U_NetRoadSegmentation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "U-NetRoadSegmentation.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5fMyiz26AHdj",
        "colab_type": "text"
      },
      "source": [
        "# Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BNV_HkFBBBJU",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import cv2 # For CV operations\n",
        "from PIL import Image  #To create and store images\n",
        "import numpy as np\n",
        "\n",
        "#To binarize the input\n",
        "import h5py\n",
        "import os"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MQ9ehyweCgPZ",
        "colab_type": "text"
      },
      "source": [
        "### Mapping the Drive"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J_bdjIA0Cjzj",
        "colab_type": "code",
        "outputId": "a6cfea76-f2b7-4c55-bb87-eb491af6017d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 128
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O4gs3JGVCuqO",
        "colab_type": "code",
        "outputId": "47089da9-7a05-46aa-e044-2d64050ddf9f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd drive/My Drive/Colab Notebooks/cropped_months/dataset/"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/My Drive/Colab Notebooks/cropped_months/dataset\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kJD_pPnXB4a7",
        "colab_type": "text"
      },
      "source": [
        "## Resizing the Images (Input) (Satellite Images)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wSa4vX9-CFhv",
        "colab_type": "code",
        "outputId": "bef48138-ba0d-432f-fceb-79d58e5b9340",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 60454
        }
      },
      "source": [
        "# Resizing each image (1500 * 1500) to image (256 * 256) and converting the ground truths to binary masks\n",
        "\n",
        "originalImages = os.listdir(\"Training/Input\")\n",
        "dim = (256, 256) #(w,h)\n",
        "\n",
        "for index,image in enumerate(originalImages):\n",
        "  \n",
        "  print(\"Reading Image : \" + str(image) +\" with Index : \"+str(index))\n",
        "  readImage = cv2.imread(\"Training/Input/\" + str(image), 1)\n",
        "  \n",
        "  resizedImage = cv2.resize(readImage, dim, interpolation=cv2.INTER_AREA)\n",
        "  \n",
        "  imageName = str(image).split(\".\")[0]\n",
        "  print(\"Shape of resized Image is : \", resizedImage.shape)\n",
        "  \n",
        "  #Converting to .png and Storing resized image to a directory\n",
        "  \n",
        "  cv2.imwrite(os.getcwd() + \"/TrainingImages/\" + imageName + \".png\", resizedImage)\n",
        "  print(\"Resized and Stored Image : \" + str(image) +\" with Index : \"+str(index))\n"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading Image : 11278720_15.tiff with Index : 0\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278720_15.tiff with Index : 0\n",
            "Reading Image : 11278735_15.tiff with Index : 1\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278735_15.tiff with Index : 1\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11278780_15.tiff with Index : 4\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 22529425_15.tiff with Index : 538\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 22529440_15.tiff with Index : 539\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23279005_15.tiff with Index : 635\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23279110_15.tiff with Index : 641\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23428525_15.tiff with Index : 647\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23428930_15.tiff with Index : 655\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23428945_15.tiff with Index : 656\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429005_15.tiff with Index : 660\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429035_15.tiff with Index : 662\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429050_15.tiff with Index : 663\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429065_15.tiff with Index : 664\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429110_15.tiff with Index : 666\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429125_15.tiff with Index : 667\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23429140_15.tiff with Index : 668\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23429155_15.tiff with Index : 669\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23578975_15.tiff with Index : 688\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23579020_15.tiff with Index : 691\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23579125_15.tiff with Index : 698\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23579140_15.tiff with Index : 699\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23579155_15.tiff with Index : 700\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728525_15.tiff with Index : 704\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728570_15.tiff with Index : 707\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728600_15.tiff with Index : 708\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728780_15.tiff with Index : 710\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728795_15.tiff with Index : 711\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728810_15.tiff with Index : 712\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728825_15.tiff with Index : 713\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728840_15.tiff with Index : 714\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728930_15.tiff with Index : 716\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728945_15.tiff with Index : 717\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728960_15.tiff with Index : 718\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728975_15.tiff with Index : 719\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23728990_15.tiff with Index : 720\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23728990_15.tiff with Index : 720\n",
            "Reading Image : 23729005_15.tiff with Index : 721\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729035_15.tiff with Index : 722\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729050_15.tiff with Index : 723\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729065_15.tiff with Index : 724\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729080_15.tiff with Index : 725\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729095_15.tiff with Index : 726\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729110_15.tiff with Index : 727\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23729110_15.tiff with Index : 727\n",
            "Reading Image : 23729230_15.tiff with Index : 728\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23729245_15.tiff with Index : 729\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878480_15.tiff with Index : 730\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878495_15.tiff with Index : 731\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878510_15.tiff with Index : 732\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878525_15.tiff with Index : 733\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878555_15.tiff with Index : 734\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878570_15.tiff with Index : 735\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878585_15.tiff with Index : 736\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878765_15.tiff with Index : 737\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878780_15.tiff with Index : 738\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878795_15.tiff with Index : 739\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878810_15.tiff with Index : 740\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23878810_15.tiff with Index : 740\n",
            "Reading Image : 23878825_15.tiff with Index : 741\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878915_15.tiff with Index : 742\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878930_15.tiff with Index : 743\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23878930_15.tiff with Index : 743\n",
            "Reading Image : 23878945_15.tiff with Index : 744\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23878945_15.tiff with Index : 744\n",
            "Reading Image : 23878960_15.tiff with Index : 745\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23878960_15.tiff with Index : 745\n",
            "Reading Image : 23878975_15.tiff with Index : 746\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23878990_15.tiff with Index : 747\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23879005_15.tiff with Index : 748\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879005_15.tiff with Index : 748\n",
            "Reading Image : 23879020_15.tiff with Index : 749\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23879035_15.tiff with Index : 750\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879035_15.tiff with Index : 750\n",
            "Reading Image : 23879050_15.tiff with Index : 751\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23879065_15.tiff with Index : 752\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879065_15.tiff with Index : 752\n",
            "Reading Image : 23879080_15.tiff with Index : 753\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 23879095_15.tiff with Index : 754\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879095_15.tiff with Index : 754\n",
            "Reading Image : 23879110_15.tiff with Index : 755\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879110_15.tiff with Index : 755\n",
            "Reading Image : 23879200_15.tiff with Index : 756\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879200_15.tiff with Index : 756\n",
            "Reading Image : 23879215_15.tiff with Index : 757\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879215_15.tiff with Index : 757\n",
            "Reading Image : 23879230_15.tiff with Index : 758\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879230_15.tiff with Index : 758\n",
            "Reading Image : 23879245_15.tiff with Index : 759\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 23879245_15.tiff with Index : 759\n",
            "Reading Image : 24028480_15.tiff with Index : 760\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028480_15.tiff with Index : 760\n",
            "Reading Image : 24028495_15.tiff with Index : 761\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028495_15.tiff with Index : 761\n",
            "Reading Image : 24028510_15.tiff with Index : 762\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028510_15.tiff with Index : 762\n",
            "Reading Image : 24028525_15.tiff with Index : 763\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028525_15.tiff with Index : 763\n",
            "Reading Image : 24028540_15.tiff with Index : 764\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028540_15.tiff with Index : 764\n",
            "Reading Image : 24028555_15.tiff with Index : 765\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028555_15.tiff with Index : 765\n",
            "Reading Image : 24028795_15.tiff with Index : 766\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028795_15.tiff with Index : 766\n",
            "Reading Image : 24028810_15.tiff with Index : 767\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028810_15.tiff with Index : 767\n",
            "Reading Image : 24028825_15.tiff with Index : 768\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028825_15.tiff with Index : 768\n",
            "Reading Image : 24028990_15.tiff with Index : 769\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24028990_15.tiff with Index : 769\n",
            "Reading Image : 24029005_15.tiff with Index : 770\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029005_15.tiff with Index : 770\n",
            "Reading Image : 24029020_15.tiff with Index : 771\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029020_15.tiff with Index : 771\n",
            "Reading Image : 24029050_15.tiff with Index : 772\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029050_15.tiff with Index : 772\n",
            "Reading Image : 24029065_15.tiff with Index : 773\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029065_15.tiff with Index : 773\n",
            "Reading Image : 24029080_15.tiff with Index : 774\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24029095_15.tiff with Index : 775\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029095_15.tiff with Index : 775\n",
