StableDiffusion_inpainting_demo.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9NENcrgDJv9q"
      },
      "source": [
        "論文  \n",
        "https://arxiv.org/abs/2112.10752<br>\n",
        "<br>\n",
        "GitHub  \n",
        "https://github.com/CompVis/stable-diffusion<br>\n",
        "<br>\n",
        "<a href=\"https://colab.research.google.com/github/kaz12tech/ai_demos/blob/master/StableDiffusion_inpainting_demo.ipynb\" target=\"_blank\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LHqYjlJ4Jv9u"
      },
      "source": [
        "# 環境セットアップ"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z7jySK7RJv9v"
      },
      "source": [
        "## GPU確認"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2PcII5fLdHnJ",
        "outputId": "8df0c455-6899-4d0b-92e0-39b0204e9a77"
      },
      "outputs": [],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aaAzHlBvJv9y"
      },
      "source": [
        "## GitHubからコード取得"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R-Y5auuvnnnT",
        "outputId": "2f37a3c8-cd76-4a62-a968-32bc004b5e9b"
      },
      "outputs": [],
      "source": [
        "%cd /content\n",
        "\n",
        "!git clone https://github.com/huggingface/diffusers.git\n",
        "!sed -E -i \"s/sample\\(generator=generator\\)/sample\\(\\)/\" /content/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4tp-fduPJv9z"
      },
      "source": [
        "## ライブラリのインストール"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LScsvO3UppqT",
        "outputId": "d2109570-e6ce-4055-b97f-d43d3a8349a6"
      },
      "outputs": [],
      "source": [
        "%cd /content\n",
        "\n",
        "!pip install diffusers transformers scipy ftfy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ka3Dh7n9Jv92"
      },
      "source": [
        "## Access Token取得\n",
        "[Huggingface](https://huggingface.co/)にSign Up後メール認証<br>\n",
        "その後、[CompVis/stable-diffusion-v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4)にアクセスし以下に同意<br>\n",
        "![image.png](data:image/png;base64,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)\n",
        "<br><br>\n",
        "その後、Settings → Access Token\n",
        "![image.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAAGPCAYAAACgWfErAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAGYgSURBVHhe7d0NeFvlgSf6v2wnkSEpcglUokmJTEKRh7RRClOsabpFnmQm9oZt7A3P1r7hGXBgH7DLs8Ru7m3iZu6kDr2X2HQv2PAsoDIX1mYX1k6fybXSKRulO2mltKRW2mQiPgIKjYsFCVgQEyuxLd33PR+2pPgzlmP75P+DN+95zzn6sOz36K/3fMiUEEBERERkEFlaTURERGQIDDdERERkKAw3REREZCg85oaIiIim7I334jj87iBO/DmO0x8n8FmfGi++kGvC0utNKPhyFu66JRt35k//uArDDREREV22vb8fwP/47QDeF4FmIm4WQefffzMHG7+Ro83JPIYbIiIimrS3uuP4z//cj2On40pbjs7c7ciG8+Zs5N9oQt61JmV+z+cJvPdRAsH3B3EwNKiM6kgrl2bhP/3NPHzVlvmRHIYbIiIimpQD/zqIf9h7EXGRIGSoeeDb8/DN/CycPnkeC8/24pozFxCPDqI/kY349fPx+Q3zceGGXOTnm/Hbd+P42b/0KyEnS+Sfv984H0V/ka3dc2Yw3BARERlA7+d9Sr3w2lylni4y2Px9+0VleoMzBz8omYd33ojCergLceRgICsbg1nzRBHTsp3IQv+gWg+KsDP4b+Zj1dcWYE9HP/YFB5T7+YfSzAYchhsiIiIDuBLhRu6KetBzQRmxue9bOfi3K7Nh/tV7yAmfw2COFmiy54syDwMmtd0fF4FGlIHBLFHE9KAJZocJ1981Hx1/GMBLvx5QRnCer1yQsV1UPBWciIiIJkQeYyODjRyxKVmZhYVtf0TOWx8jPhAXJSFCjAgwShFhBtlKsJGjOYOyiKAzaMoS7Wz0HstC5BcDKPl6jnJf8j7lfWfKuOFmYGAQ/f0DuNjfrxQ5LefR7PTZuc/RP6AO89H06u09j76+mNYiIjI2eVaUPHhYHmMjd0Xl/vPbMP35HNA/iISIBfFBkyiiFuFG7n6SAWcwIXdHiVqGmoQJiYSsAVGh708mnP1tXLkveZ/yvuVjZMKou6UuXLiIT6Kfaa2RfdHyBSxYMF9r0ZXw68NBJcCkK/hqPsJ/+mDozXbZV25S5lHmyVDzflc3Ll7sFx01gXnz5mFlwXJtKY3m/dPd+JdAp/K6SfPnz8O3C1fj5qU2pX0lRd/0oROr4b7Nos2ZArktnr4zWo2Lr1vGTfduqYpnYsrp3vIA4K9Ee/Bl7x+RMIngkpWDeI7cFTUf/fPMuJidq9T9WfPV0Ro5aiNDTVyEH1mUICRDkEmkHOCaEqBHhB15gLI8TbzlEbP2iJdv1HDTHTkjlqqncY1K3NRmvUFrjCMagOd5P6Ji0rLcCbslF7aVhXAsVhfTxHhf/zWys7NxTe4CpX3x4gAuXFQP7Eo3uYATRXh/G9qPy9+Q+B3dXoqy9XZkYNNvGPJNueuDj/DpZ+KTinBeBMnTf/4QNy7Og/vbf6nMm7CrsD/8z1/9Fuc+P4+77liptA8fOYZF116Dv/7ON5X2ZERPetG2N6S8fljsQOnGYvEaKosmJPBjE1zwI/GjQm3O5Ym8VgHbvUBbdwtKrdrMuSzp7xJmGxy3W5FnWw2nCIFjv91E0H6fDWVoQ/dLpRjvpTDc6yac6xUfOkd8Nx22aNG12tT0mM5wIy/Q91jLBWWE5b/83QJk1R9QRmsgDx426cfZLED/fBlursHFHLMyTx5YLEdu5K4oOXITjyfE7dSQo6QPrax6LAv/8cULyhlUP61YMOUL/Y16608/61UCzic9n+L8+T7EYheUIqflPLlMrjNhvWF4t7Wgs0dumILwvlyDkhtsKNrpUzvSRB3ZLTpFq+hKV4LssCbsPqw1ZwkZbBaKNwVZvvCF4c5y/RctWP212/AXt92itE/96YMJ7qKKwvvoarj2BNCz2A774h4Eny6CQ7zOYW2Nq50MMm++HVaCjdw1K0POm++cwueiP4z7IWAkmeoPs1ivCDL/+ua7CP7xTaVc/8XrsGypDZEPzypFTst5+nK5rrzNeKL7q7F6TSMC5yywL7eg541mFDnK0HpKW2GayDdk048DWktlvbMSTU9VwmmQN+jkv0vEuhE62I76TQ7Y3bsRGHNzb4VzcxOaNjvHDTaS4V434cf/dzN++H82DJWdu/9zSluW4B9OaGvPPfLKw5K8js2fQ5/B1B+HSQaVeFwZ6DCJOhEfRLxfzBsQ04MyxACD4i1IH61Rdl3JUCPvSAs1MuDIyXf/lFDuW9IfaypGHbl5590/jbuhkW+uK275itYaR1crypa2oex0G8qXaPMiXtSuL4H/vk74H3NqM8dxeDdMT9rR/Wr5hDrR1ETQeq8N4a0J7LhLmzXD5MjNooVqsJEGBgdx5qzcEgFf+bIVi69XP752ijcL6Vt3OfGF8T4tnPSgaEUAVWdeQOnQyEEUkYgZVuvUhweNoOuDD/GH429j3rwc8frrr6dpKNfcKvrBF/OuUxsTkan+MIvJ3VDyg9BkyNdw7N1UYXjW5SPwcA9e2Dg8VBPtisC8xDrO6MKwyxm5ibxSBtvJ2imP9sxqI/1dyte8OB/tm95Dx/12bR7NRtM5cvPwP15QjomRoypf/sN7+IL/pEglWeL/bAwou6bmoT97gbJL6mLONaKWIzhmDCpnTM2DiEKIK7um5L0Nj9ok1Ov/YdEaEYSWmJTRIXlxv2f/Tt07cbmmNu4zVdZi1O2sROCJNvj04zLPBtH+4y1wrZBvHPko2daKkPaJQY4mFD3mAQ7Vo2KdmF7XjKBcMMZtpNibrai9pwA28U6UX7gFjQeTx32iCL1SixJ5W1uBuG07wnKwQ77RrKtA/SHA85h8rCLU7lNvF/11I7YU5ovHsqHgnlq0artyrpSL8qDuwbhSYrHhXVLd4tPw2U+ieF9s6CUZasYNNlI0gks/T1hSgo187ev2h9XXaqVNea0q9gRSRhliXT40P1KCApv6WqYvH3qt5e3F78n1gPj0fVZbNNrvQRFFYI/2+1WWid/vDAxvmMTfj/XG62FeMF8r87BgvlrkG/mUDy4eqT9Ip7zY/YAL+drf727xe0g1xuvaG0LrNu13ssKFLXt8iExkMC8D4upWbFLGv40I3ce0ySSW9GATDcKj/S3aVpag+sWguOXoIvtqUbTVmzIirGxvnpZbmAi8W4