python37.[실습05]_합성곱_신경망(2)_transferLearning.ipynb

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"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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 95
        },
        "id": "5ElGeFaA9l3B",
        "outputId": "9cd875b4-2cf5-49b6-ea4b-305ae93c392c"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-67c7e88a-b1c8-4cc6-9a9a-42c98706e6c8\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-67c7e88a-b1c8-4cc6-9a9a-42c98706e6c8\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving utils.py to utils.py\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "38073"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "HihbQvqyC_Hn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b34c2feb-8aad-4360-b0f1-6eed50da37aa"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!unzip /content/drive/MyDrive/aircraft.zip"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K3V6zHU_2lfC",
        "outputId": "6a612e5c-6078-4a03-8a40-9f9875687c72"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  /content/drive/MyDrive/aircraft.zip\n",
            "   creating: aircraft/test/\n",
            "   creating: aircraft/test/airplane/\n",
            "  inflating: aircraft/test/airplane/a_test01.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test02.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test03.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test04.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test05.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test06.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test07.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test08.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test09.jpeg  \n",
            "  inflating: aircraft/test/airplane/a_test10.jpeg  \n",
            "   creating: aircraft/test/helicopter/\n",
            "  inflating: aircraft/test/helicopter/h_test01.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test02.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test03.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test04.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test05.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test06.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test07.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test08.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test09.jpeg  \n",
            "  inflating: aircraft/test/helicopter/h_test10.jpeg  \n",
            "   creating: aircraft/train/\n",
            "   creating: aircraft/train/airplane/\n",
            "  inflating: aircraft/train/airplane/a_train01.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train02.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train03.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train04.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train05.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train06.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train07.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train08.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train09.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train10.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train11.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train12.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train13.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train14.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train15.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train16.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train17.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train18.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train19.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train20.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train21.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train22.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train23.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train24.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train25.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train26.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train27.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train28.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train29.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train30.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train31.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train32.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train33.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train34.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train35.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train36.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train37.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train38.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train39.jpeg  \n",
            "  inflating: aircraft/train/airplane/a_train40.jpeg  \n",
            "   creating: aircraft/train/helicopter/\n",