            "Reading Image : 24029110_15.tiff with Index : 776\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029110_15.tiff with Index : 776\n",
            "Reading Image : 24029185_15.tiff with Index : 777\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029185_15.tiff with Index : 777\n",
            "Reading Image : 24029200_15.tiff with Index : 778\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029200_15.tiff with Index : 778\n",
            "Reading Image : 24029215_15.tiff with Index : 779\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029215_15.tiff with Index : 779\n",
            "Reading Image : 24029230_15.tiff with Index : 780\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029230_15.tiff with Index : 780\n",
            "Reading Image : 24029245_15.tiff with Index : 781\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24029245_15.tiff with Index : 781\n",
            "Reading Image : 24178480_15.tiff with Index : 782\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24178495_15.tiff with Index : 783\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24178495_15.tiff with Index : 783\n",
            "Reading Image : 24178510_15.tiff with Index : 784\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24179230_15.tiff with Index : 800\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24329200_15.tiff with Index : 820\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24478840_15.tiff with Index : 830\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24478885_15.tiff with Index : 832\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24479005_15.tiff with Index : 835\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24479200_15.tiff with Index : 840\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24479230_15.tiff with Index : 841\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24479260_15.tiff with Index : 843\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24628810_15.tiff with Index : 848\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24628825_15.tiff with Index : 849\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24628840_15.tiff with Index : 850\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24628840_15.tiff with Index : 850\n",
            "Reading Image : 24628855_15.tiff with Index : 851\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24628900_15.tiff with Index : 853\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629170_15.tiff with Index : 855\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629185_15.tiff with Index : 856\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629215_15.tiff with Index : 857\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629230_15.tiff with Index : 858\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629245_15.tiff with Index : 859\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629260_15.tiff with Index : 860\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629275_15.tiff with Index : 861\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629290_15.tiff with Index : 862\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24629305_15.tiff with Index : 863\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778780_15.tiff with Index : 864\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778795_15.tiff with Index : 865\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778810_15.tiff with Index : 866\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778825_15.tiff with Index : 867\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24778825_15.tiff with Index : 867\n",
            "Reading Image : 24778840_15.tiff with Index : 868\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778855_15.tiff with Index : 869\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24778855_15.tiff with Index : 869\n",
            "Reading Image : 24778870_15.tiff with Index : 870\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778885_15.tiff with Index : 871\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778900_15.tiff with Index : 872\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24778915_15.tiff with Index : 873\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779155_15.tiff with Index : 874\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779170_15.tiff with Index : 875\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779185_15.tiff with Index : 876\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779200_15.tiff with Index : 877\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24779200_15.tiff with Index : 877\n",
            "Reading Image : 24779215_15.tiff with Index : 878\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24779215_15.tiff with Index : 878\n",
            "Reading Image : 24779230_15.tiff with Index : 879\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779245_15.tiff with Index : 880\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779260_15.tiff with Index : 881\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779290_15.tiff with Index : 882\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24779305_15.tiff with Index : 883\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 24928900_15.tiff with Index : 884\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24928900_15.tiff with Index : 884\n",
            "Reading Image : 24929155_15.tiff with Index : 885\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929155_15.tiff with Index : 885\n",
            "Reading Image : 24929185_15.tiff with Index : 886\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929185_15.tiff with Index : 886\n",
            "Reading Image : 24929200_15.tiff with Index : 887\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929200_15.tiff with Index : 887\n",
            "Reading Image : 24929215_15.tiff with Index : 888\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929215_15.tiff with Index : 888\n",
            "Reading Image : 24929230_15.tiff with Index : 889\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929230_15.tiff with Index : 889\n",
            "Reading Image : 24929260_15.tiff with Index : 890\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929260_15.tiff with Index : 890\n",
            "Reading Image : 24929275_15.tiff with Index : 891\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929275_15.tiff with Index : 891\n",
            "Reading Image : 24929290_15.tiff with Index : 892\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 24929290_15.tiff with Index : 892\n",
            "Reading Image : 25079155_15.tiff with Index : 893\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 25079155_15.tiff with Index : 893\n",
            "Reading Image : 25079185_15.tiff with Index : 894\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 25079185_15.tiff with Index : 894\n",
            "Reading Image : 25079200_15.tiff with Index : 895\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 25079200_15.tiff with Index : 895\n",
            "Reading Image : 25079215_15.tiff with Index : 896\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 25079215_15.tiff with Index : 896\n",
            "Reading Image : 25079230_15.tiff with Index : 897\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26428720_15.tiff with Index : 964\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26429260_15.tiff with Index : 970\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26578780_15.tiff with Index : 978\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26728735_15.tiff with Index : 984\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26878720_15.tiff with Index : 990\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26878735_15.tiff with Index : 991\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 26878750_15.tiff with Index : 992\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 27028720_15.tiff with Index : 996\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 99238660_15.tiff with Index : 998\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 99238675_15.tiff with Index : 999\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078660_15.tiff with Index : 1000\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078675_15.tiff with Index : 1001\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078690_15.tiff with Index : 1002\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078705_15.tiff with Index : 1003\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078720_15.tiff with Index : 1004\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078735_15.tiff with Index : 1005\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10078750_15.tiff with Index : 1006\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10228675_15.tiff with Index : 1008\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10228720_15.tiff with Index : 1010\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 10228720_15.tiff with Index : 1010\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10528660_15.tiff with Index : 1025\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10528720_15.tiff with Index : 1029\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10528750_15.tiff with Index : 1031\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10828855_15.tiff with Index : 1061\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978690_15.tiff with Index : 1067\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978720_15.tiff with Index : 1069\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978750_15.tiff with Index : 1070\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978825_15.tiff with Index : 1074\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978840_15.tiff with Index : 1075\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978855_15.tiff with Index : 1076\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978870_15.tiff with Index : 1077\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978900_15.tiff with Index : 1079\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978915_15.tiff with Index : 1080\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978930_15.tiff with Index : 1081\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 10978945_15.tiff with Index : 1082\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11128645_15.tiff with Index : 1083\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11128660_15.tiff with Index : 1084\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11128690_15.tiff with Index : 1086\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11128705_15.tiff with Index : 1087\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
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            "Reading Image : 11128720_15.tiff with Index : 1088\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128720_15.tiff with Index : 1088\n",
            "Reading Image : 11128735_15.tiff with Index : 1089\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128735_15.tiff with Index : 1089\n",
            "Reading Image : 11128750_15.tiff with Index : 1090\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128750_15.tiff with Index : 1090\n",
            "Reading Image : 11128765_15.tiff with Index : 1091\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128765_15.tiff with Index : 1091\n",
            "Reading Image : 11128780_15.tiff with Index : 1092\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128780_15.tiff with Index : 1092\n",
            "Reading Image : 11128795_15.tiff with Index : 1093\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128795_15.tiff with Index : 1093\n",
            "Reading Image : 11128810_15.tiff with Index : 1094\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128810_15.tiff with Index : 1094\n",
            "Reading Image : 11128825_15.tiff with Index : 1095\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128825_15.tiff with Index : 1095\n",
            "Reading Image : 11128840_15.tiff with Index : 1096\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128840_15.tiff with Index : 1096\n",
            "Reading Image : 11128855_15.tiff with Index : 1097\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128855_15.tiff with Index : 1097\n",
            "Reading Image : 11128885_15.tiff with Index : 1098\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128885_15.tiff with Index : 1098\n",
            "Reading Image : 11128900_15.tiff with Index : 1099\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128900_15.tiff with Index : 1099\n",
            "Reading Image : 11128915_15.tiff with Index : 1100\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128915_15.tiff with Index : 1100\n",
