sample_submission.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "about-heavy",
   "metadata": {},
   "source": [
    "## 0. Libarary 불러오기 및 경로설정"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cubic-scoop",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "from PIL import Image\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "\n",
    "from torchvision import transforms\n",
    "from torchvision.transforms import Resize, ToTensor, Normalize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "built-elevation",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 테스트 데이터셋 폴더 경로를 지정해주세요.\n",
    "test_dir = '/opt/ml/input/data/eval'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "extensive-north",
   "metadata": {},
   "outputs": [],
   "source": [
    "from facenet_pytorch import MTCNN\n",
    "from PIL import Image\n",
    "\n",
    "mtcnn = MTCNN()\n",
    "\n",
    "class TestDataset(Dataset):\n",
    "    def __init__(self, img_paths, transform):\n",
    "        self.img_paths = img_paths\n",
    "        self.transform = transform\n",
    "\n",
    "    def __getitem__(self, index):\n",
    "        image = Image.open(self.img_paths[index])\n",
    "        boxes, probs = mtcnn.detect(image)\n",
    "        if boxes is None:\n",
    "            img_width = 384\n",
    "            img_height = 512\n",
    "            crop_width = 224\n",
    "            crop_height = 224\n",
    "            boxes = [[img_width / 2 - crop_width / 2, img_height / 2 - crop_height / 2,\n",
    "                    img_width / 2 + crop_width / 2, img_height / 2 + crop_height / 2]]\n",
    "        image = image.crop(boxes[0])\n",
    "        if self.transform:\n",
    "            image = self.transform(image=np.array(image))['image']\n",
    "        return image\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.img_paths)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "coral-shade",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "error",
     "ename": "NameError",
     "evalue": "name 'tqdm_notebook' is not defined",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-e0aecc10f39c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     35\u001b[0m \u001b[0;31m# 모델이 테스트 데이터셋을 예측하고 결과를 저장합니다.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0mall_predictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mimages\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm_notebook\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloader\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     38\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mno_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimages\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'tqdm_notebook' is not defined"
     ]
    }
   ],
   "source": [
    "from albumentations import *\n",
    "from albumentations.pytorch import ToTensorV2\n",
    "from tqdm.notebook import tqdm\n",
    "import timm\n",
    "\n",
    "# meta 데이터와 이미지 경로를 불러옵니다.\n",
    "submission = pd.read_csv(os.path.join(test_dir, 'info.csv'))\n",
    "image_dir = os.path.join(test_dir, 'images')\n",
    "\n",
    "# Test Dataset 클래스 객체를 생성하고 DataLoader를 만듭니다.\n",
    "image_paths = [os.path.join(image_dir, img_id) for img_id in submission.ImageID]\n",
    "transform = Compose([\n",
    "    Resize(384, 384, p=1.0),\n",
    "    ToTensorV2(),\n",
    "])\n",
    "dataset = TestDataset(image_paths, transform)\n",
    "\n",
    "loader = DataLoader(\n",
    "    dataset,\n",
    "    shuffle=False\n",
    ")\n",
    "\n",
    "# 모델을 정의합니다. (학습한 모델이 있다면 torch.load로 모델을 불러주세요!)\n",
    "device = torch.device('cuda')\n",
    "model_age = timm.create_model('efficientnet_b0', pretrained=False, num_classes=3).to(device)\n",
    "model_age.load_state_dict(torch.load('/opt/ml/code/results/Age/004_accuracy_91.64%_f1_0.89.ckpt'))\n",
    "model_age.eval()\n",
    "model_gender = timm.create_model('efficientnet_b0', pretrained=False, num_classes=2).to(device)\n",
    "model_gender.load_state_dict(torch.load('/opt/ml/code/results/Gender/003_accuracy_97.58%_f1_0.98.ckpt'))\n",
    "model_gender.eval()\n",
    "model_mask = timm.create_model('efficientnet_b0', pretrained=False, num_classes=3).to(device)\n",
    "model_mask.load_state_dict(torch.load('/opt/ml/code/results/Mask/001_accuracy_99.87%_f1_ 1.0.ckpt'))\n",
    "model_mask.eval()\n",
    "\n",
    "# 모델이 테스트 데이터셋을 예측하고 결과를 저장합니다.\n",
    "all_predictions = []\n",
    "for i, images in tqdm(enumerate(loader)):\n",
    "    with torch.no_grad():\n",
    "        print(len(images))\n",
    "        images = images.to(device)\n",
    "        pred_age = model_age(images.float())\n",
    "        pred_age = pred_age.argmax(dim=-1)\n",
    "        pred_gender = model_gender(images.float())\n",
    "        pred_gender = pred_gender.argmax(dim=-1)\n",
    "        pred_mask = model_mask(images.float())\n",
    "        pred_mask = pred_mask.argmax(dim=-1)\n",
    "        pred = pred_mask * 6 + pred_gender * 3 + pred_age\n",
    "        all_predictions.extend(pred.cpu().numpy())\n",
    "submission['ans'] = all_predictions\n",
    "\n",
    "# 제출할 파일을 저장합니다.\n",
    "submission.to_csv(os.path.join(test_dir, 'submission.csv'), index=False)\n",
    "print('test inference is done!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "verbal-sample",
   "metadata": {},
   "outputs": [],
   "source": [
    "submission.to_csv(os.path.join(test_dir, 'submission.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[ 9 27 26 12 35]\n"
     ]
    }
   ],
   "source": [
    "a = np.array([1, 2, 3, 1, 2])\n",
    "b = np.array([0, 4, 2, 1, 6])\n",
    "c = np.array([3, 3, 2, 3, 5])\n",
    "\n",