            "  inflating: aircraft/train/helicopter/h_train01.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train02.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train03.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train04.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train05.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train06.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train07.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train08.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train09.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train10.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train11.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train12.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train13.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train14.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train15.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train16.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train17.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train18.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train19.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train20.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train21.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train22.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train23.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train24.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train25.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train26.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train27.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train28.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train29.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train30.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train31.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train32.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train33.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train34.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train35.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train36.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train37.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train38.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train39.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train40.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train41.jpeg  \n",
            "  inflating: aircraft/train/helicopter/h_train42.jpeg  \n",
            "   creating: aircraft/valid/\n",
            "   creating: aircraft/valid/airplane/\n",
            "  inflating: aircraft/valid/airplane/a_valid01.jpeg  \n",
            "  inflating: aircraft/valid/airplane/a_valid02.jpeg  \n",
            "  inflating: aircraft/valid/airplane/a_valid03.jpeg  \n",
            "  inflating: aircraft/valid/airplane/a_valid04.jpeg  \n",
            "  inflating: aircraft/valid/airplane/a_valid05.jpeg  \n",
            "  inflating: aircraft/valid/airplane/a_valid06.jpeg  \n",
            "   creating: aircraft/valid/helicopter/\n",
            "  inflating: aircraft/valid/helicopter/h_valid01.jpeg  \n",
            "  inflating: aircraft/valid/helicopter/h_valid02.jpeg  \n",
            "  inflating: aircraft/valid/helicopter/h_valid03.jpeg  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1. Settings\n",
        "### 1) Important required libraries"
      ],
      "metadata": {
        "id": "V5F7k0uKrCDx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "import torch.nn.init as init\n",
        "import torch.utils.data as data\n",
        "import torchvision.datasets as dset\n",
        "import torchvision.models as models\n",
        "import torchvision.transforms as transforms\n",
        "from torch.utils.data import DataLoader\n",
        "from torch.autograd import Variable\n",
        "import time\n",
        "import matplotlib.pyplot as plt\n",
        "import utils"
      ],
      "metadata": {
        "id": "F2zrtA7HTN90"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2) Hyperparameter"
      ],
      "metadata": {
        "id": "xAgQMianrNr7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "batch_size = 16 #64  #1\n",
        "learning_rate = 0.0001\n",
        "epoch = 20\n",
        " \n",
        "n_node = 1024 # customized last layer의 노드 수. 64, 128, 256, 512, 1025\n",
        "dropratio = 0.5 # 얼마나 drop시킬지 inverse keepratio\n",
        "\n",
        "imgsize = 256"
      ],
      "metadata": {
        "id": "wDd-YjQVVnNq"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2. Data Loader\n",
        "### 트레이닝 데이터"
      ],
      "metadata": {
        "id": "bAuBnsmWrVbd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# img_dir = \"../../../images/painting_dataset/real_artwork_divided_shffl_4K/Train\"\n",
        "img_dir = \"aircraft/train\"\n",
        "train_data = dset.ImageFolder(img_dir, transforms.Compose([\n",
        "            transforms.CenterCrop(imgsize*2),  # CenterCrop(512)\n",
