notebooks/TrainVectorWithYOLOv9.ipynb

{
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  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hiamitabha/course/blob/master/notebooks/TrainVectorWithYOLOv9.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# How to Train YOLOv9 on an Anki Vector Dataset (Adapted from Roboflow tutorial)\n",
        "---\n",
        "\n",
        "[![GitHub](https://badges.aleen42.com/src/github.svg)](https://github.com/WongKinYiu/yolov9)\n",
        "[![arXiv](https://img.shields.io/badge/arXiv-2402.13616-b31b1b.svg)](https://arxiv.org/pdf/2402.13616.pdf)"
      ],
      "metadata": {
        "id": "DQjdUKvQigN2"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Before you start\n",
        "\n",
        "Let's make sure that we have access to GPU. We can use `nvidia-smi` command to do that. In case of any problems navigate to `Edit` -> `Notebook settings` -> `Hardware accelerator`, set it to `GPU`, and then click `Save`."
      ],
      "metadata": {
        "id": "m09A8n4djDwY"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_5hX88yficL7",
        "outputId": "449ef26c-1d25-41d6-c838-3fcd4634ed40"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Wed Mar  6 01:53:32 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
            "|-----------------------------------------+----------------------+----------------------+\n",
            "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                                         |                      |               MIG M. |\n",
            "|=========================================+======================+======================|\n",
            "|   0  Tesla T4                       Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   56C    P8              10W /  70W |      0MiB / 15360MiB |      0%      Default |\n",
            "|                                         |                      |                  N/A |\n",
            "+-----------------------------------------+----------------------+----------------------+\n",
            "                                                                                         \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| Processes:                                                                            |\n",
            "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
            "|        ID   ID                                                             Usage      |\n",
            "|=======================================================================================|\n",
            "|  No running processes found                                                           |\n",
            "+---------------------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** To make it easier for us to manage datasets, images and models we create a `HOME` constant."
      ],
      "metadata": {
        "id": "UTprsNjHja4l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "HOME = os.getcwd()\n",
        "print(HOME)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rowKDIT-jJ9k",
        "outputId": "e058ebbd-5bfb-4adc-dbc6-0da8de361138"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Clone and Install"
      ],
      "metadata": {
        "id": "qWRGGT7Zjjbq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** YOLOv9 is very new. At the moment, we recommend using a fork of the main repository. The `detect.py` script contains a bug that prevents inference. This bug is patched in the fork."
      ],
      "metadata": {
        "id": "9WyY-fboBLZB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/SkalskiP/yolov9.git\n",
        "%cd yolov9\n",
        "!pip install -r requirements.txt -q"
      ],
      "metadata": {
        "id": "pixgo4qnjdoU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "20f13abb-2376-4eeb-e6d9-29978f4b3f27"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'yolov9'...\n",
            "remote: Enumerating objects: 147, done.\u001b[K\n",
            "remote: Total 147 (delta 0), reused 0 (delta 0), pack-reused 147\u001b[K\n",
            "Receiving objects: 100% (147/147), 607.53 KiB | 15.58 MiB/s, done.\n",
            "Resolving deltas: 100% (58/58), done.\n",
            "/content/yolov9\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m195.4/195.4 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** Let's install the [`roboflow`](https://pypi.org/project/roboflow) package, which we will use to download our dataset from [Roboflow Universe](https://universe.roboflow.com/)."
      ],
      "metadata": {
        "id": "bcx7KoNzqpgz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q roboflow"
      ],
      "metadata": {
        "id": "TPGqlohQqgAO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ab5386d2-c655-428b-8410-d828643c5577"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/70.2 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m70.2/70.2 kB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.5/54.5 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Download model weights"
      ],
      "metadata": {
        "id": "X8oLIkX2l2P0"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** In the YOLOv9 paper, versions `yolov9-s` and `yolov9-m` are also mentioned, but the weights for these models are not yet available in the YOLOv9 [repository](https://github.com/WongKinYiu/yolov9)."
      ],
      "metadata": {
        "id": "0FieRuZnB4wH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-c.pt\n",
        "!wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-e.pt\n",
        "!wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-c.pt\n",
        "!wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-e.pt"
      ],
      "metadata": {
        "id": "h7j3aUE7l1Je"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!ls -la {HOME}/weights"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Au6np1JS8eRB",
        "outputId": "eb58fc71-356c-4c81-cc99-51baeca6ddd8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 402444\n",
            "drwxr-xr-x 2 root root      4096 Mar  6 01:55 .\n",
            "drwxr-xr-x 1 root root      4096 Mar  6 01:55 ..\n",
            "-rw-r--r-- 1 root root  51508261 Feb 18 12:36 gelan-c.pt\n",
            "-rw-r--r-- 1 root root 117203713 Feb 18 12:36 gelan-e.pt\n",
            "-rw-r--r-- 1 root root 103153312 Feb 18 12:36 yolov9-c.pt\n",
            "-rw-r--r-- 1 root root 140217688 Feb 18 12:36 yolov9-e.pt\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Authenticate and Download the Dataset"
      ],
      "metadata": {
        "id": "D7fZKrxsq_td"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** The dataset must be saved inside the `{HOME}/yolov9` directory, otherwise, the training will not succeed."
      ],
      "metadata": {
        "id": "J5yx2GkI2P7Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd {HOME}/yolov9"
      ],
      "metadata": {
        "id": "MyLpftfU2Q1U",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2e67cd9d-1c7c-4eb3-9ec0-1bc5e0d81553"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/yolov9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** In this tutorial, I will use the [football-players-detection](https://universe.roboflow.com/roboflow-jvuqo/football-players-detection-3zvbc) dataset. Feel free to replace it with your dataset in YOLO format or use another dataset available on [Roboflow Universe](https://universe.roboflow.com). Additionally, if you plan to deploy your model to Roboflow after training, make sure you are the owner of the dataset and that no model is associated with the version of the dataset you are going to training on."
      ],
      "metadata": {
        "id": "eosmGt89vMO1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install roboflow\n",
        "\n",
        "from roboflow import Roboflow\n",
        "rf = Roboflow(api_key=\"Xzg2wL8vamx2wO42BYTQ\")\n",
        "project = rf.workspace(\"vectorstuff\").project(\"vectorcompletedataset\")\n",
        "version = project.version(8)\n",
        "dataset = version.download(\"yolov9\")"
      ],
      "metadata": {
        "id": "4J3s_2_7p_gn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7a87f9fc-2017-4924-8020-d71a94e1b26f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting roboflow\n",
            "  Downloading roboflow-1.1.21-py3-none-any.whl (70 kB)\n",
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            "  Downloading opencv_python_headless-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (49.1 MB)\n",
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            "Collecting requests-toolbelt (from roboflow)\n",
            "  Downloading requests_toolbelt-1.0.0-py2.py3-none-any.whl (54 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.5/54.5 kB\u001b[0m \u001b[31m7.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting python-magic (from roboflow)\n",
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            "Installing collected packages: python-magic, python-dotenv, opencv-python-headless, idna, cycler, chardet, certifi, supervision, requests-toolbelt, roboflow\n",
            "  Attempting uninstall: opencv-python-headless\n",
            "    Found existing installation: opencv-python-headless 4.9.0.80\n",
            "    Uninstalling opencv-python-headless-4.9.0.80:\n",
            "      Successfully uninstalled opencv-python-headless-4.9.0.80\n",
            "  Attempting uninstall: idna\n",
            "    Found existing installation: idna 3.6\n",
            "    Uninstalling idna-3.6:\n",
            "      Successfully uninstalled idna-3.6\n",
            "  Attempting uninstall: cycler\n",
            "    Found existing installation: cycler 0.12.1\n",
            "    Uninstalling cycler-0.12.1:\n",
            "      Successfully uninstalled cycler-0.12.1\n",
            "  Attempting uninstall: chardet\n",
            "    Found existing installation: chardet 5.2.0\n",
            "    Uninstalling chardet-5.2.0:\n",
            "      Successfully uninstalled chardet-5.2.0\n",
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            "    Found existing installation: certifi 2024.2.2\n",
            "    Uninstalling certifi-2024.2.2:\n",
            "      Successfully uninstalled certifi-2024.2.2\n",
            "Successfully installed certifi-2023.7.22 chardet-4.0.0 cycler-0.10.0 idna-2.10 opencv-python-headless-4.8.0.74 python-dotenv-1.0.1 python-magic-0.4.27 requests-toolbelt-1.0.0 roboflow-1.1.21 supervision-0.18.0\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "certifi",
                  "cycler"
                ]
              },
              "id": "fc0020e3513e4fa1a1864a49846d483b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loading Roboflow workspace...\n",
            "loading Roboflow project...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading Dataset Version Zip in vectorCompleteDataset-8 to yolov9:: 100%|██████████| 5117/5117 [00:00<00:00, 17570.19it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "Extracting Dataset Version Zip to vectorCompleteDataset-8 in yolov9:: 100%|██████████| 1374/1374 [00:00<00:00, 9981.60it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Train Custom Model"
      ],
      "metadata": {
        "id": "CTbGpF2IsZ24"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd {HOME}/yolov9\n",
        "\n",
        "!python train.py \\\n",
        "--batch 16 --epochs 50 --img 224 --device 0 --min-items 0 --close-mosaic 15 \\\n",
        "--data {dataset.location}/data.yaml \\\n",
        "--weights {HOME}/weights/gelan-c.pt \\\n",
        "--cfg models/detect/gelan-c.yaml \\\n",
        "--hyp hyp.scratch-high.yaml"
      ],
      "metadata": {
        "id": "N68Bdf4FsMYW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8c2565e3-8451-412a-bfc7-6c10cf39565d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/yolov9\n",
            "2024-03-06 01:55:58.350191: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
            "2024-03-06 01:55:58.350248: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
            "2024-03-06 01:55:58.351761: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
            "2024-03-06 01:55:59.381112: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mweights=/content/weights/gelan-c.pt, cfg=models/detect/gelan-c.yaml, data=/content/yolov9/vectorCompleteDataset-8/data.yaml, hyp=hyp.scratch-high.yaml, epochs=50, batch_size=16, imgsz=224, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, flat_cos_lr=False, fixed_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, min_items=0, close_mosaic=15, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest\n",
            "YOLOv5 🚀 1e33dbb Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, cls_pw=1.0, dfl=1.5, obj_pw=1.0, iou_t=0.2, anchor_t=5.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.9, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.15, copy_paste=0.3\n",
            "\u001b[34m\u001b[1mClearML: \u001b[0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLO 🚀 in ClearML\n",
            "\u001b[34m\u001b[1mComet: \u001b[0mrun 'pip install comet_ml' to automatically track and visualize YOLO 🚀 runs in Comet\n",
            "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
            "Downloading https://ultralytics.com/assets/Arial.ttf to /root/.config/Ultralytics/Arial.ttf...\n",
            "100% 755k/755k [00:00<00:00, 26.8MB/s]\n",
            "Overriding model.yaml nc=80 with nc=1\n",
            "\n",
            "                 from  n    params  module                                  arguments                     \n",
            "  0                -1  1      1856  models.common.Conv                      [3, 64, 3, 2]                 \n",
            "  1                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
            "  2                -1  1    212864  models.common.RepNCSPELAN4              [128, 256, 128, 64, 1]        \n",
            "  3                -1  1    164352  models.common.ADown                     [256, 256]                    \n",
            "  4                -1  1    847616  models.common.RepNCSPELAN4              [256, 512, 256, 128, 1]       \n",
            "  5                -1  1    656384  models.common.ADown                     [512, 512]                    \n",
            "  6                -1  1   2857472  models.common.RepNCSPELAN4              [512, 512, 512, 256, 1]       \n",
            "  7                -1  1    656384  models.common.ADown                     [512, 512]                    \n",
            "  8                -1  1   2857472  models.common.RepNCSPELAN4              [512, 512, 512, 256, 1]       \n",
            "  9                -1  1    656896  models.common.SPPELAN                   [512, 512, 256]               \n",
            " 10                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 11           [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
            " 12                -1  1   3119616  models.common.RepNCSPELAN4              [1024, 512, 512, 256, 1]      \n",
            " 13                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
            " 14           [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
            " 15                -1  1    912640  models.common.RepNCSPELAN4              [1024, 256, 256, 128, 1]      \n",
            " 16                -1  1    164352  models.common.ADown                     [256, 256]                    \n",
            " 17          [-1, 12]  1         0  models.common.Concat                    [1]                           \n",
            " 18                -1  1   2988544  models.common.RepNCSPELAN4              [768, 512, 512, 256, 1]       \n",
            " 19                -1  1    656384  models.common.ADown                     [512, 512]                    \n",
            " 20           [-1, 9]  1         0  models.common.Concat                    [1]                           \n",
            " 21                -1  1   3119616  models.common.RepNCSPELAN4              [1024, 512, 512, 256, 1]      \n",
            " 22      [15, 18, 21]  1   5491411  models.yolo.DDetect                     [1, [256, 512, 512]]          \n",
            "gelan-c summary: 621 layers, 25437843 parameters, 25437827 gradients, 103.2 GFLOPs\n",
            "\n",
            "Transferred 931/937 items from /content/weights/gelan-c.pt\n",
            "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
            "\u001b[34m\u001b[1moptimizer:\u001b[0m SGD(lr=0.01) with parameter groups 154 weight(decay=0.0), 161 weight(decay=0.0005), 160 bias\n",
            "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01), CLAHE(p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/yolov9/vectorCompleteDataset-8/train/labels... 590 images, 33 backgrounds, 0 corrupt: 100% 590/590 [00:00<00:00, 1724.05it/s]\n",
            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/yolov9/vectorCompleteDataset-8/train/labels.cache\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/yolov9/vectorCompleteDataset-8/valid/labels... 61 images, 6 backgrounds, 0 corrupt: 100% 61/61 [00:00<00:00, 1280.77it/s]\n",
            "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/yolov9/vectorCompleteDataset-8/valid/labels.cache\n",
            "Plotting labels to runs/train/exp/labels.jpg... \n",
            "Image sizes 224 train, 224 val\n",
            "Using 2 dataloader workers\n",
            "Logging results to \u001b[1mruns/train/exp\u001b[0m\n",
            "Starting training for 50 epochs...\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       0/49      1.84G      1.384      2.247      1.457         40        224: 100% 37/37 [00:20<00:00,  1.82it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:02<00:00,  1.04s/it]\n",
            "                   all         61         55      0.963      0.939      0.962      0.809\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       1/49      1.84G     0.9187     0.7363      1.121         38        224: 100% 37/37 [00:09<00:00,  3.89it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  2.86it/s]\n",
            "                   all         61         55      0.943      0.945      0.952       0.81\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       2/49      1.84G     0.9491     0.7442      1.117         35        224: 100% 37/37 [00:07<00:00,  4.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.69it/s]\n",
            "                   all         61         55      0.827      0.945      0.971      0.828\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       3/49      1.84G     0.9777     0.7652       1.15         32        224: 100% 37/37 [00:07<00:00,  4.97it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.32it/s]\n",
            "                   all         61         55      0.922      0.982      0.975       0.76\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       4/49      1.84G     0.9601     0.7503      1.166         29        224: 100% 37/37 [00:08<00:00,  4.38it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.28it/s]\n",
            "                   all         61         55          1      0.942      0.983      0.794\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       5/49      2.01G     0.9637     0.6958      1.154         36        224: 100% 37/37 [00:08<00:00,  4.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.20it/s]\n",
            "                   all         61         55       0.98      0.982       0.98      0.797\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       6/49      2.01G     0.9672     0.6815       1.15         26        224: 100% 37/37 [00:08<00:00,  4.36it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.82it/s]\n",
            "                   all         61         55      0.946      0.964      0.976       0.77\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       7/49      2.01G     0.9164     0.6642      1.117         48        224: 100% 37/37 [00:07<00:00,  4.74it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.72it/s]\n",
            "                   all         61         55      0.979      0.982      0.985      0.845\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       8/49      2.01G     0.9329     0.6454      1.134         36        224: 100% 37/37 [00:07<00:00,  4.65it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  2.87it/s]\n",
            "                   all         61         55      0.982       0.98      0.984      0.888\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "       9/49      2.01G     0.9145     0.6202      1.104         33        224: 100% 37/37 [00:07<00:00,  4.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.13it/s]\n",
            "                   all         61         55      0.979      0.964      0.984      0.852\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      10/49      2.01G     0.9091     0.6155      1.127         33        224: 100% 37/37 [00:08<00:00,  4.35it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.05it/s]\n",
            "                   all         61         55      0.982       0.98      0.984       0.89\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      11/49      2.01G      0.909      0.639      1.133         34        224: 100% 37/37 [00:09<00:00,  4.05it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.03it/s]\n",
            "                   all         61         55      0.978      0.982      0.979       0.87\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      12/49      2.01G     0.8845     0.6007      1.087         45        224: 100% 37/37 [00:08<00:00,  4.17it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.16it/s]\n",
            "                   all         61         55      0.982      0.981      0.985      0.879\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      13/49      2.01G     0.8523     0.5719      1.093         38        224: 100% 37/37 [00:08<00:00,  4.20it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.30it/s]\n",
            "                   all         61         55      0.982      0.982      0.977      0.868\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      14/49      2.01G     0.8429      0.561      1.101         37        224: 100% 37/37 [00:07<00:00,  4.80it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.29it/s]\n",
            "                   all         61         55       0.98      0.982      0.986      0.884\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      15/49      2.01G     0.8258     0.5736      1.096         34        224: 100% 37/37 [00:07<00:00,  4.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.43it/s]\n",
            "                   all         61         55      0.994      0.982      0.986      0.878\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      16/49      2.01G     0.8182     0.5416      1.092         29        224: 100% 37/37 [00:08<00:00,  4.32it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.12it/s]\n",
            "                   all         61         55      0.986      0.982      0.986      0.869\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      17/49      2.01G     0.8003     0.5227      1.065         39        224: 100% 37/37 [00:08<00:00,  4.27it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.10it/s]\n",
            "                   all         61         55      0.985      0.982      0.985      0.883\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      18/49      2.01G     0.8066      0.534      1.088         26        224: 100% 37/37 [00:07<00:00,  4.78it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  2.81it/s]\n",
            "                   all         61         55       0.98      0.982      0.984      0.909\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      19/49      2.01G     0.7894     0.5348      1.072         26        224: 100% 37/37 [00:07<00:00,  4.86it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.17it/s]\n",
            "                   all         61         55       0.98      0.982      0.985      0.906\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      20/49      2.01G     0.7662     0.5182      1.064         34        224: 100% 37/37 [00:07<00:00,  4.63it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.15it/s]\n",
            "                   all         61         55          1      0.973      0.985      0.874\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      21/49      2.01G     0.8073     0.5346      1.079         26        224: 100% 37/37 [00:08<00:00,  4.39it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.22it/s]\n",
            "                   all         61         55      0.997      0.982      0.985      0.897\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      22/49      2.01G     0.7786     0.5077      1.069         23        224: 100% 37/37 [00:08<00:00,  4.22it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.23it/s]\n",
            "                   all         61         55      0.998      0.982      0.985      0.886\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      23/49      2.01G     0.7587     0.4776      1.044         29        224: 100% 37/37 [00:07<00:00,  4.71it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.00it/s]\n",
            "                   all         61         55      0.999      0.982      0.985      0.877\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      24/49      2.01G      0.731     0.4659      1.026         27        224: 100% 37/37 [00:07<00:00,  5.03it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.32it/s]\n",
            "                   all         61         55      0.996      0.982      0.985      0.917\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      25/49      2.01G     0.7412     0.4676       1.04         28        224: 100% 37/37 [00:08<00:00,  4.44it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.05it/s]\n",