    "d = (a * 6 + b * 3 + c)\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "test inference is done!\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 12 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"263.63625pt\" version=\"1.1\" viewBox=\"0 0 366.457832 263.63625\" width=\"366.457832pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <defs>\n  <style type=\"text/css\">\n*{stroke-linecap:butt;stroke-linejoin:round;}\n  </style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 263.63625 \nL 366.457832 263.63625 \nL 366.457832 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"patch_2\">\n    <path d=\"M 33.2875 86.271066 \nL 97.240441 86.271066 \nL 97.240441 22.318125 \nL 33.2875 22.318125 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pf418dbeb2a)\">\n    <image height=\"64\" id=\"imagec28282c73f\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\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\" y=\"-22.271066\"/>\n   </g>\n   <g id=\"matplotlib.axis_1\">\n    <g id=\"xtick_1\">\n     <g id=\"line2d_1\">\n      <defs>\n       <path d=\"M 0 0 \nL 0 3.5 \n\" id=\"m8b14816655\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n      </defs>\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.370772\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_2\">\n     <g id=\"line2d_2\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.679596\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_2\">\n    <g id=\"ytick_1\">\n     <g id=\"line2d_3\">\n      <defs>\n       <path d=\"M 0 0 \nL -3.5 0 \n\" id=\"mccaf5e3cb4\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n      </defs>\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"22.401397\"/>\n      </g>\n     </g>\n     <g id=\"text_1\">\n      <!-- 0 -->\n      <defs>\n       <path d=\"M 31.78125 66.40625 \nQ 24.171875 66.40625 20.328125 58.90625 \nQ 16.5 51.421875 16.5 36.375 \nQ 16.5 21.390625 20.328125 13.890625 \nQ 24.171875 6.390625 31.78125 6.390625 \nQ 39.453125 6.390625 43.28125 13.890625 \nQ 47.125 21.390625 47.125 36.375 \nQ 47.125 51.421875 43.28125 58.90625 \nQ 39.453125 66.40625 31.78125 66.40625 \nz\nM 31.78125 74.21875 \nQ 44.046875 74.21875 50.515625 64.515625 \nQ 56.984375 54.828125 56.984375 36.375 \nQ 56.984375 17.96875 50.515625 8.265625 \nQ 44.046875 -1.421875 31.78125 -1.421875 \nQ 19.53125 -1.421875 13.0625 8.265625 \nQ 6.59375 17.96875 6.59375 36.375 \nQ 6.59375 54.828125 13.0625 64.515625 \nQ 19.53125 74.21875 31.78125 74.21875 \nz\n\" id=\"DejaVuSans-48\"/>\n      </defs>\n      <g transform=\"translate(19.925 26.200616)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_2\">\n     <g id=\"line2d_4\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"55.710221\"/>\n      </g>\n     </g>\n     <g id=\"text_2\">\n      <!-- 200 -->\n      <defs>\n       <path d=\"M 19.1875 8.296875 \nL 53.609375 8.296875 \nL 53.609375 0 \nL 7.328125 0 \nL 7.328125 8.296875 \nQ 12.9375 14.109375 22.625 23.890625 \nQ 32.328125 33.6875 34.8125 36.53125 \nQ 39.546875 41.84375 41.421875 45.53125 \nQ 43.3125 49.21875 43.3125 52.78125 \nQ 43.3125 58.59375 39.234375 62.25 \nQ 35.15625 65.921875 28.609375 65.921875 \nQ 23.96875 65.921875 18.8125 64.3125 \nQ 13.671875 62.703125 7.8125 59.421875 \nL 7.8125 69.390625 \nQ 13.765625 71.78125 18.9375 73 \nQ 24.125 74.21875 28.421875 74.21875 \nQ 39.75 74.21875 46.484375 68.546875 \nQ 53.21875 62.890625 53.21875 53.421875 \nQ 53.21875 48.921875 51.53125 44.890625 \nQ 49.859375 40.875 45.40625 35.40625 \nQ 44.1875 33.984375 37.640625 27.21875 \nQ 31.109375 20.453125 19.1875 8.296875 \nz\n\" id=\"DejaVuSans-50\"/>\n      </defs>\n      <g transform=\"translate(7.2 59.509439)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 33.2875 86.271066 \nL 33.2875 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path d=\"M 97.240441 86.271066 \nL 97.240441 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_5\">\n    <path d=\"M 33.2875 86.271066 \nL 97.240441 86.271066 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_6\">\n    <path d=\"M 33.2875 22.318125 \nL 97.240441 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_3\">\n    <!-- 14 -->\n    <defs>\n     <path d=\"M 12.40625 8.296875 \nL 28.515625 8.296875 \nL 28.515625 63.921875 \nL 10.984375 60.40625 \nL 10.984375 69.390625 \nL 28.421875 72.90625 \nL 38.28125 72.90625 \nL 38.28125 8.296875 \nL 54.390625 8.296875 \nL 54.390625 0 \nL 12.40625 0 \nz\n\" id=\"DejaVuSans-49\"/>\n     <path d=\"M 37.796875 64.3125 \nL 12.890625 25.390625 \nL 37.796875 25.390625 \nz\nM 35.203125 72.90625 \nL 47.609375 72.90625 \nL 47.609375 25.390625 \nL 58.015625 25.390625 \nL 58.015625 17.1875 \nL 47.609375 17.1875 \nL 47.609375 0 \nL 37.796875 0 \nL 37.796875 17.1875 \nL 4.890625 17.1875 \nL 4.890625 26.703125 \nz\n\" id=\"DejaVuSans-52\"/>\n    </defs>\n    <g transform=\"translate(57.628971 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-49\"/>\n     <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_2\">\n   <g id=\"patch_7\">\n    <path d=\"M 120.62663 86.271066 \nL 184.579572 86.271066 \nL 184.579572 22.318125 \nL 120.62663 22.318125 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p06ac690029)\">\n    <image height=\"64\" id=\"image1bcf60786e\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"120.62663\" xlink:href=\"data:image/png;base64,\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\" y=\"-22.271066\"/>\n   </g>\n   <g id=\"matplotlib.axis_3\">\n    <g id=\"xtick_3\">\n     <g id=\"line2d_5\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.709902\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_4\">\n     <g id=\"line2d_6\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"154.018726\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_4\">\n    <g id=\"ytick_3\">\n     <g id=\"line2d_7\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"22.401397\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_4\">\n     <g id=\"line2d_8\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"55.710221\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_8\">\n    <path d=\"M 120.62663 86.271066 \nL 120.62663 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_9\">\n    <path d=\"M 184.579572 86.271066 \nL 184.579572 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_10\">\n    <path d=\"M 120.62663 86.271066 \nL 184.579572 86.271066 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_11\">\n    <path d=\"M 120.62663 22.318125 \nL 184.579572 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_4\">\n    <!-- 2 -->\n    <g transform=\"translate(148.785601 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-50\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_3\">\n   <g id=\"patch_12\">\n    <path d=\"M 207.965761 86.271066 \nL 271.918702 86.271066 \nL 271.918702 22.318125 \nL 207.965761 22.318125 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p0b7210820c)\">\n    <image height=\"64\" id=\"image108a537b4f\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"207.965761\" xlink:href=\"data:image/png;base64,\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\" y=\"-22.271066\"/>\n   </g>\n   <g id=\"matplotlib.axis_5\">\n    <g id=\"xtick_5\">\n     <g id=\"line2d_9\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"208.049033\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_6\">\n     <g id=\"line2d_10\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"241.357856\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_6\">\n    <g id=\"ytick_5\">\n     <g id=\"line2d_11\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"22.401397\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_6\">\n     <g id=\"line2d_12\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"55.710221\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_13\">\n    <path d=\"M 207.965761 86.271066 \nL 207.965761 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_14\">\n    <path d=\"M 271.918702 86.271066 \nL 271.918702 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_15\">\n    <path d=\"M 207.965761 86.271066 \nL 271.918702 86.271066 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_16\">\n    <path d=\"M 207.965761 22.318125 \nL 271.918702 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_5\">\n    <!-- 1 -->\n    <g transform=\"translate(236.124731 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-49\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_4\">\n   <g id=\"patch_17\">\n    <path d=\"M 295.304891 86.271066 \nL 359.257832 86.271066 \nL 359.257832 22.318125 \nL 295.304891 22.318125 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p27c9a05f4b)\">\n    <image height=\"64\" id=\"imagee64f7b5873\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"295.304891\" xlink:href=\"data:image/png;base64,\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\" y=\"-22.271066\"/>\n   </g>\n   <g id=\"matplotlib.axis_7\">\n    <g id=\"xtick_7\">\n     <g id=\"line2d_13\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.388163\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_8\">\n     <g id=\"line2d_14\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"328.696987\" xlink:href=\"#m8b14816655\" y=\"86.271066\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_8\">\n    <g id=\"ytick_7\">\n     <g id=\"line2d_15\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"22.401397\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_8\">\n     <g id=\"line2d_16\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"55.710221\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_18\">\n    <path d=\"M 295.304891 86.271066 \nL 295.304891 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_19\">\n    <path d=\"M 359.257832 86.271066 \nL 359.257832 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_20\">\n    <path d=\"M 295.304891 86.271066 \nL 359.257832 86.271066 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_21\">\n    <path d=\"M 295.304891 22.318125 \nL 359.257832 22.318125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_6\">\n    <!-- 2 -->\n    <g transform=\"translate(323.463862 16.318125)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-50\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_5\">\n   <g id=\"patch_22\">\n    <path d=\"M 33.2875 163.014596 \nL 97.240441 163.014596 \nL 97.240441 99.061654 \nL 33.2875 99.061654 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p73d03e59e1)\">\n    <image height=\"64\" id=\"image1dfe401a67\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\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\" y=\"-99.014596\"/>\n   </g>\n   <g id=\"matplotlib.axis_9\">\n    <g id=\"xtick_9\">\n     <g id=\"line2d_17\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.370772\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_10\">\n     <g id=\"line2d_18\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.679596\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_10\">\n    <g id=\"ytick_9\">\n     <g id=\"line2d_19\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"99.144926\"/>\n      </g>\n     </g>\n     <g id=\"text_7\">\n      <!-- 0 -->\n      <g transform=\"translate(19.925 102.944145)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_10\">\n     <g id=\"line2d_20\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"132.45375\"/>\n      </g>\n     </g>\n     <g id=\"text_8\">\n      <!-- 200 -->\n      <g transform=\"translate(7.2 136.252969)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_23\">\n    <path d=\"M 33.2875 163.014596 \nL 33.2875 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_24\">\n    <path d=\"M 97.240441 163.014596 \nL 97.240441 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_25\">\n    <path d=\"M 33.2875 163.014596 \nL 97.240441 163.014596 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_26\">\n    <path d=\"M 33.2875 99.061654 \nL 97.240441 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_9\">\n    <!