        "            transforms.RandomCrop(imgsize),    # RandomCrop\n",
        "            transforms.RandomHorizontalFlip(), # RandomHorizontalFlip\n",
        "    \n",
        "            transforms.Resize(imgsize),\n",
        "            transforms.ToTensor()\n",
        "        ]))\n",
        "print(train_data.__len__())\n",
        "\n",
        "train_batch = data.DataLoader(train_data, batch_size=batch_size, shuffle=True, num_workers=2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "awQljmw7VpIg",
        "outputId": "8b6a4601-71e9-41eb-a7f3-59caea6d075e"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "82\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 고정된 데이터 셋"
      ],
      "metadata": {
        "id": "pPBEzp35riZ3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 2. Dev data\n",
        "# img_dir = \"../../../images/painting_dataset/real_artwork_divided_shffl_4K/Valid\"\n",
        "img_dir = \"aircraft/valid\"\n",
        "dev_data = dset.ImageFolder(img_dir, transforms.Compose([\n",
        "            #transforms.Scale(256),\n",
        "            #transforms.RandomSizedCrop(224),\n",
        "    \n",
        "            transforms.CenterCrop(size=imgsize),\n",
        "            transforms.Resize(imgsize),\n",
        "            transforms.ToTensor()\n",
        "            ]))\n",
        "dev_batch = data.DataLoader(dev_data, batch_size=batch_size,\n",
        "                            shuffle=False, num_workers=2)"
      ],
      "metadata": {
        "id": "-vb0kwqtVqUn"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# 3. Test data\n",
        "img_dir = \"aircraft/test\"\n",
        "test_data = dset.ImageFolder(img_dir, transforms.Compose([\n",
        "            #transforms.Scale(256),\n",
        "            #transforms.RandomSizedCrop(224),\n",
        "    \n",
        "            transforms.CenterCrop(size=imgsize),\n",
        "            transforms.Resize(imgsize),\n",
        "            transforms.ToTensor()\n",
        "            ]))\n",
        "\n",
        "test_batch = data.DataLoader(test_data, batch_size=batch_size,\n",
        "                             shuffle=False, num_workers=2)"
      ],
      "metadata": {
        "id": "PgySZyG7Vrxb"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nclass = len(train_data.classes)\n",
        "print(\"# of classes: %d\" %nclass)\n",
        "print(train_data.classes)\n",
        "print(train_data.class_to_idx)\n",
        "print(train_data.__len__())\n",
        "\n",
        "print(\"Training: %d, Dev: %d, Test: %d\"\n",
        "     %(train_data.__len__(), dev_data.__len__(), test_data.__len__()))\n",
        "\n",
        "# for imgs, labels in train_batch:\n",
        "#     for j in range(len(imgs)):\n",
        "#         img = transforms.ToPILImage()(imgs[j])\n",
        "#         plt.title(\"label: %d\" %labels[j])\n",
        "#         plt.imshow(img)\n",
        "#         plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S2vg0plyVtOn",
        "outputId": "14010639-07a6-489b-e6bd-3afaa72d46c1"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# of classes: 2\n",
            "['airplane', 'helicopter']\n",
            "{'airplane': 0, 'helicopter': 1}\n",
            "82\n",
            "Training: 82, Dev: 9, Test: 20\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_data.classes)\n",
        "print(dev_data.classes)\n",
        "print(test_data.classes)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AkwR6WPOVumi",
        "outputId": "bb80d583-267d-4d52-9666-c6d158d198e2"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['airplane', 'helicopter']\n",
            "['airplane', 'helicopter']\n",
            "['airplane', 'helicopter']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3. Model\n",
        "### 1) Pretrained VGG Model"
      ],
      "metadata": {
        "id": "w08f1QkTroPr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "vgg = models.vgg19(pretrained=True)\n",
        "\n",
        "for name, module in vgg.named_children():\n",
        "    print(name)\n",
        "\n",
        "print(list(vgg.children())[0])\n",
        "print(list(vgg.children())[-1])\n",
        "\n",
        "# cnt = 0\n",
        "# for i in model.children():\n",
        "#     print(\"ysb[%d]\" %cnt)\n",
        "#     print(i)\n",
        "#     cnt = cnt+1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 993,
          "referenced_widgets": [
            "7ce37381c1924bec8fa012ebbb750b91",
            "c463ac434ddc439d9c353cb596d9af60",
            "2766c4eeb0604b74a06312243178ee44",
            "1cb440ff2f1144378cfe3510c55cd774",
            "0afbec039fb049c9b95dee10bc108820",
            "84df47ff619b4f2e9e84059849fb3144",
            "28a61cc9ede849b8824d46e137941d7e",
            "58cefea3c11841e194f3b7a33de984c8",
            "eb3270dd49914eb3b0dc93f21f6be3a7",
            "6fc54a6c177a41ed8bc4b6c98a7d2a59",
            "f279026fd75049d582edd0047376adf1"
          ]
        },
        "id": "aBxj1t52Vv1p",