            "Reading Image : 11128930_15.tiff with Index : 1101\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128930_15.tiff with Index : 1101\n",
            "Reading Image : 11128945_15.tiff with Index : 1102\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11128945_15.tiff with Index : 1102\n",
            "Reading Image : 11278645_15.tiff with Index : 1103\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278645_15.tiff with Index : 1103\n",
            "Reading Image : 11278660_15.tiff with Index : 1104\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278660_15.tiff with Index : 1104\n",
            "Reading Image : 11278675_15.tiff with Index : 1105\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278675_15.tiff with Index : 1105\n",
            "Reading Image : 11278690_15.tiff with Index : 1106\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278690_15.tiff with Index : 1106\n",
            "Reading Image : 11278705_15.tiff with Index : 1107\n",
            "Shape of resized Image is :  (256, 256, 3)\n",
            "Resized and Stored Image : 11278705_15.tiff with Index : 1107\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YG_r_6qxNZDl",
        "colab_type": "text"
      },
      "source": [
        "## Resizing the labels to Binary Masks"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NAqsWRSiNgsQ",
        "colab_type": "code",
        "outputId": "dd603664-e0ad-487f-db05-214b82a7f81c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 60454
        }
      },
      "source": [
        "# Resizing each image (1500 * 1500) to image (256 * 256) and converting the ground truths to binary masks\n",
        "\n",
        "originalImages = os.listdir(\"Training/InputLables\")\n",
        "dim = (256, 256) #(w,h)\n",
        "\n",
        "for index,image in enumerate(originalImages):\n",
        "  \n",
        "  print(\"Reading Image : \" + str(image) +\" with Index : \"+str(index))\n",
        "  readImage = cv2.imread(\"Training/InputLables/\" + str(image), 0)\n",
        "  \n",
        "  resizedImage = cv2.resize(readImage, dim, interpolation=cv2.INTER_AREA)\n",
        "  \n",
        "  imageName = str(image).split(\".\")[0]\n",
        "  \n",
        "  (thresh, im_bw) = cv2.threshold(resizedImage, 128, 255, cv2.THRESH_BINARY)\n",
        "  \n",
        "  print(\"Shape of resized Image is : \", im_bw.shape)\n",
        "  \n",
        "  #Converting to .png and Storing resized image to a directory\n",
        "  \n",
        "  cv2.imwrite(os.getcwd() + \"/TrainingMasks/\" + imageName + \".png\", im_bw)\n",
        "  print(\"Resized and Stored Image : \" + str(image) +\" with Index : \"+str(index))"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading Image : 11278720_15.tif with Index : 0\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278720_15.tif with Index : 0\n",
            "Reading Image : 11278735_15.tif with Index : 1\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278735_15.tif with Index : 1\n",
            "Reading Image : 11278750_15.tif with Index : 2\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278750_15.tif with Index : 2\n",
            "Reading Image : 11278765_15.tif with Index : 3\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278765_15.tif with Index : 3\n",
            "Reading Image : 11278780_15.tif with Index : 4\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278780_15.tif with Index : 4\n",
            "Reading Image : 11278795_15.tif with Index : 5\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278795_15.tif with Index : 5\n",
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            "Reading Image : 23729005_15.tif with Index : 721\n",
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            "Reading Image : 23729035_15.tif with Index : 722\n",
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            "Reading Image : 23729050_15.tif with Index : 723\n",
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            "Reading Image : 23729065_15.tif with Index : 724\n",
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            "Reading Image : 23729080_15.tif with Index : 725\n",
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            "Reading Image : 23729230_15.tif with Index : 728\n",
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            "Reading Image : 23729245_15.tif with Index : 729\n",
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            "Reading Image : 24479260_15.tif with Index : 843\n",
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            "Reading Image : 24628825_15.tif with Index : 849\n",
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            "Reading Image : 24628840_15.tif with Index : 850\n",
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            "Reading Image : 24629275_15.tif with Index : 861\n",
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            "Reading Image : 24629290_15.tif with Index : 862\n",
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            "Reading Image : 26428720_15.tif with Index : 964\n",
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            "Reading Image : 11278645_15.tif with Index : 1103\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278645_15.tif with Index : 1103\n",
            "Reading Image : 11278660_15.tif with Index : 1104\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278660_15.tif with Index : 1104\n",
            "Reading Image : 11278675_15.tif with Index : 1105\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278675_15.tif with Index : 1105\n",
            "Reading Image : 11278690_15.tif with Index : 1106\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278690_15.tif with Index : 1106\n",
            "Reading Image : 11278705_15.tif with Index : 1107\n",
            "Shape of resized Image is :  (256, 256)\n",
            "Resized and Stored Image : 11278705_15.tif with Index : 1107\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BGrfdb9zmDdu",
        "colab_type": "text"
      },
      "source": [
        "## Creating input & mask arrays"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DLWhnVXomKeV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 20163
        },
        "outputId": "eb0b1c83-fbb5-4934-c9fa-85af21d02ced"
      },
      "source": [
        "images = []\n",
        "originalImages = os.listdir(\"TrainingImages/\")\n",
        "\n",
        "for index,image in enumerate(originalImages):\n",
        "    print(\"Image number : \" +str(index) )\n",
        "    img = Image.open(\"TrainingImages/\" + str(image))\n",
        "    \n",
        "    arr = np.array(img)\n",
        "    #arr = np.expand_dims(arr, -1)\n",
        "    images.append(arr)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vTGbgLEym0m0",
        "colab_type": "code",
        "outputId": "039818b4-2fd6-489d-b090-d5de91f91126",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 20163
        }
      },
      "source": [
        "masks = []\n",
        "originalImages = os.listdir(\"TrainingMasks/\")\n",
        "\n",
        "for index,image in enumerate(originalImages):\n",
        "  print(\"Image number : \" +str(index) )\n",
        "  img = Image.open(\"TrainingMasks/\" + str(image))\n",
        "  arr = np.array(img)\n",
        "  arr = np.expand_dims(arr, -1)\n",
        "  masks.append(arr)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f28OHwbcpT-K",
        "colab_type": "code",
        "outputId": "4c2de72b-c380-431e-d86d-c8dc0ba57ece",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "images = np.array(images)\n",
        "masks = np.array(masks)\n",
        "\n",
        "print(masks.shape)\n",
        "print(images.shape)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(1108, 256, 256, 1)\n",
            "(1108, 256, 256, 3)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nOy1QTKGpV8k",
        "colab_type": "text"
      },
      "source": [
        "## Finalizing Dataset for Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J3svZnTSpYrN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "with h5py.File(\"Dataset_train.h5\", 'w') as hdf:\n",
        "    hdf.create_dataset('images', data=images, compression='gzip', compression_opts=9)\n",
        "    hdf.create_dataset('masks', data=masks, compression='gzip', compression_opts=9)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tl7vw0OSpzmY",
        "colab_type": "text"
      },
      "source": [
        "# U-Net Model for Road Segmentation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b6b7M2GZp_MB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "625737c9-2279-4481-f70a-9ff5230d0832"
      },
      "source": [
        "from keras.models import *\n",
        "from keras.layers import *\n",
        "from keras.optimizers import *\n",
        "import keras\n",
        "import keras.callbacks\n",
        "from keras.callbacks import TensorBoard\n",
        "from keras.callbacks import ModelCheckpoint\n",
        "from keras import backend as keras\n",
        "\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Using TensorFlow backend.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "01OsYjMDq06l",
        "colab_type": "text"
      },
      "source": [
        "## Model Definition"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X1jmuKwDrEkC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def unet(pretrained_weights = None,input_size = (256,256,3)):\n",
        "    inputs = Input(input_size)\n",
        "    conv1 = Conv2D(64, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(inputs)\n",
        "    conv1 = Conv2D(64, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv1)\n",
        "    pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",
        "    conv2 = Conv2D(128, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool1)\n",
        "    conv2 = Conv2D(128, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv2)\n",
        "    pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",
        "    conv3 = Conv2D(256, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool2)\n",
        "    conv3 = Conv2D(256, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv3)\n",
        "    pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",
        "    conv4 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool3)\n",
        "    conv4 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv4)\n",
        "    drop4 = Dropout(0.5)(conv4)\n",
        "    pool4 = MaxPooling2D(pool_size=(2, 2))(drop4)\n",
        "\n",
        "    conv5 = Conv2D(1024, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(pool4)\n",
        "    conv5 = Conv2D(1024, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv5)\n",
        "    drop5 = Dropout(0.5)(conv5)\n",
        "\n",
        "    up6 = Conv2D(512, 2, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(UpSampling2D(size = (2,2))(drop5))\n",
        "    merge6 = concatenate([drop4,up6], axis = 3)\n",
        "    conv6 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(merge6)\n",
        "    conv6 = Conv2D(512, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv6)\n",
        "\n",
        "    up7 = Conv2D(256, 2, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(UpSampling2D(size = (2,2))(conv6))\n",
        "    merge7 = concatenate([conv3,up7], axis = 3)\n",
        "    conv7 = Conv2D(256, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(merge7)\n",
        "    conv7 = Conv2D(256, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv7)\n",
        "\n",
        "    up8 = Conv2D(128, 2, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(UpSampling2D(size = (2,2))(conv7))\n",
        "    merge8 = concatenate([conv2,up8], axis = 3)\n",
        "    conv8 = Conv2D(128, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(merge8)\n",
        "    conv8 = Conv2D(128, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv8)\n",
        "\n",
        "    up9 = Conv2D(64, 2, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(UpSampling2D(size = (2,2))(conv8))\n",
        "    merge9 = concatenate([conv1,up9], axis = 3)\n",
        "    conv9 = Conv2D(64, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(merge9)\n",
        "    conv9 = Conv2D(64, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv9)\n",
        "    conv9 = Conv2D(2, 3, activation = 'relu', padding = 'same', kernel_initializer = 'he_normal')(conv9)\n",
        "    conv10 = Conv2D(1, 1, activation = 'sigmoid')(conv9)\n",
        "\n",
        "    model = Model(input = inputs, output = conv10)\n",
        "\n",
        "    model.compile(optimizer = Adam(lr = 1e-4), loss = 'binary_crossentropy', metrics = ['accuracy'])\n",