-- 12 -->\n    <g transform=\"translate(57.628971 93.061654)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-49\"/>\n     <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_6\">\n   <g id=\"patch_27\">\n    <path d=\"M 120.62663 163.014596 \nL 184.579572 163.014596 \nL 184.579572 99.061654 \nL 120.62663 99.061654 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p54ca43abe0)\">\n    <image height=\"64\" id=\"image9074b50de0\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"120.62663\" xlink:href=\"data:image/png;base64,\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\" y=\"-99.014596\"/>\n   </g>\n   <g id=\"matplotlib.axis_11\">\n    <g id=\"xtick_11\">\n     <g id=\"line2d_21\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.709902\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_12\">\n     <g id=\"line2d_22\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"154.018726\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_12\">\n    <g id=\"ytick_11\">\n     <g id=\"line2d_23\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"99.144926\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_12\">\n     <g id=\"line2d_24\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"132.45375\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_28\">\n    <path d=\"M 120.62663 163.014596 \nL 120.62663 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_29\">\n    <path d=\"M 184.579572 163.014596 \nL 184.579572 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_30\">\n    <path d=\"M 120.62663 163.014596 \nL 184.579572 163.014596 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_31\">\n    <path d=\"M 120.62663 99.061654 \nL 184.579572 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_10\">\n    <!-- 0 -->\n    <g transform=\"translate(148.785601 93.061654)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-48\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_7\">\n   <g id=\"patch_32\">\n    <path d=\"M 207.965761 163.014596 \nL 271.918702 163.014596 \nL 271.918702 99.061654 \nL 207.965761 99.061654 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p8aec0bd66e)\">\n    <image height=\"64\" id=\"imageeeeca01cfb\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"207.965761\" xlink:href=\"data:image/png;base64,\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\" y=\"-99.014596\"/>\n   </g>\n   <g id=\"matplotlib.axis_13\">\n    <g id=\"xtick_13\">\n     <g id=\"line2d_25\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"208.049033\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_14\">\n     <g id=\"line2d_26\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"241.357856\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_14\">\n    <g id=\"ytick_13\">\n     <g id=\"line2d_27\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"99.144926\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_14\">\n     <g id=\"line2d_28\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"132.45375\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_33\">\n    <path d=\"M 207.965761 163.014596 \nL 207.965761 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_34\">\n    <path d=\"M 271.918702 163.014596 \nL 271.918702 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_35\">\n    <path d=\"M 207.965761 163.014596 \nL 271.918702 163.014596 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_36\">\n    <path d=\"M 207.965761 99.061654 \nL 271.918702 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_11\">\n    <!-- 2 -->\n    <g transform=\"translate(236.124731 93.061654)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-50\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_8\">\n   <g id=\"patch_37\">\n    <path d=\"M 295.304891 163.014596 \nL 359.257832 163.014596 \nL 359.257832 99.061654 \nL 295.304891 99.061654 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p5eddba1606)\">\n    <image height=\"64\" id=\"imageb36f99da38\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"295.304891\" xlink:href=\"data:image/png;base64,\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\" y=\"-99.014596\"/>\n   </g>\n   <g id=\"matplotlib.axis_15\">\n    <g id=\"xtick_15\">\n     <g id=\"line2d_29\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.388163\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_16\">\n     <g id=\"line2d_30\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"328.696987\" xlink:href=\"#m8b14816655\" y=\"163.014596\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_16\">\n    <g id=\"ytick_15\">\n     <g id=\"line2d_31\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"99.144926\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_16\">\n     <g id=\"line2d_32\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"132.45375\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_38\">\n    <path d=\"M 295.304891 163.014596 \nL 295.304891 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_39\">\n    <path d=\"M 359.257832 163.014596 \nL 359.257832 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_40\">\n    <path d=\"M 295.304891 163.014596 \nL 359.257832 163.014596 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_41\">\n    <path d=\"M 295.304891 99.061654 \nL 359.257832 99.061654 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_12\">\n    <!-- 5 -->\n    <defs>\n     <path d=\"M 10.796875 72.90625 \nL 49.515625 72.90625 \nL 49.515625 64.59375 \nL 19.828125 64.59375 \nL 19.828125 46.734375 \nQ 21.96875 47.46875 24.109375 47.828125 \nQ 26.265625 48.1875 28.421875 48.1875 \nQ 40.625 48.1875 47.75 41.5 \nQ 54.890625 34.8125 54.890625 23.390625 \nQ 54.890625 11.625 47.5625 5.09375 \nQ 40.234375 -1.421875 26.90625 -1.421875 \nQ 22.3125 -1.421875 17.546875 -0.640625 \nQ 12.796875 0.140625 7.71875 1.703125 \nL 7.71875 11.625 \nQ 12.109375 9.234375 16.796875 8.0625 \nQ 21.484375 6.890625 26.703125 6.890625 \nQ 35.15625 6.890625 40.078125 11.328125 \nQ 45.015625 15.765625 45.015625 23.390625 \nQ 45.015625 31 40.078125 35.4375 \nQ 35.15625 39.890625 26.703125 39.890625 \nQ 22.75 39.890625 18.8125 39.015625 \nQ 14.890625 38.140625 10.796875 36.28125 \nz\n\" id=\"DejaVuSans-53\"/>\n    </defs>\n    <g transform=\"translate(323.463862 93.061654)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-53\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_9\">\n   <g id=\"patch_42\">\n    <path d=\"M 33.2875 239.758125 \nL 97.240441 239.758125 \nL 97.240441 175.805184 \nL 33.2875 175.805184 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p76eaddfd4a)\">\n    <image height=\"64\" id=\"image1ef734e30e\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\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\" y=\"-175.758125\"/>\n   </g>\n   <g id=\"matplotlib.axis_17\">\n    <g id=\"xtick_17\">\n     <g id=\"line2d_33\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.370772\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_13\">\n      <!