        "outputId": "a987b1c0-17c6-479f-90d0-86f140301814"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Downloading: \"https://download.pytorch.org/models/vgg19-dcbb9e9d.pth\" to /root/.cache/torch/hub/checkpoints/vgg19-dcbb9e9d.pth\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0.00/548M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7ce37381c1924bec8fa012ebbb750b91"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "features\n",
            "avgpool\n",
            "classifier\n",
            "Sequential(\n",
            "  (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (1): ReLU(inplace=True)\n",
            "  (2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (3): ReLU(inplace=True)\n",
            "  (4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (6): ReLU(inplace=True)\n",
            "  (7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (8): ReLU(inplace=True)\n",
            "  (9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (11): ReLU(inplace=True)\n",
            "  (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (13): ReLU(inplace=True)\n",
            "  (14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (15): ReLU(inplace=True)\n",
            "  (16): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (17): ReLU(inplace=True)\n",
            "  (18): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (19): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (20): ReLU(inplace=True)\n",
            "  (21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (22): ReLU(inplace=True)\n",
            "  (23): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (24): ReLU(inplace=True)\n",
            "  (25): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (26): ReLU(inplace=True)\n",
            "  (27): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (29): ReLU(inplace=True)\n",
            "  (30): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (31): ReLU(inplace=True)\n",
            "  (32): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (33): ReLU(inplace=True)\n",
            "  (34): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (35): ReLU(inplace=True)\n",
            "  (36): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            ")\n",
            "Sequential(\n",
            "  (0): Linear(in_features=25088, out_features=4096, bias=True)\n",
            "  (1): ReLU(inplace=True)\n",
            "  (2): Dropout(p=0.5, inplace=False)\n",
            "  (3): Linear(in_features=4096, out_features=4096, bias=True)\n",
            "  (4): ReLU(inplace=True)\n",
            "  (5): Dropout(p=0.5, inplace=False)\n",
            "  (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
            ")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(list(vgg.children())[0][0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LnOXG8zGVxCI",
        "outputId": "2577201b-081c-45ef-c187-33833979b23a"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2) Customized Fully Model"
      ],
      "metadata": {
        "id": "vd6rLeRWryGf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "base_dim = 64\n",
        "fsize = int(imgsize/32)\n",
        "\n",
        "class MyVGG(nn.Module):\n",
        "    def __init__(self):\n",
        "        super(MyVGG, self).__init__()\n",
        "        # [0]: features(conv), [1]: classifier(fc)\n",
        "        self.layer0 = nn.Sequential(*list(vgg.children())[0])\n",
        "\n",
        "        self.layer1 = nn.Sequential(\n",
        "            nn.Linear(8*base_dim * fsize * fsize, n_node),\n",
        "            nn.BatchNorm1d(n_node),\n",
        "            nn.ReLU(),\n",
        "            nn.Dropout2d(dropratio),  # 0.3 만큼 drop 하자.\n",
        "\n",
        "            nn.Linear(n_node, n_node),\n",
        "            nn.BatchNorm1d(n_node),\n",
        "            nn.ReLU(),\n",
        "            nn.Dropout2d(dropratio),\n",
        "\n",
        "            nn.Linear(n_node, n_node),\n",
        "            nn.BatchNorm1d(n_node),\n",
        "            nn.ReLU(),\n",
        "            nn.Dropout2d(dropratio),\n",
        "\n",
        "            nn.Linear(n_node, nclass),\n",
        "        )\n",
        "        # weigth initialization\n",
        "        for m in self.layer1.modules():\n",
        "            #print(m)\n",
        "            if isinstance(m, nn.Conv2d):\n",
        "                init.kaiming_normal(m.weight.data) # ReLU 일 때\n",
        "                m.bias.data.fill_(0)\n",
        "            if isinstance(m, nn.Linear):\n",
        "                init.kaiming_normal(m.weight.data)\n",
        "                m.bias.data.fill_(0)\n",
        "\n",
        "    def forward(self, x):\n",
        "        # layer0의 사이즈를 무식하게 프린트하여 알아낼 수 있음(batchsize, x,x,x)\n",
        "        # print(x.size())\n",
        "        out = self.layer0(x)\n",
        "        out = out.view(out.size(0), -1)\n",
        "        out = self.layer1(out)\n",
        "        return out"
      ],
      "metadata": {
        "id": "dm0QSdihVy3H"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3) Model on GPU"
