cifar.ipynb

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      "gpuType": "T4",
      "authorship_tag": "ABX9TyMhoIBzgXEJsSv7Uzyr2dLT",
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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Diya910/git_test/blob/main/cifar.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "6MmxbK8TC075"
      },
      "outputs": [],
      "source": [
        "\n",
        "\n",
        "!mkdir -p ~/.kaggle\n",
        "!cp kaggle.json ~/.kaggle/\n",
        "!chmod 600 ~/.kaggle/kaggle.json\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!kaggle competitions download -c cifar-10"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O1e6hhKFEhRW",
        "outputId": "305d3cf5-9e98-4e8c-fff6-2d5d642bbc71"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading cifar-10.zip to /content\n",
            "100% 714M/715M [00:10<00:00, 124MB/s]\n",
            "100% 715M/715M [00:10<00:00, 69.3MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Qd3pIu8ErWY",
        "outputId": "bbc8762a-64d9-4664-a1a9-a867c73f0263"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#extracting the compressed Dataset\n",
        "from zipfile import ZipFile\n",
        "file_name = \"/content/cifar-10.zip\"\n",
        "\n",
        "with ZipFile(file_name, 'r') as zip:\n",
        "  zip.extractall()\n",
        "  print(\"Done\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dar7X-4ZFTp8",
        "outputId": "4d0a1b14-f35c-434c-ea6d-b1e3b456744c"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Done\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ls"
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      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install py7zr"
      ],
      "metadata": {
        "colab": {
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        "id": "IA_9JUplFxH2",
        "outputId": "12a46fd3-5248-4fee-b840-fb36b01ef2dc"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting py7zr\n",
            "  Downloading py7zr-0.21.0-py3-none-any.whl (67 kB)\n",
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            "\u001b[?25hCollecting texttable (from py7zr)\n",
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            "\u001b[?25hCollecting pyzstd>=0.15.9 (from py7zr)\n",
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            "\u001b[?25hCollecting pyppmd<1.2.0,>=1.1.0 (from py7zr)\n",
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            "  Downloading pybcj-1.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (49 kB)\n",
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            "\u001b[?25hCollecting multivolumefile>=0.2.3 (from py7zr)\n",
            "  Downloading multivolumefile-0.2.3-py3-none-any.whl (17 kB)\n",
            "Collecting inflate64<1.1.0,>=1.0.0 (from py7zr)\n",
            "  Downloading inflate64-1.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (93 kB)\n",
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            "\u001b[?25hCollecting brotli>=1.1.0 (from py7zr)\n",
            "  Downloading Brotli-1.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.0 MB)\n",
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            "\u001b[?25hRequirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from py7zr) (5.9.5)\n",
            "Installing collected packages: texttable, brotli, pyzstd, pyppmd, pycryptodomex, pybcj, multivolumefile, inflate64, py7zr\n",
            "Successfully installed brotli-1.1.0 inflate64-1.0.0 multivolumefile-0.2.3 py7zr-0.21.0 pybcj-1.0.2 pycryptodomex-3.20.0 pyppmd-1.1.0 pyzstd-0.15.10 texttable-1.7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import py7zr\n",
        "archive = py7zr.SevenZipFile('/content/train.7z', mode='r')\n",
        "archive.extractall()\n",
        "archive.close()"
      ],
      "metadata": {
        "id": "vOCH94XIF7T3"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Importing the libraries\n",
        "import os\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "from PIL import Image\n",
        "from sklearn.model_selection import train_test_split\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.image as mpimg\n",
        "import tensorflow as tf"
      ],
      "metadata": {
        "id": "Mljc_eDOGh9N"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filesname = os.listdir('/content/train')"
      ],
      "metadata": {
        "id": "H7C65MRuHOFT"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "type(filesname)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zBFRCXmHHibH",
        "outputId": "a1093e78-d73e-4f47-d73a-cf230e694270"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(filesname)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DfmXO8UKHlFU",
        "outputId": "167c5ee1-bfc3-487d-a739-efa8afe47601"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "50000"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(filesname[0:5])\n",