-- 0 -->\n      <g transform=\"translate(30.189522 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_18\">\n     <g id=\"line2d_34\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"66.679596\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_14\">\n      <!-- 200 -->\n      <g transform=\"translate(57.135846 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_18\">\n    <g id=\"ytick_17\">\n     <g id=\"line2d_35\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"175.888456\"/>\n      </g>\n     </g>\n     <g id=\"text_15\">\n      <!-- 0 -->\n      <g transform=\"translate(19.925 179.687675)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_18\">\n     <g id=\"line2d_36\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"33.2875\" xlink:href=\"#mccaf5e3cb4\" y=\"209.197279\"/>\n      </g>\n     </g>\n     <g id=\"text_16\">\n      <!-- 200 -->\n      <g transform=\"translate(7.2 212.996498)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_43\">\n    <path d=\"M 33.2875 239.758125 \nL 33.2875 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_44\">\n    <path d=\"M 97.240441 239.758125 \nL 97.240441 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_45\">\n    <path d=\"M 33.2875 239.758125 \nL 97.240441 239.758125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_46\">\n    <path d=\"M 33.2875 175.805184 \nL 97.240441 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_17\">\n    <!-- 5 -->\n    <g transform=\"translate(61.446471 169.805184)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-53\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_10\">\n   <g id=\"patch_47\">\n    <path d=\"M 120.62663 239.758125 \nL 184.579572 239.758125 \nL 184.579572 175.805184 \nL 120.62663 175.805184 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pdc0ccbcb08)\">\n    <image height=\"64\" id=\"image357f674384\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"120.62663\" xlink:href=\"data:image/png;base64,\niVBORw0KGgoAAAANSUhEUgAAAEAAAABACAYAAACqaXHeAAAABHNCSVQICAgIfAhkiAAAHmxJREFUeJx9m9uPLMlx3n8RmVXV3XM5Z87Zsxdyl8tdLknxTtCiCVKyDBiSLEsyJFFciRQp2jRgPxg2/OR3/XMCBMi2RHLNy/LOXe5y91xnprvrkpkRfsiqnhmScAONPmdmuiozMuKLL76Iks9+6AOOCkED9x89Ztv3ZDccwYuDgARBABUhxghAyYVV01KKUTBUhaDCputYdS1JCpeXe6Yhodk4bhqO20gQ5/0vv8RXv/5Vnnr6Lg/uv8PDX77Dd779Gt957Xv0/YC7U7ygKmhQFMVNmUpmO05cTJldgcHAPYMXEA4vcWibhq5tiSFguZBTIoZIEKWJga5taJqGmK0gEhDqZnEDdwwnC4ATUfB6cXfH3VHAFIoZCqgbXWzp2gYX2PeJPGWCG10TaNvAerPh8//qC7z65b/i/S++wE9/8DrRnFbh05/4KM+c3eVb3/42jx4/priRS6G44W5EEWIUutiyXjXc3434ZEzF64GJIKqYGY0obk7KmWKG54IilFwgQPQALuBCtGIEVdwhhEApVn8HuFcDuDv41c/MjChXRhERVJW2bRGB7XbLNExgRhcjm7bhxRde4Mtf+hK/+69/j83pEeIFkbooNyeGwHvf/zxHp8d8/7vf460338RSwXJmTJl9nkBAg9JF5ZnTNavtjseDsDNhKlbXCSBgbgQCZvVAXUBnA7k7pRS6riM68ymqI/NmzA0HquPL4cIiirvhZkgMgCMiiAhNjMSmYeh7xmFAzWli5Nbxht/9nS/w16++yksvvkhoIm4O7oQQyCVjbpiBR+Hk7IRPf+aTPH33jB99/3W2Ty4gKpME9uNIyaAhoiqcrlqSBcwVscxoGURwHEfmzYP4vBvVw4GqKgCR2RrVCxwRwBxjPnEccTls1NxhdrdSDA2KAF3XMU0Tfb8HdzZNw7PPPsOX/vKL/MHv/z4nJ8eIVGMDBKn3cnfcHBfHvYAKzarl+Zfex9HJEd//7vd4++23Ce6EpmU/ZFKaMUegjS1dgZJrKBQzitSwmV2YRgOi9Tid6gkiFTSiAWaOmeMOgmJW6uYXYPErbygl0zZtvZA4KrBarykI/X7Ai3G8XvPpT3yUr33ta3z8Yx+jaeIN9xQcn2Pc3QDDzKEENCgIhKbl9O5dPvKpT9Iebfjhj36ETSMiQnZjGOtpC4VcSjXqfIgOGD57MfXkRWpoe/3/cpjRHMzrylRD/UOnftp8BauZwB3cBUdIxWhDdXMRZd8PWCm8595dvvhnf8of/8m/4+zsDADzsoBFfc+Aa5ZrSC04k6tbqgYcJ4aG09PbfOi3PsL65JRvfvM1hvuPEDdQ2BfDDawYhiOqBA1MKcHsbVEVtIaFUb1OtBojl0xcUH05oRBCBYtrAGjuxBgxswpcpQKY0KAEpn2P5JF/8amP8o2//TKf+fQnEW3mkLrKT/U+9RpihZwzN15SAfY6sLo76/WaF198gaPNEf/8z6/xw5+/Sc5GA0xmlFLq5mZc0aAHnPFrlzczgtRrLveJV6hohzifV3v44gIYy5euG8pz5nTV8Ed/+Ad85a+/xLPP3qtIi1bgma9XN3+1EC/VAFbs8HvmE1oMfd0QbRN59ul7fO6zv83m6ITXXv8hebsjz3/DvCnRCsgp59ljl30IIlfxL1LBPS4nvBhi2bwt1pOrRS8LM7OaQiK8/OJ7+cZX/5rf+/zn6NoGcwVtDnEmNeIPmyy2WD8QQqgZp66Ua85yWMvBazCaGLl354zPfPKTnJzc5n9/69u88fgxyXzGqErQQjuD3LUDczdU5p9fM270+SZmZQbCxWL1xBRQfHYzQd1ZtYHTTcfvff6zfOPrf8Mr738R9ZpyYmwhxApm83XMrjYTqKflVrh9doc39WcgsRrpGq/w6x4ognvAraavW6dHfPiV93N6suEfvv0ar//8TXZjXV8xR0ohCJTD3gxxqBBXr23z/eIM7gd3MbNqIa8pEBHMoVgFj7ZRPvC+5/j6l1/lj/7w9zk9Ob2KrxgIMx9Y8rCZocpVihXFrfKMO3fusTk+pWTDSsHy9CthOHugB0QUk7o2Ved40/LCc0+xOvoMt06P+D/feZ3HuxERJadM28SDt9bYvzKquWFziovLfbgGFzKTiZrrIqYRfGLdKP/mdz/Hf/sv3+BjH3wZiS3FKqK3bUsI1a3nixzi9zqwLeEmCG3XcvfuU5SUKDlBbg4YUEo5LN7daya6ZpwYI+v1mnvqfO5TH+HO2Rn/8M+v8eb9h0yuTEWI4gfWpyHym17h7OT476wUggRyqTk1m5HN0RBqDjXjZNPwxT/5t/zP//Ff+a1XXiLq7G4aaJpaWOi1PFwT/hKZHE6jsk4hqCLu7Hdbhn6POLhXQlbxJR6+pzOWHBYdAiq63IKgyu3TE+7dvUMuhScXl/VgfCZdqqgIQQQVrW+t64nLQVcMuAKNJkYKDlZ4+uyUr776F/zHr77KM3fPcIdEQIIeTv16upsDfomkSl5yrowzNhUDDmk30jQtVgqUiM6XiTHSdR3DMJBTokg5XGexr6oSmhUNypFOvPjsPdarFeuu45vffZ2h3FjQ1T8Pic6JPlvJ5tgAJ8xVIGY8decW//0//wde/cu/4HSzmgsNx0Vreal6SJM3XrIUTjXduTsxXhnKlgIlBIIqQZSiSmgiMUZyzmRz1kdHTNPENPSQ5zplzkYCBA10uqpeIsIzZ6d84dMfpRXnn374U3b9iBmYhEPcu3mly0C0+TQsyKwDODEIasbxquNvvvTnfOnP/5STozVL4VQ9RAmqV+bkWqmsSnEjpVRPPdQwqTev1hERbK7ublBWDUiIdE2LmTEMAxICq+Mj0jQhKqRxxK2SrCDzd5um6hUh0qjy+U9/jLA55h//6dv0qVDMCcqBdfq8hihAKQbByaVU+iLO8WbFv/+TP+Zvv/oVTk4r0i+bEZH5s5bE11OWuzNNE8UNneN58RCfC6mr6lKQ2edV9HBt1avQCiEwjiOlJGLTIhJQDaRxopRSizUVgoQDzqxWK+6GwCc+1LC7vORb3/0BxTKVHCrmhtg1DxCV6ibmNFE5OTriK3/1Jf72K1/mzp1bMJfHC/tbFnpt3wfkLqWgqgdQ/P+9ZK4/VBVXvVF1LtlEVdFQAXroe0RhfXRMbBJjP1BKqgXVjAlL9li1Le+9c4t/+YmPcnlxyU9+8UvMMtkrCC7XDrePN3+HO2U+ybt3zvhPX/8aX/vKX3F26wjmyjDGWIuNG4BXP3MupJzAqTLTXCAhN72jbu6aN7jTb7fsLi4qa1NB53DRGVsW5mYiNLEhhEDKuWoQTVuVrPnaS6i5O2maWAU4OTmh2xxx//Fjdn0PWv8uaqyfiwt7yRx1DX/z6hf5yl/+BZtVM5eJQgzNIQ0JVxsouZBSqicem6s8/SsJ4eax+6Eo9KVGU4EoBK9GrjT6uvc4URWfU16cwyJNE+1qTWMt0zjO/ALW3ZpGI1PqicV55cXn2fU7/v5//RNPdvtaKM10JdqsuQXg4x/+IK/+2Z9y62hV06I7Gpr5pGV2HcFKBTioQsgCfocC5nAu/Fo1uJTC9cdW4zFKjW3TQ1gsWLFwCl0cTiqHiDGS2pa+39faZL0hTxMlZ8SpFC8qPgyscV554b288+4DvvvjnzOlcmC90crs4kH5wu/8DmdnZ4goQReQ0hsgdkhpM9+/AWjXioybheivv1SEPH9XNaCykPfZcNzI3NeuvfyWA0hO08