        "    \n",
        "    #model.summary()\n",
        "\n",
        "    if(pretrained_weights):\n",
        "    \tmodel.load_weights(pretrained_weights)\n",
        "\n",
        "    return model"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kMxMDCRJrMUx",
        "colab_type": "text"
      },
      "source": [
        "### Optimizer : Adam, Loss : Binary Cross Entropy"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bIcuqZshrTPs",
        "colab_type": "code",
        "outputId": "00388a9f-a292-499a-ab20-89ccd0920660",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        }
      },
      "source": [
        "print('*'*30)\n",
        "print('Loading and preprocessing train data...')\n",
        "print('*'*30)\n",
        "file = h5py.File('Dataset_train.h5', 'r')\n",
        "imgs_train = file.get('images')\n",
        "imgs_mask_train = file.get('masks')\n",
        "imgs_train = np.array(imgs_train)\n",
        "imgs_mask_train = np.array(imgs_mask_train)\n",
        "\n",
        "print(imgs_train.shape)\n",
        "print(imgs_mask_train.shape)\n",
        "#imgs_train = imgs_train.reshape(1108,256,256,1)\n",
        "\n",
        " \n",
        "imgs_train = imgs_train.astype('float32')\n",
        "\n",
        "mean = np.mean(imgs_train)  # mean for data centering\n",
        "std = np.std(imgs_train)  # std for data normalization\n",
        "\n",
        "imgs_train -= mean\n",
        "imgs_train /= std\n",
        "\n",
        "imgs_mask_train = imgs_mask_train.astype('float32')\n",
        "imgs_mask_train /= 255  # scale masks to [0, 1]\n",
        "\n",
        "print('*'*30)\n",
        "print('Creating and compiling model...')\n",
        "print('*'*30)\n",
        "model = unet()\n",
        "model_checkpoint = ModelCheckpoint('weights.h5', monitor='val_loss', save_best_only=True)\n",
        "tensorboard = TensorBoard(log_dir='tensorboard/', write_graph=True, write_images=True)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Loading and preprocessing train data...\n",
            "******************************\n",
            "(1108, 256, 256, 3)\n",
            "(1108, 256, 256, 1)\n",
            "******************************\n",
            "Creating and compiling model...\n",
            "******************************\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Colocations handled automatically by placer.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:43: UserWarning: Update your `Model` call to the Keras 2 API: `Model(inputs=Tensor(\"in..., outputs=Tensor(\"co...)`\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wwmleiqmsSZN",
        "colab_type": "text"
      },
      "source": [
        "## Model Fitting"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GQ_2PxSbsCYH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6LUBV72YsMNZ",
        "colab_type": "code",
        "outputId": "476687bf-e1aa-4e4e-c7bc-19ab17fec9f2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1255
        }
      },
      "source": [
        "print('*'*30)\n",
        "print('Fitting model...')\n",
        "print('*'*30)\n",
        "history =  model.fit(imgs_train, imgs_mask_train, batch_size=16, epochs=30, verbose=2, shuffle=True,validation_split=0.2,callbacks=[model_checkpoint, tensorboard])"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Fitting model...\n",
            "******************************\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n",
            "Train on 886 samples, validate on 222 samples\n",
            "Epoch 1/30\n",
            " - 86s - loss: 0.2241 - acc: 0.9489 - val_loss: 0.1671 - val_acc: 0.9620\n",
            "Epoch 2/30\n",
            " - 64s - loss: 0.1691 - acc: 0.9498 - val_loss: 0.1514 - val_acc: 0.9620\n",
            "Epoch 3/30\n",
            " - 64s - loss: 0.1597 - acc: 0.9498 - val_loss: 0.1381 - val_acc: 0.9620\n",
            "Epoch 4/30\n",
            " - 64s - loss: 0.1516 - acc: 0.9498 - val_loss: 0.1338 - val_acc: 0.9620\n",
            "Epoch 5/30\n",
            " - 64s - loss: 0.1491 - acc: 0.9498 - val_loss: 0.1282 - val_acc: 0.9620\n",
            "Epoch 6/30\n",
            " - 64s - loss: 0.1444 - acc: 0.9498 - val_loss: 0.1247 - val_acc: 0.9620\n",
            "Epoch 7/30\n",
            " - 64s - loss: 0.1419 - acc: 0.9498 - val_loss: 0.1280 - val_acc: 0.9620\n",
            "Epoch 8/30\n",
            " - 64s - loss: 0.1381 - acc: 0.9498 - val_loss: 0.1209 - val_acc: 0.9620\n",
            "Epoch 9/30\n",
            " - 64s - loss: 0.1360 - acc: 0.9498 - val_loss: 0.1214 - val_acc: 0.9620\n",
            "Epoch 10/30\n",
            " - 64s - loss: 0.1347 - acc: 0.9498 - val_loss: 0.1171 - val_acc: 0.9620\n",
            "Epoch 11/30\n",
            " - 64s - loss: 0.1320 - acc: 0.9548 - val_loss: 0.1207 - val_acc: 0.9653\n",
            "Epoch 12/30\n",
            " - 64s - loss: 0.1298 - acc: 0.9567 - val_loss: 0.1152 - val_acc: 0.9661\n",
            "Epoch 13/30\n",
            " - 64s - loss: 0.1287 - acc: 0.9572 - val_loss: 0.1169 - val_acc: 0.9664\n",
            "Epoch 14/30\n",
            " - 64s - loss: 0.1267 - acc: 0.9577 - val_loss: 0.1153 - val_acc: 0.9665\n",
            "Epoch 15/30\n",
            " - 64s - loss: 0.1250 - acc: 0.9583 - val_loss: 0.1120 - val_acc: 0.9670\n",
            "Epoch 16/30\n",
            " - 64s - loss: 0.1231 - acc: 0.9589 - val_loss: 0.1150 - val_acc: 0.9671\n",
            "Epoch 17/30\n",
            " - 64s - loss: 0.1213 - acc: 0.9594 - val_loss: 0.1135 - val_acc: 0.9669\n",
            "Epoch 18/30\n",
            " - 64s - loss: 0.1207 - acc: 0.9598 - val_loss: 0.1174 - val_acc: 0.9673\n",
            "Epoch 19/30\n",
            " - 64s - loss: 0.1193 - acc: 0.9602 - val_loss: 0.1135 - val_acc: 0.9683\n",
            "Epoch 20/30\n",
            " - 64s - loss: 0.1170 - acc: 0.9606 - val_loss: 0.1107 - val_acc: 0.9683\n",
            "Epoch 21/30\n",
            " - 64s - loss: 0.1152 - acc: 0.9610 - val_loss: 0.1112 - val_acc: 0.9679\n",
            "Epoch 22/30\n",
            " - 64s - loss: 0.1149 - acc: 0.9612 - val_loss: 0.1084 - val_acc: 0.9684\n",
            "Epoch 23/30\n",
            " - 64s - loss: 0.1118 - acc: 0.9619 - val_loss: 0.1237 - val_acc: 0.9681\n",
            "Epoch 24/30\n",
            " - 64s - loss: 0.1116 - acc: 0.9622 - val_loss: 0.1091 - val_acc: 0.9690\n",
            "Epoch 25/30\n",
            " - 64s - loss: 0.1091 - acc: 0.9629 - val_loss: 0.1027 - val_acc: 0.9701\n",
            "Epoch 26/30\n",
            " - 64s - loss: 0.1075 - acc: 0.9633 - val_loss: 0.1011 - val_acc: 0.9699\n",
            "Epoch 27/30\n",
            " - 64s - loss: 0.1053 - acc: 0.9640 - val_loss: 0.1130 - val_acc: 0.9693\n",
            "Epoch 28/30\n",
            " - 64s - loss: 0.1050 - acc: 0.9642 - val_loss: 0.0987 - val_acc: 0.9707\n",
            "Epoch 29/30\n",
            " - 65s - loss: 0.1032 - acc: 0.9646 - val_loss: 0.0968 - val_acc: 0.9708\n",
            "Epoch 30/30\n",
            " - 64s - loss: 0.1017 - acc: 0.9650 - val_loss: 0.1095 - val_acc: 0.9693\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mh_R4OgvO6Rx",
        "colab_type": "text"
      },
      "source": [
        "## Creating Test Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vppLoOfaO8gE",
        "colab_type": "code",
        "outputId": "f996f34d-7324-480d-b67c-22045b1c06c6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1799
        }
      },
      "source": [
        "originalImages = os.listdir(\"Testing/testingInput\")\n",
        "dim = (256, 256) #(w,h)\n",
        "\n",
        "for index,image in enumerate(originalImages):\n",
        "  \n",
        "  print(\"Reading Image : \" + str(image) +\" with Index : \"+str(index))\n",
        "  readImage = cv2.imread(\"Testing/testingInput/\" + str(image), 1)\n",
        "  \n",
        "  resizedImage = cv2.resize(readImage, dim, interpolation=cv2.INTER_AREA)\n",
        "  \n",
        "  imageName = str(image).split(\".\")[0]\n",
        "  \n",
        "  #Converting to .png and Storing resized image to a directory\n",
        "  \n",
        "  \n",
        "  cv2.imwrite(os.getcwd() + \"/TestingImages/\" + imageName + \".png\", resizedImage)\n",
        "  print(\"Resized and Stored Image : \" + str(image) +\" with Index : \"+str(index))"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading Image : 10378780_15.tiff with Index : 0\n",
            "Resized and Stored Image : 10378780_15.tiff with Index : 0\n",
            "Reading Image : 10828720_15.tiff with Index : 1\n",
            "Resized and Stored Image : 10828720_15.tiff with Index : 1\n",
            "Reading Image : 11128870_15.tiff with Index : 2\n",
            "Resized and Stored Image : 11128870_15.tiff with Index : 2\n",
            "Reading Image : 11278840_15.tiff with Index : 3\n",
            "Resized and Stored Image : 11278840_15.tiff with Index : 3\n",
            "Reading Image : 11728825_15.tiff with Index : 4\n",
            "Resized and Stored Image : 11728825_15.tiff with Index : 4\n",
            "Reading Image : 12328750_15.tiff with Index : 5\n",
            "Resized and Stored Image : 12328750_15.tiff with Index : 5\n",
            "Reading Image : 15928855_15.tiff with Index : 6\n",
            "Resized and Stored Image : 15928855_15.tiff with Index : 6\n",
            "Reading Image : 16078870_15.tiff with Index : 7\n",
            "Resized and Stored Image : 16078870_15.tiff with Index : 7\n",
            "Reading Image : 17878735_15.tiff with Index : 8\n",
            "Resized and Stored Image : 17878735_15.tiff with Index : 8\n",
            "Reading Image : 17878780_15.tiff with Index : 9\n",
            "Resized and Stored Image : 17878780_15.tiff with Index : 9\n",
            "Reading Image : 17878885_15.tiff with Index : 10\n",
            "Resized and Stored Image : 17878885_15.tiff with Index : 10\n",
            "Reading Image : 18028750_15.tiff with Index : 11\n",
            "Resized and Stored Image : 18028750_15.tiff with Index : 11\n",
            "Reading Image : 18178780_15.tiff with Index : 12\n",
            "Resized and Stored Image : 18178780_15.tiff with Index : 12\n",
            "Reading Image : 18328735_15.tiff with Index : 13\n",
            "Resized and Stored Image : 18328735_15.tiff with Index : 13\n",
            "Reading Image : 18328780_15.tiff with Index : 14\n",
            "Resized and Stored Image : 18328780_15.tiff with Index : 14\n",
            "Reading Image : 18328960_15.tiff with Index : 15\n",
            "Resized and Stored Image : 18328960_15.tiff with Index : 15\n",
            "Reading Image : 18478735_15.tiff with Index : 16\n",
            "Resized and Stored Image : 18478735_15.tiff with Index : 16\n",
            "Reading Image : 18478900_15.tiff with Index : 17\n",
            "Resized and Stored Image : 18478900_15.tiff with Index : 17\n",
            "Reading Image : 18478930_15.tiff with Index : 18\n",
            "Resized and Stored Image : 18478930_15.tiff with Index : 18\n",
            "Reading Image : 20278885_15.tiff with Index : 19\n",
            "Resized and Stored Image : 20278885_15.tiff with Index : 19\n",
            "Reading Image : 20728960_15.tiff with Index : 20\n",
            "Resized and Stored Image : 20728960_15.tiff with Index : 20\n",
            "Reading Image : 20878930_15.tiff with Index : 21\n",
            "Resized and Stored Image : 20878930_15.tiff with Index : 21\n",
            "Reading Image : 21479035_15.tiff with Index : 22\n",
            "Resized and Stored Image : 21479035_15.tiff with Index : 22\n",
            "Reading Image : 21779005_15.tiff with Index : 23\n",
            "Resized and Stored Image : 21779005_15.tiff with Index : 23\n",
            "Reading Image : 22078975_15.tiff with Index : 24\n",
            "Resized and Stored Image : 22078975_15.tiff with Index : 24\n",
            "Reading Image : 22228900_15.tiff with Index : 25\n",
            "Resized and Stored Image : 22228900_15.tiff with Index : 25\n",
            "Reading Image : 22229050_15.tiff with Index : 26\n",
            "Resized and Stored Image : 22229050_15.tiff with Index : 26\n",
            "Reading Image : 22528885_15.tiff with Index : 27\n",
            "Resized and Stored Image : 22528885_15.tiff with Index : 27\n",
            "Reading Image : 22529065_15.tiff with Index : 28\n",
            "Resized and Stored Image : 22529065_15.tiff with Index : 28\n",
            "Reading Image : 23278915_15.tiff with Index : 29\n",
            "Resized and Stored Image : 23278915_15.tiff with Index : 29\n",
            "Reading Image : 23278930_15.tiff with Index : 30\n",