      ],
      "metadata": {
        "id": "O9EQRRgEr4Zz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = MyVGG().cuda()\n",
        "\n",
        "for params in model.layer0.parameters():\n",
        "    params.required_grad = False\n",
        "    \n",
        "for params in model.layer1.parameters():\n",
        "    params.required_grad = True"
      ],
      "metadata": {
        "id": "gSjtoBBZV0C7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eecbdf93-cf18-451f-8af5-1af5444b8508"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:35: UserWarning: nn.init.kaiming_normal is now deprecated in favor of nn.init.kaiming_normal_.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for name in model.children():\n",
        "    print(name)"
      ],
      "metadata": {
        "id": "Bfovvl8XV17t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8cc2d7a5-78e8-429b-e6d9-9939e2acd3ee"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sequential(\n",
            "  (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (1): ReLU(inplace=True)\n",
            "  (2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (3): ReLU(inplace=True)\n",
            "  (4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (6): ReLU(inplace=True)\n",
            "  (7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (8): ReLU(inplace=True)\n",
            "  (9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (11): ReLU(inplace=True)\n",
            "  (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (13): ReLU(inplace=True)\n",
            "  (14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (15): ReLU(inplace=True)\n",
            "  (16): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (17): ReLU(inplace=True)\n",
            "  (18): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (19): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (20): ReLU(inplace=True)\n",
            "  (21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (22): ReLU(inplace=True)\n",
            "  (23): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (24): ReLU(inplace=True)\n",
            "  (25): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (26): ReLU(inplace=True)\n",
            "  (27): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            "  (28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (29): ReLU(inplace=True)\n",
            "  (30): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (31): ReLU(inplace=True)\n",
            "  (32): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (33): ReLU(inplace=True)\n",
            "  (34): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
            "  (35): ReLU(inplace=True)\n",
            "  (36): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
            ")\n",
            "Sequential(\n",
            "  (0): Linear(in_features=32768, out_features=1024, bias=True)\n",
            "  (1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  (2): ReLU()\n",
            "  (3): Dropout2d(p=0.5, inplace=False)\n",
            "  (4): Linear(in_features=1024, out_features=1024, bias=True)\n",
            "  (5): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  (6): ReLU()\n",
            "  (7): Dropout2d(p=0.5, inplace=False)\n",
            "  (8): Linear(in_features=1024, out_features=1024, bias=True)\n",
            "  (9): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
            "  (10): ReLU()\n",
            "  (11): Dropout2d(p=0.5, inplace=False)\n",
            "  (12): Linear(in_features=1024, out_features=2, bias=True)\n",
            ")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4. Optimizer & Loss"
      ],
      "metadata": {
        "id": "W1td92sCr8uV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "loss_func = nn.CrossEntropyLoss()\n",
        "optimizer = optim.Adam(model.layer1.parameters(), lr=learning_rate)"
      ],
      "metadata": {
        "id": "jzdKrOxG3TXy"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5. Train"
      ],
      "metadata": {
        "id": "W1L9pDZysCPU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import utils\n",
        "\n",
        "total_time = 0\n",
        "disp_step = 10\n",
        "\n",
        "to_train = True\n",
        "if (to_train == False):\n",
        "    netname = '/catdog_vgg19_10.pkl'\n",
        "    model = torch.load(netname)\n",
        "else:\n",
        "    print(\"3 layer, n_node: %d, dropratio: %.2f\" %(n_node, dropratio))\n",
        "    model.eval() # evaluation(test) mode로 바꾸기 -> dropout, batch normalization에 영향을 줌.\n",
        "    train_corr = utils.ComputeCorr(train_batch, model)\n",
        "    dev_corr = utils.ComputeCorr(dev_batch, model)\n",
        "    test_corr = utils.ComputeCorr(test_batch, model)\n",
        "    print(\"Correct of train: %.2f, dev: %.2f, test: %.2f\"%(train_corr, dev_corr, test_corr))\n",
        "    model.train()\n",
        "    \n",
        "    netname = '/catdog_vgg19'\n",
        "    \n",
        "    # graph 그리기\n",
        "    x_epoch = []\n",
        "    y_train_err = []\n",