jQD4SmORA3VBEDXa1gFG6dnvLe597DW/cf8+DR+aGkjwu4xRC5fet2FTYpdeOi2JKyFk49g9P1zd7YuPtv3PyvZopD+QrEOKu0c/1Qrwlicw3BzXsd7uNObCMohBgY+4HJjNA0aDDKZChC0kyjgTu3b3N6fML55f4aN1l0/pI5P39CKYUYKsEozsFSN3j+b3hdF1Z8Jjm/yQAH8WUpwecDcIOFBl5t1A+1/m8ygJlhAhIDUasBm7YlTQkvBXJGZ8HW+5Gogc1qRQzhwFFilMCUJsSc3f4Sk0yQluCRbAnUb4iIS6znnKtAeljYtc1yUzy5Xt4uIqjMBQ4GSqjVqCyq2ZUapBpmbWL2oGUt7ogZWjK4EGKLolipXjqNE8N+C+a0TYObMaWEzfRcEdyMmHMhpYIQ+OXD+0w2QbsGj4hmmniFxr/qxlXOthsgWNHbfy0sFtd29wpSVPJTsmG57r5mED9oh0EDxYwQlOwzcM2GqsInszGhCbE2P+aawd0hKGkaOT46mr28sB8GhnEkLFVlmqaquDQdH3zpFVqJTMVIoS44cDMG4UodapqmJrJratIiff2q1nj9/yJSF2uGuVfWKFpFCtXazXGnYBQrdQ0qN4iVu2Olsk1fAK2JB281MzabDUlq6MYYSSnx8MEDzApBa+jHUqoW/+EXn+WzL79I/8YbrF98iTFEViESSsbUr5nhygApp4O7/triroXA8iqlHLwmlcKUKmVGZWajM78P8aDfa9DDPa6HVDFjmiaaWW9YcGoqU1WegtJ1K2zKTONE27bs93vOzy8wvcKyiFTJ65WzjvST7/H4/F2OT06we8+RshDMSOGqA7QYADgg6RUOyAEPVMONMFg+lxMPoVaeJ7dOabsOM2McxyvjzXWDzBu/jvzLASyvhTnePAynaRoGEfp+z8XFRWWKbcOYrr4bg0ADvLdT1mUgXTzkp//495y99EFu3XmafLShXykQcBOEgEhEiIgWFJ91/wpUpZS5YpzZnAjKXNxoLaCUKm85hdh0eBHSMKKzekMxxB33quwWK+TaUZmruLrZLlZEX9TbWs9YLcMLWCooiqaRd17/Pudv32ez3tDnLTrT9Kg4R03LC3duE9VRLejlQ9795iN+qS1htWZ1csLm9Dbd6W3i0QnSbZCmxeeOi3lVHCVGCJHQCI1kcKeUuhrLhVTmk3Uju9EPPcO+J/cjUz8wWO3EiFSUxirhil3E45wVfOGlS6MGcKNYpfOeE0yJMgykJxc8uf8mv/zpDxl++QvKkx6b0pVSJVRZvFt1bNpI9EIoEENF6Kn02OMtw5s/41HKJA1MolhsaDZHdLfPOLp9xsntO6xPb9MenaDtCoKSgyGqhxNTVSQ2ta3umZITNlVNwLS+ZabaOqe5RZKrvCEjpVJ2MSOYYznDlJj6PeNuy7C9YLg4Z395QX95CfuBKQ/oOHIaG9Yy0pgTDslMiAti77Z7pnEieEAsQ4iIQ7LE0EwUCmnYkYdEGjKjORfBecsKpgHt1qyPb3H7qXucPfMs+tR72Byf0G02xLZFQ1NL3hn9p5zIfaIMif5iR9oPRB8rFzLHSiEXY8gZTwlNiTyOUDKUhOdEmkZ8HMjjQBknNBtqhU3KdDmTLBModaMoUZUmCJpqltGgRBGYpom33nnI80/fxa2lCYIxkh2KOyUn3BxLNQ8TlZQyMhWkFMQzpZ/otzvy4wds3/wpq9MNovX2oevojo44OjlltTqmiSsyzm57yfnjJ7z7i7fZnV/ANABG1EDUUN3UHTFoJKBBaKIQGyEGiArihSgFi5UfWIISFKFBimAmTO6MBtkdVSOEqw5RxIUxF15/8IjnH1/yvK/pmkIRcI9YqmVv8YWuBwiClUIhkLNRpgwYGvKsKBdaLWyOVrglyvgI2wX2DyM9DTk7Qz9wcX7JbrenHwZKMaJC07WEtkMkEFGC1ZpEtGoAFKHguM/l0swrzIXiTp6zjOGkkhinwjgZu2yMApNV5XkhbdEdCsJblwM/f/cRd7q7CE7G8BIpk9FPPS5CaDoMYUgZQ5hwijpGQUrCpkxTGla+5qJpyZpYd0qcZ3WixppNvKBVkSV4JX8GZKkpLS+9fKvVp1gB9coXFk5wvXcii8y+9B2NkjPTzHL7fqLPmX0xikHQiCya4JJP95Nz//GOi7undKsVLsY0Fc4fb3m82zGaE46O2Zw9RTi9y3d/8CNef+MNvBh3j4947vYpK4c49ByNNe6CbIja0LQr2rajbdc4iulIGCdC26DDWHVBA48r4vqElFLlCxjoIq87JZXaTJ3ne0ouJJswjK5p6JqGOCN8yYWhONs0cZkTvRv7acKv6RqOE6v7wOjCxTBxOYyceUspiYvtlrfvP+IX+0QJDc8/8zLPvPwxvvn6j/i/DxNv7BuGoefWODCtb/OBe0/RP36ElBqbY79jsz4laCC2K0KzoogjVtA2EuL81kCQSoObpuXddx9wvt2zOjnm5M4dVptj7r/7kHfeeQfLmaPVmnXXMY0jueQKhiVzvF5xul6zaiIiMJTC3gqDQu/GdppAFKGqTqnkuTXmxuSFfR7p08BUWtoucOfuCeujDUfbPb948Jif/eg1fvrWm7xx/5x9n7jVtjSWCDbSXzxgF0furSJ3uhbPE2G1RnWe3vI6VJGlcgCCEmb9MIZALkZOPanfcufsjHfOt9x9+j186Ld/m+/9+E2+9a03+eXbl3geOT3qeeXlOkLz+K0H7HunTJn1sGc3OSebNes2UjBGYG+FJ0PPkDMSWswclVqVRhNIZiSv8lTbRNZdR7tuiNpyeitw5xnjpRee4/FFz0U/8eJpy26YGKdCsTVI4agLnETlNASOG2G9bjhad7XhkTKlmcg2zwOkjORCtkTyhESh1YamgI97NkcnfPjlF7h/8YSf/eDH/OzNd5DbtymXF0x99ZKfPHjMndNjHvQ9437PSaOsxRmngRCEIh2TORej8XCXebybKMy8wjI+i7ZRQq2+rGRiUDbdinW3omkDMXRgirrRaMMqdtwzZ5gm9v3AOEyknBimmr9XIbAOkaO2ZbNpaFcdsWkQUfKUKmMtDqngOSNA27UUB3VHimKl4Gng7OiEzWbDL974MdODc8a+cMKEN46MO3xyhnHH3a5lfXSLW01kNTdWp+Jc7nsejYWLqfCoT1xORqL2Iw/sVYSoB6ZVaahJoBBqo0Erj/d5UEilEMVZRcGjIMFZhcBxs0JVWDUNbQx0bUuIc2mqAZWKulYKnq22pooTNKJquE9VFI21iFEcySOrCM+ddGg+QqfHPP2+p9k0AZ8GxJ227VA1GoUyJlLKbLPRW+FiGnl713M5ZbbJ2RfDRIiz7mBz/yIemh0R9sl5tM/cneC4i4gpEaVIwINVo5SqF+K1gaqzwNE2ofb+wqzjm2BQmx3FUaujt25OHUEIhKC4TbjPpXCAECPiThonUp/ZT8bl43OaNPLcyZqYe9wNd8FlZnQuIMq2ONsMD6fCO0PiyVTYZ6fPMBYnRj30EA+aYt2MYyHycDfxnZ+8zVASd87WnLaRddMR1ke1CYqh4kStnoLOretlWosqomY3gkNz6CDViRAxUIkghuvcFTCvqCxUvq9VUk9ZuOgz2xHuXwxsTo+Z3AhBUIkYgd1QKNpQRiNl4Twrb213vLUfub8f6adCdiWbgyuNNoTitRKdCVRkGR9xp0d5/eEF7w4jZ8cdJ41wq+vYdC0hKG3bsOla1l1DM0+LNEEXjoJOethAGwNhFesYHQJuiCyqEGjoyBjZI04mBiDKPC/oFITdlHjUZy6GzPEJ9PsRaSr7GYtx0U/0ecA0si9wfzfyi/Md59PEdhgpVvuIgtXGqBtl0dsrgyIqcqjnJzFGc3YXO7ZT4qQR/ExpRQhdO4+ZGPv9jhCETWkooXZqYoioldqdjRGVgEoghLkr7HUoUqVqdUWUVIzitVW+Wm2qBJYT+33PdjQe9yNvPtmyM2PI8M5FTxuguDFk47Ifq/6gkfPkvHO55yJlhlKYDIKEWUx1VKve6FI9XkXr+F/Vz5wsdXLDkbnQmTACm33PrSgcHa24c2vD6emG0ARC09BYBb5FlCgzsgdRUD9ocSXnQ6egahdCKVUB2m633D45JoaIpMw0GLs+8XA/8mDX87DvyQXe2e7RUCvJVArZYcwFFWHME5fJeTImMjCVCqXNtWZp27aHAmhxf7NSDQB+QMUyg9RQnKbAw+3AraahW09cXp5z1Ckn69tsjk+JUktMqROO+CJTmZMt3biZqCwTKwedfxyHg3jZKIgrrJzRjUsE2+6xnDk+OqYJMOTCaJBcGVNCVUgoe5zzsWfyaiC89jUWwRb4NU1RWBShpeNrmSjd3A+MdfzUlaHAu/vErVswDon+fMtJXCPR0FUAnUtLVWz2ABenCbVZOo+c1oou1ImRlBLFa0l9fHxcNT0KMRorlLU3dNOA5JHTNvLs7VM627MvwjYL57seVaGJyqXDbhyYcqoaRh2Wo9VwGBMMMV6T7Q/zMbUlF2NtNGYP1Ck+oQ2RKIoQcG15vB95suvJ5gx9z8X5Of12S55GPFdxgmu6YO3VL+IohFhRvqYvkNiQS2G7vWDdRigjwTMlZkIphL5wfrnnwgvH6zV3taExuLVa0XlGS6JtI6MVLoaJ7ZhAlxTn80BkOIinMYTD5IpInRMueG2yNjGCO5PNg5ChunSIEWMRRDKPzi+4WMFGOvZDT7w4x7Ww2azQmUtcl69LyajK4ZGVaRrBfKY5ym63x81mBajMJXhBzBnHwsOLPZMLx6pM/QBNQ0qZfhiJbUvvsB0zF/2IUSXxRbwPMeJSwf3GtNlC+pYJNpFKhHLONCESRIhNi+WCSRUWogTatuNy3/PgYk8nQpCIsEVjnQRfxtqqHr80T2fCM7fC8Ku+QHHh4uKcEOp0t6qS80i2zJid++PIdsxEAk1USnCyw0U/MJqTo7IbJ3ZTIhc7SPCCoLHqjykl3J2ubWtY6690suc+R9S5124GZCOuu6reqpJyJsaIxkjKynlfOF0ZJyuhmSb6vidGvdExvj70vMTa0gpbbjyNEzkX2q67RpScMmYe7kZ+/uScodQaJHQwkdlPznbMJAL7qbCbMqNLpdpzL+D6jMJyGBoCPs82LY3e5fQPw9KqFc1LMQQ/KC7LqKwjaGzZjYXLPrFfTWyaFSklhnEkzo2J2DQzws/tba4mSVjG171qkAg0TQScnGtxlMbEo92OxymREVZaQW0qxm40RrNZ5MgMuZAM5NpYzIL4ZnVAsOu6Qwa4fvo+79HN6gMTrgEJc8vamet3m3GgVI7QRoZknI+Jk/3AKiqhEWScEO1r11b1sGn1GpeWq0S1eISVwpidSRpWIRAkIXkCEQaH7eiMkxCKcbIOBIRdMnozRoVdLgwOCYUQKhOd413mZwFKcZoQaZqGcZrmYeur8HQ3xI2oQjTzQ7cVEVJOtG2L5aWbWx8/KdRBqe04cdEr6xgQMcypnR8NkGvBwdzOtng1sLycwjAM5FIYc+0g6dwS7zOc9yMX+7F2n8g0TaCUzJCdyZ0hV6aavD4dElFimCvIEGeM8ToTMLfEDy22a/376gVGG9saAsUNrrWvSyk34innAkodTkJ5PEzEpj5r6KZYFiw7fmRsVivaJhzy/fWBhpwriiORUjI5jaQUseyc98797cDowlRqNpiKsR8zfRGmUiu6Mnuoeh3eQirNzTkfxuSapk6TTbncmNe6vicV5bnn3jM/MXItXkXk0N9TM2JYWBNMBi6BbSlonxCDbMLkQhXGIZfCqm1owtX1YowHSppyYShVgMECU3KG0Xm4M86HzOhKP/VsGmHImdEDvcFYCskFo7bjYqhzRUsvcInxBdQPD1ocBi1uziw2bcMHP/gKsZgdnri8GmAO4MvkaMCVKoOX+reDOz5l1IzsThIoGEZVacfUsA5y2PzSRa6DlMa+zwSp6kwpxnZIPLpMXAyZ7eRMpXC87shm9NnpszAWKCjFCz4Pafv8mM8yqreE2tVQtdw49bnjhqpy7949nn/+eaJZOcRyVYbA5naSO0xzxRZD7diKCybOVGos7qUwScZcyLnQD8pm3bIODU0U1p0TZmE0m2MSyOOOEGv4pCnyZJt4tN+zmzLbYayY40rJsM+JXqhGnpuhYk6xfNi0iBxmhxesWcZqHKvdZGZxxp0utHzwxZd5/rnniVePqlyliuVBJpHabSmlFpWBeaI8BMQrIteurFHSxNRFNl1gLE7uYDUrMFEFDRGXQErOlDIahFycy3Hisp+4HAfGDMM04bOxpjEzeGYUxz0eRuUrhPnMOMvhWcPlpMv8POLSNKnd5PpWVe7eucNHPvRbvO+F91UdYnk+8FeJxOFNJSpdjFCcyUt9Hg/Y54yVTMrKVBpOrGU0JSc4WTfg0AZBxNDYMmbnMmXaJqC5MGxHtlNiX4zBoKjiIbDPmSklpuCMs5pUrMwnvDy+l28QsOUAS7l6UOD6flRrdvj4xz7OBz7wAdbrNbGJSj9kZGZ0eZ7DXdKXQ52zdycVI6CkUp84Bw4N1FyMkgpJCgljKiOjF8bcsG4iMYCPIx4bBoNcDJsS+2HiYkpMKEPJjMyImxIFo8+FJOA5zZ3lcnD1kjNNbGbyc/VMY91xLchmM9QfODz99NN86lOf4u7du6gq/w8VcNIKWJpLEwAAAABJRU5ErkJggg==\" y=\"-175.758125\"/>\n   </g>\n   <g id=\"matplotlib.axis_19\">\n    <g id=\"xtick_19\">\n     <g id=\"line2d_37\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.709902\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_18\">\n      <!