            "                   all         61         55      0.996      0.982      0.986      0.915\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      26/49      2.01G     0.7578     0.4788      1.045         31        224: 100% 37/37 [00:08<00:00,  4.21it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.37it/s]\n",
            "                   all         61         55      0.994      0.982      0.986      0.923\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      27/49      2.01G     0.7282     0.4656      1.016         32        224: 100% 37/37 [00:08<00:00,  4.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.19it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.919\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      28/49      2.01G     0.7297     0.4547      1.048         41        224: 100% 37/37 [00:07<00:00,  4.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.21it/s]\n",
            "                   all         61         55      0.999      0.982      0.986       0.92\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      29/49      2.01G     0.7046     0.4473      1.027         40        224: 100% 37/37 [00:07<00:00,  4.77it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.21it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.908\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      30/49      2.01G     0.7104     0.4295      1.025         40        224: 100% 37/37 [00:08<00:00,  4.40it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.20it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.915\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      31/49      2.01G     0.6912     0.4345      1.019         30        224: 100% 37/37 [00:08<00:00,  4.30it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.25it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.926\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      32/49      2.01G     0.6995     0.4349      1.015         26        224: 100% 37/37 [00:08<00:00,  4.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.36it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.919\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      33/49      2.01G     0.6699     0.4172      1.007         39        224: 100% 37/37 [00:07<00:00,  5.00it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.62it/s]\n",
            "                   all         61         55      0.999      0.982      0.985      0.921\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      34/49      2.01G     0.6806     0.4158      1.011         38        224: 100% 37/37 [00:07<00:00,  4.66it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.22it/s]\n",
            "                   all         61         55      0.999      0.982      0.986      0.907\n",
            "Closing dataloader mosaic\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      35/49      2.01G     0.4937     0.2793     0.9486         13        224: 100% 37/37 [00:07<00:00,  5.28it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.43it/s]\n",
            "                   all         61         55      0.999      0.982      0.986       0.92\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      36/49      2.01G     0.4853     0.2722     0.9605         12        224: 100% 37/37 [00:07<00:00,  5.25it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.56it/s]\n",
            "                   all         61         55      0.999      0.982      0.988      0.909\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      37/49      2.01G     0.4744     0.2636     0.9655         13        224: 100% 37/37 [00:06<00:00,  5.53it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.27it/s]\n",
            "                   all         61         55      0.999      0.982       0.99      0.931\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      38/49      2.01G      0.473     0.2656     0.9498         14        224: 100% 37/37 [00:07<00:00,  4.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.49it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.924\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      39/49      2.01G     0.4605     0.2554     0.9408         13        224: 100% 37/37 [00:07<00:00,  4.96it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.27it/s]\n",
            "                   all         61         55      0.999      0.982      0.989       0.92\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      40/49      2.01G     0.4526     0.2508     0.9338         14        224: 100% 37/37 [00:06<00:00,  5.56it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.27it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.929\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      41/49      2.01G     0.4423     0.2407     0.9266         12        224: 100% 37/37 [00:06<00:00,  5.48it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.41it/s]\n",
            "                   all         61         55      0.999      0.982       0.99      0.917\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      42/49      2.01G     0.4534     0.2388     0.9249         14        224: 100% 37/37 [00:07<00:00,  5.19it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.53it/s]\n",
            "                   all         61         55      0.999      0.982      0.989       0.94\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      43/49      2.01G     0.4255     0.2304     0.9077         13        224: 100% 37/37 [00:06<00:00,  5.37it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.08it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.932\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      44/49      2.01G     0.4388     0.2259     0.9197         13        224: 100% 37/37 [00:06<00:00,  5.58it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.37it/s]\n",
            "                   all         61         55      0.999      0.982       0.99      0.936\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      45/49      2.01G     0.4337     0.2272     0.9155         13        224: 100% 37/37 [00:07<00:00,  4.92it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.42it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.943\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      46/49      2.01G     0.4264     0.2242     0.9191         14        224: 100% 37/37 [00:07<00:00,  5.14it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.38it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.951\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      47/49      2.01G     0.4017     0.2144     0.9039         14        224: 100% 37/37 [00:06<00:00,  5.65it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  3.52it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.943\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      48/49      2.01G     0.4033     0.2063     0.9216         14        224: 100% 37/37 [00:06<00:00,  5.72it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.20it/s]\n",
            "                   all         61         55      0.999      0.982      0.989       0.95\n",
            "\n",
            "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
            "      49/49      2.01G     0.3959     0.2046      0.905         14        224: 100% 37/37 [00:07<00:00,  5.11it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:00<00:00,  4.48it/s]\n",
            "                   all         61         55      0.999      0.982       0.99      0.949\n",
            "\n",
            "50 epochs completed in 0.142 hours.\n",
            "Optimizer stripped from runs/train/exp/weights/last.pt, saved as runs/train/exp/weights/last_striped.pt, 51.4MB\n",
            "Optimizer stripped from runs/train/exp/weights/best.pt, saved as runs/train/exp/weights/best_striped.pt, 51.4MB\n",
            "\n",
            "Validating runs/train/exp/weights/best.pt...\n",
            "Fusing layers... \n",
            "gelan-c summary: 467 layers, 25411731 parameters, 0 gradients, 102.5 GFLOPs\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:01<00:00,  1.96it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.951\n",
            "Results saved to \u001b[1mruns/train/exp\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Examine Training Results"
      ],
      "metadata": {
        "id": "fpCwjSUg2Mrw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** By default, the results of each subsequent training sessions are saved in `{HOME}/yolov9/runs/train/`, in directories named `exp`, `exp2`, `exp3`, ... You can override this behavior by using the `--name` parameter."
      ],
      "metadata": {
        "id": "rHsMq7wc3bve"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!ls {HOME}/yolov9/runs/train/exp/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WslwgMAW2Euc",
        "outputId": "bf85033d-097f-40c0-ed95-b2f4650f8597"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "confusion_matrix.png\t\t\t\t    P_curve.png       train_batch2.jpg\n",
            "events.out.tfevents.1709690160.97ea8f6e2d15.1474.0  PR_curve.png      val_batch0_labels.jpg\n",
            "F1_curve.png\t\t\t\t\t    R_curve.png       val_batch0_pred.jpg\n",
            "hyp.yaml\t\t\t\t\t    results.csv       val_batch1_labels.jpg\n",
            "labels_correlogram.jpg\t\t\t\t    results.png       val_batch1_pred.jpg\n",
            "labels.jpg\t\t\t\t\t    train_batch0.jpg  weights\n",
            "opt.yaml\t\t\t\t\t    train_batch1.jpg\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image\n",
        "\n",
        "Image(filename=f\"{HOME}/yolov9/runs/train/exp/results.png\", width=1000)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "id": "grirpuCstpZE",
        "outputId": "17b067e4-89ba-4640-bb32-a446964af93e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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4OjpCrVZj9uzZRv/Os7OzcebMGZw5cwb//PMPFi1aZHJuDShoGfvpp5/ir7/+MnpMNwd69uxZrF69GrNnz8azzz5b/J01YfPmzZgzZw5yc3Ntts6///4bX3zxhej8n24O8dy5c1i9ejU+++wzvPrqqwbLJCYmYuzYsTh//rzR87Ozs3H//n3cv38fYWFh+OGHH7B27Vp06tRJcjwajQb//PMPAKBOnTqoW7dukfuwZcsWzJ49W6imoXPt2jVcu3YNGzduxLx58yQT1cWcO3cOEyZMQHx8fJHLRkdHY/Lkybh69arRYw8fPsTDhw9x8OBBfPfdd1ixYkWRF9dqNBqsXLkSP/zwA7Kzs40ej4+PR3x8PI4dO4avvvoKe/bsMfuCXX22fu+KYsvfD4Wlp6dj0qRJRr8nkpOTceLECZw4cQJ79uzBihUr4OzsbPU+EFHJYJwvwDgvzpLX5Y8//sCcOXOQkJBg9Njt27dx+/ZtbN++HT169MCiRYskE6Z00tLSMHPmTPzxxx/QarUGj+Xn5wtzAn/88QeWLl2KEydOGK1jwYIFWLt2rdHzgX+PVa9du4ZNmzbhueeew5w5c+Di4lLkvpJ94ll0sgvu7u54/fXXAQA7d+5EZmYmAGDgwIFwc3MzWr5q1aqi6/nhhx+wYsUKABAqGTg7O+P+/ftGSSW6Ay9HR0fUr18ftWrVgoeHB7RarXAC7cmTJ8jPzxcSW2w5+fz48WO89dZbSEhIgKenJ1q3bg1/f388efIEp0+fFhJ4vvnmG9SrVw/9+vUrcp1FZRwXNmXKFBw8eBAymQzNmjVDSEgI8vLycP78eSEz+fz583jrrbewceNGyZO+2dnZGD58OCIjI4X7AgIC0KZNG7i6uuLOnTs4d+6ccILy3XffxeLFi41+6Dg5OeHLL7/EkCFDkJeXh7///htbt24VnZj95ptvcOHCBQCAt7c3FixYUOZXv6xZswYLFy4U/nZ0dES7du0QGBiItLQ0hIWFISUlBWq1Gj/99BPi4+Px9ddfi477p59+Ej7LAFClShW0aNEC/v7+kMlkSElJQWxsLG7evCl5kiU+Ph6jRo0S/j05ODigSZMmqF27NpydnYUfVtHR0UIiGxFVbozHpRePMzMzMWrUKIMDXxcXF7Rq1QrVqlWDVqvF48ePERUVhZSUFOTn50Oj0Vi8fxkZGRgxYoTwOsvlcjRq1AghISFwdXUVTohGR0fjyZMnFq+/JCQmJuLVV1/FnTt3hPt0nyNHR0fcvHkTFy9eBFBw0vzNN9/EDz/8IFotxVb7v3DhQoPkq6pVq6JZs2bw8fGBRqNBSkoKbty4gdjYWFu9DERUCTDull7cjYqKwttvv42srCzhviZNmqBBgwbIz8/HxYsXcefOHSxfvlzyqmig4D3QvWe3bt0SEoXr1q1rdPWt1JXH5YFGo8G4ceMMTnB6e3ujXbt28PLyQnx8PMLCwpCfn4+0tDRMnjwZaWlpGD58uOj6Pv74Y4N11a5dG40aNYKXlxdUKhWSk5Nx7do1YZ5BzIEDBzBjxgzhb3d3d7Ro0QLVqlWDQqFARkYG4uLicO3aNeTn59vgVSCi0rRp0yYhroSGhqJRo0aQy+WIjIzEjRs3AADHjx/HF198gVmzZuHzzz/H5s2bIZfL0bRpU4SEhECj0SA8PBz37t0DAOzbtw8NGzbE6NGjJbebkJCA4cOHGyT91q9fH6GhoXBzc0NSUhLCw8ORkpKCtLQ0fPDBB1i4cKFR1Q3dd//+/fuFRN7evXuLxuaQkBDJ8fz5559YtGgRAAiVEjw8PITKldb48ccfsXDhQuGEoEwmQ2hoKOrVqwc3NzfhhKDuWKXwiU+1Wo3Ro0fj8uXLwn0NGjRA/fr14eHhgby8PCQkJCA6Olr0RKiYCxcuCJWezJmjPnjwIObOnQugINa2bt0arq6uiIuLQ0REBDQaDVJTUzF+/HisWrUKXbp0KXKdt2/fxty5c5Geng43Nze0bdsWAQEBSE1NRXh4uMGyZ8+exTvvvCPMj+rmUOvUqQOlUon79+/j3LlzyM3NRWxsLF555RVs3rxZ8r1Wq9UYP3489u/fL9zn4OCAli1bokaNGlAqlUhMTBQqkGg0GqtiW0m8d6bY+veDPpVKhXHjxuHUqVPCa1WrVi3k5ubi3LlzePDgAYCCKtnz5s3D559/Xuz9ISLbYZwvwDgvzpLXZd26dZg/f76wv/rHhRqNBtevX0dUVBS0Wi0OHz6MYcOGYePGjZLJTo8ePcLw4cMN5mw9PT3RqlUr+Pv7Q6VS4cGDB7h8+TIyMjIkE8QePnwIrVYLmUyG4OBgBAcHw9vbG0qlUii+oZvL3rdvHzIyMvDdd9+V+XlrKhlMwCK74O3tLUy0/fPPP8LE87hx40TL70pZsmQJPDw8MH/+fPTu3dvgscJXz/Tp0wc9evRA+/btRa+YUKvV2LVrF2bPno2srCwsW7YMzz77LGrWrGnp7on65ptvkJeXh7fffhvvvfeeQXBISUnB+PHjcfr0aQDAV199hb59+5r8otYFGwAICgoqspXc+fPnkZ+fj6CgICxdutSocsTWrVvx+eefIz8/H9euXcPChQsxa9Ys0XUtWLBASL5SKBT45JNPMGzYMIMSlXFxcfjoo49w+fJlqFQqTJs2DU2aNDF6fxs2bIiJEycKB91z585FmzZtEBwcLCwTHh6O7777Tvj7iy++kDwZUVoiIiKwePFi4e+uXbti3rx5Bu0v8vLysHTpUqxZswZAQdb6unXrMGLECIN1qVQqrFq1Svh7woQJGDFihGiLpZSUFBw8eFD4saNv7dq1wr+lNm3a4KuvvhJ9nVQqFSIiIrBlyxb+GCCq5BiPSy8eT58+XUi+UigUePfddzFy5EijtnUajQZnzpzBzz//bNV39LZt24ST7fXq1cPy5ctFr0rSarW4dOkStm/fLtkSqLRMmTJFOGB1dXXFF198geeee85gmUuXLuHDDz/E3bt3haobu3fvNmohYYv9f/LkidAiWaFQYM6cORg4cKDo+/H48WP89ddfvBqXiMzCuFs6cTcvLw+TJk0Skq8CAwOxZMkStGzZ0mC5nTt34tNPP8WCBQskt1enTh3hPdO13QEKkq30k4fKuzVr1hicPB09ejTGjRtnEAMTEhIwefJkHD9+HEBBMnKLFi2MEsuio6Nx4MABAAVxe+nSpaIVr4GCtst79+4VrbCtfwHSG2+8gYkTJ4pOomdmZuLo0aMGJxCIqPybM2cO/P39sXjxYqN2tT/++KPw3btt2zbUrVtXSG756quv0LBhQ2FZtVqNBQsW4KeffgIArFq1Cm+88YZo+2+NRoMJEyYIJ2WbNWuGzz//HE899ZTBcrm5uVi9ejVWrFgBrVaLmTNnomXLlgaxT/cdf/36deHE7JtvvinaeteUJUuWwMHBATNmzMCQIUMMYlzhmG2OI0eOGJyU7dChA2bMmCF6cvju3bvYvn27UaLx4cOHhe9Uf39/fPPNN5JJxNevX8euXbuKrMysH2PMOTG7aNEiyOVyTJo0CcOHDzeYU75x4wY++OADXL9+Hfn5+ZgyZQr27dtnMmEaKEhQV6lUeP311zFhwgSD5Pb8/HyhokpCQgLGjx8vJF8NHDgQEyZMQEBAgMH6EhMT8dlnn2H//v1IT0/HBx98gJ07d4pWZlmyZIlB8tUbb7yBsWPHirbki4yMxIYNG6zqSFAS750ptvz9UNhff/2FvLw8dO3a1WiuX6VSYfHixfjxxx8BFFRRefvtty36vUxEJYtxvgDjvDhzX5dTp05hwYIF0Gq1cHBwwPvvv49hw4YZHRdevXoVEydOxI0bN3D16lUsWLAAn332mdF2VSoVPvjgAyH5ytnZGZMmTcLQoUONzrfm5eXh+PHj2LZtm+g+NG7cGF26dEH37t3h4+Mjukx4eDimTp2K27dv48iRI9i9ezcGDBhQ5OtD9sd0g06iCkaj0WDVqlVGk84AjE6mffbZZ+jWrZvkCTKFQoHBgwdjzpw5AAoOzDZt2mSzsebl5WHMmDGik4re3t5YvHix8KPi7t27BtWlxFy6dEnITjan/WB+fj5cXV2xdu1a0bY9Q4YMwcyZM4W/t2zZYlCJQufOnTsGFSGmTZtmdKAMFExUr127FjVq1ABQUJHim2++ER3bm2++KVzJlJWVhYkTJwpXAaWlpeHjjz8Wqj4NHToUffr0KXJ/S9pXX30ljKlly5b45ptvDJKvgILP4KRJkzBs2DDhvhUrVhhVn7p165ZQhaNVq1YYPXq0aPIVUPBZefHFF0WvSte/mmvu3LmSSWpKpRLt2rXDl19+WWQ5VyIiczAem47HJ0+eNGjZu2jRIowdO1Z0MkEul6NDhw5YuXJlkeWUxZw7d064PW3aNMmS0LpqmJ999hkCAwMt3o6tnD59GkePHhX+XrJkiVHyFQA0bdoU69atE16T+Ph4/Pzzz0bL2WL/L1y4ILSI7NevHwYNGiSZDBAQEIBhw4aJVu8kIiopjLum4+7OnTuFSXknJyesWbPGKPkKKDjhOmfOnApfXSkjIwMrV64U/h45ciQmTJhg9Fnx9/fHqlWrhPkC3cnPwvSPO998803J5CsAqFmzJv773/8aTdJnZmYKLZ8CAwMxffp0ySuY3dzc0LdvX0ycOLGIPSWi8kQmk2Ht2rWiJzJHjhwptLlRqVSYN28efH19sX79eoOTssC/F37qLtTMysoSWuAUtnv3boSFhQEAWrRogfXr1xudlAUKYsPYsWPx3nvvCev84YcfrN5XU1QqFebOnYuhQ4caHVNYeiGMSqXC559/LpyU7dGjB9asWSNZmaNmzZoYP368UUs4/WOm8ePHm0yUqV+/PiZOnIhmzZqZHJsuOdrb2xutWrUqcl/y8/Px4YcfYsSIEUZzyvXq1cPatWuF5KWEhASsW7euyHWqVCoMGTIEM2bMMKos6uDgIGxnyZIlSEpKAgAMGzYMCxYsMEq+AgA/Pz8sW7YMHTp0AFDQGlGs3VVsbKxw8S1QcGHtp59+Kpp8BRQkDCxYsAD169cvcp8KK4n3Toqtfz8UlpeXhzZt2mDVqlVGc9hKpRKTJk0S1qnVag3mVIio7DHOF2Ccl96Xol4XjUaDzz77TOgAsWTJEowePVr0uLBRo0ZYt26dcA72t99+w8OHD42W27FjByIiIgAUxP41a9bg9ddfFz3f6ujoiJ49e0qet/7Pf/6DwYMHSyZfAQWFMH788Uc4OTkBAH755RfJZcm+MQGLKpVnnnkGbdu2tfk6dRPAuqtbbcHHx0cI+GL8/PwMJi6LmnjWzzju1auXWWN46623UKtWLcnHhwwZgsaNGwMoOLDZunWr0TJbtmwRAmKjRo3w2muvSa7Py8vLYJJ07969QosJfTKZDPPnzxeuio2KisKyZcsAADNnzhRKDtepUwdTp04tajdL3M2bN3H27Fnh7xkzZpj8MfXRRx8JB90ZGRnYu3evweP6CVmmgnlRdFfQF3c9RESWYjwuIBWPdVdtAgUJPWIJRrZiq5hSWvSTunv27Inu3btLLhsUFIQxY8YIf2/atEmYlNCxxf7b22tIRJUP424Bqbirfxz7xhtvmGwZ0b9/f9HkrIpkz549QjUwPz8/jB8/XnJZR0dHg8peYWFhuHXrlsEyto613t7erMxMVAG9/PLLJhNMCh8TjRkzRrRaHlBwcrZv377C35cuXRJdTj9J5/PPPy+ySu3o0aOFirr79u2zqgV8UZo1a2bU9shaf//9t9Da1dXVFXPnzrWqipL+d7BUkpAl7t69K7Sb6tq1q1kXewYFBWHkyJGSj/v7+xv8fvjtt9+Mjv0Kc3Jywscff2xymeTkZOzevVvYRlHLKxQKfPjhh8LfuufqW7dunfDZadGihU1bORdm6/fOFFv/fhAzdepUyc+wTCbD4MGDhb+l/t0TUdlgnC/AOC/OnNfl0KFDiIuLA1DQ/rGowhv+/v5Ci9v8/Hz88ccfRsvoz8G/9dZbaNOmTZFjLa6goCAhEfHSpUtGBTioYmALQqpUrD2BGR0djatXr+L+/fvIyMgwKgWpm/y7du0aNBqN0ZU41ujRo4eQBSvlqaeeEoKGLtBK0WUce3h4mB1EBg4caNYyuvKUumxyfbr2EABMVoTQ6dOnD7y9vZGSkoK8vDycP38eXbt2NVrOz88P8+bNE/o7r1mzBhkZGcLVLQ4ODli8eLHkVbGlSf81aNSokWiWvT5XV1c8//zzWL9+PYCC1/WVV14RHtevvBEWFobY2FiDFozmqlatmvCDZePGjSZ7ZRMR2RLjsXQ8zsvLw5kzZ4S/33jjDUuHbJFq1aoJtzdu3IjPP/+8RLdXXPq/NV588cUil3/xxRfx1VdfQaPRICEhAbdu3TI4sW6L/dePy/v37zc5SUREVBYYd6XjbkZGBqKiooS/zTkGHjRokNAmuCLSP3597rnnijxR0axZMzRo0ADXrl0DUBCr9StK6sfaXbt2YejQoRYfp1epUgVOTk7Izc3F9evXce7cObRu3dqidRBR+fbMM8+YfLxwC9lnn33W5PL6J3nv3btn9Pjjx4+Fynr16tUzqrAhxsnJCS1atMDRo0eRnp6Oa9eumfU8S9jy4ptjx44ZrNfaJFj97/GtW7eiR48exaqQf/DgQeG2OV0aAOD5558v8qRy//79MW/ePKjVajx+/Njo2K+wp59+usg2hSdPnhQqX/bp06fI3yhAQdthV1dXZGVlCVU19Om/L6+//nqJJhXb+r0zxda/HwqrWbOmcCG4FP0596J+IxJR6WKcL8A4L86c10W/I8Lzzz9v1np1VSmBgkpfI0aMEP6+f/++QfKvLefgHzx4gMjISMTFxSEtLQ25ubkGieG6z6xWq0V0dHSpJH5R6WICFlUqRf1IL2zHjh349ttvhSSVouTn5yM9Pb3IgzdzFP7BIcbb21u4bSpL9sGDB4iOjgYAdOnSRbJdnb4qVaqgdu3aRS7XokUL4fbVq1eh1WqFA0dd8NAx50phBwcHNG3aVPjxcOXKFdEELADo1q0bhg0bhvXr10Oj0WDjxo3CY++//z6aNGlS5PZKg+6HHmDeawAUtBbUJWBduXLF4LHAwEC0aNECFy5cQHp6OgYPHowBAwagT58+aNWqldmT2X379hUOjhcvXoyTJ0/ihRdewNNPP23wo4uIyNYYj6Xj8dWrV5GbmwsAcHFxMVn22Rb69u0r9K7ftGkTLl++jEGDBqFz585m/Q4oTY8ePRJaPwAwq4S1j48P6tSpIxxQX7lyxWAS3hb737x5cwQGBiI+Ph4PHjzAc889h8GDB6Nnz55o1qyZxSXEiYhsjXFXOu7GxMQIVza7ubmZ1d5H/xi4IrL2+FV3ArXw8Wu3bt2EE9GXL19G37598dJLL6Fbt2546qmnzJrcd3R0RO/evbFv3z6oVCoMHz4c/fr1E6q76a5UJyL7VdT3v36M8fDwMGpBVlhRseLChQvC7ZycHMyaNcuscd65c0e4/fDhQ5ufmLU0Zpuiv49iLZ/M9eyzz2LFihXQaDT4559/8Pzzz+PFF19E165dUb9+fYsTiHTJ0Q4ODpJzvoWZE4+8vLwQHBwsVN24evWqyQQsc15r/dcwJibG7M+JTmpqKrKysoSqoYmJiQaJQcV5X8xh6/fOFFv/fijMlr8Riaj0Mc4XYJwXZ87ron8R1N9//23QdUiKfoel+Ph4g8cuXrwo3K5Tp45NzomeP38eixcvRnh4eJGVOHWePHlS7O1S+cMELKpUzM0A1mq1mDp1KrZv327xNjIzM20y8ezh4VHkMvpX/qhUKsnldAEPMD/juHr16hYvl5eXh8zMTLi7uwMoCG66q4QAoEaNGmatU3+5ooLPxx9/jLCwMOFgDSj4sfGf//zHrG2VhuTkZOG2ua9rUa/BnDlzMHz4cCQmJiIrKwsbN27Exo0boVQq0bBhQ7Rt2xadO3dGx44dJSe0hwwZgmPHjuHAgQMAClqH6NqHVK9eHa1bt0b79u3Rq1cvtlQiIptiPJaOx4mJicLtatWqWVU62hJdunQRkpmBgtLHutLdfn5+aN26Ndq1a4fevXuXeXKufjx1dnY2+3NUo0YNIQGrcEy1xf47ODhg4cKFGDNmDLKysvDkyROsWbMGa9asgZOTE5o0aYK2bduia9euaNWqFdsmEVGpY9yVjrv6cSEwMNCs72hzj+nslX68tcUxfJUqVfDFF1/gk08+QX5+PuLj47F8+XIsX74crq6uaN68Odq2bYuePXuiUaNGktuYMmUKLl++jLi4OOTn52PXrl3YtWsX5HI56tWrhzZt2uDpp59G165dmfxMZIeK+v7Xn9syJ1boLy8WKx4/fizcvnfvHjZs2GDOMA2kpqZa/Jyi2HL+Tf/ilZo1a1q9npCQEHz88cdYuHAhtFotbt26hUWLFmHRokXw8vJCy5Yt0bZtW/Tq1avICv1paWk4d+4cAKBt27bCHHJR9KsOF7WcLgFLP56JMee11v+cnDt3Thi7JdLS0gwSsHQcHR2LTDAoLlu+d0Wx9e+Hwmz5G5GISh/jfAHGeXGWxmRdJyRLpKWlGfytH5ODgoIsXl9hv/32G6ZPn2524pVOZmZmsbdN5U/x68MT2ZGiSt/qbNmyxWDSuUuXLliwYAH27NmDs2fP4tKlS4iJiRH+0z9YsFVfYFuenDt06BCAgoOQbt26mfUcc1+rwtWW9IOFru+71LJSdAelhdcnxsHBwWiiv2fPnjZpf2Er+q+D/r6Zov9aib0G9erVw65duzBs2DCDH6QqlQpRUVFYu3YtRo0ahR49emDr1q2i21AoFFixYgW++OIL1KtXz+CxBw8eYM+ePZg+fTq6du2KadOmISUlxayxExEVhfFYOh7rf+ebGzOKa/r06VixYgWaNWtmcH9iYiL++usvzJ49G927d8f777+PBw8elMqYxOi/Npa0Lirqd4Ut9r9du3bYvXs3Bg4caPD5zs3Nxblz5/Dtt9/itddew7PPPiskPhMRlRbGXfPirrXHwBWN/vGrrY7hn3vuOWzduhV9+vQxqESWlZWFU6dO4euvv8bAgQMxePBghIeHi27D398f27Ztw3//+1/4+fkJ92s0Gly7dg2//vor3nvvPXTu3Bnff/891Gq1WWMnovLBku9/W8QK/YoI1iqJ7xlzWtyZy5bHliNHjsTPP/+Mjh07Grz+qamp+Oeff7Bo0SI8++yzeOuttxATEyO5nmPHjgkX6/bs2dPs7ZfEnLI5cd8WnxP9xICyON631XtXlJL4/aCPFzIR2TfG+QKM8+LMeV2KW9mw8Pup//q5ubkVa903btzAzJkzheSr+vXrY9q0adi6dStOnjyJyMhIg7mUQYMGCc+11VwKlS+sgEUk4scffxRujxs3DmPHjjW5fHnOUM3MzMSZM2cAFJT1Nfeq5JycHLOWy87ONvhbP1AVDvrZ2dlm/RDQP2ArKvB9//33RqUmly1bhm7duhX7yh1b0d/nwklpUvRfV6nXwM/PD9OnT8ekSZNw4cIFhIeH4/z584iIiBB+jDx69AjTp09HTEwMpk+fbrQOmUyGIUOGYMiQIYiNjcXZs2cRERGB8PBw3L17F0BBS5HffvsNZ86cwebNm1kNi4hKTWWMx/rf+ebGDFvo06cP+vTpgwcPHuDMmTOIiIjAuXPnhKuHtVot/vrrL4SFhWHTpk1lEmP1X5vCvz9MMed3hS32v2bNmliwYAFmzpwpXB0dERGBixcvCr+r4uLi8N5772Hy5MkYMWKE2ftARFQaKnvctfYYuKJxdXUVTliYu6/mxNpGjRphxYoVSEtLw9mzZ4U4GRUVJUzSX758GW+++SYWL16Mvn37Gq3D3d0dH3zwAcaNG4eoqCiEh4cLMVtXOSM1NRWLFy/GhQsX8M033/CELRGJ0k8Q6dmzJ1atWlWGoykZbm5uQvUOWxxbtmvXDu3atUNiYqJwzBQREYGrV68KJw9PnTqFoUOH4scff0Tr1q2N1qFLjgYsOzFry3hkCf3PyZQpU/DWW28Va31ldbxvi/euKCX1+4GIyBqM85YryzhvDhcXFyHO7NixA0899VSx1qcfd4o7t/HTTz8JCdedO3fGqlWrTFZlLs9zKWQb5adEDFE5ER8fj7i4OACAp6cnxowZY3L5jIyMEilFaSvHjx9HXl4eAMsCXuF+uOYs5+joaBC0PDw8DK5uNbdqxv3794XbVapUkVwuMjISy5cvF/7WnQzNysrCxIkTDdofliX9hCVzX1dzXwOg4HVv164d3n33XaxevRqnT5/G6tWrDX4ArV+/HpGRkSbXExwcjKFDh2L+/Pk4cOAA/vzzT4wYMUIo53rnzh2sWLHCrPETERVXZY3H+hUdHj58WOpl86tXr46BAwdi1qxZ2LdvH/755x+MGzdOmLhISUnB/PnzS3VMOvrxNCcnp8iWEjqWxFRb7L+rqyu6dOmCDz74AD///DPCwsKwbNkyNGjQQFhm8eLFePTokVnjJyIqDZU17urHhYcPH5rVLsDcYzp7pR9vbX0MDxR8vnr16oVJkyZh06ZNOH36NObNmye0dlSr1fj8889NJsQpFAo0b94co0aNwjfffIOTJ09iw4YNBu/1wYMH8ddff5k1fiKqfPSPu/Rb0FQkvr6+wu179+7ZbL1+fn7o168fpk+fju3bt+PEiROYOnUqvL29ARQcq82cOdPoeSqVCkePHgUANGjQwOw2dYD5sffhw4fC7aLikTn0PycJCQk2XV9eXp5BO6XSYO17Z46S/v1ARGQJxnnrlUWcN4f+/to6Jhf39Tt16pRw+4MPPjCZfAUYxj+qmJiARVSI/oFP3bp1DRKIxJw7d87inq6lydqM4+TkZNy5c6fI5S5cuCDcbtSokcHVpTKZDA0bNhT+Pn/+fJHrU6lUuHTpkvC3VBZzVlYWPv74Y+HE9ODBg7FhwwYhCEdFReHrr78ucnuloVGjRsJtc14DAIiIiBBuW5rJ7eDggK5du2LdunUGJ3sPHz5s0XqCg4MxefJkjBs3TrhP//NERFSSKms8btSokVB2OTs7GxcvXizxsZkSGBiIsWPHYtasWcJ9J06cEE5ql6aqVasaHGybE1OTk5OFhALA8phqi/13dnbGs88+i/Xr1wsH9/n5+Th27JhFYyEiKkmVNe6GhoYK7eszMjKEyoem6B8DV0TWHL/qL2dprHV3d8fgwYPx008/CRPVT548MXvbACCXy9GmTRusXLkSTz/9tHA/j1+JSErz5s2F21evXi3VakSlpUWLFsLt06dPl9h2fHx8MHz4cKxcuVK47/r160JlfZ3w8HCkpaUBsLwqhjmxNy0tDbdu3RL+Lm5lDAAGber152qt5efnZ3BCuiTfF3OY+96Zo7R/PxARmcI4bzulEefNof+e2iIm668vLi7OIInbUvrzKaGhoSaXTU9Px7Vr16zeFtkHJmCR3dHvBVsSVSH0E4jMKZe7ceNGm4/BVjQaDY4cOQKgYBK9du3aFj1/165dFi3Tvn17o8c7dOgg3N65c2eRk/QHDhxASkoKgIL3umXLlqLLffHFF8IJ1Vq1amH69Onw9fXF3LlzhWV++OEHhIWFFbkPJU3/Nbhy5Qqio6NNLp+dnY3ff/9d9PmWcHR0NJh8TkpKsmo9+j+WKurVAkRkOcZj81kSjx0dHQ3i6YYNG0p8fObQjwX5+flCrC5t+q/Njh07ilx+x44dQpnsgIAA1K1b16rt2mL/vb290apVK+Fva+MyEVVOjLvmsyTuuru7o0mTJsLf5hwD79y5s9hjLM/0jz/37duH3Nxck8tfunQJMTExwt9i8wLmqFWrFurXry/8bU2clMlk6NGjR7HWQUSVQ82aNRESEgKg4Pf9b7/9ZpP1lnS8tkSXLl2E2/v27TO7grC1WrduLVTHAIznEPUvDLX0xOy+ffugVqtNLrNnzx5hGX9/f6uP/fR16dIFSqUSQEGyUFFzuubo2rWrcPvXX38tFwntRb135iir3w9ERGIY522vJOO8Obp37y7c3rZtW5Fxpig1atQQPiNA8ebgdRd1AUXPp2zdurXcdG+iksMELLI7+l/wJdG6JSgoSJh8LuqKj99//93iqkKl6fz583jy5AkA6wLe2rVrTe7/9u3bhWpVMpkML730ktEyQ4cOFYLP5cuXsXnzZsn1paWlYdGiRcLfzz33HDw8PIyW+/PPP7Ft2zYAgFKpxJdffim0PuzevTtef/11AAUT75988kmZt8YICQlB27Zthb9nz55tMsAuXbpUmCh2d3fH888/b/B4amqqcDK5KPoluvVLQQMw+weZfua3fuURIqrcGI/NZ2k8HjFihHB737592LdvX4mNzZpYIJfLDd7/0vTyyy8Lt/fv32+yitT9+/fx7bffGjxXP8EAsM3+695bc5iKy0REpjDums/SuDtkyBDh9vr16xEbGyu57L59+3Du3LniD7Ice+GFF+Dq6gqgoLWDqTb0eXl5+OKLL4S/27dvb3TC29xYq1arDa4c1j/2zMjIMLv6JGMtEZnr7bffFm4vXbrUIBmkKFKtb0o6Xlvi//7v/4RqS1lZWZg6dapVJ4vN/R5PS0tDZmam8HfhOUTdbwd/f3+DylLmuHPnDtatWyf5eGJiIr755hvh75deesno2M8aVatWRf/+/QEAWq0WkyZNQkZGhlnP1Wg0oq/d8OHDhbny8+fPY/Xq1cUepxRbvXfmsPXvByKi4mKcN095iPPmeOaZZ4SLqxISEvDZZ5+ZncScmZkpWgVNfw5+7dq1CA8Pt2psNWvWFG6bqsIcFxdnMj5SxcEELLI7+ldE/vnnnzZfv4+Pj1C6UaPR4P333zcoX6y7f8OGDZg0aRIUCoVB1nN5ov9Fr38VqDkcHByQmZmJkSNH4vLly0aPb9u2DTNmzBD+fumll0SvLK5Vq5bBydLZs2djw4YNRglEt2/fxsiRI4Veu+7u7njvvfeM1vfw4UOD/sLvvvuuQalIAJg0aRLq1asHoGDy1dre9bb00UcfQaFQACgoxTlu3Dijq3Hz8vKwePFigwmFsWPHCsllOgcPHsQzzzyDNWvWSPYmzsvLwy+//IK//vpLuE//Ciug4DMxY8YMnDlzRjKh69KlS5g9e7bkOoio8mI8Np+l8bhTp0549tlnhb8//vhjrFixQvQKGo1Gg9OnT+O9995Denq6xWN75ZVXMGHCBBw5ckTyxGZsbCw++eQT4e+OHTsW2cu+pHTo0MEgFr3//vv4448/jJaLiorCiBEjhNLXgYGBePPNN42Ws8X+//LLLxgwYAB+/fVXyQmazMxMLFmyREhcVygU6Ny5sxl7TERUgHHXfJbG3YEDByI4OBgAkJOTg5EjR4q2AN69ezemTJlSZHtGe+fu7o53331X+Pv777/H0qVLjeJkYmIi3n33XaEtlFKpxIQJE4zWt2jRIrz++uvYuXOnEJcLe/LkCaZPny7EUXd3d4Nq2JcvX0bPnj2xfPlyyTaRarUav//+O3755RfhPh6/EpEp/fv3F6r2ZGZm4rXXXsOmTZskjwsyMjKwe/duDBs2zGCuTF+DBg2E23/99VeZVjdSKpX49NNPhUSkw4cPY9SoUbh586bo8vfu3cOyZcuMKj1+8MEHGDNmDP7880/Jqg6PHj3ChAkThAtO69Spg1q1agmP37x5E7dv3wYAdOvWzeLkKAcHB3z55Zf46aefjOYwb968iREjRgjzrH5+fnjrrbcsWr8pH3zwAfz9/QEAMTExeOmll3D8+HHJ5R8+fIh169bh2WefNehwoBMcHGxwwnfx4sWYPXu2ZJXlyMhITJ48GdevX7dq7MV978xl698PRETFxThvqDzHeXMoFAp89tlnwnnW7du3Y/To0ZL7CxS0n1y0aBG6d+8uei510KBBwnFnfn4+/vOf/2DDhg2iBTTy8vJw6NAh0fPW+vMO8+fPF71g+NSpUxg2bBgyMzOFhGWquJRlPQAiSz3zzDNCFaVff/0Vly9fxlNPPQUXFxdhmVdffdWqAwWd8ePHY+TIkdBoNLhy5Qr69++Pli1bombNmsjKykJ4eLgwMfjhhx9iy5YtuH//fvF2rAToMo6rVKli0PLGHC1btoSXlxf279+PF198ES1atEDdunWRl5eHCxcuGFwRHRISYnBisrBPPvkEUVFRuHTpElQqFWbNmoXvv/8erVu3hqurK+7cuYPw8HChTLRSqcScOXMQFBRksB6NRoNJkyYJB6StW7fGO++8Y7Q9Z2dnLF68GEOGDEFeXh7++OMPdO3aFYMHD7boNbClVq1aYcKECVi4cCGAgveme/fuaN++PQIDA5GamoqwsDCDg+0+ffpIThjcuXMHCxcuxMKFC1G9enWEhoYKV/cmJibi4sWLBut64YUXjD4DOTk52Lx5MzZv3gw3Nzc0atQI1atXh4uLC1JSUnDr1i2Dg3sfHx+MHTvWNi8IEdk9xmPzWROP58yZgwcPHiAyMhJqtRrLly/HmjVr0KpVK1SrVg1arRaPHj1CVFSU8H1vzUG/SqXC3r17sXfvXjg7OyM0NBQ1a9aEm5sb0tLScPfuXURFRQnLOzs7Y9KkSRZvx5bmzZuHV199FXfu3EFWVhY++OADLF26FM2aNYODgwNu3ryJixcvCq+Hq6srFi9eDE9PT6N12Wr/o6Oj8fnnn2PWrFlCC6UqVapApVIhISEBERERBldavf322wgMDCyBV4eIKirGXfNZGncdHR2xcOFCDB8+HFlZWXjw4AGGDh2KZs2aoX79+sjPz8fFixeFCeXp06cbVG2oiEaNGoVz584Jr+WqVauwceNGtG/fHl5eXoiPj0dYWJjByYuPP/7Y6OIooOD3SXh4OMLDw6FQKFC3bl3UrVsXXl5eyMnJwaNHjxAREWEwyf3JJ5/A2dnZYD26ahorVqyAv78/GjZsCH9/fygUCiQmJuLy5csGFbTatGmD5557ztYvDRFVIAqFAkuXLsXIkSNx5coVZGRkYObMmVi0aBFatGiBqlWrQqFQIDU1FbGxsbh165ZQWeKZZ54RXWefPn3w1VdfQavV4p9//hFiqf7Flf369UPTpk1LZR979OiBjz76CIsXLwYAnD59Gs899xwaNmyIevXqwdXVFampqYiJiREqQE6ZMsVgHbp9+eeff+Dg4ID69eujTp068PDwQGZmJh48eIALFy4IiVEKhQLTpk0zWId+crQ1XRo+/vhjzJ07F3PnzsWPP/4ozCnHxcXh3LlzwraVSiXmzp1r04rNVatWxcqVKzF69Gg8efIEsbGxGDVqFKpWrYpmzZrBx8cH+fn5ePLkCa5fvy55say+jz76CLdu3RLi7C+//ILNmzejZcuWCAoKEmJbVFSU8Ntr+PDhFo/dFu+dJWz5+4GIqLgY5+0nzpurU6dO+Oyzz/DZZ59BrVbj6NGjOHbsGOrVq4fQ0FC4ubkhJycHCQkJiI6OLrK6l1KpxNKlSzF8+HDExcUhOzsbs2bNwtKlS9GqVSv4+/tDrVbj/v37uHz5MjIyMkS7Ng0fPhxbt25FcnIyUlJS8J///AeNGzdGSEgIZDIZrly5Ipxr7dy5M3x9fbFr164SeY2ofGACFtmdp59+Gs8//zz27t0LALh48aLR1andu3cv1sRzx44dMWPGDHzxxRdQqVTIz8/HmTNncObMGWEZuVyO//73vxgzZgy2bNli9bZKyu3bt4XM3+7duxv0oDXX/PnzoVKpcPjwYZw/fx7nz583WqZ58+b45ptvRIOOjouLC3766SdMmzZNqFLx8OFD0ZZK/v7+mDNnDrp162b02A8//ICwsDAAgIeHBxYuXChkOxfWsGFDfPTRR5g/fz4A4IsvvkDbtm0NSkGWtlGjRsHT0xPz588XWiiIZUIrFAq8/vrrmDx5smimuKurK2QymXBi+cGDB3jw4IHoNuVyOV555RVMnTpVdD26k8GZmZkmy2s2bNgQX331FapWrWrWvhJRxcd4bB5r47G7uzvWr1+POXPmYNu2bVCr1cjKypK80tbJycmqWK8/QZCTkyP6PuoEBQVh0aJFaNiwocXbsSU/Pz9s3LgREyZMwOnTpwEUlHCOi4szWrZ27dr48ssvJUtf22L/9deh1Wpx+/Zt4SR9YQ4ODnjnnXeY0ExEFmPcNY+1cbdZs2b4/vvv8eGHHwonOiMjIxEZGSksI5fL8e6772LYsGEVPgFLLpdjxYoVmDdvHjZu3Ai1Wo2UlBSDCss6Hh4emDp1quQFT/pxUq1W4/r165JVPNzc3DB58mQMHTrU4H5nZ2colUrhhEhCQoJk1Umg4ITJ3LlzrfptRESVS5UqVbBx40bMmzcPv/32G1QqFTIyMkxWOHJ2dkbjxo1FHwsODsbo0aPx3XffAQCuXbuGa9euGSxTv379UjsxCwCjR49GUFAQ5syZg8TERGi1Wly9ehVXr14VXb5wVQb97/H8/HxcuXIFV65cEX2ur68vZs2aZVSBUHdi1tnZGU8//bTF+9CrVy84Ojpizpw5knPKnp6emDt3ruiccnE1a9YM27Ztw7Rp03Dq1CkABdVA9u/fL/kcPz8/0W4RQMEJ35UrV2LZsmX48ccfkZeXJ/q7S0ehUFhVhdoW750lbPn7gYjIFhjnjZXHOG+JoUOHolatWpg5cybi4uKg1WpNHmMCBe+Jl5eX6GPVqlXD5s2bMX36dCGup6Wl4Z9//hFdXqx6la+vL1auXIn//ve/ePLkCYCCKs6Fu0v17t0b8+fPx5w5c8zZVbJjTMAiu/Tll1+ie/fu2LdvH65evYonT54gNzfXptt49dVX0apVK6xbtw5hYWF4/PgxnJ2dUbVqVXTo0AEvvvginnrqKZtu05Z0V5oAlrcf1HF3d8eqVavw559/YufOnYiJiUFiYiI8PT0RGhqKF154AQMHDjRrUtPNzU3IJN61axfOnDmDx48fIycnB1WqVEGDBg3QvXt3vPjii6IB7PLly/j666+Fv2fMmGFUIauwt956C8eOHcOJEyeQmZmJiRMnYsOGDVAqy+6rb8iQIejVqxe2bt2Ko0ePIi4uDqmpqXBzc0O1atXQqVMnvPjii0ILRTHPPvssjh8/juPHjyMiIgIxMTG4e/eu0M7Bw8MDderUQevWrTFw4EDJdYWFhSE8PBxnzpzBpUuXcPv2bSQlJSE3NxfOzs6oVq0aGjdujGeeeQY9e/bk5DURGWE8Llpx4rGzszNmz56Nt956C7t27cKpU6dw//59pKamwsHBAf7+/ggNDUWnTp3Qr18/uLu7Wzy+nTt34sKFCwgLC0NkZCRiY2OF+Ozs7CxUmOjZsyf69etXZq0HC/Pz88NPP/2Eo0eP4o8//sC5c+eQkJAAlUoFX19fNGrUCL1790b//v1Ntoqyxf6PHDkS//d//4eTJ0/i/PnziImJwf3795GZmQmZTAZPT0/UrVsXHTp0wMCBA1GjRo2SfGmIqAJj3C1aceJu27Zt8fvvv2PDhg3Yv38/7ty5A5VKhYCAALRp0wavvPKKZEJvRaRrafHKK69g27ZtOHXqFB4+fIjMzEx4eXmhTp066NatG4YMGYIqVapIrufTTz/Fa6+9hpMnT+LChQu4ceMG4uPjkZmZCYVCAW9vb9SvXx9PP/00BgwYAF9fX6N1NG/eHCdPnsTJkydx7tw5XL16FXfu3EFKSgo0Gg3c3d1Rs2ZNtGjRAv37969U7xMRFZ+zszM+//xzvP3229i9ezdOnz6NuLg44TvGw8MDNWvWRMOGDYWW6KaOvT766CO0bt0a27Ztw+XLl5GUlCTZ0qe09OvXD927d8fOnTtx9OhRxMTEIDk5GWq1Gl5eXggODkbr1q3xzDPPGMX5VatW4cqVKzh16hQiIyNx8+ZNPHz4ENnZ2XB0dISPjw8aNGiAbt264YUXXjB6bZKTk4V2cx07djSqcGiuV199FW3atMGmTZtw8uRJPHz4EEDBhTI9evTAG2+8gYCAAKvWbY4aNWpg3bp1OH/+PP7880+cPXsWDx8+RFpamhDPateujSZNmqBz585o166dyTlouVyODz/8EK+88gq2b9+OkydP4vbt20hJSYFCoYCvry/q1auHjh07ol+/flZdFFvc984atvr9QERkK4zz9hHnLdGhQwf8/vvvOHDgAP755x9cvHgRiYmJyMjIgLOzM/z8/FC3bl20bNkSXbt2RaNGjUyuz9vbGytWrEBkZCT27t2LM2fOCDHeyckJ1apVQ6NGjdClSxfJ6mgtW7bEvn378NNPP+Hw4cNCFyl/f380btwY/fv3L9HqYFS+yLRl2aCUiErMsGHDcObMGTg6OuL06dMGWcxERERUOhiPiYiISg/jLhERUfmyY8cOTJ48GQAwe/ZsoyqHUnr27Cm0Oj548GCRF+ISERFR6bM2zhNVZCxnQlQBpaWlISIiAgDQrl07TjoTERGVAcZjIiKi0sO4S0REVP7oqlPKZDJ07969bAdDRERENsU4T2SMCVhEFdDRo0ehUqkAgCUNiYiIygjjMRERUelh3CUiIipf8vLycPz4cQBAkyZNSrRFIBEREZUuxnkicWxBSEREREREREREREREROUCWxASERERkT1iBSwiIiIiIiIiIiIiIiIiIiIiIiIrKct6AEREpW3WrFnFXseAAQPQvHlzG4yGiIjIPh05cgRHjhwp1jq8vb3x/vvv22hEREREFUtcXBx+/vnnYq/n/fffh7e3d/EHREREREREREREkpiARUSVzoYNG4q9jiZNmjABi4iIKrXIyMhix9QaNWowAYuIiEjCo0ePbHL8OnLkSCZgERERERERERGVMCZgERERERERERERERERUblw6NChsh4CEREREZHFZFqtVlvWgyAiIiIiIiIiIiIiIiIiIiIiIrJH8rIeABERERERERERERERERERERERkb1iAhYREREREREREREREREREREREZGVmIBFRERERERERERERERERERERERkJSZgERERERERERERERERERERERERWYkJWERERERERERERERERERERERERFZiAhYREREREREREREREREREREREZGVmIBFRERERERERERERERERERERERkJSZgERERERERERERERERERERERERWYkJWERERERERERERERERERERERERFZiAhYREREREREREREREREREREREZGVlGU9ACq+tLQcqNUai57j6ekMhUIOtVqDtLScEhoZlVd8/4mfAdMUCjk8PZ3LehhUDlkac/lvjfgZqNz4/heNMZfE8BiXrMHPQOXG979ojLkkhjGXLMX3n/gZMI3xlqRwXpksxc9A5cb3v2jlNeaW6wQstVqNmzdvIioqCpcvX0ZUVBSio6ORk1PwIRs0aBDmz59fKmOZPHkyduzYIfw9duxYjBs3rlS2XRS1WgOVSm3184vzXLJ/fP+JnwEi8xUn5vLfGvEzULnx/ScyH49xqbj4Gajc+P4TmY8xl4qD7z/xM0BkPs4rU3HwM1C58f23L+U6AeuDDz7A33//XdbDwJEjRwySr4iIiIiIiIiIiIiIiIiIiIiIiABAXtYDMEWtNszm8/b2Rp06dUp1DBkZGZg5cyYAwNXVtVS3TURERERERERERERERERERERE5Vu5roDVrFkzhISEoHHjxmjcuDFq1qyJ7du3Y8qUKaU2hoULFyI+Ph6BgYF49tlnsXbt2lLbNhERERERERERERERERERERERlW/lOgHrnXfeKdPtnzp1Clu2bAEAzJw5E1FRUWU6HiIiIiIiIiIiIiIiIiIiIiIiKl/KdQvCspSdnY1PP/0UWq0W/fr1Q48ePcp6SEREREREREREREREREREREREVM4wAUvC4sWLcffuXXh7e2PatGllPRwiIiIiIiIiIiIiIiIiIiIiIiqHynULwrISERGBDRs2AAAmTZoEPz+/Mh4RERERERERERERUcWlVqtx8+ZNREVF4fLly4iKikJ0dDRycnIAAIMGDcL8+fNLZNsHDx7Erl27EBUVhYSEBLi7u6N27dro3bs3XnnlFbi7u5u9rtu3b2PTpk04duwY4uPjodFoEBAQgE6dOmHo0KFo1KhRiewDERERERERlS0mYBWSm5uLqVOnQqPRoGPHjnjxxRfLekhEREREREREREREFdoHH3yAv//+u1S3mZmZiYkTJ+LQoUMG9ycnJyM5ORnnz5/HL7/8gqVLl6JFixZFrm/z5s2YO3eukDSmExcXh7i4OGzevBnvvvsuxo4da8vdICIiIiIionKACViFLFu2DLGxsXB2dsasWbPKejhm8fR0tvg5crlM+L+Pj5uth0TlHN9/4meAiIiIiIiIiMoTtVpt8Le3tze8vb0RFxdXYtsbP348jh07BgDw8/PDkCFDUK9ePaSmpmLv3r2IiIhAfHw8Ro8ejY0bNyIkJERyfbt27cKMGTMAAHK5HP369UPHjh2hVCoRERGBHTt2IC8vD8uXL4ejoyNGjx5dIvtFREREREREZYMJWHoiIyOxbt06AMC4ceNQq1atsh2QmRQKuUXLP0rOwqUbicjKyYerswOa1vNDVR/XEhodlWcymQwKhaysh0FliJ8BopKTmJKN87eSkZOrgrOTEjV9XODn7VLWwyIiIqpwGHOJiCqGZs2aISQkBI0bN0bjxo1Rs2ZNbN++HVOmTCmR7W3dulVIvqpXrx5++ukn+Pn5CY+//vrrWLBgAX788UekpqZixowZ2LBhg+i6kpOThYt55XI5VqxYgV69egmPDxw4EIMHD8Zbb72F7OxsLFu2DL1790bdunVLZN/sWWJKNqLvpCA7VwUXJyUa1vJmXC8n+JuLiMg+WRpbrYnFpRW/bTk2U+sqjefY+nUu6zGX1+eU9fatHbPUb67yPGZbbt+eMQHrf/Ly8jBt2jSo1Wo0btwYI0aMKOshmU2t1pi13PW7Kdi8PwbnYh5Dq/33fpkMaB0agJf7hKJ+Te+SGSSVK3K5DDKZDFqtFhqNtugnUIXDz0DRLE1uJdKJjU/DruOxuHQzCfr/umQAmob4YkDnYAQHepbV8EiERqNBbm42cnKyoFbnQ6Mx77eVOZ48UUImA7RaID9fZbP1kn2oyO+/XC6HQuEAZ2dXODm5QC5n3KTSx5hLRFSxvPPOO6W2LbVajRUrVgh/L1y40CD5SmfixIk4deoUrl69ivDwcBw/fhydO3c2Wm7NmjXIyMgAUJC4pZ98pdOiRQuMHz8e8+fPh0qlwjfffIPFixfbcK/sG+N6+cX3hojIPln6/W3N931pxQhbjg0APFwdkJ6Vb3CfDEBIDS/IZMCNe6kl9hxT67LmdS7rMZfG9jnmyjPmivDbkglY/7Nq1Spcu3YNCoUCs2fPhkKhKOshmS0tLQcqldrkMudiHuO73ZehUhsnWmi1QHj0Y1y4noAx/RujdWhASQ2VygkfHzcoFDJoNFokJ2eW9XCoDPAzYJpSqUCVKqwMSJYzGW8BRN5MwpW4ZMbbciQnJwspKYmA0SGAbeTna1Bw6MCE18qoIr//Go0aKlU+cnOzAMjg7e0HZ2fGTio9jLlERFQcZ8+eRUJCAgCgXbt2aNy4sehyCoUCw4YNw9SpUwEA+/btE03A+uOPP4Tbw4cPl9zukCFD8PXXXyMrKwuHDh1CTk4OnJ2di7MrFQLjevll7++NNdUYyrPSqKJS1pVvyrqCh633h6isWPr9bc33fWnFCFuPDYBoEokWwI37qZLjsNVzTK1Lf1/6dAwGAJy6FI/Fv56T3P+yHnNpbJ9jrjxjLu+/Lc3BBCwA0dHRWL16NQDgrbfekjzgtlex8Wkmg4yOSq3Fd7svY8obznadVUhERFQWGG/tj3jylcymlXxksn/bvMrlFSsBh4pWkd//gkpxun3SIiUlkUlYVGoYc4mIqLiOHj0q3O7atavJZfUf13+ezo0bN3D//n0AQEhICGrWrCm5Lnd3d7Ru3RrHjh1DVlYWzpw5U+T2KzrG9fKrJN+bkk5wsaZSiK7qQrcW1ZGZrSpXrX3Ss/MtruIitS/WrmtA52B4uDgYtESCSo0jFx+YrEjj4eJg1n66OSsl11XWVT8qSkUOqjws/f4e/qwaP/0ZbdH3PYBSid/WxCJzx1Ze6falTlAVyOUyLP41wm73hcga9v67nwlYALZv3478/HzI5XI4ODhg5cqVosudPXvW4LZuueDgYPTt27dUxmqNXcdjzf5iVqm12H08FuOHNC/hUREREVUsjLf2RaPRGCRfOTm5wNXVE46OTgZJM8WlUMiFFnTmto2miqMiv/9arRZ5ebnIykpDbm42dElYAQFBbEdIJY4xl4iIiuvatWvC7aZNm5pc1t/fH4GBgYiPj0diYiKSk5Ph4+Nj1bp0yxw7dkx4bmVPwGJcL79s8d5YkmRjqwSXoiqlSFVj0FVdiLyZZPRYWbf2kUG6brepChJi+2LtusQStqQU9Ryp/ZRaV1lX/agoFTmo8rD0+3vL4RsWf99r/3fbkudYE7+tiUWWjK28Uqm12Hzg2v9uV6w5RSJz2PPvfiZgoeDkAVBwIu7bb7816zlhYWEICwsDAPTq1avcJmAlpmTjksiPbFMibyYhMTUbfl4sqUpERGQOxlv7o0sYAQqSr7y9/W2aeEVU0clkMjg5OcPR0QkpKQnCv6nc3Gy4uLiV9fCoAmPMJSIiW4iNjRVuBwUFFbl8UFAQ4uPjAQC3bt0ySMC6deuWxesSG0dlxLhefhX3vZGqQCXFVgku5lZKsVRZt/ax5d5Yuy5rnmdJopc9sPeKHFQ5WPP9bem/yYs3k2DpLKo18duafbFmbOVV+NVHFWZfiKxhr7/7mYBVwUXfSbH4h7EWQMydFPg1ta8PMxERUVlhvLU/OTlZwm1XV08mXxFZSSaTwdXV838JWAX/tpiARSWJMZeIiGwhPT1duF2lSpUil/f29hZ9rq3XVdo8PZ0tfo5cLhP+7+NTvN99528lWxXX7yVlo0GwX7G2TaYV571Jysj/X7skyyt2FCS4XMG8d6ugfk1vi5+/cmeU3Vc9ofJNpdbijzN3MX1Eu7IeCpEoa46ZrVEax+XW7ktFigIVaV+ILGWv83lMwAIwbdo0TJs2rcjlli9fjhUrVgAAxo4di3HjxpX00IotO1dl1fOyrHweERFRZcR4a3/Uat2VXTI4OjqV6ViI7F3Bv6GCRhb//tsiKhmMuUREZAtZWf9ekOHkVPTxgP4ymZmZxVqXs/O/SU+F11XaFArrW0fLZDIoFMW7kCXHyvicnacq1tipaNa+N4fP3cWV2GSoNdafMlapNdhy8BpmjOpg0fMeJWfhXMxjq7dLZK5z0Y+QlJqDAB/Xsh4KkRFrj5lLg6XH5eV5X4iodNjjfF6lSMDavn07pkyZAgBo164d1q9fX8YjKj0uTta9xa5WPo+IiKgyYry1PxpNwZW4crmc1a+Iikkmk0Eul0OjUQv/tohKCmMuERGR7aitqFAkl8sgk8mg1WqhKUaSDQA4WxmfXRyVVo2dzGfte2Npqygp4VcfIT4xAwFVzE9wuXg9AVqWCqFSoNUWfN56tqkp+jgTRKksWXvMXBosPS4vz/tCRKXDHufzyvWI7969i99++83gvpiYGOH2lStXsGTJEoPHO3TogI4dO5bK+OxBw1re/7sW3XwyAKG1vEtmQERERBUQ4y0REVHpYMwlIiJbcHV1RWpqKgAgNzcXSqXpafLc3FzhtpubYds9V1dX0eWk5OTkSK6rtKWl5UClUlv0HB8fNygUMmg0WiQnF6+CV00fF6viepCvS7G3TaZZ897YklYLhEU+wNNNA4X7ElOyEX0nBdm5Krg4KdGwljf8vP9tSZOYxM8ElZ6E5EzR7yGlUoEqFiQOEtmaNcfM1iiN4/LS2pfyrLLvP1Vu9jqfV64TsB48eIBvv/1W8vGYmBiDhCwAUCqVTMDS4+ftgqYhvoi04MqTZiG+8POyr16aREREZYnxloiIqHQw5hIRkS14eHgICVhPnjwpMhEqJSXF4LmF16Xz5MmTIrdtal2VDeN6+WXNe2Nr5/9X0crNWYkjFx/g0s0kg5PQMgBNQ3wxoHMwggM9WSmFSpU9VuSgysGa728PVwekZ+WbvXzzEF9ogRKP3+UhFpWlNo2qAiioCklUGdnr737WwawEBnQOhlJhXmsdpUKG/p2DS3hEREREFQ/jLRERUelgzCUiouIKDv43Nty7d6/I5fWXqVu3rsFj+n9bui79cVRWjOvllyXvTUmIuJaIH3+/iuXbLyGyUPIVAOHk/7xfzuFczGOhUgpRSbPXihxUeVgaW4f2qGdxLLZkG3KZ9fF7QOdgyOWV79tdqZDh5d4N8Or/hULJtqZUCdnz7/5y/S+2ffv2QpUrc/8bN26c0XoGDx4sPL5+/XqrxzNu3DiT2ymvggM9MaZ/4yIDoVIhw5j+jREc6FlKIyMiIqo4GG+JiIhKB2MuEREVV4MGDYTbly5dMrlsYmIi4uPjAQC+vr7w8fGxel2Fl6lfv75Z463IGNfLL917U95PfKvUWny3+zLSs/PRNMS3rIdDlYC9VuSgykP3/a0o4vtbF1ufbhpocSw2N34DgKebA2pXs67qZ3CgJ2r6l23L5tKme53r1/RGg1pVMOG1VmWaEE1U2uz9d3+5TsAi22kdGoApb7SWDLbNQ3wx5Y3WaB0aUMojIyIiqjh08bZ2VXfRx+vV8GK8JSIisgFdzK3i4ST6OI9xiYjIlC5dugi3jx49anLZI0eOCLe7detm9Hi9evVQvXp1AMDNmzdNVsHKzMzEuXPnAAAuLi5o166dReOuqHRx3dvdUXKZ8S81Z1wvA61DA9C5aWBZD6NIKrUWu4/Hom+HWmU9FKrg7LkiB1UurUMDMKRHPcnHCx8z62JxDT/xZKeqPi5Gx9i653i6OpgcS0pGHi5Z2UYwKycf9xIyrXquKWJjlgGoX8ML9YO8RCsq2uo5pu53c1Yavc4dmwZi0mstRZdHGY+5tF4zjrnyjLkizOexSXElEhzoCQ9XB6Rk5Bnc3zTEF+OHNC+jUREREVUswYGeeOHpYKzYbnzl84vd6tpt1j4RlY74+AcYMqQ/AKBv3+cxbdpnZTsgonIsONATTev64OjFeIP7HZQyHuMSEZFJ7dq1g7+/PxISEnDmzBlcvnwZjRs3NlpOrVYbdFTo16+f6Pr69u2LNWvWAADWrVuH6dOniy63ZcsWZGVlAQB69uwJFxdWUNEJDvRE3epeiLiWIPq4s5OilEdEOvkqTVkPwSyRN5MQFCB+QRyRLdh7RQ4xBw8exK5duxAVFYWEhAS4u7ujdu3a6N27N1555RW4u9v239TNmzexceNGnDlzBvHx8cjJyYGfnx8aNmyI5557Dv369YNcbl7tkNzcXPz+++/4+++/ER0djeTkZKjVanh4eKBu3bro2LEjXnzxRQQGlv8k0pIS4C3+O6NHqxoY9n+hRvcHB3qiS/Pq2HTwutFjbUIDRD/7wYGeqOHvjrTbT0yOZfOh63j8JBsuTko0rOUNP4mxFXb+eiLUmsJNaK3T4amqaBzsg9Ba3vDzckFiSjZi7qYgK1cFVyelcD8Aycds+Zwvfj6LWw/SDcbo5e4k+jr7e7uK7tMzbYPwcq8GpTbmsn7NKtOY7yVnIztPBRdHJYJ8XexizLbcvj1jAlYl46A0/uGikLFsIRERkS1JVZxU2ehgkYgqt6NH/8H16zEAgKFDX4OHh3Vl3IkqAqXC+BhXrS6DgRARUbmxfft2TJkyBUBBopV+ApWOQqHAu+++i88//xwA8Mknn+Cnn36Cr69h+7Ivv/wSV69eBQC0atXKoHKWvlGjRmHTpk3IzMzEhg0b0LFjR/Tq1ctgmYsXL2LZsmUAAKVSiffee694O1oB5amkg/jjJ9kIqe5ViqMpfxJTshF9JwXZuSqLT2AXR0JKdolvwxa0AP46c8fkMjIUVCeHDLhxLxX2NEsjA0TH6+nqgLSs/BJdl9Ty1mzDUkW9Z2JjtvVzZChoO9i/c3CFSb7KzMzExIkTcejQIYP7k5OTkZycjPPnz+OXX37B0qVL0aJFi2JvT61WY8mSJfjhhx+g1Rq+Iw8ePMCDBw9w6NAhbNiwAUuXLkXVqlVNru/q1av44IMPEBcXZ/SYbh/Cw8Px/fffY+LEiXjzzTeLvQ/2SK0RT6B1dpBOatZIzF/n5Usn45qK3zoPk7Ox8X+JXTIUFAcZYMa/qfDox6L3W/odIwMwuFtdg+QOP28XyTgq9Zgtn+Pj6WKUgJWelWe0HABkSNwf4PNvxbLSGHNZv2aVacwN6vpBoZBDrdYgOTnTrOeU9ZhtuX17xgSsSsZRaRxUzQmMREREZD6xk8EAoFbbx1WjRFS+HTv2D/74Yy8AoF+/F5iARZWaWMzVaLXQaLSQSyREExFR+XT37l389ttvBvfFxMQIt69cuYIlS5YYPN6hQwd07NjRqu0NHToUBw4cwIkTJ3D9+nUMGDAAQ4YMQb169ZCSkoJ9+/YJ7QI9PT0xa9YsyXX5+vri008/xeTJk6HRaDB27Fj069cPTz/9NORyOSIiIrBz507k5uYCAMaNG4eQkBCrxl2R5Zs4ufv4iX0kAZWE2Pg07Doei0s3k4ySQsw9gV0cj+0kAQsoaEVYWEAVF/RqFQRXZ9PVGFydlTh64QEiC73OQOkk+Zh6ji75x8PFwawKElL7Ys26Qmt5Iz0rH7uPx0qur2uL6sjKUZn1nKL2U2xd5aXqR0WhVqsxfvx4HDt2DADg5+cnxL/U1FTs3bsXERERiI+Px+jRo7Fx48Zix6xZs2Zh06ZNAAqSoPv27YsOHTrAzc0N9+7dw549e3Dt2jVERERg1KhR+PXXX+HpKf69Fh8fj+HDhyM1NRVAQQweNGgQ6tSpA0dHR9y/fx/79u3DjRs3kJubizlz5sDFxQVDhgwp1j7YI6nKUaYqSkklbZk6l2wqfovRoqBq4ZW4ZIzp31iy1VhWjgqX45KN7g/yd4OPpzMiLWhr2CzEt9z9O/YQacGWkZ0PjVYLeaHiKekSibYeLqbbPxJR6WMCViWjFKmAZS8lhImIiOyFVAUstchEIBEREVlPKulZpdbAUc5WRURE9uTBgwf49ttvJR+PiYkxSMgCCipJWZuApVQq8fXXX2PixIk4fPgwEhISsHLlSqPlqlWrhiVLlqB+/fom1zdo0CBkZ2dj/vz5yM3Nxd69e7F3716DZRQKBd555x288847Vo25osszMU/9+ElWKY6k/DgX8xjf7b4smlhk7gns4sjJUyEt07jqRkAVF6uS4gon2Zy/noCIa4k2GKm0Dk9VRZ+2NY3uF6u60LK+f5kn+RSV/GNuBQlT+2Lpuvy8XDB+SHOTLZGM1qP3HFu1HSrrqh8VxdatW4Xkq3r16uGnn36Cn5+f8Pjrr7+OBQsW4Mcff0RqaipmzJiBDRs2WL29EydOCMlXrq6uWL16Ndq0aWOwzKhRo/DZZ59hy5YtuH79Or766it89tlnoutbsWKFkHzVuXNnrFixwqil73//+18sXbpU+F3x1VdfYdCgQVAqK9dpcesSsKypgGXdeWaVWovvdl/GlDecRROJL9xIEI1/bUID0DTEF1fikkUfL0ypkKF/52CrxliSxJKntNqCxDP3Qo9lZEskYIkkcRFR2apckYbgKJKAZW1gJCIiInGSJ4PZgpCIiMimlAqJtr9qDRxNtFUgIiICAHd3d3z77bc4cOAAdu3ahUuXLiEpKQlubm6oVasW+vTpg1deecXsiqOvvfYaOnXqhE2bNuHYsWOIj4+HVqtFQEAAOnTogJdffhlPPfVUCe+V/covogVhZRMbnyaZfKWvqBPYxZGQkiN6f8cmgdh3MtasE99yGdCnbU0E+bsbJdlotSjxBKzfT99G83p+Zr82ZZ3kY8vkH1snEplqiWTpGCp6klN5pVarsWLFCuHvhQsXGiRf6UycOBGnTp3C1atXER4ejuPHj6Nz585WbXPdunXC7fHjxxslXwEFCcozZ87E2bNnERsbiy1btuA///kPgoKCjJbVJY8BwJQpU4ySrwBAJpPh/fffx2+//YbExEQkJyfj1q1baNCggVX7YK+kLgaWajNo6jFTFbCK02lJpdZi9/FYjB/S3Oix8OgE0ee0aRiA6n5uGNO/cZFxUqmQYUz/xuWyfaiHq6Po/elZeUYJWFKtCd0l1kFEZYcJWJWMAytgERERlTiFxMlgtiAkSyWmZCP6Tgqyc1VwcVKiYS1vTlASEekRO8YFxNvPEBFR+da+fXujClfWGDx4MAYPHmzRc3r37o3evXsXe9sAUKdOHUyePBmTJ0+2yfoqE1MXCj+qhAlYu46bl+AEmD6BXRxSiW9N6/khyM/V7BPfUtW5GtbyhgwwalFnSyX12hDZo7NnzyIhoSCppV27dmjcuLHocgqFAsOGDcPUqVMBAPv27bMqAUuj0eDMmTMACpKiBg4cKLmsUqlE//79sWzZMqjVavz+++8YPXq00XLJyf+2pKtdu7bk+hQKBWrWrInExIIkz6ysyldJUaqdoDUVsEydSzZVHcsckTeTkJiabZCge+9xBiJvGifo1vBzQ3U/NwBA69AATHnD2WSL1P4l3Ka3OAonWemkZ+Uj0LfQfVIVsNiCkKjcYQJWJeOoNL4C2NSVRURERGQ5qRaEPBlM5oqNT8Ou47G4JDJ50DTEFwPK8eRBcUREhOP99wvasYwY8TZGjRqDu3fvYOfObQgLO4XExMfIyMgQHtPJzc3FH3/sxcmTx3DjxnWkpDyBg4MDAgKqonXrthg8eChq1ZKelAOAzMwM7N69EydPHkNcXCzS09Pg4OAILy8veHtXQUhIPbRv3wldunSDg4Ph5MbYsaNx4UIEAOD48XCT21mz5jusXbsaAPD119+iVSvjKz+lzJnzGf74w7CNzZAh/Y2Wa9GiFVas+N7gvvv372HXrm2IiDiHe/fuIjs7C66ubvDy8oKvrx8aNmyELl26o0WLVmaPh6g8UMilWxASERGRfTF1cjcjOx9ZOSq4OleOUxqJKdm4dDPJoueIncAuroQU8QSsar6uqFvVvdgnvv28XdA0xBeRFu6rpUritSGyR0ePHhVud+3a1eSy+o/rP88SKSkpyMkpqKTn4+MDb29vk8sHB//bJu7QoUOiCVg+Pj549OgRACAuLk6yRbBarcadO3cAFCR36a+7spBKprKqAlZ+yVTAAgqScGPupMCvqYswJyoVF0JqeBn8HRzoabLdaXkm1T5QrN1gepbxfTJIJ3ERUdmpHEcrJBC7OpgtCImIiGxLIdGCUOqqIyJ952IeS15FrEXBxPGVuGSTVxFXFH/99TsWLpyD3NxcyWXOnz+HWbM+RULCY4P78/LyEBt7C7Gxt7Bjx2/4z3/ewbBhI0TXER19FZ988gGSkgwnd1QqFbKzs/DwYTyio69g377d+OGHn9GwoX21jdm7dxe++moB8vIMy5Wnp6chPT0N9+7dxcWL57F79w7s339MYi1E5ZN0BSzGXCIiIntj6uQuUJAMVLuaee0g7V30nRSLq0Lpn8C2lcciCVgyGVDVxxXpaTk2OfE9oHMwrsQll+hFayXx2hDZo2vXrgm3mzZtanJZf39/BAYGIj4+Xmjj5+PjY9H2tFrr/13rj1Vf7969sWHDBgDAvHnz8M033xi1IdRqtVi2bJkwz/Piiy/Cy8vLaF0VnVQClqk5aqnnSJ1L1mq1yC9mBSwAyMpVmZwT1TlxKR5N6/oYzYnaY1tTUy0IzbnPzcUBcokLwYmo7DABq5IRm5xWMQGLiIjIppSsgEVWio1PK3KiASj4LH23+zKmvOFcISthAUBUVCR+/vlHyGQy9O37PJo3bwFnZxfcu3cXVatWAwCcOnUCU6ZMgEqlglwuR/v2HdGmTTv4+QUgLy8XMTFX8eef+5CRkYHvvvsGAIySsHJycjB16kRhUi40tBG6du0Of/8AODu7ID09DbdvxyIi4hxu3BCf/CstL730Crp06Y7fftuEiIiCSlsffzwVVaoYToB6eXkLt69di8aiRXOhVquhUCjQrl0HtG3bHt7ePpDLZXjy5Alu3LiGs2fDkJ6eVpq7Q2QTSom2v/mMuURERHbHVAUsAHj0JKvSJGBl56qsel6Wlc+TkvDEuGWXr5cLHAp12ijOie/gQE+M6d/YrGPh4rD1a0Nkj2JjY4XbQUFBRS4fFBSE+Ph4AMCtW7csTsDy8vKCg4MD8vPzkZycjNTUVJOJUHFxccLtzMxMPHr0CFWrVjVYZuzYsThx4gTi4uJw4sQJ9OrVC4MHD0adOnXg4OCABw8eYN++fbh+/ToAYODAgZg2bZpF464o1BLfqda0IJRqM6hSa23SRjYzOx9bD98oMg6oNRVnTlSqepVYBSyx+1j9iqh8YgJWJePIClhEREQlTiFxMtjUwS2Vb5fjknEiMl6y/YIkmd5nwYyr/uKTssyecFaptVi86QICfV0tG5OF/L1d8HSzQDSuY9kkW3GdPRuGKlV8sGTJN6hXz7icfGJiImbPngGVSoUqVXwwb95iNGliePVm377P4/XXh2PChHG4desmfvjhW3Tt2gO1a9cRljl16jgePy4oXf/yy69j3LgPJccUG3sL3t5VbLODVggNbYjQ0IY4duwf4b527TogMLC65HP27t0FtbqgksCcOYvQubN4iwGtVouLF8/bcLREpUMpUXWSFxoRERHZF61WW+Q89eMnFh6P2TEXJ+tO3bha+TwpYhWwAn3dbLoNAGgdGlBkO8OuLaojK0eFqNhkhF15ZPE2bP3aENmj9PR04XaVKkXPb+i3DNR/rrmUSiVatGiBs2fPQqvVYteuXXjzzTdFl1Wr1di9e7fBfWlpaUYJWD4+PtiyZQs+//xz/PXXX0hKSsLq1auN1tepUyeMGTMGHTp0sHjcFYVUpSurWhBKtBksbvtBoOB7/tq9FIvmRHcfj8X4Ic2Lve2yJNWCUKzdoNh9Us8norLFX5yVjFIkAStfpYFWq4VMxjKFREREtqCQS7QgZDsku3Q5LhlLt1wslwl0Wbkq3HxQslWLbj5Iw9nox/hwaHM8VcpJWB9/PFU0+QoANm78GWlpqQCAL75YYJR8pePvH4DZsxfgzTdfhlqtxtatGzFx4hTh8Xv37gm3n39+gMnxBAfXtXQXypxu/7y9q0gmXwGATCZDixatSmtYRDYjmYDFtr9ERER2xZz2wZUpAathLW/IAIuqisgAhNbyttkYVGoNklKN28FXK6GLgMxtZxha0xtnrjwq09eGyF5lZf1b1c7JyanI5fWXyczMtGqbQ4cOxdmzZwEAS5YsQdOmTdGyZUuDZTQaDWbPno1bt24Z3J+RkSG6Ti8vL0ycOBE+Pj5Yv3696DKnT5+GTCaDl5cXGjVqZNXYbcnT09mi5XWt5eRyGXx8rEt8dXIWT9BRKBWS61Q6KETvV2u04s9JzbFqbPqahPgh6laiRc+JvJUElUyGgCole2FqSXN1ViIrx7BCY65aAx8fN4PPgFgVRx8vF6s/G1T+2eI7gMoGE7AqGUeleOBUqTVGZYOJiIjIOlLtkFTlMIGHinYiMr5cJl+VJrVGi+OR8aWagFWtWiC6dOkm+phWq8Wff+4DADRp0gzNm7cUXU6ndu06aNSoMaKiIhEWdtrgMReXfyfAYmKu2mWSlSm6/UtLS0V8/AOT1bKI7BErYBEREVUM5nRpeCzSDq+i8vN2QdMQX0TeTDL7Oc1CfA0SlYorOS0HGpFKzoF+JXsSsKh2huXhtSEi8z3//PPYtWsXjh8/jqysLLzxxhvo27cvOnToADc3N9y7dw979uxBTEwMfHx8kJubKyR7ySUucl2zZg0WL14MtVqNAQMG4NVXX0WDBg3g4OCAu3fv4o8//sD333+PEydO4Pz581i2bBm6dpW+KK00KCSOXYsik8kkuy0UReq6JLVGKzkese99AMjNU4s+J19iI3K5zGSlLR2lQo6n6vrg0k3LErC0WuBKbDIC/dwtel554+XmZJSAlZ6Vb/Rap2bkGT3X28PJ6s8V2Y/ifAdQ2WACViXjIFIBCyg4wGUCFhERkW2wAhZR8TVt2lyyQmts7C2kphZUv/Lw8MDRo/8UuT7dpF18/H3k5uYKV3G2adMeMpkMWq0WixfPx/3799C79zMGbQrtWdu2HXDkyGFoNBqMGzcGb7zxFrp27Q4fH9+yHhqRTUgmPZvZuoCIiIjKh7z8oo+XH1naEt7ODegcjCtxyWb9rlEqZOjfOdim2xdrPwgA1UqgBaGlyvq1IbJXrq6uwnxKbm4ulErTp4lzc/+tgufmZt2/fblcjmXLlmHy5MnYv38/VCoV9uzZgz179hgs5+/vj5UrV2LUqFHCfZ6enkbrW7ZsGVauXAkAmDRpksHyABASEoKxY8eiY8eOGD58OLKysvDRRx/h77//ho9P6VZ212fpvLBcLhPmq8xJZBKTL9EeUK3WSI5HqiJlXr5a9DnZOcaVmQDg/9rXwoEzd01WuFQq5JjwWiskploX3zOy8ux+vt3DzQHxhfKJU9NzoVZrhM9AVo5K9HV0d3Gw+/0nabb4DqgMymMSIhOwKhlHiQSsfF4dTEREZDNSJ4MrexUle/V0s0CcjX5cqd8/hVyGzs0CS3Wb/v4Bko89fBgv3D516gROnTph0brT09Pg5OQPAKhTJxjDh4/CunU/IDs7G2vXrsbatavh6+uHpk2boVmzlujQoSNq1apj1X6UteefH4DDhw/i3LkzePgwHl9+OQ9ffjkPtWvXQZMmzdCiRSt07NgZ3t7eZT1UIqsoJY5xzWljREREROWH1ElifakZecjNU8PJsXJcSBwc6Ikx/Rvjmx1RRS47sl8jBAcaJyoUh1TLx8BykICle22+233ZZBKWUiHDmP6Nbf7aENkrDw8PIQHryZMnRSZVpaSkGDzXWu7u7lixYgVOnjyJ7du34/z580hMTIRcLkdQUBD69OmDN998E25ubkL1K5lMBj8/P4P1PHr0CKtXrwYABAcHY+TIkZLbbN26NQYOHIitW7ciPT0d27Ztw9tvv231PhRXWloOVGbEOh0fHzcoFAVVpJKTrWv/mJllXDUJAHJyVZLrzM7OF70/T6VBYlIG5IUulkxIEm8TWcvfDVPeaIXFmy6Its9rHuKL/p2DERzoiYQk6/ZPq9ZY/dqUFy4iLR9T0nORnJwpfAZS0sXbPDrIYPf7T9Js8R1Q0SmVClQph21ImYBVyZiqgEVERES2IVUSVs1qHHapcR0ffDi0OY5HxiPB0iuu9SclJEp46+SrNLjzWHzSwpRaAe6Sv/Fswd/bBZ2bBZZq+0EAQoUqMRkZ6cVad36+4WTSf/7zDho2fAobNqzDpUuRAICkpET8888h/PPPIXz9dUFFrrFjP0Tjxk2Kte3SplQqsXjx19i+fQu2bduC+/fvAQBu347D7dtx2LdvNxQKBXr27IP33vvAaHKTqLxTyqUqYPEYl4iIyJ6YOz+dkJKNoAD7bjdkiXo1vMxaTi7xm6g4pBKwqpVwC0JztQ4NwJQ3nLH7eCwibyZB/4hbhoK2g7qT+0RUIDg4GPfuFcwL3Lt3D0FBQSaX1y0LAHXr1i329jt16oROnTpJPh4TEwO1uiBJqU6dOkZJXydOnBDmdDp16iRZOV3n6aefxtatWwEAkZGRxRm6XZKaizZVTcfUY/kqDZwKJQzlS1SwdFQqEBzoiVpV3RF9J8XgsWo+Lhg/pLnwd8Na3pABsGTmXAYgtJa3Bc8on9xdHYzuS882TJxLyxRPpBN7LhGVPSZgVTJSJ+dYAYuIiMh25DKZ6EEjTwbbr6fq+FiVgKRQyCGTFeRemVMSeunWi4i8mVTkcjrNQ3wNJiwqCxcXF+H2yy+/jnHjPiz2Ojt37orOnbsiOTkJFy+eR1TUJVy4EIFr16Kh1Wpx6dJFvPfef7Bo0TK0bdve6u1oNKX/PaBUKjF06GsYOvQ13LkTh8jIi4iKikRERDgePLgPtVqN/fv/xPnz5/DDDz/Dz8+/1MdIZC2pClj5jLlERER2xdz56UdPKlcC1u1H5l2kc+bqY7RrVNWm2xa7AMnD1aFctTwKDvTE+CHNkZiSjZi7KcjKVcHVSYnQWt7w83IpegVElUyDBg1w7NgxAMClS5fQoUMHyWUTExMRH19QgdzX17dU2vedOXNGuN22bVujxx8/fizcNqcil34Lw6ysrGKOzv6oJeagTFX5N/WYWAKWVAK1riOTo0iFp8LD8vN2QdMQX4vmRJuF+FaI73kPV0ej+/LyNcjN/7damlQClthziajslb+miFSiHJXi5ZnNKfFMRERE5pHJZKJVsCpzCzsyz4DOwZItLAtTKmTo3zm4hEdUPvn7/3ti4fHjRzZdt4+PL3r06I1x4z7EmjXrsXXrHvTo0RsAoFKpsHz5V0bPcXT8d8KjcHWtwlJTU2w6XkvVqlUHzz8/AJMnf4otW3bh++/XISSkHgAgMTEB69evLdPxEVnKQSE+rcGqk0RERPYlL9+8+enHKZXrBPrtR+ZV/428mYSsHOMWT8XxWCQBq1o5aD8oxs/bBU83DUSfNjXxdNPACnFSnqgkdOnSRbh99OhRk8seOXJEuN2tW7cSG5OOVqvF9u3bhb+HDBlitIx+y0RdcpgpDx48EG57e3sXb4B2SGou2toELLFYLRW/dYlXYglYuSLnpCvrnKiHi3gVq4ysf+cXJStgSTyXiMoWE7AqGckWhBIlIomIiMg6CpETwqyARUUJDvTEmP6Ni5xwUCpkGNO/caVtpVC/fgO4uxdc9X7+fDjy8sQnImyhWrVqmDnzC3h7VwEA3Lp1E+nphidB9K+6TEh4DFOioi4Ve0z6Jfa1RbS2LMpTTzXB9OmfC39fvHihWOsjKm1i8RZgBSwiIiJ7Y24FLKm2eBXVnYfmJWCp1Bqcv55gs+1qtVrRCljVfFxttg0iKn3t2rWDv39B1eszZ87g8uXLosup1WqsX79e+Ltfv34lPrZNmzbhypUrwjibNWtmtEyDBg2E2//88w8yMkxXCdy9e7dwu2nTpjYaqf2QSqaytgWhWLUrqfitOx/t5GB8zC6WtKWbE5UX0Vayos2JSrURzMguOgHLgy0IicolJmBVMpItCDk5TUREZFNKOStgkXVahwZgyhut0TzEF4U/RTIUtB2c8kZrtA4NKIvhlQsKhQJ9+vQFAKSkpGDz5g0luj2lUilMUAIFE5H6goNDhNvh4WcgJTz8DG7cuFbs8bi6/nvSIyen+CegAgNrCLfVatteNU9U0hwkElZVZp7EJSIiovJBqoVRYZUtAUusApanxAnXsKu2qw6cmpknetF2ea2ARUTmUSgUePfdd4W/P/nkEyQlGbd9+/LLL3H16lUAQKtWrQwqZ+nbvn07QkNDERoaimHDhklu98KFC5IXz2m1WmzevBlffPEFgII5jzlz5ogu26pVK1SvXh0AkJqaio8++ki0taBWq8WSJUuElobOzs7o27ev5PgqKqnK0FKtCQses6wCllg1K8B0BSypoiCtQwPQu02Q6GMVdU5Uqo1geta//17YgpDIvijLegBUuiQTsFgBi4iIyKZYAYuKIzjQE+OHNEdiSjZi7qYgK1cFVyclQmt5s5XC/7z55gjs3/8nMjLSsXr1Kjg5OeGll16BXC7+ezc7OxsHDvwFZ2dn9OnzrHD/1q2b4Ovrhy5dusHBQfxERmTkBdy8eQMAEBBQ1ahsfYcOnfDDD98CAH7++Ud06dIdVapUMVjm1q2b+OKLmdburoHAwOrC7ZiYaNStW09y2eXLv0L37r3QtGlzyWV27Ngq3K5fP9QmYyQqLUqJClgqtiAkIiKyK3kSJ3ALe/yk8rQgzMjOR2JqjtH9rRr448b9VNxLyDS4//KtZBwIv4sW9fzg512840apRLdqvqyARWTvhg4digMHDuDEiRO4fv06BgwYgCFDhqBevXpISUnBvn37cO7cOQCAp6cnZs2aVextrlq1ChEREejatSuaNm2KgIAA5Ofn4+7du/j7778RExMDoCBRatmyZahVq5boehwcHDB9+nSMHTsWGo0GR44cwTPPPIMBAwagQYMGUCqVuHfvHn7//XchgQwAPvzwQ1StWrXY+2FvpBKtrG5BKFYBS+L8sqOuApbSOAFLrdFCpdaIHs9LVXWaPrxNhal6pU+qBWG6XgvC1Mxco8cdlXI4iSS3EVHZYwJWJeMoEugAVsAiIiKyNQUrYJEN+Hm7FHvivKLy9w/A7Nnz8MknHyEvLw9ff/0Vtm//DV27dkdwcF24uLggKysL8fEPEB19BefOhSMvLxf/+c87Buu5di0af/yxF+7u7mjXriMaNAiFv38AlEoHPHmShAsXInD8+FFo/jdpNWzYCKOxNGz4FFq3botz587i4cN4jBz5OgYMGIw6dYKRnZ2JCxfO4++//4RSqUSXLt1w7NiRYu17mzbthdurVi3HkydPUKtWbSiVBYd3np6eeOqpJgCAI0cOY/PmX1GtWiDatm2PkJB68PauAo1Gg4SExzh+/CguXboIoKDS16uvSl+xSlQeSSdg8RiXiIjInph7gXByWi7yVRrJC40rkjsi1a8AoFY1D/h4OuNewi2D+7UAfj1wHRsPXEfTEF8M6Bxs9clqsfaDAFDNjxWwiOydUqnE119/jYkTJ+Lw4cNISEjAypUrjZarVq0alixZgvr169tku2lpadi7dy/27t0r+ni9evUwe/ZstGrVyuR6evXqha+++gozZ85EamoqHj9+jNWrV4su6+joiAkTJuCtt94q7vDtklQ7QWtbEOaLVMCSSqD+twKWeLzOyxdPwMqV+D1QUVvgSiWcpeu1IEwXqYDF9oNE5RcTsCoZqQNTsbKRREREZD2lSEskqbLPRGSdtm07YOXKHzBr1qe4c+c27t27g19//VlyeYVCAV9fP4P7ZLKCf6sZGRk4dGg/Dh3aL/pcpVKJESPexqBBL4k+PnXqTIwf/1/cu3cXCQmPhYpYOp6eXvjsszm4dOlisROwQkLq4Zln+uKvv/5AcnISVq5cZvB4ixatsGLF9wb79/BhPPbs2Sm5Ti8vL0yfPgv16zco1tiIShsTsIiIiCoGc1sQagEkpmYjsBK0whNrPwgAtat6IDY+TfJ5WgCRN5NwJS4Zr/aqDwelAtm5Krg4KdGwlrdZF/lIVcAK9Kn4rztRZeDu7o5vv/0WBw4cwK5du3Dp0iUkJSXBzc0NtWrVQp8+ffDKK6/Aw8PDJtsbP348mjZtirNnz+LevXtISkqCTCaDr68vGjdujD59+uDZZ58VLiwrSt++fdGxY0fs2rULx44dQ0xMDFJTU6HRaODh4YGQkBC0b98eL730EgIDA22yD/ZI6mJgaytg5YrEaql2gkIFLIkqTbn5arg6G7/fUuerK2q1J3eXolsQpookYEk9j4jKHhOwKhnJFoRmHuASERGReRQibdBUEmWfich6DRs+hV9+2YojRw7h+PEjuHz5Mp48SUJOTg5cXFwQEFAVdevWQ8uWrdG5c1ejBKwJEyajV6//Q0REOKKjr+Lu3dtISUmBWq2Cm5s7goJqomXL1nj++QGoWVO8BD4AVK1aDT/++As2b/4VR44cxv37d6HValG1ajV06dINL774Mvz9A4RqU8U1bdrnaNGiNQ4c+Au3bt1EenoaVCqV0XJr1qxHWNgpXLx4Adevx+DBg/tIT0+DTCaDp6cn6tQJQYcOnfDcc/3h6VnxSrlTxeegNE54BtiCkIiIyN5YMj/96EklScB6aJyApZDLoFKpseng9SKfr1Jrsf7vawb3yQCzqmOJVcByVMpRxdOp6IETkd3o3bs3evfubfXzBw8ejMGDBxe53FNPPYWnnnrK6u2I8fb2xvDhwzF8+HCbrrcisS4BSzoei8VqqfitOx/tKJE4JVU5SywBS6mQQy7SbaIicHFSQCGXGb0nGXoVsNIyWAGLyJ4wAauScWQCFhERUalQsAIWkcVatWqD48fDLX6eXC5Hjx690aOH5ZOGTk5OaN++I9q372jxcwtzdXXDiBFvY8SItwEACoUcMhmg1QLq/1XjGTVqDEaNGiO5jsDA6ma9BnK5HC+8MBAvvDDQ5HKenl7o0+dZ9OnzrPk7QmRHFKyARUREVCFInYgVI1WdqaK5/SjD6L7qfm7Yd/qO1cnm+tWxxvRvjNahAaLLPRZJwPL3dhEq7BIRUfmnljgutrYFoVhyVK5I/FbIZUK1aqnz0lKVs3JFtuEk0cawIpDJZHB3dUBqoSSr9Cy9BKwskQpYTMAiKrcq7jcWiZJsQWjBAS4REREVTSlSAUvqoJeIiCoPtVqNa9euYfv27Zg9ezZefvllNG/eHKGhoQgNDcXkyZNLbSyTJ08WthsaGorly5eX2rZtRS6TQSFyJSwTsIiIiOyLJRcIP36SVYIjKR+yc1V4lGy8n1WruODSzaRir1+l1uK73ZclWxmKJbn5m9G6kIiIyg9btyAUaxecL5JIpX8uWrIClkSrwVyR9Tk5Vsz2gzoeIu0EM/6XdKVSa5CpVw3L1HOIqHxgBaxKxkEpHqRYAYuIiMi2xCpgqUwcwBIRUeXwwQcf4O+//y7rYeDIkSPYsWNHWQ/DJpQKOdQaw8lbJmARERHZF6lKGF5ujkjNNKz8UBkqYN19bFz9CgCUSjlsNbOgUmux+3gsxg9pbnB/dq7KoPWRTkAVJmAREdkTqWQqaytg5YskTYkV+NBPunKSSMASq3QFiCdmOUqc264oxNoJpv8vDqdnGle/AlgBi6g8YwWsSsZRokwjE7CIiIhsSylSjYMtCImISK02nEz09vZGnTp1SnUMGRkZmDlzJgDA1dW1VLddEpQiSc/5KsZcIiIie5IvcgJXqZChqo/xb5XKkIB1+2G66P3uLrY94Rp5MwmJqYavp9TrywpYRET2xdYVsHJFziWLJVA7GlTAskULwkqYgPW/FoSFk9BNPYeIygcmYFUyCrkMYl3amYBFRERkWwqFSAtCDeMtEVFl16xZM4wePRrLli3DgQMHEBYWhjFjxpTqGBYuXIj4+HgEBgbi5ZdfLtVtlwQlYy4REZHdE2tr5KBUiFZdSkrLqfDVLm8/Mk7AkgGo7utm0+1oAcTcSTG4LyFFPAGLFbCIiOyLrROwxJKlxe4zqwWhyPMAiYQuiSSuikKsnWBmdj7UGi3SMnPNfg4RlQ9sQVjJyGQyODjIjQKY2AEuERERWU+0BSErYBERVXrvvPNOmW7/1KlT2LJlCwBg5syZiIqKKtPx2IJYAhYvMiIiIrIvYvPTjko5qook/ag1WiSn5SCgiv1X8pQiloBVzdcVTYJ9IANs1oYQALJyVQZ/P5ZKwGIFLCIiuyLVjcHaFoRiyVFiVbH0k670q2EZPE+iBWFlrIAl1k5QCyAjKw+pGayARWRvmIBVCTkojBOwxDKUiYiIyHpKOatxEBFR+ZKdnY1PP/0UWq0W/fr1Q48ePSpIAhaTnomIiOxdvsgJVwelXDLJ6vGT7GIlYCWmZCP6Tgqyc1VwcVKiYS1v+BWRYGTL55haV26+Gg8SM43WVbuaB/y8XdA0xBeRN5Os3vfCXJ0MTxOJtSCUyQBfL2ebbZOIiEqe1Fy0RquFVquFTGZ8LG2qApZYsnR+ES0InRwlKmBZ0IJQqopWRSGVTJWWmYc0tiAksjtMwKqEHB0UyMwxvKqFVwcTERHZFitgERFRebN48WLcvXsX3t7emDZtWlkPx2aUIlfUVvS2RERERBWNaAUsB4Vk1aVHT7LRxIrtxManYdfxWFy6mWRQRUoGoGmILwZ0DkZwoGeJPQcoOGmanpVvcJ/+ugpOjBuPvXZVDwDAgM7BuBKXbJM5BhmA0FreBveJtSD09XQWrTpKRETll6lqVmqNVvRiJpMtCEWSo8RaCRpWwJJKwJJqQShWAatixx93FxMJWBniLQilnkNEZY8JWJWQg8iBElsQEhER2ZZCbtkBLBERUUmKiIjAhg0bAACTJk2Cn59fGY/IdsROBjIBi4iIyL6IXSDsoJTDXyIBS6xKU1HOxTzGd7sviyYuaQFE3kzClbhkjOnfGK1DA0rkOQCMkq8Kr+vpJtVEn6dLwAoO9MSY/o1NbsNczUJ84edl+BqLvbZS7wMREZVfpuaiNRotIJIbZSppS6zdoFglK4MKWBLJU9ItCI3XV9FbEHq4OoreL1UBSyYD3JyZgEVUXjEBqxJyEAl2rIBFRFS5ZWRk4MSJEwgLC8OVK1cQFxeH9PR0ODk5ISAgAM2aNcPzzz+PLl26iJYmLo6DBw9i165diIqKQkJCAtzd3VG7dm307t0br7zyCtzd3W26vdIidjJYzZPBRERUBnJzczF16lRoNBp07NgRL774YlkPyabEWxAy5hIREdkT0QoaSjlcnZWiFaOibycjMSW7yBaAOrHxaWYlLKnUWny3+zKmvFHQbq+knmNqXUcj40Ufq1X13/mR1qEBmPKGM3Yfj0WkSJUtc8hlQP/OwYW2r0Fyeo7RsgFVmIBFRGRvTCVgST1maQWs/KIqYEkkT4kVBtFotKLH8hW+BaFkBaxcpIokYLk5O0AucvE3EZUPTMCqhBxF2jMwAYuIqPJau3YtlixZgtxc43K2KpUKsbGxiI2Nxa5du9CmTRssWrQI1atXL/Z2MzMzMXHiRBw6dMjg/uTkZCQnJ+P8+fP45ZdfsHTpUrRo0aLY2yttYhWwVKyARUREZWDZsmWIjY2Fs7MzZs2aVdbDsTmxKs9s+0tERGRfxOandfPYnm6ORglYdxMy8cm3pyRbABa263is2b8PVGotdh+PhRbm/6aw5jlSxNoP+ns7w7VQtYvgQE+MH9IciSnZiLmbgqxcFVydlMhTqbHxwPUixyGTyXA5Nhn3EzLRsJY3/LxdkJiaI7p9qVaQRERUfpm6GFg6AUv6OWJJU2JVsRz0zkMrFXIo5DKj7YlVwJKqilXhE7BcTbQgzDQ+ZyO1PBGVD0zAqoTEWxCKBzUiIqr4YmNjheSrqlWrolOnTmjcuDF8fX2Rm5uLCxcuYPfu3cjKykJ4eDiGDRuGLVu2wNfX1+ptqtVqjB8/HseOHQMA+Pn5YciQIahXrx5SU1Oxd+9eREREID4+HqNHj8bGjRsREhJik/0tLayARURE5UFkZCTWrVsHABg3bhxq1apVtgMyg6ens0XLu4iU3tcC8PFxs9GIyB7orgCWy2V87yshvv9E9k+shZGDUoFzMY/xIDFT9DlSLQALS0zJxqWbSRaN5+LNJFhaW8Ka55hL135QjJ+3i1ElsDrVPIusjqXWaLH96C0AgAxASA0vZOUYt0cEgDNXH6Nh7Sr8jiUisiNFtiAsfJ9WK5qEq1P4XLJWq0V+ES0IAcDRQY7sXMPn5okkW4ndB0i3Mawo3CQqYKVm5iE1w7gCllTFLCIqH5iAVQk5iGQKswIWEVHlJZPJ0LlzZ4wcORIdO3aEXG54QDNo0CCMHj0ao0aNQmxsLO7du4cvv/wS8+bNs3qbW7duFZKv6tWrh59++gl+fn7C46+//joWLFiAH3/8EampqZgxYwY2bNhg9fbKglgFLLVaC61Wa/M2jkRERGLy8vIwbdo0qNVqNG7cGCNGjCjrIZlFIZLEbIqDUvwY19L1UMUgk8mgEGlLSZUD338i+5UvcsFSnkqN73ZfNnkyGDBsAVi4ElZiSjb2nIyzqkVfaT3HHPcSMhEbn1ZkpS+dwtWx7j7KwN/hdyWX1wK4cT9V8vHbj9Ix75dzmPBaa3RuUcPS4RMRURmwtAWhWFKWvsLJVmqNFhqRIF24YpWjUiGSgGVeNS2x9VU0SoUcrk5KZOWqDO5Pz8xDmkgLQg9Xx9IaGhFZgQlYlZBYBSwmYBERVV4ffvghvL29TS5To0YNLF26FAMGDAAA/PHHH5gxYwZcXCwvQa9Wq7FixQrh74ULFxokX+lMnDgRp06dwtWrVxEeHo7jx4+jc+fOFm+vrIid+NGi4EoiBROwypxcLodGo4ZGo2FSHFExabVaaP5Xor5wEi+VrVWrVuHatWtQKBSYPXs2FAr7mLS0tGKkUiTmqtQaVp6sZORyGWQy2f++k9iCsrLh+28eJqZSeZYv0qEhPinL4haA44c0BwDExqdh1/FYXDJRAcqePEzOwrxfzpms9CVGVx0r1i8N+8/dLTKZzRSVWovFv0YgwMcVITW8rF8RERGVCosrYBXxO7pwgpRYEhUgXgGrMNEKWHlSFbDsYy6jONxdHYwSsFIlWhC6swUhUbnGBKxKSCzQMQGLiKjyKir5Sqdhw4YIDg5GbGwssrOzcfv2bTRs2NDi7Z09exYJCQkAgHbt2qFx48aiyykUCgwbNgxTp04FAOzbt8+uErDEWhACBVWweN6j7CkUDlCp8gFokZeXCycny9pdEdG/8vJyobvWX6HgJFB5ER0djdWrVwMA3nrrLcl4Wx6lpeVAJXISVopGJNEqN0+N5GTxdkVUMfn4uEGhkEGj0fK9r4T4/hdNqVSgShXXsh4GkSSxk7hP0o1POpoSeTMJianZuP0wHd/tvmx28pa9MFXpqyi7jscWK/nq3zFosGl/DKa91a74KyMiohJlKqFKrTGOu6YStgDjZOnCLQl1ClesEkugyhVJwMqVXF/Fn0z3cHXA4yfZBvc9TMoU/S3jwQQsonKNCViVkFgFrDwmYBERkRnc3d2F27m5lk2E6hw9elS43bVrV5PL6j+u/zx7INaCECiYMHXkMVKZc3Z2RW5uFgAgKysNjo5OrIJFZAWtVousrDThb2dnntgtL7Zv3478/HzI5XI4ODhg5cqVosudPXvW4LZuueDgYPTt27dUxlpcYknPKla/IiIishsajbbIk77m0AI4HhmP30/frnDJVzqFK32ZIzElG5duJtlsDOFXH+HxkyyeXCIiKse0WtOxVeyxomJx4WRpqXPLDkYVsIwTsMSeW5krYHm4GLcVfJScZfayRFR+8DdyJeQgEqhYAYuIiIqSl5eHuLg44e/q1atbtZ5r164Jt5s2bWpyWX9/fwQGBiI+Ph6JiYlITk6Gj4+PVdstbVLtPcSuLqLS5+TkAkAGQIvc3GykpCTA1dWTiVhEZtJqC6rHZWWlITdXd4We7H//tqg80P6vxIFGo8G3335r1nPCwsIQFhYGAOjVq5f9JGApxRKwKuZJVyIioopIqoKGNcJjHpfZ74BAX1ckPMmGqoRboeoqffl5mffbO/pOik3bMGq1QNTNJLSoax/zM0RElVFRyVTWtCAsHK/zRapYASItCEWO2cVaEBZucSg8vxIkYIm1FZSqXMkWhETlGxOwKiGxQKdSa6DRaiHnCUciIpKwd+9epKenAwAaN24Mf39/q9YTGxsr3A4KCipy+aCgIMTHxwMAbt26ZTcJWEqJCli2uKqXik8ul8Pb2w8pKYnQJWEVJJHIIJfbrqy1fjKX1hb9HsiuVOT3X6PRAAancWTw9vaz6b8fInOJxVyVWgOtVsukWiIiIjtgy+4MDxLFq0WUhvik0tm2FkDMnRT4NTUvASs7V2XzMWTl5Nt8nUREZDtFzUFbUwErP9/wOFsqfhdOmBKtgCXSelgsKQuoJBWwLEiqYgtCovKNCViVUOHSjzr5Kk2lCGJERGS55ORkfPnll8Lf//3vf61ely6JCwCqVKlS5PLe3t6izy0Lnp7OZi/r4SG+rLuHM3yqsEVX+eAGT08XxMc/+F8yie7KIttN/mu1+if+K1YCDhWtIr//crlMmHCTy+UIDKxu0KaWyt60adMwbdq0Ipdbvnw5VqxYAQAYO3Ysxo0bV9JDszmxClhAweSxUsEELCIiovIuX+QkLJmWZUFSlYuT7U8DuTrz5C8RUXlWVDUr8QQs0/FYi4KLnRyUBeeSpRKmChcCETv3nCtWAYstCG2+LBGVPiZgVUJMwCIiIkvk5eVh3LhxSEpKAgD07t0bffr0sXp9WVn/XhHq5ORU5PL6y2RmZlq9XVuQaisoRqziJFBwoGrJeqhkeXl5wsPDHRkZGUhLS0NeXh7Uatu1vyCqqBQKBRwdHeHp6Ql3d3dWvioD27dvx5QpUwAA7dq1w/r168t4RGVHKRFXVWqN5GNERERUfki1IKzh54b7iebPA1T3dcWDUqpCVRyerg5IyypeBSlXC5KqGtbyhgy2uyREJgOahPhK90YiIqIyVxItCIGCqldCApbZFbBEWhCKxH7p9VX843pWwCKqOJiAVQmZSsAiIiLSp9FoMHXqVISHhwMAatWqhblz55bxqMqOWm1+rJRLtCDMy1NbtB4qHW5u7nBzs331Hl2VIK1Wa9YkBlUsleX912ot+34srLIlpd69exe//fabwX0xMTHC7StXrmDJkiUGj3fo0AEdO3YslfHZI6kqVyp1xf13R0REVJFIzUu3auCPR0+yzIrpSoUMbRoGYPeJOBuPrvhq+ruhc/PqcHVSIrSWN/y8XJCYko2Yuyl4nJKNPRaOWQYgtJa32cv7ebugaYgvIm8mWbQdKW0aVUVAFVckJ5ftRXJERCStqHkaa1oQAgWtA92c/70tpvCFyea2IBSrigVUjgpY7i7mJ1VZsiwRlT4mYFVCjkrxQJUvcaURERFVTlqtFjNnzsSePXsAANWrV8fatWvh5eVVrPW6uroiNTUVAJCbmwul0vTPkdzcXOG2m5tbsbZdXGlpOVCZGS9zssWvZk1KzoRbJbhqhwr4+LhBoZBBo9FycroS4vtfNKVSgSqVrC3rgwcP8O2330o+HhMTY5CQBQBKpZIJWCY4mKiARUREROWfVMWLGv5uGNO/Mb7bfdlkEpZSIcOY/o1Ru6oH/p+9vw+Mqr7z/v/XmZkk5IYQknATi8EY7iQGb1AEi/ZG6FbrBcq1eLH1Zm/YFbdXW7x22Z/Sb9cqtlVbW9S1VretLYpi0dKGm+6uN1gVaguCyq2BQhBSUskNSYCEZO5+f8SMmcw5M2cmZ5JJ5vn4p5OZzznnQxPzyTnnfV7vDVuPpFzz79r6M7pkYrGKR2SH3isuyFZxQdfXH/7lVFzFUdPKi8L2Zcf82WXad6SpzwXqHrdLi+ZO7tM+AADJl7wErE+ujVvdV87odR86y+S+tD8QjEittm5pOPQLsIbn2GsrmJXhNi1oA5A6uPuXhqwSsKxOdAEA6ScYDOree+/V2rVrJUljx47VqlWrNG7cuD7ve/jw4aHXJ0+ejDm+ubnZdNtUZ5XGYedJIgAAYJ9lC0LOcQEAGBS8FjdcMzwuTZ88Wstvma6xheZF+1PPG6nlt0zX9MmjQ0lP8bjg4/Z8yRSUVH202fLz+bPLLK8h9OZxG5o3uyzuOZSV5GvJvArbx7E69r9++VJNKh2Z8D4AAP0j1jXoRBOwvD2Sq+y2DLRqIdi74MoqASsdWhDm2WwrSPoVkPpIwEpDtCAEAEQTDAZ133336YUXXpAkjRkzRs8884xKS0sd2X9ZWZlqa2slSbW1tTGLurrHStL555/vyBz6g1VLLT/tkAAgrV1xxRURCVeJWLBggRYsWNDn/Xzta1/T1772tT7vZyBZ3Uj0koAFAMCgYHkD9+PEi7KSfH3xilL94r8+iBhz0+cmqHTMJw9rxZP05HEb+uvPTVDVlhrH2vNZaevwWX7WXRxlN+mrrCQ/oTl0FbMN0/qP/709j2RImvCpEZIh/am2JeKzaeVFmje7TNMrShI6NgCgfyWrAKujR+qVdWJV+HVxqxaCHd6AcoaFf92b22VYPnQ1lAy3WVg13GahFoCBQwFWGuq98HWjAAsA0F18tWbNGknS6NGj9cwzz2j8+PGOHWPSpEl66623JEm7d+/WzJkzLcc2NDSorq5OklRUVKTCwkLH5pFsHpf5zWDaIQEA4Cyri7EUPQMAMDhYXZfu+SCx1Y3JU+3esK+7i5me+M0eBaP8KdCzmCmeoi2XISUSbJ2TFf1WTKziqO4CqESLr7qVleRr6cKL1NDcrupjzWrr8Ckny6PJpQWhtobRPgMADA7+GNegE21BaC8Byx3160+2Dy/gMivosireGmqGZbrlcRsx/xaxm5QFYOBQgJWGrFsQmlcqAwDSQ+/iq1GjRumZZ57Reeed5+hxrrrqKv3sZz+TJL355pv6p3/6J8uxb7zxRuj1Zz7zGUfnkWxuWhACANAvPFYPGVH0DADAoGB1XbpnyyGrG46n2joj3ps+ebQuGD9S+46cjPjMrJgpngSqv7lmola/fEDxnNkbkiaXFsQcZ6c4yinFBdkqLjDfZ7TPAACDQ+wErMjzZTvXrTsTSMCyCgbp7JV4ZdaCMCszPQqwDMPQ8JxMnTzVEXXc8OzMfpoRgERRgJWGMjzmixUJWACQ3lasWBFRfFVWVub4cWbMmKFRo0apvr5e27Zt0969e1VRURExzu/369lnnw19fd111zk+l2SyakFIAhYAAM6ySsBizQUAYHCwStDoeR17eI75DcfTbV7T983Sr0bkZur/u226aTFTPAlU7x9qjKtl4bTyorgKqCiAAgD0VbJaEHYmkIBlVUTVu4Crd0GWZF28NRQNz86IXYBFAhaQ8ijASkNWCVgUYAFA+rr//vv1/PPPS/qk+Or888+Pez/r1q3T8uXLJXUVWvUsoOrmdrv1la98Rffdd58k6a677tKqVatUVFQUNu7hhx/W/v37JUmXXnqprrrqqrjnM5CsWhCSgAUAgLM8FqmTdtoIAQCAgec1ueEqhd90zbNqQWhRgNVqkow1pjAnaiGU3QSqeFoWetyG5s12/uE2AACiiXUNOuEWhD3uJZut34YhuXtdF8+0CAbpnXhlmoCVJi0IJXvtBSnAAlIfBVhpyKpamAIsAEhPK1eu1OrVqyV1Rd3edtttOnz4sA4fPhx1u6lTp+qcc85J6Jg33XSTXn31VW3dulUHDx7U/PnztXDhQk2YMEHNzc3atGmTduzYIUnKz8/XihUrEjrOQHK7SOMAAKA/ZJCABQDAoGbZgrDHdeycYR65DEOBXtFWp9vNC7DMCrPs3rSMlUAVT8vCJfMqQq0OAQDoL7GKqRJNwOro2YLQZP3O9LhlGL0KsDISb0HYO01rKLNK+4x3DICBRQFWGrJKwLKKigQADG07d+4MvQ4Gg/rBD35ga7sHHnhACxYsSOiYHo9Hjz32mJYtW6bXX39d9fX1euKJJyLGjR07VitXrtTEiRMTOs5AclukcZCABQCAsyzb/nKOCwDAoGD1YHDPFoQuw1BetketvQqrTpkkXQWCQdPWhPkO3rSMp2UhAAD9zR/jgSTzAqzY59DeGC0IzYqtrIqoehdw9W5JKElZFsVbQ5FV2me8YwAMLAqw0pBlC0KThQ0AgGTJy8vTk08+qVdffVVVVVXavXu3GhsblZubq9LSUs2dO1eLFi3S8OHDB3qqCekdtdyNNA4AAJxlmYBF0TMAAIOC1YPBvW/iDs/JjCjAMkvAajvri0jK6tre2ZuWdlsWAgDQ35LVgrBn0ZRZwZRZFyarNoK9E69M95dWCVi0IASGAgqw0pBVr10vN4QBIC09++yzju1rwYIFcadizZkzR3PmzHFsDqnCY3EzmAQsAACc5fFYFD2TgAUAwKDg9Uau2YYR+WCTWeqDWatBs1QsKXlte2K1LAQAoL/FugadaAvCzpgJWJH3oO23IIzcn1Xx1lA0nAQsYEhIn9w+hFi2IDRZ2AAAQGIsWxD6KcACAMBJHpdFyjMPGQEAMCj0bkEkdT1EbBjh59VmqQ+nTBKwWs9YFWBx0xIAkB6SlYDVs22wWWcls3vQVsEgvROvSMCKXSierGJyAM6hACsNWbYg5OI0AACOsboZ7Ge9BQDAUR6Lc1zWXAAABgevSYKG2TXsPJObjqfbvBHtBs1SsSRuWgIA0keyErA6erYgNEvAMim2yrJIwOrZgjAQDFokaqVPKUOsdCuXYShnGM3NgFSXPr+1EOJ2GXKZhHKYRT0DAIDEWCZg0YIQAABHecxOcCV5SZ0EAGBQsHvD1aw1TyAYVHuHL+w9qxaE+SRgAQDSRKwHkvyByM/tXLf2xmxBaJKAZZFi1RmWpmU+37RqQRjj75S8bI9chvn1DwCpI6XLJP1+vw4dOqQ9e/Zo79692rNnjz744AOdPXtWknTjjTfqwQcfdOx4p0+f1tatW/XHP/5R+/bt05EjR3Tq1CllZWVp9OjRmjZtmq6//npdddVVEfHHg4lhGMrMcOtsZ69oR5OoZwAAkBiP27zO3UcaBwAAjiIBCwCAwc3sunSGSYJGnsWNyVNtXuUOywj72gwJWACAdJGsFoQ912zTloEm67fH7ZLbZUTMqWcCVofJvqR0K8CK/ncKf8cAg0NKF2Ddeeedevnll/vlWD//+c+1cuVKdXR0RHzm8/lUU1OjmpoaVVVV6bLLLtP3v/99nXPOOf0yt2QwK8CiBSEAAM5xW6RxkIAFAICzrIqeOccFAGBwMEu9yDQpsLZKhjjd5pUKP/m61SQBy1Ds1j4AAAwVyWpB2JlAAlb3++0dvYJBvNGLubq2S58CrNzs6GUb/B0DDA4pXYDl94f/si0oKFBBQYGOHDni+LFqampCxVdjxozRlVdeqYqKChUVFamjo0Pvvfee1q9fr7a2Nr3zzju69dZbtXbtWhUVFTk+l/6QYXICSwtCAACc47FoQeijHRIAAI6yXnM5xwUAYDAwvYFrVoCVbZ780LvloFkCVm52hlwWD0oBADDUJKsAy9sjActrmmBpUYDlcZsUYH2y/lsnYJnvbyhyu1zKHebRmbM+089jtSgEkBpSugBr2rRpKi8vV0VFhSoqKnTuuedq3bp1Wr58uePHMgxDs2fP1j/8wz9o1qxZcrnCf6HfeOONuv3227V48WLV1NSotrZWDz/8sB544AHH59IfzCIbeToYAADnuF0W7ZACrLcAADjJuu0vRc8AAAwGdm/gWt14PNUeXnDVuyAr2rYAAAxFsdoJJtqCsKNH0XSnWYKlRWKV2X3psAQsk2LsaPsbqvJyMi0LsPJoQQgMCildgHXHHXf027H+3//7fyooKIg65lOf+pQeeeQRzZ8/X5L0X//1X7rnnnuUnZ3dDzN0ltkJrFW8IwAAiJ/LZchlSL3PW7kZDACAs9wuQ4YhBXuvuRYXcAEAQGoxb2EUecPVqvWOnQSsfG5aAgDSiD9G6IZ5Albsc+jubkr+QMB0H2YJlpJ5a8KeqVcdnVYJWOlVgDU8J0MfNVl8RgtCYFBIn9y+GGIVX3WbMmWKysrKJEnt7e368MMPkzir5DE7gSUBCwAAZ7lNEjnsRDkDAAD7DMMwTcGiBSEAAIOD16QAK54ErNMkYAEAECZZLQg7P06tNEu/kqQMj3nBlNl96Z4F2NYtCNOsACtKkVUef8sAgwIFWAnIy8sLve7o6BjAmSTOtADLYrEEAACJcbuMiPe4GQwAgPPMbtKSOgkAwOBg1pnBLEEjw+NWVmbkde2eiVeBYDCiJaEkDc8lAQsAkD58SWpB2F14ZdUyMMsk6UoyX9fttSBMr1KGaAXjFJMDg0N6/dZyQGdnp44cORL6+pxzzhm4yfSB6UJHewYAABxldjPYz81gAAAcl0ECFgAAg5Z5ApZ54oVZMkTPBKwz7d6ItsRW2wEAMFTFKqbqawKW1yKxymr9Nkuy6pmiRQvCLnnZ1gXjw6N8BiB1UIAVp40bN+rUqVOSpIqKCo0aNWqAZ5QY0wQsCrAAAHCU22XWgpD1FgAAp3lMip69FGABAJDygsGg6YPBZg8QS+bpDz1bDvZMw+opnwQsAEAaiXUNOuEErI/X7I44E6vM7kt3hCVgmRdgmW03lJGABQx+FGDFoampSQ8//HDo63/+538ewNn0jdkJrNdicQMAAInxeCJbEJKABQCA8zwmCVisuQAApD6rxMoMixu4w3MiC6l6Fl31LMaKtR0AAENVrPNhswItOwlYXm9AwWDQ8p6yVQG1WWFWz6KrDotErXRLwGrv8Fl+9svNf1JNXWs/zgZAIjwDPYHBorOzU1/72tfU2NgoSZozZ47mzp07wLPqkp8/LO5tMjMjFyxfIKjCwlwnpoQU53IZof/le56e+BkA+od5AhY3gwEAcJpZ218SsAAASH1m6VeSlGnRwijPpJXgqfaeBVjmCVi0IAQApJNY16ATbUEYCAblDwTD2gf2ZLV+myVZ2WlBaJWoNRTtqD6hTW9/aPn5/g9P6oHVO7RkXoWmTx7djzMDEA8KsGwIBAL6xje+oXfeeUeSVFpaqu9+97sDPKtPuE2e9I3FfKHzJ7QvDF6GYcjtjkxnQfrgZwBILrObwVZP9wIAgMSZJWD5LG7oAgCA1GF9A9d+C8KOTr+8Pr8yPG61WiVg0YIQAJBGYhVTJdqCUOpau61bBpqv32ZJVv5AUD5/QB63y7IgO10SsGrqWvXU+r0xv28+f1BPrd+r5bcMU1lJfj/NDkA8KMCKIRgM6lvf+pY2bNggSTrnnHP085//XCNGjBjgmX3Cn8CNXLMTWJ8/2FWE5aIYY6hzuQwZhqFgMGj7DyoMLfwMxEZBKpxgtqaSgAUAgPNMi55NWioAAIDUYtXCyGxtl8wTsKSu5KvCfLd1ApZJ4RYAAENVshKwpK7WgV6LAuoMqwQsi3W90+uXx+0ybUHodhmmD1sNRVVbauSL0Taym88f1PotNVq68KIkzwpAIijAiiIYDOree+/V2rVrJUljx47VqlWrNG7cuAGeWbjW1rPyWZyoWrGKgDxx4pSyTNoTYmgpLMyV220oEAiqqenMQE8HA4Cfgeg8HrdGjswZ6GlgCDBN4yABCwAAx5kWYPkoegYAINVZtiC0SLwYnmOeZHW63avC/GE6ZZKAZRhS3jAKsAAA6SMQ44Ek8wIse9etO30BdTiQgCVJHd6AcoZ1FWLZ3ddQ09Dcrt2HGuPaZtehRjW0tKt4RHaSZgUgUenxmysBwWBQ9913n1544QVJ0pgxY/TMM8+otLR0gGfmjAyLRcsqMhIAAMTPrACLBCwAAJxnWvRMAhYAACnPa1GAlWGReDHcKgGrvSv5qtUkASsvO0Muuj4AANKIP0aaUl9aEHq91glYVgEgVoXV3felO0z2Z7XNUPPB0WbFe8cgKKn6aHMSZgOgryjAMtFdfLVmzRpJ0ujRo/XMM89o/PjxAzwz51gtgFYnvAAAIH4ed+QFXhKwAABwnnkCFmsuAACpzizxQrJuQWiVgNWdfHXaJAHLahsAAIaq5LYgDFgnWFqs31ZpVp0fF16Z/T2QZXEve6hp7/AltF1bgtsBSC5aEPbSu/hq1KhReuaZZ3TeeecN7MQcZrXQUYAFAIBz3CRgAQDQL0wLsCh6BgDAUQ3N7Xr3cJPOdvg0LMujcwuzVVzQt9Y3Vtejra5f5+WYJ2CdbrNOwMq32AYAgKHKF+MadF8SsDq9fsuOSlapVdYtCP2hfdrd11CTnZVYuUZOgtsBSC7+y+xlxYoVEcVXZWVlAzwr51ktWhRgAQDgHNN2SDHinwEAQPxYcwEASJ6aulZVbanR7kONYS1yDEmV5UWaP7tMZSX5Ce3bKkEjwyL1YrhFMdWpjwuvTpkkYOWRgAUASDOxiqn6moBl1YLQKsHSqjNTd+FVh1kCVmZ6NPKaUlogQ4qrDaEhaXJpQXImBKBP0uI317p16zR58mRNnjxZt956q+W4+++/X88//7ykT4qvzj///P6aZr+yWgCtTngBAED8zFoQ+knjAADAcSRgAQCQHDuqT+iB1Tu0q1fxldR1o3DXoUY9sHqHdlSfSGj/lgkaFtevs7M8chmR59qn270KBII63U4CFgAAsa5B96kAyxtQh8X6nWWRYBm7BWHkfK2Ktoaa4oJsVZYXxbXNtPIiFY/oWwopgORI6QSsY8eO6aWXXgp7r7q6OvR63759WrlyZdjnM2fO1KxZs+I+1sqVK7V69WpJkmEYuu2223T48GEdPnw46nZTp07VOeecE/fxBppV1KPXYsEEAADxM0vjoAUhAADOM1tzvRRgAQDQJzV1rXpq/d6YqZI+f1BPrd+r5bcMizsJK94EDZdhKC8nQ61nwpOuTrV16vRZr4ImUx1OAhYAIM3EugbdlxaEXp/fdP02ZH5uLlnfl+4uxDZNwEqTFoSSNH92mfYdabKV5O1xG5o3e+h17wKGipQuwDp+/LiefPJJy8+rq6vDCrIkyePxJFSAtXPnztDrYDCoH/zgB7a2e+CBB7RgwYK4jzfQaEEIAEDyuc0KsLgZDACA48xu0vppQQgAQJ9Ubamx3dLX5w9q/ZYaLV14UVzHsOrIYHX9WpKGZ0cWYJ1u94baEPZGAhYAIN3EKsDyByLX33haEJolWGZkuGSYpFRK1ut6R2fXfjpNCrCsUrOGorKSfC2ZVxGz8N3jNrRkXkXCrZ8BJF/6/OZCGFoQAgCQfGYtCO1evAYAAPZZpU4GzGIwAABATA3N7dp9qDGubXYdalRDS3tc21g9EGzVglCShpsUVJ1q8+pUr6KsT8aTgAUASC+xC7D60oLQb3o/OVrLQMsWhB/vp8MkUSudErAkafrk0Vp+y3RdVF6k3ncVDEkXlRdp+S3TNX3y6IGYHgCbUjoB64orrohIuErEggULYqZUPfvss30+zmBi3YKQAiwAAJxCC0IAAPqH1UNGPl8gaoIGAAAw98HRZsV79hqUVH20WcWV2ba3MUvQkKzXdknKyzYpwGr36lS7eQKWWcEWAABDmVnCVU99aUHY6Quo06RgKtrabVWc1en1KxgMmiZgpVsBltSVhLV04UVqaG5XbVO72jt9ys70aFxRtopH2P/7CsDASekCLCSPdQKW+QkvAACIn9s0AYtiZwAAnGZW9Cx1JU9mcs8VAIC4tXf4EtquLc7trBOworQgNEm0Ot3mjWhLGG08AABDmT9GF4a+J2CZtQy0Xrutiqk6vH55fQHTou90fpiquCBbk84vltvtkt8fUFPTmYGeEgCbaEGYpqwWLRKwAABwjlUCVpB2SAAAOMoyAYvCZwAAEpKdldiz2zlxbmeWoCFJGRatiiTzBKxAMKiPmtpMx5OABQBIN7HSrMwLsOydP3t9AXlN1u9o7YMtWxB6A+owSb+SpKwofwsAQKriN1eaogALAIDk87jM/9QKUIAFAICjrBOwOMcFACARU0oLFJnpHJ0haXJpQVzbeE0SNDxuQy7D+uhWBVXHGyPTIQxDyjUp2AIAYCiLlWbVpxaE3oBFApZ12YHH7ZLbFbm2d/j8lsXY6ZyABWDwogArTVlVIXdSgAUAgGM8HvMLxr4YEdAAACA+JGABAOCs4oJsVZYXxbXNtPIiFY/Ijmsbs+vRGVHaD0pSnlUBVkNkAdbw7IyoxVwAAAxFvoQSsGwWYPn8put3tPbBknmBVqfXHyUBiwIsAIMPBVhpigQsAACSz22RgOWnAAsAAEdZFWB5WXMBAEjY/Nll8rjtFS953IbmzS6L+xjmN3Cj37YYnpNp+n7z6U7bYwEAGMoCMdoJ9ikByxdQp0nRlNV5eTeze9PRWhBGS9QCgFTFb640ZXUSaxb5DAAAEuOxSuOIcQIMAADiY9mCkIeMAABIWFlJvpbMq4hZhOVxG1oyr0JlJflxH8ObwA3c4XG0FLRqVwgAwFAWK82qTwlYXosErBiJVVkmCVmdXr9pMZdEAhaAwYkCrDTltui1SwIWAADO8ZistRIJWAAAOM2yBSFFzwAA9Mn0yaO1/JbpmjhuhOnnnxqVq+W3TNf0yaMT2n8iN3DjSbUiAQsAkI5iXX/uSwGW1xeQ1xt/gqVZolWH168Ok31JFGABGJwowEpjpr12KcACAMAxVglYfj/rLQAATrIswOIcFwCAPisrydfX/3qa6WcXlhUmlHzVzeyB4FgJWHlxJGDlU4AFAEhDsYqp+tSC0OtXp0lHpVgF1KYtCC3aGdrZHwCkIgqw0pjZwkUCFgAAznG7LAqwbJ7MAgAAeyxbELLmAgDgiNxhGcod5ol4/8TJ9j7t1/QGbowCrAyPS8My7d2UpQUhACAdxSzACgYVDIaPsXvN+qzXL59Jwlas9dss0arT61cHLQgBDCEUYKUxCrAAAEiuDLd5C0IfCVgAADiKBCwAAJJv9MiciPdONPetAMvsenSsG7iS/RQsCrAAAOnIH4h9Lty74MpuAdaZdp/p+2adl8I+N1nfO73RErAoYwAw+PCbK42ZLnQmTxwBAIDEuC3SOEjAAgDAWVZtfyl6BgDAOaNHZke8V9/cHpGgEY9Or1kLwtiJF8Nttha0Ow4AgKHEb5JQ1VvvloN2WxCePus1fT/W+m0WDNLh9avD5G8BiQQsAIMTBVhpzGyh4+lgAACc47ZMwKIACwAAJ2VYtSBkzQUAwDGjCyILsDq9AbWc6Ux4n16zFoQ2Ei/sJluRgAUASEd2iqkSTcDq6LRIrIqRYGm2vnf6/FESsCjAAjD4UICVxjJNKpE7KcACAMAxVjeD7URAAwAA+0jAAgAg+cwSsCTpxMnE2xCaXY+2ai3c03CbLQjzc0nAAgCkl0AgKDulVJEFWH07f45VMGWWaNXpDajDojtTFi0IAQxC/OZKY2YLoVnkMwAASIxVC0LSOAAAcJZV0bOXAiwAABwzyiQBS+pbAZbXpADL7MHh3vJsJ2BRgAUASC92C6l6pmQFgkH1oaOwJDsJWJHruz8QVPtZX8T7hiF5LM7zASCV8ZsrjWWYVA5zcRoAAOd4LFoQkoAFAICzrBKw/BQ9AwDgmDFWCVjNbQntzx8ImLY7spWAZaOwymUYyhnmSWhuAAAMVnZbCfYcZ6dlYSyxErCsCrROtXlN92UY5tfWASCVcfaRxsyiHr0WMY8AACB+Vk/pkIAFAICzLBOwTFI1AABAYvJzMzUs062zneHXkBNNwLLqxpBpo+VQno0WhHk5GXJx8xYALL322muqqqrSnj17VF9fr7y8PI0fP15z5szRokWLlJeX5+jxDh06pDVr1mjbtm2qq6vT2bNnVVxcrClTpuhLX/qSrrvuOrlc1mtAbW2trrnmmoSO/dprr2ncuHGJTn1QsVuAFXC4ACtWAbXZfWlJOtXWaXssAKQ6CrDSmFmUMxenAQBwjlUBFmkcAAA4y+pCr4+UZwAAHGMYhsYW5epIXWvY+4kWYFldi86w0YJwuI0WhHbGAEA6OnPmjJYtW6bNmzeHvd/U1KSmpia9++67Wr16tR555BFdfPHFfT6e3+/XypUr9dOf/lTBXn3ujh8/ruPHj2vz5s167rnn9Mgjj2jMmDF9PmZPOTk5KioqcnSfqczuteeeXRqsirbcLsN2QVciLQgl6VR7ZAJWlo1ibABIRRRgpTGzJ4k6KcACAMAxbloQAgB68fv9OnTokPbs2aO9e/dqz549+uCDD3T27FlJ0o033qgHH3zQsePt2rVLu3fv1u7du3Xw4EGdPHlSJ0+elNfrVX5+vsrLy3XFFVfoxhtv1Kc+9SnHjtvfrFMnWXMBAHDS2KKciAKs+uYEE7AsujHEuoErScOzY7cgzLfRphAA0o3f79fSpUv11ltvSZKKi4u1cOFCTZgwQS0tLdq4caN27typuro63X777VqzZo3Ky8v7dMwVK1bohRdekCS53W5de+21mjlzpnJzc1VbW6sNGzbowIED2rlzpxYvXqznn39e+fn5EfspKirSj370I1vHXL16td5++21J0nXXXafsbPM2ukNRIi0IrbbJzvLotEmBlJmYLQgtiqqsWhACwGBEAVYaM1u8fBRgAQDgGBKwAAC93XnnnXr55Zf77Xh/+7d/q7a2NtPPGhsb1djYqG3btumpp57SV7/6VS1ZsqTf5uYk6wQs1lwAAJw0tig34r0zZ3063e611RawJ6sELFsFWCRgAUBCXnzxxVDx1YQJE7Rq1SoVFxeHPr/55pv10EMP6emnn1ZLS4vuuecePffccwkfb+vWraHiq5ycHP3kJz/RZZddFjZm8eLFuvfee7V27VodPHhQP/zhD3XvvfdG7Cs7O1tz5syJeUyv16tvfvOboa//+q//OuH5D0Z2H/6104JwWKbbfgFWgi0Iz5gmYFGABWBwogArjZldoPYHgvIHAnJH6bEMAADssUzjIAELANKW3x+e9FBQUKCCggIdOXIkaccsKirStGnTNHnyZI0bN07Dhw+Xz+fTn//8Z/3ud7/Tzp071dnZqR/+8Ifyer366le/mrS5JAsJWAAwtLz22muqqqrSnj17VF9fr7y8PI0fP15z5szRokWLlJeX5+jxDh06pDVr1mjbtm2qq6vT2bNnVVxcrClTpuhLX/qSrrvuOrliXC9dt26dli9fbvuYX/3qV/W1r32tr1PvdyVFOabv1ze3x12A1elNvAVhnq0CLBKwAKAnv9+vxx9/PPT19773vbDiq27Lli3T22+/rf379+udd97Rli1bNHv27ISO+Ytf/CL0eunSpRHFV1JXKta3vvUtbd++XTU1NVq7dq3+8R//UePGjUvomJs3b9bJkyclSeXl5brkkksS2s9g5WQC1rBM+6UEMROwLNZ3syPbKcYGgFREAVYas6oe7vQGlJ3FwgYAQF95rFoQksYBAGlr2rRpKi8vV0VFhSoqKnTuuefGfcM2Hr/85S81ceJEGYb5mrRkyRL95je/0d13361gMKgf//jHWrhwocaMGZOU+SSLy2XI7TIiLhpTgAUAg8uZM2e0bNkybd68Oez9pqYmNTU16d1339Xq1av1yCOP6OKLL+7z8fx+v1auXKmf/vSnCgbD15Djx4/r+PHj2rx5s5577jk98sgjg259TAazBCxJ+uhkm8pKIttFRWOZgGXRoqinnCyPXIahQND6/JoELAAIt337dtXX10uSZsyYoYqKCtNxbrdbt956q77xjW9IkjZt2pRQAVYgENC2bdskSYZh6IYbbrAc6/F4NG/ePD366KPy+/367W9/q9tvvz3uY0rSSy+9FHqdbulXkv1rz+EFWOZrcnaW/SSq2AlY9u89k4AFYLCiACuNWVUie/0BpU8nZAAAksdt1YLQ5lNIAICh54477ujX402aNCnmmBtuuEH//d//rddff10+n09vvfXWoLxIneFxyd8ZnjBGARYADB5+v19Lly4NtUUqLi7WwoULNWHCBLW0tGjjxo3auXOn6urqdPvtt2vNmjUqLy/v0zFXrFgRaovkdrt17bXXaubMmcrNzVVtba02bNigAwcOaOfOnVq8eLGef/555efHLjK69dZbNXPmzKhjysrK+jT3gWJVgFV/sj3ufXX6/KbvW7UW7skwDOXlZKj1TKflGBKwACDcm2++GXp99dVXRx3b8/Oe28WjublZZ8+elSQVFhaqoKAg6viea+PmzZsTKsD66KOPtHXrVklSRkaG5s+fH/c+BjurdoLRxlltk51lv5Qg1vodKyGrp6xMCrAADE4UYKUxqyeJvBbRzwAAID60QwIADBYTJ07U66+/LklqaGgY4NkkpmvdDb+R6/VR9AwAg8WLL74YKr6aMGGCVq1aFdYW6eabb9ZDDz2kp59+Wi0tLbrnnnv03HPPJXy8rVu3hoqvcnJy9JOf/CSiLdLixYt17733au3atTp48KB++MMf6t57742576lTp2rOnDkJzy2VFRdky+M25OuVrnEigQIsywQsGy0Ipa6Eq2gFWPkkYAFAmAMHDoReV1ZWRh07atQolZSUqK6uTg0NDWpqalJhYWFcx+udLhmPnnONx69//Wv5/V3nhZ/73OdUVFSU8BwGK2dbEMaRgBWrBWEcBVh2/xYAgFRDn7k0Fi0BCwAA9J1lC0ISsAAAKebDDz8Mve55s3swMXva1qqNAgAgtfj9fj3++OOhr7/3ve+ZrkfLli3TBRdcIEl65513tGXLloSP+Ytf/CL0eunSpRHFV1JXKta3vvWtUCLH2rVrVVtbm/AxhwK3y9CYwpyI9080O1eAZScBS5KGZ0cvsCIBCwDC1dTUhF6PGzcu5vieYw4fPhz38UaMGKGMjK7f1U1NTWppaYk6/siRI6HXZ86c0UcffRT3MdetWxd6PRiTnZ3gs3kebCcBa1imkwlYtCAEMPRRgJXGrHrxdnrNo58BAEB8SMACAAwGmzdv1quvvipJysrK0mc/+9mBnVCCzC72Wt3YBQCklu3bt6u+vl6SNGPGDFVUVJiOc7vduvXWW0Nfb9q0KaHjBQIBbdu2TVJXK7sbbrjBcqzH49G8efMkdRWK/fa3v03omEOJWRvCRBKwrFoQ2r1BmxejwGo4CVgAEObUqVOh1yNHjow5vmfLwJ7b2uXxeHTxxRdL6krDqqqqshzr9/u1fv36sPdaW1vjOt62bdtCDxeNGTNGs2fPjm/CQ4Tf71wCVnaWvUKoDI9LLsP8YeRu8RRVxVOsBQCphBaEacwyAYsL1AAAOMLjMj9RtHsSDACAk7Zv3x564rizs1N/+ctftHXr1lB6iMfj0X333TdoE7DMCp9JnQSAweHNN98Mvb766qujju35ec/t4tHc3KyzZ89KkgoLC8NuMJvpTsCSugqXb7/99oSOO1SUFEcWYLWc6VRHp19ZcbQq6rRMwLLZgpAELACIS1tbW+h1VlZWzPE9x5w5cyahY950003avn27JGnlypWqrKzUJZdcEjYmEAjo/vvvj0jZOn36dFzH+tWvfhV6feONN8rtTp0Upfz8YXGNd7mM0P8WFkauu9Hk2iyKzsnNDO276YzXdMzIEdm29pWV4Y45z6xs++tyQX523P/uoaYvPwMY/Pj+D14UYKUxqxNZCrAAAHCG26IFod0YaAAAnPT9739f77//fsT7hmHo8ssv19e//nVdfvnlAzAzZ5CABQCD14EDB0KvKysro44dNWqUSkpKVFdXp4aGBjU1NamwsDCu4wWDiRfo9pyrleeff14/+clP9Je//EWBQEAjR47UlClTdPXVV+vGG29Udra9m5mpqsQkAUvqakN47ug82/vxes3XaavODb1FS7hyuwzlDOP2BwAMtOuvv15VVVXasmWL2tradMstt+jaa6/VzJkzlZubq9raWm3YsEHV1dUqLCxUR0dHqNjLZfFwq5nTp0/rf/7nfyR1neP+7//9v5Py70mU26JTQiyGYVheY7Zi/88cIzSvoMUhcm0WTWVlumP+G3NiFE73NCzLk/D/Z0NNIj8DGDr4/g8+nIGkMauoR6snjwAAQHysThJJwAIApJIxY8bo05/+tMaPHz/QU5EU/5PBUtcTgWYFWDJ4UjBd8HRoeuP7P/jV1NSEXo8bNy7m+HHjxqmurk6SdPjw4bgLsEaMGKGMjAx5vV41NTWppaVFI0aMsBx/5MiR0OszZ87oo48+0pgxYyzH7969O+zruro61dXV6fXXX9d//Md/6Lvf/a4+97nPxTXnVGKWgCV1tSGMpwDLsgWhzQKsvCg3cvOyM2K2QgKAdJOTkxNKRe7o6JDHE/02cUdHR+h1bm5if2O5XC49+uijuvvuu/XKK6/I5/Npw4YN2rBhQ9i4UaNG6YknntDixYtD7+Xn59s+zqZNm9Te3pX8dPnll6u0tDSh+SaL3x/fvVeXy5BhGAoGgwrEmezc6TVfX83Gdc/LapthNpMtMz3umP9GQ10F0naSqjMzXHH/fzbU9OVnAIMf3397UrFQkwKsNGbVP5cnhAEAcIbbZchlSL3/PqYACwAwENauXRt63dbWpqNHj+q1117Tz3/+c61cuTL0v1deeeUAzjLxiyfmLQgDKXkxBsnD06Hpje//4HXq1KnQ65EjR8Yc37NlYM9t7fJ4PLr44ou1fft2BYNBVVVV6bbbbjMd6/f7tX79+rD3WltbTQuw3G63Lr74Yl122WU677zzlJOTo1OnTmnPnj367//+bzU3N6upqUn//M//rIcffljXX3993HNPBWMtE7DaTN+3YnUd2nYLwigtBqOlYwFAuho+fHioAOvkyZMxi6qam5vDtk1UXl6eHn/8cf3+97/XunXr9O6776qhoUEul0vjxo3T3Llzddtttyk3NzeUfmUYhoqLi20fo2f7wb/+679OeK7J0tp6Vj6LwmMzhYW5crsNBQJBNTXF1/6xpdVeC8KW1vbQvpubzbcJ2Jyz2yVb88zMcKu9wxdznK/TF/e/e6jpy88ABj++/7F5PG6NHJkz0NOIQAFWGsu0SMDyxvEHAAAAiM7jdkWkS/ppQQgAGGA5OTmaMmWKpkyZonnz5unLX/6yTpw4odtvv12/+tWvNHny5AGbWyJPuXYlYEWe43Z6A2n/1Gy64OnQ9Mb3355ULkhta/ukcCcrKyvm+J5jum/Uxuumm27S9u3bJUkrV65UZWWlLrnkkrAxgUBA999/vw4fPhz2/unTpyP2N336dG3evFljx46N+GzhwoX6t3/7N/37v/+7fvvb3yoYDOob3/iGLr30Up1zzjkJzd8JiaZOji3KkWFEtjhqbfPFlULnsii0GjN6uHmyZS/njLEuBigckU0iXhKQOAh+Bga3srIy1dbWSpJqa2tjpk52j5Wk888/v8/Hv/LKK6M+8FNdXS2/v+se5XnnnWe76OvgwYN6//33JXUViv3VX/1Vn+c6mNl9+Lfn381Wf0NnelwyJMXao9U958hxLrV3xB5n1cUJAFIdBVhpzLoAi4vTAAA4xe12Sb3WVh83hQAAKeTcc8/Vv/7rv+quu+6S1+vVk08+qZUrVw7YfOJ9MljqejLQ7EZtB0/Npg2eDk1vfP9jS9WngwfS9ddfr6qqKm3ZskVtbW265ZZbdO2112rmzJnKzc1VbW2tNmzYoOrqahUWFqqjoyNU7OVyRa45sVr55uXl6eGHH1ZDQ4O2bdumjo4O/eQnP9G3vvWtpPz77Ei0KC/D41ZxQbbqT4anZXzU1BbXPn0m16FdhpSV6ZZho33gyCgFZAV5WSlddDjYkTgIfgYGp0mTJumtt96S1NUud+bMmZZjGxoaQu1+i4qK4m73m4ht27aFXl9++eW2t+uZfnX99ddr2LD4C4yHEjst/nqPs9rG7TaUkeFSpzf6vWO77YOzbKZc2i3oAoBUQwFWGrNaDHundAAAgMSZtkMiiQMAkGKuvvrq0OueF70HE7M118eaCwCDQk5OTqglUkdHhzye6JetOzo+iU6I1T7Jisvl0qOPPqq7775br7zyinw+nzZs2KANGzaEjRs1apSeeOIJLV68OPRefn5+Qsd0u92688479eUvf1mS9Lvf/W5AC7ASTZ00DENjC3MjCrCON5yOa59nOyMLrjMz3B+ncMS+eZw7zPrnJD83k3PvJCBxEPwMxJbKxZ9XXXWVfvazn0mS3nzzTf3TP/2T5dg33ngj9Pozn/lM0ucWDAa1bt260NcLFy60tZ3X6w1rFZyK7Qf7m93/NsMLsMzXTLdhKNPjjl2AFUcClh1ZNscBQKqhACuNkYAFAEDyeUyeBrT7FBIAAP0lLy8v9Lr7BvhgY5aA5bPZegEAMLCGDx8eWn9OnjwZs6iqubk5bNtE5eXl6fHHH9fvf/97rVu3Tu+++64aGhrkcrk0btw4zZ07V7fddptyc3ND6VeGYai4uDjhY15yySXKyspSR0eHjh8/rvb2dmVnZye8v75INHXS7e5qQ7j7UPhn9c3tOlF/yrQo2szpM5E9iDxul+0kuz8da7b8bPv+v+iSCUUqK0msWA7mSBwEPwPRpXri5IwZMzRq1CjV19dr27Zt2rt3ryoqKiLG+f1+Pfvss6Gvr7vuuqTP7YUXXtC+fftC85w2bZqt7V5//XU1NjZKkqZMmaILL7wwaXMcLHwWxVS92WlB6Ha7uoqm2k0/DrHTOliy31qQBCwAgxXlo2nMajH0xnnSDQAArHm4GQwAGASOHDkSet0frSWSwewclweMAGBwKCsrC72ura2NOb7nmPPPP7/Px7/yyiv18MMP67XXXtP777+vd999Vxs2bNDXv/51FRQU6PDhw/L7u66ZnnfeeX0q+nK5XBoxYkTo69bW1j7PfyCUFEUWyQWDUkPLWdv7MOvEYDcZY0f1CX3/hXctP/+oqV0PrN6hHdUnbM8HAIY6t9utr3zlK6Gv77rrrlDxUk8PP/yw9u/fL0m69NJLddVVV5nub926dZo8ebImT56sW2+91fK47733njo7O00/CwaD+uUvf6lvf/vbkrpSMb/zne/Y/jf1bD9I+lUXJ1sQulxdCVix2G1BaLewym6hFgCkGhKw0pjV4kULQgAAnONx0YIQAJD6XnjhhdDrSy+9dABnkjjTtr82n/wFAAysSZMm6a233pIk7d69WzNnzrQc29DQoLq6OklSUVFRvxQO92zPe/nll/dpX4FAIKzoKtF2hgNtbLF5wsuJk+0aW2gv/aXT5EHgDBs3eWvqWvXU+r0xH27y+YN6av1eLb9lGElYAPCxm266Sa+++qq2bt2qgwcPav78+Vq4cKEmTJig5uZmbdq0STt27JDUtUatWLGiz8f88Y9/rJ07d+rqq69WZWWlRo8eLa/Xq2PHjunll19WdXW1JGnYsGF69NFHVVpaamu/H330Uejvh8zMTP2v//W/+jzXocBv8+FfWwlYLsNWcZXtFoS2C7XIkAEwOFGAlcYyaEEIAEDSeTyRLQh9tCAEAPTRunXrtHz5ckld7Rl6tofotmbNGpWVlemKK66QYUSuR1JXa4mf/exnev7550PvffnLX07OpJPMPAGLNRcABoOrrrpKP/vZzyRJb775pv7pn/7Jcuwbb7wRev2Zz3wm6XMLBoNat25d6OuFCxf2aX/vvfeezp7tSokaO3bsgLUf7KuxJglYknTiZJukIlv78HpNErBs3Jit2lJjO1na5w9q/ZYaLV14ka3xADDUeTwePfbYY1q2bJlef/111dfX64knnogYN3bsWK1cuVITJ0505Litra3auHGjNm7caPr5hAkTdP/998f1QNBvfvObUELl3LlzVVBQ4MRUBz2rYqre7CRguV2GreIquy0IScACMNRRgJXG3C5DHrcRcbJKARYAAM5xk4AFAOjh2LFjeumll8Le637aV5L27dunlStXhn0+c+ZMzZo1K+5jvf/++7r33ntVUlKiK6+8UpMmTVJRUZEyMjJ06tQpHThwQK+99pr+/Oc/h7ZZsmSJZsyYEfexUoHZBV+fP6BgMGhZgAYASA0zZszQqFGjVF9fr23btmnv3r2qqKiIGOf3+8OKjq+77rqkz+2FF17Qvn37QvOcNm1awvsKBAJ67LHHQl9/9rOf7ev0BkxJoUUBVnO77X2YtiCMcQO3oblduw9FtsuKZtehRjW0tKt4xOAsdgMAp+Xl5enJJ5/Uq6++qqqqKu3evVuNjY3Kzc1VaWmp5s6dq0WLFvWp5W5PS5cuVWVlpbZv367a2lo1NjbKMAwVFRWpoqJCc+fO1Re/+EV5PPHdtu5ZIP2///f/dmSuQ4H9FoSBHq+tWxDaKa6yWzBld5zdQi0ASDUUYKW5zAy3fH5f2Htm0c8AACAxHrObwSRgAUDaOn78uJ588knLz6urq8MKsqSuJ5QTKcDqVldXp1/96ldRxwwfPlz/8i//MmjTryTzFoRS14Vkj5sCLABIZW63W1/5yld03333SZLuuusurVq1SkVF4UlKDz/8sPbv3y+pq2XuVVddZbo/O0mRUlca1dSpU5WZmRnxWTAY1Nq1a/Xtb39bkpSTk6PvfOc7pvt59913deDAAd1www3KysoyHdPW1qZ77rlHb7/9tqSuVknRkr5SXfYwj/JzMtTa5g17/8RJ+wVYXtMWhNFv8n5wtFnxnlEHJVUfbVZxJQVYANDTnDlzNGfOnIS3X7BggRYsWBBz3NSpUzV16tSEj2Plf/7nfxzf51DQs7AqGidbENpPwIo9zpD9VoUAkGoowEpz5i0aSOUAAMApHlfkDV+/zVYJAAD0xTe/+U1dc8012r59u/bv36+jR4/q5MmT8vl8ysnJUVFRkSZPnqyrrrpKX/ziFx17unmgWF3w9fkDlsVZAIDUcdNNN+nVV1/V1q1bdfDgQc2fP18LFy7UhAkT1NzcrE2bNmnHjh2SpPz8fK1YsaLPx/zxj3+snTt36uqrr1ZlZaVGjx4tr9erY8eO6eWXXw4VRQ8bNkyPPvqoSktLTffT2Nioe+65Rw8++KA+/elPq6KiQiUlJcrOztapU6e0b98+bdq0Sc3NzZIkwzD07W9/W+PGjevzv2EgjRqZHVGAVd/XBKwYiRftHb6on1tpS3A7AAAGG/sJWLFbELpstiDM9DiXbJWZ4SbFGsCgRQFWmjNb6CjAAgDAOWYJWLQgBID0dcUVV0QkXCXCzpPGeXl5mjt3rubOndvn4w0GZmuuJPkofAaAQcHj8eixxx7TsmXL9Prrr6u+vl5PPPFExLixY8dq5cqVmjhxoiPHbW1t1caNG7Vx40bTzydMmKD7779fl156acx9tbW16ZVXXtErr7xiOWbUqFH69re/PajbD3YbXZCjQ39uDXvvo6Y2nTjZptEjc2Jub3YdOlaCRnZWYrc0chLcDgCAwcbuw792CrDsJmDZSbaS7CVb2d0XAKQizjrSnNlCRwEWAADO8bhMCrBoQQgAgOMyLFKufBQ+A8CgkZeXpyeffFKvvvqqqqqqtHv3bjU2Nio3N1elpaWaO3euFi1a5Fhq49KlS1VZWant27ertrZWjY2NMgxDRUVFqqio0Ny5c/XFL35RHk/0y+izZs3SE088oV27dmnXrl2qq6tTc3OzTp06pWHDhqmoqEhTp07VZz/7WV177bWWbQoHG7NiqUBQWv7UH1RZXqT5s8tUVpJvuX2nN7IFYawbs1NKC2RIcbUhNCRNLi2IYwsAAAYvu9ee7bUgdNlKrbLbgjArM/a+smwcDwBSFQVYac5s0TSLfgYAAIlxuyPjkrkRDACA8yxbEHKOCwCDzpw5czRnzpyEt7eTFClJU6dO1dSpUxM+Trfc3Fxdc801uuaaa/q8r8Hi7d112rK7zvSzoKRdhxq170iTlsyr0PTJo03HmSdgRb/pWlyQrcryIu061Gh7rtPKi1Q8Itv2eAAABjN/wN45cHgClvk2Lpdhq7jKbtGUnVaFdgq+ACBVkeGX5mhBCABAcnlM0jhIwAIAwHmWLQhZdwEAcNSBoyf1g+d3WqZldPP5g3pq/V7V1LVGfBYMBk0fBLbTmmj+7DJ5TB52MuNxG5o3u8zWWAAAhgK7155ttyC00RLQbgKWnX1l0YIQwCDGb7A0Z96CMDL6GQAAJMasAIsELAAAnGfZgpCHjAAAcNSal6ttn9f6/EGt31Jj8r759hk2brqWleRrybyKmEVYHrehJfMqorZBBABgqHG2BaHhaGqVnaQsO8cDgFRFAVaaowUhAADJRQIWAAD9w+qJWy+FzwAAOOajpjbt+OCjuLbZdahRDS3tYe9ZXYO2e9N1+uTRWn7LdF1UXqTeZViGpIvKi7T8lumW7Q8BABiq/H7nErBcLsNWOqWdMZK9Qq2sTAqwAAxenoGeAAaW2QVqWhACAOAct8kTuXZPggEAgH1WLQhZdwEAcM6ew40Kxrm0BiVVH21WcWV26L1Or1UBlv1nxstK8rV04UVqaG5X9bFmtXX4lJPl0eTSAhWPyI69AwAAhqBYLYLNxkVNwHIwtSrLTjGXzTQtAEhFFGClObOoRwqwAABwjlmxsy/AWgsAgNOsWhCSgAUAgHPaznoT267DF/a11+c3HWeVaBlNcUG2igsouAIAQJL8Nq899xwXLQHLztqcaaOFcNc4GwlYCfwtAACpgt9gac5soaMACwAA57hdJGABANAfMiyeuPVRgAUAgGNyhmUktl1W+LPgli0ISb0AAKBPrIqpoo0z28YwJJdhLwHLbgG1rTQtWhACGMQowEpzZgtip8+vYLw50gAAwJRZOyR/IMhaCwCAwzyeyKJniQIsAACcdOH5RTLMl1xLhqTJpQVh71k9BJxIAhYAAPiE3Yd/Y7Ug7H6w2E57YLsF1Fk2krKybLYzBIBUxNlMmjNbEINB+9XRAAAgOo/L/M8t1loAAJyV4bZKwGLNBQDAKWMKczR9ypi4tplWXqTiEeEtAju95i0I7dzkBQAA1pxKwHLFU4DlZAKWzXaGAJCKPLGHYCizWhC9voA8bhY4AEgXfr9fhw4d0p49e7R3717t2bNHH3zwgc6ePStJuvHGG/Xggw86drxbb71V27Ztsz3+tdde07hx4xw7fn8yS8CSup5E4mEeAACcY5WY4bNI2AAAAIn5my9M1nsH6m2lTHrchubNLot43zoBixNlAAD6IrECrMh12f3xg8W2iqZsrt92xmXRghDAIEYBVpqzWjQ7fQFlZ/XzZAAAA+bOO+/Uyy+/PNDTGJI8LvPeDF0ntZxMAgDgFKuiZ1oQAgDgrEmlI/WvX75UP3h+R9SkSY/b0JJ5FSoryY/4rNOiAIsELAAA+sasmMqM3RaEsdoDe9xGKC0rFjvpVnaLuQAgFVGAleasE7DMI6ABAEOT3x/+e7+goEAFBQU6cuRI0o/9ox/9KOaYoqKipM8jWaxvBtMOCQAAJ1kmYFGABQCA42ZVlmj5LdP1ZNUe1Tefjfh8WnmR5s8uMy2+kqROi+vPGbQdAgCgT8yKqczYbkEYIwErnvRKj9slt8uImtKVZSNxCwBSFQVYac5q0bSKgAYADE3Tpk1TeXm5KioqVFFRoXPPPVfr1q3T8uXLk37sOXPmJP0YA6k7qrk3u1HQAADAngy3xQNGFD0DAJAUZSX5mnHBGG16+8OIz/75hguj3kD1eq0SsLjpCgBAX/hsXne2m4AVK53STqpV+Hi32jt8ju0PAFIJBVhpjgIsAIAk3XHHHQM9hSHL4zaPXyaNAwAAZ1mlTvpZcwEASBqPRQG03x+QohRgWbUgjNXmCAAAROe3+RBSrAQst80ErHjbB2dmuNTeYf05CVgABjPOZtKc1aJodQIMAADiY3kzmAQsAAAcZXXD1ksBFgAASWP90FH0c16rB4DjvYkLAADCOd6CMGYCVnwFU1kx0i4pwAIwmHE2k+YsE7C8/n6eCQAAQ5NVC0ISsAAAcJZVC0LWXAAAkifRc95On/n1ZxKwAADoG3/A3jmw3RaEsdbm+BOwYiRqUYAFYBCjBWGay7Doo8sTwgCA/rJkyRLt27dPJ0+eVHZ2tkaPHq1LLrlE119/vWbOnDnQ0+uzDI/508B2o6ABAIA9VqmTsRI4AABA4iwTsGKkb1gnYHHTFQCAvrDbeaFnoVa0BCzDMJTpcUVpHxxnApbFvWm7nwNAKqMAK81ZVRF3einAAgD0j9/97neh116vV62trfrTn/6kF198UTNnztT3v/99jR49euAm2EdWTwPTghAAAGe5XYYMQwr2WmJ9FheJAQBA33ksEij9sRKwLK4/Wz0wDAAA7LH74G+sFoTdCVhSVwqWVQFWZpxrNwlYAIYyCrDSnNUTRSRgAQCSbcSIEbryyit14YUXasyYMXK73froo4/09ttv680331QwGNQf/vAHLVq0SL/85S81atSogZ5yQqzTOFhrAQBwkmEY8rhdEYkasRI4AABA4txWCVgxbv56TVoQetyGXIb5/gAAgD12H/y124JQ6iqKOnPWZ7qfeNMrY7UszKIAC8AgltIFWH6/X4cOHdKePXu0d+9e7dmzRx988IHOnj0rSbrxxhv14IMPJuXYr732mqqqqrRnzx7V19crLy9P48eP15w5c7Ro0SLl5eUl5bj9zaoq2SoCGgAAJ/zLv/yLKioqlJmZGfHZ3//932v37t36+te/ruPHj+vPf/6zvvGNb+gnP/nJAMw0XH7+sLjGu1yGPC7zi8e5uVkqLMx1YlpIYd1R3S6Xwfc7DfH9B/pfhsekAIvzWwAAksYqASvWQ0dmKRrxtjACAACRerYWjD4uegKWq2cBVpSiqXgTsLIyYyVgkYYJYPBK6QKsO++8Uy+//HK/HvPMmTNatmyZNm/eHPZ+U1OTmpqa9O6772r16tV65JFHdPHFF/fr3JLBugVh5BNIAAA45ZJLLon6eWVlpX7605/qhhtuUGdnp958803t2rVL06ZN66cZmnNbXFiOxioBKxBMbH8YnAzDsHwyHEMf33+g/2SYrK2kTgIAkDzWLQijp2+YFWDFSsQAAACx2U3ACi/AilyX3a5P1uVoRdLxrt+xErNoQQhgMEvpAiy/P7wIqKCgQAUFBTpy5EjSjrd06VK99dZbkqTi4mItXLhQEyZMUEtLizZu3KidO3eqrq5Ot99+u9asWaPy8vKkzKW/WC2KtCAEAAy08vJyzZ8/Xy+++KIk6Xe/+92AF2D541wfuxKwzNfaTq8/7v1h8HG5DBmGoWAwaBrljaGN7789FKPCSWaFzxRgAQCQPFapz7HWX6/JA8AZFGABANBndq9BxdOCMCtKKlW8CZbREq4yPS7aEQMY1FK6AGvatGkqLy9XRUWFKioqdO6552rdunVavnx5Uo734osvhoqvJkyYoFWrVqm4uDj0+c0336yHHnpITz/9tFpaWnTPPffoueeeS8pc+otVFbHXywVqAMDAu+KKK0IFWIcOHRrg2UitrWfl89lPiSwszLVMwGpuaVNT0xmnpoYUVViYK7fbUCAQ5Pudhvj+x+bxuDVyZM5ATwNDiFkKhy9GAgcAAEicVTG9L0b7I9MELBIvAADoM19CCVjRWxBGK5KOt2VgtPWevwUADHYpXYB1xx139Nux/H6/Hn/88dDX3/ve98KKr7otW7ZMb7/9tvbv36933nlHW7Zs0ezZs/ttnk4jAQsAkMoKCwtDr0+dOjWAM0mcVdsxu1HQAADAPrOLwpzfAgCQPB6Lc95YBdBekwIsErAAAOi7WG2Au8WTgBW1aCrOBKysKPuKlrQFAIMBv8U+tn37dtXX10uSZsyYoYqKCtNxbrdbt956a+jrTZs29cv8ksUqFrKTBCwAQAo4efJk6PXw4cMHcCaJM0vikGiHBABAMpitu7T8BQAgeazOeWOtv50m6dJWDwsDAAD7/DFSKD8ZFz0BK6wAy9EErGj7IgELwODGGc3H3nzzzdDrq6++OurYnp/33G4wcrkM05NknhAGAKSCP/7xj6HXZWVlAziTxFlfjCYBCwAAp5GABQBA/7JKfU4kAYsCLAAA+iYQDCpo87JzfC0InUvAijaeAiwAgx1nNB87cOBA6HVlZWXUsaNGjVJJSYkkqaGhQU1NTUmdW7KZXqD2Rj6BBABAf6qpqVFVVVXo68997nMDOJvEWbZjoAUhAACOMzu/9flYcwEASBaPK7HUZ7MODNFu7gIAgNjMWgnaGRurBWG01oDxFlBHS8CK1p4QAAYDCrA+VlNTE3o9bty4mON7jjl8+HBS5tRfzBbGTpMnkAAAiGXdunWaPHmyJk+eHNayt6dnnnlGO3fujLqfffv2afHixero6JAkzZ49WxdddJHj8+0PibZjAAAA8TNbd3022y8AAID4WT10ZJak0ZPXrAVhnC2MAABAuHi6LnSlZXWN70sCVkac63e0Iiv+FgAw2HkGegKp4tSpU6HXI0eOjDm+oKDAdNuBkJ8/LO5tuhdNl8tQVqZbOhP+ueEyVFiY68T0kIJ6fv/5PqcnfgbQ27Fjx/TSSy+FvVddXR16vW/fPq1cuTLs85kzZ2rWrFlxH+sPf/iDvvOd76i0tFSzZs3SpEmTVFBQIJfLpRMnTugPf/iD3njjDQU+vln6qU99St/97ncT+FelBrfl08CkcQAA4DTzBCwKsAAASBarh45iJmCZrM9m6zgAALAvVgG02XiP2zDdrmcCVrTCqLhbEEYpwCIBC8BgRwHWx9ra2kKvs7KyYo7vOebMmTNRRiaf2+Ik1w7D+LgAq5dOX6BP+8XgYBiG3BZPqSE98DOAbsePH9eTTz5p+Xl1dXVYQZYkeTyehAqwuh09elRHjx6NOmb27Nn67ne/qzFjxiR8nIHm8Vg9DczNYAAAnGZagEXqJAAASWN1XSnWQ0dekwKseG/gAgCAcPFecw4EgpI7dgvCaG0G402tyoq2L/4WADDIUYA1BCTSwsjlMmQYhoLBoDJMCq06vX5aIw1hPb//8fSDxtDBz0BsFKEmz913363Pfe5z2rVrlz744AM1Njbq5MmT8nq9ysvL06c+9Sldcskl+l//638N2raDPVm3IOS/PQAAnGbagpA1FwCApLE+57W+tuwPBEyTNkjAAgCgb6wSsDxul+nDSd3jzVsQfrIuR2tB6GgClkloCAAMJhRgfSwnJ0ctLS2SpI6ODnk80f+v6ejoCL3OzR3Y9l2trWfl8/nj2qawMFdut6FAICiXEfmUUlu7V01NsZO9Gprb9cHRZrV3+JSd5dGU0gIVF2THNRf0v57ffzvfZww9/AxE5/G4NXJkzkBPo19dccUVEQlXiViwYIEWLFgQdUxpaalKS0u1cOHCPh9vMLBsx0DxIwAAjiMBCwCA/pVIC8JOr/ln8SZoAACAcFYP3Gd6YhVgRX7m7nH/OCtaC8J4E7CitiDkbwEAgxsFWB8bPnx4qADr5MmTMYuqmpubw7YdzMwuUJtFQPdUU9eqqi012n2oUT2XckNSZXmR5s8uU1lJvrMTBQBgEPJYtGOgBSEAAM4jAQsAgP7Vsz1RT9HWX6trz9HSNQAAQGxWD/1mZLikjsj3A4GgAsGggiab9WwzHG2Njnf9jlawRQtCAIMdZaQfKysrC72ura2NOb7nmPPPPz8pc+ov8RZg7ag+oQdW79CuXsVXkhSUtOtQox5YvUM7qk84O1EAAAYht4sWhAAA9BcSsAAA6F/Wqc9RErAsujlk0oIQAIA+sWoBnGVR2OQPBC1Ts1w9iqyjF03Ft37TghDAUMYZzccmTZoUer179+6oYxsaGlRXVydJKioqUmFhYVLnlmxmC6PVSXBNXaueWr835hPEPn9QT63fq5q6VkfmCADAYOVyGWEnq90owAIAwHlmN4H9Hz/RCwAAnOe2Sn1OIAGLAiwAAPrGHy0By0QgSgFWz5TLaMlU0QqqTMdH2xd/CwAY5Pgt9rGrrroq9PrNN9+MOvaNN94Ivf7MZz6TtDn1l3gSsKq21Nhu3+DzB7V+S02f5gYAwFBg1oYw2tPAAAAgMWbnt5L1U8AAAKBvXIZh2oYwWgJlp5cWhAAAJINVMVWGRWKlPxCwLNrqub5bFXBJiSRgWY/PirOYCwBSDQVYH5sxY4ZGjRolSdq2bZv27t1rOs7v9+vZZ58NfX3dddf1y/ySyezE1qwAq6G5XbsPNca1712HGtXQ0m5rbENzu7bsqtMr249py646NTTb2w4AgFRnmsZBAhYAAI6zaoPk9bHuAgCQLGYpWNEe4rVMwIpyQxYAAMRmVUxlVSTlDwQtt+nZ1cGqhaFk/SCUFY/bZVq8LdGCEMDg5xnoCfSHdevWafny5ZK6Cq16FlB1c7vd+spXvqL77rtPknTXXXdp1apVKioqChv38MMPa//+/ZKkSy+9NCw5a7CySsAKBoMyjE8WwA+ONiveS9ZBSdVHm1VcmR16r6G5XR8cbVZ7h0/ZWR7lDvPojfePa/ehxrD9G5Iqy4s0f3aZykry4zwyAACpw+xmMAlYAAA4z+rCb7QUDgAA0Dcel0udCl9ro6VPdvr8pu/HewMXAACEs3roN8MiWcpuC0KrNdrtMiwfhIomM8Ot9g5f5PukYQIY5FK6AOvYsWN66aWXwt6rrq4Ovd63b59WrlwZ9vnMmTM1a9ashI5300036dVXX9XWrVt18OBBzZ8/XwsXLtSECRPU3NysTZs2aceOHZKk/Px8rVixIqHjpBqzquegup5SyvB8sriaLYR2tH28XU1dq6q21EQUWlkJqitBa9+RJi2ZV6Hpk0cndHwAAAaa2RM9JGABAOA8CrAAAOh/HrMELIubuZLUaZWAxU1XAAD6xG/x0G9fE7CsUioTTa/MzHCpvSPy/SzSMAEMcildgHX8+HE9+eSTlp9XV1eHFWRJksfjSbgAy+Px6LHHHtOyZcv0+uuvq76+Xk888UTEuLFjx2rlypWaOHFiQsdJNVYXqL0+f9hn2VmJ/bjUnjit13fWas1rB6NGT1vx+YN6av1eLb9lGElYAIBByWOy1nIjGAAA51k9ecu6CwBA8sR7zmvVgpAELAAA+saqmMpqje0qwDJfl92uT7axKpLuOSYeWRaJXJkW7wPAYMEZTS95eXl68skn9aMf/Uhf+MIXVFJSoszMTI0cOVIXXXSRli1bpo0bN+rSSy8d6Kk6xroAK3zBnVJaIPOOvNG9tatOz758IKHiq24+f1Drt9QkvD0AAAPJY3IianUyDAAAEmd5fkvyJAAASWN6zhtl7e30mrcgTDRFAwAAdLG65mxVQGW3BWFd0xnTMafbvXrkxfdVU9dqe441da1qPdNp+tmLv/tTXPsCgFST0glYV1xxRUTCVSIWLFigBQsWxLXNnDlzNGfOnD4fezCwWnR7R0EXF2TrwvMLtftwU39MK8KuQ41qaGlX8YjsATk+AACJcpu0Y/CTxAEAgOOsErBYdwEASB6zc97EErBIvQAAoC+sCqAzLIqc7bQg3FF9Qk+t32t5zF2HGrXvSJOWzKvQ9Mmjo86ve19WoR0HjrXogdU7bO0LAFIRj5TAdgKWJI0tzEn2dCwFJVUfbR6w4wMAkCizm8EkYAEA4DzrBCwKsAAASBazc95oBVi9H/ztlkkLQgAA+sQ6Act8jY2VgFVT1xq1YKqbzx/UU+v3Rk2vcnJfAJCqOKNBzAKshuZ2bdlVp01vH9Eb7x3vz6lFaOvwDejxAQBIhMf0aWAKsAAAcJrV+a3P4kYvAADoO9Nz3igPHXl9Fi0IKcACAKBP/IH4UiajJWC5XYaqttTYvo7t8we1fkuN5edO7gsAUlVKtyBE/8jMMF90j/ylVb9+67B2H2pUqtwizsniRxYAMPiYJ2BxIxgAAKdZtSCMdhMYAAD0jdvsnDdaApaXFoQAACRDvAlY0Qqwzpz1avehxriOv+tQoxpa2lU8Ijvs/Ybmdsf2BQCpjEdKoAyLC9SrXz6gXTaKryrPL3R+UiYMSZNLC/rlWAAAOMn8YjQ3ggEAcBoJWAAA9D+PK77UZ69VC8IMblcAANAXVu0EE2lB+JemtrgDOoKSqo82R7z/wdFmx/YFAKmMMxoow+LE1qriuSdDUklRrsMzMjetvIgqZwDAoBRvOwYAAJAYj1UBVpQUDgAA0DdmCZTR1t5OkxaEhtHV6ggAACTO6t5uhkU3JH8gYLlNog8ytXX4It5rN3kv0X0BQCqjAAuWCVh2BCXtP9Lk3GQseNyG5s0uS/pxAABIBtMWhNwIBgDAcVbnt9FSOAAAQN/EX4AV+VmG2yXDoAALAIC+sLrmnEgLwmGZnoTmkJMVuV22yXuJ7gsAUhkFWOhztPOx+jNK9qnxknkVKivJT/JRAABIDvOL0dwIBgDAaSRgAQDQ/9xmqc8W57w1da3ac7gx4v1OX0CPvPi+aupaHZ8fAADpwqrrQkYCLQjPHZMX9/1fQ9Lk0oKI96eUFji2LwBIZRRgoU8JWN3Gjc5zYCbWzinunzaHAAAkg9nFaH+AG8EAADjNOgGLdRcAgGSxm/q8o/qEHli9Q82nO033s+tQox5YvUM7qk84PkcAANKBVTFVpseqBaF1AtbI4VmqLC+K6/jTyotUPCI74v3igmzH9gUAqYzcPlj2/Y3HBeNHqq7xTEJpHoa6FtGrLz5Huw416o33jkeMee9gg0qKIouwGprb9cHRZrV3+JSd5dGU0gIVF7AYAwBSi9nNYBKwACA9+f1+HTp0SHv27NHevXu1Z88effDBBzp79qwk6cYbb9SDDz7o2PFOnz6trVu36o9//KP27dunI0eO6NSpU8rKytLo0aM1bdo0XX/99brqqquGRNsf6wQs1l0AAJLF44qdgFVT16qn1u+NuSb7/EE9tX6vlt8yjI4IAADEyaqYKsOiG1JXAZb5A0tul0vzZ5dp35EmW+fUHrehebPLLD93cl8AkKoowIJl3994nDs6T0vmVcQ8ifa4Df3NNROVmeFWW4dPOVkeTS4tCFUwTzq3QG+9X6dAMHwf7x5s0LUzx4e+rqlrVdWWGu0+1KieIw1JleVFmj+7jBN0AEDKcJs9DWxxMgwAGNruvPNOvfzyy/1yrJ///OdauXKlOjo6Ij7z+XyqqalRTU2NqqqqdNlll+n73/++zjnnnH6ZW7JYJWB5fSRgAQCQLGbnvL5eN3OrttTYLoj2+YNav6VGSxde5Mj8AABIF2YJlJL1veBoLQjdLkNlJfm27/8umVcR9d6sk/sCgFRFARYs+/7a1d2Dt3hEtpbfMkzrt9Rol0lh1LTyIs2LURiVOyxDk0sLtP/Dk2HvH/pzi1rPdCo/N1M7qk9YLs5BdUVV7zvSpCXzKjR98ug+/dsAAHCCx6wFIa2QACAt+f3+sK8LCgpUUFCgI0eOOH6smpqaUPHVmDFjdOWVV6qiokJFRUXq6OjQe++9p/Xr16utrU3vvPOObr31Vq1du1ZFRfG1BUglVue3tP4FACB5zM95P7l229Dcrt2HGuPa565DjWpoaaf1EAAAcbB66DeRFoSujxMup08e3ef7v92c3BcApCIKsNDnBKyePXjLSvK1dOFFamhuV/WxZtOUq1gunlgcUYAVlPT+nxo0bnQeUdUAgEHHQwIWAOBj06ZNU3l5uSoqKlRRUaFzzz1X69at0/Llyx0/lmEYmj17tv7hH/5Bs2bNkssVvh7deOONuv3227V48WLV1NSotrZWDz/8sB544AHH59JfzNZciQQsAACSyeqcNxAMymUY+uBos+I9Aw5Kqj7arOJKCrAAALDLsgVhgglY3Zy4/5uMfQFAqqEAC5YXqO1ta96Dt7ggW8UFiS2Sl0wo1ppXD0a8/+7BBu04UE9UNQBg0LG6GB0MBmUYkU8KAwCGrjvuuKPfjvX//t//U0FBQdQxn/rUp/TII49o/vz5kqT/+q//0j333KPs7MF50dPqorLd80gAABA/t0kCltSVguXyGGrv8CW037YEtwMAIF1ZJ2BZpUVbJ2D1LMDq1pf7v8ncFwCkir5FH2FIMAwjoTaEyerBW1yQrXGj8iLe31vTmHBUNQAAA8nyYjQpWACAJIpVfNVtypQpKivrerCmvb1dH374YRJnlVxWDxj5aP0LAEDSeFzR19/srMSeA89JcDsAANKVVZqV1X1gfyAQswUhAMA+CrAgScqIIwXLkHRReZGW3zJd0yePTsp8LplYHPGe1x9MOKoaAICBFOtiNAAAAy0v75OHYDo6OgZwJn3jchmmT+my5gIAkDyeGA8dTSktULy3cA1Jk0sL+jQvAADSjd8k/dllGHJb3Ae224IQAGAPj5BANXWt6vT5o47Jy87Ql2aNV152Rr/04L14YrE2/P6II/siqhoAMNCs0jhIwAIApILOzk4dOXIk9PU555wzcJNxgMftkj8Qfo5LARYAAMkTK4GyuCBbleVF2hVHd4Np5UVJvwYNAMBQ4w9Envu63eYPKnWNt25BSAIWAMSPBKw09/buOj2weod8JhXRPV0+ZbT+akapPl1Z0i8nvueNHa6Rw7Mc2VftidNqaKYNIQBg4Fi1IIy1/gIA0B82btyoU6dOSZIqKio0atSoAZ5R35ilcLDmAgCQPFapGj0LoOfPLrNMyurN4zY0b3aZI3MDACCd+EyKqVwuw7KYKloBFglYABA/ErDS2IGjJ/WD53fauhD91q7jmj2tRGUl+f0wM8kwDH2qOFcnT/W99cVbu+q0ZVedKsuLNH92Wb/9GwAA6GaZgEUaBwBggDU1Nenhhx8Off3P//zPAzibLvn5w+LepvtisstlKDPDrTNnw5OQXW6XCgtzHZkfUlPPnwG+1+mH7z8wsCxbEPa47lxWkq8l8yr01Pq9Ua9He9yGlsyr4BouAAAJMGsn6HFZJ2BFb0FIjgsAxIsCrDS25uVq220YfP6g1m+p0dKFFyV5Vl1q6lq1/8OTju0vKGnXoUbtO9Kkv7lmojI8brV3+JSd5dGU0gIVF2SrobldHxxtjngfAIC+srwYTQtCAMAA6uzs1Ne+9jU1Nna1A5ozZ47mzp07wLOyTtGwwzAMZXgit/f5A33aLwYPwzAs00cx9PH9BwZGrBaE3aZPHq3/399k6rurd5qOv6i8SPN4gBYAgISZXW92x0zAMr9XTAtCAIgfBVhp6qOmNu344KO4ttl1qFENLe390oKwaktNUm5K+/xBPfvygYj3h+dk6FSbN+w9QyI1CwDgCLsXowEA6C+BQEDf+MY39M4770iSSktL9d3vfneAZ9UlkYRIl8uQYRgKBoOm667XFyB5cojr+TNg9QQ3hi6+//ZQiIpksUrVMEu6+tSoPNOx11w6Tjd/YZKj8wIAIN2Ynfe63S65DEOGIQV7Lc20IAQAZ1GAlab2HG6MWGRjCUqqPtqs4srkFmA1NLdr96HGpB6jt97FV1J4ataSeRWaPnl0v84JADB0WN3oIAELADAQgsGgvvWtb2nDhg2SpHPOOUc///nPNWLEiAGeWZfW1rPy+fxxbVNYmCu321AgEJRhco24rd2rpqYzDs0QqajnzwDf6/TD9z82j8etkSNzBnoaGKIsHzoySdTwWhRE5+dlOjonAADSkdn1ZtfHJ8lulxFRHB29BSEFWAAQLx57SlNtZyMLjmxt1+FzeCaRPjjarFS6He3zB/XU+r2qqWsd6KkAAAYpyxaEJk8DAwCQTMFgUPfee6/Wrl0rSRo7dqxWrVqlcePGDfDMnGN2E5jUSQAAkieec16fz3xNziChDQCAPjNtQfjxOm3WUjBaAhYtCAEgfpzVpKmcYRmJbZeV/NC09n4o8oqXzx/U+i01Az0NAMAgFc/TwAAAJEswGNR9992nF154QZI0ZswYPfPMMyotLR3gmTnL7CawWQskAADgDKvUZ7MCaKsErAwPtyoAAOgr0wIsV3cCVuRaSwIWADiLs5o0deH5RaZtGaIxJE0uLUjGdMJk90ORVyJ2HWpUQ0v7QE8DADAIWRVgkYAFAOgv3cVXa9askSSNHj1azzzzjMaPHz/AM3OeWYIGCVgAACSPVQKWWQG0VQKW1T4AAIB9fpNz308KsMwSsAIkYAGAgyjASlNjCnM0fcqYuLaZVl6k4hHZSZrRJ6aUFigVl/SgpOqjzQM9DQDAIOS2bMfAzWAAQPL1Lr4aNWqUnnnmGZ133nkDO7EkoQUhAAD9y2OSqCGZn/NapVKSgAUAQN+ZpVl1J1/F04LQMCRXvEkeAAAKsNLZ33xhsmUiR28et6F5s8uSPKMuxQXZqiwv6pdjxastBdsjAgBSn1kShyT5LJ4uAgDASStWrIgovior65/zu4FAARYAAP3L6hqz2Tmv1zIBi1sVAAD0lWkLQrd1ApZVC0LaDwJAYjirSWOTSkfqX798acx4Z4/b0JJ5FSorye+nmUnzZ5fZjp32uA1NHDciyTPqkpOi7REBAKnNTQtCAIDD1q1bp8mTJ2vy5Mm69dZbLcfdf//9ev755yV9Unx1/vnn99c0B4TZuaRV2gYAAOg7q9RnswJor0VRtNWDSwAAwD6z4ufoLQjNE7BoPwgAiaGaJM3NqizR8luma/2WGu061KieS6yhrraD82aX9WvxlSSVleRrybwKPbV+b9QL5d3FYYX5w/TA6h1JvahuSJpcWpC0/QMAhq54LkYDAIa2Y8eO6aWXXgp7r7q6OvR63759WrlyZdjnM2fO1KxZs+I+1sqVK7V69WpJkmEYuu2223T48GEdPnw46nZTp07VOeecE/fxUoXHpIURay4AAMljmYBl2oLQogCLFoQAAPRZtDQr6xaEkWuz26K9MAAgOgqwoLKSfC1deJEamttVfaxZbR0+5WR5NLm0QMUjsgdsXtMnj9byW4bZLg6zU7DVFyXFuXr3QIOyszyaUlqg4oKB+/8GADC4WD3Ja/Z0EQBgaDt+/LiefPJJy8+rq6vDCrIkyePxJFSAtXPnztDrYDCoH/zgB7a2e+CBB7RgwYK4j5cqPCYXiinAAgAgeaw6GZilPtOCEABSx2uvvaaqqirt2bNH9fX1ysvL0/jx4zVnzhwtWrRIeXl5jh7v0KFDWrNmjbZt26a6ujqdPXtWxcXFmjJlir70pS/puuuukyvOwp+WlhatX79emzdvVk1NjRobG5Wdna2ioiJNmDBBV1xxhebOnasxY8Y4+m9JVaYtCKMkYNGCEACcRQEWQooLslOuqCie4rBoBVtOON5wRmteOyipqwCssrxI8wcgHQwAMPhYnbByMxgAAOeZJWB5fRQ9AwCQLG4HErDM1m8AQHKcOXNGy5Yt0+bNm8Peb2pqUlNTk959912tXr1ajzzyiC6++OI+H8/v92vlypX66U9/qmAw/Nzs+PHjOn78uDZv3qznnntOjzzyiO1iqXXr1umhhx5Sc3Nz2PudnZ1qaWnR4cOH9fLLL8vn8+nv/u7v+vzvGAz8Juts9zptnYBFC0IAcAoFWBgU7BaHWRVsdfr8WvPqQcfSsYKSdh1q1L4jTVoyr0LTJ492ZL8AgKHJ6kIyCVgAkH6uuOKKiISrRCxYsCBmStWzzz7b5+MMRmYpHH5/QMFgUIbBRWQAAJzmsXzoyH4CllVyNADAWX6/X0uXLtVbb70lSSouLtbChQs1YcIEtbS0aOPGjdq5c6fq6up0++23a82aNSovL+/TMVesWKEXXnhBkuR2u3Xttddq5syZys3NVW1trTZs2KADBw5o586dWrx4sZ5//nnl50cPP3j88cf1H//xH5KkjIwMfe5zn9Nll12mUaNGKRAIqK6uTrt27dKWLVv6NPfBxrSYyiABCwD6CwVYGJLMCrbOG5tvmY6Vn5Oh1jZv3Mfx+YN6av1eLb9lGElYAABLZq2QJAqwAABIBrMWRkF1rbtWLZIAAEDirNoH+gORxVZeErAAYEC9+OKLoeKrCRMmaNWqVSouLg59fvPNN+uhhx7S008/rZaWFt1zzz167rnnEj7e1q1bQ8VXOTk5+slPfqLLLrssbMzixYt17733au3atTp48KB++MMf6t5777Xc58aNG0PFV1OmTNFjjz2m8ePHm47t7OzUqVOnEp7/YGPagtBtXYBllYBFARYAJIYCLKSNWO0Me77/u3f/rLrGNlv79fmDWr+lRksXXpTkfwEAYLCyupBMC0IAAJxndRPY5w9YfgYAABJnVeBsloDls0zA4kYvACSb3+/X448/Hvr6e9/7XljxVbdly5bp7bff1v79+/XOO+9oy5Ytmj17dkLH/MUvfhF6vXTp0ojiK6krFetb3/qWtm/frpqaGq1du1b/+I//qHHjxkWMPXnypO6//35J0pgxY7Rq1SoVFBRYHj8zM1NFRUUJzX0wilZMRQtCAEg+rjwi7RQXZOvTlSWae9m5+nRliYpHZIe9f8mEYv3FZvFVt12HGtXQ0p6M6QIAhgCrJ4b8DrXGBQAAn7C6getUS3oAABDOHaX4OfI98/U4w+N2dE4AgEjbt29XfX29JGnGjBmqqKgwHed2u3XrrbeGvt60aVNCxwsEAtq2bZskyTAM3XDDDZZjPR6P5s2bJ6mrUOy3v/2t6bgXX3xRzc3NkroKuqIVX6Ujv8na6/64O4PbpEsDLQgBwFkUYAG9fHC0OaJFYSxBSdVHm5MwGwDAUGCVgGXWjgEAAPRNtAQsAADgPKsELLOHjrw+f1z7AAA458033wy9vvrqq6OO7fl5z+3i0dzcrLNnz0qSCgsLYxZLlZWVhV5v3rzZdMxLL70kScrIyNB1112X0LyGskDQupjKvAVhgBaEAOAgWhACvbR3+BLari3B7QAAQ5+HBCwAAPqNZQGWRcsjAADQNy7DkCFFPNRqVvzstTgPpk0wACTfgQMHQq8rKyujjh01apRKSkpUV1enhoYGNTU1qbCwMK7jBU2KgezqOdduJ06c0IcffihJmjRpkrKzs3XkyBE988wzeuutt/TRRx9p2LBhGjdunD796U/rlltu0ZgxYxKew2Bkdr3Z7aYFIQD0F85qgF6ysxKrS8xJcDsAwNBnlYDlIwELAADHWa+7fSt8bmhu15ZddXpl+zFt2VWnhmba0AMAIHW1lTJrQ2i29loVRGdYrN8AAOfU1NSEXo8bNy7m+J5jDh8+HPfxRowYoYyMDElSU1OTWlpaoo4/cuRI6PWZM2f00UcfhX2+e/fu0OuSkhL95je/0fz58/Xcc8/p6NGj6ujoUEtLi/bu3av//M//1Be+8AX95je/iXveg1m0NCuzVCtaEAKAs6gYAXqZUlpg+sRWNIakyaUFyZkQAGDQc7ssWhCSgAUAgOOskicTTcCqqWtV1ZYa7T7UGHaeaEiqLC/S/NllKivJT2jfAAAMFRkeQ727C5onYEW+Z4gbvQDQH06dOhV6PXLkyJjje7YM7LmtXR6PRxdffLG2b9+uYDCoqqoq3XbbbaZj/X6/1q9fH/Zea2trWIJVfX196PWBAwf0+uuvy+/369JLL9W1116r4uJinThxQhs3btTu3bt19uxZ3XXXXcrJydEXvvCFuOc/2ASD0dOszFsQkoAFAE6iAAvopbggW5XlRdp1qNH2NtPKi1Q8IjuJswIADGYet8WNYAqwAABwnFUCltkN31h2VJ/QU+v3mq7ZQUm7DjVq35EmLZlXoemTR8e9fwAAhoquB4/CK7D8JmuvWVGWx+OSYXCjFwCSra2tLfQ6Kysr5vieY86cOZPQMW+66SZt375dkrRy5UpVVlbqkksuCRsTCAR0//33R6RsnT59Ouzr1tbW0OujR49Kkr761a/qa1/7Wti4v/3bv9X3vvc9Pf3005Kkf//3f9fs2bOVk5OT0L/BCfn5w+Ia310A5XIZKizMtbWN2borSXk5WSoszNWwYRkRnwUlmS3BwzI9to+L5EjkZwBDB9//wYsCLMDE/Nll2nekydaNcbfL0LzZZf0wKwDAYGUYhtwuI+JpIj8tCAEAcJzHpAWSFH/yZE1dq2XxVU8+f1BPrd+r5bcMIwkLAJC2zB48MltDvSaJlBkWazcAYPC7/vrrVVVVpS1btqitrU233HKLrr32Ws2cOVO5ubmqra3Vhg0bVF1drcLCQnV0dISKvVy9ugoEel1LvfzyyyOKr6Sua7H/9m//pj/+8Y/au3evmpubtX79ei1atCh5/9AYzFr12tHV5tdekbJZ619Jyshwye12mZ4rBwJBmW3mdrsSnjOcFc/PAIYevv+DDwVYgImyknwtmVdh62J7RVkhF9kBADG53ZEFWCRgAQDgPKvkyXgTsKq21Nheq33+oNZvqdHShRfFdQwAAIYKs5u6ZmlXVglYAIDky8nJUUtLiySpo6NDHk/028QdHR2h17m5iSWwuFwuPfroo7r77rv1yiuvyOfzacOGDdqwYUPYuFGjRumJJ57Q4sWLQ+/l54ffe+s9h//zf/5P1OPedNNN+ta3viVJ+sMf/jCgBVhW6VRWXC5DhmEoGAwqYFFY1Vtnp8/0fePj45t1FfQHgqZrs8tlxD1nOCuRnwEMHXz/7UnFQlEKsAAL0yeP1vJbhmn9lhrtOtQoq19te2uatH5rjQqHD9OU0gIVF9CKEAAQqasdQ/hJKwlYAAA4zypFI56Lxw3N7dodR1t6qasdYUNLO+3pAQBpyezmR++HkCSrBCye6geA/jB8+PBQAdbJkydjFlU1NzeHbZuovLw8Pf744/r973+vdevW6d1331VDQ4NcLpfGjRunuXPn6rbbblNubm4o/cowDBUXF4ftp3dBVkVFRdTjXnjhhaHX3S0LB0pr61n5fP7YAz9WWJgrt9tQIBBUU5O99o+n272m73d2+tTUdMb0+D5fQF5v5PsBf8D2cZEcifwMYOjg+x+bx+PWyJED11rWCgVYQBRlJflauvAiNTS3q/pYs17dUasP/3IqbIw/ENRv3qqR1FVFXllepPmzy0jFAgCEcZs8YhRvKyQAABCb1dNv8SRgfXC02fIhHCtBSdVHm1VcSQEWACD9mLcgjFx7zdZjj8edlDkBAMKVlZWptrZWklRbW6tx48ZFHd89VpLOP//8Ph//yiuv1JVXXmn5eXV1tfz+rmKg8847L6Loq/ccYhWF9fy8u7BrKDMrfJY+uS5ten06EDTdzmwsACC21MvkAlJQcUG2Pl1Zon+8fmrUcUF1PfX8wOod2lF9on8mBwAYFEwvRhMdCwCA46wSsOJp/dveYd66IZa2BLcDAGCw87hMWhCapF2ZvUcCFgD0j0mTJoVe7969O+rYhoYG1dXVSZKKiopUWFiY1LlJ0rZt20KvL7/88ojPJ06cGNY28dSpUxFjeur5eV5engMzTG1Wqc/uj9dol8labVWA5aIACwASQgEWEIdOr1+Gjb85fP6gnlq/VzV1rcmfFABgUHCbneDGkcQBAADs8XjMT9rMUjisZGclFhiek+B2AAAMdnYfOjIriPZYFE8DAJx11VVXhV6/+eabUce+8cYbodef+cxnkjanbsFgUOvWrQt9vXDhwogxw4YN04wZM0Jf7927N+o+9+zZE3pdVlbmwCxTWyBWApbJDc5AIGi6HQlYAJAYzmyAOFRtqVHQ5kPTPn9Qv/jtfr2y/Zi27KpTQ3N7cicHAEhpZhejrWKhAQBA4swSOCTzxA0rU0oLlMjl5lNtnZz7AQDSklkLYNMWhGYJWB5uAVjpIgABAABJREFUUwBAf5gxY4ZGjRolqSttyqqAye/369lnnw19fd111yV9bi+88IL27dsXmue0adNMx82bNy/0+pe//KXl/gKBgNauXRv6+uqrr3ZopqnLsgXhx9el3SbXpwNBWhACgJM4swFsamhu1+5DjXFtc6z+jNa8dlBP/3a/7nrybT3y4vukYgFAmjK7GE0CFgAAzvNY3MSNJwGruCBb48cOj/vYa18/xLkfACAtmT50ZJJ2ZbYek4AFAP3D7XbrK1/5Sujru+66S42Nkfe9Hn74Ye3fv1+SdOmll4YlZ/W0bt06TZ48WZMnT9att95qedz33ntPnZ2dpp8Fg0H98pe/1Le//W1JUk5Ojr7zne9Y7mvevHmaMGGCJGn79u16/PHHTff5/e9/P1Rg9qlPfUrXXnut5T6HCrPkSemTYiqrtoJmxdG0IASAxJCND9j0wdFm9SWnJChp16FG7TvSpCXzKjR98minpgYAGAQ8JietZq0XAABA35jdAJbiW3d9/oBa28xvEMTCuR8AIB2ZFVGZJmCZvEcCFgD0n5tuukmvvvqqtm7dqoMHD2r+/PlauHChJkyYoObmZm3atEk7duyQJOXn52vFihV9PuaPf/xj7dy5U1dffbUqKys1evRoeb1eHTt2TC+//LKqq6sldbUYfPTRR1VaWmq5L7fbrQcffFC33Xab2tra9B//8R/aunWrrrvuOhUXF+ujjz7Sxo0btXv3bklSRkaGHn74YWVkZPT535HqrB727S6mskq16vT5I94jAQsAEkMBFmBTe4fPkf34/EE9tX6vlt8yTGUl+Y7sEwCQ+swinmlBCACA86xSNOwkYDU0t+uDo81670/1amrt6NM8fP6gnqzaoy/NOk+5wzKUneXRlNICFRdk92m/AACkIrMbtWbFz6YtCEnAAoB+4/F49Nhjj2nZsmV6/fXXVV9fryeeeCJi3NixY7Vy5UpNnDjRkeO2trZq48aN2rhxo+nnEyZM0P33369LL7005r4qKyv1n//5n1q2bJn+8pe/aOfOndq5c2fEuKKiIq1cudLWPoeCQND8WrPH1bXOWhVVmW3mcrE2A0AiKMACbMrOcu4/F58/qPVbarR04UWO7RMAkNrMWhDG0woJAADYY1WAZZa40a2mrlVVW2q0+1Bjn5KPe/MHpPVbj4S+NiRVlhdp/uwyHsgBAAwppglYgci117QFIQlYANCv8vLy9OSTT+rVV19VVVWVdu/ercbGRuXm5qq0tFRz587VokWLNHx4/G3ZzSxdulSVlZXavn27amtr1djYKMMwVFRUpIqKCs2dO1df/OIX5fHYvw93+eWXa9OmTXrxxRf1yiuv6MMPP1RLS4vy8vI0YcIEff7zn9f/+T//R7m5uY78GwYDs9a/0icPBsfTVpAELABIDAVYgE1TSgtkSI5djN91qFENLe0qHsHTzwCQDsxaEJKABQCA86xSNKxaEO6oPqGn1u+N2aKwIC9Tcy4bp5d+dzjhudGeEAAwVJm1ADa7EWxWgEUCFgAMjDlz5mjOnDkJb79gwQItWLAg5ripU6dq6tSpCR/HSl5env7+7/9ef//3f+/4vgcjq2vN7hgtCKNtAwCID2c2gE3FBdmqLC9ybH9BSdVHmx3bHwAgtZGABQBA/zBr+yuZr7s1da22iq8k6VSbV51eZ9bu7tb0NXWtjuwPAICBZvec16wFIQlYAAD0nVUBVnfyVTwJWPGMBQB8gjMbIA7zZ5eZPs2VqD01TWpobndsfwCA1GX21BAJWAAAOM/tMmR21uYzueFbtaXGVvGV1LVuv/PBiT7Orsd8Pm5NDwDAUGDagrDXGhsMBk3XXSevtwIAkK78Jq1/JcntcoX9rx0kYAFAYijAAuJQVpKvJfMqHLso8Md9H+muJ9/WIy++z5PPADDEmV2M9pOABQCA4wzDME3S8PUqfG5obtfuQ41x7ft4Y1uf5tZbd2t6AAAGO4/ZQ0f+gILBT9Zfq6LnDBKwAADoM7PWv9InKdG0IASA5PMM9ASAwWb65NFafsswrd9So12HGtXX7JKgui667zvSpCXzKjR98mgnpgkASDFmJ629bwQDAABneNyGvL7w93onYH1wtLnP53N91d2avrgye4BnAgCp5bXXXlNVVZX27Nmj+vp65eXlafz48ZozZ44WLVqkvLw8R4936NAhrVmzRtu2bVNdXZ3Onj2r4uJiTZkyRV/60pd03XXXyRVHasSHH36oF154QW+99Zbq6uoUCAQ0evRoXXnllbrpppt0wQUXODr/VGD20FFQUiAYlNvoOh82az8oSRkm2wIAgPgELK41d6/DtCAEgOSjAAtIQFlJvpYuvEgNze2qPtastg6ftuyq07ETpxPep88f1I9/s0dzLjtX40blaUppgYoLuAgPAEOF2yQ90eqpJAAA0DddN4H9Ye/5eiVPtnf0qtCy6ZziHB1vcC4Jqy3BeQDAUHTmzBktW7ZMmzdvDnu/qalJTU1Nevfdd7V69Wo98sgjuvjii/t8PL/fr5UrV+qnP/1pWFKTJB0/flzHjx/X5s2b9dxzz+mRRx7RmDFjYu7zl7/8pb773e/q7NmzYe8fOXJER44c0S9/+Ut95Stf0Ve/+tU+zz+VmJ3zSl3XPLvrq3qvxd3MircAAEB8/FYFWCRgAUC/oQAL6IPiguxQkdSET43QA6t3WEZp2xEISi9vPyZJMiRVlhdp/uwylZXkOzFdAMAA8pg8Le0P0IIQAIBkMLuR2/umb3ZWYpdELps8Wr89+WGfzv16yklwHgAw1Pj9fi1dulRvvfWWJKm4uFgLFy7UhAkT1NLSoo0bN2rnzp2qq6vT7bffrjVr1qi8vLxPx1yxYoVeeOEFSZLb7da1116rmTNnKjc3V7W1tdqwYYMOHDignTt3avHixXr++eeVn299na6qqkr33HOPJMnlcum6667TrFmz5PF4tHPnTv36179WZ2en/uM//kOZmZm6/fbb+zT/VGJVROX3B6QMtyTrAixaEAIA0Hc+i2vN7o+vS8dXgMXaDACJ4Cof4JCyknwtmVehp9bvdeRCPK0JAWBoMXsa2KkbtwAAIJzHxro7pbRAhhRXG0JD0uxpJTp3dJ4j536GpMmlBX3aBwAMFS+++GKo+GrChAlatWqViouLQ5/ffPPNeuihh/T000+rpaVF99xzj5577rmEj7d169ZQ8VVOTo5+8pOf6LLLLgsbs3jxYt17771au3atDh48qB/+8Ie69957TffX1NSkFStWSOoqvnr88cd1zTXXhD6/4YYbtGDBAv3d3/2d2tvb9eijj2rOnDk6//zzE/43pBKztVcKX3+tWhCSgAUAQN9ZdVvoLryiBSEAJB9nNoCDpk8ereW3TNdF5UVy6k8Tnz+op9bvVU1dq0N7BAAMBNMELAqwAABICjsJWMUF2aosL4prv9PKi1Q8Ituxc7/u/QFAuvP7/Xr88cdDX3/ve98LK77qtmzZMl1wwQWSpHfeeUdbtmxJ+Ji/+MUvQq+XLl0aUXwldaVifetb31JZWZkkae3ataqtrTXd389+9jOdPn1aUlexWM/iq24XX3yxli5dKkny+Xz60Y9+lPD8U41VUkbP9ddLAhYAAEkTsGpB6KIFIQD0l0FzZvPaa6/p61//uj7/+c+rsrJSs2bN0qJFi/TTn/40dGLrpNraWj3yyCP6m7/5G11xxRWqqKjQJZdcomuuuUZf/epXVVVVJa/X6/hxMfiVleRr6cKL9NAds3TF1DGO7NPnD2r9lhpH9gUAGBhmCViBYFCBIEVYAAA4LcNGAZYkzZ9dZpnY0ZvHbWje7LLQ1z3P/RZ/6QL9zZyJmvfp82xfqO69PwBIZ9u3b1d9fb0kacaMGaqoqDAd53a7deutt4a+3rRpU0LHCwQC2rZtmyTJMAzdcMMNlmM9Ho/mzZsnqatQ7Le//a3puP/6r/8Kvf7bv/1by/0tXLhQOTk5kqTNmzfr7Nmz8U4/JVkmYPW4GWzZgpAELAAA+sxvVYDljr8AiwQsAEhMyrcgPHPmjJYtW6bNmzeHvd/U1KSmpia9++67Wr16tR555BFdfPHFjhzz5z//uX74wx+qs7Mz7H2fz6e2tjbV1tbqlVde0Y9//GM99thjmjRpkiPHxdBSXJCtivMK9cd9Hzmyv12HGtXQ0h72dHRDc7s+ONqs9g6fsrM8mlJaoOKCxJ+ednp/AIBPmBVgSV0pWC4PJ7QAADjJbXIj1yx1o6wkX39zzUQ9+/KBqPvzuA0tmVehspL8iM+KC7LDzpvstCe02h/nZADS1Ztvvhl6ffXVV0cd2/PzntvFo7m5OVT4VFhYqIKCgqjjuxOwpK6iqdtvvz3s8z/96U/685//LEkqLy/Xueeea7mvvLw8TZ8+XW+99Zba2tq0bdu2mP/mwcCqjaC/ZwKWVQtCErAAAOgzywKsBFoQkoAFAIlJ6QIsv9+vpUuX6q233pIkFRcXa+HChZowYYJaWlq0ceNG7dy5U3V1dbr99tu1Zs0alZeX9+mYq1ev1oMPPhj6+pJLLtHnP/95lZSU6PTp0/rTn/6kdevWqa2tTTU1Nbrtttu0YcMGjRo1qk/HxdA0pbRAhiQnsk2CkqqPNqu4Mls1da2q2lKj3Ycaw/ZtSKosL9L82WWmNwasOL0/AEAkq3YM/kBAGYMnlBQAgEEhw6Tw2aogyqxYq5uhrjaB8+I4J+pqTzhM67fU6P1DjaZjFl8/VdMnjw59naxzMgq6AAwWBw58UghbWVkZdeyoUaNUUlKiuro6NTQ0qKmpSYWFhXEdL9iHJOKeczV7L9b8u8d0X/M+cODAkCjAsnroqOf667MqwLKZRgkAAKxZFWC5aEEIAP0mpQuwXnzxxdCJ6IQJE7Rq1SoVFxeHPr/55pv10EMP6emnn1ZLS4vuuecePffccwkf7+zZs/rhD38Y+vrb3/62Fi5cGDHu//7f/6u//du/1YEDB3Ty5En99Kc/1fLlyxM+Loau4oJsVZYXaZfFRfd4tXX4tKP6hOXT1EF1JWXtO9KkJfMqwi7oW3F6fwAAc5btGKKkYwAAgMSYFVVZtT3a/+FJ0/cXXTNRl04qDkshtqu7PeHrO2tN07VOnfkkcTsZ52Q8ZANgsKmpqQm9HjduXMzx48aNU11dnSTp8OHDcRdgjRgxQhkZGfJ6vWpqalJLS4tGjBhhOf7IkSOh12fOnNFHH32kMWPGhN47fPhw3PPv1vPfPphZJWD1XH+9Fue/GSRgAQDQZ/6A+Tlv94PB8SRg0YIQABKTsgVYfr9fjz/+eOjr733ve2HFV92WLVumt99+W/v379c777yjLVu2aPbs2Qkdc+fOnTpz5oykrqeQzIqvpK5Y6n/913/VkiVLJEnbt29P6HhID/Nnl2nfkSZHbrDvOtSo/R+eVMCiir2bzx/UU+v3avktw6JeVD94rDlma4x49gcAsGb11JDVk0kAACBxZjdyzVI3gsGg9h9pini/pChHX7jcun2UXZdfMEarXz4QkYq8/8OTmnPZuaqpa3X8nIyHbAAMRqdOnQq9HjlyZMzxPVsG9tzWLo/Ho4svvljbt29XMBhUVVWVbrvtNtOxfr9f69evD3uvtbU1rACrv+fvlPz8YXFv4+rRxqiwMDf0foFFwXJublZo3LDjraZjCgtywvaF1GX1/Uf64GcASF1+y9Tn7gQs+wXPJGABQGJStgBr+/btqq+vlyTNmDFDFRUVpuPcbrduvfVWfeMb35Akbdq0KeECrMbGT1KKxo8fH3Vsz8/b2toSOh7SQ1lJvpbMq7B1UT2WvTWRNwas+PxBrd9So6ULL7Ic88tXqm3Pyc7+AADWrJ4G9lukcQAAgMSZrbtm5z5/rj+j1jZvxPtTx8eXpGIlLztDpWOH68O/hN9crz7arEAgqKotNY6ekyWjoAsA+kPP66tZWVkxx/cc0/1Abbxuuumm0IO1K1euVGVlpS655JKwMYFAQPfff39YwpUknT59OuzreOc/bNgnhU+Jzt8J0drwxmIYRljbwcwMt+m4QPCT41g9gJSV5enTXND/en//kX74GQBSj9U666YFIQD0m5QtwHrzzTdDr6+++uqoY3t+3nO7eBUVFYVe94yVNtPz84kTJyZ8TKSH6ZNHa/ktw7R+S4129WoBkUy7DjWqoaXdtGXGR01t2lF9wrH9AQCiszpp9ZGABQCA48xa/5q1INxn0X7wgvNip5fYdcH4kREFWG0dPr1/qEG742xXb3ZO1tDcrg+ONqu9w6ctu+p4yAYAbLr++utVVVWlLVu2qK2tTbfccouuvfZazZw5U7m5uaqtrdWGDRtUXV2twsJCdXR0hIqlXHEkSKSyRB4IcrkMGYahYDAYltJvdZ+2w+sLHaej0286xu0yeDhpkLD6/iN98DMQGwWlGCixCrBoQQgAyZeyBVgHDhwIva6srIw6dtSoUSopKVFdXZ0aGhrU1NSkwsL4n1adPn26Ro4cqZMnT2rPnj168cUXTdsQNjU16Yc//KGkrpPtv/u7v4v7WEg/ZSX5WrrwIjU0t6v6WLOOnTitV3fUJvUkJaiuJ6uLKyMLpnb/qUHBOA8dbX8AgOhIwAIAoP+YJ2BFrrlm7QcNQ5pSWuDYXKaOH6n//uPRiPff3vOXuB/O6XlOVlPXqqotNdrdh4d8eMgGQKrIyclRS0uLJKmjo0MeT/TL1h0dHaHXubmJtcByuVx69NFHdffdd+uVV16Rz+fThg0btGHDhrBxo0aN0hNPPKHFixeH3svPD08PzMnJMZ2blbNnz/Z5/k5obT0rn8+8KMpKYWGu3G5DgUBQTU2fpHe1t3Wajj/Z3B4a19zSbjqm7XRH2L6Quqy+/0gf/AxE5/G4NXJkTuyBQBL4A+bXmbtbD5KABQDJl7IFWDU1NaHX48aNizl+3LhxqqurkyQdPnw4oQKsrKws3XffffqXf/kX+Xw+ffOb39S6dev0+c9/XiUlJTp9+rQOHjyoX//61zpz5oxycnL0ne98R9OnT4/7WEhfxQXZKi7ourg9cdwIR1oTRvPuwXoFg103ELqPK0ltZyPbbNjR1uFzamoAUojf79ehQ4e0Z88e7d27V3v27NEHH3wQuih844036sEHH0zKsV977TVVVVVpz549qq+vV15ensaPH685c+Zo0aJFysvLS8px+5vVSas/iWsAAADpyk4LQn8goOpjzRHjzhs7XDnDMhyby8RxBV3JHr0evqmtP22xRXRtHT7tqD7hyLkkD9kASBXDhw8PFWCdPHkyZlFSc3Nz2LaJysvL0+OPP67f//73Wrdund599101NDTI5XJp3Lhxmjt3rm677Tbl5uaG0q8Mw1BxcXHE/LudPGmerpiM+acSOw8deS0eQPJ4SIsBAKCvrK4zd7cLjaeoigQsAEhMyhZgnTr1STz/yJGxo/8LCgpMt43XX/3VX+nnP/+5VqxYoYMHD2rnzp3auXNn2JiMjAzdcccdWrRokUpKShI+FtAfrQl3HmjQzgMNMiRVlhdp/uwyFRbmJnxDIScrZX9tAOiDO++8Uy+//HK/HvPMmTNatmyZNm/eHPZ+U1OTmpqa9O6772r16tV65JFHdPHFF/fr3JLB6mK0z+LJJAAAkDg7LQhr6k7prEkrpAvGx/9AVzRZmW6Vn5OvA7UtYe/XN5+12CK6M+1evfj6nxx7kIeHbACkgrKyMtXW1kqSamtrYz6Q2z1Wks4///w+H//KK6/UlVdeafl5dXW1/P6uNeO8886LKJrqOYeec7PSc0xZWVm8001JbpO1VwovgDZLo5SkDNp1AQDQZ2YddwxJLiP+FoTuIdJuGQD6W8pWUrS1tYVeZ2VlxRzfc0z300iJuvzyy/Xv//7vevDBB7Vv376Iz71er55//nm1t7frX/7lXzRs2LA+Ha+v8vPjP76rR7/fwsKBi7lGV2Tv9IoSfdTUpr2HG/XegRN6873jjh8nqK72EvuOnNSyWy5V5YRiGYbiakNoGNIV085RIRG6gx6/A9Bb94XkbgUFBSooKNCRI0eSdrylS5fqrbfekiQVFxdr4cKFmjBhglpaWrRx40bt3LlTdXV1uv3227VmzRqVl5cnZS79xepiNAlYAAA4z6zw2R8IKhAMhi4+m7UflKQLzov9EFi8LjivMKIAq3cilh2GpAO1zY6mKPOQDYBUMGnSpND54e7duzVz5kzLsQ0NDaFOCEVFRQl1QojXtm3bQq8vv/zyiM8nTZoUer179+6Y++s5ZuLEiX2cXWrwWNyo7Vl05fVZFGCRgAUAQJ+ZnWP2vCZNC0IASD6usvXS1NSkO++8U3/84x81YsQILV++XNdcc43Gjh2rs2fPas+ePfr5z3+uN954Q6tWrdK7776r//zP/7SV0pUs7j48IWQYhuUNYfSvc0bl6ZxReWrv8CWlAKubzx/Qw6t36qGvztb0KWP0zv6PbG972QVjVFI8NFqBoQu/A9Bt2rRpKi8vV0VFhSoqKnTuuedq3bp1Wr58eVKO9+KLL4Yurk+YMEGrVq0Ka+Fw880366GHHtLTTz+tlpYW3XPPPXruueeSMpf+YnXSavUEMAAASJzVjVy/PyCXxy1J2v9hZIsoj9uliZ8a4fh8Lhg/UlVbaiLeHz0yWydOttvez5TSAn3wYbNj8zIkTS4tcGx/AJCoq666Sj/72c8kSW+++ab+6Z/+yXLsG2+8EXr9mc98JulzCwaDWrduXejrhQsXRoyZMGGCzjnnHB0/flyHDh2KmuJ15swZ7dixQ5KUnZ2tGTNmJGfi/cwsfVIKvxlsdf5rtS0AALDPb9JpoWeSVTwJWLQgBIDEpGwBVk5Ojlpaup4O7ejokMcTfaodHR2h17m5iaW5tLe36+abb9bhw4c1YsQIrV27Vuedd17o84yMDM2aNUuzZs3SihUr9Nxzz2nXrl369re/rR/84AcJHdMJ/gRu3LpchgzDUDAYNI2kxMAZ1g9PH/v8Ab3wSrWuvvgc2wVYbpehm66ZlNDPG1IPvwNi60tx62B0xx139Nux/H6/Hn/88dDX3/ve98KKr7otW7ZMb7/9tvbv36933nlHW7Zs0ezZs/ttnk6z+plKJP0CAABYq6lr1TsfnDD97LFf7daCq8/XOcW5+tOfWyI+nzhuhDIz3I7P6fxz8pWZ4VKnN/x8qsOkBaIVj9vQxHMLtP9os2PzmlZepOIR2Y7tDwASNWPGDI0aNUr19fXatm2b9u7dq4qKiohxfr9fzz77bOjr6667Lulze+GFF0JdEmbMmKFp06aZjrv22mtDRWS/+MUv9M1vftN03Nq1a0PdHz7/+c8rO3to/B42S5+UwouufD7z818SsAAA6Duz68w9C6lIwAKA5EvZAqzhw4eHCrBOnjwZs6iqubk5bNtEPP/88zp8+LAk6R/+4R/Ciq96W7ZsmTZs2KDW1lb99re/1d13361Ro0YldNy+am09K5/P/kVbqavtndttKBAIqqmpby0b4axzC7NlqKtlYDK9s/8jDc/OsD3e43Zp+57j2n+oQVNKC1RcMDQuDqUrfgdE5/G4NZJWm0mzfft21dfXS+q6eG12UV2S3G63br31Vn3jG9+QJG3atGlQF2B5LBOwKMACAMApb++u0w+e32G5vu6taVL10ZP67MXnmI65YHxy0q09bpcmnVugPYfD2x62nOm0vY9/+NIFOnXG6+CcDM2bXebY/gCgL9xut77yla/ovvvukyTdddddWrVqlYqKisLGPfzww9q/f78k6dJLL9VVV11lur+eic4zZswIK9rq6b333tPUqVOVmZkZ8VkwGNTatWv17W9/W1LXA8Pf+c53LP8Nixcv1gsvvKAzZ87oueee06xZs3TNNdeEjXn//ff16KOPSpI8Ho/+7//9v5b7G2ysEtZ7rrdmLQgNIzydAwAAJMa0BWFYAZb99ZYCLABITMoWYJWVlam2tlaSokY2d+seK0nnn39+Qsf83e9+F3r96U9/OurYnJwcXXLJJXrjjTcUCAS0e/duff7zn0/ouEBPxQXZqiwv0q5DjUk9TjAo/X53ne3xHV6/1r5+SFJXm4rK8iLNn12mspL8JM0QwFD15ptvhl5fffXVUcf2/LzndoORdQIWyYIAADjhwNGT+sHzO2MWN/v8Qb2648+mn43Ii7wB75Sp4wsjCrDikZ3psUwOiZfHbWjJvArO5wCklJtuukmvvvqqtm7dqoMHD2r+/PlauHChJkyYoObmZm3atCnUui8/P18rVqzo8zF//OMfa+fOnbr66qtVWVmp0aNHy+v16tixY3r55ZdVXV0tSRo2bJgeffRRlZaWWu6rqKhI//7v/667775bgUBAX/3qV3Xdddfp05/+tFwul3bu3Knf/OY3oU4OX/va11ReXt7nf0OqsErA6pmm7zVJ1s9IswRyAACSxW9yLtyzQJoWhACQfClbgDVp0iS99dZbkqTdu3dr5syZlmMbGhpUV9dVSFJUVKTCwsKEjnnixCctCuykaPUc0x0bDThh/uwy7TvSZCsVxWVIk84t0AcJtKE4a9LuYuK4ERpdkK2te/5iuV1Q0q5Djdp3pElL5lVo+uTRcR8bQPo6cOBA6HVlZWXUsaNGjVJJSYnq6urU0NCgpqamhNf5gWb11JDZiTEAAIjfmperw9ocJeLZ/6lWTpYnSec49tb8grxMNZ+OTMbadbhR184o7XNi8rBMt/7tby6h+ApAyvF4PHrssce0bNkyvf7666qvr9cTTzwRMW7s2LFauXKlJk6c6MhxW1tbtXHjRm3cuNH08wkTJuj+++/XpZdeGnNfN954o9rb2/Xggw+qo6PDdL9ut1t33HGH7rjjDkfmnypstSA0K8Ci/SAAAI4wS8Dy0IIQAPpVyp7d9IyPjpV48cYbb4Ref+Yzn0n4mD3bHHYXdEVz/Pjx0OuCgoKEjwv0VlaSryXzKuSxiO7u5nEb+ucbLtSVF5Y4duwFV5+vz136KVtjff6gnlq/VzV1rY4dH8DQV1NTE3odK+Gy95juVsGDkeXFaBKwAADos4+a2rTjg4/6vJ9knePU1LVq3Zv2/o451eZVbpY74v3dhxpVNGKYKsuLTLayz+sL6NzReX3aBwAkS15enp588kn96Ec/0he+8AWVlJQoMzNTI0eO1EUXXaRly5Zp48aNtoqh7Fi6dKm+9rWvaebMmRo3bpyys7OVk5Ojc889V1/84hf1gx/8QFVVVXEd78tf/rLWr1+vv//7v9eECROUm5urnJwcnXfeeVq0aJFeeuklff3rX3dk/qnE6kZtrBaEVufKAAAgPgGTAiwXBVgA0K9SNgFrxowZGjVqlOrr67Vt2zbt3btXFRUVEeP8fr+effbZ0NfXXXddwsecNGmS9u7dK0nasGGDZs2aZTn2ww8/1K5duyRJLpdLF154YcLHBcxMnzxay28ZpvVbarTrUGPYE86GpGnlRZr3cQvAhub2Pj8FLUmjC7I16dwCPfrSLtvb+PxBrd9So6ULL+rj0QGki1OnToVejxw5Mub4nkXOPbcdbEjAAgAgefYcblTQoSU1Gec4VVtqbCUcS11PLWdmenSmIzyxuKHlrP7S1Kb5s8u053CTAjb+wS5D6n0N3h8I6s/1ZzR+bOzkbwAYKHPmzNGcOXMS3n7BggVasGBBzHFTp07V1KlTEz6OlfPOO09333237r77bsf3naqskqx6PnRkloBFARYAAM4we9DX7fpknaUFIQAkX8oWYLndbn3lK1/RfffdJ0m66667tGrVKhUVhT/p+fDDD2v//v2SpEsvvTQsOaundevWafny5ZK6irt6Fm11u/766/XrX/86NP6SSy7RwoULI8bV19frzjvvlM/nkyR99rOfJQELSVFWkq+lCy9SQ3O7qo81q63Dp5wsjyaXFqh4RHZoXHFBtirLi7TrUGOfjvfpaSVqbDmr3XHuZ9ehRjW0tIfNCQCs9Gzbm5WVFXN8zzFnzpxJypzsys8fFtf47hNVl8tQUWGu6ZhhwzJUaPEZBr+ePwN8n9MP33+g/7Sd9Tq6