        "    y_dev_err = []\n",
        "    y_test_err = []\n",
        "    \n",
        "    x_epoch.append(0)\n",
        "    y_train_err.append(100.0-train_corr)\n",
        "    y_dev_err.append(100.0-dev_corr)\n",
        "    y_test_err.append(100.0-test_corr)\n",
        "    \n",
        "#    # 학습을 재시작한다면\n",
        "#    netname = '../almondpeanut_vgg19.pkl'\n",
        "#    model = torch.load(netname)\n",
        "#    # 파라미터 학습 여부 결정\n",
        "#    for params in model.layer0.parameters():\n",
        "#        params.required_grad = False\n",
        "\n",
        "#    for params in model.layer1.parameters():\n",
        "#        params.required_grad = True\n",
        "#    for i in range(34, epoch):\n",
        "   \n",
        "    # 재시작하지 않는다면\n",
        "    for i in range(epoch):\n",
        "        start_time = time.time()\n",
        "        print(\"%d..\" %i),\n",
        "        for img, label in train_batch:\n",
        "            img = Variable(img).cuda()\n",
        "            label = Variable(label).cuda()\n",
        "            \n",
        "            optimizer.zero_grad()\n",
        "            output = model(img)\n",
        "            loss = loss_func(output, label)\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "            \n",
        "        end_time = time.time()\n",
        "        duration = end_time - start_time\n",
        "        total_time += duration\n",
        "        if (i % disp_step ==0) or (i==epoch-1):\n",
        "            torch.save(model, netname+'_%d.pkl' %i, )\n",
        "            print(\"\\[%d/%d] loss: %.3f, \" %(i, epoch, (loss.cpu()).data.numpy())),\n",
        "        \n",
        "            # evaluation(test) mode로 바꾸기 -> dropout, batch normalization에 영향을 줌.\n",
        "            model.eval() \n",
        "        \n",
        "            # train, dev, train accr\n",
        "            train_corr = utils.ComputeCorr(train_batch, model)\n",
        "            dev_corr = utils.ComputeCorr(dev_batch, model)\n",
        "            test_corr = utils.ComputeCorr(test_batch, model)\n",
        "            print(\"Correct of train: %.2f, dev: %.2f, test: %.2f, \"\n",
        "                 %(train_corr, dev_corr, test_corr)),\n",
        "            model.train()\n",
        "            print(\"time: %.2f sec...\" %(total_time))\n",
        "        \n",
        "            # graph 그리기 \n",
        "            x_epoch.append(i+1)\n",
        "            y_train_err.append(100.0-train_corr)\n",
        "            y_dev_err.append(100.0-dev_corr)\n",
        "            y_test_err.append(100.0-test_corr)\n",
        "    print(\"Total time: %.2f sec\" %total_time)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7BVI8SM63V9g",
        "outputId": "57cd0b1d-a114-4529-811b-b98d0677c9b0"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3 layer, n_node: 1024, dropratio: 0.50\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:1320: UserWarning: dropout2d: Received a 2-D input to dropout2d, which is deprecated and will result in an error in a future release. To retain the behavior and silence this warning, please use dropout instead. Note that dropout2d exists to provide channel-wise dropout on inputs with 2 spatial dimensions, a channel dimension, and an optional batch dimension (i.e. 3D or 4D inputs).\n",
            "  warnings.warn(warn_msg)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Correct of train: 51.22, dev: 55.56, test: 45.00\n",
            "0..\n",
            "\\[0/20] loss: 0.693, \n",
            "Correct of train: 52.44, dev: 100.00, test: 60.00, \n",
            "time: 2.00 sec...\n",
            "1..\n",
            "2..\n",
            "3..\n",
            "4..\n",
            "5..\n",
            "6..\n",
            "7..\n",
            "8..\n",
            "9..\n",
            "10..\n",
            "\\[10/20] loss: 0.692, \n",
            "Correct of train: 75.61, dev: 88.89, test: 70.00, \n",
            "time: 22.61 sec...\n",
            "11..\n",
            "12..\n",
            "13..\n",
            "14..\n",
            "15..\n",
            "16..\n",
            "17..\n",
            "18..\n",
            "19..\n",
            "\\[19/20] loss: 0.681, \n",
            "Correct of train: 78.05, dev: 88.89, test: 70.00, \n",
            "time: 40.48 sec...\n",
            "Total time: 40.48 sec\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# epoch-err curve\n",
        "if (to_train):\n",
        "    plt.plot(x_epoch, y_train_err, color='black', label='train err', linestyle='--')\n",
        "    plt.plot(x_epoch, y_dev_err, color='red', label='dev err')\n",
        "    plt.plot(x_epoch, y_test_err, color='blue', label='test err')\n",
        "    \n",
        "    plt.xlabel('epoch')\n",
        "    plt.ylabel('err')\n",
        "    plt.title('epoch & err graph')\n",
        "    plt.legend(loc = \"upper right\")\n",
        "    plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "id": "e0FYeJay3Y0A",