-- 0 -->\n      <g transform=\"translate(117.528652 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_20\">\n     <g id=\"line2d_38\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"154.018726\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_19\">\n      <!-- 200 -->\n      <g transform=\"translate(144.474976 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_20\">\n    <g id=\"ytick_19\">\n     <g id=\"line2d_39\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"175.888456\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_20\">\n     <g id=\"line2d_40\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"120.62663\" xlink:href=\"#mccaf5e3cb4\" y=\"209.197279\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_48\">\n    <path d=\"M 120.62663 239.758125 \nL 120.62663 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_49\">\n    <path d=\"M 184.579572 239.758125 \nL 184.579572 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_50\">\n    <path d=\"M 120.62663 239.758125 \nL 184.579572 239.758125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_51\">\n    <path d=\"M 120.62663 175.805184 \nL 184.579572 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_20\">\n    <!-- 3 -->\n    <defs>\n     <path d=\"M 40.578125 39.3125 \nQ 47.65625 37.796875 51.625 33 \nQ 55.609375 28.21875 55.609375 21.1875 \nQ 55.609375 10.40625 48.1875 4.484375 \nQ 40.765625 -1.421875 27.09375 -1.421875 \nQ 22.515625 -1.421875 17.65625 -0.515625 \nQ 12.796875 0.390625 7.625 2.203125 \nL 7.625 11.71875 \nQ 11.71875 9.328125 16.59375 8.109375 \nQ 21.484375 6.890625 26.8125 6.890625 \nQ 36.078125 6.890625 40.9375 10.546875 \nQ 45.796875 14.203125 45.796875 21.1875 \nQ 45.796875 27.640625 41.28125 31.265625 \nQ 36.765625 34.90625 28.71875 34.90625 \nL 20.21875 34.90625 \nL 20.21875 43.015625 \nL 29.109375 43.015625 \nQ 36.375 43.015625 40.234375 45.921875 \nQ 44.09375 48.828125 44.09375 54.296875 \nQ 44.09375 59.90625 40.109375 62.90625 \nQ 36.140625 65.921875 28.71875 65.921875 \nQ 24.65625 65.921875 20.015625 65.03125 \nQ 15.375 64.15625 9.8125 62.3125 \nL 9.8125 71.09375 \nQ 15.4375 72.65625 20.34375 73.4375 \nQ 25.25 74.21875 29.59375 74.21875 \nQ 40.828125 74.21875 47.359375 69.109375 \nQ 53.90625 64.015625 53.90625 55.328125 \nQ 53.90625 49.265625 50.4375 45.09375 \nQ 46.96875 40.921875 40.578125 39.3125 \nz\n\" id=\"DejaVuSans-51\"/>\n    </defs>\n    <g transform=\"translate(148.785601 169.805184)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-51\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_11\">\n   <g id=\"patch_52\">\n    <path d=\"M 207.965761 239.758125 \nL 271.918702 239.758125 \nL 271.918702 175.805184 \nL 207.965761 175.805184 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#pd8c2866e3f)\">\n    <image height=\"64\" id=\"image4c2ab67cb4\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"207.965761\" xlink:href=\"data:image/png;base64,\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\" y=\"-175.758125\"/>\n   </g>\n   <g id=\"matplotlib.axis_21\">\n    <g id=\"xtick_21\">\n     <g id=\"line2d_41\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"208.049033\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_21\">\n      <!-- 0 -->\n      <g transform=\"translate(204.867783 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_22\">\n     <g id=\"line2d_42\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"241.357856\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_22\">\n      <!-- 200 -->\n      <g transform=\"translate(231.814106 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_22\">\n    <g id=\"ytick_21\">\n     <g id=\"line2d_43\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"175.888456\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_22\">\n     <g id=\"line2d_44\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"207.965761\" xlink:href=\"#mccaf5e3cb4\" y=\"209.197279\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_53\">\n    <path d=\"M 207.965761 239.758125 \nL 207.965761 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_54\">\n    <path d=\"M 271.918702 239.758125 \nL 271.918702 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_55\">\n    <path d=\"M 207.965761 239.758125 \nL 271.918702 239.758125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_56\">\n    <path d=\"M 207.965761 175.805184 \nL 271.918702 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_23\">\n    <!-- 2 -->\n    <g transform=\"translate(236.124731 169.805184)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-50\"/>\n    </g>\n   </g>\n  </g>\n  <g id=\"axes_12\">\n   <g id=\"patch_57\">\n    <path d=\"M 295.304891 239.758125 \nL 359.257832 239.758125 \nL 359.257832 175.805184 \nL 295.304891 175.805184 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g clip-path=\"url(#p32ca420a4a)\">\n    <image height=\"64\" id=\"image9ecd46ebd4\" transform=\"scale(1 -1)translate(0 -64)\" width=\"64\" x=\"295.304891\" xlink:href=\"data:image/png;base64,\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\" y=\"-175.758125\"/>\n   </g>\n   <g id=\"matplotlib.axis_23\">\n    <g id=\"xtick_23\">\n     <g id=\"line2d_45\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.388163\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_24\">\n      <!