            "Resized and Stored Image : 23278930_15.tiff with Index : 30\n",
            "Reading Image : 23428540_15.tiff with Index : 31\n",
            "Resized and Stored Image : 23428540_15.tiff with Index : 31\n",
            "Reading Image : 23428810_15.tiff with Index : 32\n",
            "Resized and Stored Image : 23428810_15.tiff with Index : 32\n",
            "Reading Image : 23429080_15.tiff with Index : 33\n",
            "Resized and Stored Image : 23429080_15.tiff with Index : 33\n",
            "Reading Image : 23729020_15.tiff with Index : 34\n",
            "Resized and Stored Image : 23729020_15.tiff with Index : 34\n",
            "Reading Image : 23878540_15.tiff with Index : 35\n",
            "Resized and Stored Image : 23878540_15.tiff with Index : 35\n",
            "Reading Image : 24029035_15.tiff with Index : 36\n",
            "Resized and Stored Image : 24029035_15.tiff with Index : 36\n",
            "Reading Image : 24478825_15.tiff with Index : 37\n",
            "Resized and Stored Image : 24478825_15.tiff with Index : 37\n",
            "Reading Image : 24478855_15.tiff with Index : 38\n",
            "Resized and Stored Image : 24478855_15.tiff with Index : 38\n",
            "Reading Image : 24479170_15.tiff with Index : 39\n",
            "Resized and Stored Image : 24479170_15.tiff with Index : 39\n",
            "Reading Image : 24479215_15.tiff with Index : 40\n",
            "Resized and Stored Image : 24479215_15.tiff with Index : 40\n",
            "Reading Image : 24628885_15.tiff with Index : 41\n",
            "Resized and Stored Image : 24628885_15.tiff with Index : 41\n",
            "Reading Image : 24629200_15.tiff with Index : 42\n",
            "Resized and Stored Image : 24629200_15.tiff with Index : 42\n",
            "Reading Image : 24779275_15.tiff with Index : 43\n",
            "Resized and Stored Image : 24779275_15.tiff with Index : 43\n",
            "Reading Image : 25079170_15.tiff with Index : 44\n",
            "Resized and Stored Image : 25079170_15.tiff with Index : 44\n",
            "Reading Image : 26278720_15.tiff with Index : 45\n",
            "Resized and Stored Image : 26278720_15.tiff with Index : 45\n",
            "Reading Image : 26428735_15.tiff with Index : 46\n",
            "Resized and Stored Image : 26428735_15.tiff with Index : 46\n",
            "Reading Image : 26578720_15.tiff with Index : 47\n",
            "Resized and Stored Image : 26578720_15.tiff with Index : 47\n",
            "Reading Image : 26878690_15.tiff with Index : 48\n",
            "Resized and Stored Image : 26878690_15.tiff with Index : 48\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7LBE2cOtQXqE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "testImages = []\n",
        "originalImages = os.listdir(\"TestingImages/\")\n",
        "\n",
        "for i in originalImages:\n",
        "    img = Image.open(\"TestingImages/\" + str(i))\n",
        "    \n",
        "    arr = np.array(img)\n",
        "    #arr = np.expand_dims(arr, -1)\n",
        "    testImages.append(arr)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "udJyPFiqQNmX",
        "colab_type": "text"
      },
      "source": [
        "## Finalizing input for testing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N_99A2OXQzW2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "with h5py.File(\"Dataset_test.h5\", 'w') as hdf:\n",
        "    hdf.create_dataset('images', data=testImages, compression='gzip', compression_opts=9)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c8kSzVbpOhht",
        "colab_type": "code",
        "outputId": "4cf72d13-ad2a-4dbf-d716-96aebe147b6d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        }
      },
      "source": [
        "file = h5py.File('Dataset_test.h5', 'r')\n",
        "imgs_test = file.get('images')\n",
        "#imgs_mask_test = file.get('masks')\n",
        "imgs_test = np.array(imgs_test)\n",
        "#imgs_mask_test = np.array(imgs_mask_test)\n",
        "imgs_test = imgs_test.astype('float32')\n",
        "imgs_test -= mean\n",
        "imgs_test /= std\n",
        "\n",
        "print('*'*30)\n",
        "print('Loading saved weights...')\n",
        "print('*'*30)\n",
        "model.load_weights('weights.h5')\n",
        "\n",
        "print('*'*30)\n",
        "print('Predicting masks on test data...')\n",
        "print('*'*30)\n",
        "imgs_mask_test = model.predict(imgs_test, verbose=1)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Loading saved weights...\n",
            "******************************\n",
            "******************************\n",
            "Predicting masks on test data...\n",
            "******************************\n",
            "49/49 [==============================] - 15s 312ms/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZejaD0MhV7VF",
        "colab_type": "code",
        "outputId": "5ae0fc33-4f00-428c-91f2-23fed1a96b50",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        }
      },
      "source": [
        "print('*' * 30)\n",
        "print('Saving predicted masks to files...')\n",
        "print('*' * 30)\n",
        "pred_dir = 'Predictions'\n",
        "if not os.path.exists(pred_dir):\n",
        "    os.mkdir(pred_dir)\n",
        "for i, image in enumerate(imgs_mask_test):\n",
        "    image = (image * 255).astype(np.uint8)\n",
        "    cv2.imwrite(os.path.join(pred_dir, str(i + 1) + '_pred.png'), image)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Saving predicted masks to files...\n",
            "******************************\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EE8x6c_tWg_K",
        "colab_type": "code",
        "outputId": "a7df9600-6503-4875-c87d-3b4872144e11",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        }
      },
      "source": [
        "plt.figure(figsize=(10, 10))\n",
        "plt.plot(history.history['loss'], linewidth=4, color='r')                   #visualising training and validation loss curves\n",
        "plt.plot(history.history['val_loss'], linewidth=4, color='b')\n",
        "plt.title('Model train vs Validation Loss', fontsize=20, fontweight=\"bold\")\n",
        "plt.ylabel('Loss', fontsize=20)\n",
        "plt.xlabel('Epoch', fontsize=20)\n",
        "plt.legend(['Train', 'Validation'], loc='upper right', fontsize=20)\n",
        "plt.xticks(fontsize=20)\n",
        "plt.yticks(fontsize=20)\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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R7aPYv3//hIN0Bg8eHLNfWEVFRY2ynXbaCYCVK2vMMJh1TWvIkdROgVFERHIk\nOsDjyiuvZNy4cYwdOxZ358EHH8TMtg2MiRo7diyjR4+mU6dOHHXUUfTq1YvWrVtjZvz973/nP//5\nD5s2bWpQXVavXg0ErZjxiouLY1odoyZMmMDpp59O69atOfroo9l1110pLS2lRYsWTJkyhRkzZjS4\nPvH16tGjR8Lt0fJVq1bV2NaxY8caZdHQ2dCW2HRSYMwn8YFx+XLYuhWS/CYlIiKZ4Z7rGuTGyJEj\nufbaa3nkkUe45ZZbmDFjBp9++imDBw+OebJKZWUlN9xwAzvssANvv/12jWA3Y8aMRtWjQ4cOAHz9\n9dfsvPPOMds2b97MypUrawSwa665hu222445c+awxx57xGxbvHhxo+sUrteSJUsSbv/qq69i9ssn\nShr5pKQE2rWrXq+qin22tIiISAZ1796dk046aVs/vGh/xmhfu6ivv/6atWvX0q9fvxphcc2aNQlv\nydbHgQceCMD06dNrbHvllVfYunVrjfIFCxawzz771AiLVVVVzJw5s8b+0dva9WndO+CAA4AgECc6\nburUqTH1zycKjPlGt6VFRCSHoreex44dyz/+8Q+6dOnC97///Zh9evToQUlJCbNmzWLdunXbyjdv\n3szFF1/c6D55I0eOBODGG2+Mub27YcMGrrrqqoTH9OrVi/nz58e0/rk71157bcK5Dlu0aEFZWRmL\nFi1KuV7l5eUMGjSIBQsWcPfdd8dsmzlzJn/5y1/o3LlzzOCgfKFb0vmma1f49NPq9W++gb59c1cf\nERFpVoYOHUp5efm2kbsXXXQRxcXFMfu0bNmSiy++mNtvv519992Xk046iU2bNjFlyhRWr17NgAED\nErYOpqp///6cf/753Hfffey999784Ac/oFWrVjz99NN07dqVbt261Tjmsssu46KLLmL//fdn+PDh\ntGrVihkzZvDRRx9xwgkn8Nxzz9U4ZsiQITz11FMMGzaMAw44gFatWjFw4ED69euXtG5/+MMf6Nev\nH5dddhkTJ07koIMOYtGiRUyYMIFWrVoxfvx4SktLG/zec0UtjPlGLYwiIpJD8U83iR/sEnXLLbcw\nZswYSkpK+MMf/sDTTz/NoYceyqxZs+jZs2ej63HPPfdwxx130L59e+6//36efPJJjjvuOCZNmlRj\ntDbAhRdeyIMPPkj37t15+OGHefzxxykvL+fNN9/kO9/5TsJr3H333Zx++um8/vrr3HjjjVxzzTVM\nmzat1nrtvvvuzJkzh5/+9KfMmzeP22+/nRdeeIHjjz+emTNncsIJJzT6veeCeXPtuZtmFRUVPnv2\n7Mxf6JxzIDL/FAD33w8//WmzhJNRAAAgAElEQVTmrysi0gzNmzePPffcM9fVEElZqt9ZM5vj7jXn\n8klCLYz5Ri2MIiIikmUKjPlGgVFERESyTIEx3ygwioiISJYpMOYbBUYRERHJMgXGfKPAKCIiIlmm\nwJhvFBhFREQkyxQY802iwKipkURERCSDFBjzTWkptG5dvV5ZCWvW5K4+IiIFTvMVS77I5HdVgTEf\n6ba0iEhWtGzZksrKylxXQyQllZWVtGzZMiPnVmDMRwqMIiJZ0a5dO9boLo7kiTVr1tCuXbuMnFuB\nMR8pMIqIZEWnTp1YuXIly5YtY/Pmzbo9LU2Ou7N582aWLVvGypUr6dSpU0au0yojZ5XMUmAUEcmK\nkpISdt55Z1asWMHChQupqqrKdZVEamjZsiXt2rVj5513pqSkJCPXUGDMRwqMIiJZU1JSQo8ePejR\no0euqyKSM7olnY8UGEVERCSLFBjzkQKjiIiIZJECYz5SYBQREZEsUmDMRwqMIiIikkUKjPlIgVFE\nRESySIExH8UHxmXLclMPERERaRYUGPNR+/ZQVFS9vn598BIRERHJAAXGfGSm29IiIiKSNQqM+UqB\nUURERLJEgTFfKTCKiIhIligw5isFRhEREckSBcZ8pcAoIiIiWaLAmK8UGEVERCRLFBjzlQKjiIiI\nZIkCY75SYBQREZEsUWDMVwqMIiIikiUKjPlKgVFERESyRIExXykwioiISJYoMOarsjJo2bJ6fc0a\n2LQpd/URERGRgqXAmK9atIDOnWPLli3LTV1ERESkoCkw5rMuXWLXdVtaREREMkCBMZ+pH6OIiIhk\ngQJjPlNgFBERkSxQYMxnCowiIiKSBQqM+UyBUURERLJAgTGfKTCKiIhIFigw5jMFRhEREckCBcZ8\npsAoIiIiWaDAmM8UGEVERCQLFBjzmQKjiIiIZIECYz6LfzTgihWwZUtu6iIiIiIFS4ExnxUVQVlZ\nbNny5bmpi4iIiBQsBcZ8p9vSIiIikmEKjPlOgVFEREQyTIEx3ykwioiISIYpMOY7BUYRERHJsCYT\nGM2sp5k9ZGZfmtkmM1toZneYWVndR4OZlZrZCDP7s5l9aGbrzGytmc02s1FmVlzLsXuZ2V/NbKmZ\nbTSz+WZ2g5m1Tt87zBAFRhEREcmwVrmuAICZ9QZeA7oB/wQ+BA4BLgGONbMj3L2u4b9HAo8BK4Cp\nwNNAGXAScDtwipkNcfeNcdc+FJgCFAFPAYuBwcC1wJDIMZvS8kYzQYFRREREMqxJBEbgXoKw+HN3\nvztaaGa/BS4DbgJ+Vsc5lgBnABPcfXPoHKOBacDhwIXA2NC2lsDDQBtgmLs/EylvAfwVGB65/q2N\ne3sZpMAoIiIiGZbzW9KR1sWhwELg93GbrwPWAWeaWWlt53H3d9z98XBYjJSvpTokDow7bACwJ/BK\nNCxGjtkK/CKy+jMzs5TfULYpMIqIiEiG5TwwAoMiy0mRoLZNJOzNJGgBPKwR16iMLOMfgzI4snwh\n/gB3/xT4COgF7NqIa2eWAqOIiIhkWFMIjHtElh8l2f5xZNmnEdc4J7KMD4bZuHZmKTCKiIhIhjWF\nwNghslydZHu0vGNDTm5mFwHHAu8AD2Xz2lkRHxiXL4etWxPvKyIiItIATSEwZoyZnQLcQTAgZri7\nV9ZxSH3Pf15k2p7Z3+SqZa+kBNq1q16vqoKVK3NTFxERESlITSEwRlvxOiTZHi1fVZ+TmtnJwJPA\nUmBgpE9iWq/t7n909wp3r+ga39KXTbotLSIiIhnUFALj/MgyWT/B3SPLZP0MazCzU4EJwNfAAHef\nn2TXtF87JxQYRUREJIOaQmCcGlkOjcx/uI2ZtQOOANYDb6RyMjMbATwBfEkQFj+uZfcpkeWxCc6z\nK0GQ/C+QqHWy6VBgFBERkQzKeWB09wXAJKCcYGLtsBuAUuBRd18XLTSzvmbWN/5cZnYW8AiwCOif\n5DZ02HRgHtDfzE4KnacFcFtk9X5393q9qWxTYBQREZEMaipPermA4NGAd5nZEIIQdyjBHI0fAb+K\n239eZLltQm0zG0QwCroFQavlyATzba9y9zuiK+5eZWYjCVoanzKzpwjC5hCggmAOyN+l4w1mlAKj\niIiIZFCTCIzuvsDMKoBfE9wePg74CrgTuMHdUxn224vqFtNzkuzzX4JR0+Frv2lmBxO0Zg4F2kX2\n+zVwa5N+jnSUAqOIiIhkUJMIjADuvhgYmeK+NZoO3X08ML6B1/4AOLUhxzYJCowiIiKSQTnvwyhp\noMAoIiIiGaTAWAgUGEVERCSDFBgLgQKjiIiIZJACYyGID4zLlkETnwlIRERE8ocCYyEoLYXWravX\nN2+GtWtzVx8REREpKAqMhUK3pUVERCRDFBgLhQKjiIiIZIgCY6FQYBQREZEMUWAsFAqMIiIikiEK\njIVCgVFEREQyRIGxUCgwioiISIYoMBYKBUYRERHJEAXGQqHAKCIiIhmiwFgoFBhFREQkQxQYC4UC\no4iIiGSIAmOhUGAUERGRDFFgLBTt20NRUfX6+vXBS0RERKSRFBgLhZlaGUVERCQjFBgLiQKjiIiI\nZIACYyFRYBQREZEMUGAsJAqMIiIikgEKjIVEgVFEREQyQIGxkCgwioiISAYoMBaSLl1i1xUYRURE\nJA0UGAuJWhhFREQkAxQYC4kCo4iIiGSAAmMhUWAUERGRDFBgLCQKjCIiIpIBCoyFpFMnaBH6ka5Z\nA5s25a4+IiIiUhAUGAtJixbQuXNs2bJluamLiIiIFAwFxkKj29IiIiKSZgqMhUaBUURERNJMgbHQ\nKDCKiIhImikwFhoFRhEREUkzBcZCo8AoIiIiaabAWGgUGEVERCTNFBgLjQKjiIiIpJkCY6FRYBQR\nEZE0U2AsNAqMIiIikmYKjIVGgVFERETSTIGx0MQ/GnDFCtiyJTd1ERERkYKgwFhoioqgrCy2bPny\n3NRFRERECoICYyHSbWkRERFJIwXGQqTAKCIiImmkwFiIFBhFREQkjRQYC5ECo4iIiKSRAmMhUmAU\nERGRNFJgLEQKjCIiIpJGCoyFSIFRRERE0kiBsRApMIqIiEgaKTAWIgVGERERSSMFxkKkwCgiIiJp\npMBYiOID4/LlsHVrbuoiIiIieU+BsRCVlEC7dtXrVVWwalXu6iMiIiJ5TYGxUOm2tIiIiKSJAmOh\nUmAUERGRNFFgLFQKjCIiIpImCoyFSoFRRERE0kSBsVApMIqIiEiaKDAWKgVGERERSRMFxkKlwCgi\nIiJposBYqBQYRUREJE0UGAuVAqOIiIikSZMJjGbW08weMrMvzWyTmS00szvMrKwe5zjazMaa2WQz\nW25mbmav1nFMSzMbYWYzzGyJma03s4/M7GEz27vx7yxHFBhFREQkTVrlugIAZtYbeA3oBvwT+BA4\nBLgEONbMjnD35Smc6kJgGLAR+ATolMIxfwZOAz4H/g6sBfYFzgL+x8y+5+5T6veOmoBEgdEdzHJT\nHxEREclbTaWF8V6CsPhzdz/Z3X/p7oOB3wF7ADeleJ7bgH2AtsCJde1sZgcThMX3gT3c/QJ3/3/u\nfhzwY6AYuLre76YpKC2F1q2r1zdvhrVrc1cfERERyVs5D4yR1sWhwELg93GbrwPWAWeaWWld53L3\n1939fXevSvHyu0aWk919fdy2f0aWcU11eUS3pUVERCQNch4YgUGR5SR33xre4O5rgZlAG+CwDFz7\n/chysJm1jtt2QmT5cgaumx0KjCIiIpIGTSEw7hFZfpRk+8eRZZ90X9jd3yO47b0P8KGZ/d7MbjWz\nZ4EHgSfJ11vSoMAoIiIiadEUBr10iCxXJ9keLe+YiYu7++VmNp8gOF4Q2jQH+JO7r0t2rJmdB5wH\nsPPOO2eieo2jwCgiIiJp0BRaGHPGAncR9J38NbAT0A44EnBgopldmOx4d/+ju1e4e0XX+HDWFCgw\nioiISBo0hcAYbUHskGR7tHxVBq59FnAxcJe73+run7v7t+7+KsEo6w3ArWbWNgPXzjwFRhEREUmD\nphAY50eWyfoo7h5ZJuvj2BjRgS1T4ze4+xKC+SDbUt3PMr8oMIqIiEgaNIXAGA1rQ80spj5m1g44\nAlgPvJGBa5dElsnuJ0fLN2fg2pmnwCgiIiJpkPPA6O4LgElAOcGTWsJuAEqBR8ODT8ysr5n1TcPl\nZ0SWl5tZzC1xM/sZ0BNYAnyQhmtlnwKjiIiIpEFTGCUNwejk14C7zGwIMA84lGCOxo+AX8XtPy+y\njHnOnZn1A86NrEb7He5uZuOj+7j72aFD7gVGAPsBH5nZMwR9JQ8EBgNVwIX1mAi8aVFgFBERkTRo\nEoHR3ReYWQXBSOVjgeOAr4A7gRvcfWWKp9qNYCBLWLe4srND1/3WzI4ALgdOAf6H4HGA3wATgNvd\n/a16v6GmokuX2HUFRhEREWkAc/dc16EgVFRU+OzZs3NdjVjuUFIClZXVZevWQZs2uauTiIiI5JyZ\nzXH3ilT3z3kfRskgM7UyioiISKMpMBY69WMUERGRRlJgLHQKjCIiItJICoyFToFRREREGkmBsdAp\nMIqIiEgjKTAWOgVGERERaSQFxkKnwCgiIiKNpMBY6BQYRUREpJEUGAudAqOIiIg0kgJjoVNgFBER\nkUZSYCx0CowiIiLSSAqMha5TJ2gR+jGvWQObNuWuPiIiIpJ3FBgLXYsW0LlzbNmyZbmpi4iIiOQl\nBcbmQLelRUREpBEUGJsDBUYRERFpBAXG5kCBUURERBpBgbE5UGAUERGRRlBgbA4UGEVERKQRFBib\nAwVGERERaQQFxuZAgVFEREQaQYGxOVBgFBERkUZQYGwOFBhFRESkERQYmwMFRhEREWkEBcbmIP7R\ngCtWwJYtuamLiIiI5B0FxuagqAjKymLLli/PTV1EREQk7ygwNhfxt6WXLctNPURERCTvKDA2F+rH\nKCIiIg2kwNhcKDCKiIhIAykwNhcKjCIiItJACozNhQKjiIiINJACY3OhwCgiIiINpMDYXCgwioiI\nSAMpMDYX8YHx669zUw8RERHJOwqMzcWOO8auz5wJixblpi4iIiKSVxQYm4s994Tdd69e37IFbr89\nd/URERGRvKHA2Fy0aAH/7//Flo0bB0uX5qY+IiIikjcUGJuTM8+Enj2r1zdsgDvvzF19REREJC8o\nMDYnxcUwenRs2T33wOrVuamPiIiI5AUFxjyzZUsjT3DuudC5c/X6mjVw772NPKmIiIgUMgXGJs4d\n/v1vuO02GDAAvvOdRp6wtBQuvTS27He/g/XrG3liERERKVQKjE3cunVQUQG//CW88gp88AF88kkj\nT3rhhdCuXfX6N9/AQw818qQiIiJSqBQYm7i2baF//9iyiRMbedKyMrjggtiyMWNg8+ZGnlhEREQK\nkQJjHjjuuNj1f/0rDSe99FIoKaleX7wY/vznNJxYRERECo0CYx6ID4zTpqWhy+H228OPfxxbduut\nUFXVyBOLiIhIoVFgzAN77AHl5dXrGzcGobHRrrgCWrasXp8/H55+Og0nFhERkUKiwJgHzDJ0W7q8\nHEaMiC27+eZgaLaIiIhIhAJjnogPjM8/n6ZcF/+4wLffhkmT0nBiERERKRQKjHli0KDYMSoLFwZ3\nkBttr73g+9+PLbv55jScWERERApFWgOjmZWZWWk6zymBNm1g4MDYskZPrxN15ZWx66+8AjNnpunk\nIiIiku/qHRjNbIiZjTGzslBZNzObDiwDVpjZb9NZSQlkpB8jwMEHw9FHx5bdckuaTi4iIiL5riEt\njBcDp7j7ylDZ7cCRwAJgOXCJmZ2WhvpJSHxgnD4dvv02TSePb2V8/nl45500nVxERETyWUMC43eA\nV6MrZtYa+AHwkrv3AfYAFgM/S0sNZZvddoPdd69er6yEyZPTdPKBA+Gww2LLbr01TScXERGRfNaQ\nwNgN+DK0fiiwHTAewN3XAs8RBEdJs4zdljaDq66KLZswAT7+OE0XEBERkXzVkMC4CWgdWj8ScOCV\nUNkaoFMj6iVJfO97sesTJ6Zx2sTjj4d9961e37o1eMa0iIiINGsNCYyfAYND68OBj939i1DZTgQD\nYCTNBgyA1qG4vngxvP9+mk7eogX88pexZX/6E3z+eZouICIiIvmoIYHxT8C+Zvammc0A9gX+HLfP\nfkA6ZgmUONttB0OGxJal7bY0wGmnwa67Vq9XVsLYsWm8gIiIiOSbhgTG+4AngQrgCIL+irdFN5rZ\nPgQhcloa6icJZKwfI0CrVjWf/vLHP8IyNRiLiIg0V/UOjO5e6e7/A5QBHdx9mLtvCu2yBDgAuDtN\ndZQ48f0YX30VVq9O4wXOOgt69KheX78e7rorjRcQERGRfNLgJ724+5rIiOj48mXu/q67pzPCSEh5\nOey5Z/V6VRW8/HIaL1BSAqNGxZbdfTesWZPGi4iIiEi+aMiTXsrMbC8zK4krH2lm/zSzP5vZIemr\noiSS0dvSAD/9KZSVVa+vWgX335/mi4iIiEg+aEgL483Am+FjzexiYBxwInA6MM3M9kpLDSWhRIEx\nbdPrALRtC5dcElv229/Cxo1pvIiIiIjkg4YExiOAye6+IVQ2GvgC6A9EHwl4eSPrJrXo1y/IdFFL\nlmTgSX4XXwylpdXrX38NDz+c5ouIiIhIU9eQwLgjwVyMAERaEncC7nb3V939KeBZgvCYMjPraWYP\nmdmXZrbJzBaa2R1mVlb30dvOcbSZjTWzyWa23MzczF6t+0gwsx+Y2YtmtszMNprZosgt9sPqPjr7\niovh6KNjy9J+W7pTJ/hZ3BMex4wJptoRERGRZqMhgbE1EL4veQTBk17Cwy4WEATLlJhZb2AOMBJ4\nC/gd8ClwCfC6mXVO8VQXErRsHk7s4wtru3YrM3scmADsAvwF+C3B++kDHJTq+8i2RE99SbvLLw/S\nadTChfDkkxm4kIiIiDRVDQmMXwB9Q+vHEDwK8N1QWRkQvmVdl3sJnlH9c3c/2d1/6e6DCYLjHsBN\nKZ7nNmAfoC1Bf8pU3AD8T+Qafd39Qne/yt3Pcfc9gT/W431kVXxgfP11WLEizRfZYQcYOTK27NZb\ng8cGioiISLPQkMA4FTjOzC4ys3OBk4AX3D2cIHoDi1M5WaR1cSiwEPh93ObrgHXAmWZWSh3c/XV3\nf9/dq1K89vYE/S/fcPer495D9JxN9v5rz56w337V61u3wqRJGbjQL34RPDYw6oMP4JlnMnAhERER\naYoaEhhvAb4F7iRofdsIXB/daGbtgX7Aaymeb1BkOSk+sEXmeZwJtAEy0ZfwB0Ax8KSZtY70Y/yl\nmV1oZt/JwPXSLuPT60DwqMDTT48tu/nmNA/LFhERkaaqIU96+QzYm6B/4c+Bfdw9/Nzo3YA/AONT\nPOUekeVHSbZ/HFn2qV9NU3JwZNkG+JCgH+MtwD3AO2b2lJm1ycB10yY+ML7wQobuFv/yl7Hrs2bB\n5MkZuJCIiIg0NQ160ou7L3H3eyKvRXHb3nb3y9x9Voqn6xBZJnsyTLS8Y0PqWodukeWNBLfEDyTo\n/3gYMBsYTtC/ssn67nehQ4fq9W++gTlzMnChffeFk06KLbv55gxcSERERJqaBj8aEMDMisxsXzM7\n0sz2M7OidFUsS6LvfwVworvPdfd17v4mQd/Mbwn6TyYc8W1m55nZbDOb/c0332SpyrFatYKhQ2PL\nMnJbGuDKK2PXp06F6dMzdDERERFpKhoUGM2svZndD6wC3gGmAXOBVWZ2v5nVpzUw2oLYIcn2aPmq\nhtS1DtFzTnb3mAclu/tXVD/RpiLRwe7+R3evcPeKrl27ZqB6qclKP0aAww6DQYNiy0aN0ohpERGR\nAteQZ0m3JxiIch6wBZgB/DWyrIyUvxrZLxXR/o/J+ijuHlkm6+PYGNFrJwujKyPL1hm4dtoce2zs\n+qxZsHRphi52442x63PmwBNPZOhiIiIi0hQ0pIXxSoJBL/cBvdx9oLv/yN0HAr0IpsbZK7JfKqZG\nlkPNLKY+ZtaOYGLw9cAbDahrXaKTje+TZPvekeVnSbY3CdtvDweFphd3hxdfzNDFjjgChg+PLbvy\nSthQn2k3RUREJJ80JDCeQjBv4YXuHtMy5+6r3f1i4HWCASN1cvcFwCSgnOBJLWE3AKXAo+6+Llpo\nZn3NrC+NN4Pglno/M/t+eIOZ/QTYE/iEYABMk5aVp75E3XYbFIW6qy5eDHfckcELioiISC6Z13Mu\nPTPbCPzW3a+qZZ+bgcvcPaVbuZHJu18jGLX8T2AecCjBHI0fAYe7+/LQ/g7g7hZ3nn7AuZHVtgSh\ndSmwLT65+9lxx+wHTCfoK/ls5Hp7A98jmDR8qLvXOadkRUWFz56du1z5+utw+OHV62VlwYjpli0z\ndMHLL4ff/a56vV07+OQT6NYt+TEiIiLSJJjZHHdPOEYjkYa0MK6jejqaZLoS3EZOSaSVsYJg7sZD\ngVEET4u5EzgsHBbrsBtwVuQVbeHsFio7K8G1/00wnc4jBPMyXgocADwOHJRKWGwKDjkEOnWqXl+5\nEt58M4MXvPrqIJVGrV0L112XwQuKiIhIrjQkMM4CTjWz3RNtjLQWnhbZL2XuvtjdR7p7D3cvdvde\n7n6pu69MsK/Fty5GysdHtyV7Jbn2Z+5+trvv4O5FkTqcETcheZPWsmXNwS8ZGy0NQTq99trYsgce\nCB4bKCIiIgWlIYHxNwS3e2eZ2Y1mNtjM9jSzQWZ2A0FQbAvcns6KSt3i+zFmNDACXHAB9O5dvV5V\nFTx3WkRERApKQx4NOBm4ANgOuAp4CXiPYMTxNQSDVC5y95eTnkQy4phjwEJtqHPnwldfZfCCxcXB\nAJiw55/XIwNFREQKTEMfDfgHgnkTrwX+AUyJLK8B+rj7fWmroaSsa9egL2PYCy9k+KKnnAL9+sWW\njRoVtDaKiIhIQWjwowHdfZG73+TuP3D3oyPLm9z9v2a2XT0m7pY0ytpTX6LMYOzY2LJ334VHHsnw\nhUVERCRbGvUs6VrcR/B8Zsmy+MA4aRJUVmb4ooccAj/6UWzZ1VfDunWJ9xcREZG8kqnACJBwRLJk\n1oEHxk6FuGYNvJaNiYFuvhlKSqrXv/yyZsujiIiI5KVMBkbJgRYtak6vk9GnvkSVl8Mll8SWjRmT\n4VE3IiIikg0KjAUo6/0Yo666Crp0qV5ftw6uuSZLFxcREZFMUWAsQEOHBi2NUf/5T/C454zr0AGu\nvz627KGH4N//zsLFRUREJFMUGAtQWVnsc6UhS7elAc47D/bYo3rdHa64IksXFxERkUxQYCxQWX/q\nS1RREfzmN7FlkyZlYUJIERERyZSUAqOZVdXnBfxvhustdYjvxzh5MmzalKWLn3ACDBoUWzZ6NGzZ\nkqUKiIiISDql2sJoDXhJDn3nO9CjR/X6t9/Cq69m6eJmcPvtsc8pfP/9oD+jiIiI5J2UAqO7t2jA\nq2WmKy/JmeVwtDQEE0KeeWZs2TXXwNq1WayEiIiIpIP6MBawnAZGgJtugtatq9eXLg3mZhQREZG8\nosBYwI46Clq1ql7/8EP47LMsVqBnTxg1KrZs7Fj4/PMsVkJEREQaS4GxgLVvD/36xZZlbXqdqF/8\nArp3r17fsAF+9assV0JEREQaQ4GxwOX8tnS7dnDjjbFljzwCb7+d5YqIiIhIQykwFrj4wDhlStDI\nl1UjR8Lee8eWjRoVTOotIiIiTZ4CY4Hbay/Yeefq9Q0bYPr0LFeiVatgmp2wadPg2WezXBERERFp\nCAXGAmeWw6e+hB17bPCQ67Bf/AIqK3NQGREREakPBcZmIP62dNYHvkTdfju0CH3l5s+HP/4xR5UR\nERGRVCkwNgODB0NxcfX6J5/Axx/noCL77gvnnBNbdv31sHp1DiojIiIiqVJgbAbatoUBA2LLcnJb\nGuDXv4bS0ur1ZcvgkEPgn//UIBgREZEmSoGxmYjvx/jcc7mpBz16BH0Xwz76CE4+GQYNgtmzc1Mv\nERERSUqBsZk4/vjY9alT4ZtvclMXRo2CffapWT59Ohx8cPAM6kWLsl8vERERSUiBsZno0yfoQhhV\nVQV//3uOKlNaGiTWn/wkdhBM1GOPwR57wFVXwZo12a+fiIiIxFBgbEZOOy12/a9/zU09AOjSJRgh\n/c47wZQ78TZuhFtugd12g/vugy1bsl9HERERARQYm5X4wDhtGnz9dU6qUm3ffYN5fl58MbYJNOqb\nb+CCC4Jtzz2ngTEiIiI5oMDYjPTpA/vvX72+dSv87W+5q0+MoUNh7lx48MFgYEy8Dz+EE0+EIUOC\n/URERCRrFBibmR/+MHb9L3/JTT0SatkymKfxo4+C+RnbtKm5z9SpcNBBcNZZsHhx1qsoIiLSHCkw\nNjPxt6VnzIAvv8xNXZJq2xauuy6YXfzHPw6ebxjmDo88EjSZXn01rF2bm3qKiIg0EwqMzcyuu0JF\nRfW6Ozz1VO7qU6sddoBx44KBMUcfXXP7xo1w003BwJgm1VQqIiJSWBQYm6H4VsYmn7X22w8mTQoG\nx+y9d83tS5fC6afDQw9lv24iIiLNgAJjMxQfGF97LU+6Ax57bNDa+MADsP32Nbefey488UT26yUi\nIlLgFBiboV694LDDYssmTMhNXeqtVasgGH78MVx7LRQVVW9zD54S8/TTuaufiIhIAVJgbKaa1CTe\nDdG2LdxwQ1Dxli2ry6uqgqHgL76Yu7qJiIgUGAXGZurUU2PX33wTFi7MSVUa5+ST4dFHY0dSb94c\nlE+blrNqiYiIFBIFxmaqZ0844ojYsry5LR3vRz8KRlOHbdwIJ5wAb7yRmzqJiIgUEAXGZqxJT+Jd\nX+ecA/fcE1u2bl0wUObtt3NTJxERkQKhwNiMDR8eeyd3zhz45JPc1afRLrwQxoyJLVu9Onjs4Pvv\n56ZOIiIiBUCBsRnbYQfo3z+2LG9vS0ddcUXwlJiw5cvhqKOCkdUiIiJSbwqMzVzeTeKdiuuuC4Jj\n2JIlMGQI/Pe/uamTiHIQFDwAACAASURBVIhIHlNgbOaGD4cWoW/Bu+/C/Pm5q09amMFttwW3qMMW\nL4bBg+GLL3JTLxERkTylwNjMde8OAwfGluXdnIyJmMFdd8HIkbHln34a3J5eujQ39RIREclDCoxS\nY7R0QQRGCJpOH3ggeM502IcfBgNhVqzITb1ERETyjAKjcMopsQ9Lee89+OCD3NUnrVq2hEcegWHD\nYsvffTeYcmfNmtzUS0REJI8oMApdugTjQcIKYvBLVFFR8IaOOSa2fNasYHLvdetyUy8REZE8ocAo\nQOLb0u65qUtGlJTA3/9ecx6hGTOCxwhu3JibeomIiOQBBUYBgszUqlX1+ocfwn/+k7v6ZESbNvDc\nc3DoobHlL78czC9UWZmbeomIiDRxCowCQKdOwTiQsIIZ/BLWrh288ALsv39s+bPPwogRsHlzbuol\nIiLShCkwyjaJJvEuqNvSUR07wqRJsNdeseUTJgRlf/tbgb5xERGRhlFglG2GDYPi4ur1Tz6Bd97J\nXX0yqmvX4Fb0brvFli9YAD/4AfTrB2+8kZu6iYiINDEKjLJNx441BxIX1GjpeD16wOTJUF5ec9tr\nr8F3vxuMBvrss6xXTUREpClRYJQY8aOlC/a2dNTOOwfT65x/fuxklFF//Sv07QujR8PKldmvn4iI\nSBOgwCgxTjopmIEmauFCmD07Z9XJji5d4N57g2HhJ55Yc/vmzTB2LPTuDXfcoYExIiLS7CgwSox2\n7eC442LLCvq2dNiee8Izz8CUKXDggTW3r1wJl12mgTEiItLsKDBKDQU/iXddBg0KblM/+ijstFPN\n7RoYIyIizYwCo9Rw/PHQunX1+uLFzTAXtWgBZ5wB8+fDzTcHTa/xwgNjPv00+3UUERHJEgVGqaFt\n2+ARy2EFOYl3Klq3hiuvDOYYqmtgzKhRGhgjIiIFSYFREoqfxHvCBNi6NTd1aRK6dat9YExlJfz2\nt8HAmAcfzH79REREMkiBURI67jgoLa1e/+ILmDkzd/VpMlIZGHPuuXDxxbBlS/brJyIikgEKjJLQ\n/2/vvsOkqLI+jn/vkAVBEQkqAiqKioKAoqAoEkyIBMOawbzm+Lq7JjDsursGFuOyBswJFQQTICgC\nIpJFEQWJkrPkdN8/TrfTeaZnOs3M7/M8/fTUreqq20XpnLnh3D32iG5IK7Pd0rEUNDHm6aetX3/9\n+szXTUREJMVyJmB0zh3gnHvJObfEObfNOTffOdfPObd3Eufo5Jx73Dn3hXNutXPOO+fGJlmPewOf\n8865jsl/k9Ijcrb0oEGwa1d26pKTQifG/OMf4U2yAJ9/bpNi5s7NTv1ERERSJCcCRufcwcBkoDcw\nEXgS+BW4BfjGObdPIU91A3A70AZYUoR6tADuBzYm+9nS6PTTwycHL1sGX3+dvfrkrCpV4C9/sT77\nyNbGWbOgdWsYMyY7dRMREUmBnAgYgWeB2sDN3vtu3vu/eO9PxQLHw4BHCnmefwJNgWpAjJkJ8Tnn\nKgOvAd8BHybz2dKqcmU455zwsjKTxLsomjWDiRMtQAy1ejV07Agvv5ydeomIiBRT1gPGQOtiZ2A+\n8EzE7geATcClzrmI/r5o3vtvvPc/eO+L0nH6D6AR0Asoy/OBw0R2S7//vuZyJFS3LoweDRdeGF6+\nYwdccQXcfXcZn24uIiIlUdYDRqB94H249z7sN6n3/ndgHLAHcHy6KuCcOxXr/v6r9/6XdF2nJOrU\nCWrUyN9euRK+/DJr1SkZqlSBN96Avn2j9/3rX9CjB2zUqAcRESk5ciFgPCzw/nOc/cEA7tB0XNw5\nVwMYCHwN9E/HNUqySpWge/fwMnVLF4JzcP/9drMqVw7fN2SILSu4aFF26iYiIpKkXAgYg+1X8fKP\nBMv3StP1nwJqAr29T27FZOfcNc65Sc65SStXrkxP7XJAZBLvDz6wHlYphPPPh6++sq7qUNOnw3HH\n2ZhHERGRHJcLAWPWOOd6ApcC/+e9T3oxYO/9AO99K+99q3333Tf1FcwRHTvC3iHJjdasgS++yF59\nSpxgYNi8eXj5smVw8snw9tvZqZeIiEgh5ULAGGxBrBFnf7B8XSov6pyrCTwPfAE8l8pzlzYVKtiw\nu1BK4p2k+vUtJ1G3buHlW7faBJk+fSC5Bm4REZGMyYWAcXbgPd4YxcaB93hjHIvqQKAW0AHYHZKs\n2wOXB44ZESi7NcXXLnEiZ0t/+CFs356dupRY1arZNPO7747e17cvXHQRbNmS+XqJiIgUoHy2KwCM\nDrx3ds7lhc6Uds7tCbQFNgMTUnzd1cCLcfa1wwLVT7EE4DNTfO0Sp317qFULVq2y7XXrYMQIOOus\n7NarxMnLg0cfhSZN4JprwgeDvv02zJsHgwdHj3kUERHJoqy3MHrv5wLDgYbYSi2h+gJVgde895uC\nhc65Js65JsW87iLv/VWxXsD4wGFPBMpGFudapUH58tCzZ3iZZksXQ69eNhB0n4hFjL791sY8Tp+e\nlWqJiIjEkvWAMeB6YAXQ3zk32Dn3D+fcKOA2rCv6nojjZwVeYZxzJzrnBjrnBgKPBYobB8sC5VJE\nkd3SgwfD2rXZqUupcNJJNhnm8MPDyxctgjZt4K67YEnSK1yKiIikXE4EjIFWxlZYPsTWwB3AwcB/\ngOO996sLeapDsPGHlwPB9rDaIWWXx/mcFEK7dlCnTv7277/DqadaMm8pooMOgm++gdNOCy/fvBke\newwaNYKrroLZs2N/XkREJANyImCEP7qIe3vv63nvK3rvG3jvb/XeR7Vhee+d997FKB8Y3BfvVci6\n9AocX+a7okOVK2c9qaGmTYNTToGlS7NRo1KiRg0YNgxuuil63/bt8OKL1grZs6fyNoqISFbkTMAo\nJcN999kiJaF+/NF6VxcsyE6dSoXy5aF/fwsOa9eO3u+9ZUxv3dqadT//XGl4REQkYxQwSlKqVoXP\nPrNk3qHmzrWgcc6c7NSr1LjiCpg/H557zrqrYxk9Gk4/HVq0sJnVO3dmtIoiIlL2KGCUpFWtCkOH\nwtlnh5cvWmRB4w8/ZKdepUaVKnDddTZu8e23o1eICZo2zZJ+H3aYBZjK4SgiImmigFGKpHJly0Ed\nuc50cLW7qVOzU69SpXx5m5o+ZYp1QbdvH/u4X3+F66+Hhg3h73+3JJkiIiIppIBRiqxCBXjzzeiJ\nMKtXW2zzzTdZqVbp4xx07gyjRtmkl549rSzSihVwzz22DKFS8oiISAopYJRiKVfO5mlcf314+fr1\n0KkTfPllVqpVeh17LAwaBLNmWbqdihWjj9m40VLyNGwIXbpYd/XChRmvqoiIlB7Oa6ZlSrRq1cpP\nmjQp29XIGu/h//7P4pRQlSvbutOnn56depV6S5ZAv37w/POWGDORpk1tLcezzoITTrAubxERKZOc\nc5O9960KfbwCxtQo6wEjWND44IPQp094eYUKtoxg9+5ZqVbZsG6dtST262dd0wXZe29LFn7WWRbN\n16qV/jqKiEjOUMCYJQoY8z32mA2hC1WuHLz6Klx0UXbqVGZs2QKvvAKPP174HEd5eZbfMdj62KxZ\n7DGSIiJSaihgzBIFjOGefRZuuCG8zDkYMMCG3kmaeQ8zZ8LHH9tr/HjYvbtwn91///zgsUMHy6Mk\nIiKligLGLFHAGG3gQLjyyug45T//gZtvzkqVyq41ayw1z8cfw6ef2nZhVKoEZ54JDz8MRxyR3jqK\niEjGJBswapa0pE2vXpZ2J3JuxS23wD/+kZUqlV01a1qS79dftzGO48bB3/5m3c+JbNtms5aOPhpu\nvVU5HkVEyii1MKaIWhjjGzoUzj0Xtm8PL7/nHnjoIQ2Xy7pFi+CTT+w1ciRs3hz/2Fq1LDn4FVfY\nwFQRESmR1CWdJQoYExsxAs45J3r1ultvhSeeUNCYM7ZuteSZwbGP8+bFPq5FC+jfH9q2zWj1REQk\nNdQlLTmpUycbQrfnnuHl/fpZS6PkiMqVLc3OU0/B3Lm2/mODBtHHTZkCJ54Il1wCv/2W+XqKiEhG\nKWCUjDnpJPjiC0sBGOof/4D33stOnSQB56BHD1tV5sEHoUqV6GPeeAMOO8z+EbduzXwdRUQkIxQw\nSkYde6z1eO67b3h5r14wY0Y2aiQFqlIF7rsPfvoJLrggev+mTTaBpmlT+OgjS+kjIiKligJGybij\nj4YhQ2wFmKDNm6Fbt8Jne5EsOPBAePtti/iPPjp6/9y5NlD1jDMsuBQRkVJDAaNkxQknwDPPhJfN\nm2eZX3btyk6dpJBOPhkmT7bs7DVrRu///HM46ii44w5Yvz7z9RMRkZRTwChZc/XVcO214WXDh1vv\npuS48uXhz3+GX36xJX3yIv5XsnOnTX8/9FB46aXCrzIjIiI5SQGjZFX//tCmTXjZv/4F77yTnfpI\nkmrWhKefhqlT4ZRTovevWGHL/bRuDV99lfHqiYhIaihglKyqWBEGDYL99gsvv+IKmD49O3WSIjj6\naBg1yqa7H3hg9P5JkyygPOUUGD1aE2NEREoYBYySdfXqwQcfWPAYFJwEs3p19uolSXLOlvSZNQse\neMByOkb66is49VQbB/nFFwocRURKCAWMkhNat7Y5FKHmz4c//cmGw0kJssce0KePzZQ+99zYx3z9\nNXTsaMk5hw9X4CgikuMUMErOuPJKm0cRauRI+Otfs1MfKaYGDayLeuxYW+onlnHj4LTTbCDrZ58p\ncBQRyVEKGCWn9OtnK86FeuwxeOut7NRHUqBtW2tFHD/egsNYJkyw/I3HHw+ffKLAUUQkxyhglJxS\nsaI1Su2/f3j5lVfCtGnZqZOkyAknWCtiMDiMZeJEOOssOO44GDpUgaOISI5QwCg5p25dmwRTqVJ+\n2ZYtNglm1ars1UtSpHVra0WcOBG6dIl9zKRJ0LUrtGplywIpcBQRySoFjJKTjjsOnnsuvGzBAlvK\nWJNgSoljj7VWxGBwGMuUKfaXwjHH2F8RSgAuIpIVChglZ/XubYuIhBo1Cu6+Ozv1kTRp2dJaEadM\nge7dYx8zfTr07AmNG8M118Drr8PChZmtp4hIGea8unpSolWrVn7SpEnZrkaps2OHZV8ZMya8/LXX\n4JJLslMnSbPp0+Ghh+D99ws+tkEDaNfOXiedZEsROpf+OoqIlHDOucne+1aFPl4BY2ooYEyfFSus\nEWrx4vyyypUtI0uLFtmrl6TZzJkWOL73XuHHMNaunR9AtmsHRx0Vvc61iIgoYMwWBYzpNWmSpdvZ\nti2/7MADrXzffbNXL8mAH36Ahx+2NSSTHcC611724AQDyBYtoEKF9NRTRKQEUcCYJQoY0++VV6BX\nr/Cy9u3h888VA5QJGzfCN9/Y+IQxY+Dbb8P/giiMPfawvJCXXGLLCIWuRykiUoYoYMwSBYyZcfPN\n8NRT4WW33GIJv6WM2boVvvsuP4AcNw42bSr85+vWtVlV110HtWqlr54iIjlIAWOWKGDMjB07bJW5\nr74KL3/lFbjssuzUSXLEzp0wdWp+APn117B2bcGfq1wZLr0Ubr0Vjjgi/fUUEckByQaMGg0uJUqF\nCvDuu1C/fnh5797w6KPZS9M3c6YtXnLwwfD009mpQ5lXvrzldrzjDkvTs2oVzJhh/yDnn28tirFs\n3Qr/+x8ceaQtXag1rUVEoqiFMUXUwphZkyfbXIatW8PLu3a11sa99spMPbyHAQOscSq0Lp98En/1\nO8kS72HWLHj+eXjppcTd14cfbv+ol14KVapkro4iIhmiFkYpE1q2hBdfjE6599FHtppcJtadXrcO\nzjvPhsBFBq7XXWdzNCSHOGddzv37W46mxx6zqfaxzJoF115rTdn33ANLlmS2riIiOUYBo5RYF10E\nH38MNWuGl8+dCyecAAMHpu/a33wDzZvHzy29cCHce2/6ri/FtNde1nU9d66NcTjhhNjHrV4Nf/87\nNGxorY2TJ2e0miIiuUIBo5RoZ5xhv8NbRTSqb91q4xqvvjq69a84du2y+OGkk2xt60T697fML5LD\nype3ZuLx42HCBEu1U65c9HE7dthyhK1aWT7HDz+0h0FEpIxQwCglXsOGMHasdQNHeuEFS7s3b17x\nr7N0qc2JuOee6FihRQuboNuwYX6Z9xaw7thR/GtLBrRuDW+9ZQ/L3XfHHwj79dfQo4fNcOrTJzUP\nl4hIjlPAKKVCpUrw3HM24SVyjsKUKRbQffxx0c//6afQrBl88UX0vltvtQaq5s1tPkWo77+Hf/+7\n6NeVLKhf36bcL14MzzwDjRvHPm7BAujbFw46yDLIv/pqcnkgRURKEAWMUqpcdpl1A0f+jl+3Drp0\nsXGFyfQkbt8Od94JZ54JK1eG76tVC4YNgyeftIAVrAXykkvCj3vwQfj55+S/i2RZ1apw/fXw00/2\nD92hQ/xjv/wSLr/cUvdceaU1eSsDhYiUIkqrkyJKq5Nb1q+3MYwffhi9r0MH63ksaA3qOXPgwgtt\nvepI7dvbkLb99ovet2qVZWVZtSq/7OSTYdQoyNOfaCXbjBm2rNBbbxU8OPaQQ2wty8sui04cKiKS\nZUqrIwLUqGEzmB97LHoOwxdfwDHH2EzneN5807qxI4PFvDx46CEYMSJ2sAjW8vjkk+FlX31lqf+k\nhDv6aPuHXLYM/vvf+LOrwf7iuPdeaNAAOne2h2rLlszVVUQkhdTCmCJqYcxdY8bABRfY7/hQ5cvD\n44/DTTfl53PctMm2X345+jz169vv/BNPLPia3tsM7s8/zy+rUcPS+9WrV/TvIjnop58sh9Orr9rM\nqERq1LCZ2L162SSbyESiIiIZorWks0QBY25butR+T48ZE73vggtsNvWcOXbM7NnRx3TvbsdE5nxM\nZP58W21u8+b8snPPhffeS7r6UhLs3GlNzwMHwuDBNgA2kSZNLHDs1Qvq1MlABUVE8ilgzBIFjLlv\n5074299iz1pu1MgW89i2Lby8UiXrXr7uuqI1Bj35JNx+e3jZ4MFwzjnJn0tKkDVrbJzjwIGxB8GG\nqlDB1rq+4QY4/ni1OopIRihgzBIFjCXHhx9ao86GDYmPO/xwePttG7ZWVLt2WQwQ+mjstx/8+KP1\nTkoZ8P33lu/ptddgxYrEx7ZoATfeaE3dWsNaRNJIk15ECtC9uwVwRx0V/5irroLvvitesAg24eaF\nF8In3ixZAn/9a/HOKyXIUUfZ7KvFi2HIEHsAy5ePfeyUKXDFFXDAAfB//6ek4CKSMxQwSpnUuLGt\nBHfZZeHl1atbq+L//mdp+FKhWTO4667wsueeg3HjUnN+KSEqVICuXeGDD+yvhieeiJ8UfM0aGztx\n8MFw9tk2e2r37szWV0QkhLqkU0Rd0iWT9zbz+X//swU77rvPxjOm2pYt1lo5Z05+WZMmMG1aftJv\nKYN277aJMk8/bUsRJfr/cePGlki8V6/4yxZKqeS9pQBdscJyulasmO0aSWmgMYxZooBRCjJ6NJx6\nanjZAw/YcsQizJtnTc8vvABr18Y/bo894NJLbZJMonEVUmo8/zz8+c/28znn2DhszY2S4lLAmCUK\nGKUwrroKXnwxf7tCBWtlPOKI7NVJcszmzTYu4umnYerUxMe2a2eTZLp1s4dJSp3du22i3PLl+WXf\nfQetCv1rXiQ2TXoRyWH//nd4yr0dO+DqqzU8TULssYdNfJk8GcaPh4suih8MjhljKXkaNLDm6sWL\nM1tXSbvJk8ODRYCPPspOXaRsU8AokkF77w39+4eXjR9vXU4iYZyzpQffeAMWLbI1KfffP/axS5fC\ngw9Cw4Y2C3v4cP0VUkoMGxZdNmRI5ushooBRJMPOO88mvob6y1/UOCQJ1Klj61LPmweDBsEpp8Q+\nbtcuywx/2mlw2GG29uXq1RmtqqTWxx9Hl82YoYxLknkKGEUyzDl45hmoVi2/7PffbQKshhRLQhUq\nQM+eNoPq++9tCaJ4+Z/mzIE777RWycsvtzxSesBKlKVLrUs6lqFDM1sXEQWMIllQvz48+mh42dCh\n1ngkUihNm9qs6iVL7C+Qpk1jH7dtG7z6qnVvt2gBAwbAxo2ZrasUyaefxt+nbmnJNAWMIlny5z/b\n7/BQN92UOKOKSJTq1a15esYM+PprmyQTL1HftGlw7bXW6njjjfDDD5mtqyQlVnd00Fdf6f8VkllK\nq5MiSqsjRfHDD3DMMTZbOujKKy0VXzK2brUxkAsX2vyIRYtszsNll9k8CCljVqyAl1+22VTz5yc+\ntl07++ulRw9lhM4h27ZBrVrhjcHVq8OGDfnbb7xhfx+IFIXyMGaJAkYpqgcesAmuoUaNgvbt7edd\nu2DZsvxgMPJ90SKLD2KpUcO6tSJbMqWM2LXLlhV87rmCV5KpWROOPBIOPDD/Vb9+/s81amSu3sLI\nkdCpU/523br2B+C//pVfdv758M47ma+blA4lNmB0zh0APAicDuwDLAUGA32994VqeHfOdQp8vnng\nVRMY570/Mc7x+wM9gDOBw4F6wEZgCvCc9/6DwtZfAaMU1bZt0Lw5/PRTflm9eraM8MKFNkRt586i\nn79qVRsfGQxApYxasMDGL77wQvy/MBKpXj08mIx87befkoen0G23Qb9++dtXXGGJ/9u0yS/bc09Y\ntUoNw1I0JTJgdM4dDIwHagNDgJ+A44D2wGygrfe+wNwQzrnBwDnAVmAO0JTEAeOjwN3APOArYBnQ\nAAsiKwFPeu9vL8x3UMAoxTF2LJx0UvrOX7kyvP8+nHlm+q4Ry6ZNlndy3jxbya5Zs8xeX2LYvt3W\nlnvuORsIlyp5eRY0tmxp69edfbb1qUqRHHoo/PJL/vYHH9htjVz15fPPoXPnzNdPSr6SGjB+DnQG\nbvbePxVS/gRwG/Bf7/11hTjPCcAGLOCsjwWCiQLGHsBq7/1XEeWHAxOA6kAr732cxAb5FDBKcV1/\nvf0OL4rg7+r69e3lXHRXVYUK8NZblpUlE+bMsRzSM2fadpUqMG6cjdmUHPHjjzbO8dVXYf361J47\nL8/+Cure3SIdDaYttJ9/tjSaQRUqWDrNPfe0laFCxzhff71NkhdJVokLGAOti3OA+cDB3vvdIfv2\nxLqmHVDbe78pifM2pICAsYDPDwCuBu703j9e0PEKGKW41q+H448P75oO2mef/OFkoe/Bn/fbD8qX\nD//MY4/BXXeFl+XlwcCBcOmlafsaAHzyCVx8MaxbF15+4IEwaRLsu296ry9J2r7dmoEXLox+BQfM\nbttWvGscc4yted29u6UAci41dS+FnnwSbg/p2+rYEUaMsJ+HDoWuXfP3HXCA/fPodkqykg0Yyxd8\nSNoFR1YNDw0WAbz3vzvnxmGtj8cDX2SwXsF5q8UYPSZSeDVq2DKBw4bZrOnQoHCPPZI/35132udu\nuCG/bPduy+G8ZQtcc03q6h56/kcesYk8sf4WXbgQzj3XBvRruFsOqVjRmrRCm7VCeQ8rV8YOKIOv\nyAWPI02daq8HHoCDDrLAsVs3m5FVrlzqv1MJFplO56yz8n/u2NH+u9682bYXL7bb2qJF5uonZVMu\nBIzB/0P9HGf/L1jAeCgZChidc9WBnoAHhmfimiJga02nsvXv+utt0ssVV+QvLey9peLbtMkG1qfK\n+vU2i/OjjxIfN2YM3HqrutFKFOegdm17tYrTILF1q3Vxf/SRjZGcMSP++X791ZYtfPxxO2fXrhY8\nduhgA27LsN9/t/9GQoUGjFWq2JjFwYPzy4YMUcAo6ZcLibuDuRriDaAJlu+VgbrgnHPAC0AdbKb0\nrATHXuOcm+Scm7Ry5cpMVE8kaZdfbmMXI7usb78dHn44NavF/fgjHHdcdLCYl2dpQCKXPn72WZuw\nK6VI5coWtfTpA9Onw9y5FhCedFLi/tIVK2xQXpcuNlbh/PPtgd26NWNVzyUjRoTnZW3c2F6hQruk\noeA/0kRSIRcCxlzzOHAe8DWQcIa0936A976V977VvhqUJTns/POt0adSpfDy++6Dv/2teEHjoEEW\nLP4c0UdQq5b98rvrLnjvPWjQIHz/jTfaJBgppQ46yP4qGTPGEom+8II1lUU+hKE2brSH5aKL4JBD\n7K+K0OipDIjsju7SJfqYLl3sj7GgadMsa5JIOuVCwBhsQYyXFTZYvi7O/pRxzv0Lm5U9BjjTe1/M\nUd4iuaNLFxsfGTke8tFH4ZZb8rusC2vXLvjLX+C886x7O1SrVjB5Mpx6qm3XqmXdZqHX3rHDZmwv\nWpT8d5ESpnZtW8Jo2DAbC/nuuxYUJkoG/ttvNnbi8MPhzTeTf0BLoN27bcJYqNDu6KB99w3Pxwhq\nZZT0y4WAcXbg/dA4+4ON8fHGOKaEc+5J4C5gNHCG935jAR8RKXE6drS8bXvuGV7+1FM2CWbXrsKd\nZ/VqOP10+Oc/o/f17m1LGh94YHh5s2Y2QzvU8uU292HLlkJ/BSnp9tzT/sp44w3rjv78c1uasF69\n2MfPnWtT7ps3t6goB1LBpcuUKdYYG7TnnvHzs6pbWjItFwLG0YH3zs65sPoE0uq0BTZjeRFTzpln\ngFuBEcBZ3vvN6biWSC448URberBmzfDyF1+0CTcF9QBOmWK5mUeODC+vUMHySL74Yvx5C+edB/fc\nE142ebLllivFcYDEU7GizeB49lmb7jthAtx0U+xu6++/t3yOJ5xgD3ApFNkd3alT/FVczjknfPvL\nL6PTWImkUtYDRu/9XGwmckPghojdfYGqwGuhORidc02cc02Ke+3ABJcBwPXAp0BX773aOqTUa9XK\nfsHUrh1e/tZbFtTFS7n36qvQtm30eKl69WzRkOuuKzgf3IMP2iIgod54w+ZHSBmWlwetW9vSQHPm\nWJN3rHQ7335rs6k7drSfS5FE6XQiHXooNAn5Lbhzp60bL5IuWU/cDTGXBpwFtMZyNP4MtAldGtA5\n5wG89y7iPCcCVwU2q2GpcVZgwSCBz/QKOf4BoA+wBegHbI9RvWne+8ExysMocbeURLNn2+/e334L\nL+/c2SbJBMcc2inUUAAAIABJREFU7thh8xeefjr6HG3b2jyFeD2KsWzYYEnKZ4XkIMjLs1+Yp5+e\n/PeQUmrOHJt1/eab8ZugzzkHHnoIjjoqo1VLteXLoW7d8LKlS6PLQt19t2UhCPrTn+yPPpHCSDZx\nN977nHhhS/m9jK3ssh1YgAVxe8c41lvVo8p7BffFe0UcP7Cg44GBhal/y5YtvUhJ9Ouv3jdq5L39\nRs5/tWvn/YYN3i9d6v2JJ0bvB+9vvNH7bduKdt2ff/Z+r73Cz1ejhpWLhJkxw/tzzon9EIL3znl/\n0UXe//JLtmtaZC+/HP6VWrUq+DPjxoV/pnr1ov/3KGUPMMknEadlvUs6yHu/yHvf23tfz3tf0Xvf\nwHt/q/d+bYxjnY9oXQyUDwzui/eKOL5XQcf7kBZJkdKoUSObpNIkYpDHmDGWP7FFCxg7Nnxf5crw\nyis2WSbeGKuCNG4Mb78dnh5k/XprMNqwoWjnlOwZPtzmpjz6aPFXEYxy1FGWqXrCBGsSj+S9tUI2\naWIzqxcvTnEF0m/YsPDtRN3RQa1bhw8r2bDBhoaIpEPOBIwikj3772+/aI4+Orx8yhTrFgvVoIHl\nT7zssuJf97TTomdaz5oFl1xSJrKolAreWwL4006zmO2vf7XhhatWpeFirVvbbKuRI+3nSLt2We7G\nQw6BO+6wFD4lwPbtFnCHKkzAWK5cdJ5GzZaWdFHAKCKAtVSMHm1JuOPp2BEmTUrtMmR33GEtU6GG\nDrUlh1NlwwaLI046yWKJ66+3VlMFpcWzbRv06mUJ4EONHWtjVGfPjvmx4uvQAb75xpJ7Nm0au2JP\nPGG5nS6+2GZV5/A/9tixtiRgUJ06lomgMCJnSw8ZoowDkh4KGEXkDzVr2uossXK/3X03fPaZJeFO\nJefgf/+L/gX58MM2maaovLeu9l69bELOtdfaL+a5cy39z0knWXf83XfbSnb6JZuc1ast7curr8be\nP3euBY2jR8feX2zOWTLC6dOtafOQQ6KP2brV9nXoYPsfeignM8VHzo4+44zwoRqJdOxo60sHLVpk\nK7+IpJoCRhEJU726BYY9e9r2PvtY4Pboo7GznKRClSo2KzsyzU+vXhYPJGPZMps52qQJtGtnYy03\nx8msunChHdu8uTVUPfII/Pprkb5CmfLzzxYMfv114uPWrbMZ9y+/nMbK5OXBhRfaguYDBtj4iljm\nzYP777cxFWecYWtabo+VGCPzCrMcYDx77GGBeyh1S0s65ERandJAaXWkNFq2zFZvC23BSKexY205\nwdDk4Q0aWDd4opbNnTstyH3hBZs8UNgVa+I5/niLQc4/P3Fak7Loyy+hRw9YGzEdsXFjC/ofeyx6\nRR+wZSQfeaTwLWdFtnWrNSH37w/z5yc+tlYtGzB75ZWxu7YzYM4cu3dBFSrY+M/q1Qt/jpdesq8Q\ndMwxNv5YJJESm1anpL+UVkckNQYMiM6acsop3m/fHn3sL794/9e/el+vXvyMK8HXAQd4f++93r/7\nrvcXXOB9lSoFfyYvz/tOnSzlybp1Gb8VOefll72vUCH6PrVr5/2qVXbM7t3e//3vse9nz57eb9qU\nocru2uX9yJHeX3ih95UqFfyPfdxx3v/3v96vX5+hCpp+/cKrceqpyZ9j+XLLLBR6noULU19XKV1I\nMq1O1gOt0vJSwCiSOtdfH/37/KabbN/mzd6/9poFkQXFABUqWJDyySfe79wZfo3ff/f+9de9P/NM\n78uVK/hclSp536OH94MGeb9lS+bvSTbt2uX93/4W+75cfnns3H/vvut95crRxx97rOX2zKg1a7x/\n+mnvjzmm4H/oKlW8v+wy77/6yqLfNOvUKfzyjz9etPO0aRN+nqefTm09pfRJNmBUl3SKqEtaJHV2\n7LDB/GPGhJd37Wrpf9avT/z5ww+3LrpLL40eFxnLqlU2pO3NNwselwfWXXjRRdbFGrkmd2mzZYul\nUBo0KHrfI49YGp14y0F++63N4l2+PLz8wANt6EBWFmeZOtX6cF9/veDFlxs3tlnWjRrZP/Tee9t7\n8OeiJiEN2LjRxgiHDqX86Sc47LDkz/Wvf9kErqBOnaJT9YiESrZLWgFjiihgFEmtlSttzeuFCwt3\nfNWqtjTalVfaGMSC1rSOZ+FCSyj+5psFT7g54ABbB7tdu6Jdq7iWLbMJE/vtZ2M/K1VK7fmXL7cg\nfeLE8PJg4vbzzy/4HAsWWE7BH34IL99zT3jnHZt/khVbt9qgyxdfhC++KNo5qlXLDyBjvYIBZq1a\ncOyxUYOBBw+G7t3ztw85xCYUFeXZnT07PPl+hQr231CNGkX7alL6aQxjll7qkhZJvalTCx5reMIJ\n3r/4onUxp9oPP9i4x4MOin/9vDzv77/f+x07Un/9eHbt8v6ZZ7yvVi2/Hnvu6f2f/uT9e++l5l58\n/733DRpEf9/atb2fMCG5c61b5/1pp8W+dznRdTpvnv0j1q+f+GErzqtGDe9feimsm/uqq8IPueWW\n4n2NQw8NP9/bbxfvfFK6oTGMChhFSpN33on+3bvvvt7fcYcFdJmwe7cFSbfc4n2dOrHjgbZtvZ8/\nP/11mT3b+5NOShybVK7sfbdu3r/6qvdr1yZ/jc8+swA08rxHHmmxVVHs2BF7bCp4f/PN0WNMs2Ln\nTvvy550Xe3ZPKl7du3u/YoXfvTt6stbw4cWr/l13hZ/vwgtTc1ukdEo2YFSXdIqoS1okfd57D/7z\nHxuPeMkllqeumMPHimz7drj3Xvj3v6P37bWXJSE/99zUX3fnTnj8cVsBJ5m1msuXt7zVPXvaeMKC\nxnQ+9xzcdFN0aqLOneHdd4vXxem9Zbu57Tb7OdRZZ8Fbb1lXdU5YtcoevB9/tBxCa9aEv9auLfrq\nMXXqMOWv79Hy1vwM+VWrWjL04gwrGDcOTjwxf7tGDeuWrlCh6OeU0ktjGLNEAaNI2TJ8uE0GiZzQ\nAXD11dCvnyVVToXp0+GKK2Ln1qtWzV7LlhV8nrw8W+GmRw97HXBA/r5du2yZxv/8J/pzf/6zBXrl\nyxf9O4QaOtTyXG7aFF5+9NE2GaZ+/dRcJ61277Y1JyMDydCAcs0aiwJHjrTZQyEe4l7u56E/trt1\nsyGVxbFrl61qFLqE9siR9geDSCSNYczSS13SImXP8uXen3567J7Hww/3ftq04p1/yxbv77nH+/Ll\nY1/jjDO8X7DAelK//tr7226LPe4w3uu447z/5z+9nz7d+y5dovc7Z3kC05FdZupUy40Zec26db3/\n7rvUXy+rZs+2fEIhX7Q134R97xdeSM2levcOv5/BdFQikdAYRgWMIpI5u3ZZ7rxYQ94qVfL+qaeK\nFnCNG+d9kyaxA72aNS0XZazz7t7t/aRJltA8chJEMq+qVb3/6KPi359EfvvN+xYtoq9dpUr871di\nbd/u/QMPeF+unF/Ovt6xK+w7L7n937Gz0ydp8ODwe9mgQSm7j5IyyQaMWktaRKQY8vLg9tthwoTw\nJd7AxhredJONHVy1qnDn27gRbrnFxqL99FP0/vPPh1mzbCxnrPQrzkHLlvD3v9vnZ86EBx+09bIL\na//9bZnGs88u/GeKYr/9LNdmt27h5Vu2WA7N006zpfNKhQoVoE8fGDeOT+v0JvTXbwsmU++Ju6Bt\nW8urUwwdO1rao6AFC2DGjGKdUgRAAaOISCq0aGFjDHv3jt43dCg0awajRiU+x4gRlsy6f//oSSH1\n6tkYt3feKVwycrDg8cgj4b77LF/1nDk2Wef44xN/j4kTkwswi6NqVXj/fbjrruh9I0bYEs8PPpjc\nRJ+c1ro1H7d5JKzoLD62H777zm78c89FPwCFVLWqJe0ONWRIkU6V87ZuhWeegYcfhqVLs12bMiCZ\n5ki91CUtIgV7883YaWmcsyX2Inse16yJHnsW+rryyqKlx0lk8WLrLm/f3vIhguVx3LgxtddJxoAB\n3lesGPseHHqoLQ1d0m3f7n316uHfbQLHRX/hM87wfsmSIl3jhRfCT1Vafz1dc03+d2zVKkdSM5Ug\nKK1OdmiWtIiE+vVXWz7w22+j9x1/vK0k06iRtRpef33sWc6NGlmannTPcl2/HjZvtlbMbPvpJ7sf\no0fH3n/xxZZeqE6dzNYrVb78Etq3z9/et9ZulrU9l7whMaZI77MPDBhgU9qTsHy5/VuG/npftCh8\nVnxJt2yZfZ/Q9E9ffZW9VZdKomRnSatLWkQkDQ46yNaljrXW8oQJ1vN4xhkWC0QGi87BrbfC999n\nJiVKjRq5ESyCLW/3xRfw2muw777R+994w9Zafv75oqdBzKaPPw7fPvOsPPI+fN/Wt65WLXzn6tWW\nQLN3b0vhU0h16kQPO/jooyJWOEe9/np0rtDipiWSxBQwioikSYUKNvlkxIjogGzDBvjss+jPHHEE\njB8PTz5p49HKIudsUs/s2XDttdH716+33JBt2sC0aZmvX3FEBoxnnYV94d69bXZKaObtoIEDLUnl\nmDGFHtt4zjnh26UpYPTe4utIH35Y5KGfUgjqkk4RdUmLSCIrV1pMEBkwBJUvb62R99xTvNU+SqNv\nvoHrros92zcvz2aV9+2bQ6vExPHrr3Dwwfnb5cvb7Pmw1XN27bKZSfffDzt2RJ+kXDn7S6JaNXsP\nvkK3q1Vj1tZGHPFy/kyiCuV2serlYVSvuwcce6wtS1RCfftt/IlbU6bAMcdktj4llRJ3a9KLiOSo\n3bu9798/emJHy5aWPFvi27HD8l1WrRp7Usz++3s/aFBu5xzs3z+8zqeckuDgKVO8P+KI2F+2EK/d\n4BszO6z4Hc6zHypXttlXGzZk7Lun0rXXxv/q992X7dqVHCgPo4hIbnLO8jJOnGg5Dps1swkcEyZY\nj6PEV7685bucNQu6d4/e/9tvtoZ3ly4wb17hz7t7t00SmTYNPv3UujofeQRuvNGGD153nU2mSIWY\n3dHxHHMMTJpkg1mLwAHnEJ5P5yO62g9bt9pYiUMOscGgO3cW6RrZsHmzrTkej8Yxpo+6pFNEXdIi\nIpkzdKgF3wsWRO+rUsVyT150kQWDS5fGfy1fHj15IpbLLoPHHos9EacwNm2ySc+h+SRnzbJJPgUa\nOdK6qL/7Lqng7mtOpB1f/7G9F2tZQW0qEHGOww+3bvAzz4ydDT6HvPGGjW8N2mcfWLcu/N/wl18s\nFpbEku2SVsCYIgoYRUQya9MmeOgha6XNRCNZzZoWV/XunXxc9dFH4RNRDjrIEqknHZ9t325ffONG\ne4/8OWR71++bqfvEXazakj/7+ou9e3Lq2g9in7tDB7uZzZolWanM6djRZtEH3XGHjVsMTcP0r3/F\nTgQv4RQwZokCRhGR7Jg502ZNjx2bmeu1a2c9uYcfXvjPXHON5dQMuukmW9En3Xr3tknWQbdcv51+\ntR6xyHfLlugPOAe9elkkvv/+6a9gEhYssNykoWHLzJkWLN50U37Z8cfbRClJTHkYRUSkTGna1MYZ\nvviitQIma6+9LPg79VTr7rzrLnjiCTtf06bRx48ZY41w994bO+aK5D188kl4WcLxiynUtWv49pBP\nKuL79LV+2169ops4vYeXX4ZDD4UHHrDWyhzxyivhweKxx9rSl5FrkU+YAEuWZLZuZYFaGFNELYwi\nItm3apWNXxw2zHpv69VL/Kpb18Y8xrNjhwWPffvGDg4PPtiWfo5cvznUtGnhqV722MNycleuXPTv\nWVibNkGtWjbPJWjGDFuz/I/K3XlneD9vqLp1rbWxd29L6ZMlu3fbvZ4/P7/suedsUhLAccfZEM+g\nZ5+1VmeJTy2MIiJSZtWqZYHEokWJZz+3aWPdm4mCRbDk63ffDT/8YCvzRJo7Fzp3tgk2sZZ3hOjZ\n0R07ZiZYBEvL2LFjeNmQ0MnTzZtbZvlhw2L3sS9bBldfbcd9/nla65rIV1+FB4uVK8Of/pS/HTlz\nvqTOln7uOWvBzsVVjBQwioiIFKBRIwv83n3XGt0ivfWWxVv//W/0L/vIgLFLl/TVM5aobukhEQc4\nZ33kM2ZYxBJrKvjMmXD66faaOTNtdY3n5ZfDt7t3D889Hhkwjh4Na9emv16ptHatZVE6+WR73v7y\nl/CW4WxTwCgiIlIIzsF558FPP8ENN0QP/1u3zrpITzzR1gEHW+FnwoTw4848MzP1DTr77PC6Tppk\neSujlC9vX2DOHPjb32I3g37+uQ3gvPpq+PHHtNU51IYNMGhQeFnv3uHbTZqEpyjauTP+qkq5atAg\nG0YBsHAhvP9+bq36pIBRREQkCTVqwNNPWyAYKwPNN99AixbWlf3BB+ETNZo3z/zk47p1oXXr8LLI\nACxM9erWfz97dnjSw6Ddu+GFF2zGSbNm8M9/xk6ImSLvvhs+frR+fZugFKmkd0u/8Ub49sUX51Za\nTAWMIiIiRXDccdZa9/jjNpEl1M6dlg8wOCkjKFOzoyNFdkvff3/4mMCYDjwQXnvNvuTJJ8c+ZsYM\n6ztt2BDatrVIevnyFNQ430svhW/36hV7/k1kwPjZZ7YyTEmwaFH0ikIXX5ydusSjgFFERKSIQpcs\nPPvsgo/PVsB48cXh3ZsbNljjYaESnrdsaYMCBw+2dDvxjB9vCRH3289mAg0cCOvXF6veP/0UnVOx\nV6/Yx7ZqBQcckL+9eTMMH16sy2dM5HKHxx4LjRtnpy7xKGAUEREppgMPtMkkH3wQv8u5Vi1rlcyG\nAw+0XN2hxo2Df/yjkCdwzpaqmTnTEiJ26gR5cUKI3btt5nXv3lCnDvToAe+9V7iklRFCk46DNXQe\ndFD8KpbUbulY3dG5RgGjiIhICgQDllmz4JZbouOpLl2ymsqQG2+MTg3Ut2/0pJyEKlSwhbWHD7fs\n2P37wwknxD9+2zaL2s4/H2rXhksvtTxHO3YUeKmdO+HVV8PLIie7RIoMGIcOLdSlsmrmTOvZD8rL\ngwsuyF594lHAKCIikkJ77gn9+sHEibZMHdgQv4ceymq1cM7S04Rmzdm1y1qzNmwowgnr1LEu6PHj\nYd48a648+uj4x2/cCK+/btPE69WzzNoTJ8Y9/PPPYenS/O1q1eDccxNX6aSTYJ998rfXrrW8hrks\nsnWxY8fYqZuyTQGjiIhIGrRsaePvVq60BN+h4+uypU6d6JyGv/4KN99czBM3bGiTX6ZPtyaze+6J\n33cMttTN88/b9O1OnWIuBB5ZzwsusETkiZQvHz2WNJe7pXfvhjffDC/Lxe5oUMAoIiKSVrVqxR/u\nlw1nnWV5JEO98gq8806KLnDkkfDww5bP8dtvrX8+UZPZyJHWNNihwx/NgatWwUcfhR9WUHd0UGS3\n9ODBublyCtg40oUL87erVImuf67IoUdYREREMuHf/4Yjjggvu/ba8OCl2JyzWT79+sHixbZe9VVX\nhS/REmrUKJvV0r49b/b9JWzs4aGH2nKOhdGpU3hL5G+/WWagXBTZHd21qw1pyEUKGEVERMqYKlWs\nK7Rixfyy9ettTsquXWm4YLlylm37f/+z9akHD46f2/HLL3n56Y1hRb16FT6JdZUqtoJhqFzslt6+\n3SaPh8rV7mhQwCgiIlImNWsGjz4aXjZmjCUcT6tKlSxFz5df2qt9+7DdU2nONI75YzuPXVzW6Ovw\nJXMK0KNH+Hbkiju54LPPYM2a/O2aNeG007JXn4IoYBQRESmjbrnFcmyHuv9++O67DFXg5JOtK3rM\nGBvDCLxM+GDF0/ic/S9sZ4t0Dx9eqMjvrLMsA1DQzz