PyfPcRqa2+M+xzp5qsNyXn81o1SF+VlqaDkbdR8et6FrryjVht9/GPHZ0ROnKMACADjKzkNHXloQAgCQNGYP+rrdiSZgsT4DQCJStgBLkm666Sa9+uqr2rp1qw4ePKj58+dr4cKFmjBhgpqbm7Vp0ybt2LFDkpSfn68VK1b06XizZ8/WX/3VX+l//ud/FAwG9c1vflPr16/XNddcozFjxqijo0N79uxRVVWVWlu72hEUFBSk1ZNMGBjFBdkqLoh+4X/+7DLtO9Jk+6lqM5++cKz2HTkZd5JWUFL10WYVV1KABWBocyf4ZK5hGMrMjGwlJEmBPuwXg4dhGGEXPJBe+P4DyZczLMPR/Tl5jvPB0eaE0orNUo53HWrUlNKRUYuveiYmF+YPMy/A+uh0AjMCAMCaYRhyuwz5e0Uv9ky98tGCEACApDFrQeg2PrkeRQIWACRfShdgeTwePfbYY1q2bJlef/111dfX64knnogYN3bsWK1cuVITJ07s8zEffvhh5eXl6Ve/+pUkadu2bdq2bZvp2LKyMq1cuVLjx4/v83GBviorydeSeRV6av3ehIqwDEk1da1q7/AldPy2BLcDkH5ycnLU0tIiSero6JDHE/3PkY6OTxIgcnMHNkHGb/K0bjQulyHDMBQMBmV1ytrp9ce9XwwePX8GzC6CYGjj+28PRahwwoXnF8kw5FgbQsm5c5xEz7GKRwxTfa9CqwPHmvXqO8dMx19xwWhdeH5RRGLyiLxMtZzuDBt77KPB29YZAJC6PG6X/IHwFro+ErAAAOgXvYugpfAELJdh2D5vjictCwDwiZQuwJKkvLw8Pfnkk3r11VdVVVWl3bt3q7GxUbm5uSotLdXcuXO1aNEiDR/uTHR+Zmamvvvd7+rWW2/VunXrtHPnTtXW1ur06dPKyMhQYWGhLrzwQl1zzTW69tprlZmZ6chxASdMnzxay28ZpvVbarTrUGNcT1kHJT21fq+um5lYQWHtidNqaG6PmdQVTUNzuz442qz2Dp+yszyaUlrQp/0BSE3Dhw8PFWCdPHkyZlFVc3Nz2LYDqbX1rHw+f+yBHysszJXbbSgQCOr0KfOkilOnOtTUNLCtFZE8PX8G+D6nH77/sXk8bo0cmTPQ08AQMKYwR9OnjNE7+z9ybJ85Wc5cMslOcD/jxw6PKMDyB4LauucvEWOzMty67YtTTI81fsxw7Tod3gLx6InTCgSDchlcVAcAOMfjNtTRqytweAJW5NXKDJJiAQBwhD8QWejcu5Wg22XYCnGgAAsAEpPyBVjd5syZozlz5iS8/YIFC7RgwQLb4y+44AL9f//f/5fw8YCBUlaSr6ULL1JDc7uqjzXrv/74oY43tNna1ucP6uCxZtNWF7G8tatOW3bVqbK8SPNnl6msJN/2tjV1raraUqPdvYrGDCmh/QFIbWVlZaqtrZUk1dbWaty4cVHHd4+VpPPPPz+pc0smq/ZjPtKv8P9n794Do6rv/P+/JjMhV5LJFaIxEAMEiQEkFtEG3VZo66Wh5Vv80ord7rqVft36o9uya7GtbdXW6lpR13pZe/MrXlYt3QSw+1VEgVAqGLQJCQQMQYiMkAuTQBJCZjK/P9KMuZzJ3JNJ8nz808mZc87nQzPmzDnnfV5vABOK0+lUXV2d9u/fr+rqau3fv18HDx7UuXO9hTZf/vKX9Ytf/GLMjjeavvq5fL1/qDEkx1aTpPwca9D7kaTZOVa/z7FMkhbPu0Dv1jb6tP6nZmd6LPS6KDNRlXUDC7DOnXeqyd6pTAogAQAhZJRs2v+4bJSAZSEBCwCAkHAaFFYNbiUYFWWSfCjAogUhAARmzBRgAfBPX3LUb7cc8Gu7g8fsyp9m1cEP7X6P6ZJUWdesmqMtWl1SoKL8TK/bVNSe8tg2MZD9AYh8s2bN0s6dOyVJVVVVWrRokcd1m5qaZLPZJElpaWlKTU0dkTmGg8XDSatRNDQAYPz6zne+o9dff33cjjeaZuWk6HtfW6BfvlARUFv2/ubmpQ1o4xeMdGucCvPShhRBeRv/0txUpUyO0ekzXV7XXzwvy+N7OVOME0SPnTxLARYAIKQsBg8e9b8Z7HAYtCCkHTUAACHhNOgtODjJqjcRy/tDSyRgAUBgOLsBxrGDx+x+J1m5JM3KthpeMPGVw+nS02XVqre1Dbteva3NY/FVIPsDMDYsXrzY/XrHjh3Drrt9+3b362uuuSZscxoJRk8CSyRgAcBE43QObGVrtVo1ffr0cTPeaLuyMEvrVhVpXl6aAj2jsZhNKinODem8lhXn+nyO1Te+yWRS4cVpXtdPS4rRjAuTPb6fMyXRcPmxU2d8mg8AAL6yRJGABQDAaDFKwBrclcHXwioSsAAgMCRgAeNYZ5cjoO0S4qK1uqTAp+IoTxxOl8rK67VmxTyP65SW1/u8f1/2B2BsWLhwoTIyMtTY2Kg9e/aourpaBQUFQ9ZzOp167rnn3D9ff/31IznNkPN0cksCFgBMLHPnzlVeXp4KCgpUUFCgiy66SBs3btS6devGxXiRYHBb9o4uh+JjLDrvcOrFrYeHPQexmE1aXVIQ8hbouVlJPp1jDR4/Idb7ZZvTZ7q071Cjx8TgDGucYieZde78wGK8YyfP+vEvkJrsnTp4zK7OLofiYiyanWN1Jy8DACANvckrSY5+57zdJGABABA2zh6DQudBxdG+FFaZTFKUiQIsAAgEBVjAOBYXE9h/4vExFhXlZ2rdqliVldersq7Z7yQtqbd9YFNrp2HrjiZ7p6r8aMHhbX8AIkP/G7oLFy4cUEDVx2w26/bbb9dPf/pTSdKdd96pZ599VmlpAxMeHnroIR040NtGdcGCBQOSs8YiTwVYJGABwMTyrW99a1yPF0nSrXFDCoSmT00yPMcxqbftX0lxbsiLr/oMd45lNH69rU1vvHvc6357XNLTZdVatyrWcO5RJpMuykzU4YbWAcuPnfQtAave1qbS8npVGcy5MC9Ny8L4/xkAYGyxGBRTOfud8xqd/5KABQBAaPQYPOg7uODKlwQs2g8CQOAowALGsdk5Vpkkv4qnTJLyc6ySBj45vunPR7Wz0ubX+C5JtcfsSi8cWjAVaHtET/sDEJzjx4/r1VdfHbCstrbW/bqmpkbr168f8P6iRYt05ZVXBjTeTTfdpK1bt2rXrl06fPiwli1bphUrVmjGjBmy2+3asmWLKioqJElJSUm65557AhonkphMJpmjTEMSr0jAAgBg5HhKx8rPsY7Igx7+jB/KxOCczMlDCrDsZ8+rrf28khImedxvRe0pj6ldLvU+JFNztEWrSwo8JnABACYOo3a7/Y8hRgVYJGABABAaDoPrzIOLqXwrwOLYDACBogALGMfSrXEqzEtTpR9JU3Pz0oZc+E+3xik7IzGgOXQMaoPY17bi/cONIdkfgNA4ceKEnnrqKY/v19bWDijIkiSLxRJwAZbFYtFjjz2mtWvX6q233lJjY6OeeOKJIetNnTpV69ev18yZMwMaJ9KYzQYFWAG2egUAAIEzSseKpPFDnRicM8X4fO7YqTO6NDfN8L16W5tPbekdTtewCVwAgInDbFBM1Vd01eNyGR5TjFKzAACA/4yuMw9uD+xLC0Jf1gEAGKMACxjnlhXnquZoi09PTlvMJpUU5xq+F0w7Q8lz24pA9wdg7EtMTNRTTz2lrVu3qrS0VFVVVWpublZCQoJycnK0dOlSrVy5UpMnTx7tqYaMJSpK5zXwiV8nLQgBAMAgoU4Mzpli/H3q+MmzHguw/E3g+s3mGn3himmanWMd1eI2AMDosRjcsO07lng6942mBSEAACFh1GnBbKIFIQCMJCoZgHEuNytJq0sKvD65bDGbtLqkwOMTy8G0MxyubYU/+rdHBBBaV1xxxZCEq0AsX75cy5cv92ubJUuWaMmSJUGPPRYMfuJIogUhAAAYqjPA5F9PicEXpCcYtkL+8OQZw/UDSeA60dyh3752QCZJhXlpWlacSyIWAEwwRmlWzp7ewqtuh/G5r1HbQgAA4L8eowIss/8FWCRgAUDgeLwEmACK8jO1blWR5uWlafDXJpOkeXlpWreqSEX5mR730dfO0B9z89J0pqM7JMVXffszaqcBAGOF0cVoBwlYAABgkGATiAeLtkQpKy1hyPLjp84OWdZk79SmPx8NOLnYpd52iPdvqFBF7akA9wIAGIuGO+ftJgELAICw6it67s8cNfA460txFQlYABA4ErCACSI3K0lrVsxTk71TDS2d6jzvUNwki7LT4nwuavKnnaEkWSxR+s3mmpAUX5mjPLdHBICxwujklQQsAAAGSkqK9XubvovIUVEmpaYOLTQaa66Ye4F+96cDcvnxNcFk6t0uNSXe8P2ZOVY1NA4suPq4pUPxiTGKnWTR4eN2/dcbtaqoPeXXuJ44nC49VVqt//XZ85ocH6342GhdenGapqQazy9Y4+0zAP/w+wcig1Hqc991QYfDQwGWQdEWAADwn9PgXtzg69G0IASA8KIAC5hg0q1xmnVxuszmKDmdPWppafd5W1/bGfapqG0MZqoDJCdO0gcNrfqosV2zc6xKt/YWjTXZO3XwmF2dXQ7FxVgGvAcAkcZs+DQwBVgAAPRndLz0lclkMrz5O9ZckJGootlT9O6Bkz5vc/klU5SVnujx/bxsq96qaBiwzOXqTcFqaT2nf99QEfJkTmePSy9vPeT+2WSSimZP0Vc/l69ZOSkhHeuTMcbHZwCB4fcPjC7DFoR/O7Z4OsZYSMACACBoPS6XYYrx4MQrXxKwaEEIAIGjAAuAX3rbGcaqrLxelXXNAbel8FdLW5defPOwpN62iXkXJstkkj5oaB0wB5Okwrw0LSvOVW5W0gjNDgB8YzFMwKIFIQAA/TkDKAKKijLJZDLJ5XKpZ5ykS/7vJbP0/qFGn4qiLOYo3XTtrGH/v5s+dbLh8t2VJ1S2s35E2iK7XNK7B07q/UON+t7XFujKwqyQ7Xs8fgbgO37/vgmmwBXwhdE5b99DR90eErCMirYAAIB/jNKvpKHplINbEhpuQwEWAASMAiwAfuvfzrD2uF0dXQ4d/LBF7x1uDsn+p6TG6WRLp8f3XZI++KjV43uVdc2qOdqi1SUFKsrPDMmcACAUhmvHAAAAerW1nZPD4fRrm9TUBJnNJvX0uPxK+Y1kaQnRWl0yx2sCscVs0uqSOUpLiB72326NM74E9Pa+hhEpvurP4ezRL1+o0LpVRUMenAk05Xg8fgbgO37/3lksZqV4aFEKhIph6vPfHjrq9nCsiSYBCwCAoHl6yHdwwRUtCAEgvCjAAhCwdGuc+0J4dX1LyPZ72cwM/c87x4Lah8Pp0tNl1Vq3KpYkLAARw+gJIxKwAACAJ8MlEJskzc1LU4mP6b/xsdFKT45VU+u5Actb2rpCO2kfOZwulZXXa82KeZKkelubSsvrVWXw7yTlGADGBovBQ0d9iRyein2jScACACBonlJgBxdT0YIQAMKLAiwAQWuyd6qqLjTpVyZJRz9uC8m+Bl/QB4DRZnQxmgQsAAAwHKME4vgYi/JzrEpP9p4M1V+aQQHWaKqsa1ZTa6c+/PiMx6QvUo4BYOwwaifo7HGpx+WiBSEAAGHk8LEAiwQsAAgvCrAABO3gMbtCVT4wO8eqgx/aQ7S3Ty7o+3tjAgDCwejk1UkBFgAA8EH/BOJAVNSe0uHj9tBNKARcksorbXrtLx96LUon5RgAIp/Z4KEjqfe812MCFi0IAQAImqdrzIOPzb4VYHFsBoBA8RcUQNA6uxwh2Y/FbNLMi6whK+aSei/o1x6zh3CPABA4s+HTwLQgBAAA4VVva9PTZdXy8FD0qHq39pTPiaB9KccAgMhk8XDD1uHsUbfD+G+9UVI0AADwj6drzIOLqWhBCADhRQEWgKDFxQQfpmcxm7S6pEAJsdEhmNFAHSEqEAOAYFlIwAIAhMjGjRuVn5+v/Px83XLLLaM9HUS40vL6kLY9DmVLihNNHX6t35dyDACIPJ6KqZw9LnU7ncbbkIAFAEDQemhBCAARgRaEAII2O8cqkxRQcpVJ0ty8NJUU5yo3K0nllbYQz06K71cg1mTv1MFjdnV2ORQXY9HsHGtQbTwAwB9GCVgOErAAYEI5fvy4Xn311QHLamtr3a9ramq0fv36Ae8vWrRIV1555ZgYD5Gnyd6pqrrmkO1vXl6aiudm6emy6pAWdfmqL+U4vdD7eRznfwAwsiwG57xSbwKWw0MCVrSHbQAAgO+cPhZgkYAFAOFFARaAoKVb41SYl6ZKPy7qX5AWr+sWTVN+jlXpyZ9cAA+mmMuISVJ+jlX1tjaVlterqq55wL5Nkgrz0rTsbwVgABBORk8Dk4AFABPLiRMn9NRTT3l8v7a2dkCBlCRZLJaAC6JGejxEnoPH7CE7v7KYTe6HZ9atilVZeb0qB51j+eOCtHidaPYvAUvynnLM+R8AjA6jh46kvxVgOY0fPoomAQsAgKB5usZMAhYAjCwKsACExLLiXNUcbfHpCWiL2aRbb5xjeME7kGKu4WSlxet/3jmm7e+fMHwCwKXeFhY1R1u0uqRARfmZIRkXAIwYnbx6ejoJAAAgFDpD1JK9r21833lcblaS1qyYpyZ7p2qP29XR5VB7Z7e27P7Qp+83FrNJl8/OVNmuo37PpX/K8WC7q2z65QsVhuemnP8BQHh5bEHodKnbYVyA5Sk1CwAA+M7TOdjgNCsKsAAgvCjAAhASuVlJWl1S4LUNxeCL9kb8Keby5kRzh09PVDucLj1dVq11q2J5EhpA2Bi2IPTwFDAAYHy64oorhiROBWL58uVavnz5iI2HsStumGIlXwxuGz9YujVuQFu/izITvZ4XmkzS6pICTZsyWZt2HfUrQasv5djIoWOn9csX9nk9l+T8DwDCY9gWhCRgAQAQNh5bEJoHtyD0ftylBSEABI6zGwAhU5SfqXWrijQvL02Dv56ZJM3LS9O6VUVenzLuK+by9NRcuDicLpWV1w9Z3mTvVHmlTW/sPa7ySpua7J0jOi8A44eFBCwAADDC+tq8+6vk09N16w2X6IH/c6XWrJjnc6HScOeFfeInmXXZzAx3ArI/5ualDWhj39+Lr9f6XNzu6fwPABA4T4kZDqdL3R7+PpOABQBA8Jw9Ho6zgwquSMACgPAiAQtASBm1oYiPsSg/x+rxIrmR3ov2sSorr1dlXfOAJ6JNkmZcmCyZpA8aWv16WtqbyrpmNbV2Kj05TvW2NpWW16vKYPzCvDQt8/AEOAB4QgIWAAAYaYG0eZ+Xl6YvLb444DH7nxf+5rUDqj1mH/B+e5dThxvsys9J0ZUFU3yeW5RJKinONXzvZEuHKg6e9Gue/c//AADB85iA1dPjsQVhNAVYAAAEzekhBZgWhAAwsijAAhAWg9tQBMKXYq6+9177y4ey+dBq0BuXpNpjdn046YzHthku9V6orznaotUlBV4TvQCgj9HJq8sl9fS4iHYGAABh40+bd4vZ5LHIyV/p1jjdcOW0IQVYklRR26j8nBQd/fiMz/uLijKp5miLPmps1+wc64Bzzv1HmuXy8+mcvvO/9EIKsAAgFDyl2TudLo8PH1ksnAsDABAsp4eTocHXo325Bs11agAIHAVYACLecMVcfct/u+VAyMY7fuqstu1r8HpzwuF06emyaq1bFUsSFgCfeHoa2NnTo6go8wjPBgAATBR9bd49PWTSx2I2aXVJQUjPb2bnpCg+xqKOLseA5RWHGnXTZ2dod7XvqVUOp0t/2H5E0tBk4o5z3QHNb/C8AACBM0p9lnqTnx2OocefKJNJ5igSsAAACJanBCyzmQQsABhJnN0AGPMOHrOHtA3hngMnfXoyXOq9AVBWXh/C0QGMZ55OXn39mwMAABCo3jbvRZqXl6bB30hM6m07uG5VUcgTfi3mKM2fmT5k+ekzXSrbdVRt7eeHvJd3YZKWFGUPu9++ZOL7N1SoovaU4mOjA5pfw6mzarJ3BrQtAGAgTwlYDqdL3U7n0PVJvwIAICScPcZJk4MLnX0rwKJ8AAACRQIWgDGvM8RPLNvPDr0BMJzKumY1tXa62yICgCce2zH0UIAFAADCz5c27+FQlJ+hP+//eMjyLbuPGq7/5cUXKy7GojcrGrw+bNOXTPyvqy6XySS/2xDurLSpvNI2IE0LABAYi4cbtk5nj7oNErCiPSRmAQAA//R4uL5MC0IAGFkUYAEY8+JiRvdPmUtS7TG70gspwAIwPE/tGJxO4yeUAAAAwmG4Nu/hcGluqmImmdV1fmD6iVGxVGpSjGZPS9Fjr1b6nHTscLr0xp5jKshN0/4jzX7Pry9Nq+Zoi1aXFIQ8BQwAJgqLpxaEPS45DM57LRYKsAAACAVPD/gOLsCiBSEAhBdnOADGvNk51iEtNEZaR4hTuACMTxZaEAIAgAko2mLWvLw0n9a96tIstbSeU1Wdf4VUFQdP6rxjaHsrf/SladXb2oLaDwBMVGaPLQh71O0YWoBFAhYAAKHh9HB9efCxmQQsAAgvznAAjHnp1jgV+ngxP1ziB6VwNdk7VV5p0xt7j6u80qYme+cozQxAJPGYgNVDAhYAABjfFszK8Gm94sKpOnjM7nP6VR+XSzp0zO73vAZzOF0qK68Pej8AMBF5TMBy9hgmYEWTgAUAQEh4SsCKMg1OwPJ+7CUBCwACRwtCAOPCsuJc1RxtGZUUGZOk/ByrJKne1qbS8npV1TUPuGFgklSYl6ZlxbnKzUoa8TkCiAyeTl5JwAIAAOOdpxsC/ZkkHT91Vp2jnDBcWdesptZOpSfTZh4A/GHxkIDldHpoQUgCFgAAIeHpAd/BDwTTghAAwoszHADjQm5WklaXFHi80NPHHCVdu+BCXTFnSsjGnpuXpvTkOFXUntL9GypUOaj4SpJc6r2If/+GClXUngrZ2ADGFk/tGHy5IQkAADBW1dva9LvXDnhdzyXp6bJqtZ/rDtnYsy5K9nsbl6TaEKRpAcBE4yn12WMLQhKwAAAICU/Xly1RtCAEgJHEGQ6AcaMoP1PrVhVpXl6aBn89NEmal5emu265XDd/Ll8XhyiFyiSppDhX9bY2PV1W7TXFxuF06emyatXb2kIyPoCxxeIh4pkWhAAAYDwrLa/3OfHT4XTp8HH7kHO6QH3Q0BrQdh2jnMIFAGNRtMcCLJe6ScACACBsnB7OtwanWZGABQDhRQtCAONKblaS1qyYpyZ7p2qP29XR5VB8jEX5OdYB7SPiYkLz588lae+Bk6qsa/brhkJZeb3WrJgXkjkAGDs8JWDRghAAAIxXTfZOVdU1+7XNwWN25U+z6uCH9qDHDzRoND5E54wAMJF4Tn3uMTzvjfaSZA8AAHzjKQFrcJqVbwVYFEgDQKC4mgRgXEq3xindGufx/dk5VpmkIa0CA/E/e477vU1lXbOaWjsHFIUBGP88nbw6DZ4EHqzJ3qmDx+zq7HIoLsai2TnWYf/OAQAARIKDx+x+n3e5JM3KtuqDhtZRKVQ3ScrPsY74uAAw1nlKfXY4Xep2OIcsj7aYwz0lAAAmBE8dFga3B6YFIQCEFwVYACakdGucCvPSVOnHk9hZqfFqOdOlru6hF4z85ZJUe8yu9EKKJ4CJxOIpAWuYaIZ6W5tKy+tVVdc84OalSVJhXpqWFecqN0RtVQEAAEKtM8BWfglx0VpdUuBTq/dQm5uXxsMyABAAj+e8TuMELE/rAwAA/3hKwKIFIQCMLDIEAUxYy4pzfb7QYzGb9E9fnKOr52WFbPyOAG9EABi7PLZj8HBTsaL2lO7fUKHKQcVXUm8hZ2Vds+7fUKGK2lOhnSgAAECIBNr+PT7GoqL8TK1bVaR5eWkK9hZAlMn3c7+S4twgRwOAicli9pSA1aNux9BkDouF2xMAAIRCTwgLsEjAAoDAcYYDYMLKzUrS6pICr0VYFrNJq0sKlJuVpI9bOkI2fnyANyIAjF2e2jEYtSCst7X5lPjgcLr05H/v10tvHlZ5pU1N9s6QzBUAACAU+tq/+6N/C8DcrCStWTFPD3zrSt16wyW6Ys6UgObxmcsu8OkBnMVzLyBdFAACFBVlklG9q8PpUrfBeW+0h4ItAADgH18TsHwpriIBCwACx91/ABNa7xPVsSorrx+SMGNSb+uJkr+192qyd2r/kZaQjNv/hgKAicNjApbBCXJpeb3P7XZ6XNLre49LojUhAACILIG0fzdqAZhujVO6NU75F1m1p+bkkHTQ4Zgkff6KHF1VmGV47tdfKB+6AYCJyGKOGpJ25XT2yEECFgAAYeOpw8Lg69G0IASA8KIAC8CE1/dEdZO9U7XH7erocig+xqL8HOuAi/4Hj9n9usg/HKMbCgDGv+HaMUhSk71TB4/Z1Wjv9OsmZX99rQlrjrZodUmBivIzA50uAABASCwrzlXN0Rafisu9tQAMpqArPTluwLnfxh1HdPpM14B1D354WqfPdCllcozP+wcAfMJiNqnbMXBZt6PH8MEjErAAAAgNR8/QQmdpaCt2XxKwaEEIAIGjAAsA/qbviWpPOrscHt/zh7cbCgDGL09PDx050aq/1JxU1TBpDP5yOF16uqxa61bFkoQFAABGVV/7d2/tlfu3fx9OsAVdfed+Zzq69fJbHwx4zyVp78FT+tynLvK673DoK8jv7HIoLsai2TnWYc9TASDSmKOiJDkHLDt33mm4bjQJWAAAhESPQaGzOcokk2lwApb3Yy8JWAAQOAqwAMBHcTHB/8n09YYCgPHJ5qGlzdaKj8IynsPpUll5vdasmBeW/QMAAPjKn/bv3oSqoGvhJZl65a0PhhTAv1Pz8YgXYNXb2lRaXj+kIJ/20gDGGot56E3bc+eNH2r0lBINABgZb775pkpLS7V//341NjYqMTFR06ZN05IlS7Ry5UolJiaGdLy6ujq9+OKL2rNnj2w2m86dO6f09HTNnj1bN9xwg66//npFeSkQ2rhxo9atW+fzmN/+9rd1xx13BDv1iGeUNGlUSEULQgAILwqwAMBHs3OsMkkBp9NMTY3TN79I8RUwUVXUntKvN9WM+LiVdc1qau2k7SkAABh1vrZ/90UoCrpSk2KVn2PVwWP2AcvrbWd0sqVDU1Lj/ZrTYL6mWVXUnvJYTEZ7aQBjjVFRlacELKNiLQBA+LW3t2vt2rXatm3bgOUtLS1qaWnRe++9pw0bNuiRRx7R/Pnzgx7P6XRq/fr1+vWvfy2Xa+B33hMnTujEiRPatm2bnn/+eT3yyCOaMmVK0GNONE6DcwmzwXGWFoQAEF4UYAGAj9KtcSrMS1NlXXNA2xfkplF8BUxQh4/b9XRZteGTSOHmklR7zK70QgqwAABAZPDW/t1X/Qu6Glo61XneobhJFmWnxflc0LVwzpQhBViS9MLWQ/rU7CkBtQD0J82q3tbmNclLor00gLHDbFCA1emxBaE53NMBAAzidDq1Zs0a7dy5U5KUnp6uFStWaMaMGWptbdXmzZu1b98+2Ww23XbbbXrxxReVl5cX1Jj33HOPXnrpJUmS2WzWddddp0WLFikhIUENDQ3atGmTDh06pH379unWW2/VCy+8oKQk7995b7nlFi1atGjYdXJzc4d9f7wwuu4cZSIBCwBGGgVYAOCHZcW5qjna4vXiuJEzHefDMCMAY8F/vVEb0N+NUOnoMm73AAAAMB6kW+M06+J0mc1Rcjp71NLS7vO2l+dn6vnXDw25YVF1pEVVR1r8bgHob5pVaXm9z98TaS8NYCzwpwVhNAlYADDiXnnlFXfx1YwZM/Tss88qPT3d/f7NN9+sBx54QL/97W/V2tqqu+++W88//3zA4+3atctdfBUfH69nnnlGl19++YB1br31Vv3kJz/Ryy+/rMOHD+vhhx/WT37yE6/7njNnjpYsWRLw3MYTZ0/PkGVGRdG+FWDRIhgAAsVfUADwQ25WklaXFAQUkX6mozsMMwIQ6U62dKii9tSoziE+hpp7AAAAI4lx0booM9Hj+31FU/dvqPD6nc7fNKv3Djeqys+E5b720gAQqSwGN23PdXlqQcjtCQAYSU6nU48//rj75wcffHBA8VWftWvX6pJLLpEkvfvuuyovLw94zN///vfu12vWrBlSfCX1pmL9+Mc/dqdVvfzyy2poaAh4zInIKAHLqNiKFoQAEF6c4QCAn4ryM7VuVZHm5aVp8NdQk6R5eWnKyUwYsh0JWMDEVPVBk1yjF34lk6T8HOvoTQAAACCC1dvadOzUWa/r9RVN1dvahrzXZO9UeaVNv9lc41ea1X/vOCJ/vyb2tZcGgEhl9NBip6cELAu3JwBgJO3du1eNjY2SpIULF6qgoMBwPbPZrFtuucX985YtWwIar6enR3v27JEkmUwmfelLX/K4rsViUUlJiaTeQrHXXnstoDEnqh4fC7BoQQgA4UUcAgAEIDcrSWtWzFOTvVO1x+3q6HIoPsai/Byr0pPj9Ks/VunYqYFtL0jAAiamjnOj+9/+3Lw0pSfHjeocAAAAIlVpeb3hzQojg1sA1tvaVFper6q6Zr8LqSTpeKPvrRL7o700gEhm1O7I00NJJGABwMjasWOH+/XVV1897Lr93++/nT/sdrvOnTsnSUpNTZXVah12/b4ELEnatm2bbrvttoDGnYh8TcDypbiKBCwACBwFWAAQhHRrnNKtQwsbJsdPGrLsbGe3elwuRZn48gpMJPGx0SHd3+K5Wdq1/2OfbxROSY1XeaVNs3Oshn+vAAAAJqome2fALQA//PiMT+0Gw4H20gAimVEClsd1ScACgBF16NAh9+vCwsJh183IyFBWVpZsNpuamprU0tKi1NRUv8ZzBdEWoP9cPXnhhRf0zDPP6OOPP1ZPT49SUlI0e/ZsXX311fryl7+suLiJcy3U6ewZssyoKNqX4ioSsAAgcFyxAYAwmBw3tODC2eNSxzmHEg3eAzB+Fc5Il8nk+Ylff8zLS9M/XH+J5ual+XzD7/W9xyX1tiIszEvTsuJc5WYlBT8ZAACAMe7gMXtALQDLK2167S8fjkrxFe2lAUQ6f1KtaEEIACOrvr7e/To7O9vr+tnZ2bLZbJKkI0eO+F2AlZycrOjoaHV3d6ulpUWtra1KTk72uP7Ro0fdr9vb23Xy5ElNmTLF4/pVVVUDfrbZbLLZbHrrrbf0H//xH/r5z3+uz3zmM37NeazyPQHL+7GXAiwACBxnOAAQBkkJQxOwJOlMx/kRngmA0TYlNV5F+ZlB78diNqmkuDeGuyg/U+tWFWleXpp8PR12qTex4f4NFaqoPRX0fAAAAMa6zgBb+b1beypkxVcXZSb6tT7tpQFEOn9u2kbTghAARtSZM2fcr1NSUryu379lYP9tfWWxWDR//nxJvWlYpaWlHtd1Op0qKysbsKytrc1wXbPZrKKiIq1evVr333+/Hn30Ud13331auXKle84tLS36P//n/2jz5s1+z3ssMirAMkq78iUBixaEABA4ErAAIAwmxxunXJ3p6FZW2ghPBsCo+99L8/X+4caAb9RZzCatLikYkFyVm5WkNSvmqcneqdrjdn3wUau2v3/C674cTpeeKt2vG66croTYaMXFWGhPCAAAJqS4AFv5nWjqCMn4JklfWpyrJ/643/CGyWD9C/IBIFL5k4Dlz7oAgOB1dHzyPTYmJsbr+v3XaW9vD2jMm266SXv37pUkrV+/XoWFhbrssssGrNPT06N7771XR44cGbD87NmzQ/ZXVFSkbdu2aerUqUPeW7Fihf71X/9VP/rRj/Taa6/J5XLprrvu0oIFC3TBBRcENP9QSUqK9Wv9viKoqCiTUlMTvK5vMiiaip1kGbJtdKz3Di1pKQk+jYnw8vczgPGF3//YRQEWAITB5HgSsAB8YuZFVq0uKfC5bWAfk3pTDkqGaRuYbo1TujVOew/6nmrl7JHKdh0dMA7tCQEAwEQzO8cqk+R3G8JQmZuXpstmZuiKOVP05/0fe11/uO+EABApLGY/ErBoQQgA496NN96o0tJSlZeXq6OjQ6tWrdJ1112nRYsWKSEhQQ0NDdq0aZNqa2uVmpqqrq4ud7FXlEG7vGnTpg07XmJioh566CE1NTVpz5496urq0jPPPKMf//jHYfn3+cocYNGxyWSS2Ydjq9EDHRZL1JBxJ0Wbve4rOtoc8HwRer5+BjA+8fsfeyjAAoAwGC4BC8DE1Ns2MFZl5fWqrGsecKOvr9Dq6vkXqOOcQx1dDsXHWJSfY/WpxUyTvVNVdc0Bz62vPWHN0RatLikISctEAACASJdujVNhXpoq/fgedUFavE40B5+A1T/Nqs3HB3VOtoQmeQsAwsmfG7b+FGsBAIIXHx+v1tZWSVJXV5csluFvE3d1dblfJyQElsASFRWlRx99VN///vf1xhtvyOFwaNOmTdq0adOA9TIyMvTEE0/o1ltvdS9LSgrs4QOz2azvfOc7+trXviZJevvtt0e9AMvp7PFr/agok0wmk1wul3p8SMt1Gjz0G2UyGNfly+MnLr/ni9Dz9zOA8YXfv28isViUAiwACANPCVi+XlgHMD4Nbhvob6GVJweP2UOS3OBwuvR0WbXWrYolXQEAAEwIy4pzVXO0xaeUUnOUSZfPzhyQJBqIKJPc7aW7HT06dNzu03Z7D5zSV6+dqXgf2oYAwGjxp61gdATeMAGA8Wzy5MnuAqzTp097Laqy2+0Dtg1UYmKiHn/8cf35z3/Wxo0b9d5776mpqUlRUVHKzs7W0qVL9fWvf10JCQnu9CuTyaT09PSAx7zssssUExOjrq4unThxQp2dnYqLC/z6a7Da2s7J4XD6vH5qaoLMZpN6elxqafHe/rHrvGPIMqNtHT4UVp1pOyeLT4VaCCd/PwMYX/j9e2exmJWSEj/a0xiCAiwACIPEOIthKwsSsABIn7QNDJXOrqEn2IFyOF36zeYafeGKaZqdYw3pPAEAACJNblaSz62i585IU3FhljbtOhpU8fsF6QnuxNEjJ1p1vnvoTZDYSWadOz/wBs15R492V5/UtUXZQYwOAOFliaIFIQBEqtzcXDU0NEiSGhoalJ09/PfKvnUl6eKLLw56/KuuukpXXXWVx/dra2vldPZ+B54+fXpQRV9RUVFKTk7WqVOnJEltbW2jWoAVbkYtCM0Gx+QoH47TRtsBAHzDGQ4AhIE5KkoJcUOfSj5DAhaAMIiLCW1N/YnmDv32tQO686ndeuSVv6re1hbS/QMAAESS3lbRRZqXl6bhbjVU1TXrLzUnFR0d3OW0jxrb3eeG1UdPG65z02dmGC7f/Oej2ll5Qk32zqDmAADh4k8CloUCLAAYUbNmzXK/rqqqGnbdpqYm2Ww2SVJaWppSU1PDOjdJ2rNnj/v1pz71qaD21dPTo7a2T65pBtrOcKwwakFoWIBlMsnkpb7KlyItAIAxznAAIEwmxxsVYJGABSD0ZudYh71ZGCiXpMq6Zt2/oUIVtafCMAIAAEBk6GsV/cC3rtStN1yiizKHtmNxOF3auOOIYWKVJ1EGdzdckqqONEuSDnzYMuT9SdFRKp6bpZnZyUPea20/r9+9dnBAoXyTvVPllTa9sfe4yittFGcBGFVms+9np/4UawEAgrd48WL36x07dgy77vbt292vr7nmmrDNqY/L5dLGjRvdP69YsSKo/b3//vs6d+6cJGnq1KnjOv1KknoMWgZ6SrLylnBFAhYABI4WhAAQJpPjJ8nW3DFgGQlYAMIh3Rqnwrw0VdY1h2X/DqdLT5Xu1w1XTldCbLTiYiy0JwQAAONSX6voCzMSdM/v3w1qXxazSSs/O1Mb3jg05L2/ftCs+TMyVH/izJD38i9KkcUcpWlTJutwQ6vhvvsK5avqmoe0QzRJKsxL07LiXOVmje8n/QFEHn+KqqIpwAKAEbVw4UJlZGSosbFRe/bsUXV1tQoKCoas53Q69dxzz7l/vv7668M+t5deekk1NTXuec6dOzfgffX09Oixxx5z//x3f/d3wU4v4jmdQx8SMXs4zkZFmaRh2q+TgAUAgRszBVhvvvmmSktLtX//fjU2NioxMVHTpk3TkiVLtHLlSiUmJoZl3JqaGm3atEm7d+/Wxx9/rLNnzyolJUUZGRmaP3++Fi5cqKVLl8psNodlfABjFwlYAEbSsuJc1RxtkWOYk+dgOHuksl1H3T9zYw8AAIxnLlfv951AvlmZJM3NS1PJ374nvbmvYcjDOfvrm1VztMXwSfU501NUb2vT2+9/5H2eHpZV1vXuf3VJgYryMwP4VwBAYCw+JmCZo0zc4AWAEWY2m3X77bfrpz/9qSTpzjvv1LPPPqu0tLQB6z300EM6cOCAJGnBggUDkrP627hxo9atWyept2iqf9FWf++//77mzJmjSZMmDXnP5XLp5Zdf1n333SdJio+P189+9jPD/bz33ns6dOiQvvSlLykmJsZwnY6ODt19993avXu3JGnSpEn65je/abjueOLs8ScBK0qS51RfErAAIHARX4DV3t6utWvXatu2bQOWt7S0qKWlRe+99542bNigRx55RPPnzw/ZuGfPntXPfvYz/fGPf5Rr0MWwU6dO6dSpU6qurtbzzz+vvXv3jvvewQD8Nzl+6MnEmY5u9bhchm0oACAYuVlJWl1SoKfLqsNWhNVfMDf2muydOnjMrs4uB2laAAAgIpWW1/tVfHVRRoKK512g+BiL8nOsSk/+5LvNvBnpsjUfG7B+Z5dzQHF7f3Omp+oP2+uC/k7ncLr0dFm11q2KpWAewIjpvanrHe0HAWB03HTTTdq6dat27dqlw4cPa9myZVqxYoVmzJghu92uLVu2qKKiQpKUlJSke+65J+gxn3zySe3bt09XX321CgsLlZmZqe7ubh0/flyvv/66amtrJUmxsbF69NFHlZOTY7if5uZm3X333frFL36hT3/60yooKFBWVpbi4uJ05swZ1dTUaMuWLbLb7ZIkk8mk++67T9nZ2UH/GyKdUQGWp0JnbwVWFEgDQOAiugDL6XRqzZo12rlzpyQpPT3d/SWgtbVVmzdv1r59+2Sz2XTbbbfpxRdfVF5eXtDj2u123Xrrrdq/f78kacqUKfrc5z6n/Px8TZ48We3t7frwww+1a9cuVVdXBz0egPEpySABq8flUsc5hxLjhr4HAMEqys/UulWxKiuvV6VBO5pw8OfGXr2tTaXl9UNa5ZCmBQAAIkmTvVNVfrZ2bmhs12Uz0wcUXvWZl5em/3nnmME2Z4csmxwfrZhJUX6P74nD6VJZeb3WrJgXkv0BgDe+JmBFWyjAAoDRYLFY9Nhjj2nt2rV666231NjYqCeeeGLIelOnTtX69es1c+bMkIzb1tamzZs3a/PmzYbvz5gxQ/fee68WLFjgdV8dHR1644039MYbb3hcJyMjQ/fdd9+EaD8oGRdgWTwUUg1XYGUyiQABAAhCRBdgvfLKK+7iqxkzZujZZ59Venq6+/2bb75ZDzzwgH7729+qtbVVd999t55//vmgx/3e977nLr76x3/8R33nO98xjLL87ne/q5MnTyo+Pj7oMQGMP0YJWJJ0puM8BVgAwiY3K0lrVsxTk71Ttcft6uhyqL2zW1t2f2h4Ih4KvtzYq6g95TGdizY5AAAgkhw8Zve7kN0lqfaYXemFQwuwZmQnKyHWovZzDq/7uWRaig4daw1pIf1f65r1P+98qMvzM0kdBRB2viZb+VqoBQAIvcTERD311FPaunWrSktLVVVVpebmZiUkJCgnJ0dLly7VypUrNXny5JCMt2bNGhUWFmrv3r1qaGhQc3OzTCaT0tLSVFBQoKVLl+oLX/iCLJbhb1tfeeWVeuKJJ1RZWanKykrZbDbZ7XadOXNGsbGxSktL05w5c/R3f/d3uu666zy2KRyPnAbXXD2lUg6XgEX7QQAITsQWYDmdTj3++OPunx988MEBxVd91q5dq927d+vAgQN69913VV5eruLi4oDH3bhxo8rLyyVJX/3qV3XnnXcOu/6UKVMCHgvA+DbZIAFL6m1DmJVm+BYAhEy6NW7ADbaLMhPD2p5wuBt79bY2n8amTQ4AAIgEnV3eC6WMdHjYzhwVpcKL0/SXmpNe9zFnemrA4w/n5bfq9MpbdaSOAgg7MwlYADBmLFmyREuWLAl4++XLl2v58uVe15szZ47mzJkT8Dh9EhISdO211+raa68Nel/jicvlUo8rNC0IfW0lDAAwFrF/Rffu3avGxkZJ0sKFC1VQUGC4ntls1i233OL+ecuWLUGN+8wzz0iS4uPjtXbt2qD2BWBiGy4BCwBGWm97wiLNy0tTuJ5jevmtOt351G498spfVW9rU5O9U+WVNv1mc43PhV99aVoAAACjJS4msOcV44fZbu4M357CmTM9JeDxvelLHb1/Q4Xe2teg8kqb3th7XOWVNjXZO8MyJoCJx/cErIi9NQEAwJjiqeuBp6Lo4VoQDvceAMC7iE3A2rFjh/v11VdfPey6/d/vv52/KioqdOTIEUnStddeq8TExID3BQDDJWABwGgY3J7wT+98qBNNHSEdo+/GXlVdc8CtcyrrmtXU2qn0ZFrkAACAkTc7xyqT5Nd3GZOk/Byrx/cvzU1TlMlk+GR6n0mWKJ3p6A5ofH84nC499/qhActMEulYAELC18KqaAqwAAAICY8FWAElYFGABQDBiNiznEOHPrkQVFhYOOy6GRkZysrKkiQ1NTWppaUloDH37t3rfj1v3jxJ0uuvv65vfvOb+vSnP61LL71UxcXFuu222/SHP/xBDkfoI+EBjB+eErDaSMACMMrSrXH6dGGWbr1hjiw+tofwVzA3DF2Sao/ZQzQTAAAA/6Rb41SY51/f+Ll5acMWjyfGRWtK6vDF5ecdPbp/Q4U+PHnG7/GD1T8dq6L21IiODWB8sfh445YWhAAAhIbTQ+cBCrAAYORF7FlOff0nrWeys7O9rt9/nb4UK3/t37/f/TotLU133HGH7rjjDu3YsUNNTU3q7u5WY2Ojtm/frrvuuktf/vKXdfz48YDGAjD+JcZZDNt8kYAFIFLkZiVpdUlB2IqwgrG/voVWOAAAYNQsK871+TuSxWxSSXHusOvU29p0ssV78qjD6dLTZdX61OzMUfmO1jd+va1tyHt97aVpWwhgOGZaEAIAMKI8pex6KqaiBSEAhE/EtiA8c+aM+3VKSorX9a1Wq+G2/mhsbHS/fuyxx1RfX6/o6Gh96UtfUlFRkSwWiw4ePKhXX31Vdrtdhw4d0t///d9r48aNA8YfaUlJsX5v03cAjYoyKTU1IdRTQoTj9z9yEuOjhxRcdTl6Rv3/dz4DAPoU5Wdq3apYlZXXqzKItoGh9k7NSe2pOUkrHAAAMCr6CtWfLquWw8MT5VJv8dXqkgKv31VKy+vloTPIEA6nS+8ePOXT+OHgcLpUVl6vNSt60+HrbW0qLa8f0mKatoUAjPhcvEoCFgAAIeF09hgu91QUTQIWAIRPxBZgdXR88lRgTEyM1/X7r9Pe3h7QmK2tre7X9fX1Sk5O1u9//3vNmTPHvfyLX/yivvGNb+gb3/iGPvjgA3300Ud6+OGHdc899wQ0Zij4+lSREZPJJHMEpl5gZPD7D7/kxJghBVht7eeD+u82lPgMAJB6bzCuWTFPTfZO1R63q6PLofbObm3Z/aGcvt4pDIO+Vjg1R1u0uqRARfmZozYXAAAw8QxXqG5Sb9vBEh+Kj5rsnaqqa/Zr7Mq6Zt38uVlat6rIY6G8ScG1ffY2flNrpz78+IzHIjC+qwEw4muyVXSEXBsDAGCs83T9lgQsABh5EVuANRpcgyIa/+3f/m1A8VWfjIwM/fKXv9SyZcskSX/84x/1b//2b0pMTByReQ7mqbJ5OFFRJplMJrlcLvWM4o1VjA5+/yMnOWGSGgYtaz3bFdB/t6HEZ8C7SCmSA0ZSujVO6dY4988XZSaOSurCYH2tcNatiiVdAQAAjCijQvX4GIvyc6xKT47zvgNJB4/Z/S6UckmqPWbXpwuzPI5/pqM7bCmmLknllTa99pcPvX4X5LsagP58fdCPBCwAAELDUwGWp2Iqc5TnYzAJWAAQnIgtwIqPj3cnUnV1dcliGX6qXV1d7tcJCYG10+q/XXx8vEpKSjyuO3v2bM2fP1/vv/++zp8/r4qKCl1zzTUBjRustrZzcjicfm2Tmpogs9mknh6XWloCSwzD2MXvf+TETjIPWXb6TNeo///OZ2B4FotZKSnxoz0NYNRFUnvCwa1wAAAARtLgQnV/dHY5Atquo992RuOnJ8e5i7PerT2ll9+qC2gcT3b89YTPhfh8VwPQx9dkq2gS2QEACAlPBVgWjwVYtCAEgHCJ2AKsyZMnuwuwTp8+7bWoym63D9g2EElJnzylN2vWLE2aNGnY9S+99FK9//77kqTjx48HNCaA8S0pfujfkbMd3epxuRRl4ossgMjXP/UhHDf2/NHXCsfXtAkAiEROp1N1dXXav3+/qqurtX//fh08eFDnzp2TJH35y1/WL37xi7CM/eabb6q0tFT79+9XY2OjEhMTNW3aNC1ZskQrV64ctVRnYLyLiwns8lu8j9ulW+P0hSum6eAxuyr9bHU4HPvZ836tz3c1AJLvieLRJGABABASnjqueDom04IQAMInYguwcnNz1dDQ27iroaFB2dnZw67ft64kXXzxxQGNefHFF2v37t2S5NOF5/7rnD17NqAxAYxvk+OjhyzrcbnUcc6hxLih7wFApArXjT1/uCT9YfsRFUxP1ewcq9cUiiZ7pw4es6uzy6G4GItP2wBAuH3nO9/R66+/PqJjtre3a+3atdq2bduA5S0tLWppadF7772nDRs26JFHHtH8+fNHdG7ARDA7xyqT5FeaqElSfo7Vr3GWFeeq5mjLqLWP7mubmF7I9y1gIrP42oLQx0ItAAAwPE8JWJ7SrEjAAoDwidgCrFmzZmnnzp2SpKqqKi1atMjjuk1NTbLZbJKktLQ0paamBjTm7Nmz3a99Kajqv06gqVsAxrfJBglYknSm4zwFWADGpNG+sfdOzUm9U3NSJkmFeWlaVpyr3KykAevU29pUWl6vqkFtE4fbBgBGitM5sH281WqV1WrV0aNHwzbemjVr3OfX6enpWrFihWbMmKHW1lZt3rxZ+/btk81m02233aYXX3xReXl5YZkLMFGlW+NUmJfmVxH73Lw0v5OkcrOStLqkQE+XVY/ad7WOANstAhg/LFG+FVZRgAUAQGh4KsDylGY1fAEWx2cACEbE/hVdvHix+/WOHTuGXXf79u3u19dcc03AY1599dUy/a0l2KFDh3T+/PBR6/v373e/zs3NDXhcAOOXUQKWJJ3p6B7hmQBAaPTd2PP1qWZPgn2YyqXeNjc/f+5dbXi9Vm/sPa7ySpve2teg+zdUqHJQ8VX/be7fUKGK2lPBTQAAAjR37lzddtttevTRR7V161a98847Wr16ddjGe+WVV9zFVzNmzFBpaam+853v6MYbb9TNN9+sF198Uf/4j/8oSWptbdXdd98dtrkAE9my4lw/UmFMKikO7DpTUX6m1q0q0ry8NI3Gs+u+tk0EMH75+reOFoQAAISGvwlYtCAEgPCJ2KsiCxcuVEZGhhobG7Vnzx5VV1eroKBgyHpOp1PPPfec++frr78+4DGnTp2qT33qU9qzZ486OjpUVlamr3zlK4brHjx4UO+//74kKSEhQQsWLAh4XADj13AJWAAwVvXe2ItVWXm9YaGTtxY7FrNJX712pja8fsivVjxGnD3Stn0f+bWNw+nS02XVWrcqliQsACPuW9/61oiN5XQ69fjjj7t/fvDBB5Wenj5kvbVr12r37t06cOCA3n33XZWXl6u4uHjE5glMBL6mU1nMJq0uKQjqO0puVpLWrJinJnunao/b1dHlUHyMRecdTr249XDY0rECaZsIYPwx+5hsFU0CFgAAIeF09hgu95RmRQtCAAifiD3LMZvNuv32290/33nnnWpuHhrV/tBDD+nAgQOSpAULFgxIzupv48aNys/PV35+vm655RaP4373u991v37wwQdVU1MzZJ2mpiatXbvW/fMtt9yi2NhY7/8oABOOpwSsNhKwAIxxfTf2HvjWlbr1hkv01SUzdesNl+jB/3Olfvj3lxumLpgkzctL07pVRfrMgmwV5qWNxtQl9RZhlZXXj9r4ADAS9u7dq8bGRkm9DzkZPdQk9Z5/9z9P3rJly4jMD5hohkun6v89qSg/MyTjpVvj9OnCLC29/CJ9ujBLn7ksO6zpWIG0TQQw/vic9kcCFgAAIdHjZwIWBVgAED4Rm4AlSTfddJO2bt2qXbt26fDhw1q2bJlWrFihGTNmyG63a8uWLaqoqJAkJSUl6Z577gl6zMsuu0zf/OY39cwzz6i1tVU33XSTvvzlL6uoqEgWi0UHDhzQq6++KrvdLkm69NJLBxSKAUB/SSRgARjn0q1xSrcOvNGWnhxnmLqQn2MdcFNuWXGuao62hC2FwZvKumY1tXZyoxDAuLVjxw7366uvvnrYdfu/3387AKHlKZ1q8PekkRj/DzuO6J2akyHZbzBtEwGMLxYSsAAAGFEeWxB6KIqmBSEAhE9EF2BZLBY99thjWrt2rd566y01NjbqiSeeGLLe1KlTtX79es2cOTMk465du1Zms1nPPPOMuru79fLLL+vll18esl5xcbEefvhhxcTEhGRcAONPYly0YSuuMyRgAZgAjIqz+vO1FU+4uCRt2nVUX7xq+rDzBICx6tChQ+7XhYWFw66bkZGhrKws2Ww2NTU1qaWlRampqeGeIjBhefueNBLjF0xPDUkBVijaJgIYP3xNziABCwCA0HCQgAUAESOiC7AkKTExUU899ZS2bt2q0tJSVVVVqbm5WQkJCcrJydHSpUu1cuVKTZ48OaTj/su//Iuuu+46vfrqq9q1a5dOnjwph8OhtLQ0XXbZZVq2bJmuueaakI4JYPyJijIpIS5aZzsHFlyRgAUAvXpb8cSqrLxelXXNQwpWw21npU3llTYV5qVpWXGu3zcOm+ydOnjMrs4uh+JiLJqdY/V6MzWQbQAgEPX1n7Razc7O9rp+dna2bDabJOnIkSMUYAHj3Owcq+EDQ/7Iv8iqmz47g+IrAG4mk0nmKJPHNI4+vrYqBAAAw3N6eLDVUzFVVJTnImgSsAAgOBFfgNVnyZIlWrJkScDbL1++XMuXL/drm9mzZ+uHP/xhwGMCgCRNjjcqwCIBCwD6DG7Fs7++JWTtcHzhUm87wpqjLVpdUqCi/Mwh6wwumkqItWj7X0+oalDRmEnyWMxVb2tTaXm9X9sAQDDOnDnjfp2SkuJ1favVarjtSEtKivV7m76LxFFRJqWmJoR6ShgD+Az4LzU1QUWzM/XuwVMB7+N/fXamigqmhnBWgeH3D0QWizlKzh7nsOtEk4AFAEBI9Lg8FWAZH2tJwAKA8BkzBVgAMFZNjp8kW3PHgGVtJGABwBB9rXjyL7JqT83JEU/DcjhderqsWutWxboLoTwVTXkyuJhr6ZW5kqTdVTb98oUKw1aLvhSAAUAgOjo++Q4aExPjdf3+67S3t4dlTr4wmwO/IWsymWQmUWNC4zPgn69+frbeP9wkh7MnoO1Pnu4I6r/ZUOP3D0QGi9mkLi/PHkZH0N8OAADGMqeH7/KevhdTgAUA4UMBFgCE2eT46CHLSMACAM/SrXEqzEtTZV3ziI/tcLr0+9cOqHjuBTp5ukPb3z/htXWGp/08XVat6dkpiooy6Zcv7DMsvjLapn8BGABMRJ4uHg8nKsokk8kkl8ulngD+bmPs4zMQmLwLk/W9ry3423cVz//tWcxRhu9/1Hg2oP9mQ43fv28iqVgO45svnzULn0cAAELC07VLzy0IPRdZ0YIQAIJDARYAhFlS/KQhy852dKvH5VKUiS+ziDxvvvmmSktLtX//fjU2NioxMVHTpk3TkiVLtHLlSiUmJoZknFtuuUV79uzxa17Z2dkhGRuRb1lxrmqOtngtWgqH443tevHNw0Hvx+F06Vev/lXOHpfPqRIOp0tl5fVas2Je0OMDQHx8vFpbWyVJXV1dsliGvwTQ1dXlfp2QMHotvNrazsnhGL5t0WCpqQkym03q6XGppWX00rswevgMBC7/wiStW7VAZeX1qjRolTw3L00lxbl6fGOVTp/pGrDt8Y/PRMT/3/z+vbNYzEpJiR/taWCCsPiQREcLQgAAQsNTAZanYioSsAAgfCjAAoAwM0rA6nG51HHOocS4oe8Bo6W9vV1r167Vtm3bBixvaWlRS0uL3nvvPW3YsEGPPPKI5s+fPzqTxISRm5Wk1SUFerqselSKsELlqK3N720q65rV1Nqp9OS4MMwIwEQyefJkdwHW6dOnvRZV2e32AdsCmDhys5K0ZsU8Ndk7VXvcro4uh+JjLMrPsbq/k0xJiRtSgHXqdIfR7gBMcJYoErAAABgp/iZgDV+AxfEZAIJBARYAhNlkgwQsSTrTcZ4CLEQMp9OpNWvWaOfOnZKk9PR0rVixQjNmzFBra6s2b96sffv2yWaz6bbbbtOLL76ovLy8kI3/q1/9yus6aWlpIRsPY0NRfqbWrYo1TGMYz1yS/rD9iAqmp2p2jlXpVgqxAAQmNzdXDQ0NkqSGhgavSZJ960rSxRdfHNa5AYhM6dY4j989MlPidPCYfcCyptZzcjh7KKQAMICZBCwAAEaMp5bgnloC04IQAMKHAiwACDOjBCxJOtPRrSzqSRAhXnnlFXfx1YwZM/Tss88qPT3d/f7NN9+sBx54QL/97W/V2tqqu+++W88//3zIxl+yZEnI9oXxxSiN4VRLh95+/4THp7uk3pYXX712po5+fEY7K20jOOPQeKfmpN6pOSmTpMK8NC0rzlVuVtJoTwvAGDNr1iz38b2qqkqLFi3yuG5TU5Nstt6/l2lpaUpNTR2ROQIYOzIMCrNcLqm59ZympNLaDsAnfCnKjKZwEwCAkOjxlIBlogUhAIw0CrAAIMw8JWC1tZ8f4ZkAxpxOpx5//HH3zw8++OCA4qs+a9eu1e7du3XgwAG9++67Ki8vV3Fx8UhOFRPY4DSGqwqzDJOxTJLm5qWp5G8FS032TpVX2sZsepZLvS0Ja462aHVJgYryM0d7SgDGkMWLF+s3v/mNJGnHjh365je/6XHd7du3u19fc801YZ8bgLFnSopxkdUpeycFWAi5N998U6Wlpdq/f78aGxuVmJioadOmacmSJVq5cqUSExNDOl5DQ4NeffVVvfPOOzpy5IjOnj2rSZMmKTU1VZdccomWLl2q66+/XtHRnpPM33nnHX3961/3ecwvf/nL+sUvfhGK6Ucciw8JWBYSsAAACAmPLQg9HI+HazNIAhYABIcCLAAIM48JWJ3dIzwTwNjevXvV2NgoSVq4cKEKCgoM1zObzbrlllt01113SZK2bNlCARZGjVEyVnyMRfk5VqUnf1KolW6NU2FemirrmkdxtsFzOF16uqxa61bFkoQFwGcLFy5URkaGGhsbtWfPHlVXVxse551Op5577jn3z9dff/1IThPAGJGZYtya8NTpzhGeCcaz9vZ2rV27Vtu2bRuwvKWlRS0tLXrvvfe0YcMGPfLII5o/f35Ixvzd736nhx9+WOfPD3xQzuFwqKOjQw0NDXrjjTf05JNP6rHHHtOsWbNCMu545qnlUX++FGkBAICBmuydOnjMrs4uh+JiLJqdY5XDUwGWh2Kq4YqsSMACgOBQgAUAYZbkIQHrTAcJWIgMO3bscL+++uqrh123//v9twNGy+BkLCPLinNVc7RFDudYzcHq5XC6VFZerzUr5o32VABEgI0bN2rdunWSegut+hdQ9TGbzbr99tv105/+VJJ055136tlnn1Va2sA+2A899JAOHDggSVqwYIEWL14c5tkDGIuMWhBK0snTHSM8E4xXTqdTa9ascbfPTU9P14oVKzRjxgy1trZq8+bN2rdvn2w2m2677Ta9+OKLysvLC2rMDRs2DEihuuyyy/TZz35WWVlZOnv2rD744ANt3LhRHR0dqq+v19e//nVt2rRJGRkZw+73+uuv1w033DDsOllZWUHNPZJZfLh5G20xj8BMAAAYH+ptbSotr1fVoG4AkjQp2rjw+T831Wj51RcPeZiTFoQAED4UYAFAmCXGRcskDflSfKadBCxEhkOHDrlfFxYWDrtuRkaGsrKyZLPZ1NTUpJaWFqWmpgY9h9WrV6umpkanT59WXFycMjMzddlll+nGG2/UokWLgt4/JrbcrCStLinQ02XVY74Iq7KuWU2tnQNSvgCMLcePH9err746YFltba37dU1NjdavXz/g/UWLFunKK68MaLybbrpJW7du1a5du3T48GEtW7bMfTPbbrdry5YtqqiokCQlJSXpnnvuCWgcAONfXIxFSfHRausYeC5LAhZC5ZVXXnEXX82YMUPPPvus0tPT3e/ffPPNeuCBB/Tb3/5Wra2tuvvuu/X8888HPN65c+f08MMPu3++7777tGLFiiHr/fM//7P+/u//XocOHdLp06f161//2l0E7cnFF1+sJUuWBDy3sc7iQwJWNAlYAAD4pKL21LDXNc939xgur65vUe2x01pdUqCi/Ez38uESsGhBCADBoQALAMIsKsqkhLhonR3UcvBMJwlYiAz19fXu19nZ2V7Xz87Ols1mkyQdOXIkJAVYb7/9tvt1d3e32tra9MEHH+iVV17RokWL9O///u/KzMz0vAPAi6L8TK1bFauy8npVGjwpNla4JG3adVRfvGq61+QvT4yiygPdFwD/nThxQk899ZTH92trawcUZEmSxWIJuADLYrHoscce09q1a/XWW2+psbFRTzzxxJD1pk6dqvXr12vmzJkBjQNgYshMiVdbR+uAZY12CrAQPKfTqccff9z984MPPjig+KrP2rVrtXv3bh04cEDvvvuuysvLVVxcHNCY+/btU3t7u6Teh5GMiq8kKTU1Vd/73ve0evVqSdLevXsDGm8i8aUAy5d1AACY6A4ftwf1UKnD6dLTZdVatyrWnYRFAhYAhA8FWAAwAibHGxRgdZCAhchw5swZ9+uUlBSv61utVsNtA5GcnKyrrrpKl156qaZMmSKz2ayTJ09q9+7d2rFjh1wul/7yl79o5cqV+q//+i+vbR7CLSkp1q/1+54YiooyKTU1IRxTgh9SUxNUVJClky0dqj7SrI5z3dq697iO2tpGe2p+2VlpU3mVTUX5mfrfS/M18yKrT9sdPm7Xf71Rq4raU3L1u2ZjMsnvfcE3/A1ApEhMTNRTTz2lrVu3qrS0VFVVVWpublZCQoJycnK0dOlSrVy5UpMnTx7tqQKIcJkpcfrgo6EFWD09Lp6WR1D27t2rxsZGSb2tdQsKCgzXM5vNuuWWW3TXXXdJkrZs2RJwAVZzc7P79bRp04Zdt//7HR203fTG7EO6lcVCARYAAN781xu1QSf6O5wulZXXa82KeZK8FWBxfAaAYFCABQAjYHL8JNmaB16ga+sgAQuRof/F45iYGK/r91+n72nhQHz3u99VQUGBJk2aNOS9f/iHf1BVVZX+v//v/9OJEyf00Ucf6a677tIzzzwT8HihYA7wCV2TyeTTBWiMjAsyEnVBRqIk6ZLcNN35eLkcTuOobk9MJunyS6boc1dMU3tnt9rPdWvrnmOqP+F7MVdqUqxa2s75NW4fl0t69+ApvX+4Sd/80qWaZDGr41y34mOjVTgjXVNS43WypUNVHzSp41y3TjS16//95ajhBRtf9oXg8DcA/V1xxRVDEq4CsXz5ci1fvtyvbZYsWTKh2yEBCF6mQWqmw+lSy5lztEhGUHbs2OF+ffXVVw+7bv/3+2/nr7S0NPfro0ePDrtu//dJi/TOW7qVOcqkKBPfjwEAGM7Jlg5V1J4Kyb4q65rV1Nqp9OQ4WhACQBhRgAUAIyApPnrIMhKwMNFddtllw75fWFioX//61/rSl76k8+fPa8eOHaqsrNTcuXNHaIZDOf0s0omKMslkMsnlcqmnZ6w2vRvf8i5M1ve+tkC/fGHfsEVY5iiTPr9omi5IT1B8bLQuzUtTZsrAwqRZF6Vo3RO7fCrmspijtPrLhfrF/907II3KXw5nj578Q+WQ5ckJk9TWft6vVotG+yIdKzj8DfBNoMWtAICRl5liXGR16nQnBVgIyqFDh9yvCwsLh103IyNDWVlZstlsampqUktLi1JTU/0es6ioSCkpKTp9+rT279+vV155xbANYUtLix5++GFJUlRUlL7xjW943ffrr7+urVu36vjx4+ru7lZycrJmzZqlq666Sl/5ylcGJEuPRxYvN2+jSb8CAMCrqg+agrpu2J9LUu0xu9IL42hBCABhRAEWAIyAyfFDE37OdnSrx+XiiT+Muvj4eLW29rYR6erqksUy/NeDrq4u9+uEhPC21MrLy9OyZcv0yiuvSJLefvvtUS3Aams7J4fD6fP6qakJMptN6ulxqaUl8LQwhFf+hUlat2qBysrrVVnXPKBoySRpbl6aSopzlZuV9MkbrqG/07SEaK0umaOny6qHjQa3mE1aXTJHM7Mmq/DiNFXWNXtcN1Ct7aFJWexLx3rv0CldM/9CTUmJV1yMRbNzrEo3SMDAQPwN8M5iMSslhZQ1ABgrBheg9zll79ScEZ4Lxpf6+nr36+zsbK/rZ2dny2azSZKOHDkSUAFWTEyMfvrTn+q73/2uHA6HfvjDH2rjxo367Gc/q6ysLJ09e1aHDx/WH//4R7W3tys+Pl4/+9nPVFRU5HXf/QvKJKmxsVGNjY3atWuXfvWrX+kHP/iBvvKVr/g957HCW4G9t4QsAAAgdZwL7UP8HV0OSd5aEHK/CgCCQQEWAIyAyQYJWD0ulzrOOZQYN/Q9YCRNnjzZXYB1+vRpr0VVdrt9wLbhdsUVV7gLsOrq6sI+Hiam3KwkrVkxT032TtUet6ujy6H4GIvyc6x+pTkU5Wdq3apYn4u5lhXnquZoy7AFW5HA2SNt2/eR+2eTpMK8NC0bXJgGAADGteESsIBgnDlzxv06JSXF6/r9E6T6b+uvz3/+8/rd736ne+65R4cPH9a+ffu0b9++AetER0frW9/6llauXKmsrKxh92cymTRnzhxdccUVuvjiizV58mR1dHSotrZWf/rTn3Ty5El1dHToBz/4gVpaWnTbbbcFPPdIZvHSfpsELAAAvIuPDe29o/iY3rIAWhACQPhQgAUAI8AoAUuSznScpwALoy43N1cNDQ2SpIaGBq9PG/etK0kXX3xxWOcmacCTzMFcWAd8kW6NCzrZqX8xV0NLpzrPOxQ3yaLstLghxVy5WUlaXVLgNTUr0rgkVdY1q+Zoi7567UxFW8zq7HKQjgUAwDiXGBet+BiL++n5PhRgIVgdHR3u1zExMV7X779Oe3twSaOf+tSn9KMf/Ui/+MUvVFNTM+T97u5uvfDCC+rs7NR3v/tdxcbGGu4nNzdXf/rTn5Sbm2v4/ve+9z099NBDevbZZyVJDz/8sBYuXKj58+cHNf9gJCUZ/1uG03djNirKpNRU4we4EhOG/x3GTDJ73BaRzZffP8Y3PgPAyCmckS6TSSFpQ2iSlJ9jlUQCFgCEEwVYADACjBKwJKmt/byy0jhRxeiaNWuWdu7cKUmqqqrSokWLPK7b1NTkbvOQlpYWUJsHf50+fdr9eiQSt4BQSbfGadbF6TKbo+R09nhsQTdcalakczhdeu71ge1VSMcCAGB8y0yJ09GPBz4Ycep0h4e1gcjW0tKi73znO3rnnXeUnJysdevW6dprr9XUqVN17tw57d+/X7/73e+0fft2Pfvss3rvvff0n//5n4YpXZmZmcOONWnSJN11112y2+0qLS2Vy+XSE088of/8z/8M1z/PK2+tAodjMplk9pB05S3hKtpiDmpsjL7hfv+YGPgMAOE3JTVeRfmZevfgqaD3NTcvzf1gKAlYABA+FGABwAjwnIAV2h7eQCAWL16s3/zmN5KkHTt26Jvf/KbHdbdv3+5+fc0114R9bpL0zjvvuF97epIYGOv6p2Zt+vNR7ay0jfaUAtY/HWt1SYGK8ofeiGqyd+rgMfuQ1CxPywEAQOQwLMCyd8rlcslk4oYNAhMfH6/W1lZJUldXlyyW4S9bd3V1uV8nJAT2YFtnZ6duvvlmHTlyRMnJyXr55Zc1ffp09/vR0dG68sordeWVV+qee+7R888/r8rKSt1333365S9/GdCYkvTd735XZWVlcrlc2r17t86dO+cxVSvcnM4ev7eJijLJZDLJ5XKpp8f48RFv6RnRZlNAY2P0+fL7x/jGZ8A7CkwRSv97ab7eP9wYVHK+xWxSSfEn19XNUZ4/oyRgAUBwKMACgBGQ5CEB60wnBVgYfQsXLlRGRoYaGxu1Z88eVVdXq6CgYMh6TqdTzz33nPvn66+/Puxzq6+vV2lpqfvnz3zmM2EfExhN6dY4ffGq6SqvtI2pJCwjDqdLT/73fi25/CJlZyRqdo5VZzq7VVperyqDpK/J8dFDCpNJ0wIAIPJkpgwtjj7f3aPW9vOyJnpvHSd5LsbGxDV58mR3Adbp06e9FlXZ7fYB2wbihRde0JEjRyRJ//iP/zig+GqwtWvXatOmTWpra9Nrr72m73//+8rIyAho3KlTp2ratGk6evSozp8/r4aGBs2YMSOgfQWrre2cHA6nX9ukpibIbDapp8flMeW3+7zDcHkfk0ket0Vk8+X3j/GNz8DwLBazUlLiR3saGEdmXmTV6pICPfHf+wNqRWgxm7S6pGDAdTVaEAJA+FCABQAjwGMCVvv5EZ4JMJTZbNbtt9+un/70p5KkO++8U88++6zS0tIGrPfQQw/pwIEDkqQFCxZo8eLFhvvbuHGj1q1bJ6m3uKt/0Vaf//t//68uvfRSLViwwOO8ampq9O1vf9v9ZHNxcbHmzZvn/z8QGGPSrXEqzEtTZV3zaE8laD0u6fW9x90/mySPhWVGqZC+pGkBAICRlWk1vql46nSn1wKselubYTE2RdfIzc1VQ0ODJKmhoUHZ2dnDrt+3riRdfPHFAY359ttvu19/+tOfHnbd+Ph4XXbZZdq+fbt6enpUVVWlz372swGNK0kpKSk6evSoJKmtrS3g/UQqi5f0l2jSYQAA8FlRfqampMTr4xbjtt9J8dFqM3iocW5emkoMvl/TghAAwocCLAAYAYlx0YY3nWlBiEhx0003aevWrdq1a5cOHz6sZcuWacWKFZoxY4bsdru2bNmiiooKSVJSUpLuueeeoMb7y1/+op/97GfKycnRlVdeqVmzZslqtSoqKkqnTp3SX/7yF/eFbUm68MIL9fOf/zzofycwViwrzlXN0Zag4sUjUaD/GofTpafLqrVuVSw3ZQEAGGVGCViSdPJ0h2ZdZPW4XUXtKT1dVm34/Yaia8yaNUs7d+6UJFVVVWnRokUe121qapLN1tuyOy0tTampqQGNeerUKfdrX1K0+q/T0WF8A9RXp0+fdr9OShp/32+9td/yVqAFAAAG6jg39F7StCmT9c/LL1V6cpya7J2qPW5XR5dD8TEW5edYlZ5s/L19+AQsjtEAEAwKsABgBERFmZQQF62zg1oOnukkAQuRwWKx6LHHHtPatWv11ltvqbGxUU888cSQ9aZOnar169dr5syZIRn32LFjOnbs2LDrFBcX6+c//7mmTJkSkjGBsSA3K0mrSwo83qSciBxOl36zuUZfuGLagDZFtDACAGBkTfFQgNVo7/S4Tb2tzafvNRRdT1yLFy/Wb37zG0nSjh079M1vftPjutu3b3e/vuaaawIes3+bQ5vNNmwLQkk6ceKE+7XVag143JMnT+rDDz+UJE2aNEkXXnhhwPuKVBbz8OkZ0RZu7gIA4KtuR8+QhCtJmpGd7C6ySrfG+Xw9jBaEABA+FGABwAiZHD+0AKuNFoSIIImJiXrqqae0detWlZaWqqqqSs3NzUpISFBOTo6WLl2qlStX+vRksDff//739ZnPfEaVlZU6ePCgmpubdfr0aXV3dysxMVEXXnihLrvsMn3xi1+k7SAmrKL8TK1bFauy8npVDmrTM1GdaO7Qb187IJOkvAuTZTJJHzS00sIIAIARlJQwSTHRZnV1OwcsP3V6YAFW/yLp8kqbz0XlDqdLZeX1WrOC84CJZOHChcrIyFBjY6P27Nmj6upqFRQUDFnP6XQOaHN//fXXBzzmrFmzVF1dLUnatGmTrrzySo/rfvjhh6qsrJQkRUVF6dJLLw143EceeUQuV+9/D1dccYXi4sbfwwPeEq5IwAIAwHenz3YZLk9NGr79tye0IASA8KEACwBGyOT4SbI1D4yo//h0h5rsnSR1IKIsWbJES5YsCXj75cuXa/ny5cOuk5OTo5ycHK1YsSLgcYCJIDcrSWtWzBsSI37e4dSLWw8HlI5ljpL+bv6FykyND3pfo8Ul6YOPWj2+RwsjAADCx2QyKcMap4bGswOWn/xbAVa9rU2l5fWqCqKAvLKuWU2tnR7bpmD8MZvNuv322/XTn/5UknTnnXfq2WefVVpa2oD1HnroIR04cECStGDBAi1evNhwfxs3btS6desk9RZ39S/a6nPjjTfqj3/8o3v9yy67zPActbGxUd/5znfkcDgkSX/3d383JAHrww8/1Ouvv66vfvWrSkxMNJxTd3e31q9fr40bN7qX3X777YbrjnXe0jMowAIAwHen284ZLk+ZHFgBFglYABA+FGABwAgxSl+3nzmvO5/aTVIHAGBYRjHi06cmeUzHSoqPHhJNbpI0Ny9NJQbHm+H2NVbRwggAgPCZkjK0AOvU6U69e/CU/nNT8C2UXZJqj9mVXkgB1kRy0003aevWrdq1a5cOHz6sZcuWacWKFZoxY4bsdru2bNmiiooKSVJSUpLuueeeoMYrLi7W5z//ef2///f/5HK59MMf/lBlZWW69tprNWXKFHV1dWn//v0qLS1VW1ubpN7Wg9///veH7Kujo0MPPfSQHnvsMS1atEiFhYXKzs5WQkKCOjo6dOjQIf3pT3+SzWZzb/Mv//IvWrBgQVD/hkjlrcCKFoQAAPiupc1DAtbk2ID2RwEWAIQPBVgAMAIqak/p4HG74XskdQAAAuEpHSs/x6r05DiPy33d16mWDr39/gk5e8ZuSRYtjAAACI/MlKHfKTq7HHp6U7WcIUrV7OhyhGQ/GDssFosee+wxrV27Vm+99ZYaGxv1xBNPDFlv6tSpWr9+vWbOnBn0mA899JASExP1hz/8QZK0Z88e7dmzx3Dd3NxcrV+/XtOmTfO4v/Pnz2vHjh3asWOHx3USExO1bt06feUrXwlu8hHMYvQUYj/RJGABAOCzljPGCVi0IASAyEMBFgCEWb2tTU+XVcvl5Rq0w+nSk/+9X0suv0jZGYmanWOlNSEAwCujdKzhlvuzr6sKs8Z8MhYtjAAACL0MgwIsSSErvpKk+BguW05EiYmJeuqpp7R161aVlpaqqqpKzc3NSkhIUE5OjpYuXaqVK1dq8uTJIRlv0qRJ+vnPf65bbrlFGzdu1L59+9TQ0KCzZ88qOjpaqampuvTSS3Xttdfquuuu06RJkwz3k5eXp1//+tf661//qsrKSn300Uc6ffq02traFB0drZSUFM2ePVuf/vSntWzZMo9tCscLs5cCK4uFm7sAAPiq5czQBCyTJGtioC0IPR+nScACgOBwJQMAwqy0vN7n9gs9Lun1vccl9X6BpjUhAGA0eUrZOu9w6sWth4NuLzQSaGEEAEDoTQnzw0ImSfk51rCOgci2ZMkSLVmyJODtly9fruXLl/u8/iWXXKIf/OAHAY83adIkLV68WIsXLw54H+OJ1wQsWhACAOCz0wYtCJMSJ3lt+esJCVgAED4UYAFAGDXZO1VV1xzQtrQmBABECqM0relTk8ZMOhYtjAAACK3MlPiw7n9uXhrplcAY5q3FYKA3jAEAmIiMWhCmTg4s/UoaPuWKBCwACA5nOgAQRgeP2YO+Ke1wuvR0WbXqbW0hmRMAAKHQl471wLeu1K03XKLPfeqiiH1KjhZGAACEVsrkGK8JN4EySZqSGq/ySpua7J1hGQNAeHlrQeitQAsAAHzitEELwtTJsQHvjwIsAAgf7kQAQBh1hihxw+F0qay8XmtWzAvJ/gAACJX+6Vgzs5P1dFn1sK0JTZJhcXJSfLTaOrpDPj9aGAEAEHpRUSZlWONka+4I+b5dkl7fe1xS73G8MC9Ny4pzlZuVFPKxAISHtwJNCy0IAQDwyflup84YXC9LCSIBixaEABA+FGABQBjFhTBx4691zfqfdz7U5fmZ7hvdTfZOHTxmV2eXQ3ExFs3OsQ5pEQUAwEgpys/UulWxhq0JTeptJ1RSnKvJcdGqPW5XR5dD8TEW5edYlZ4cpyZ7p2qP2/Wndz7UiabQ3NClhREAAOGRGBsd9jFckirrmlVztEWrSwpUlJ8Z9jEBBM8SRQIWAACh0Nw6tP2gJKUmhSsBi2M0AASDAiwACKPZOVaPSR+BePmtOr3yVp3yLkyWySR90NA65OY2TwcDAEZTX2vCvmKqwUVWfYwKhvvStC5IT9D9GyqGTdLyhcVsUklxblD7AAAAQ1XUntIHJ1qD2sdFGQnKzkzU7uqTXtd1OF16uqxa61bFcq4LjAFmbwlYFGABAOCTplbjltypSeFJwKIFIQAEhzMdAAijdGucCvPSQrpPl6QPPmrV4UHFV33vVdY16/4NFaqoPRXScQEA8Ee6NU6fLszS0ssv0qcLs/xKocrNStLqkgKvrUuGYzGbtLqkgJu0AACEWL2tTU+XVcsVRJ20xWzSN66/RO3nHD5v43C6VFZeH/igAEaMtwKraFoQAgDgkya7cQFWUC0ITSaZPFxyowUhAASHMx0ACLNlxblB3UAORN/TwfW2thEdFwCAUOltZ1ikeXlpGnwUNUmaeWGyZmYne9z+H6+/hDZFAACEQWl5fVAplX1F0pPjolVV1+zXtpV1zR5TAABEDm8FWCRgAQDgG48tCCcH3oJQ8px0RQIWAASHFoQAEGZ9KR5Pl1UH3UrJH31PB69ZMW/ExgQAIJR8aWe4468n9Ps/HRyybUeX74kaAADAN032Tr+LpvqYJM3NS1NJca5ys5JUXmkbkursjUtS7TG70gt9T9YEMPK8tSCMtnBzFwAAXxg9fGCSlJw4Kaj9mqOi5HA6DZZzjAaAYFCABQAjoDfFI1Zl5fWqrGv2+yJzoPqeDvan7RMAAJEm3RqndKvxsawoP8OwAOtwQ6s+uyA73FMDAGBCOXjMHtD57NXzsnTjVdMHnJt2Blgs/d7hRrlc0uwcq8fvBwBGlyXKSwtCErAAAPBJs31oAlZy4qSg0yQ9tRqkBSEABIcCLAAYIYNTPI6fOqutFQ3q6QlfOZZL0qZdR/XFq6ZzYRoAMC4lxEbrwowEfdTYPmD5oeN2uVwumUxcOAIAIFQCLZq6MCNxyINBcTGBXZbcd6hJ+w41ySSpMC9Ny4pzlZqaENC+AISHxUsClsVCARYAAL4wSsBKCbL9oOQ56YoCLAAIDgVYADDC+qd4zMxODntrwp2VNpVX2twXpnOzksI2FgAAo2FWtnVIAdbpM11qbjtHCiQAACEUaNFUvMF2s3OsMkkBJ0S71Jv6XHO0Rd/7WpGK518Y4J4AhJq3VI5gUzsAAJgomuxDC7BSk2KC3q9RoZXJJEXxICMABIUzHQAYRb2tCYs0Ly9N4fxa23dh+v4NFaqoPRXGkQAAGHkzs5MNlx8+3jrCMwEAYHzrK5ryh0lSfo51yPJ0a5wK89KCnpPD6dIvX9inQ8dOB70vAKERFWXScPdvo0nAAgDAq65up850dA9ZnhqmBCyzlxbCAADvSMACgFHWvzXhu7Wn9PJbdWEby+F06anS/Wo8c17JCZMUG2PRRalxXtsTNtk7dfCYXZ1dDsXFWDQ7x0pLQwBAxJiZbTVcfrjBrisvnTqykwEAYBzrK5qqrGv2eZu5eWkeEymXFeeq5mhL0KnQDmePXnqjVj/4xsKg9gMgdCzmKHU7egzfiyYBCwAAr5oN0q8kKWVy8AlYxgVYpF8BQLAowAKACJFujdMXrpimg8fsfl3M9pezR3p56yH3zybJY3vCelubSsvrVVXXPKAtxHDbAAAw0tKSY5WWFKPmtq4Byw81kIAFAECo+VM0ZTGbVFKc6/H93KwkrS4p0NNl1UEXYe2tOan/3v6B5lzEA0NAJLCYTep2eHqPAiwAALxpajUuwApXC0KjZQAA/3CmAwARZllxrizmkfui66k9YUXtKd2/oUKVg4qvhtsGAIDRYpSCdaKpXWc7h0a1AwCAwPUVTXk7b7WYTVpdUuD1oZ2i/EytW1WkeXlpfrc3HOz3Ww7ozqd265FX/qp6W1uQewMQjOHaGNGCEAAA75o8JGCFqwUh5VcAEDzOdAAgwvh6MTvUHE6Xni6rVr2tTfW2Np+eQO6/DQAAo2nmRVbD5R+QggUAQMgNVzRlkjQvL03rVhWpKD/Tp/3lZiVpzYp5euBbV+rWGy7RglnpAc+NB4aAyDDcdS0SsAAA8K7Jfs5webAJWPW2Np0+0zVkeUeXgwcZACBItCAEgAjUezE7VmXl9UMSqEySZlyYLJl6byoH16RhIIfTpd9srpE5Ksrn9g8Op0tl5fVas2JeCGcCAIB/ZmYnGy4/1GDX/JmB38QFAADG+oqmmuydqj1uV0eXQ/ExFuXnWJWeHFgLwHRrnNKtcXK5pH2HmoKaX98DQ+tWxXpN4QIQesMVWZGABQCAd0YJWCaTlJw4KeB9VtSeGvbh+8q6ZtUcbdHqkgKfH6YAAHyCAiwAiFC+XMxusndq05+PamelLWTjnmju8HubyrpmNbV2BnyRHQCAYF2QnqCEWIvazzkGLD/cYB+dCQEAMEH0FU2F0uwcq0xS0A8c8cAQMHrMwxRgjXTqOwAAY1GjQQGWNTFm2Da/w/G38wkPMgCA/3jUBAAiXLo1Tp8uzNLSyy/SpwuzBhQ5pVvj9MWrpo96b26XpNpjdvfPTfZOlVfa9Mbe4yqvtHnsVQ4AQKhEmUy9CZGDHLWd0flu5yjMCAAABCrdGqfCvLSQ7KvvgSEAI8tTkZXFbJLJNNpXsgAAiHzNBt9hUycH3n6wtLze784nAAD/kIAFAGNc34XpyrrmUZ1HR5dD9bY2lZbXq8qgbWJhXpqWFefyxAQAIGxmXmTVXwcdD509LtXb2pSfkzJKswIAAIFYVpyrmqMtPt8k8sQladOuo/riVdNDntQFwDOLh3QO2g8CAOAbowfbUwIswGqyd6rKz3tIdD4BAP9RgAUA40CoLkwH41RLh1556wPDObj0Se/wr147U9EWszq7HIqLsWh2jpWL4ACAkJiVbTVc/sa7x5WWFMvxBgCAMSQ3K0mrSwp8apPizc5Km8orbe4HgybHRevgMTvnpUAYeU7AogALAABvus47dKaje8jy1KTYgPZ38Jjd7/befZ1P0gv5ngwAvqIACwDGgVBemA7U2++fkLPHe+/w514/NGAZ6VgAgFCZNnWyzFGmIcejfYea9N6hJo43AACMMUX5mVq3KlZl5fWqHJS07K++B4MGJzZLnJcC4WD2UGhFARYAAN41tZ4zXB5oAlZnlyOg7ToC3A4AJioKsABgnAjlhWl/TY6PNnwawxf907FWlxSoKD8ztJMDAEwYlXVN6vFQDEwaIwAAY1NuVpLWrJinJnun3q09pZffqgtqf0bfFCLlvLTJ3kkyF8YNTwlYtCAEAMC7Zg8FWIEmYMXFBFYSEB/gdgAwUfFXEwDGkf4XpmuP29XR5VB7Z7e27P7QazpVMAItvurP4XTpyf/eryWXX6TsjEQuNAMA/FJva9PTZdVeC5CHS2O8Zv4Fau90GN705IYoAACjK90apy9cMU0Hj9lVWdccljEcTpeeLqvWulWxI5qEVW9rU2l5/ZB0LpK5MJZ5SrqKJgELAACvmuydhstTA0zAmp1jlUnGDyN4YpKUn2MNaDwAmKgowAKAcSjdGjfgpvBFmYmj2p7QVz0u6fW9xyVxoRkA4J/S8vqAj3N9qReDb+aaJOVdmCyTSfqgoZUbogAARIBlxbmqOdoStvNbh9OlsvJ6rVkxb8DyQIqxfdmmovaUx/P1SEnmAgJhjjJOwKIFIQAA3jW1GhdgBdqCMN0ap8K8NL8eZJibl6b0ZB4+BAB/UIAFABPAaLYnDBQXmgEAvmqyd6oqDEkYLkkffNTq8b3KumZV1zfrmvkXakpKPMlYAACMgNysJK0uKQjrQ0aVdc1qau1UenJcQOlUvm7Tl+Dp7d8xWslcQDA8JmDRghAAAK+a7UNbEEaZTLImBlaAJfn3IIPFbFJJcW7AYwHAREUBFgBMEP3bEza0dOqP2+t0/OQZn7e/KCNB2RmJ2l1zMoyzHIoLzQAAbw4es49acbGzR9q27yP3z/3bGcrconNdDsXGWHRRahyFWQAAhEi4HzJySao9ZteHk874nU7lT6LVzkqbz0VknpK5gEhlMXtKwDJeDgAAPmGUgJWcOElRHhImfeHrgwwWs0mrSwq4HwMAAaAACwAmmHRrnGZdnK5pWUm68/FyOZw9XrexmE36xvWXqLS8fgRmOBQXmgEAw+nscoz2FNyGa2dIy0IAAEKn/0NGr1c0aOvf2tmHyvFTZ7VtX4NP6VRP/vd+Lbn8IsVEm/XaXz6Us8f7Nk+V7pcPp+MD9E/mAiKd2UMCloUELACIGG+++aZKS0u1f/9+NTY2KjExUdOmTdOSJUu0cuVKJSYmhnS8uro6vfjii9qzZ49sNpvOnTun9PR0zZ49WzfccIOuv/56RUUFfpz4y1/+om984xtyuXq/i1144YXatm1bqKY/oppbhyZgpSYFnn7VZ7gHGUzqbTtYwrUrAAgYBVgAMEHNyknR9762QL98ocKnpx0mx0WHpb2Tr7jQDADwJC4m8k9r+idefPXamYq2mNXZ5RjQtrDJ3qmDx+xDlgMAAM/SrXFace0svfnucblCGIV14MPTPqdT9bik1/0sAPO3+Er6JJkrvZDvB4h8HlsQelgOABg57e3tWrt27ZDipJaWFrW0tOi9997Thg0b9Mgjj2j+/PlBj+d0OrV+/Xr9+te/dhdH9Tlx4oROnDihbdu26fnnn9cjjzyiKVOm+D1GZ2enfvjDHw7Z/1jVZB+agJUyOTYk++7/IEPtcbs6uhyKj7EoP8fK/RcACFLk36kAAITNlYVZWreqyKenHcorbaPW3kniQjMAwLPZOVaZpFE9TvnK4XTpudcPDVk+OT5aZzq6BywjNQsAAN9MSY1X0ewpevfAyZDts+HU2ZDtK5Q6Iij5ExiOxUOLpGgSsABgVDmdTq1Zs0Y7d+6UJKWnp2vFihWaMWOGWltbtXnzZu3bt082m0233XabXnzxReXl5QU15j333KOXXnpJkmQ2m3Xddddp0aJFSkhIUENDgzZt2qRDhw5p3759uvXWW/XCCy8oKcm/6yC//OUvdfz4ccXHx6ujoyOo+Y62rvNOne3sHrI8dXLwCVj9pVvjePAPAEJszBRgjXQMppHvf//7+uMf/+j++dvf/rbuuOOOsI8LAOHk69MOkdDeiQvNAAAj6dY4FealDWn7N5YMLr6SfEvNAgAAvb76uXy9f6hRjkCipQa5KCNBxxvbQzCr0IsfA8mfgOQ5AcvTcgDAyHjllVfcxVczZszQs88+q/T0dPf7N998sx544AH99re/VWtrq+6++249//zzAY+3a9cud/FVfHy8nnnmGV1++eUD1rn11lv1k5/8RC+//LIOHz6shx9+WD/5yU98HmPfvn3uOa5Zs0b3339/wPONBC1nhrYflKTUpNAkYAEAwifiz9hHOgbTk+3btw8ovgKA8cbb0w6R0N6JC80AAE+WFeeq5miLz62CxhKj1Ky+dKxr5l+g9k6HYWGWp5aGtDoEAIxHs3JS9L2vLdAvX6gI6vtAlMmkS6anRmQBlklSfo51tKcB+MRsJgELACKN0+nU448/7v75wQcfHFB81Wft2rXavXu3Dhw4oHfffVfl5eUqLi4OaMzf//737tdr1qwZUnwl9aZi/fjHP9bevXtVX1+vl19+Wf/0T/+k7Oxsr/vv6urSXXfdpZ6eHn3+85/XkiVLxnwB1ukzXYbLQ52ABQAIvYi+kz0aMZhGzp49qx//+MeSNC6iKwEgEIG2d7rpM3mKmWTWi1sPB3UR3OhCMzeQAQB9crOStLqkQE+XVY/LIqzB+tKxBqd+mSTlXZgsk0n6oKF1yHGbVocAgPHsysIsrVtVpLLyelXWNQ85DvpyTmsxm3TaQ+rAaJublzYgqRqIZCRgAUDk2bt3rxobGyVJCxcuVEFBgeF6ZrNZt9xyi+666y5J0pYtWwIqwOrp6dGePXskSSaTSV/60pc8rmuxWFRSUqJHH31UTqdTr732mm677TavYzz22GOqr69XUlKSfvSjH6mry7h4aSxpaTP+N6QkUYAFAJEuoguwRjoG05MHH3xQNptNWVlZ+sIXvqDf/e53IR8DACJdIO2d5uWl6QtXTJMkTZ+a5PEiuC8uSE/Qe4eaFBdjUUKsRdv/ekJVg/bFDWQAmNiK8jO1blVsUMebsc4l6YOPWj2+P1yrw+r6Zl0z/0JNSYmnsBkAMGblZiVpzYp5arJ3qva4XR1dDsXHWJSfY9WZjm6v3xPOO3q092DjiM3XnwedbrxqehhnAoSWxVMCFgVYADBqduzY4X599dVXD7tu//f7b+cPu92uc+d6C9tTU1NltVqHXT83N9f9etu2bV4LsKqqqtz3bP/1X/9VGRkZamhoCGiukcRjC8LJtCAEgEgXsQVYoxGDaWT37t16+eWXJUk//vGPtX///pDtGwDGGn/aO1nMJpUUf3LCNPgi+PFTZ7W1okE9Pb5dav6oqV0vvnl42HX6biDXHG3R6pICFeVn+rRvAMD44emm63mHM+g0xvHO2SNt2/eR+2cKmwEAY1m6NW5IIXF6ctyA7wkfNLRq+19PjNIMpRnZyfqgwXPh9GA7/npCR060USiNMcEc5SEBixaEADBqDh065H5dWFg47LoZGRnKysqSzWZTU1OTWlpalJqa6td4Llfg12D6z9VId3e37rrrLjmdTi1cuFArVqwIeKxIY9SCMMpkUnLCpFGYDQDAHxFbgDXSMZhGOjs79aMf/Ugul0vXX3+9PvOZz1CABWBC87W9k8Vs0uqSAsObtf0vgs/MTg5LqyiH06WnSvfrhiunKyE2movTADABGd10DTaNcaLpX9j81WtnKtpiHtL2l3bAgXvzzTdVWlqq/fv3q7GxUYmJiZo2bZqWLFmilStXKjExMaTj1dXV6cUXX9SePXtks9l07tw5paena/bs2brhhht0/fXXK8rDjVIAGG/6vidkpcWPWgGWySTZDW6uDWdnpe2T7UWhNCKbpwSs892OEZ4JAKBPfX29+3V2drbX9bOzs2Wz9X7/OHLkiN8FWMnJyYqOjlZ3d7daWlrU2tqq5ORkj+sfPXrU/bq9vV0nT57UlClTDNd98skndejQIcXExOjee++VyWR83BmLPm7uGLLMOnmSoqLGz78RAMariC3AGukYTCO//OUvdfz4cVmtVv3gBz8I2X4BYCwbrr2TSdLcvDSV+HgBOJytopw9UtmuowPmxsVpAJjYPKVjxcdatOP9E4bHtRkXJksm6YOG1glbtOVwuvTc60OfPJ0cHz2kpSHHW+/a29u1du1abdu2bcDylpYWtbS06L333tOGDRv0yCOPaP78+UGP53Q6tX79ev36178e8vTxiRMndOLECW3btk3PP/+8HnnkEY8XtwFgPOp/zjjSXC6pqXVoe5loS5S+eNV0vVnRoNb28563FwnQiGz2s8YFhq/vbdDHLZ18XwSAUXDmzBn365SUFK/r928Z2H9bX1ksFs2fP1979+6Vy+VSaWmpvv71rxuu63Q6VVZWNmBZW1ub4TnqwYMH9Z//+Z+SpH/+53/W9OnT/Z7bSEtK8t4+8PBxu/7rjVrVHrcPea+ru0fN7d2aeZE19JNDROoruIuKMik1NWGUZ4ORxu9/7IrYAqyRjsEcbN++fXr++eclSf/2b/9m2P4QACYqTzew83OsSk/2L/XCaF9vv/eRbAZPeQSDi9MAgD5G6ViXzcwY9rjW/71TLR16+/0TcvrYRne8Glx8JXG89cbpdGrNmjXauXOnJCk9PV0rVqzQjBkz1Nraqs2bN2vfvn2y2Wy67bbb9OKLLyovLy+oMe+55x699NJLknoTpK+77jotWrRICQkJamho0KZNm3To0CHt27dPt956q1544QUlJXEzFMD412TvVFVd82hPY4h5M9J041XTZTJJf9h+xOv6DqdLT5dVa92qWIpZEDEqak/pf/Yc9/g+3xcBYHR0dHxyzT0mJsbr+v3XaW9vD2jMm266SXv37pUkrV+/XoWFhbrssssGrNPT06N7771XR44M/O5z9uzZIftzOBy666671N3drdmzZ+vWW28NaF4jzWwePnH6z5Un9O8bKuRw9hi+397ZrXVP7NK/rirSVXMvCMcUEaFMJpPMHpJFMf7x+x97IrYAa6RjMPvr6urSXXfdpZ6eHl155ZX6X//rfwW8LwAYz4xuYAe7ryZ7p17aejgk+zTCxWkAgCfDHdcGv3dVYRbtDIfB8dbYK6+84i6+mjFjhp599tkBD/vcfPPNeuCBB/Tb3/5Wra2tuvvuu90PBgVi165d7uKr+Ph4PfPMM7r88ssHrHPrrbfqJz/5iV5++WUdPnxYDz/8sH7yk58EPCYAjBUHj9kDOoZfmpuqmg9Pq8eHQmxzlHTDldP14ckz+usHvhV7vX+4SfW2Nh1uaPV5Tg6nS2Xl9VqzYp7P2wDhUm9r09Nl1V7/G+H7IgBMDDfeeKNKS0tVXl6ujo4OrVq1yvDBoNraWqWmpqqrq8td7BUVNbRo6de//rWqq6tlNpt13333yWKJ2FvdAzg9FFZJvclXwxVf9XE4e/TvGyp0/+2xJGFNAFFRJplMJrlcLp/OPTC+8Pv3jbfi1tEQsUelkY7B7O/RRx9VfX29YmNjdc899wS1LwCAfwK9CO4PLk4DAILlbzvDiYjj7UBOp1OPP/64++cHH3zQMGl57dq12r17tw4cOKB3331X5eXlKi4uDmjM3//+9+7Xa9asGVJ8JfWmYv34xz/W3r17VV9fr5dffln/9E//5NODUAAwlnV2OQLarjAvTdfMv0BPl1XL4fR8tLeYTe50n0de+avP+3c4XXr1rQ908Jjdr3lV1jWrqbXT71RqINRKy+uH/W+jP74vAsDIio+PV2trb5F3V1eX1+Klrq5P2skmJATWAisqKkqPPvqovv/97+uNN96Qw+HQpk2btGnTpgHrZWRk6IknnhiQaDU4nbmurk6/+tWvJEm33HKL1w5KkaSt7ZwcDqfhe8+9VuO1+KqPw9mjDa/VcOycAFJTE2Q2m9TT41JLS2AJdBi7+P17Z7GYlZISP9rTGCJiC7BGIwZTkiorK90Xqe+44w7l5OQEvK+R4kvf4MHoGzqx8ftHJH8GTJaRqVauPNIsh8mkzAg8OAMAxo7h2hk2tHSq87xDcZMsOt3aoRe3Hvb5ZtR4wc3gT+zdu1eNjY2SpIULF6qgoMBwPbPZrFtuuUV33XWXJGnLli0BFWD19PRoz549knrjyr/0pS95XNdisaikpESPPvqonE6nXnvtNd12221+jwkAY0lcTGCXReNjLCrKz9S6VbGGaZgmSXPz0lRSnKvcrKSAWh0e8LP4SuptA1x7zK70Qo65GD2BfN75vggAI2fy5MnuAqzTp097Laqy2+0Dtg1UYmKiHn/8cf35z3/Wxo0b9d5776mpqUlRUVHKzs7W0qVL9fWvf10JCQnue7wmk2nAQ0s9PT266667dP78eV144YVas2ZNwPOJJBw7AWB8idgCrNFw/vx5/eAHP5DT6VRBQYH+4R/+YbSn5JNgotXoGzqx8ftHJH4GEuMmjcg4LpdUU9+irPTEERkPADCxpFvjNOvidJnNUXI6e9TS0q7pU5M8ti1Mio9WW0f3qMw1nLgZ/IkdO3a4X1999dXDrtv//f7b+cNut+vcuXOSpNTU1AGp0UZyc3Pdr7dt20YBFoBxb3aOVSbJr8RKk6T8HKskz2mY+TnWATfDRiLluU9HgKleQKgE8nnn+yIAjJzc3Fw1NDRIkhoaGrwmH/etK0kXX3xx0ONfddVVuuqqqzy+X1tbK6ezNyVq+vTpA4q+Dh06pPfff1+SNHPmzAGJz/3175J05swZPfHEE+6f/+mf/kmTJo3M/QdfcewEgPElYguwRiMG88knn9ShQ4dkNpt17733ymw2B7SfkTZc32BP6Bs6sfH7RyR/Bubkpspk6i2QCrezHec9/g2NxL7BAICxzduN2sHLzzuc4yI1i5vBvQ4dOuR+7a1NQkZGhrKysmSz2dTU1KSWlhalpqb6NZ4riC9T/ecKAONVujVOhXlpqvQjcWBuXtqQpAGjNMz+Am11GIj4AFO9gFAJ9PPO90UAGBmzZs3Szp07JUlVVVVatGiRx3Wbmppks9kkSWlpaX6fkwaiL8VZkj71qU8NeK//Oe7bb7+tt99+2+v+2tra9Oijj7p/XrVqVcQVYHHsBIDxJWLPykc6BvPgwYN65plnJEnf+MY3PLaDiETD9Q32hL6hExu/f0TyZyBaUuHF/l0ED5Trb4kkg0Vq32AAwPjg6Uat0fLhUrPGCm4G96qvr3e/9vaUcd86fRe7jxw54vfF7uTkZEVHR6u7u1stLS1qbW1VcnKyx/WPHj3qft3e3q6TJ09qypQpfo0JAGPNsuJc1Rxt8anY2WI2qaQ41+t6gwXa6tBf/dO5gNESTGtPAED4LV68WL/5zW8k9aYtf/Ob3/S47vbt292vr7nmmrDPzeVyaePGje6fV6xYEfYxIwHHTgAYXyL2r/NIx2Bu3LhR3d3dioqKUnR09IBIyv727t074HXferm5ubruuuv8HhcAMJQ/F8EDxcVpAMBY4Ck1Kz7Woh3vnxhSmGWSNOPCZMkkfdDQOuqtDjnefqJ/G4SUlBSv6/dvGdh/W19ZLBbNnz9fe/fulcvlUmlpqb7+9a8brut0OlVWVjZgWVtb26gVYCUlxfq9TVSUyf2/qamBpWJjbOMzMLEF+vtPTU3Q975WpF++sE+OYRLmLeYofe9rC1RUkOX33K6Ye4F+96cDfqU8m0zSpRenqcqPB5OKLpmiWbnpfs8PCKVgW3sCAMJr4cKFysjIUGNjo/bs2aPq6mrDQAqn06nnnnvO/fP1118f9rm99NJLqqmpcc9z7ty5A96/5JJLVFtb63U/DQ0NuvbaayVJF154obZt2xb6yYYQx04AGF8itgBrpGMw+6Ire3p69NRTT/m0zTvvvKN33nlHknTttddSgAUAIZKblaTVJQV6uqw6bEVYRq0jAACIVEbpWJfNzPDYzlCST60OT7V06O33T8gZppbEHG8/0dHR4X4dExPjdf3+67S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            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "image/png": {
              "width": 1000
            }
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image\n",
        "\n",
        "Image(filename=f\"{HOME}/yolov9/runs/train/exp/confusion_matrix.png\", width=1000)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 767
        },
        "id": "qggEg7Hv1zJ6",
        "outputId": "98937fd2-85a7-4baf-90dc-ad927fe7980d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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jj5T42muvjQsuuKDU6sw7/8qVK2PNmjXF3kmtNOX9EsDixYuLNTZ/fklvsQ4AAMDOlZOTk3aD+5IlS1LivGu9jRs3xr333puMW7RoEe+++25kZ2cXOefW3cCLUr169cjKyoqNGzdGRMTChQvTqrckrr766qhSpUoMGDAgIiLmzp0bHTt2jNdffz1atGiR1hy1a9dOHs+bN69Y1y9ufnHlX58vXrw4WrVqldbYdevWpTTgF7bWz8jIKFFtxW223xnyP6ecnJy0x+b/+wAAAAB+nsrt6gIAAIAfh0MOOSRat26djPM2tE+fPj2mTJmSjAvbvT0iol69elGjRo1kPH/+/FKtM+8Hylu2bIkPPvigVOcvrmbNmiWPFyxYEEuXLk177NSpUwudCwAAgLLjs88+K1FutWrVYu+9907G77//fkqz+nXXXbfd5vaI73dJT8eBBx6YPM67jt8ZLr744njggQeSjdrffPNNdOrUKT799NO0xh988MHJ42XLlsXs2bPTGrdu3br43//+V+x6iyP/+jz/+r0on376aWzZsqXQubbK+2X9dJvWN2zYEMuXL0+7lp2lefPmKXFx/j7S/fcBAAAA/LRpcAcAANKWt3F98uTJ8cUXX0REarN7+fLlo2/fvoXOUb58+ejUqVMyznvb9dLQsWPHlPj5558vlXmzsrJS4rwfRhelffv2KfErr7yS1rhEIpGS27hx46hTp05aYwEAAPhhjRo1Kq289evXx5tvvpmMDz300ChX7v9/XLdgwYKU/IMOOiiteV9//fW08vKumWfPnh0ff/xxWuNK6pxzzolHH300+RxzcnLiqKOOig8//HC7Yzt06JASp7u+HzlyZGzYsKH4xRZDmzZtomLFisk43bV+xPf15ZX/fYOt8n6xId3NAd5///3YtGlT2rXsLAcffHBUqFAhGaf791HcXAAAAOCnS4M7AACQtr59+0ZmZmYyfuKJJ2LLli3x73//O3numGOOiT333LPIefr06ZM8fv/992PixImlVmPr1q2jZcuWyfixxx4rlduuV6tWLSVesWJFWuOOPfbYlA9177///kgkEtsd99JLL8XcuXOTcc+ePdOsFAAAgB/as88+m7LzemGGDh2asp484YQTisxft27ddudcunRpyrq8KL17906Jb7rpprTG7Yj+/fvHU089lXw/YdmyZdGlS5eYNGlSkeOOPfbYqFWrVjK+66674rvvvityzJYtW36Q51ShQoU49thjk/GECRNi2rRp2x333XffxaOPPpqM69atG+3atSswt0WLFsnj7b1WW+Wde1eqWLFiHHPMMcn49ddfT+suA+PHj48vv/xyZ5YGAAAA/EhocAcAANJWp06dlA9wn3zyyRg7dmzKTmJ5d3kvzMknn5xyu+p+/frF4sWLi11PQR/0Z2RkxOWXX56MV65cGWeccUasX7++2PPntc8++6TE6d4yu27dunHSSScl4ylTpsTgwYOLHPPtt9/GgAEDknFGRkacf/756RcLAADAD2rZsmXx5z//ucicJUuWxDXXXJOMK1euHGeeeWZKTqNGjVLi/Lt957dly5b43e9+F6tXr06rznbt2qXs4v7cc8/FP//5z7TG7ojevXvH8OHDk18AX7FiRXTt2jUmTJhQ6JgKFSrEOeeck4wXLFgQZ511VpF3VLv88stj6tSppVZ3UfKu0xOJRJx99tnb3Tn+yiuvjG+++SYZn3322Slfis8r787uc+bMidGjRxc599tvv51yh71d7eyzz04eb9q0KS644IIif3dr1qyJP/3pTz9EaQAAAMCPgAZ3AACgWPr37588njdvXlx44YXJuGbNmmntNF6uXLl45JFHkh/izpo1Kw477LB45ZVXtru7+aJFi+LBBx+M1q1bF3rb6jPPPDO6dOmSjMeNGxe/+tWvYvr06YXOu2HDhhg2bNg2zQVbtWzZMmrUqJGMb7755pgxY0aRtW41aNCglB3gL7744kJ3cp81a1Z07do15syZkzx30UUXRZMmTdK6FgAAAD+8cuXKxZAhQ+LKK6+MTZs2bfP4nDlz4rjjjosFCxYkzw0cODBq1qyZknfooYem7Fr+j3/8o9C1b05OTvTq1StGjBgR5cql/5Hf/fffH1WqVEnGf/zjH+O6666LNWvWFDrmm2++iYEDB+7QDuEnnHBCvPDCC1GpUqWIiFi9enUcd9xxMWbMmELHXH311Snr4eHDh0fHjh1jwoQJKc3SH3zwQfTs2TPuuOOOKFeuXMqX6neWo48+Orp3756M33333TjxxBNj6dKl2+Ru3Lgx/vznP8d9992XPNewYcO45JJLCp2/V69eydcqIuIPf/hDzJw5s8DcESNGRI8ePWLz5s2RkZFRkqdT6rp37x6dO3dOxq+99lqcddZZBe7Cv2TJkujZs2d89tlnxfq3DAAAAPx0Ze7qAgAAgB+X448/PnbfffdYtmxZRERKk3fv3r2jYsWKac3ToUOHePjhh+O3v/1tbN68OebPnx89evSIpk2bRpcuXaJFixZRo0aNWL9+feTm5sYXX3wRU6dOjalTp263Cb5cuXLx1FNPxeGHH5788HfixInRqlWr6NixY3Ts2DH22muvSCQSsXjx4pg6dWqMGzcucnNz46CDDipwzszMzOjfv3/cfffdERHx+eefx/777x/169eP3XffPeUD2FdffTXq1auXjPfdd9948MEH44wzzogtW7bE5s2b4/zzz48HHnggfvOb30SjRo1i9erVMXny5HjxxRdj7dq1ybGHHnpo/OMf/0jrNQUAAGDXuP766+P666+Pm2++OYYPHx6nnHJKNGnSJNauXRvvv/9+PP/88ykN5O3bt0+5+9hW5cuXj6uuuiouvfTSiIhYu3ZtdOvWLbp27RpdunSJ2rVrR25ubnzwwQcxYsSIWLVqVURE/O1vf4urrroqrVpbtmwZjz76aPTt2zc2bdoUiUQibrzxxnjggQeie/fu0bp169h9993ju+++i9mzZ8fkyZPj3XffjS1btsSdd965Q69Tt27d4uWXX46ePXvGd999F2vXro1f//rX8dxzz0WPHj22ya9cuXK88MIL0blz52Tj+MSJE6NTp05RuXLlqFWrVixfvjxlB/sbbrghvvrqq+SX3MuXL79DNRflkUceibZt28bcuXMjIuKVV16J/fbbL04++eRo3bp1VKhQIWbOnBnDhw9P+SJ7pUqV4t///nfKF+nzy87OjssuuywGDRoUEd9vMtC6devo06dPHHbYYZGVlRXz58+PV199Nd5///2I+P7LCqNHj46vv/56pz3n4hgyZEi0a9cuvv3224iIeOKJJ2Ls2LFx6qmnRvPmzWPz5s3xySefxLPPPhu5ublRvnz5GDhwYPzlL3/ZxZUDAAAAu5oGdwAAoFgqVKgQffr0icGDB2/zWL9+/Yo115lnnhn169ePPn36xJIlSyIiYubMmYXuSJZfUR9S161bNyZNmhS9evWKt956KyK+vyX2uHHjYty4ccWqc6tBgwbFlClTYtKkSclzCxYsSNmBLyIKvCX5aaedFuXKlYv+/fvH+vXrIyJi2rRpMW3atEKv17lz55Td7QAAACibBg4cGF988UU8/fTTMWvWrCK/qPyLX/wiXn311cjKyirw8YsvvjgmT54czz77bEREJBKJGD16dIwePXqb3PLly8dNN90Up5xyStoN7hERp556atSsWTN69+4dy5cvj4iIpUuXxuOPP572HCXVpUuXGDVqVHTr1i1WrVoV69evjxNPPDGeeeaZ6NWr1zb5rVq1ivHjx0ffvn3jk08+SZ5fu3ZtzJs3LxlnZWXFzTffHAMGDIg+ffokz1evXn2nPZe6devGO++8E8cdd1xyfZ+bmxsPP/xwoWNq1qwZL730UhxxxBHbnX/gwIExefLkGDt2bER8/5wfffTRAnfSP+mkk2Lw4MHRtGnTEj6b0tekSZMYO3ZsHH300ckm94ULF8Zdd921TW758uXjnnvuiZYtW2pwBwAAAMI93gAAgGLr37//NueaN28e7dq1K/ZcXbp0iVmzZsXf//732Hfffbeb36xZs7jooovivffei+OPP77I3Fq1asWbb74Zw4YNi0MPPbTI23RXrlw5jj/++CKbEKpWrRpvvfVWPP3009GrV69o2rRpVKtWLe3bZ/fu3Tu++OKL6Nu3b1SuXLnQvBYtWsQTTzwRr7/++k79IB4AAIDSsfVOYg8++GA0atSowJzs7Oy44YYbYuLEiZGdnV3kXEOHDo0777wz6tSpU2BORkZGHHHEEfHWW2/FFVdcUaKau3btGl999VVceeWVhV5nq7333jsGDBgQJ554Yomuld/hhx8er7/+etSsWTMiIjZu3BinnnpqPPXUUwXmH3jggfHBBx/Ek08+GT169IgGDRpExYoVo3bt2tGmTZu4+uqr43//+18MGDAgIiJ517mIKPK1Lg177713fPjhh3HHHXdEgwYNCs2rUaNGXHTRRTFjxoy0mtsjIipWrBgjR46MgQMHRpUqVQrMadiwYTz44IMxfPjwyMwse3ubHXLIIfHf//43TjvttEK/1NG2bdsYP358nHfeeT9wdQAAAEBZlZFIJBK7uggAAICtZs2aFR988EEsWbIkcnNzo2LFipGdnR2NGzeOAw88cLsfuhdl0aJF8c4778TixYtj+fLlyQ/DmzVrFoccckhUrFixFJ9J0dauXRsTJ06MOXPmxNKlS6Ny5cpRt27daNu2bTRp0uQHqwMAAIDSlUgkYtKkSfHll1/GokWLolq1atGkSZPo3LlzVKhQoVhzbdiwId5777347LPPIjc3N7Kzs2OvvfaKdu3aRf369Uu15o8//jj++9//xpIlS2Lt2rVRtWrVaNCgQbRq1Sr222+/UrvWD2GvvfaKRYsWRUTE73//+yJ3VC9tn332WUydOjVycnJi48aNUbt27dhvv/2iQ4cOO9SAvmbNmpgwYULMnDkzVq9eHXXr1o1mzZpFhw4divx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            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "image/png": {
              "width": 1000
            }
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image\n",
        "\n",
        "Image(filename=f\"{HOME}/yolov9/runs/train/exp/val_batch0_pred.jpg\", width=1000)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Xja2fjTl32Ml",
        "outputId": "e5c7b733-2e3f-419c-bca7-cc647dad0610"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/jpeg": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "image/jpeg": {
              "width": 1000
            }
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Validate Custom Model"
      ],
      "metadata": {
        "id": "ih1rk9O_4CYG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%cd {HOME}/yolov9\n",
        "\n",
        "!python val.py \\\n",
        "--img 224 --batch 32 --conf 0.001 --iou 0.7 --device 0 \\\n",
        "--data {dataset.location}/data.yaml \\\n",
        "--weights {HOME}/yolov9/runs/train/exp/weights/best.pt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XoZv8kNE4NxS",
        "outputId": "911a73ba-c204-414c-ace1-bec6b679afec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/yolov9\n",