-- 0 -->\n      <g transform=\"translate(292.206913 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_24\">\n     <g id=\"line2d_46\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"328.696987\" xlink:href=\"#m8b14816655\" y=\"239.758125\"/>\n      </g>\n     </g>\n     <g id=\"text_25\">\n      <!-- 200 -->\n      <g transform=\"translate(319.153237 254.356563)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_24\">\n    <g id=\"ytick_23\">\n     <g id=\"line2d_47\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"175.888456\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_24\">\n     <g id=\"line2d_48\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"295.304891\" xlink:href=\"#mccaf5e3cb4\" y=\"209.197279\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"patch_58\">\n    <path d=\"M 295.304891 239.758125 \nL 295.304891 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_59\">\n    <path d=\"M 359.257832 239.758125 \nL 359.257832 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_60\">\n    <path d=\"M 295.304891 239.758125 \nL 359.257832 239.758125 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_61\">\n    <path d=\"M 295.304891 175.805184 \nL 359.257832 175.805184 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"text_26\">\n    <!-- 3 -->\n    <g transform=\"translate(323.463862 169.805184)scale(0.12 -0.12)\">\n     <use xlink:href=\"#DejaVuSans-51\"/>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"pf418dbeb2a\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"33.2875\" y=\"22.318125\"/>\n  </clipPath>\n  <clipPath id=\"p06ac690029\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"120.62663\" y=\"22.318125\"/>\n  </clipPath>\n  <clipPath id=\"p0b7210820c\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"207.965761\" y=\"22.318125\"/>\n  </clipPath>\n  <clipPath id=\"p27c9a05f4b\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"295.304891\" y=\"22.318125\"/>\n  </clipPath>\n  <clipPath id=\"p73d03e59e1\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"33.2875\" y=\"99.061654\"/>\n  </clipPath>\n  <clipPath id=\"p54ca43abe0\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"120.62663\" y=\"99.061654\"/>\n  </clipPath>\n  <clipPath id=\"p8aec0bd66e\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"207.965761\" y=\"99.061654\"/>\n  </clipPath>\n  <clipPath id=\"p5eddba1606\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"295.304891\" y=\"99.061654\"/>\n  </clipPath>\n  <clipPath id=\"p76eaddfd4a\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"33.2875\" y=\"175.805184\"/>\n  </clipPath>\n  <clipPath id=\"pdc0ccbcb08\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"120.62663\" y=\"175.805184\"/>\n  </clipPath>\n  <clipPath id=\"pd8c2866e3f\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"207.965761\" y=\"175.805184\"/>\n  </clipPath>\n  <clipPath id=\"p32ca420a4a\">\n   <rect height=\"63.952941\" width=\"63.952941\" x=\"295.304891\" y=\"175.805184\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "from albumentations import *\n",
    "from albumentations.pytorch import ToTensorV2\n",
    "from tqdm.notebook import tqdm\n",
    "import timm\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# meta 데이터와 이미지 경로를 불러옵니다.\n",
    "submission = pd.read_csv(os.path.join(test_dir, 'info.csv'))\n",
    "image_dir = os.path.join(test_dir, 'images')\n",
    "\n",
    "# Test Dataset 클래스 객체를 생성하고 DataLoader를 만듭니다.\n",
    "image_paths = [os.path.join(image_dir, img_id) for img_id in submission.ImageID]\n",
    "image_paths = image_paths[:12]\n",
    "transform = Compose([\n",
    "    Resize(384, 384, p=1.0),\n",
    "    ToTensorV2(),\n",
    "])\n",
    "dataset = TestDataset(image_paths, transform)\n",
    "\n",
    "loader = DataLoader(\n",
    "    dataset,\n",
    "    shuffle=False\n",
    ")\n",
    "\n",
    "# 모델을 정의합니다. (학습한 모델이 있다면 torch.load로 모델을 불러주세요!)\n",
    "device = torch.device('cuda')\n",
    "model_age = timm.create_model('efficientnet_b0', pretrained=False, num_classes=3).to(device)\n",
    "model_age.load_state_dict(torch.load('/opt/ml/code/results/Age/004_accuracy_91.64%_f1_0.89.ckpt'))\n",
    "model_age.eval()\n",
    "model_gender = timm.create_model('efficientnet_b0', pretrained=False, num_classes=2).to(device)\n",
    "model_gender.load_state_dict(torch.load('/opt/ml/code/results/Gender/003_accuracy_97.58%_f1_0.98.ckpt'))\n",
    "model_gender.eval()\n",
    "model_mask = timm.create_model('efficientnet_b0', pretrained=False, num_classes=3).to(device)\n",
    "model_mask.load_state_dict(torch.load('/opt/ml/code/results/Mask/001_accuracy_99.87%_f1_ 1.0.ckpt'))\n",
    "model_mask.eval()\n",
    "\n",
    "# 모델이 테스트 데이터셋을 예측하고 결과를 저장합니다.\n",
    "\n",
    "fig, axes = plt.subplots(3, 4, sharex=True, sharey=True)\n",
    "all_predictions = []\n",
    "loader = iter(loader)\n",
    "for i in range(12):\n",
    "    with torch.no_grad():\n",
    "        images = next(loader)\n",
    "        axes[i // 4][i % 4].imshow(images.squeeze(dim=0).permute(1, 2, 0))\n",
    "        images = images.to(device)\n",
    "        pred_age = model_age(images.float())\n",
    "        pred_age = pred_age.argmax(dim=-1)\n",
    "        pred_gender = model_gender(images.float())\n",
    "        pred_gender = pred_gender.argmax(dim=-1)\n",
    "        pred_mask = model_mask(images.float())\n",
    "        pred_mask = pred_mask.argmax(dim=-1)\n",
    "        pred = pred_mask * 6 + pred_gender * 3 + pred_age\n",
    "        axes[i // 4][i % 4].set_title(pred.item())\n",
    "\n",
    "# 제출할 파일을 저장합니다.\n",
    "submission.to_csv(os.path.join(test_dir, 'submission.csv'), index=False)\n",
    "print('test inference is done!')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python377jvsc74a57bd098b0a9b7b4eaaa670588a142fd0a9b87eaafe866f1db4228be72b4211d12040f",
   "display_name": "Python 3.7.7 64-bit ('base': conda)"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7-final"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}