9buqNcEtkdff754S2+uUYBo4iISBmVl2fJ\nsUNT0ezcCRddZFlwMuakk2DkSLaNGscbFXqF7epNYLr0+PHWBNemjTXPJQgca9SIXm86l7qlN2yI\nntQTa9nuXKKAUUREpAyrVy96veY5c+DWWzNfl6Gr27BmR/U/tmuymq5ERFYTJlgG8uOPh08+iRs4\n5vKqLx9+CFu35m83bFj4ST3ZUj7bFRAREZHs6toVrrvOUiMGvfiixWU9e2auHpGB60Xn7qDS5o4W\nGEaaONH6no86Cg45BKpXt1eNGlC9OudQlz+7S/DeZstMngwLxy/mwCOq2VTkLC67E9kdfdFFhZ/U\nky3O59oo0BKqVatWflKuztsXEREpwObN0KIFzJ6dX7b33rZsXSaSjv/2m615HZozccoUOOYYbFDl\ngw/CsGFJnbMtYxlP2z+2/8PN3MxTtlG16h/BJXvtZS2WV11leSTTaOlSu5+h3/OHH6LTHKWbc26y\n975VYY9Xl7SIiIiwxx7w1lvhk0XWrrWlozOR+Pq118Kv06xZIFgEOPZYWxh60iRrDi2k7oT3Q39I\nSD/1pk22HvZPP1k3d79+0LSpjad8443wPuMUevvt8O/ZvHnmg8WiUMAoIiIigAVof/97eNno0fDY\nY+m9rvfRSwHGXNmlZUsYMsSaHrt1K/C8kQHjGNqxin3iHB0wdqzNQDngALjzTvjllwKvk4zI7uhc\nzr0YSl3SKaIuaRERKQ1277bVUkaNyi+rUMHWxW7ZMj3XHD8e2ub3HFOhgjX+1apVwAcXLbJ8ORs2\n2Gv9+vyfA9vNPn2UGRvz17V+sfINXLHtueQSM3boYIM8zzknvAk2SbNnQ5Mm+dvO2VfYf/8in7LI\nku2S1qQXERER+UNeHrz6Khx9dH5i6R07rCVs8uTwZfdSJXKyS9euhQgWAerXt1cC3fvAjL752x92\nfIYrhjxleYOCgeX06TBggCUSj+WLL+xVpw5ceSVcfbVNbU5SZOviKadkJ1gsCnVJi4iISJj994cX\nXggvmz0bbr899dfatAneeSe8LGZ3dBFFptcZMQJ+35Rnk10OOMAGEF54ofW9z5oFt91ms31iWb7c\n+uwPOgjOPNOSKe7cWah6eF9yu6NBAaOIiIjE0L27TRoONWCALQOdSu+/H54kvF691C6Rd/TR0KhR\n/va2bZb3O6YmTeCJJ2zK9iuvxE+O6D18+ql1UTdqBH372mcS+PZb+PXX/O2KFTObsqi4FDCKiIhI\nTP36waGHhpdddZWNL0yVyMkul14K5VM4YM65IiTxrlLFpoePG2d5hW64wXI3xrJ4MfTpAw0a2ESc\nQYMsR1GEyNbFLl0sm09JoYBRREREYqpa1QKd0ABu9Wq4/PLUpNr59dfoYYOp7I4OigwYP/4Ytm8v\n5IePOgqeftqi5P/9D1rFmSeya5fN4D7vPKhd27q5Bw+GrVvZsSO6270kdUeDAkYRERFJoFUreOih\n8LKRI23ex/ffF+/cAweGb59wQvgs4lQ54QSL4YI2bAifBV4o1apZ8+p339nrqqsseWUsmzZZwsXu\n3aF2bUae9m9WrszfXaOGDYEsSRQwioiISEJ33WUzekO99JKND2zeHB5/3FYwScbu3TZMMFQ6WhfB\nVgGMTNtYrLWlW7Wy1sYlS+CZZ6wVMp7ff+eN0fXCis5tvYjK5XYUowKZpzyMKaI8jCIiUpotWmQB\n4rp1sffn5UHHjjYGsVs3a5BLZORIy/cYVKUKLFtmk5fT4bPPbG3soNq1Ld5LyZLS3tva1u+8A+++\nGzYBZhN7UIflbCL/hoyiPe1rzrAWyAsugPbtUztwsxC0NKCIiIikXP361iq3776x9+/eDcOHW8BY\nt669Dx9uQ/tiiZzs0rNn+oJFgFNPDT//ihWWjDwlnIPWrW2G9cKF8PXXcNNNULcuQzgnLFjcn8Wc\nzFeW5PLFF6FzZ5saft11lton3g3LMgWMIiIiUiinnALz5sHrr1vqm7w4UcSmTfnH1K9vK+xNn56/\nf906+OCD8M+kqzs6qGJFOOus8LJidUvHk5cHJ54I/fvD4sW80fqpsN0X8hZ5RPTurloF//2vRbX7\n7w833mhBZyYW8S4kdUmniLqkRUSkrFm6FN56C157DaZNK/j4o46ylsetW+H++/PLGzaEuXPjB6Cp\n8t57cP75+duNGtl1nUvP9VautMbD0EbDqT0epPmX/8lfRieemjWtj74YSxEmUmK7pJ1zBzjnXnLO\nLXHObXPOzXfO9XPOxUm3HvMcnZxzjzvnvnDOrXbOeefc2EJ87gjn3LvOuRXOua3OudnOub7OuSrF\n+1YiIiKlV716tvrL1Kk2Y/r//i/xUnfBY0KDRYBevdIfLIKNYaxUKX973jxLs5gu774bHiwecQQ0\nG3S/BYKffWbNqvGSMfbokbZgsShyImB0zh0MTAZ6AxOBJ4FfgVuAb5xz+xTyVDcAtwNtgEKlFXXO\ntQa+A7oBI4H/ABuA+4ERzrlKCT4uIiIiQNOm8M9/woIFNqHl8ssLnvgSdPnl6a1bULVq4RNtIE3d\n0gGxlgJ0DgsETzvNppovXw7DhlnTa2hy8AsuSF/FiiAnAkbgWaA2cLP3vpv3/i/e+1OxwPEw4JFC\nnuefQFOgGnB2QQc758oBLwN7AOd67y/y3t8NtAbeB9oCtyX7ZURERMqqcuWgQwfLsbhsmQVNp58e\nvwXx1FOtSzpTkl71pYh+/TV6Us1FF8U4MDi48tVXbSbO4MGW4zEyj1GWZX0MY6B1cQ4wHzjYe787\nZN+ewFLAAbW995uSOG9DYB4wznt/YpxjTgW+AMZ470+O2HcQMBdYADTyBdwojWEUERGJb9my/PGO\nU6damXOWQDuTsdGqVVCnTvh8kjlz4OCDU3udhx+G++7L327bFsYWOEguc0riGMb2gffhocEigPf+\nd2Ac1gJ4fBqufWrgPWoZcu/9r8DPQAPgoDRcW0REpMyoWxduuw2mTIGZMy2tzowZmW9Iq1UL2rUL\nL0t1K6P30d3Rl1yS2mtkWi4EjIcF3n+Os/+XwPuhcfaX1GuLiIiUSUceaRNdmjbNzvXT3S09dSr8\n9FP+dvnytsR0SZYLAWONwPv6OPuD5XGmEZXYa4uIiEgWRC4T+M031mWeKpGti2ecAfsUdvpujsqF\ngLHEcs5d45yb5JybtDJ0VXERERHJWQceCC1b5m97D0OGpObcu3bZWM1QF1+cmnNnUy4EjMFWvBpx\n9gfL46xQ9nmmAAAO00lEQVRemb1re+8HeO9bee9b7RtvrSQRERHJOenqlv7yS0toHlStGpxdYN6W\n3JcLAePswHu8cYKNA+/xxhmW1GuLiIhIlkQGjKNGwfp4A9SS8Prr4ds9esAeexT/vNmWCwHj6MB7\nZ+dcWH0CaXXaApuBCWm49qjA++mROwJpdQ7F0ur8moZri4iISJYcfjgcdlj+9o4d0LkzvP22/VwU\nW7bA+++Hl5WG7mjIgYDRez8XGA40xFZqCdUXqAq8FpqD0TnXxDnXJAWX/wqYBbRzznUNOX8elgQc\n4PmCcjCKiIhIyeJcdCvjxIlw4YWWSPyhh2wRlmQMGwa//56/XaeOJSYvDbKeuBv+SN49HlvtZQgW\nxLXGcjT+DLTx3q8OOd4DeO9dxHlOBK4KbFYDegIrgE+Dx3jve0V8pjXW0lgBGAQsBDoArbAckB28\n99sK+g5K3C0iIlKy/PyzpfaJ16JYsSL86U9w883hk2Ti6dYtfPLMLbdAv36pqWuqJZu4OycCRgDn\nXH3gQax7eB9shZcPgb7e+7URx8YLGHthS/3FFfmZwOeOwFoz2wN7Yt3QbwGPeu+3FKb+ChhFRERK\nngkT4IEHYPjwxMe1aQM33QQ9e9pS0JHWrLHk5KHB58SJcOyxqa1vqpTYgLGkU8AoIiJScs2aBU8/\nDa+8ApsSLES8337w5z/DNddA7dr55QMGwLXX5m83bgyzZ1vXdy4qiUsDioiIiGTV4YfDM8/A4sXw\n5JNwUJxFgZcssTWi69eHyy+HyZOtPDJZ98UX526wWBRqYUwRtTCKiIiUHrt2waefQv/+MGJE4mNb\nt4Zvvw0v++UXOOSQ9NWvuNTCKCIiIlJM5cpBly42tvHHH+H666Fq1djHRgaLxx2X28FiUShgFBER\nEUkgtLv6iSfid1cHlZbci6EUMIqIiIgUwl57wW23WTqeoUOhU6foYypUgAsuyHzd0k0Bo4iIiEgS\nQrurf/jBZk1Xr25d1k89ZQm7SxtNekkRTXoREREpu7y3HIwVK2a7JoWjSS8iIiIiGeZcyQkWi0IB\no4iIiIgkpIBRRERERBJSwCgiIiIiCSlgFBEREZGEFDCKiIiISEIKGEVEREQkIQWMIiIiIpKQAkYR\nERERSUgBo4iIiIgkpIBRRERERBJSwCgiIiIiCSlgFBEREZGEFDCKiIiISEIKGEVEREQkIQWMIiIi\nIpKQAkYRERERSUgBo4iIiIgkpIBRRERERBJSwCgiIiIiCSlgFBEREZGEFDCKiIiISELOe5/tOpQK\nzrmVwII0X6YWsCrN1yjLdH/TR/c2vXR/00f3Nr10f9OnoHvbwHu/b2FPpoCxBHHOTfLet8p2PUor\n3d/00b1NL93f9NG9TS/d3/RJ9b1Vl7SIiIiIJKSAUUREREQSUsBYsgzIdgVKOd3f9NG9TS/d3/TR\nvU0v3d/0Sem91RhGEREREUlILYwiIiIikpACRhERERFJSAFjjnPOHeCce8k5t8Q5t805N9851885\nt3e261bSBe6lj/Nalu36lQTOuXOdc0855752zm0I3LvXC/hMG+fcJ865Nc65Lc65Gc65W51z5TJV\n75IgmXvrnGuY4Fn2zrm3M13/XOac28c5d5Vz7kPn3JzAc7jeOTfWOXelcy7m70Y9uwVL9t7q2U2e\nc+6fzrkvnHOLAvd3jXNuqnPuAefcPnE+U+xnt3zqvoKkmnPuYGA8UBsYAvwEHAfcApzunGvrvV+d\nxSqWBuuBfjHKN2a6IiXUvUAz7H4tBpokOtg5dw7wPrAVeAdYA5wNPAm0Bc5LZ2VLmKTubcB0YHCM\n8pkprFdpcB7wHLAUGA0sBOoAPYAXgDOcc+f5kEH+enYLLel7G6Bnt/BuA6YAI4AVQFXgeKAPcI1z\n7njv/aLgwSl7dr33euXoC/gc8MBNEeVPBMqfz3YdS/ILmA/Mz3Y9SvILaA80BhxwSuC5fD3OsdUD\n/3PbBrQKKa+M/WHkgT9l+zvlyivJe9swsH9gtutdEl7AqYFfmHkR5XWxAMcDPUPK9eym797q2U3+\nHleOU/5I4F4+G1KWsmdXXdI5KtC62BkLap6J2P0AsAm41DlXNcNVE/mD93609/4XH/g/UAHOBfYF\n3vbeTwo5x1asNQ3gz2moZomU5L2VJHjvR3nvh3rvd0eULwOeD2yeErJLz24hFeHeSpICz10s7wbe\nG4eUpezZVZd07mofeB8e4z+8351z47CA8njgi0xXrhSp5Jy7BDgQC8JnAGO897uyW61S6dTA+2cx\n9o0BNgNtnHOVvPfbMletUmU/59y1wD7AauAb7/2MLNeppNkReN8ZUqZnNzVi3dsgPbvFd3bgPfS+\npezZVcCYuw4LvP8cZ/8vWMB4KAoYi6Mu8FpE2TznXG/v/VfZqFApFveZ9t7vdM7NA44EDgJmZbJi\npUinwOsPzrkvgcu99wuzUqMSxDlXHrgssBn6C1bPbjEluLdBenaT5Jy7E6gG1ABaASdiweKjIYel\n7NlVl3TuqhF4Xx9nf7B8rwzUpbR6GeiABY1VgaOA/2Jjaj51zjXLXtVKJT3T6bMZeAhoCewdeJ2M\nTTo4BfhCw1cK5VGgKfCJ9/7zkHI9u8UX797q2S26O7EhardiweJnQGfv/cqQY1L27CpglDLLe983\nMN5mufd+s/d+pvf+OmxSURVsxplIzvPer/De3++9n+K9Xxd4jcF6Ib4FDgGuym4tc5tz7mbgDiwb\nxaVZrk6pkuje6tktOu99Xe+9wxo9emCthFOdcy3ScT0FjLkrGPXXiLM/WL4uA3Upa4IDs9tltRal\nj57pDPPe78RSmYCe57icczcC/wF+BNp779dEHKJnt4gKcW9j0rNbeIFGjw+xIHsf4NWQ3Sl7dhUw\n5q7ZgfdD4+wPzoKKN8ZRii7YnK9ukNSK+0wHxjc1wgbD/5rJSpUBep4TcM7dCjyF5ftrH5jNG0nP\nbhEU8t4momc3Cd77BVhgfqRzrlagOGXPrgLG3DU68N45Rmb8PbFkm5uBCZmuWBlwfOBd//NPrVGB\n99Nj7GsH7AGM1yzTlNPzHIdz7m4sefE0LKBZEedQPbtJSuLeJqJnN3n7Bd6DmT5S9uwqYMxR3vu5\nwHBsAsYNEbv7Yn9xvea935ThqpUKzrnDYw2kds41BJ4ObCZc4k6SNghYBfzJOdcqWOicqww8HNh8\nLhsVK+mccy1iLWfnnOuArQoBep7DOOfuwyZiTAY6eO9XJThcz24Skrm3enaT45w71DkX1b3snMtz\nzj2CrQw33nu/NrArZc+uU07Y3BVjacBZQGssR+PPQBuvpQGLxDnXBxuEPQZYAPwOHAychWXA/wTo\n7r3fnq06lgTOuW5At8BmXeA0rDXg60DZKu/9nRHHD8KWqHobW6KqK5b6YRBwvhJVm2TubSD9SGPs\n/xeLA/uPJj8H233e++AvhzLPOXc5MBBrhXmK2DNI53vvB4Z8Rs9uISR7b/XsJifQzf8PYCwwD8tZ\nWQebWX4QsAwL0n8M+Uxqnt1klqPRKytLANXH0r8sBbZjwU0/YO9s160kvwL/cb2FzdpbhyWUXYmt\nzXkZgT+m9CrwPvbBlpaK95of4zNtsYB8LbAF+B5rSSiX7e+TS69k7i1wJTAMWxlqI7YM2EJs3diT\nsv1dcu1ViHvrgS9jfE7PborvrZ7dpO9vU6wXbBrWcrgTC8q/C9z7mnE+V+xnVy2MIiIiIpKQxjCK\niIiISEIKGEVEREQkIQWMIiIiIpKQAkYRERERSUgBo4iIiIgkpIBRRERERBJSwCgiIiIiCSlgFBEp\nI5xzfZxz3jl3SrbrIiIliwJGEZFCCgRbBb1OyXY9RURSrXy2KyAiUgL1TbBvfqYqISKSKQoYRUSS\n5L3vk+06iIhkkrqkRUTSJHTMoHPucufcVOfcFufcCufcS865unE+19g596pz7jfn3Hbn3JLAduM4\nx5dzzl3nnBvnnFsfuMYc59wLCT5zrnNuonNus3NujXPubefc/qn8/iJSeqiFUUQk/W4DOgPvAJ8B\nJwK9gVOcc6299yuDBzrnjgVGAnsCHwE/Ak2AS4BznHMdvfffhRxfERgGdAIWAW8CG4CGQHdgLPBL\nRH2uB7oGzv8V0Bq4AGjmnGvuvd+Wyi8vIiWfAkYRkSQ55/rE2bXVe/9ojPIzgNbe+6kh53gSuBV4\nFLgyUOaAV4HqwCXe+zdCjr8AeBt4zTl3hPd+d2BXHyxYHAqcFxrsOecqBc4V6XTgWO/99yHHvglc\nCJwDvBv3y4tImeS899mug4hIieCcK+h/mOu993uFHN8HeAB4yXt/ZcS5agALgErAXt77bc65tliL\n4Dfe+zYxrv811jp5svd+jHOuHLAaqAgc4r1fUkD9g/V5xHt/b8S+9sAo4HHv/Z0FfE8RKWM0hlFE\nJEneexfntVecj3wV4xzrgWlAZeDwQHGLwPuoOOcJlh8TeG8C1ABmFBQsRpgUo2xR4H3vJM4jImWE\nAkYRkfRbHqd8WeC9RsT70jjHB8v3inj/Lcn6rItRtjPwXi7Jc4lIGaCAUUQk/erEKQ/Okl4f8R5z\n9jRQL+K4YOCn2c0iklYKGEVE0u/kyILAGMbmwFZgVqA4OCnmlDjnaR94nxJ4/wkLGo92zu2XkpqK\niMSggFFEJP0udc4dE1HWB+uCfitkZvM4YDZwonPu3NCDA9snAT9jE2Pw3u8CngWqAM8HZkWHfqai\nc27fFH8XESmDlFZHRCRJCdLqAAz23k+LKPsUGOecexcbh3hi4DUf+EvwIO+9d85dDowA3nHODcFa\nEQ8DugG/A5eFpNQBW6awNXA28LNzbljguPpY7se7gIFF+qIiIgEKGEVEkvdAgn3zsdnPoZ4EPsTy\nLl4AbMSCuL9571eEHui9/zaQvPteoCMWCK4C3gIe8t7Pjjh+u3PudOA64DLgcsABSwLXHJv81xMR\nCac8jCIiaRKS97C99/7L7NZGRKToNIZRRERERBJSwCgiIiIiCSlgFBEREZGENIZRRERERBJSC6OI\niIiIJKSAUUREREQSUsAoIiIiIgkpYBQRERGRhBQwioiIiEhCChhFREREJKH/Byorjo9NIngvAAAA\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "807_O4wGYcUk",
        "colab_type": "text"
      },
      "source": [
        "# Model Saving"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IPq-yS3MldM9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# keras library import  for Saving and loading model and weights\n",
        "\n",
        "from keras.models import model_from_json\n",
        "from keras.models import load_model\n",
        "\n",
        "# serialize model to JSON\n",
        "#  the keras model which is trained is defined as 'model' in this example\n",
        "model_json = model.to_json()\n",
        "\n",
        "\n",
        "with open(\"StoredModel.json\", \"w\") as json_file:\n",
        "    json_file.write(model_json)\n",
        "\n",
        "# serialize weights to HDF5\n",
        "model.save_weights(\"modelWeights.h5\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zlP0qYVKmdcv",
        "colab_type": "text"
      },
      "source": [
        "## Using the stored Model to predict & Test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7OE3swDDmhBb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 92
        },
        "outputId": "933c704d-9053-4f87-b77c-f480ce11fdfd"
      },
      "source": [
        "# load json and create model\n",
        "json_file = open('StoredModel.json', 'r')\n",
        "\n",
        "loaded_model_json = json_file.read()\n",
        "json_file.close()\n",
        "loaded_model = model_from_json(loaded_model_json)\n",
        "\n",
        "# load weights into new model\n",
        "loaded_model.load_weights(\"modelWeights.h5\")\n",
        "print(\"Loaded model from disk\")\n",
        "\n",
        "loaded_model.save('finalModel.hdf5')\n",
        "loaded_model=load_model('finalModel.hdf5')"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Loaded model from disk\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/keras/engine/saving.py:292: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.\n",
            "  warnings.warn('No training configuration found in save file: '\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8SNj81Vm8nw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        },
        "outputId": "244fb64f-06d8-4395-848c-58865c397391"
      },
      "source": [
        "file = h5py.File('Dataset_test.h5', 'r')\n",
        "imgs_test = file.get('images')\n",
        "#imgs_mask_test = file.get('masks')\n",
        "imgs_test = np.array(imgs_test)\n",
        "#imgs_mask_test = np.array(imgs_mask_test)\n",
        "imgs_test = imgs_test.astype('float32')\n",
        "imgs_test -= mean\n",
        "imgs_test /= std\n",
        "\n",
        "print('*'*30)\n",
        "print('Loading saved weights...')\n",
        "print('*'*30)\n",
        "loaded_model.load_weights('modelWeights.h5')\n",
        "\n",
        "print('*'*30)\n",
        "print('Predicting masks on test data...')\n",
        "print('*'*30)\n",
        "imgs_mask_test = loaded_model.predict(imgs_test, verbose=1)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Loading saved weights...\n",
            "******************************\n",
            "******************************\n",
            "Predicting masks on test data...\n",
            "******************************\n",
            "49/49 [==============================] - 1s 28ms/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EEd2AVgZnWsB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "198529f1-5560-497b-8aea-f53e0837f3c3"
      },
      "source": [
        "print('*' * 30)\n",
        "print('Saving predicted masks to files...')\n",
        "print('*' * 30)\n",
        "pred_dir = 'PredictionsFromLoadedModel'\n",
        "if not os.path.exists(pred_dir):\n",
        "    os.mkdir(pred_dir)\n",
        "for i, image in enumerate(imgs_mask_test):\n",
        "    image = (image * 255).astype(np.uint8)\n",
        "    cv2.imwrite(os.path.join(pred_dir, str(i + 1) + '_pred.png'), image)"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "******************************\n",
            "Saving predicted masks to files...\n",
            "******************************\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}