tQ8bgfeKlG2RYMrXukeXg7pBvz9yXvqwyeo0l/7ytKxLYleZ3Z8fc+zI4Ckee82nZF2Tbe60HwbACN5WK7aqtDQPxNDb9eujH+LtNeN3X7EkHkYCMq9O2LuK+UHtWb/DtVt8lKSXnM6XP4jaMpffxjsa3943H1Q+TVQL+qsLzy8ML3xS9SHhws2sr4iCzyKGGlyFEb0Y8HxbQ+UqON4uiBJqVoEu+L/iLuW9IfaypGDTeDE9kwXcZofDpLYTHKRWcJan8j4X0t6FxeiZY3etDT3YbiUxWofF7943Xe34amB8Qn2sIaNL3ahrZXKyE/3451G9Ft0Py9GsQ2+xAWr+yJV0ph6VXTrXg7RvAnxXDvd6A+0IdE2IeqnAaU/SSAmNWNuldrUCr6c/lO+VhtqFtrFUGqHbVrfHD8tFP8osLw71otOt2VHd2QB3ufOfuJUpT9vBq5C+pPYgMkO5305Zu+pNTjuqMc9es9qLq3Fp7DyZv3YbGoD54HtqA5VoamQyF0769DXrsLFc/rG+UY/C+3Ahsa4AuJ30OgAbbWUtTt07fK6mtd8FQMFS8H0dPjR/NaM7qVEDrG70Esje6theugA40B0UHCftSLX3p0Fh6IOCg79BSl9wecakVFYSVOFDbD39MD/7OFCD8qXvdXhl/30V9X8df/bAVqeivhC4vXLtiC0sUx9F2h1+5yzqoc/zZOlO8qFm9yZah9MTByUOsNYPf61fBYqtAh/hZD+6pgebkYxT9W/55G1BuGrys1Qci/eV9U3sIKt9gG1GwQfWNTnbItaNvpVkeOB6LwvR4dvt9xf1/ib7erHZ6HK9GMCnjENuvETgta7tmNdu2Nf/b9vUfRLZ6+c6G2nRM/c/g1L+q3NsH8aAdCx2rhFM9v+PWSxv67TH/d5G29uypQddgpPlCK7UtrhXjdxGt0VFtBjqI/sBrelQ3wdyfQ/XoNnGfMKH1c/C7uvzKjnO+8ewr/z7P/rxJwuv4cwf/15H9RdlfrOn7xK/yT98CYRd82z0X6l2DKr1TI+kj8IrVha/mvEnP0sCI2gybZFHVChB1ld5XSFmvKeXJa/KPU8g40n59ODH1dg/5YUzFquDn7cY9y9o08pkAeBCh/ibLIaTlPLvvwo4+1tafAakOBCCAx7W/Efn8D6r9XCLvFAovVibJN5QgEQuqnpIUW5C0UdU4u8uRyi9rZxrxNtBvhowVwrFQ/2ZmXFaNygza0KjYy9dsL0PykCEmLxVKzFcXb6uDa2SGekVncfx7k4F5unnwsUeQddIXRKT7JOG6XQ+JinVXlKL9L6/SzTOit97Sp8dhR+eoJNN8dxu5Cm/hUVIHd+sGaSSKP1KPpfvV1toqfu35bJbzPtGufvsxw//AFVK13wCpfK/E6V9wLsXEKKUvV1zqGhmebUL7KKl5PK5zfq0LpMn3ZaL8HEV5PdQLLHWKZaJgt4nblKJR/B0aU0h9i8D1Xg9ZNHngedCqvq3VVJZqeqYBvq0cd3RnrdVXelIIoWCl+J/JPdKEdxfcXi9/2lfH2e39C+P0/oy92QZszOrmOXFfeZjz2B9tw4hk3wo+7YFsqPuH/uD1lZCP8Wj3qFjXB87g8yFj9W6x/rh55O+vRclJbaZLM4n7y1I2Bui3Qtj2pJvD70tgeaUDT99R1HJurUQkPQtpzmw1/733RKKKiRN70oXW7CB37y1G3KTlE+GHfLD4Q3WWHZfEIBxuP+Xc5suDaerT90K1uX+4uR/XGIPwh7cNWxI+O10pRtsGhnuRgLUZZqReeQ2FYrtBrs/k/fFf5wCgDjixl/+5vcNedq7Sl0tTfkOcKuSsKWSI+iJIQIUcWJU1oL0FCSTaioRyTIybFhxBZx+Vojvw/oYaY5JdM3l0mjXp3X7rhemXftzwzRz4B+alU+WQqpuU8uUyuM2WxPqhHjAyLdQXR/mIdqu8tQsUuH/BaeNwDW0e9jcWNyifNqL9bbgRbEUgamIiFOtG+qg+dLzaicY9WnveK24UQ7tJWSreqFPXf70SJswTVT4t1ZyCIL5g/XzlDRxZ5/I1OTuvz5TqTstCB0h+14b2+brQ8lAvfIyIQ3jf2AcUWm3ibPBpGd9JrIE+xbX26FlvWFaHqZ+LFPhZWQqbyWqMMruRtgWa834NzYz2q3ihBQXE1mveHLwldhpLSH0QwPxJBaeHqlDcPs2M1XJGA8tqM9bqK3xDcDzXAvMuNgvLdaB1lVG469Xx6DqG3xQeCP76phBd5dllykfPkMrmOXHdizHBs3IG2d/rEJ/wq5B6sQoGjQjugOIZwyAusWQ2Hsq5meQFc8CIUTkoYGTf+72uI+ICWLLk183/vfjQ+Woaye8tQ8Wgz/HmV8IVaUDp0DI7kwmrHSAFPNfbf5SjmabVCvCLJo1Ui8NitURGCtbb4PfeJPxe7CFZXkh5wLg02QMnf3o17iovGLPKkj7nqC7lqIJFfgombxM8xFG7kXC2syEoJNWpuUUZn9Gn5r7YrSzE0obrmZu2+Bf2xpmLMrJQl0pg8tkC+aSYXOU8uy4g3g/ChFHal48QQfFp06vta0OOoRP1LB3Dg+WpltdGNdxsznI91oDvoQQk6UOm0oUjb3RGTH4/Fp9mCO5xwDpVS1Pjq4B71lFzx6fcpP3r2V8ERakZRXj62iCB1Jc2fn6METFnM5uGDruS0Pl+uc1nMVri//wIOBFrgell8Cj2izR9XBN5HxQZvZxCWtbVo8h5A+65SbZn2Wo9i3N+D+OTdFOjBge87EHq6CHkrtqB9ms+MmTEp/UF8ej6jzB1BD6K9Y7+uknlVDTpOB+HZAHQ86IRt3LNepo8ML2c+7kkpEw80IzGLT/hVeMHnR8uaVtS8Isf5YoiN8fON93pNzfi/rwmZ8b93F+rkdvSXsrSh6QelcEzyPTnjr7NZfki1YvdDdWg96IP3xVrUHapH7cYrf4CzDDjpweZqIE8Bl+S3e3/6lS8inp2DhAw44v1G1vJ6N+oojjqaMxxe1NsNRQZ91CaN6SvqfUv6Y01FhgeCJisGX2sDgpvK4JYbc3lcx6Nm1P+sAZVyuHP0DwbDJnobayHKf9SCE6JDmLc3wSs+xFqW2uH8dRSWO91w351cnOow/hgsy4tR9UwHTvyyFB2Ptmq7ZgxkmR2rRWDp6Rl9IxWVO+JX2WGTG76jLah72o2WV2tQfJsV5rRspbzW6BxxRGxivwfxyW19lQhNJ3BgYweqlDcyo0nrD3L3ZyHEa9atLB1ythth8QbkWDb26zokx4rC7+1AyzE/6s11aNp/5UdwMuqS42zssK8U8bqnR7yCFthWOMWL1p064qG8Zk7Yl47xLi3uVz8a7/KM//uauLn99z6hv8tJiSF6Koryh0tgPhVC1FqJ9kM7ZtXu6W0/egLVNf8wVB77P3antGWZy6eCF3xZjQvB9wfx2ZLrlXAzmD0P8SwRckyyZCOuFDk6o+2uUo/GUcgRHH2AJ33URnGDSblvSX+sqZiZcBMTn3BOBeDZWoKKl8Ub4hPJp3VH0aN/womG4HnOozVU1qUO4FAnTqR8ChrjNmdF+Hkl6fiRAfHJDnkwyzfNVRWo29yG+se9wwcmyoPlIvobuhX2jYD/WNLIzNFWNCefbSXuL3KFT5fu67ugnPInS/LViuW0Pl+uM1HBnxYh/95G+Lr0nzuG8MtNaLJWwe1M+tkC/uGzHU61o25XB8q3V4iNmE78HvQXOuJF0/N+rSEor7UfNdtbh8+CivgQkAfOjvN7CL7SDF/SSx6LRWC7si+5MPVPEqMatT9Y4H5AhPFt9WjWz8jrFX/fTzbA/Hgl3PJ9eqzXVfw+fC8mn2kj/vbFOnnKH//0u34yp8Zr5LVvxnS0UbmmjTzjceiv9WQrmp6xomqNujvIuakO5fvrUa+d3ai8DuI169hch4pRPnBbHS4497YhoI2QRI80ouGl1ItNWJeVij5wYoxdtRP4fU3A7Ph7n6Ix/y4vRxDe7THlQpel91ehfL344DOjB1lf6kf/exV+8n/WDpVdO/5TSlsW59cLtLXnnrtuUa9BczA0iCW3XouBeQtEwJmnnuota+V7o7SL9SnfHyUCjtxuakM2Sp4ZKdQI8hCeW5aalPuW9MeailHDzZKbblSuOSEvkZ5OzpPL5DqT044K8QOYcvOQt7YG3pxyeI+1oFz/RKMfH7MyHy53AQrKPcgTnziHd24I3ypDk6MFRU4XXCuq4cV4t8lFdF8ZHCtcKFrnQv7d7XD+Uw2KlQ2NFaXP+FB5VvzRzRO3l8uXulA3dFqmHcUPViH0kAsFhQVw/TSImNjIhPe41FMRxePZH+1G04tVSW/w00ue2i2vbSPPkpJFnjmlk9P6fLnOhE4DF5zfb8ELd3ai+s5c8Xcofj+mXLieyEX9wQYUJ++eWxhG273ytE6xjr0W3Q940bxJewPQj0VyFKBIvFYFW8Mo+X6lukwhX2sv6mJ1yJ9nQ/4KcT9rmuGPyjeBsX4PMfGGFUbjGhsK3OI1X2lHdaRJOWDzSpIXm8vJGb3DZWdnjdhXxjZOfxDMd+yA95er4d2YB9uKfNgWlaDd6kHLD53acR1jva7ir/9sB8oc8jUtEv3FjfbbO1CzYYLvslN0+2234OYlE/9qBbnuuOuvqkHLcy50PupErvK3akLumnrkPu5Dg/5zLSmF52AVotudMInXLN/kQPWpCnifGb5yrmNVFazPVAxfoFO+Gd8fRIVd3qcNZf/kRMNTFdpClX19Jare2QLXSrk9aBxxtHb839d4Zsff+9SN/Xc5eYUo/5kF1Q71d64Um9jWpFxOYmbJ61/JKxCPVeYyecVg+dUI8jTt374Xx0frlitXJB7Imq+VeSLUqFckllcsliFHGc1RRm+0gKNUMuGkppxr/q0Jv303rty3fIypXp1YMo12Eb8Z1Ss+yQ7Is5VG3xzERCeJmbUzmKTxbiM/HYuPevKshxHXGGu5siztvifwHOeeGKLKqZyX/lzJFz275LVPoizLEcvGGi4e67Ub4/cwofueRvLrF+T3rS28JvVgUEkGm8mHm8nQfjejvO6KUV/XCdx2DlL+HkQ9ap8WxvqbkcvkGZjJu1DH/xtTX0tz2u0uNfXXfKb/3jMmE9vKs15Ub/Cj4vV6OAfU37s8gLvtoQLUOTvRLcIjiZd6Gi/iJ8kvtWz09ivHxLQ8bMaf93Yh8a/nlGvYDCSyMIAcUeYr3ykl6wFlNEcLOsoojhzNSXWd+NV9bX02Kp6NKeGmpngeNn5j6sNyszPc0KyTqe/iISKarOjeLcgLlKPvCXdSkI3Bt92O2hu86DTAFb0zYbrDjaRfqXiDMwf/W2E2Bv7pA1w8fRGDcfVKxQOYh0FRBkSokaM48vgbfReVGnC0OxIWLgOsxVn4r78ZwL7gQEauTKybmWNuiIiIJshyZzHKX96Cij3t8B30ieJVjlHbcrx2Du6ym9v+09/MQ5YIKDKMdPxxEDn33ITE1yy4aFoggo0octeUHK2RBxlrgWakERQ5YiODTcdRNdjI+5T3nSkcuaGJkUPLMMAQORHNTbEIgiLY+I93Iya/sXyNG+5VaV+7cZW7EiM30oF/HcTft6vHe8oRnB+UzMMfghcw6O3DQDwbcXlquLIrSp41pe6KUi7cJ/6XBw/LY2ycf5GFPR39SrCR/qF0Por+YuoHEusYboiIiGhSZMD5h70Xla+TksfgPPDtefjmLVl499Qg8GECiT8B57tEyMgyIfdmk3IdG3m6tzwrSh48/LN/6VeOsZEjNn+/MbPBRmK4ISIiokl7qzuO//zP/coxOJIMOXc7suG8OVv5Ekz9u6LklYflBfrkdWzk6d76F2PKY2zkrqiv2jJ/hAzDDREREV02eRbV//jtAN7XQst45One//6bORk5K2o0DDdERJeJm0+iYUfei+Pwe4M48eeEMjqjf7u3/K4oOaojrzwsL9CXievYjIfhhohoAripJJo6eQHGK4HhhohoBOmbxng8gcHBQQzG48o0N51E45NhJivLhOysLOVLneV0sukKOww3RERpkjeLMsj0DwyIYBNXvoJDftWG3FBfqU+gRHOZ7EvyA4HsPwMDg0r/mZeTkxJypqMvMdwQEWnSN4dyY3zhYr/69RrzZtk3NRLNQRf7B5Svslkg+lT69/VlMuQw3BARCembwn6xEZZfQGteMF98yuTF3IkyJR6PI3bhInKyszEv7UNDpgIOww0RXdVG2gTqwSbXvIC7n4imgex3fbELIwYcaar9jh9HiOiqNVKwkccHyKFzOWLDYEM0PWTfkn1M9jXZ59JNddyF4YaIrkojbTzlPDlqI4+x4a4ooukl+5jsa7LPjdYfLxd7LxFddUbbaMpjAeTZUTx4mOjKkH1N9jnZ90ZyuQGH4YaISJAbV/10byK6cmSfk31vtIBzORhuiOiqMtInQX2jKj9ByutwENGVI/uc7HvSSAHnckZv2IuJ6Kox0kYyeV5cTMsL9BHRlSP7nOx7uvH66USwFxPRVSt5gymnZeEZUkRXluxzev/TJU9fDoYbIrqq6RvVqW5MiWhqMtkXGW6I6KqQvsGcM2Fm8BO86w/gl4eO46Pzotl7HoPaonPvhfDuBzGtRWQsU+mzDDdEZHhjbRT1ZZkLO5/i7UO/wS9f10sAgRNnhgLJZH0ggs2hT+ZhyRcsyM0OwfvzX+JASF3W/fZb+P2pc2qDaI6bSF+caD9luCGiq07mgsxILuLjj87gwhdvR+Edt+Mbt1hw/s3f4L//ry5t+eT0ft6PLy27AwVfX4JFC27F39xThO/cqi0kMrjL7asMN0R01Ur+pJjpwJOz4DosyrsO1+c7ULT6JgyejeBjMf/iByeVXUl9p4/j0OtBnL4g1+7HxyeO4Fev/waHfv8BzmnDPHK30wdi+fmzIZx471Mxpxcfhj9EVLnNCKIf4KgcNTp0HB9EL3esiGhmJPfDqfZH07ne85nt0UREs0z6hjJ5A6oXeX2NBQsWYOG1ucqyy3cGgbbfIPrV72L97dqst36Dfzy+ABvK7gD8v8A/fzIPC+KLcMuXF2PpN6z4+BcH8NuLX8LKmxdh8MP3cLT3S9jw7+5A7vsh/P7YW/j4uq/C8ZWbUJAfwf7/Goal6G9RaAPe/sXPcfQLf4V7XTcAXUfw6qFPcGNBAW6Z9wF+f/wcbllfhJWLtOdANIv1ft6HCxcuKF/JIM+e0ouUfgZjenskpkT/GYYbIjIsNccMb+aGg43yr3LxMHmNjYQINwOmL2Ys3HxwvQgkeaI5cA5vv/shcMu38d1vXIePRbj5efdibPjuHbhRXgz5/d+h1d+Pb977V7hFuTjyp/j9zw/ig2V/iw2rzEqAeXeJHpTeGiXcLMKxjl/g1JfV20gf/foXOLSgEGV3Xqe0iWYzGW5yEp/AJMJNlggvWVkywMiAoy5PDTTD80eTpfZwUVizZs3akHV8nPmiFgFHDz2ZcuGzT9D10Sf46MI1WPVv/lYJNkOuXaQGG+lcDH2LrsPSoW99uA7XL8pG3/nJHCh8Dr0x4OM3D+DlVzuU8s9dMQz2X9SWE81+CXmVYtkPE/Iqxcm17JvJ9Wjzh+ssmGRD0FMQ21qtVmyzrdZqxfbcaovIok6Mu75WZ1Be/l9h3dq/wndct2PZl+Zpc0dxsR/ntUnpYv/g8HOcsHm45a4SbL5XK//hu+ruKqK5QumHoozbX7UcM8byLOXTikxBStE+vbDNNttsXwVt5ftshtqizIT8G3Dj+Q8R6tKPIn4L7/aYsXTZ+MFk+GuwbsDNNwLvht5CnzZHBiYeUkxzSSKpL8pRnKn0b2WvVnLqYVvWSottttlWaqVliLZaK9tBbbnYIIpJpejLr7RrHPjrO6/D6UNeZXfSP/5/J4Gv/qVyTM14brx+Ec69H8KJ88BNrjuwcvAk/vt/U3dLvdz+Lzh2VluRaI5IDPXPuNJ19V4pe2p6fx6rbUpc7J6hHk1ENL2UjeTQ5nG4PVxrBxQrJY54zpcycEDx5epHX08M2V9YhPlDx9+MZxAXP7sgbnMNhm7Sdw7n+udh0RfUA4uJ5gJ5QHHWwIfK2VLyYGJZ1IOI9YOH0w8iHvug4tTr3KSvyHYqtlOxnYrtVLOynfRZbmi5Ni99/StuHnLzJhNspGzMTw42Uu4iBhua40SfvKT/JvVdacT+PUw95kb7BCM/zrDNNttsG6cdH2V50j76pOVENHPS+6Pajqe19eXa/BH7d0KeTi4bIvSwZs2a9VVUy6nhthqCiGjm6P1Q75f6aM1I/Xe8WjtbSitJCYhtttlm+2prE9HMyWR/NiUudsm5RESGo2zskuhtWauT2oHE8QQGRZ3I+fIMHlBMdPWSBxSbBv6M7KEDiuUhwepBw5fzNQym+IXT8swr0cXl3bBmzZq1cWr5tQojtWUtZ4o4I/6Ji2CjhpzEvCUMN0QzQIYb9HchR363VFK4Ua5XI0KMrPRa78/p7eRauZ2krqjV6uSlNZdzudLici4foZ7ry4loRo3ZP8U/k1melVAyjvxX1HKoNrmdXnN5aju95vLUdnrN5ant9JrLU9vp9TQuV0ZwxHIimjnK7mLtv0v66ST7d+rIjVLLhakJKLXmcrVWcXl6zeVqreLy9Hr2LZdz9LZRRN/0wfdmVGsRzQ16/9RNpP+m1sPLTfHYqaF7kwfnJB+AJ4/VSf4ww+VczuVcrpsLy5XvjtLI5fK4GklfT7kycUI9oFj5Lpv5X5ldx9wMxBDtBSyWSy/KF+sKwv9OD5BXANcqK5LXCPzYBBf8SPyoUJtDNLspx9xceB9Z2eoBxfLAYtFrlX4s+64sydTm8Lz0/p+l3lBfUZ5fntwenlbbXJ7a5vLUNpentrk8tT2LlyutpKSUAYnzA+g78hE+eulP6PqvEXx87DPE+9VwNa6zAXh2VqPEkYu8h9oR0WarovDtLELB+jq0729H42Yn7O7dCIgQRDSX6X3xkv6ptCfXv4euc8OaNWvWV20tg42czpDBdz7Bp01/xGeHPsX53nk415uL07/Kwe+eGkDvmYkEHAvsd5eiZmul1k7S5Ucgdwc6j3Wg6YkmdBzzo3FxHepfC2srEM1NSn+UvVHvl1Oo1WNuZNJhzZo166u8zoTE5xdx/qVjGLwwiAsDwIX+bFHnoD+Rgziy0PlCXF45fmyLHXDf7YbbaddmJFlSjB0/dIv4o7OjcK0b3q7U8Z1ksSONKLunDu1dWrvLh+ZHSlBgM8FkK0DFngCGjtCJeFG7rghFKaUW3tHvnigj9C6Y3i8vp1bOlpIpR/6nJJ6kdnrN5altLk+tuTy1zeWp9VxYngn9v/szEhcHkBDhJh4bRP8FYOCiCQP9JgwOys2uCR+/O8HdUxMSQ/gdH5wLR/myzN4AGr/fhtXb61C6RM6Iwf9yK7ChAb5QD3oCDbC1lqJunxZvrG7UvdqGNqW8gJrbu9G3pgxuq7qYaLpoPVL9b4T+mdweb3mWSfyjdje1Yye302uJy7mcy7ncqMszod//vrqhHRwUDVFfTCDeD8QHxGyZacRDnTqorpsRp9rRvKcYVRuc2oxkYbQ+UoETj7Zgx116+DHD/cMXULXeAavFAsuyYlTcCzQfDQ0tt8j5opjfaEZloAKNjxWmHLBMNB3G65+TWT78reDKQvEv22yzzfZV2s6IrHlImOSZHuIeta92iA+IRxBZR/sy8gwS4WVnDWLPNaFyuTZrSA8CP65ARbgGdd+7dPeWPF289elabFlXhKqfRYBj4dQDl3t9qLvPj+qf1qBwoTaPaBplsj8rZ0vJhlLJmm222Wb7Km1nQvaamzE434yECDlxU7YaaOLis6Qo+kPY71brqYnCt70CNWhE04MjHJvzTCUq3ilDw8p61D6ffLBxBN5HXVi9MwjL2lo0eQ+gfVeptkwXhXdbBfyPNqNmaMSHaHplsj8rIzcsLCwsLJkJN/O/YcWFeYsQy7kG/dlmDJjmIy42t+IRtDWAL+arIzuXL4bAj4tRcbwM3mfKMUK0AZZVo+WZGtRsa4T5oVq0ntLmH21B3dNutLxag+LbrDDnaPOTRPfVoTJYjebHnNwdRVfMSH3ycotytpRMO6xZs2Z9tdeZkJWbA8vf5aM324KY6RoMaLupEtoD3Pkfs2DKViYvkww2bri8JWh5rhL2gSiiUbXEtDUUxW51d9KycjQ8F0PNzuTr5UTRo58eFfGi6Xm/1hC62lH1UCdqn90BJ5MNXUHp/XFKdbzv7cx8XCEimmXkJ7hkelv9dKfW+hWK44NxwLwiY1coTvQnEH23H+H/JaaRjWV3Z+GLt5gmFGyUKwzv1BpD6uFP7EDhkd2w3VmXdmE/qRQtp9tQvmSkKxQH0VhYjM5H/Wj5HuB9tAIlr0XhXgZ026vg2dQN1ysF6H61HN0/sWH19vR7H75voumgXKE49s7QFYqzxAcC9crEMrDIuDJc69LbyUyJvrdEF9dWkJXS+dlWsM0229qEVs2xtjygd6S2Em7ElHLAr5hWwo2YTizIXLiZ7WJypCfHAgsPFqZZQIYbU+xtEW6y1XCTJcKNmK8GHDGl/i/nKP+O1E7u/6b4+Tf1o3EEMSEXsq1hm22253JbCTMjtNWRG7Wt/KeM3Ijbmm+9asIN0WyijNz0vYWsHH3kJlvpuvLEQ3WERoQcuWJSf05vJ/d/U6JPhBsiIgPSd0Pp9LYabtQ6ebdUwvxVhhuiGaCO3Ihwk6ndUvHzIXXkRvZ51qxZszZQLb/pe6S28g3gcrYMNfK/QXW3FMy3MdwQzQB15OZNdeRGhBZ1t5T4T47cyE6r/K/Wen9ObyfXpkSfCDdERAY0+ZEbhhuimaCO3Ihwk7mRmxMMN0RkSJMNN8h1MNwQzQB15CaUsXCTJbq3Moqj1MoE22yzzfbV2iaimTNe/5x4Wwk32t5n7VMN22yzzfbV2iaimZPeHy+/bUqcPy6nhsiGmnxGxuVczuWj4/LZtTw9sMhr2sjlcr5cJOuUY25y/4K7pYhmgLpb6l+RPcZuKdlI7t/pu6WS+78p/vkxrbfLFmvWrFkbpx73bCk93OhnS+XeznBDNAPUcHNcPeZGhJapni0lb61Ms2bNmvVVV6uTKW0imjkp/XEqdfzzP8qsQ0RkOOm7pfT20G4p8Z8csVF2S8lRHY7cEM2IoZEbuUtKKdrIjQwq2u6n9N1Q6e1kWfIf9cZqkd09tc3lqW0uT21zeWqby1Pbc2i52iSiGZPUP7U5Q21lxiT6d/zzo0kfbeTS1E86qbicy7l8dFw+25arAzX6PPmFmXFl6tKRG2gjNys5ckM0A9SRmz8qIzbi/xFGbtTpYZe2k/u/Em70WaxZs2ZtpFo9flg9eFhti092Wi1nxuUykWzk9ftkncj9mlhKRDNChJtsGWpEuJG17LVZssOKFCMrvVb7s5hS/x/q3yl1vDeo9nadvlTHNttsD2N7TrWVgRqTnKkaOltKH7kR/6ingsuRG/FP7tc5ckM0A5SRm/N/0K5QrI3cJESEEdNDx9zIzjvUv/XAozRUSf1/+GwpQV+RbRXb6j9sq9hW/zF0m4hmTnp/nEo73ts5/LGGiMhA5OiM+nFONfrZUtrIzTWrOHJDNAPUkZujYxxzM1yr1GWjEXcherhcwaQeZcw222yzffW2iWjm6P1R/D9i/5xEO957RGuJijVr1qwNVOsjNcNt5SAcpU4k5KHGw6M2ytlS1zg5ckM0A9SRm05kZWUnjdyI3ipSixpchmu1P4vlIsQMt1NrcRdiUlmBNWvWrFkT0cyZaD8dt46feyOhBB2dnM/2MLbZZnvYHGtP7GwpedyNeuwNrvkGR26IZoAycvP577WzpdSrFE/5bKkUbKdiOxXbqdhONdfbRDRzMtifs5SPLzLusGbNmvXVXhPRzJloP51AnTU0ZCsSjxJ62FaabLPNtqyvsjYRzZxM9uf4ucNaS5KLk5psi8L2MLbZnltt9WwpfZ5+tpSYI2YpRTlbSj/mRsy49k4ec0M0A9Rjbn6nnCU1/K3gotdecraUTj9bSpfa/5WzpZR5Sq0tYFur2VZrtWKbbbVWK8O2iWjmZKg/m+LnAuzRRGRIysBN0qc5/bo36siNvD7x8KiNcrbUtd80xMjNYO95YOE1yFZbiIaCONoVx/V/8TUUfEH8nEPLpi71sYgujzpy89ukkRt5NpQcrRkesZnMFYpNooMz3BCRIaVv3obDjTwVXC3qBfzUIg9DvPLh5lO8feg4Psy7HWtuv06bB3zwxm/w0Y1/hVU3azNG1Y++zwaR+wWz2rwQwr7X3sKCb3wX6xyi/f7v0Oo/B3vBTVhyI3D0QNKyyzDYew6DuYswX6aZ9Mciukwy3JgQ18KNWtRgoxYpNdxc2k6m7pYiIqKMOXv2LE6dOqUUOT22i/j4ozN4+9gf8PZ5bZbQ+/EZdJ/TGmP58Dj2vX4cH2tNLLgVf3NPEb5zq9Y+F0Nf3hIUft2Bpba0ZZN2Br//5W/w+4+0ZvpjEc0SDDdERBkUiUTw0Ucf4fz580qR03Le2MxYtjiGI290ae0RRD/A0UO/wS99R/D2h/3qvPMf4t1wFBcGz+HUH0I48d6nYmYvPgx/iOgFMflxF06cjQEXPsGJP3ThXPIyzeCH7+H38n4PHccH0UFtbj8+fvuPOPT6b/Ar/0l8fFHOi+GjUBc+HhhE9H3xWKPe30kEfOn3JyLcByfx7gexoeWHfv8Bzg0tHsS594+nPR7R5WO4ISLKIBlmLly4oJSLFy8q9ZkzZ7Slo7vGsRxf+vA4ftetzUjWdQSvdgTx0YIvYsl1cZw4+AvsP540zJMiguPHRJCQOecSqcv6jv8LWn1v42N5v9ecxx+OhiFzxUf+f8GvRM66/sYvYtFnb+Hnr4eU+Zca4f4Ovo+B68T9LfgEv+p4HYEuNcGcO3US/sP/gp//4Tyuu34R+t77HX75hnbDd3+HnwfOYNFtt+KWBR/id0c+EHGH6PIx3BARZVAsFhsKN3Jalr6+Pm3pGLLz4Vo+D8d+fxypa8dw7A9dyL7lW1j3lw4UfOMv8V3nF/Fh6Dg+uOZLuOXmRViQvQjLvi6W5Q8fs6O4fgkKFpsBEV4Kvr4Ei7TZqg9wJPQpFq/8ztD9rv/OcswXS250FaHM/TVxGwe+8e2bcWPPGZyCGTc6lsCSnQ3LzWL9Ue7vJud3sOYbYvlffhvFt2ThxB/eHgpGF3OX4rvr5P1+Dd+5ZRGiUXVE69wn53Bx4fW45aYbsPQbf4X1rpt4gDJNCcMNEVEGWSyWoWCjh5y8vDxt6dhyV9+BVYPvw/928rjFOfTG5uFGa1JwuXERFl2IoVdrXh5xvxeuwZJ87UDkZBfP4MShg2hr+wVe/Z8fiDUnQr2/G5cOxxLLF69Fduzz4dubsoZCy/z587QpYNHqr2OV6TTaXv0F9nO3FGUAww0RUQbdeuutuOGGGzAwMKCUG2+8EStWrNCWjuc6fOPrN+DDY8HhA4QV/UgZ/IldVHbbTH10Q9zvJcnlU/x+/2G8a74d3y37W9x7z82YWDST0u7v4iAGTdnjP8/sL+EbJSX4u+86cXPvW/j5L45PMFARjYzhhogowwoKCvDXf/3XKCoqUqYnZdnX8M1FHyL8uR4JbsDNN87DB6fe0nZXDeKjd8/i/OIvYanSFgbjSDqmd4JuxpK8GE6G3teObxnEuag8jucMPj43D4ttNyihZPD0p2lBYxADIz6Yen+n3vlQa5/HCXHbRdYlsGhzRnX2Q3W0JvdL4vX6EnI//zQt3BFNDsMNEdGsYsYthTdjUd/wrqmbXHdg5eBJ/Pf/1oGX/5sX3rNfRNFffVU5Pga2m7Es5wP8Ui47cFJZf2LMWPntr+Gmj4P4R+1+9/3mPURhh+PmQZw4tA8vv9qBn78JLFIeSLoBt96UjbcDctlv8G7KUb/q/d344e+0+zuA34v7WvfNG7Tlo+nHBydP4J/b96Htnw6g9dcf4ppbb8UybSnR5eBF/IjIsNI3b3pb1nqZ+Yv4TULfOZwbNGPRwuHjVVT96OuJIfsL2sX1Jmmw91NczF6I3NzhG480TzfWMmm85SOTP8N54NrrkDsUpuhqkemL+DHcEJFhpW/e9Las9TKnwg2RQfEKxURERERjYLghIiIiQ2G4ISIiIkNhuCEiIiJDYbghIiIiQ2G4ISIiIkNhuCEimgWib/rgezOqta6Qk154Dk/kMaMIvOhFWGsRzXYMN0REGRY97EHjiwERCSYu9FoRil4Laa0rIQrvk/WImlO/HCHWFYTvoA/Brpg2R7LAHG1E474rHL6ILhPDDRFRhsXCXtTuDyM5Hsw6J9vQfLYaFau0tni2wadLYL+7Du3721F3tx0VrwyP1Tg3VyH2bBtHb2hOYLghIroKhQ+2wrzRDavWxskW1D1uQePrHWh6ogkdrzciVl4Nj/51VYvdKLY2o/2o1iaaxRhuiIim25FmFG33IhLxobG8ADaTDQXlzQj2ast1/T0IvVKLkpU2mGwFqNiTvmsriuCL1UPLSx7xIKivMBBA4z1laDw8PF4U3V+LokfaEdHaw8II7AeK7xyKNkrY8W6uRKn+jZXLilH5sBfeN/RbW+AszIP/GMduaPZjuCEimm4DUfj216Pi0QCcj/sR6m5BRbgalc8GtRU0P65Hc6wMTYdC6N5fh7x2Fyqe18NEDIEfF2P1cxZU7QuhJ9SBqsWtKF6/GwEZknIKUfmgDQ2PidCkrB5A83Y/ih8qHR6dGRLBib2FKFiuNYXIaR9KV9ph1toyzNhWONF+cjjM2B2FaH/n0qhENNsw3BARXQlH3ah/dQfcyyywWN0of6QUwTdCqaMquxrRdH8h7BYLrKvKUb+tEt5n2tWwcrIF9Ttz0fRiPYrlfVjsKN71Aurz6lD/mhpALBvq0LyiAXXPhxB6uR5tGxpRNXRMTZKuMEJI/oLQCMJviion9UtDbVa7/LLuYQvz4HwzPMJIENHswnBDRHRFpAaH3BxtYgwWmwgXR8PojsqDlEPwwo3Vt2kLFXYUFALekH7wshWlIiCZd5ag5AkHGrYVJo3EpNlkF7eegHlaLS22Tew2RDOM4YaIaA6IxcY496o3NnxmVrQb3ehD3+K8tDiV5rVw0plPVthXipv29mltVfcpP6w5SfEo1jep09uJZgrDDRHRLBXtFvFjlR02C2BZaodTxJHus9pCRRRyFecKG9Sr1YTh2d4A10tBtKxpQs3TwZFPR18swowIQMnsy0vhCwSTwksEoWAEZbcnjdWcjcC3zKo9FtHsxXBDRDRbHOtEUA8vp9pRt6sD5dsrRKgRVlWgbnMH6p/wIjKgrIHo6w1o2F+Ouk3KGgi/XIu6xc2oXWuFe5sHq5+qQvNIp26b7XCsDeCEfpq3YF1biar9DWjWzraKHfag6dAOlK4djjLhdzrhXpF80DHR7MRwQ0Q0S1TeaUbLvTaYTCaY7LXofsCL5k36uU5WlD7jQ1W0Fs55+chfYYJjaxgV+z0oXSIWn2pF3bYY6ndqZ0ctLkbdU3Y0PNyoHpCcwo7V63sQDCXtZBLrN+wtgW+jPI6nAPbNneK+6+AeSjJRhAJhFN/Jo25o9jMlBG2aiMhQ0jdvelvWeonH40MlIT7vLbx2zCNVrohYNIqY2QLLaEMkvVFEB8ywjLrCBJz0oOTxPLT8rDRtN1MM0WgMZosldYTmbDu2rA2jKlijjiQRZVDv530wIY6srKyhooR8rUh6rUtvJ+PIDRHRLCODxZi5ZaE8FXwKwUZaXoZKeNCWtGtKJUNTWrARwns9wM5KBhuaExhuiIiuShaUPlqK8ISuOBxGMFyKqo08lJjmBu6WIiLDSt+86W1Z62U27pYiutpwtxQRERHRGBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUPj1C0RkWOmbN70ta72kf/0CEc2MTH79AsMNERlW+uZNb8taL+nhht8tRXTl8buliIiIiMbAcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0REMyCGyBEfgl0xrT2eya5PVzOGGyKiWSUM755GtB5NfxOPIvBiI7wnteY0C+9rROPTPkS0djJl2R6veKZTEYXviSLUH4pq7fFMdn26mjHcEBFNk57oZ0qZnAiC22pRsb0lLTzEEN5fi+BZrTnNIkdrUfvobnRcEqaCaN8plm0Ljhh8iGYDhhsiomnySfScUiavElXLdqNx38yOUpRusqB5X1BraY760LKyHOVak2g2YrghIpp1euDauAPhh+rh69VmjSJysBEVK20wmfLheqAZQS0PhV/ZgqKt3qTRlRA89xahem/SeMvJVmxZ14jAgNZOY99QhtUv+ZAcb4Kvt8C9xo1Ljnw55cXuB1zIN5mQX7gFu/en77SKIfRKLUrkc7UVoGLPCWC5tmhIVF1nhUlZp2RbO8KjPDeisTDcEBFl0GfnPseHZz5RSn//gFL0tlw2YY4K1GxuQd3zaSMnSSKvVcC5vQcV+8JI9HeiudCP4odalUBjdzjQ81MfTugp5KQfre/0wP96p4gQqmjID89yBxw52ow04RwHip0t8B3VZiAA73PFKL47V2trTrWiorASJwqb4e8Rj/FsIcKPulDxynDACb9SCffWbhQ/70dPyIe62wNoeVFbqIgh+JNiuPc7UB/oQyLsQ1VOA8p+Erg0SBGNg+GGiCiDIlqQkeVif79S9LZcNnFmuLd5sPqJerSe0malCMDzaAi1z9ajeJkZyLHA+WAtat9pg0+uv8qFMmsLAsfVtaOhICxba1H8rA+dSlqIofNQM0rXrIZFWWMkNrg3utCwL6C0Ygc74Nnkhks83LAYfM/VoHWTB54HnbBaLLCuqkTTMxXwbfXApzxWAK1bW1HyTDOq7rLDYrHCsb4SFWuUO1B1taN+ewGan6yEc7F4ALMVxdvq4NrZkTJyRDQRDDdERBl0a/5SfK1guVKuvSZXKXpbLpuUxcWo2RVDzRPeodGWISdPwBexIfy6PHNJL23oRDvCyp4nJwo3R+ALytETGWT8cK0shuthH4JvyuUhBF52o/hOq2yMyrK2FJUvdYiQEoP/dR+q7nWL2JWsG+EjEZQWrk6Zb3ashisSQLhLNLrC6IyUwn3n6DEqFhLPfFUfOl9M+nmel2dkhdT7IJoEhhsiolnMvrke1cE6NB/u0+ZoeqPogQ2OO5xwDhU3Kp88gFLlWBYzVq+pgu/1gDz/CoG9ZXCtsoh5dnjfEIHnZCd81mKsvuS4lzRmF9ybWsX9+OA7WAb3Km3+kCiiZ7TJS/QgKo8ZivWNu2spJsITFtpRkPLzlKLGVwf3Ym0logliuCEimibZ2VlKmRKzEzW73Gh6MgDcps2TljngkieL29xw351aHFoYsDhdKH2tEycO+9G2sRBOMc/qcKFHBJ5gKAjfWicc6qpjMMN9TyVat1bDd69buY9UdjgKgXBXt9bWnO0Wz84FxzIxvdgm1gqje4zT2C1L7XD+OgrLnek/jxPW1KEionEx3BARTZNlS21KmSrz2lo0ogY1z2szJIsblY/3of5xD0JD+6xiiHQl7cBaUojitT60v+SH484CdbeRPBbnkB8th9pQtSZ1V9Ko7ipG1UIHKjdcGm3EE4H7gXqYt9Wj+bj22L0heJ5sgPnxSrjlniiLC8UPd6Phydahs5+iR1rEc1CnFasqULe5Tfw8XkT0M6QGoghHeDgxTR7DDRHRrGdF+fZa2FOummeG84detKxoR0meDQXuIhTYClD5jD/p9G87Vq8Hmp+Nwu3Uj62Rx+I0o3GPCy7n6MfApHKiJtiBylF2YZnv2AHvL1fDuzEPthX5sC0qQbvVg5YfOrXwZEHxE17UxeqQP88Ek8mGslYbKre6laUqK0qf8aHybC2c8/LhWudC/lIX6vbpZ1xZ4SgsRPvOGrSPeIA10TBTQtCmiYgMJX3zprdlrZd4PD5UEuLz3sJr005zngsGYoj2xmBeaIF5lNO6rwzxPKIxkXYssIwyJBSLRhHLEcsXajNGEotCvRvx82izdPL2GGE+zW29n/fBhDiysrKGiskkg7BaJL3WpbeTMdwQkWGlb970tqz1YohwQzTHZTrccLcUERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERkKww0REREZCsMNERERGQrDDRERERmKKSFo00REhpK+edPbstZLPB4fKgnxeW/htbnKOjMnDO+edkTXVqF8lVmbJ0UReNGDnjU1KF6uzZpG4X2NaH9TTJhtcNxuhTmvAK5VolYXE2VU7+d9MCGOrKysoWIymYaKpNe69HYyjtwQEU2TnuhnSpmcCILbalGxvUXEnGQxhPfXInhWa06zyNFa1B4UzyDWjdDBdjRudiJ3xRZ43oxpa0xEELttZWjt0prT7chu2O5tFa8gXe0YboiIpskn0XNKmbxKVC3bjcZ9Ua09QworUPODGtTsakLHsRBObO3Blrtr4Z1wwBJB6EomjYEr+3A0ezHcEBHNOj1wbdyB8EP18PVqs0YROdiIipU2mEz5cD3QjKCWh8KvbEHRVm/Sm30InnuLUL036e3/ZCu2rGtEQISC8VngeLgODdZmNO/Tx5Ri4vGbUX1PAWwmE2wrK9D4a+0JHGlG0boaeOBH/X1FYroIzUfkgjFuo4gisGcLXCtMMNkKULKtFaHkxREfGsvV2+YXbhH3qS4MPi0e4zEPcKgeFeKxitaJ10JZQlcjhhsiogz67Nzn+PDMJ0rp7x9Qit6WyybMUYGazS2oe370t+jIaxVwbu9BhQgbif5ONBf6UfyQulvG7nCg56c+nND3Ip30o/WdHvhf7xTxQRUN+eFZ7oAjR5sxLifc91rhfSOk3kevuP0rQPETPoR6xH0/bkPLpjp1ZGdVJdqerBS3cKHmqTa0vdqGylXj3EaI7q2F66ADjYEEEmERjJxinv78utpR4axDz+YOhPsT6Hy2EP4NlcpuL+f9bWh6QKxcWIMm8Vhtr8rHpqsVww0RUQZFtCAjy8X+fqXobbls4sxwb/Ng9RP1aD2lzUoRgOfREGqfrUfxMjOQY4HzwVrUvtMGn1x/lQtl1hYEjqtrR0NBWLbWovhZHzqVwBND56FmlK5ZDYuyxsTYlrmAs1G5wwlY6MaO56pQfJsVFosF9g0VKEMzgifFshyzmKcenJ0rlsnlZhlSxrqNED7VCYjA5VwsGmbxM32vHIUL1WWBF6sQ2tqM+vV25b4sIkDVbgujTR4btNCCPLleTi7ylMfjoc9XM4YbIqIMujV/Kb5WsFwp116TqxS9LZdNyuJi1OyKoeYJ79Boy5CTJ+CL2BB+vRGNe/TShk60I6zseXKicHMEvqDchSSDjB+ulcVwPexDUJ4FhRACL7tRfKdVNiasrzftmQxEETrYiuZtW1C0rgoe8did6hMY3Ri3cW6sR9UbJSgorkbz/nDSzx3GiUMR2MK+pJ+3EW1BoP3UOI9HVx2GGyKiWcy+uR7VwTo0H+7T5mhEyOiBDY47nHAOFTcqnzyAUuVUcTNWr6mC7/UAIggisLcMrlUWMc8O7xsi8JzshM9ajNWTOq1chJKgD9aVdiiRqMuL6jWrUXfEAvfWJhz4ZTvqNykrjm682ywrRlOgBwe+70Do6SLkrdgiwotcEEX0DGBzJP+8Trjvb8CBTQ7lpkQ6hhsiommSnZ2llCkxO1Gzy42mJwPAbdo8aZkDLnmyuM0N992pxSF36QgWpwulr3XixGE/2jYWKsegWB0u9IjAEwwF4VvrxKRiwck2ND/rRLW4nRR8TYSutS1o+0ExHNaJ7Qaa2G0ssK+vQpP3BA5s7EDVK/K4IzschUA4x3bJz+u+bTI71uhqwHBDRDRNli21KWWqzGtr0Yga1DyvzZAsblQ+3of6xz1JZxPFEOlK2m20pBDFa31of8kPx50F6gX45LE4h/xoOdSGqjWrJ3RRvlg0gtD+RpSt34KeXc2ouSvpVtGeoV1Hkf1N8BzSGtISEUjgR2co7do4Y9wm+EozfEl7mWKxCGzKw1ngfqAefbvq4Tk+/DPGuiJD92VdKqLaIRHmxjnDjIyP4YaIaNazonx7Lewph5aY4fyhFy0r2lGSZ0OBuwgFtgJUPuNPOv3bjtXrgeZno3A79WNr5LE4zWjc44LLOc6Ix04X5FVgc/OcKNsTguup9+D7UeFQINKPj3GsLIJrZQFqTpag6n5toaIQZU8VoGVdAVyF+ajeFx3nNjFx32E0rlF/nqKVdlRHRPh5UB0pMt+xA96XCtC+MQ82cfuilWK9h5rg13/gb5WhydGCIqf42VZUwzucgegqY0ro1yMnIjKY9M2b3pa1Xmbf1y9choEYor0iGCzUzki6osRjR8d57N4oogPy7Ck9Fo1/m1g0iliOBRbtTKl0Yy1XlpnFsokMS9GskOmvX2C4ISLDSt+86W1Z68UQ4YZojuN3SxERERGNgeGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhoiIiAyF4YaIiIgMheGGiIiIDIXhhohoVgnDu6cRrUdjWlsXReDFRnhPas0rIHrSC494Lo2yvOhFOKotIJrlGG6IiKZJT/QzpUxOBMFttajY3iJiTrIYwvtrETyrNadZdH81Vq9pROCcBfblFvS80YwiRxlaT2krEM1ipoSgTRMRGUr65k1vy1ov8Xh8qCTE572F1+Yq62TCu6f+rNS3LPuyUk9MALtNHnQ/7APWd6Jpg0WbH0HrvTaEtyaw4y5t1rQJw7MuH4GHe/DCRv3xReDpisC8xAqz1ibKlN7P+2BCHFlZWUPFZDINFUmvdentZBy5ISKadXrg2rgD4Yfq4evVZo0icrARFSttYkOfD9cDzQhqu47Cr2xB0VaviES6EDz3FqF67/AcnGzFlnWNCAxo7SFRRI5pk0ksycHmSDOKtnsRPt6K2nsKYDPZUFAu7itpZCnW5UPzIyUosIk3KFsBKvYExD2nks9/S2G+eP7i9vfUovVNfXdcFKFXalGyQr1tybZ2hC95nkQjY7ghIsqgz859jg/PfKKU/v4BpehtuWzCHBWo2dyCuueD2oxLRV6rgHN7Dyr2hZHo70RzoR/FD7UqgcbucKDnpz6c0LPCST9a3+mB//XOoYARDfnhWe6AI0ebMcSJ8l3F8DxShtoXA4iMFCoGovC9WIktz/Wh7Ck/Qt1e1C1ug+s+j7Y7LQb/y63Ahgb4Qj3oCTTA1lqKun3D8UZ5/uU+2B8/gJ6eEDoes6PvrHzCMQR/Ugz3fgfqA31IhH2oymlA2U8CYgnR+LhbiogMK33zprdlrZdM75Z6+73TiMUuaK1UZvMC3Jq/VGuNRu6WaoD9dBvKzV5Ur/TAFRDTy9J3S4n1bFUw7+9EzSrlhkIQjc562PbK9eXyUmBfN3bcIYLMvmpURl1w3NcJd18D3OYYfNty0ezsRtv3rNrtk8UQ2tuIum11aO91oPyRetR9vxQOfS/V4d0wFQL+xA6ISnW2HVtuqIcjmPychgV/YsPqgXYkfiRvIZ+fC+FnUnd9KbpaUbbUh4ozL6B0sTYvKl6LPD8qEvXDj0eGwd1SRESzmAwvXytYrpRrr8lVit4eP9ikWVyMml0x1DzhvWR3Dk6egC8iws7r2tlMSmlDJ9oRVvY8OVG4OQJfUI6jxNB5yA/XymK4HvYh+KZcHkLgZTeK7xwp2EhmODbuQNs7fehurULuwSoUOCrGPqB4sQ12EbDCp4efbfRNH1qfrsWWdUWo+pl4YsfC6q4y5fmXwn1nWrARYiHxU6zqQ+eLST/b816ExXMOd2krEY2B4YaIaBazb65HdbAOzYf7tDma3ih6YIPjDiecQ8WNyicPoHS5XMGM1Wuq4Hs9IM+/QmBvGVyrLGKeHd43ROA52QmftRirlXXHYob17