        "outputId": "c9e72dc4-d676-479e-d82f-fa7d9621ed88"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 6. Evaluation for dev & test data"
      ],
      "metadata": {
        "id": "hxo2BHRusHkU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model.eval()\n",
        "utils.EvaluateClassifier(dev_batch, model, dev_data.classes, batch_size)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 952
        },
        "id": "XDVnFt8rBpZ3",
        "outputId": "e5eef52f-0625-4628-a8e5-87ca5a6c860d"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:1320: UserWarning: dropout2d: Received a 2-D input to dropout2d, which is deprecated and will result in an error in a future release. To retain the behavior and silence this warning, please use dropout instead. Note that dropout2d exists to provide channel-wise dropout on inputs with 2 spatial dimensions, a channel dimension, and an optional batch dimension (i.e. 3D or 4D inputs).\n",
            "  warnings.warn(warn_msg)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Normalized confusion matrix\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion matrix, without normalization\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\t acc  |\t pre  |\t rec  |\t f1\n",
            " airplane: 0.89 |\t 1.00 |\t 0.83 |\t 0.91\n",
            " helicopter: 0.89 |\t 0.75 |\t 1.00 |\t 0.86\n",
            "*accuracy: 0.89, precision: 0.88, recall: 0.92, *f1 score: 0.88\n",
            "[AP]\n",
            "airplane: 0.98\n",
            "helicopter: 0.92\n",
            "\n",
            "[mAP] 0.946\n",
            "[miAP] 0.944\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0, 0, 0, 1, 0, 0, 1, 1, 1]),\n",
              " array([0, 0, 0, 0, 0, 0, 1, 1, 1]),\n",
              " array([0.76845729, 0.86865604, 0.5129844 , 0.60980302, 0.66639078,\n",
              "        0.91498655, 0.70356846, 0.84988642, 0.50209439]))"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.eval()\n",
        "_, _, _ = utils.EvaluateClassifier(test_batch, model, test_data.classes, batch_size)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 879
        },
        "id": "MMS_fzojBsGf",
        "outputId": "1f973349-9ff3-491f-eafe-554c29e3c6e1"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:1320: UserWarning: dropout2d: Received a 2-D input to dropout2d, which is deprecated and will result in an error in a future release. To retain the behavior and silence this warning, please use dropout instead. Note that dropout2d exists to provide channel-wise dropout on inputs with 2 spatial dimensions, a channel dimension, and an optional batch dimension (i.e. 3D or 4D inputs).\n",
            "  warnings.warn(warn_msg)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Normalized confusion matrix\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confusion matrix, without normalization\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\t acc  |\t pre  |\t rec  |\t f1\n",
            " airplane: 0.70 |\t 0.62 |\t 1.00 |\t 0.77\n",
            " helicopter: 0.70 |\t 1.00 |\t 0.40 |\t 0.57\n",
            "*accuracy: 0.70, precision: 0.81, recall: 0.70, *f1 score: 0.67\n",
            "[AP]\n",
            "airplane: 0.94\n",
            "helicopter: 0.93\n",
            "\n",
            "[mAP] 0.931\n",
            "[miAP] 0.850\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "utils.VisTFPred(dev_batch, model, test_data.classes, batch_size, i_n=2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "okQtoeOtButX",
        "outputId": "58b3a418-5820-44c6-fde9-d93b8340f351"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:1320: UserWarning: dropout2d: Received a 2-D input to dropout2d, which is deprecated and will result in an error in a future release. To retain the behavior and silence this warning, please use dropout instead. Note that dropout2d exists to provide channel-wise dropout on inputs with 2 spatial dimensions, a channel dimension, and an optional batch dimension (i.e. 3D or 4D inputs).\n",
            "  warnings.warn(warn_msg)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Category: airplane\n",
            " True predicted images/total airplane category: 5 / 6\n",
            "Predicted probability:\n",
            "[0.7684573  0.23154269]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Predicted probability:\n",
            "[0.86865604 0.13134396]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " False predicted images/total airplane category: 1 / 6\n",
            "Predicted probability:\n",
            "[0.39019698 0.609803  ]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Category: helicopter\n",
            " True predicted images/total helicopter category: 3 / 3\n",
            "Predicted probability:\n",
            "[0.29643157 0.70356846]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Predicted probability:\n",
            "[0.1501136 0.8498864]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " False predicted images/total helicopter category: 0 / 3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "U7MzWC5WBwQA"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}