = 0\n",
        "    dict1={}\n",
        "    lst1=['shipper','consignee','notify party']\n",
        "    for i,c in enumerate(contours):\n",
        "        x, y, w, h = cv2.boundingRect(c)\n",
        "        if (w > 0 and h > 0) :\n",
        "            count += 1\n",
        "            cropped = img[y-3:y + h, x-3:x + w]\n",
        "            \n",
        "            txt=pytesseract.image_to_string(cropped).strip()\n",
        "            for el in lst1:\n",
        "              if el in  txt.split('\\n')[0].lower():\n",
        "                if cropped.shape[0]<img.shape[0]/20:\n",
        "                  cropped = img[y-3:y+ h+int(img.shape[0]/14), x-3:x + w]\n",
        "                  txt=pytesseract.image_to_string(cropped).strip()\n",
        "                dict1.update({el:' '.join(txt.split('\\n')[1:])})\n",
        "              img_s=cv2.rectangle(img_s,(x-3,y-3),(x + w,y + h),(255,0,0),2)\n",
        "\n",
        "\n",
        "     \n",
        "\t    #cv2.imwrite(\"table.jpg\", table_segment)\n",
        "\t    #cv2.imwrite(\"img.jpg\", img)\n",
        "    dict1=pd.DataFrame([dict1])\n",
        "    return  dict1,img_s\n",
        "dict2,img_s=table_detection(\"/content/sample_mavericks/BL_300363908.pdf_1.png\")\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "02LfGSKRGch1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 287
        },
        "outputId": "c563af54-5f63-4f92-fe05-74b4c9782b86"
      },
      "source": [
        "plt.imshow(img_s)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1d8778d310>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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oNPD5/bgsi3ffe++puVWHzpuREnn9+ss+i1cKh9ZABOCyLNKZDGJoCL/fT6PRwO12Y5omtXodIYSu+zAMg0qlwtLSEoODg5qcWCgUdIa5VCrRbre3FRkdKki5b3mbI+yOQ2sg0K3b+Oyzz6jVapRKJSYmJpifnyeRSJDP5/H7/QghePPNNzUd4caNG1y7dg0hBKFQiFwuh8fj4cKFCywsLJDP56lUKnzjG984fAZyhGeOQ20ghmnyrW99i0ajQbPZRAjB8ePHNRNVCRh4vV5cLheNRoO33nqLfD5PKpXSy1qtFtFoVNdodzqdR9IxjvD1waE2ECklV69eJRwO4/V6MU2TTqdDs9lkdXWVM2fOMDs7C6BbAAwMDOD3+8lmswBUq1VN6d7a2qJYLHLixInDS2bc2sL+oz/CeMogxUMVhoUWGXuy9Z/HOex1/fl55Guv7escDr2BNJtN5ubmaLfbJJNJVldXicfjmpOl1E62trYYGRnh+vXrGIaBy+Wi2Wzq+vVOp0M2m6XZbNJsNh9/8AOKsm1zaWMDXyhEIpGg0WxSr9ep1Wrd+hcp8Xi9mIZBx1F9tzsdLJcLw4kAer1eVldXiUSj3arETkcnYCORCLlcDltKIuEw9UZDKx+apknI8ffS6TQrq6vgsIXbnQ6tZhO/I5pRrVSIRKNUKxUslwu3y0W708FyXnKtdptyqaS1vbxO4demoxugzt/jdmv1xU6ng2lZ1KpVLJcLIQQet5t0IEBsn/fzUBuIYRhcuHABl3MzLMui0+lQr9exLAvbtrt0Z0eGH9BU+GazqZm/7XYbt9vN22+/rZe1Wi2tK6XqJrxeL81mE8uydHnuQYM3FuPYt79NoVpFejzQbOKREp9haMGGYDhMo9Gg02rhcgzI8vkIBAK6jn9oelo/mPV6nWAwSK1WwzZN/I6MkOHxQLVK0OfDcoqrANxuNznbJpROU6lUMIVAtFqEfT42NzeJx+N4HKEIX7tNu90mEI1SrVZ1HYrRaGC0Wvh8PryOzKgVDuMrFGi327Sk7IbyLYuAYdBut7dpDCjBPJfLhXt5+eupzWvbNj/58Y9pOHXn4XCYbDZLIBBgYGCAn/70p6RSKbxeL5ubm4yNjVEoFPD7/QwPD3Pr1q2uUHKpRCaToVgs6kYwgHb8FxcXtdGphi7nz59/yVe/O8rlMrdu3aI/k2F2drb7MLVahMNhRkZGmJ+fx7ZtVlZWdF8Qt9utVReVCJ9qgDM3N6cr9RqNBvF4nOnpaT777DPq9Tqbm5t4vV7GxsbI5/P64RRCEA6HKRQKAPr+WZZFvV7n3r17eL1eTpw4wdLSEoFAgEKh0C2fdQwyGAyyvr6OaZrkcjkMx8hjsRhCCGq1Gu12m/7+fhYWFvB6vYyOjlKpVGg0GrTbbUzTJG1Z3Z6W+8BTGYgQ4j5Qoqvw2JZSXhRC9AH/FhgD7gO/LqXMie7r9p8A3wGqwP8opfz0KY/P2XPnKBaLWrrG6/USiUSIxWL88i//MltbW9i2TSAQYGRkRPed8Hq9pNNpLMuiUCh0NXljMWKxGOFwWI8qiUSCsPPGzWazmkZ/UOF2uTh2/DjRRAKfz6dH1kajQTQaxTRNTNPE7/djGEY3d+S0elBVeEoRJhQKMeyU6iqJICV+EY/H6evrY3BwkFarRTAYpN1uE4/HdfMcIQR9fX00m02tBuNyufD5fEQiER1ACQaD+vhqxFcSTOl0Wqu0dDqdbpsJunUrJafGIxwOEwqFqFarBAIBLdQhpewGcGZn8e7TJ3sWI8iHUsrNns+/BfwnKeXvCCF+y/n894BvA8edf28D/9z5+1RQVWNKDn9xcRHDMHR2fXh4WJfdFotFfD6fzouo5jKJREIrEKpiq2q1ysDAAO12m2AwSCaTYWJi4mlP97mjVCpx/do10qOjuo+gmkZWKhXW1tb0211F/yqVCl6vl8HBQQBWVlawLIv79+/rEXNubo5Op4OUkrm5Of0wqrp1y7LweDwEg0EdAHG73dumqs1mk0AgoHsjqlHDMAzC4TCTk5N88cUXtFotrU+mRgo1SiijTiQSbGxsIIRgdHSUXC5HoVAglUptG8VM02QslyOselnuEc9jivVd4FvO//8V8Gd0DeS7wL+WXU7IT4UQUSFESkq5st8DSSm5c+eOdhJPnDjB+vo6rVaLq1evAmjfYXl5WQs5ZLNZ/H4/oVCItbU14vG4fkhisRiBQIBsNqtFIMLhMO+///6BLT/tRayvj4tvvonl9eL3+3G73dtGkoGBAVwul9bsVdOner2u1V1GRkb0W7her9NsNjlz5oyua+/v79cJVjW6qBLXVqvF0NAQlmXpkl7TNKnVatv0ytxuN5ZlUSwWWV9f7/odhsHU1BTBYJBKpaLD7r0jmmoQ2mg0OHHiBKZp4na7vxJosCxqtRpbW1tEIhEMwyB2//7eWob34GkNRAL/rxBCAv+7lPJ3gYGeh34VUKabARZ6tl10lm0zECHE94HvA4yMjDzy4IZhMDk5qXvpKTEGpXKifjQpJdlslkgkoufAhmHQbDYxDEO/CZWPoWqaO50ObrdbBwEOA4qFAn/5F3+By9ECMwyDVquluWm2bTM0NESz2SSfzyOEoFAo4Ha7GRoaolwu02q1dGTI5XJRr9cZHBzk7Nmz3L59m0ajwcrKCq1Wi+PHj3Pv3j09Uihd4Nu3b+P1enWVZ6vVIhKJkE6nmZ2dZXR0VEujlkolhBCcPn2aL7/8Up9LLpejUqlsC6jU63UmJiZYX1/XPpUyllu3bmFZFplMhuXlZQDu3LnDG8DwPvNaT2sg70opl4QQ/cAPhRC3er+UUkrHeJ4YjpH9LsDFixcfua2SB1WRqVOnTvHxxx9z6tQp8vk8sVgMy7K4e/cugUCAzz//nKGhIU6fPk2z2eTatWsAOnqzsLCAEIIPP/yQWCzGjRs3KJfLD+3HdxARCod57733EE74U70setsgqJFxenq6G5mybdrtNj6fT3doUkLgLpeLzc1N/RI6e/YsAGNjY3qbeDxOs9nUb3KPx0MymaReryOdaJOaUoXDYfr6+rTkqwq3+3w+ms0mA85UyO1209/fr5vhbG5uEovF8Hq9CCEYHh7WckXqul5//XXNkBgcHNQjpu/WrV1zN0+CpzIQKeWS83ddCPFHwFvAmpo6CSFSwLqz+hIw3LP5kLNs3zBNk7GxMWZnZwkEAlQqFSKRCIuLi8RiMdbX1zl58iSJRIL5+Xn6+/spFou6VfHY2Birq6taIyuRSOhQ6MrKip4abG1tEY/Hn+ZUXxhKxSKXLl2i7lBrMpkMq6urVCoVAM6ePcudO3ewbVtff6fT0QrwHo+HY8eOsbCwQLFY5NixYzrZWq1WkVKSSCTo7+9naWmJdDrNwsLCNg5bpVLR+261WoyMjLC4uEin02F8fJyVlRU9JVJGlk6nuXv3rlbGVIr9oVCIQqFAf38/n376KSMjIywvL9NutxkcHKRYLJLL5bQ/c/r0aa5cuYLL5dKj1Zl2m9Fkcl/3c98GIoQIAIaUsuT8/5eBfwD8MfAbwO84f/+js8kfA39XCPEHdJ3zwtP4HwqTk5NMTk7qz+ldlAJjsRhnz57VUpxq/j06OrqrCLVt2/j9flKpFCdPnnzaU3yhCEcivPHGG+By6TZlXq+Xvr4+neM4c+aMFs0LhUK43W4aToPLRqOBYRiMjIxo+R8V1Gi1WjoAYpomyWQSv9+vI3uWZenRwu12Mzg4SLVaJRKJ4Ha7tUh4MBjUBqD2tbW1xdtvv43f76fdbpPP50mn07jdbkqlEslkklgsRiQSIRgM0tfXt220q1arxONxXC6XjlK6XC4GBgYI3r37UsK8A8AfOQ+XBfyfUsofCCEuAf9OCPG3gDng1531/4RuiHeGbpj3N5/i2NvwJP5Bb29tj8ejl+22rWEYBzYR+DgUi0V+/JOfIBzxNBUOLRQKdDodqtWqjjgpf2ttbY1AIKBHjKWlJVKpFKurqywuLpJMJtna2kJKSblcplqt0tfXR61WY3R0lMXFRT33n5ubQ0qpZWA9Hg+RSIRqtcrs7KwONc/NzREKhTS7ularMTs7SyqVYmlpSedMlJB4LpejXq8TDof1+W1tbZFIJEin06yvr+uZQ7FY1Nfr8/l40+XCs0/q0L4NREp5Dzi3y/It4Bd2WS6Bv7Pf4z2wP+i+Fdpt9ltP+LjtDmOdYsDn49jkJIFolEajoSNzfr+fcrlMsVjEtm3C4bDObUxOTrKxscHY2BhCCCYmJrRTr/JDLpdL+xjlcplgMAh0XyZvvfWWDoKoMHoulyORSOjtqtUqhUJBj2R+v5+NjQ1GRkaIxWLdbLqjzm9Zls6tqAfetm1dovDGG29ozeVOp8Pa2hrRaFTnccbGxnTvFwD3/Py+7+fhzqRfvUpjYQFhGHR6IlYIgWWatDsdTGckUFMA1Q9DtTZQo8mrgsYXX1B7910K1SrhcBjbtjU7oFar0Wg0kFJSLBYZHBzUybZqtcrGxgaWZbG2tkY6ndajimmaNJtNtra2dA2NlFInG+PxOOVyt/OvkncVQtBoNKjX6wwNDbG4uIjH42HN0QJWPqLX6+3SUUyTUqm0TRVzbW0NgBs3bhCNRrFtW5NSVWRMCKEJpyMjI2xtbSGEYGZmhkQi0aUGFYv4I5F93c9DbSC1Eyf4kdMB1TAMhoaGWFpcxLQsBgcHyeVylEolRkZGWFtdRYJ+w2xsbJBMJjl16tRD93/oJlhS0vn7fx8JpFKpbRl0laTLZDJ6uqQe8lKppNeLRqO6/7i6p8qYFCNajRTDw8O7qhuq8HIvdkuyKtHwR20npWRsbGxbCfVu6/UeR0rJ+Pi43qZ9+fLXT1lR0HU+f+4b3+iyNh1nb/LYMaB7E8cc+onH4+HEyZPUajVyuRwDAwMMDA5iGAaFYlErmytKhApVHjrKuxNSjThZcr/fr8OrvejlKfl8Pl2JCV9pjClipqJ3KOZ0OBym2WxSrVZZW1sjFvuKJ9vr5z3sYe/163Z+Vuur5epvbw5H+Yc799t7fLWNWt/eZ5IQDrGBQLeJ/I9+9CPNEcpkMiwsLBCNRikUClpA7r333qNardJsNvn888/1jfT5fOTzeXw+HxcuXGB1dZWlpSUajQYffvjhE2u/HiTU63XW19fpOCXGKpKVTCZZWFhgcXFRz9X7+/tZWVnBtm0KhQLj4+PMzc0Rj8eZn58n6jBsVVvpTqdDqVTSEa1EIsHly5f1+oqH1Wg02NjYoK+vDymlzqjH43Hy+bz2JVwul86aR6NRNjc39TWEw2H924TDYaSU1J0y6t78CqATnhMTE3qKpXwZ27aJzs4ydoCoJi8MbrebDz74oFuf4Ki2RyIRkskkxZ6RQTF9K5UKJ06cIJ/Pk8lktOPabDYJBoMEAgGmpqb0dOQwQjGVDWdEVb6Wz+cjlUrppJqaKkH3gUwmkyQSCSzLIhqNaoc8HA5TLBZxuVzUajXW19fJZDI0m01NOEwmk7hcLs1e8Hq9mlzodrvJ5/O6PXen06FYLOoQrnLGm80mqVSKSqWiHXkVSIhEItRqNQYHB2k0GuTzeR1SVgwKt9uN3++n2WwSCoVoNBq601gqlXo5bN6XDdu2uXPnDv39/Zq9qZp2lstlMpkM9+/fp1gs6ilUNBolHA7rupFKpaI5WkIINjY2OHPmzOGbXjmoVqvcvHkTdyCg395DQ0Pk83k2NjYAOHnyJOvr61SrVZaWlgiFQkSjUS5fvtytBRka0onVhYUFQqEQGxsbOuRqGAabm5vMzs4ipdSUkVwuB6A76SrnPhgMUiwWNYerVCpprlWtViPhtPL+8ssvdXJQ8cSklCwuLlKr1XRApVar4fP56O/vZ3FxkWAwSKFQ0C+5paVu/lnRXIaj0a+ngXQ6HWq1Gp999hmGYehhOpFI0G63GRgYYGVlhUKhQLFYJJVKMTMzo4l0KhKSSqWIxWIsLy9Tq9Wo1+sEnAfsYTioOZJAIMDExATRZBKPx0OhUMDj8WDbth4hoJtgdblcJBIJ7XPFYjH9kolGo5qD1ul0MAyDYDCo+VWjo6N6+qZGjWq1qn3BeDyuWcTKh/F4PBSLRT31AfQoF4lENJOh1WrpKZT6LQiQA1UAACAASURBVFQiU03vFM1EMRzUtEpNHVUFpZQSe25u3/fzUBuI2+3m/PnzOumleD2K1WkYBu+++642JPX2c7vdej6rhmmPx8Obb76p4/Htdls7m6qASNG2VTj5oBrJ+vo69xYWeP3118nlcqysrOg5/YkTJ2i329y/f59Wq8WpU6dYX1/XjN0bN25Qr9dpNBqcPn2aVqvF+vo6U1NTXLp0iUajoe/t9PQ0xWKR1dVVAM1QaDmVgLZtc/78eS5dukQqlSIUCnHv3j1d6qyYxmq6NjU1xc2bNymXy9rBPn/+PLdv36ZYLOpjqJqdGzducPbsWT755BNcLhevvfYai4uLbG5u6ulzKpWiubq6b7KiOMiynRcvXpSXL1/e/cuf/Yzap5/yXzIZOp2OpiBsbW0RDocxDINbt24xPDyMy+VibW2NkZERqtWq7rqkYvKbm5tMTEyQzWapOvkD6NZWnDhxgmvXruF2u/Vb8sSJExw7duzgGYiUtP/RP6L8m79J05leqfbV6sGNRCI66dZut/W8Xa1Tr9edXXVHEhW9UteunF/FlFajQavV0tsZhoFpmpqyU61WcblcGE5prBoh1HqKCxYOh3WmXzn2fr+fWq22LVKlXnSVSoVYLKaddp/PR7lc1poDymDbly5hNpt4RkYQTpRTY3UVkUr9TEp5cbdbemhHEEl3eD516hSbm5u6Ki4YDJJMJjXLdHNzE9u2GRwcZGRkhI2NDYLBIEIIHc0BNH/I7/cTjUYpFou0223C4TBnzpzRFIt0On2gu+Hmcjn+4kc/ouG0o1MFU16vFyklP/dzP6dLVhV6/a3dfC8194/0JNt2hlYfhV59sd323/uSjuyS0HvYNqpNt8rqw/YOWep7w+Ohs08hjkNrIArFYpHx8XE9iqh+6SoaEo/HKTnqGGoUCQaDWvFEUbNt26Zer9PpdJiYmND0d/X5sCAej/PRRx9RqtfxeDzUajUdDVL9G58FnuXouZ99HXWYegKoirQbN26QTqdJJpN89tlnug7ENE0ymQwzMzNsbGwQiUSYmZnhG9/4hi7d3NjY0JSJhYVuPVcmk8GyLFZXV6nVasRisUMT1RKOj5Vw3qpH6pBPh0NtIEII3njjDU6ePKk5OsPDw9sq6AKBAKlUShPsqtWqplUcP36cgYEBnRs4deqUdg6r1SqTk5NdeRynFrt3WtGb7d25TH1+KVhfh3/5L2naNtYOeobonhgCR2Rtx/mrwIRmOTvfdZypmmWaejv4iorTsW2kbWM4oXJ1D6WUiJ71bdvWBFDTMPT/BWgOHYC0bXDOzXT8Fgn6+GqbjuMPPRbLy8hvfGOPN7KLQ20gzWaTS5cuMTU1Ra1W48aNG/T19ekfenJyUmfa3W43AwMD5PN5XRykZIIsy2JqaorPP/+c6elpKpUKX375JcFgUI9S4XBYFxqZpkkqldKZ30ajoZVCGo0G33DoLy8FsRjNX/olPvnsM9rtthZ9i0ajFIpFatVqN5E3MKCF8gzDwO/M17e2tkj291Ov1ag3GgxlMmxubhJxQuhej4diqYRlWfQnk7RaLYrFIlUnrKoE/JRgXDabxeV2E3GKoAzTZH5ujqGhIRYWFvD5fF3H3QnPrq2u4vF48Pl8rK2vMzE+roMnnU6HQDBIo17HlpJQKMTFixcf7xNevbpvXt2hNhD10FcqFS0uoKjUpVJJ9wBvtVpaKykYDBKJRMhms1qmRlW+JZNJ1tbWcDvlqolEQsf6Ac2MVREgKSW1Wk3H61WF3EuNDLpcuDMZLgwM6Lc5oKNZ6uXRGykSQlAul7cxZVUJrWmajDvXM+FErhRbV+WK1PWqKFVv/kTdP/WmtyyL1NmzWJbFoFPE1isTNO6cr2VZnHTC9WN8lf/oHambzSZGOIx4nJhGNApfR7KiBKampvRNO3HihE5KKb7PBx980F1fDd9SagVGpZZx6tQpXX2m9nXs2DEdqlRIOmWbO6dVwFdTCmefLxuqYvBRUNEpFU7duf1uo6AKByvsZ6RU09/H+XU7SxF61++NYj1PHFoDUeitClQ3XsXXVax95/rKSBR6t1PofePB3tq8Hbj8yGOwl/M9KNd2FMXaCxxnsPczPKSeY+e6j9vuUft6zH5eKg7CORwUPMW9OLQGIgGuXYN/+k/p9NQevFAKSLEIXi92j8DZS8ef/zkSqDvqhOqcVKZb0WTU6Kp4VmpK2nEU1tkRjQJn9HUiTL3X2lv7oVjViuem6DpqJFZT1l46um3bzzeMvr6O/PDDfW16aA0EgKkpGr/6q/zFX/xF1yGVkpHhYY7tpBM8L/yH/wBnz3K31WJ1dVU7wePj49uUVl4YpIR6ndbf/Jv8+V/+Ja1Wi1AoRCgUotlsanEGVRj22muvce3aNf2AK1G9gYEBOp0O5XKZoaEhlpeXNUvBNE2KxaJWe1ficor5K4TQmlj1ep12u60Jh7ZtU61WGR4eZmlpCZejvOLxePjggw+eH0Ph008RDtlxrzi0BiIAaVm4IxFOvfGGdrqDwSA10A9r7w+p3ppKBE0VWnk8HjqdjhYlexJIKcHtRni9DI2NEervp9FoUKvViA4MUHUc3xc6qkiJdLlwh8N88NFH2/Rp1SiheFiKgvLu4KCWGVWjyc7RYHx6GvjKf1P3Tvl56hpHnfJltVyJL6jAhYqaud1ups6f11FHl8uF2TPaPXM4bSD2g0NrIArtdptPP/2Uer2uhcJUQxylfXX//n2tqFGr1SgUClppsNFoaD7XL/zCL2ybljwpvvzyS+7fv49pmlSrVW7fvk0mk3mpiowul+sBWon63Dtl6l1n53X3Bib2+/D27n9nVKpXfumg4tAbiGEYZDIZLeP/+uuvU6/X9dtPycEEg0ESiYTuKCWE0OWjQghSqRTr6+sMOSIQe4EqNVUVdCqMfFDR+0A+6uF83g/uQTYMhcNtIFJiCsHrjl7sw3B6aurJ97mXyjMpwbbJpFJknFYK+97Xs4CU+pz2q2b+SuIpfodDayAS4PPPaS4t6RoCVTftdYbueqOBx1Fnt/bAYn3ioOC1a8jPPiPn+DVCCDrtttbjMp1oUK9SyHN9a0oJP/kJst2mUKng83oRzghZr9dBSgzTxGVZ4PgmTYcm03Iq/9qtFqZldXXFnHoShNDLBXxVJegc1rZtzJ4oou34em0nctZxWMRqmRCiy6Pqye77/P7n56RvbCB/8Rf3temhNRAAzp6l/NFHfPHFF4geUYBWq8Xm5qZ2RNPp9CP1r/aNP/xD5Llz3C+VyOfz9CeTZHM5YrFYtxjLcYwlXd7Yhx9++Hyzv47P0P7+97ly+TKVcplQOEw4FKJj25p75fV6MXqmlbl8Hss08ToFR0rIW/XYaDYaVGs1BDAwOMjiwgLBUIhWs6kNKzU4yOLSEh1HVHp9Y4NEPM5WNtuVIHKuu1qtEnO6TinBOKTkm++8s2styDPB5csIR7x7rzi0BiIAKQSRvj7GJie1/qsyEhVtUXykptNS7Vm9waWUYBgI0ySVyZAeGuoqb2QyFAoF3nAE15RPo0qCn/cIIg0Dl9fLex98oHMOKi/R+1nlQiZPnKDRaOiy5Z35nF5dLLXtqZ6oVi+OOy+hXn6VinjtZA4r9rCKdqnR47ncn6eg/hxaA1EoFot8/PHHWtCsVqtpwqJt25RKJcLhMMeOHXtAye+ZQEru3bvH5uYmQgitRq6c9aGhoWdWpLQXqF6EO5cp9EaoVBJvtyjWbg/uXqZCj+Klqe8OsrN+6A0kEonw3e9+V2dke99UxWKxS7F2kmDPBULw9ttv6zwMsO08nttxnxJP8lAeRbEOsYFIIWgVCsgf/ADoTrl2vtd6m8fbwP5SRY/A/DzU63D7dvecnMWi5+8zP+ZjIAsF+MEPEAe4bv5Fo7OxgbFPZsOhNRC8Xsx0+qnml0+NvYSPd0Gr1WJubg7LNHG53dRrNVxODYaicEgp6bTbxPr62Nra0iIT8XhcMwQMw6BWqwEgEwk8q6vYnQ6WI2nUbre7kSvA5/dTyOeRUjIwMEAul+u+yZ0Rr1fVJBAIUKvVGB4awuPIuB5GWAMDiLU1GBvb+7bP/nReDMSpU5jHjh1q1urm2hr/9uOPu2W9tk2z0eDim28ipWRuYYHp06e5fv06rWaTY5bFp59/Tr3RYHxsjLgzQti2zcb6OssrKyQSCVZXVhifmEDatu413mg0SKVS+Px+0pEIfzkzw+DgIH/9rbf4P/7ZP6PTbhN0pqLtVotGo0EgEMBTrTIzM8P//Ff/KkOZzEu+W88A+yBEHl5drFaLzh/+IfYLKJp5XlBEvnarRcOhvqgOuyozryr0FHUGulq6fr9fd2FSDTebzSYul4tGo6E5Zor+YhgGPp9P9130+Xz4/X5WV1e1/pWq1VdVh6VSCY/bTcBRVDzMMKtVxF/5K4idguSvrC7WnTu0y2WWy+WuaqLzANTqdS3QIKXEcKYPsViM1dVV3da50WjQajbxOurhuWwWv8N0bbfbeNxuDNMkl83i9njweb243G5qzsNWqVYJBgJUnZJbxWhdX1/H7nRoOlRv0zDweL3kcjndj12dV9t56IeHh5+qCtEfiz3y+50a9eGe/w89Ym4e2oMa4ezsLLVqFZcjSK3klZ4WKysrbG5uEggEcLvd+qWhwtaDg4OPPY6UEnt9HdOZPu4Fh9ZAaDbp/OIv4nG7qeXztKWk5fUS9HqRpRINR4K0VCoRiUTwJ5O4ymVq9Tq2x6Oz7w3DoNPXh1WtsuXUWgO0LYv+/n7KGxvd+grDoOVIj4ZCIYxikbphIKSk1mphezy0UymsYlF3bao76irecBhfrUbZySiXHNGDUChEuVyG48exnieb9TlDSolvcZFaNkvWud/m6ChWKPRU1ySlJJjLUVpZoeRIx6pRVI2sZibz2ON0Oh3sK1f2dS6H10DoRolSqVRX3v45ob+/f0/r9yr7veqQUmqJpaGhoX0RPXdC0fFVeDwWi21r0vOicagNROGwvnlfBahmnc+KR9XpdCgUCsTj8QPxuz524iuE+D0hxLoQ4nrPsj4hxA+FEHedvzFnuRBC/FMhxIwQ4nMhxPmebX7DWf+uEOI3ns/lHOGw46AFjZ5kBPmXwP8G/OueZb8F/Ccp5e8IIX7L+fz3gG8Dx51/bwP/HHhbCNEH/C/ARbr5tJ8JIf5YSpl7Fheh+lIo9XHltCltJ9UOQSsCCkE2myUQCOjqN5VPUHypQqGgOzP1TiV6dZ+USqOrJ98QjUbJZrO6H3gvDmvv9SdBNpvdVomoBPZUH49KpaIrHEOhkBbvU76g1+vdJj3UbrcpFAr4fD48Ho/O16iqUCml7gGvnHbFGFbi5M8CjzUQKeV/FUKM7Vj8XeBbzv//FfBndA3ku8C/lt3XwE+FEFEhRMpZ94dSyiyAEOKHwEfAv3nqK6Bb0Tc8PMyNGzcIhUJaCE6FPRU5ThnMm2++yccff4zf7yefz+NyuchkMuRyOa2vNTc3h8/nY3NzUwugqUYxLpeLd955h2vXrmFZFjMzM7rL0TvvvEOhUODzzz/XLZeh65u88847z+JyDyQWFxeZn5/X4nnVapWpqSnq9Tr9/f188sknxGIxbNtmenqaTz/9VDf0KZVKTE5ObmNct9ttfvrTn1Iqlfjwww9ZWVnB5XJx//59TYA8e/Ysy8vLNJtN5ufnkVIyMjLCh/sUaNgN+/VBBqSUK87/VwHVITEDLPSst+gse9jyByCE+D7wfei28noSRCIRhBBkMhldehsKhahWq1QqFYLBoO746vf7iUQiHDt2jEajoee6qkdfoVAgHA5r4QKfz6ejTZVKRbdAFk7oWAjBhQsXdO4imUxSrVbp6+vTte/PncX7kqFIjSdPntQNhwA9+sZiMd555x3q9TqGYdDf3883v/lNLVva39//ANVdSsnk5KRu4JlKpfB6vV0q/fq6vteq30gikSCZTD5z0b6ndtKllFII8cwmjlLK3wV+F7qJwifZZnh4GEA3vnkYeqMsD2P2qnUety/o9vrbDdMOHfxReFi9915kix7Xo2PnfP5R6+2ko+/lmEKIx16zapWm8Lj76/P5HlrD07uv561gs18DWRNCpKSUK84Uat1ZvgQM96w35Cxb4qspmVr+Z/s89gN4Fm9n9cNLKXUbN/VmVNT13nUfV3Ou1EEetW7vOgpq/v4k6J3z7/ccetcVQjx0PaWOAuh6G0B3tu19cz9s3d7vd/pju/2GB2HU3a+B/DHwG8DvOH//Y8/yvyuE+AO6TnrBMaI/Bf6hinYBvwz89v5Pezt6pWgUeh+83h9PN5d3/irnXEpJoVBgaWmJYrGoJXKUTFA0GiWdThMIBNjc3OTevXu7nodyItPpNJlMhmq1yhdffAF81WiytygpGAwyODhINBrFMAxWV1eZn5/fRp1/2LShr68Pv9/P4uKiFn5T56GmjaOjo5RKJW7duvXQEUUIQX9/P8lkkhs3buwaSfL5fJw5cwYpJdeuXdNNNXO5HNFodNvD7Ha7ee211zBNk5s3b1LZUc2nyg8CgQDJZFLnjg6CQezEYw1ECPFv6L79E0KIRbrRqN8B/p0Q4m8Bc8CvO6v/CfAdYAaoAr8JIKXMCiH+V+CSs94/UA77s8CtW7cIBoNcv35dS/mcPn2ara0tQqGQbjmsNJqUT5DJZPjTP/1TRkZGKJVK3L17l06nQ6PRYHJyUsvuqyaTZ86coVqtks/nWVpaIp1OUyqVME2TSCTC0tISjUaDRCJBOBzm3//7f4/f72dhYYFGo8GJEyeYn58nEomQSqW4ceMG1WpVt41Tfce3trYIBAIYhsH8/LxuW636lava+1QqRTAYJJvNUi6X9TSpVCrR19eHaZqsrKxQqVS4desWPp+PQqGwrVBJ9RhXDrTicanvFXqVK5vNpjaQRqOhG6KqbdSLYue6O6dyxWKRtbU1BgYGmJiYOJC1M08SxfobD/nqF3ZZVwJ/5yH7+T3g9/Z0dntAvV7XIV0V7jNNk3w+rzlY0HXoi8WirjgMhULk83kWFhZQiuGGYXDixAk2NzdptVosLy/rH9zj8eg2AeqYiviXTqd1Q0y3260fbEWREEIwMDCAbdvE43H6+/vZ3NykXq93+3I4RpJKpdjY2CAajbK1tbWN5q5aNff19XUbVLbbnDhxgps3b7K+vk7LkRzt7+/X7ZPr9bq+J6rdsypzVftQwYeTJ09SLBZZXl4GutWD4+Pjum/5zulcJBIhnU5vG+WUUN1ORKNRQqGQTgaqsLzqknv8+PHn8mw8DQ6eye4Dqsfge++9p5cJIRgeHtY/qBo9yuUyHo9Ht3Y+f/48d+/e1VpZhmEwMTHByZMnyeVyNJtN3n33XRYWFiiXy/T391MoFJBSEg6H8Xq9nDt3Tj+AvcefnJykVCpx5coV7c9861vf0sIN0WiU2dlZoFv2euHCBc2anZycxO12EwwGdWu4cDjMuXPnHpiKCCHwer36QYvH45w+fVq/rYvFIlevXtXncP78+QfEI9Q+BwYGMAxjm4Ekk8mHaufG43GOHTu2q0H0GpOKZqnIpGpFrY6zvr5OMpl8JgTHZ4lDbyBSSq5fv65Di0rVxDAMLl68yE9+8hNNF7csS8tdDg4OcuzYMS5fvszt27c1ZXx0dBTLsohGo/zwhz8kkUhw/PhxPvvsM/r6+iiVSty4cYPNzU3ef/99AJ30UlAPrPI1djqj6nNv+Fc51Opzr4hC73bKiHfeg92MZuc/tXy3QMB+k5itVkvT6RV2U3XceQ8sy2JsbEw3U7Vtm7W1tSMDedYQQnD8+PGunEwsRqFQ0D9+JBLhzTff1N2J1tfXdR9DNWWamJjQgspCCE6dOkUwGMTn8/HRRx9RrVa1I6nYwfF4XDvSjUaDq1evbjsn0zR5/fXXd5X4UXH7er3OysqKXh4KhV6IuEOn0+H69esP+BfT09MEAoE9729paYlKpbJtf0NDQ4w9pnpPGUkkEtFOvDKUg4RDbyDQ7UqrkNhRwzA6Ogp037JjY2MPOJNut5utrS29bHx8nNAu9Gn1ZpNSsra2Ri73FUtm54/6sDexbdv64Wy323o7r9e77dyeJ1RhVC92hpr3AsW+3RkpfFIo3wx2Dwm/bLwSBvKkN3VnQg6+mlqoz3t9g1mWxejo6LYHRHG6doPq06HOIRAIMDU1ta+3936gMtm9PDEV2dsPVCi59/r3Mk3q7ZN4ELlqr4SB1Gq1bTI76v+Kf6Watah8CXzVg0851+rtVS6Xd6U9PAyWZTE4OPhEdG8hBCMjI5TLZba2tvQUTfXPeBEwDIPR0dFdS2j383CGw2FSqdSeKR7qtyj1FKmpCOJBwqE3ECkln3zyCYVCgUgkolm9kUhES5AqAxgYGKBUKlEsFrl48SLDw8N4PJ5tXXFXV1d11KZ3ZKlWqxQKhYcWZ+32cO2WmOvv7yeVStFsNnVCcmZmRoeKXxSe9Zt6L/tT92VjY4NisaiXqyapBwmH3kCEEMTjcU0vb7fbmmioVBa9Xq+mjoRCIZLJpK5SUxEtVSarkmqjo6O6qUw2m2VhYUG/LXvR6XTI5XIPjCBer/ehOrxut5tjx47p6Fuj0eDu3btMT0/vidgoHeHndrv9QLvqer2OaZpPPHVSb/RWq/XANFCxkncL9VarVXK53AMh7t1G4Xq9Tj6f1/dsbW1NG0ssFiMejx856c8DQ0ND+qFQPc571TlM09RiCUqHtreZy8DAAIVCgfX1LqUsl8tRKBR0D71H8ZharRY3btx4YPnw8DDj4+MP3S4UCjE2NsbMzIymuczOzupk2ZMaycrKCvPz89vUHAuFAj/72c8YHBzcUyu4SqWiW7L1Xt/Vq1fx+/2cO3fugW1WV1cfCPO63W4uXLjwgJ+zurqqczW9oelgMLhr2+2DgFfCQBYWFigUClquf21tTbdDCIfDbG1tUavVNHdpaWmJDz74YFty8Pjx4zrZpvwWVeCjKBm9LNLe6dfj0OsT9WJwcJByuaz7G66vrxMMBkmn0w8IPT8MO4mI6liKS/a4c9i5r91yJKoe5mHn87jPO6HIjG63m2QySTqdfr5NPJ8Ch1YXS372GfVYDO/oKBsbG/qHVdVlwWCQTqej8yPKGVR1IYlEQtd1wFfz4kajQalUolaraadf1ZMorpASyX4UFAVFNcME9Hn1Rs7a7fY2Mp9pmtuiQPV6XYdl1Xe959z7/V7OYeeUcLdz6YVhGIRCIR3IUEa0sbFBPB5/YIqlQuXlcvmBEViRFd2OiqTaBtC+2bOsSVeqJq50Gnb6kK+qLlYvvvzySzweD7VajXA4jGEY3L17V3OC8vk8wWBQz3nb7Tbr6+tcuHBB70M9sDunXzshhHjsOr1vf5WV713eC5Us22mo6nx6fZndtvd6vQ9tzKPWV2TKR416vYm7R+2r9+FXU1ZFstx5jmrd3faz89gHFYfeQBS9fGVlRTN3fT5fVxXQeYhVZCubzeJyuTShcCee1Q/1sP08yVRkJyVjr9vvZf/P6runPaeDjENvIIpqcurUKR19cbvdTExMaOq2mvOqPuAul+uFhlSPcHhx6A1ESsnVq1d1qLVQKHDs2DGGhoa4c+eOrpuYm5sjnU7r2omf//mff4CWcoQj7MShNxAhur32BgYGaLVaWmihXC6TTqdpt9vEYjH6+/splUr4/X6klC+l69MRDh8OvYHAw8UTjnCEp8UrYSCHzfF7kXhU1OpZrP+q45UwkN6utr1xdRV/35l0U/kSlWlXIcudD0evaIMQQndfUslFtY0KAABafVF9r3IUqoiqlzCpakOgmxsIBAKaEaBEKHqPo65F5RB6C6jUftQytZ7K2ai8jmma+P1+3StEbdPLZq5UKrp7lWVZ+P1+Te7sXd+2bWq12gOZdBUy7lWzbDQa25KNvQVl6vpqtRqtVkv/PQh6Yq+Egfzwhz+kXC7Tbrd1tlx1vVWMUdV0JhgMUiwWuX//vhYtGxoa4urVqxhOr/Vms0m9XiebzRKPx3njjTdoNpt89tlnSCkZHR0lmUwyMzNDKBRifn6eYDCIZVl8+9vfZm5ujnA4zPLyMouLi7RaLXw+H9/73vdoNpt88sknSClZXFykWq3SbrcJh8N873vf46c//SkbGxtsbGzg8/mIxWK6g66qIzl37hzDw8Pcu3ePVqvFBx98wOXLl/H5fGxtbWnDGhsb49KlS6ysrOi+J+Pj44yNjeHz+Uin06RSKW0c2WyWubm5BwqXVB5ldHRUJwsByuUy169f141Se6HaOwwPDxMOh9nc3NTlxUIITp48SSKR2EZcvHv3ri4m8/v99O1sdvMS8EoYyPDw8La3pMfjIZ/PA92a6WQyydraGs1mE6/XSyKR6Da6cVQPO52OJjSq0lfLsujr6yMUCtHX10er1SIWi2njURytptMZSmWqt7a2MAyDbDbL5uamZhOrB7RcLuPz+bSMqdIAdrlcbG1taWqMouErLpmie6jjqg5SPp+PXC7H4OAgLpdLS69ms1lmZmYol8ta16uvr49gMKhHiZWVFV2Dvr6+rlVdlIGp0VYRNsvlMtPT01r0bTdKS+9ylRU/c+YMAwMDrK2taUbDwsICsVhME0yVdJFt20Sj0QPTRuKVMJC+vj7N1FXFSr16Umoakkwm9bTj/fff19OEtbU1MpmMfjDcbjeZTEYzW03TJJFIMDY2pqcuk5OTTE9PU6/XWVxc1FOper3O+fPnMQyDra0trYnldrvxeDz6rQ0wMzOjRQv6+voYGxtjbGyMYDCoqxyj0SjvvvvutusVoit7OjExsev9SKfTfP7557RaLU6ePInX62VkZETLeGazWX1c6NbTzM7OapqOIlJ6vV5KpRL379+n0WjQaDSYmZnh7NmzD0j0KLEL0zQplUqsrq5qdvDi4iJTU1OMjIxw8+ZNPaqvr69rBZdyuazv7dDQ0IEpnjr0BiKl5ObNbRdBBgAAIABJREFUmxQKhW1qftB9WCORCG+//TZXrlyh1Wrh9XrJ5/O8//77uqXX8vIy9+/fxzAMYrEYjUaDtbU1pqenmZ2dRUrJBx98AHw1x1fau9Cdt9+/fx/4SsBBzb93y37vpHz0zu13LgsEAgwODj5ARdm5fu/9WF1d1Q+7ZVmcOnVqG/08GAx2G36uriKEYH19XRu4ZVmcPHlSF3ApDppiLJfLZXK53AO1G+qeeL1e+vv76XQ6rK2tAV2WcKfTIR6Pk0gk2NjYALqC1+FwmKWlJb2PVCr10DKBl4FDbyBCCE6cOKGnVsvLy3rkCIVCBAIBLfqmpipSShKJRLcXocfDmTNntjW/HB8fZ2pqilqtpgWRHyVqppxMlbF/llVxtVpNjyYKijO1GzqdDnmnzbMaadS6vQbl9/s1HV9NR1UdhzIOZcjRaBS/36+nkfl8/pHFTUKIbezc3iDJyMgIuVxOO+O3b9+mWq3q8uNMJvNYIuiLxKE3EOjWJKiIS6PR0KWblUpFFyNNTEywvLxMtVolEAjo2g/lXGezWWq1GmNjY2QymQdaf/WKNEgpdb+LcrnMysqKfviUouGzQi6X23Zs6E67zp49u+v6au6vzmc34+j9rJQkFRSTuHdUM01TJ1+FEA99gNWLotFo6FYS0DVG0zQRQhAIBEin08zPzwNoo1OlwEo18qDg0BuIelht29ZFTkopQ7U7SCaThMNhvvjiC5rNpv7xLMsin8/riJWS3lTYbVoDX0nn7PyuVxjtWWIvc/GdGsWPk/PsDTsDDzVu9YDvdgzo3pM7d+4A3VFPGamq2OxFJpNhc3OTarWql/X19RGPxx8rsv2icegNRIhufw41HVAxefXjqB/csizeeustLbVZrVZ1bL/RaHDt2rWvOt82GloIQlFS1EOh/vaKXgshiEajWt1DTePa7TbNZlNXJqpcgNqnyoM8qiYnkUg80BzzUQ+9inypB01Jlj7q/vXq7u5cX51b74Pbayy9KBQKehvl/4yMjGwL16p7Ojw8zO3bt/Uy5ZgfGcgzhhJtUBETwzB0daGaU+dyOaanp1lcXOSdd95hbW2NbDZLp9PRGrgqonLlyhWq1Sp37tzR9PlarcbExAT5fJ5r167h9XoZGhqi2WzqY9m2ze3bt/nOd77Dxx9/DHRDvmtra/T19WldXNXUJ5FI8Od//ufAV474blAav086iqg6dGV4hUJBVyj27kNNh1TNvnohqNJk2D4NU36CEOKhTnQ4HNY+WCAQIJFIPDBlU1DFamqfB7Wi8NAbCHTfsqVSiUwmQz6f1yqJylgSiQSpVErPd1XES4iufq+qoiuXy8RiMcLhsJ4G/P/tnXmMHNed3z+/vqrPme65yTlIzpAiTYqMNKIoWeu1vTlsWdiFYgQwnBixsruA84cNJMAGiDb7R4wsFtgE2Q1214YBLyzEDjYWFsh6LQR2HNk5tIEsWdRKoniax8yQc99H311VL390vcea4UxrZnjMDFkfYNDdr6qrXvXUr957v/d7v6/O1qi7ay0tLSQSCXp6eohEIgwNDRkJgHg8jm3bdHR0mC7G0tKSmSHXEnDJZJJarca+ffsol8vkcrmGC7Bg8wuNwuEw2WzWdF/m5+dZWFgwSa81euw0MDBALpczA/vFxUVWVlaMSxhgdnbWGBCwriyzVphaz3h2g7t2u+x5AxGpZzVJpVKkUilyuZxJUJ1KpThy5Ij5B3V21pXinnnmmVXHcF2X9957j3w+Tzqd5uDBgxw4cGCVetHMzAyXLl3ixIkTRKNRnnrqKSzL4uTJk5w/f96MXUZGRjhx4oSZeMzlcmbQGY/H6e3tJRqNMjs7a1oe7W1aj5WVFZO82n/N7e3tq7IS+tFzC1ov8PLly3R3d9Pc3IxSioWFhVUZ7zs6OpiYmKBcLmPbNleuXKGvr88sPNNJIaA+6N9oEm89d/VeZ88biFKKoaEhurq6uHjxolGmtW2bffv2GR3BRujWZiNPjx7Q+8v0fEYqlWJgYIDLly/jOA6FQoGhoSGOHj1KNBqlr6+Pq1ev4rou+XyeS5curYo/0saxUVjFysqKSUnkr5fOLL8eqVSK/v5+rl27ZsZBw8PDdzgd/CsuDx8+zJUrV1a5X/3zNTp+SmcfeVTY8wai43r0eEOn+GlqajKrBv2BfhsZiz/g0D9o9X9Pb9eventrayvd3d1mdnphYYHx8XG6u7vp6OgwoRVaD8Pf725ra6Ovr2/Vmm4tn9zomv3nX4/Ozk4sy+LmzZusrKysynurE1H4dT1aWlo4ceIEIyMjJqGdf/9cLmdiuPz10EGJWxW/0d/V46Ddyp43EKUUt27dwrZtE8DX0dFhhHNCoRCzs7P09/dz7tw5ent7zQ0YDocplUpmJWIymcSyLJaXlykWi0xOTlIulxkfH6ezs5OmpiaTWmh0dNTc6FpOWkcTa0/Sm2++yYkTJ0z4RbFYpFarmUQG+ik/Pj5OS0sL+XyeWq3GwMAAc3NzpNNpM6mmQ2dyuRwzMzO89dZbJjJXh9m4rktHRwf79+8H6vMlzc3NlMtlEz8WDoeJx+Orume6pWhqauLxxx83++u5Ja1C5Y8M0Oc8deoUra2tW0pSB/X5lsHBQXP+3bqAbc8bCGBkCd59910SiQTj4+OEw2GKxSIHDx5kbm6OQ4cO0dLSwvDwsPFsua7L8vIy/f39JtOfXoabzWZZWFgwQXXXr183ilBNTU1MTEyYp+bAwICZQEskEhSLRRMGrjXUdWCkDkFJJBKUSqVVWn/azbq8vGzqr7O1lMtlo2wVj8epVqtkMhkj1+a6LqlUapWbVt/QiURiQ8GctZ+3ur+OMdtKt0vXa6Mu4m5izxuIngcB7hDI1M23fhLqGCF/F0o/VR3HWRUnFQ6H2bdvn1F00vvpc+jvQ717tn//fqPqpMczBw4cMMdaT644EomYcA89p6Ld1TrDov6+rt961+9fL7JeV2erg+aHaZB9t+x5A4GPni32P9026u82mkHezH7r+fHX6vatx3pdi/WO9SgNjHcTu3d0FBCwCwgMJCCgAR9pICLyiohMi8h5X9nXRWRMRN73/l7wbftdEbkmIldE5LO+8ue9smsi8vK9v5SAgI1RSrGdLNSbGYP8Z+AbwPfWlP8npdR/9BeIyHHgi8AJYD/wUxF5zNv8TeAfAKPAOyLymlLqTt2AbdBoPuBhIBg0bx+lVF0CfJv3yEcaiFLqDRE5uMnjvQi8qpSqAEMicg044227ppS6ASAir3r73pWBlCsV5sfHSSaTJnK3VqsZDRDHcYx/Xs9f6Jgi/+pD/V7n9fVHq2ovks58rucbdECgPwS8Uqlg27YJ6bBt26wt92cd0dtc1zXrxbVue6lUMtG/D1p16mHDvz4ls815lrvxYn1NRL4MnAV+Rym1AHQDb/n2GfXKAG6tKV8dEOUhIl8BvgJ85NqKpaUlrt26ZW7CTCbD9PQ0qVTKhLHruKWpqSna29uZmJggkUiYYMK2tjbm5+fp6ekxksb6WK2trUxMTNDV1cX09LS5ubUQ5tjYGJVKxUgt6NlnLemcTCYpFAqkUimGh4dNkKKeQdZG0dbWxtzcHB0dHczPzwMYpawjR47s6hZS/yb3Uvhmret6u+hlDalUCgmF2E47vF0D+Rbw+4DyXv8I+K1tHmsVSqlvA9+Guj5Io327urroPHnSrKvQcw/+GCLdAug1FesZXV9fnzEk/zyHiJgEC3p22k9nZ+e6oRL+hBH+fRuFVPQpRWhsjAOhEOjzT0xQ9RSZNovjulRPnEB8ruJ73UXTBuFX7/Jj27Z5CPjP3yjUx08oFDLhMf7sKnrbZo6j62dZVl07xnEIwZaNZFsGopSa0u9F5M+B/+59HAN6fbv2eGU0KN82lmVRcBxqtRoXLlwwXZdQKEQikTAzzbpLZds2x44d2xX5ltYi4+P8rW2zUqmQTCbvkDDbLMU33ySUzzPtOExOTpJIJHjyySfvaV21aM/8/DyLi4vmAWVZFu3t7USjUbLZLENDQ0Y9y3EcYrEYZ86c2bTBzs/Pk0qlqFarXL16lfn5eRKJBNlsluPHj2+6vlpcaTsu220ZiIjsU0pNeB8/D2gP12vAfxWRP6Y+SD8C/IK64R4RkUPUDeOLwD/Zzrn9lMtlJJ0mm80yODhIsVhkcXHRqBOFw2GT1LpUKmFZ1iqFp92EikQ4dvo0eW8FYqilBdlOEJ/Xvdy3b59RfrrX16uP2dXVRSqVMqs0lVJmTXkoFKK3t5eOjg4WFhaIxWJGUWozddGtRCgUIplMmiUIOjnHVq/JZeutB2zCQETk+8CngTYRGQX+LfBpEXmCehdrGPjnAEqpCyLyl9QH3zbwVaWU4x3na8BPgDDwilLqwjbquwrbtkl7g1idHnMvSxqkUilSG6wL2dax7rP2+noxW4BZ/2JZFrFY7A6Vqa0SCoVW6UM+SDbjxfrH6xR/p8H+fwD8wTrlPwJ+tKXafQRhX2K4h4V7dS0P4jdZ7xxrB9b3oh47+f/d0zPpD5NhBOxO9rSBBATcbwIDCQhoQGAgAQENCAwkIKABgYEEBDQgMJCAgAYEBhIQ0IDAQAICGhAYSEBAAwIDCQhoQGAgAQENCAwkIKABgYEEBDQgMJCAgAYEBhIQ0IDAQAICGhAYSEBAAwIDCQhowEMhf7CbE6ttmXt0LQ/iN/moc9yrOtyz4/CA8mLtCpQi/M47MDQEYJKXiQhC/Ud1XJeQCOFIBMe2wUtA5joO4UiEaDSKiJisiNFIBAmFqFYqRKNRXNetH8OXOkdECIdChD1NEiO8AyZNjz/JmUaXrU2iZtbVf/ghvPce6m50QJRieXSU4pe/THFqasM1++sltrvzUOoOEU9NrVYzKV79+2qWl5fvuPa1wkabySewsrJCtVpdlR/MX6+1x/CX+XXglVI02/a2bvY9bSDRQgF+4zcAmLx+nZGRERKJBIVCwWRJnJ6exhKhUK3S3tZGT28vly5dolKpMNDXx/T0NAooVquk43FaWltNHt5arVbP1xuP47guzc3NQD0TY0dHBwBz09OMjo6yMD9POpOhJZdjdm6OWCxGuVwmEg7T2trKzOwsSilKpRLRaJRyqcSTg4O0t7fXr+fjH7/738RxWPrOd7h26xaJ2VmT3dB1XQYGBpiZmSEajTI1NUUulyMej5v0rDqXVaVSWaVW5TgO8XicUChEc3Mz09PTJgmcUopyuUy1WqWpqYl0Os3S0hIiwtTUFOl02iSP1snlYrEYxWKReDxOPB6np6eH4eHhVUn+/KpfWtZbJ5/LZrOsrKxQKBSwLIve3l5u3bpl9BuLxSLVatW8av363DaFQvesgQjUn7aelHFzRwcHvITVXV6i4ng8Tlt3N47jUC6X68mhXZcDjz1GOp2mWCzS7ekHWpa1SvV17ZPK/3TyP7ncaJSjp06xsrJiEmV39PWZ3LtQzx/V4aU3LZVKJvl1U1MTeK3YPcG2SaRSHDt2zOg2JpNJIpEItm2TyWRIJBI0NTWZJ7rjONi2TSKRIOK1qvl83oiDatHRubk52traEBFqtZpJ61kqlUwC7ng8TiaToVqtEo/HzTmSySTFYpFKpYLjOHR2dhKJRLh+/TrVapXe3l6q1Sr5fJ5IJEIqlTJ6jCJCPp+ntbUV13VpaWkhk8lg2zYiQjqdpru7G/EkuQuFApFIhEqlYpKGNzU1IZOTDzQ3765jcXGRhYUF4vE4c3NzOI5DR0cHoVCIUqlkblh9E+unkhbKdBwH2FiibT200dy8eZORkRGSySTlcpl0Oo2IUK1WjcTamTNnbhvFfaRarTI5McHS0pK5iXt6ejh//ryRa47FYlSrVZRS9Pf388tf/tLoOMZiMbLZLGNjY/WWrlxm//79zM3NMTY2Rl9fH+Pj4yYXcm9vLzMzM0a0VOs1FgoF4vE4y8vLuK5rcu26rkt/f79J6j05OUk+nzcPE4DZ2Vksy6K7u5uxsTF6vVY/FAoxOjrKkSNHGBkZMa2KbnWi0SgHDhzg5s2b9Pb2MjIyQj6fp7m5mfZ4/BEbg6yhv7+fy5cv89hjjzE+Pm4yrefzeaMy67quybCeTqdvd2/uAqWU0TtPp9NGQlk//dLpNPPz8w8sh1c0GqW3t5c+rxVTSpFKpTh16pQxVp0U2rZtUqkUJ0+eNN/Xde7s7AQweY67uroolUokk0mTPb9UKtHU1EQ2mzWtbKVSIZvNsry8bLpxruvS2dlpFHrD4TBdXV3E43EKhUJ9/OelLNUPK90q6a6bvyXU549Go0bSQrcyqVTKdKsSiYRpJcXTsN8qe9ZA1vNrLC4usrKywtDQEPl8nlgsZvq+tVrN/OOi0ShPP/30+sfdosdERBgYGNhw+9qs5PebUqnE0MWLFAoFmpqaWF5eRkSwLIuuri6jG18sFjl06BAffPAB4XCYgYEBrl69ajRNtNruwYMHmZ2dxbZto51uWRbPPfcclUqF4eFhZmZmSKVSrKys0NXVRT6f58qVKyQSCUKhkGlJn3vuuTsSh39UelQ97lu732ZaYp3y1HVd3ImJR7CLdf48fPObABRXVjjuOMTffJPTnlcqZlko1yWfz9d/YBFsb8AYv3QJOxo1Xio8r1elXMaKx4mEw/VkzOsozhqUIjM2Rrm1td5ihEL1AWYoZPQoarVa3ZsiQigcxq7V6t28RsfdLq5LU7HIJz/5SdNH93uQYrEYImISTftlqC3LoqWlpZ7v2Osiioh5aoe8a9OtUjqdpq2tzcg6RCIRk+FdKcXhw4dNK14ul0kmk2QymT2XDXNvG8jRo/CFL4BSXHrnHRaXloznKJVOE7csLMtibGyMSDRKyNMAmZ6eplypcOjgQRKJBNPT01SqVZLJJIl4nNm5OaKRCL19fRzwBtfroVyX5De+wblnn2VkdJREPG7EerQu++zcHOlUionJSSyv73/8+PGGrc52UY5D6K//2nRBNoNOPq2UMt0q2Hxa12w227hOSplWYK8ZB+xhAxFARaPgNb09x47RWavVJRG8/mk2m0UpRbanB9u26enpYXx8nK7Dh+vGkEiglKLP05rQcx26K+S6LkSjRtDmDhwHLIueo0fJean5AVr6+rAsq65lsbSEUoqPPf00c3NzpFIpwuEwags38aZ/E9uGbboz79fNuxeNws+eNZC1LC0tcePGDeOp0b557cbUY5GhoSEymQy9vb1GjepuKZfLvP/++0SjUdMXz2QyxGIx4/7t6uoyEm+WZfH888/fg6sOuN88NAaSTqd58sknzYA8Ho/T1NSE641BHMehu7vbCL5oj8694sSJE8YIe3p6SCaTxONxZmdncV2X3t5eEokEqVTq4QqNecjZswaiAFwXbBuAnq6uDfdt1h4Qpej1NAcB891t47rgOOzv6IANQkSafd6Xg55O4j0593rY9j2L5Qqos2cNBKh7sf7szwDM7C5K3Y6Jchzw4qRCnkS0iBDx3czGi6U9PngxVUpR1ftrT44n61bTIpWui0xO4v7Jn2A7jvFe4ZOOjkQiOK6Lct16169WM27UcCiEqxTKdUGEkEjdE+Y4uD6hzE23dp7BBtw79raBnDoFX/oSiHD1wgVu3rxJPB43Es/aYwWYEIv5+Xlqto3juTOz2SyTk5NkMhkikQjz8/NEYzEy6TSZTIZKpVL3jEUizM7OGqnmarWKbdskBwdJp9OMjY2xf/9+SqWSOa+e+MpmsxSLRTKZDPl8vq7V7hmS9h7dunWLeDxOS0sLy8vLtLa2Mjk5STgc5ld/9VeJbMZIbBteffU+/+iPFnvWQASvm+UNsg8fOcJBz6eviUQiHD12bJUgpA5P0LPCSin6BwbqniWf3nc4HDYBc/qzDmvQ/n247fl6/ORJE9wXCoU4eOiQiVtSSplZXT2j7480jUajHD5yxJxHB+v1DwzU30cim3Mm7HGP0W5kzxqIHz1TbHmBi5shnU7fxxptndg6E4dbuZ6A+8NDYSABO8O98Mb5W8b7IQB6t3zkrJKI9IrI/xaRiyJyQUT+hVfeIiKvi8hV7zXnlYuI/KmIXBORcyIy6DvWS97+V0XkpbupuP+n1OEPj/zf3fygW/39ve6o7pICpuvp76pq9Ge9XUf2rr0GHQazW9hMC2IDv6OU+lsRyQDvisjrwD8DfqaU+kMReRl4GfjXwOeAI97fM8C3gGdEpIW6xvpp6vf3uyLymlJqYVs1F6EwNUXtBz/Y1tcfSlwXu1Z7YKe7cuUKExMTxiuXTqcpFAp0dnaysLBgonu7u7u5deuWGb9ZlkUymaRSqRAOh80SAT2h+/jjj5vwlJ1mMzrpE8CE935FRC4B3cCLwKe93b4L/B/qBvIi8D1Vfwy8JSJZEdnn7fu6UmoewDOy54Hvb6vmIqhf/3US+/dv6+sPK+n7EQS5AQcOHDCLsADjQYzH47S2thKLxcyKRL3gCerOk7Dndg+FQhSLRZLJpAmITCaTD+waPootjUFE5CDwJPA20OkZD8AkoCPduoFbvq+NemUbla89x1eAr0B9aWvDysfjWHswQvRhQK8UXHszp1IpUIp4PIGIi+7FayNaj48KeNxJNh3ZJiJp4L8B/1Iptezf5rUW96TjqJT6tlLqtFLq9L1Y0BRw/1iVdMKHrRxWymVc77bQ+231bzewKQMRkSh14/gLpdRfecVTXtcJ73XaKx8Den1f7/HKNioPeEhQQM1xePv8MD/+v2ep2LU9H/qyGS+WAN8BLiml/ti36TVAe6JeAn7oK/+y5816FljyumI/AT4jIjnP4/UZryzgoUChXIfJuWUm5/O0tGZRSkD2dt6yzYxBfgX4p8CHIvK+V/ZvgD8E/lJEfhsYAb7gbfsR8AJwDSgCvwmglJoXkd8H3vH2+3d6wB6wh/HufVs5KMfl5x8OM3i8j6GJKaISRnE7T9lu6TZthc14sf4fGyeD+Hvr7K+Ar25wrFeAV7ZSwYDdib9VUEqh3BrXJ5dJJy2qboVzt+Y42punt63Z3D170UiC3LwBd4kDKGp2iF9cGOXkY/v42dmbdGQyjC8sMJsvULWrwO2Jwr1EYCABd4F306O4cGOKA5055hYLTK/U2JdLEgnHuHh1nOVC6c4WZ4O/3UYQixVwB+Y29d2wwp1+fJd6CMlCvsSFq+P83ef6ee3nwwx0ZxFxOdnXTjTchU4b7e9ibRR3tdvisQIDCVgHtfqteG2FAkGBKO+zS81x+NnbN3jmiYN8eHWG2YpNKlnmicMHICQ4KEQpOPcB7nIehUIpcBzXi86vm14kHCYSEtRTg0jcQgjtuHFAYCCPBOryZZzR0W2sF1Gg6sag9I2O1G9yFMqBofEluhZWiE6lWDo/RmapwLG/c5ClxZtUYnHKxRKlYhn58BwTqSbKlQqJRIpwKEQ8GQOEStXBtSt0KZf4tWGa2ptJWQkiIWHryUJXE1IKjh3b9vcDA3kEsMfGWBwZQW0xJZBSClcparZLuVqhVrMpV2uIlYBQmNHRaZYWCxw80M7P37jIwnSRT5zuJ1NahIk8IStKUiAFyPHHaFWu1yp4hhYKIXK7vXIRVorLXD0/TWsmTnMywd0aSCYSIebL97VVAgN5BIj+2q/R5oWXz87O0tLSQjgcNgmj9WKtcqlEJBqtLztOJjg3NM1KpUI0apGxonRkkrTEI6zk84TTad76mw/4R586xa35ApFr03zpE0dJx0IU/uqHzCyscHN+mXLNxXUUgiIcEloyGbJNaTJOmdgLz2MnUoTCESLhECEltIegYtuMzC2Q29dFtVwGbsdyLS8v4zoOiWSSpaUlWlpaKBQKJnNktVqlubn5tlmJ4IjA+++v/Vk2RWAgjwJeUorCygo/f+cdk5B6eXkZy7KM/EOpVOKpp57i7bd/Tirbyk/f/JCPDXTTnokzL4qZWo2nzzzDT372OqPzZQ71tPLDH/8vro/P8Pd/5RSv/eh1JmYWODozQWlyglAkQiKZIOUlDK9UqoyNTeA60Nqc5O2xv6AcjnD6zNOszE+RScUR5VB1XBaLZeYO9tYzXc7OAjA4OMgbb7xBsVhkcHCQs2fP8txzz3Hx4kUcxyGTydDa2sqpU6dWr9D0lk0/0tndAz4ay7I4fPiwWQvf1dWFUvXs9IlEgqWlJXK5HMc+dhwUfOnzbVRqCrtQ1xmJWTFuTC5Rttr57Ke72dfSxA/+x99wsLeL0ZklevoH+PizWcrLi+RyLZRKZWq1Gjdu3ODosaNUKxUikQggZLPNdM4tslIokki3MB6JMbswj1AjlWrmRF8/3W3NZLNZcrkcAK2trXzqU5+iXC6zvLzME088QXt7O88++6zRXbFt+w5FqrtxIctu9D1rTp8+rc6ePbvuNvXee5RzOeL3KDvio8DW/tcuCoWrBFG3s9NPzC8hEUV7Ok1IXPLlGjfHpkhZUSKiCIUj9czw1Rpxy8JVdcm7aCxCtWqTTKY8cZswtlsjk0rS3JwDXG9WJQy4hFCEJLrlR752JfvdxuVymfCFC0S7uxF/XjSAyUlk3753lVKn1zte0II8Qmz+QaJQqp6dPuxzJIkI+1tXr91oSlrkkkvMzMwQi8UYHR01i6MikQjNzVmWl5bIteSYnZ0jm3UoFApmeW24q4tcLgyEfbPWt99t9eG3do2767r1NLTbzKS5pw3E8ZrUgJ2ls7PTZIY/cuTIOjd1fZVDd/cd6+MA7tv/UKeC1Yu6Hjl9kOiNGzhzcztdjYBdSjgUIh6J1LNr3rwJ23D37lkDkePHsQLjCNgs7e31vy2yZw0Ey4IgYUPAfSaI5g0IaEBgIAEBDQgMJCCgAYGBBAQ0IDCQgIAGBAYSENCAwEACAhoQGEhAQAMCAwkIaEBgIAEBDdjdoSa1GkxO7nQtAh5mZmYabt7VC6ZEZAW4stP12CZtwOxOV2Ib7NV6w/brfkAptW4k4+5uQeDKRiu9djsicnYv1n2v1hvuT931v3XPAAAC10lEQVSDMUhAQAMCAwkIaMBuN5Bv73QF7oK9Wve9Wm+4D3Xf1YP0gICdZre3IAEBO0pgIAEBDdi1BiIiz4vIFRG5JiIv73R91iIiwyLyoYi8LyJnvbIWEXldRK56rzmvXETkT71rOScigw+4rq+IyLSInPeVbbmuIvKSt/9VEXlpvXM9gHp/XUTGvN/9fRF5wbftd716XxGRz/rKt38vNVL72ak/6un1rgP9QAz4ADi+0/VaU8dhoG1N2X8AXvbevwz8e+/9C8CPqadmehZ4+wHX9ZPAIHB+u3UFWoAb3mvOe5/bgXp/HfhX6+x73LtPLOCQd/+E7/Ze2q0tyBngmlLqhlKqCrwKvLjDddoMLwLf9d5/F/iHvvLvqTpvAVmtMf8gUEq9AaxVFN5qXT8LvK6UmldKLQCvA8/vQL034kXgVaVURSk1RF1l+Qx3eS/tVgPpBm75Po96ZbsJBfxPEXlXRL7ilXWquiY8wCSgM5XtxuvZal130zV8zev+vaK7htyneu9WA9kLfEIpNQh8DviqiHzSv1HV2/094UPfS3UFvgUMAE8AE8Af3c+T7VYDGUMndK3T45XtGpRSY97rNPAD6k35lO46ea/T3u678Xq2WtddcQ1KqSmllKOUcoE/p/6706B+d1Xv3Wog7wBHROSQiMSALwKv7XCdDCKSEpGMfg98BjhPvY7au/MS8EPv/WvAlz0P0bPAkq97s1Nsta4/AT4jIjmvW/MZr+yBsmbs9nnqvzvU6/1FEbFE5BBwBPgFd3svPUhvyhY9GC8Av6Tugfi9na7Pmrr1U/eGfABc0PUDWoGfAVeBnwItXrkA3/Su5UPg9AOu7/epd0dq1Pvgv72dugK/RX3wew34zR2q93/x6nXOu9H3+fb/Pa/eV4DP3Yt7KQg1CQhowG7tYgUE7AoCAwkIaEBgIAEBDQgMJCCgAYGBBAQ0IDCQgIAGBAYSENCA/w8tGkijQAOiSAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R-DZZpE_qU_S",
        "outputId": "b170e5fe-8e63-4d9b-afa4-17b5eaf3dd6a"
      },
      "source": [
        "print(dict2)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                                        notify party                                          consignee\n",
            "0  Hacarem - Spirits Ltd  Derech Hahoresh 10  Hev...   Hacarem - Spirits Ltd Derech Hahoresh 10  Hev...\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}