iq84POjZU0ral4ZfTdZqgi8j7qwemcQlrW1aPIeQPuuUm2ZoDz/kcViMWChHQUpP1spanx1cOsjOURjYLghIpom2dlZSpkSsxM1u9xoejIA3KbNk5Y54JJHt9jccN+dWhxaALA4XSh9rRMnDvvRtrEQTjHP6nChRwSeYCgI31onHOqql7rkOBs77CtFZOnpGf24l7Pd4hk5YV9qAY62oO5pN1perUHxbVaY04/rUZ6/f8SRGMtSO5y/jsJyZ/rP5oSVp2rRBDDcEBFNk2VLbUqZKvPaWjSiBjXPazMkixuVj/eh/nEPQkN7gWKIdCXtwFpSiOK1PrS/5IfjzgL1TKdVLpQd8qPlUBuq1qwePvsp2dFG5Zo2jQcjQ0EmdrIVTc9Y027jh/+w9ngDYbTvrEfH5jpUDB1vE0WP/nQiXjQ979cagvL87ah7bDcC+jrREHxHRWNVBeo2t4mfzTt8MPNAFOEIDyemiWG4ISKa9awo314Le9JZ3HJ3kfOHXrSsaEdJng0F7iIU2ApQ+Yw/6fRvO1avB5qfjcLt1I+tkcfiNKNxjwsu56XHuyhW1aDlORc6H3UiVzugM3dNPXIf96Fh6Lo7khnhV8tgk+vMy0ft2Up4nyoVz1ZYVYr673eixFGAosICFGwNo+T7lcqtVPL5t6Cj0IfSPBPyV+TD5KiG9x05MmRF6TM+VJ6thVPcr2udC/lLXajbp56HRTQeni1FRIaVvnnT27LWS6bPlpoRAzFEe2MwL7RcuvtnimLRqDJ6Y7aI+1ZnqZLPlopFEY2ZYbFcOg6k3D7HAstCbcZIlNuP8BjSWMvIMHi2FBERpcqRwSLzwUaSoUK5b609IrNcZ+Q1lNuPFWwk5fajPMZYy4hGwXBDREREhsLdUkRkWOmbN70ta70YYrfUTFB2hWHUERuiyeBuKSIimnnKrjAGG5qdGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFD4xZlEZFjpmze9LWu9pH9xJhHNjEx+cSbDDREZVvrmTW/LWi/p4YbfCk505fFbwYmIiIjGwHBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERDSg1WQIDDdERNMk1hVA69ONaNwjyotehKPaApqkCNrvM8F0X7uYmg5B7F5qgu0nQa1Ncx3DDRFRxsUQ/GkJ7Esr0HbaDNtyG8whD4ocZWg9pa0yHY7shu3e1mkKADPJCufmJjRtdoqpqRJBxiZ+D11aU+FA8RMNaFzv0No015kSgjZNRGQo6Zs3vS1rvcTj8aGSEJ/3Fl6bq6wzFbHXa2G/rxuNgRaUL9NmCtGuCMxLrDBr7Yw7vBumJ+3ofrU8AyHAqALYbWqA/XQbypdos2jG9X7eBxPiyMrKGiomk2moSHqtS28n48gNEVFGRdD+fCNsW2tTgo1kSQ42R5pRtN2L8JutqC3Oh6m0FWE5PxpC67YS5IsNt21lCWr3KnNVA1EE9+7GlkKxvlieX1yL1jdjyqLg00UoeswDHKpHxToxva4ZQztZIj40lhfAJm9TuAXNR8bYPxYNwvNICQps6uNXvxhE8trycer2hxF6pRYlK0woe1l9frGjHlTfIx/DhgK3fHy1NB8RC8d43grttYgMPU9xH+Xi+fdqywXl53ta/4mCaNbuP7koj4UYIgebtecif4YKNP5a+wnk46yrgQd+1N+XfJsIvFuLULsvecxLPOcXq1Gy0gaTrQAlj3gQTH4hJvCcaQaJTy5ERIYUj8dTyuDgoFIGBgYS/f39iYsXLyZisVji/Pnzid7e3sS53vPaLaeg70CiBtZE/RtaezSB+gTWliZKN+xItIW6E91n+sRtOxP1d1kT5c91Jnpk83RHYsddzkR9QDSkd15I1PywJeEP9yR6eroTnc+UJnBXQ6JTLjvXkzjxnGhvfCFxokcu125zui1Rbi1M7PC+l+jrTyR6gi+Idmmi5bS6OMU5v3h8JAp/2JF4T95HWDz+3dZE4S5/Qru3hH8XEu5NpYniH7YlTnR3J3rOiZmnWxKlKE00HetR1un+p5qEc0NTovNMj/KYYz5vSb4WqwrF/dYnDsh1ug8oz8P5xNAayuNCPA9dn/IzqqXzqeKEdXNL4j254Jy47YNNiQ7xmspl78nnYq1KdJwRy/r7Ej3HXlCe6wviucrlyvNLdCdaNiFR2totG0KfeLxC8Rx3JDqU5/xeouNH7oT1rvqEX/680gSeM02c7HuyD8q+KPuk7Juyj8q+qvfb9P48FoYbIjKs9I3hFQk32hv9iOEhmXxzRHHihXe0ttDdKt70729LqBFB1fNPVQn8aPhNPUW3CC5Jj6XcflOLeKse5t9lveQNt/NJZ6L0JSUKpHjvZ8UicDUlTmhthQgmxUnPUwkZ619Qg4Sm+9XytMcVIQnORENQa6ZLe97qa7FD3GrYey+l/izp4WaIfH7W8kRLWGtfQgRGK0RA1Joj/n7Swo3yM7sTTSG1qXov8cJ6JIp/pv3kE3jONHGZDjfcLUVElHFR9CXtdRmdCwXLtUnEcCLYDudAJzzy7CqtePaHgTfDwwcJxyII7vWg7pEyFJXXwYd2hFMOjk0WxolDEdjCvqH7k6UtCLSfSj/sOIZwyAusWY2Uw2qXF4hn6UUonPQDFRbArk1KlsV2WKN96NPaiPWhR6xhs2htadznnXqsU26ONjGmMDyP1sHyZH3qLsCBKEIHW9G8bQuK1lXBI37UzvDED7OOhUPiJ3Zj9W3aDIUdBYWANxQWr5Tucp4zXQkMN0REmbTEgdVWH4KhyZ73HUOsFzAvKYDzDudw2VSDA9vckDkhdrQZJSsr0BItQOXjLTjg86BavfEoooieAWyOpPsTxX1/Aw5sSj8zSH380YhP09rUpcx3V6LRuhtbdrbCd9ALz7Y6+HfVolQLHJN/3hMT/GkF6hY3o/F7SVGry4tqEdDqjljg3tqEA79sR/0mbdkEjfWzole8TtokzV4MN0REGeVE8VYnml/2qgcIT5gFthVOBHotcN3thju53CEPRI7C91w1zDtfQMP9hbBbJnLOlR2OQiCcY0u9P1luSx5WkdTHR7g75QBinO0WP4cT9qXp6yeJRRGOlqOq2Izw8ShsD7TD/6NC7eDpy3neE3C0EVVP2NH8eGnKmWHB1+rQvLYFbT8ohsN6eY9lWWoXP3EY3We1GYoousUv1LnCpgRNmt0YboiIMsz5cDPqT1egQp5No3/MPxuE54ECbNk3+oiOc1Mdyl+rR/3+pF0oZ8OIJI2oRKP6HUYRetEDj9aSrEsdwKFOnBha3wL3A/Xo21UPjwgdulhXJDXAaJTH3y8ef+isIRFMnmxAx+Y6VKzSZo3kqBd1MRscd5Wi8vvlKF516YnoYz3vSYsFsfvhBqx+rhmlI53OHe0Z+vki+5vgOaQ1pCUi8MGPztAY4y+rKlC3uQP1T4jfn3bl4ujrDWjYX466TSIA0qzHcENElGkLC7Fjnx9lp2rhzNWu1XFDGbwODxo2jPG5f0kpPAcrEdnmhGmFC0WF+bDdXYcO5cJ/Iqg81ADz4wXILyxCwcoKeCzl2LFRuaXqW2VocrSgyOmCa0U1vOId3nzHDnhfKkD7xjzYVhahaKUNBQ81wT/SISjK41chul0+fj7yTQ5Un6qA95nU0ZFL3FWOFxZWo0D+nFqRj7VlT0CEjAk870mK7GtA3eEImu/JG3o8WXYfFgFtYz2q3iiBQzy+a2UBak6WoOp+7YaKQpQ9VYCWdQVwide3esSwaUXpMz5URcXvb554HVaY4NgaRsV+z8hhimYdkzyqWJsmIjKU9M2b3pa1XuLTcBG/FLEo5KCFeaEF5kkccBqLRhGDGZb03TgDMUR7xRKLuD9tVjrltmYL0m+qzM8R8xdqM8YwmXWj+6pR/EYFfDudiInnpoi0odJRh9VvdGPHHaI9geedOeKxxIs+5mveK34vAyO8vukmuh5NSaYv4sdwQ0SGlb5509uy1su0hxvDi6L9gTz4v9eHhrVJASDmQ529Fnn7O1Ez1i4tIoHhhohogtI3b3pb1nphuJm6yGsVcG6PofaJKjiV07rC8O7ZjdCGNrQ95rwCIzU01zHcEBFNUPrmTW/LWi8MN5kR6wrCd8iPUFcM5iUOuNa44VzCWEMTw3BDRDRB6Zs3vS1rvTDcEM08fnEmERER0RgYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQGG6IiIjIUBhuiIiIyFAYboiIiMhQ+N1SRGRY6Zs3vS1rvaR/txQRzQx+cSYR0QSkb970tqz1kh5u+MWZRFcevziTiIiIaAwMN0RERGQoDDdERERkKAw3REREZCgMN0RERGQoDDdERERkKAw3REREZCgMN0RERGQoDDdERERkKAw3REREZCgMN0RERGQoDDdERERkKAw3REREZCgMN0RERGQoDDdERERkKAw3RERz2YBWE9EQhhsioukQCaD16UY07hHl6VYEItr8jApi91ITbD8Jam0ikhhuiIgy7WgzipwVaDtthm25DebTHah0urD71zFthfGI0GIrQ2uX1lRE0H6fCbsPa02FA8VPNKBxvUNrE5FkSgjaNBGRoaRv3vS2rPUSj8eHSkJ83lt4ba6yzuWLwbctF7U3dKLzB05tnhCJIGq1wqI1xxbAblMD7KfbUL5EmyXCTeu9NoS3JrDjLm0WkUH0ft4HE+LIysoaKiaTaahIeq1LbyfjyA0RUUZFER1pF1R6sImG0LqtBPliA21bWYLavWF1/pFmFK2rgQd+1N9XJKaL0PzPXtSuq0D9IcDzmDqvdp98kAi8W/VpSbbL4DkaReiVWpSsEG8MK8R979PuWxM76kH1PQWwmWwocKv3pzzOEbk0isCeLXDJ29oKULKtFaGocjOiOYPhhogoo6wo3lyD7m1lKNvjRXikYBALYvd6NzpW1KOzL4Hw/iqYnyjD7sMxYFUl2p6shBMu1DzVhrZX21BZ5EbdqzUoFRmmfKc6r26tVbmraJcP4V5lUhHtaofn4Uo0owKeN3pwYqcFLffsRvtZbYWuVlQ4vXA87kd3ohu+x5zoMZeioVU8zipx+721cB10oDGQQCIsApZTzMvRbks0RzDcEBFlmHltA0KHapC3vxL5efkoeaQZvqTRnMjeetQ5mtH8oBMWs1h/STFqt7tQ5w0COWZYLOqusVyLRUxbYFbm5UHOzc1T58nbjcb2SAOavueEVazn2FyNSngQOqkuiwQ60L5JBK/b1XEk6wYxvc8DX5d8HCB8qhNY7oBzsVhotsD5vXIULlRWJZozGG6IiKaB5VtVeMHXjZ5gA1xnG1Fkc6kjM4jhRLAdzoFOeOSZVFrx7A8Db4Yx0h6tSctJPW4ouWVZbIc12oc+rY1YH3pgh03bZ+bcWI+qN0pQUFyNZvGcuEeK5iKGGyKiaWRZVYodr56A/0cx1D3jFeElhlivHK0pgPMO53DZVIMD29wTPOD48pnvrkSjdTe27GyF76AXnm118O+qRekybYVlxWgK9ODA9x0IPV2EvBVb0H5KW0Y0RzDcEBFl2iUX1jPD7rADkR70ifhiW+FEoNcC191uuJPLHVax5jSLRRGOlqOq2Izw8ShsD7SL4FWY9rgW2NdXocl7Agc2dqDqFV5Hh+YWhhsiokw668UWRxFqRSCI6iHnrA+ep9pRuH41RMSBc1Mdyl+rR/3+pJ1QZ8OI6AcGL7HDAT86Q8nXxbHCvhHwH0s982nSjnpRF7PBcVcpKr9fjuJV6oHJuuArqccHxWIR2KY9cRFlFsMNEVEmLS5Gw95K4OUy5M3TrtNxwxb4iw/A+5h23ZslpfAcrERkmxOmFS4UFebDdncdOoZ2/xSi7KkCtKwrgEssq94nj3yxo/jBKoQecqGgUMz/6WWOptxVjhcWVqNAPi+t2FYWYcueAKKIwYwwGtdop4ivtKM60gTPg0nX6yGaA3gRPyIyrPTNm96WtV4yfxG/JL1RZfTGvFA9E2kksagaKSwjnf6k3D5tWUzMi42y/gRE91Wj+I0K+HY6EevVRoYibah01GH1G93YcYc6S3leORZYeKYUXQG8iB8R0VwhQo16KrfWHoFZOd17lKCi3D5tmXmM9ccVhW9vM1xrnNrp5erzsyyzw2G1pTxP5Xkx2NAcxZEbIjKs9M2b3pa1XqZ15GYWirxWAef2GGqfqIJTnpoVC8O7ZzdCG9rQ9pgIPepqRFdUpkduGG6IyLDSN296W9Z6udrCjRTrCsJ3yI9QVwzmJQ641rjhXMJYQzOH4YaIaILSN296W9Z6uRrDDdFsw2NuiIiIiMbAcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENERESGwnBDREREhsJwQ0RERIbCcENENBMGtJqIMs6UELRpIiJDSd+86W1Z6yUejw+VhPi8t/DaXGWdKYsE0PqaH90xMW22wbWpHIVWdRGO7IbtziZUv9GNHXdo86ZDLILA3jb4u5QnAduaMpTfpT8Jotmj9/M+mBBHVlbWUDGZTENF0mtdejsZR26IiDLtaDOKnBVoOy0CxXIbzKc7UOl0YfevZcgQbitG4xONKL5NbU6LU+3YstKGir1hmJfYYTOH0bbZhvwH2hHWVpmoyGsVMP04oLWIZj+O3BCRYaVv3vS2rPWS+ZGbGHzbclF7Qyc6f+DU5gmRCKJWKyxac3oF0Vi4Gm3Ffvh+VAizNhe9Aexe64L/gffQ8aBdmzm+yCtlsJ2sRULcF9F04MgNEdGsFkU0ok0mSw42ES9q19XCm7Re7KgH1fcUwGayocBdhKJ1amk+IhbK9e/1IBgNoXVbCfLFRj2/WNz+lHrbdLGDbWg4XIP6HyQFG2lhIaq2VcK7sxXqOEwE3q1FqN2X/ISDaNYfV1te8bgfeKlGfU5bvWIu0ezGcENElFFWFG+uQfe2MpTt8SIc1WYnG4gi/HoYUf2g4q5WVDi9cIgQ0Z3ohu8xJ3rMpWhobUPlKrFcrv+aB1UPNQPlHnT2nED94haU7GoXUepSoaMigGx2oSAl2agsTjdKIz6cOKm2o10+hHvVaVUM0dd92nOzwr2zDTUbRJzZVIe2V9vQttMt5hLNbgw3REQZZl7bgNChGuTtr0R+Xj5KHmmGb4zhjkigA+2bRBi6XR3bsW4Q0/s88HVZYM5RZgk2VD/RhPJVVlgsDpQ/VAm8GEJIW5os1hsEVthGDiFWK+zwIXJWa4/DbLEgT+6py80Tj2sRZYTERDTLMNwQEU0Dy7eq8IKvGz3BBrjONqLI5sLuw9oBxWksi+2wRvvQp7UR60OPiCC29AN0hoKOkDPOsUHn+jDio52NICxjT/J9ERkMww0R0TSyrCrFjldPwP+jGOqeGfl4FfPdlWi07saWna3wHfTCs60O/l21KF2mrTBJ9tvKgdeDI47qoCsMP8rgXK61iQyI4YaIKNMuuUCfGXaHHYj0DI/OJItFEY6Wo6rYjPDxKGwPtIswlHYw8CRY7y5D5dEWtOmnng+JwdfehMj9briSR4UGRnxWRHMWww0RUSad9WKLowi1rwSHDxg+64PnqXYUrl+NEU/APupFXcwGx12lqPx+OYpXTfGQ3cWl2PEzOzybKuE5qh1yPBBF8PlKVLzsRsvOUu3MLSschU607wto174R6/y0AZ60h7cuKwUCJyZ9fRyimcJwQ0SUSYuL0bC3Eni5DHnztOt03LAF/uID8D6WdN2bZHeV44WF1SiQ62rFtrIIW/YERjwbaiLs97fA96QNrevz1Pucl4eyvTY0HvSgPGl3l3NTHSqDFcrp5SZbGdpub0DTZm2hxr6+ElXvbIFrpQsFhY0IavOJZitexI+IDCt986a3Za2XzF/EL0lvVBm9MS9MPuvpUtF91Sh+owK+nU7EerVdSZE2VDrqsHrKX9EQQzQq7jPHAstCbdYl1HXGfp4TWYfo8vAifkREc4UIAvL06bHDQBS+vc1wrXGK9cza6daiLLPDYbVlIEho9zlqsJHUdcZ+rImsQzQ7cOSGiAwrffOmt2Wtl2kduZkg+d1Nzu0x1D5RBac8GCYWhnfPboQ2tKHtMRF61NWIDCvTIzcMN0RkWOmbN70ta73MhnAjxbqC8B3yI9QVg3mJA641bjiXMNbQ1YHhhohogtI3b3pb1nqZLeGG6GrGY26IiIiIxsBwQ0RXtbE+/RHRlZeJPslwQ0RXveSNafquLCKaXsl9LlMfNhhuiIgEuVGVm9XBeFydQURXhOxzsu9lchSV4YaIrlr6xlSv44k4BgcGlWkiujJkn5N9T0rvk5eL4YaISFA2pokE+hluiK4opc+JvjfVQJOM4YaISJOVpQaci/2XfK03EU0Dpa+JPqf0vQxiuCGiq9JonxITiTguXuxXrntDRNNH9jHZ12SfG8lURnIYboiIUiQQHxxAX+yi2OjyzCmi6SD7luxjsq/JPpdpDDdEdFXTPx3KWp+WnyQHBvpxvu8CR3CIMkz2Kdm3ZB/TR22S+59eTwXDDRFREn0jKz9R9l+8oGyEeQwOUWbIviT7lOxbso8lh5pM4ndLEZFhjbR50+fJWp9WvldKa8tpWQYHB5UiV5k3bx6ysnOQnZWlDKAn35aIRqeHFxlf5PVslA8N/f1iHpCdna2U9O+SktPJt9Wn0400T8dwQ0SGNdLmTZ+XXMuiBxw93KQXKSsrGzky6Cgb39E3rESkU/vUgAg08bh6mQU9zKQXPdiMFGpGCjIjzdMx3BCRoaVv4vR2cq0XuRHWp+WoTXK4SV9H1vrtdcnTUnqbyEjSw0VyW58eKbToYUYWOXKTPF+flkVKr3Xp7XQMN0RkaKMFjuRan04PMclBJrmtFym91qW3iYxotNCRXOslOdQkt5OXJ99Gn06udentdAw3RGRoY4UOfVrWekkPMPq8kean3zZZepvIiEYKHXpJb8uSHmiS5ye39dvqkqel9HY6hhsiMrzRgkdynTydHmRkW9Ln69OS3tZrXXqbyIhGCx16nTwao0+nBxm9Lenz9OnkWpfeHgnDDREZ3ljBQ5+WtV70dnLIkZLDTXKdvE660eYTzWWjBQw5Xy96W6+Tg47eTl6uF72tS56W0tsjYbghIsMbaTOnzxup1oveTh6lSZ6v1+nziK5GycEkeVqv9emJhJr0OtlI81IB/z9A2VYnc3epuwAAAABJRU5ErkJggg==)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "QYmO4couoYhz"
      },
      "outputs": [],
      "source": [
        "access_tokens=\"ここに取得したAccess Tokenを記載\" # @param {type:\"string\"}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VIWoFf9MJv91"
      },
      "source": [
        "## ライブラリのインポート"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o2lxptJeo6kr",
        "outputId": "e18bf210-9dff-4b58-9cf8-a7d160149ea8"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from PIL import Image, ImageDraw\n",
        "\n",
        "import torch\n",
        "from torch import autocast\n",
        "\n",
        "%cd /content/diffusers\n",
        "\n",
        "from src.diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GqfNJFEfcv5r",
        "outputId": "e21947fd-3915-4132-efa9-a19cf3ce00c5"
      },
      "outputs": [],
      "source": [
        "%cd /content/diffusers\n",
        "filename = 'test_01.jpg'\n",
        "\n",
        "!rm -rf {filename}\n",
        "\n",
        "!wget -c https://www.pakutaso.com/shared/img/thumb/SAYA160312500I9A3721_TP_V4.jpg \\\n",
        "      -O {filename}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oXHSS39xerih"
      },
      "source": [
        "# Inpainting"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QcBr2i_Hjyvv"
      },
      "source": [
        "## load model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 643,
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            "29cdd8e256234d4abb53f2bedd6367e2",
            "77d05e9cdaa142cfb83fbf898f6ec285",
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            "4092bebe7d2842b09458e60ea7a336e3",
            "4405fa84c6164a34a3f5dd41ed5f91dc"
          ]