            "\u001b[34m\u001b[1mval: \u001b[0mdata=/content/yolov9/vectorCompleteDataset-8/data.yaml, weights=['/content/yolov9/runs/train/exp/weights/best.pt'], batch_size=32, imgsz=224, conf_thres=0.001, iou_thres=0.7, max_det=300, task=val, device=0, workers=8, single_cls=False, augment=False, verbose=False, save_txt=False, save_hybrid=False, save_conf=False, save_json=False, project=runs/val, name=exp, exist_ok=False, half=False, dnn=False, min_items=0\n",
            "YOLOv5 🚀 1e33dbb Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "Fusing layers... \n",
            "gelan-c summary: 467 layers, 25411731 parameters, 0 gradients, 102.5 GFLOPs\n",
            "\u001b[34m\u001b[1mval: \u001b[0mScanning /content/yolov9/vectorCompleteDataset-8/valid/labels.cache... 61 images, 6 backgrounds, 0 corrupt: 100% 61/61 [00:00<?, ?it/s]\n",
            "                 Class     Images  Instances          P          R      mAP50   mAP50-95: 100% 2/2 [00:01<00:00,  1.12it/s]\n",
            "                   all         61         55      0.999      0.982      0.989      0.951\n",
            "Speed: 0.0ms pre-process, 13.4ms inference, 8.5ms NMS per image at shape (32, 3, 224, 224)\n",
            "Results saved to \u001b[1mruns/val/exp\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Inference with Custom Model"
      ],
      "metadata": {
        "id": "qJJ5fiqT6mEq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python detect.py \\\n",
        "--img 224 --conf 0.1 --device 0 \\\n",
        "--weights {HOME}/yolov9/runs/train/exp/weights/best.pt \\\n",
        "--source {dataset.location}/test/images"
      ],
      "metadata": {
        "id": "8vnrn9cwIsUs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d0ace973-5505-41a8-d8c3-f495a819e86a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mdetect: \u001b[0mweights=['/content/yolov9/runs/train/exp/weights/best.pt'], source=/content/yolov9/vectorCompleteDataset-8/test/images, data=data/coco128.yaml, imgsz=[224, 224], conf_thres=0.1, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n",
            "YOLOv5 🚀 1e33dbb Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "Fusing layers... \n",
            "gelan-c summary: 467 layers, 25411731 parameters, 0 gradients, 102.5 GFLOPs\n",
            "image 1/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture134_jpeg.rf.a71791fbe20fd0e8fc55edf8bb67a5f6.jpg: 224x224 1 vector, 16.2ms\n",
            "image 2/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture137_jpeg.rf.e7bb276e008c23cf3c0784ede58fa99c.jpg: 224x224 1 vector, 16.6ms\n",
            "image 3/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture140_jpeg.rf.8f41cd3756805678f95963655f5a0361.jpg: 224x224 1 vector, 16.8ms\n",
            "image 4/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture141_jpeg.rf.ea737ed1ffa058d631f8bf0428cf892f.jpg: 224x224 1 vector, 16.2ms\n",
            "image 5/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture14_jpeg.rf.b6b9a2227c6ecf2a3889cae8fd4afa8a.jpg: 224x224 1 vector, 16.6ms\n",
            "image 6/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture16_jpeg.rf.8b31ea1c66d6615bebe6c8d216fbc8f2.jpg: 224x224 1 vector, 16.4ms\n",
            "image 7/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture177_jpeg.rf.e7eb678db9099d7d27abb0cbb3609dad.jpg: 224x224 1 vector, 16.4ms\n",
            "image 8/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture181_jpeg.rf.7ca019a8dcc30ef337179f41a5d901e8.jpg: 224x224 1 vector, 17.4ms\n",
            "image 9/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture184_jpeg.rf.0e602df69955ae14f74a17d33d973900.jpg: 224x224 1 vector, 16.3ms\n",
            "image 10/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture186_jpeg.rf.c33a0bdbbb1c575d5a76302513337def.jpg: 224x224 1 vector, 16.2ms\n",
            "image 11/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture195_jpeg.rf.3e4618cbb8348e7763560c00a778de02.jpg: 224x224 1 vector, 16.2ms\n",
            "image 12/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture200_jpeg.rf.7b555dd5090411cab988385989923962.jpg: 224x224 1 vector, 16.2ms\n",
            "image 13/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture201_jpeg.rf.462ef1b9a105525d7857d4d7ed5e7421.jpg: 224x224 (no detections), 16.2ms\n",
            "image 14/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture205_jpeg.rf.9e0abcdd2a19801a74752aa473f94ecf.jpg: 224x224 (no detections), 18.0ms\n",
            "image 15/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture209_jpeg.rf.285d8890cad5bde78a73451a193db614.jpg: 224x224 (no detections), 13.9ms\n",
            "image 16/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture237_jpeg.rf.9ffe09bc7afcaac5e7466980b6d0ef74.jpg: 224x224 1 vector, 14.3ms\n",
            "image 17/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture241_jpeg.rf.e6769bda05e8543138cbbcb95691b957.jpg: 224x224 1 vector, 15.1ms\n",
            "image 18/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture254_jpeg.rf.43211785c7b302a2a5a750976b1ba7a5.jpg: 224x224 1 vector, 14.8ms\n",
            "image 19/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture258_jpeg.rf.daa4d0d49ac83ab50d9d840c82a7590d.jpg: 224x224 1 vector, 14.8ms\n",
            "image 20/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture263_jpeg.rf.ca4977a6cbcf4c584ef596312b01f8fb.jpg: 224x224 1 vector, 14.2ms\n",
            "image 21/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture291_jpeg.rf.e09610d012575228e7b7201d4d5b159c.jpg: 224x224 1 vector, 14.1ms\n",
            "image 22/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture297_jpeg.rf.3f03d9ea323b6509d855de06f9a5b584.jpg: 224x224 1 vector, 16.9ms\n",
            "image 23/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture303_jpeg.rf.cbefb8941ab655ee4143796784356794.jpg: 224x224 1 vector, 15.4ms\n",
            "image 24/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture33_jpeg.rf.b62069f683fda5ea9ac9e297ee82cfba.jpg: 224x224 1 vector, 15.4ms\n",
            "image 25/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture35_jpeg.rf.9faf7d4c5cc4e1cfba2669a1ca0991ed.jpg: 224x224 1 vector, 16.4ms\n",
            "image 26/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture3_jpeg.rf.26b639ea06260027379c83c79090b343.jpg: 224x224 1 vector, 14.1ms\n",
            "image 27/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture40_jpeg.rf.68f25f130a8c4be8fb500a1ce6bb25b5.jpg: 224x224 1 vector, 13.9ms\n",
            "image 28/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture55_jpeg.rf.4fe6dfe00530c86f9482057f88df2141.jpg: 224x224 1 vector, 13.7ms\n",
            "image 29/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture6_jpeg.rf.2b03f94f7d62984c32effa39438fe5ce.jpg: 128x224 (no detections), 96.6ms\n",
            "image 30/30 /content/yolov9/vectorCompleteDataset-8/test/images/picture93_jpeg.rf.8d814d603a1fde5129002a9e6faa5db4.jpg: 224x224 1 vector, 15.9ms\n",
            "Speed: 0.2ms pre-process, 18.4ms inference, 21.2ms NMS per image at shape (1, 3, 224, 224)\n",
            "Results saved to \u001b[1mruns/detect/exp\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**NOTE:** Just like behore, the inference results have been saved in the appropriate directory inside `{HOME}/yolov9/runs/detect/`. Let's examine few of those results."
      ],
      "metadata": {
        "id": "WPbhTtVXtM4Q"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "4oZDaN2QCgsh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KrEOBvANgawe",
        "outputId": "b6ac7eec-be5a-4e14-e8b5-4d81d9135018"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python detect.py \\\n",
        "--img 224 --conf 0.1 --device 0 \\\n",
        "--weights {HOME}/yolov9/runs/train/exp/weights/best.pt \\\n",
        "--source /content/gdrive/'My Drive'/TrainingVector/vectorNewBackground.mp4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e9a28f48-b1c8-4b6a-cd38-90b9e52c8709",
        "id": "DXv1ui8aCP8b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[34m\u001b[1mdetect: \u001b[0mweights=['/content/yolov9/runs/train/exp/weights/best.pt'], source=/content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4, data=data/coco128.yaml, imgsz=[224, 224], conf_thres=0.1, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n",
            "YOLOv5 🚀 1e33dbb Python-3.10.12 torch-2.1.0+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
            "\n",
            "Fusing layers... \n",
            "gelan-c summary: 467 layers, 25411731 parameters, 0 gradients, 102.5 GFLOPs\n",
            "video 1/1 (1/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 95.2ms\n",
            "video 1/1 (2/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.8ms\n",
            "video 1/1 (3/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.6ms\n",
            "video 1/1 (4/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.0ms\n",
            "video 1/1 (5/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (6/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.2ms\n",
            "video 1/1 (7/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 23.6ms\n",
            "video 1/1 (8/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.2ms\n",
            "video 1/1 (9/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (10/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (11/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.5ms\n",
            "video 1/1 (12/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.4ms\n",
            "video 1/1 (13/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.4ms\n",
            "video 1/1 (14/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (15/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.4ms\n",
            "video 1/1 (16/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (17/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (18/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.3ms\n",
            "video 1/1 (19/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.7ms\n",
            "video 1/1 (20/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.4ms\n",
            "video 1/1 (21/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (22/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.1ms\n",
            "video 1/1 (23/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (24/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (25/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.3ms\n",
            "video 1/1 (26/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.0ms\n",
            "video 1/1 (27/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.2ms\n",
            "video 1/1 (28/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (29/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.9ms\n",
            "video 1/1 (30/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.3ms\n",
            "video 1/1 (31/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.6ms\n",
            "video 1/1 (32/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.7ms\n",
            "video 1/1 (33/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.8ms\n",
            "video 1/1 (34/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.1ms\n",
            "video 1/1 (35/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.8ms\n",
            "video 1/1 (36/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.9ms\n",
            "video 1/1 (37/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.2ms\n",
            "video 1/1 (38/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.4ms\n",
            "video 1/1 (39/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.4ms\n",
            "video 1/1 (40/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (41/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.7ms\n",
            "video 1/1 (42/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.2ms\n",
            "video 1/1 (43/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.0ms\n",
            "video 1/1 (44/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 24.1ms\n",
            "video 1/1 (45/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.6ms\n",
            "video 1/1 (46/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.6ms\n",
            "video 1/1 (47/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.7ms\n",
            "video 1/1 (48/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (49/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (50/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.3ms\n",
            "video 1/1 (51/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.9ms\n",
            "video 1/1 (52/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.7ms\n",
            "video 1/1 (53/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.2ms\n",
            "video 1/1 (54/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.3ms\n",
            "video 1/1 (55/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.6ms\n",
            "video 1/1 (56/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.4ms\n",
            "video 1/1 (57/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.9ms\n",
            "video 1/1 (58/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.4ms\n",
            "video 1/1 (59/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (60/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (61/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.2ms\n",
            "video 1/1 (62/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.4ms\n",
            "video 1/1 (63/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 23.0ms\n",
            "video 1/1 (64/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.7ms\n",
            "video 1/1 (65/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.7ms\n",
            "video 1/1 (66/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.1ms\n",
            "video 1/1 (67/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.6ms\n",
            "video 1/1 (68/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (69/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.9ms\n",
            "video 1/1 (70/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.6ms\n",
            "video 1/1 (71/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 25.3ms\n",
            "video 1/1 (72/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.8ms\n",
            "video 1/1 (73/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.4ms\n",
            "video 1/1 (74/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.2ms\n",
            "video 1/1 (75/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.2ms\n",
            "video 1/1 (76/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (77/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (78/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.3ms\n",
            "video 1/1 (79/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 31.7ms\n",
            "video 1/1 (80/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.1ms\n",
            "video 1/1 (81/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.3ms\n",
            "video 1/1 (82/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.1ms\n",
            "video 1/1 (83/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.7ms\n",
            "video 1/1 (84/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.9ms\n",
            "video 1/1 (85/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.3ms\n",
            "video 1/1 (86/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.4ms\n",
            "video 1/1 (87/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.2ms\n",
            "video 1/1 (88/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (89/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.6ms\n",
            "video 1/1 (90/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.2ms\n",
            "video 1/1 (91/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 30.6ms\n",
            "video 1/1 (92/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 31.7ms\n",
            "video 1/1 (93/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 27.3ms\n",
            "video 1/1 (94/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 24.9ms\n",
            "video 1/1 (95/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.0ms\n",
            "video 1/1 (96/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 39.1ms\n",
            "video 1/1 (97/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.9ms\n",
            "video 1/1 (98/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.3ms\n",
            "video 1/1 (99/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.3ms\n",
            "video 1/1 (100/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.9ms\n",
            "video 1/1 (101/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.6ms\n",
            "video 1/1 (102/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 23.8ms\n",
            "video 1/1 (103/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 35.0ms\n",
            "video 1/1 (104/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.7ms\n",
            "video 1/1 (105/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.7ms\n",
            "video 1/1 (106/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 26.8ms\n",
            "video 1/1 (107/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 19.9ms\n",
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            "video 1/1 (820/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 22.0ms\n",
            "video 1/1 (821/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.1ms\n",
            "video 1/1 (822/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.0ms\n",
            "video 1/1 (823/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.3ms\n",
            "video 1/1 (824/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.4ms\n",
            "video 1/1 (825/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 20.7ms\n",
            "video 1/1 (826/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.4ms\n",
            "video 1/1 (827/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.2ms\n",
            "video 1/1 (828/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (829/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.7ms\n",
            "video 1/1 (830/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (831/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.7ms\n",
            "video 1/1 (832/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.8ms\n",
            "video 1/1 (833/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 21.7ms\n",
            "video 1/1 (834/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.3ms\n",
            "video 1/1 (835/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.2ms\n",
            "video 1/1 (836/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.5ms\n",
            "video 1/1 (837/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 18.2ms\n",
            "video 1/1 (838/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 23.1ms\n",
            "video 1/1 (839/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.6ms\n",
            "video 1/1 (840/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 16.8ms\n",
            "video 1/1 (841/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 1 vector, 17.3ms\n",
            "video 1/1 (842/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.9ms\n",
            "video 1/1 (843/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.7ms\n",
            "video 1/1 (844/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.1ms\n",
            "video 1/1 (845/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (846/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 25.3ms\n",
            "video 1/1 (847/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 20.8ms\n",
            "video 1/1 (848/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.7ms\n",
            "video 1/1 (849/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.2ms\n",
            "video 1/1 (850/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 31.0ms\n",
            "video 1/1 (851/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.0ms\n",
            "video 1/1 (852/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (853/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.7ms\n",
            "video 1/1 (854/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.1ms\n",
            "video 1/1 (855/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 26.7ms\n",
            "video 1/1 (856/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.9ms\n",
            "video 1/1 (857/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.8ms\n",
            "video 1/1 (858/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 25.6ms\n",
            "video 1/1 (859/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.0ms\n",
            "video 1/1 (860/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (861/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.0ms\n",
            "video 1/1 (862/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.1ms\n",
            "video 1/1 (863/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.9ms\n",
            "video 1/1 (864/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.3ms\n",
            "video 1/1 (865/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (866/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.5ms\n",
            "video 1/1 (867/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.6ms\n",
            "video 1/1 (868/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (869/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.1ms\n",
            "video 1/1 (870/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.6ms\n",
            "video 1/1 (871/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.1ms\n",
            "video 1/1 (872/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.3ms\n",
            "video 1/1 (873/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.9ms\n",
            "video 1/1 (874/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.9ms\n",
            "video 1/1 (875/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.0ms\n",
            "video 1/1 (876/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.2ms\n",
            "video 1/1 (877/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.5ms\n",
            "video 1/1 (878/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 22.0ms\n",
            "video 1/1 (879/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.3ms\n",
            "video 1/1 (880/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.9ms\n",
            "video 1/1 (881/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.3ms\n",
            "video 1/1 (882/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.3ms\n",
            "video 1/1 (883/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.3ms\n",
            "video 1/1 (884/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 25.7ms\n",
            "video 1/1 (885/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.4ms\n",
            "video 1/1 (886/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (887/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.4ms\n",
            "video 1/1 (888/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.0ms\n",
            "video 1/1 (889/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.0ms\n",
            "video 1/1 (890/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 20.9ms\n",
            "video 1/1 (891/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.1ms\n",
            "video 1/1 (892/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.8ms\n",
            "video 1/1 (893/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 22.9ms\n",
            "video 1/1 (894/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.0ms\n",
            "video 1/1 (895/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.8ms\n",
            "video 1/1 (896/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 20.1ms\n",
            "video 1/1 (897/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.6ms\n",
            "video 1/1 (898/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.1ms\n",
            "video 1/1 (899/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.1ms\n",
            "video 1/1 (900/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 25.0ms\n",
            "video 1/1 (901/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.6ms\n",
            "video 1/1 (902/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 18.7ms\n",
            "video 1/1 (903/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 19.4ms\n",
            "video 1/1 (904/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 21.6ms\n",
            "video 1/1 (905/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 16.6ms\n",
            "video 1/1 (906/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.0ms\n",
            "video 1/1 (907/907) /content/gdrive/My Drive/TrainingVector/vectorNewBackground.mp4: 128x224 (no detections), 17.2ms\n",
            "Speed: 0.3ms pre-process, 20.6ms inference, 1.6ms NMS per image at shape (1, 3, 224, 224)\n",
            "Results saved to \u001b[1mruns/detect/exp2\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%ls -l runs/detect/exp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kf562nVFDAk4",
        "outputId": "76ddc1d8-02b5-44d3-92fb-57de006aa469"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ls: cannot access 'runs/detect/exp5': No such file or directory\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cp runs/detect/exp/vectorNewBackground.mp4 /content/gdrive/'My Drive'/OutputVector/vectorNewBackground_yolov9.mp4"
      ],
      "metadata": {
        "id": "BcFIFsRzDGT2"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}