        },
        "id": "DWoPryXDjz-b",
        "outputId": "49739fe1-6f9e-440f-e804-6c4336381221"
      },
      "outputs": [],
      "source": [
        "%cd /content/diffusers\n",
        "\n",
        "device = \"cuda\"\n",
        "pipe = StableDiffusionInpaintingPipeline.from_pretrained(\n",
        "    \"CompVis/stable-diffusion-v1-4\",\n",
        "    revision=\"fp16\", \n",
        "    torch_dtype=torch.float16,\n",
        "    use_auth_token=access_tokens\n",
        ").to(device)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NnpZbSxLin_s"
      },
      "source": [
        "## set image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ta3m1WH41E9g"
      },
      "outputs": [],
      "source": [
        "img_w, img_h = 768, 512"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "05szhp8hetfs",
        "outputId": "eb080756-c14a-4a0f-e3a7-b220a0ffe29e"
      },
      "outputs": [],
      "source": [
        "%cd /content/diffusers\n",
        "\n",
        "init_image = Image.open(filename)\n",
        "if '.png' in filename:\n",
        "  init_image = init_image.convert('RGB')\n",
        "init_image = init_image.resize((img_w, img_h))\n",
        "\n",
        "plt.imshow(init_image)\n",
        "plt.axis('off')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Od3MBzm8yKIJ"
      },
      "source": [
        "## create mask"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZCMLhbh41Yu-"
      },
      "outputs": [],
      "source": [
        "x1 = 400  #@param {type:\"integer\"}\n",
        "y1 = 0    #@param {type:\"integer\"}\n",
        "x2 = 650  #@param {type:\"integer\"}\n",
        "y2 = 300  #@param {type:\"integer\"}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 547
        },
        "id": "-pGwzhtiyO9T",
        "outputId": "c9927afa-a704-4353-e1e9-7157cf27c3c3"
      },
      "outputs": [],
      "source": [
        "%cd /content/diffusers\n",
        "\n",
        "temp = Image.open(filename)\n",
        "if '.png' in filename:\n",
        "  temp = temp.convert('RGB')\n",
        "mask_img = temp.resize((img_w, img_h))\n",
        "draw = ImageDraw.Draw(mask_img)\n",
        "\n",
        "# 矩形の設定\n",
        "rectcolor = (255, 0, 0)\n",
        "linewidth = 4\n",
        "draw.rectangle(\n",
        "    [(x1, y1), (x2, y2)], # 左上x,y 右下x,y\n",
        "    outline=rectcolor, width=linewidth,\n",
        "    )\n",
        "mask_img"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 529
        },
        "id": "jgpNBjym1R_H",
        "outputId": "389df5cf-c5ce-4c13-864b-bbf8cafb1f52"
      },
      "outputs": [],
      "source": [
        "# mask画像生成\n",
        "\n",
        "# 一度すべて黒く塗りつぶし\n",
        "rectcolor = (0, 0, 0)\n",
        "draw.rectangle(\n",
        "    [(0, 0), (img_w, img_h)],\n",
        "    outline=rectcolor, fill=(0, 0, 0)\n",
        "    )\n",
        "# 先ほど設定した矩形箇所白く塗りつぶし\n",
        "rectcolor = (255, 255, 255)\n",
        "draw.rectangle(\n",
        "   [(x1, y1), (x2, y2)],\n",
        "    outline=rectcolor, fill=(255, 255, 255)\n",
        "    )\n",
        "mask_img"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2E7CByczimd6"
      },
      "source": [
        "## set prompt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rGPEDjZMe5Jf"
      },
      "outputs": [],
      "source": [
        "prompt = \"ganesha face\" #@param {type:\"string\"}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "4589b0df2a9849bc816191988cac6df9",
            "5bfadb5f2cd1423896c93fff8f4d0b70",
            "fd6d3e5ac073449a9affd21186cce832",
            "fbbbb48ba66341a0b58aca7ebf13b066",
            "e2b1e96009524aa9958b9996bf6d32fb",
            "430fea50d4324deeb76869dc8f75a265",
            "3fd80b97ee3348a19c2a82f9f55c04f3",
            "d24255c447734352aa679530740e5c70",
            "468575be32da4374915a9f26d60be6dd",
            "c1e73a9ab630472da8195858c9721f32",
            "0f3beb25aab54730b8eec645eb54ed3f"
          ]
        },
        "id": "yM-pNiGrgyLq",
        "outputId": "a197e512-9145-4ecb-fe52-1779b12b217e"
      },
      "outputs": [],
      "source": [
        "generator = torch.Generator(device).manual_seed(12)\n",
        "\n",
        "with autocast(\"cuda\"):\n",
        "  images = pipe(\n",
        "      prompt=prompt,\n",
        "      init_image=init_image,\n",
        "      mask_image=mask_img,\n",
        "      strength=0.75,\n",
        "      guidance_scale=7.5,\n",
        "      generator=generator,\n",
        "  )[\"sample\"]\n",
        "\n",
        "images[0].save(\"inpainting_01.png\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "lTL7nVs-jHVt",
        "outputId": "0f7783e9-41ab-439e-fd78-bb5fa507a950"
      },
      "outputs": [],
      "source": [
        "plt.imshow(plt.imread(\"inpainting_01.png\"))\n",
        "\n",
        "plt.axis('off')\n",
        "plt.show()"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [],
      "name": "StableDiffusion_inpainting_demo.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.10.4 64-bit",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.10.4"
    },
    "orig_nbformat": 4,
    "vscode": {
      "interpreter": {
        "hash": "69158ccfe43d0b962045f592ede11796dd42f250837ab62152c8bc6cd100a15b"
      }
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "02d485424b384539bf13ff275f3513fb": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
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