        "print(filesname[-5:])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gJQNIph2HqOC",
        "outputId": "de49404d-3396-4bdf-9adb-51335981f43a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['19476.png', '38875.png', '14991.png', '18403.png', '33309.png']\n",
            "['27153.png', '22462.png', '20992.png', '17197.png', '44649.png']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels_df = pd.read_csv('/content/trainLabels.csv')"
      ],
      "metadata": {
        "id": "GGmXzC0SH89P"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "3VjkNJMBIE8O",
        "outputId": "7b99909b-4ea9-44dc-fbf3-8cb807333b35"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "   id       label\n",
              "0   1        frog\n",
              "1   2       truck\n",
              "2   3       truck\n",
              "3   4        deer\n",
              "4   5  automobile"
            ],
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              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4baf7c70-ff3b-47ce-9089-b17f0d1a84c9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "labels_df",
              "summary": "{\n  \"name\": \"labels_df\",\n  \"rows\": 50000,\n  \"fields\": [\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14433,\n        \"min\": 1,\n        \"max\": 50000,\n        \"num_unique_values\": 50000,\n        \"samples\": [\n          33554,\n          9428,\n          200\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"dog\",\n          \"truck\",\n          \"horse\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels_df['label'].value_counts()"
      ],
      "metadata": {
        "id": "8x26ZPsgIOTB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "03a851f9-a17a-4708-daf5-f17691d58e2a"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "label\n",
              "frog          5000\n",
              "truck         5000\n",
              "deer          5000\n",
              "automobile    5000\n",
              "bird          5000\n",
              "horse         5000\n",
              "ship          5000\n",
              "cat           5000\n",
              "dog           5000\n",
              "airplane      5000\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels_dictionary = {'airplane':0, 'automobile':1, 'bird':2, 'cat':3, 'deer':4, 'dog':5, 'frog':6, 'horse':7, 'ship':8, 'truck':9}"
      ],
      "metadata": {
        "id": "NOU0VlqmPOoq"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels = [labels_dictionary[id] for id in labels_df['label']]"
      ],
      "metadata": {
        "id": "R2S-YZOnPe70"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(labels[0:5])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "itJIahcoPuwo",
        "outputId": "167f46f3-565a-4fc1-9e65-0281f3a06e31"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[6, 9, 9, 4, 1]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import cv2\n",
        "from google.colab.patches import cv2_imshow\n",
        "img = cv2.imread(os.path.join('/content/train', filesname[0]))\n",
        "cv2_imshow(img)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49
        },
        "id": "Y2rEuAXGP-kq",
        "outputId": "c957c9b7-2520-49e7-dfd0-27f540aa4d75"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=32x32>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "id_list = list(labels_df['id'])\n",
        "print(id_list[0:5])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fqmbyjPOQt5g",
        "outputId": "74fa48e0-9806-4c83-aaa6-d04492ea853b"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1, 2, 3, 4, 5]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert images to numpy arrays\n",
        "train_data_folder = '/content/train/'\n",
        "\n",
        "data = []\n",
        "\n",
        "for id in id_list:\n",
        "  image = Image.open(os.path.join(train_data_folder, str(id)+ '.png'))\n",
        "  image = np.array(image)\n",
        "  data.append(image)"
      ],
      "metadata": {
        "id": "FJqhnLXURGy_"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "type(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gMpPWO-xSxqt",
        "outputId": "ee2660c6-0704-416c-ab5a-77c49daff66f"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(data[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XfbZwYlFTX6W",
        "outputId": "31789387-adc7-4a73-ec1b-cbb584690389"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data[0].shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1wlAUBj8TghH",
        "outputId": "4661a6e8-ab95-4791-abab-f70420902b5e"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(32, 32, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 887
        },
        "id": "-IVRROmPTsLP",
        "outputId": "3adf202d-b19a-4196-f970-555d9e587854"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[[ 59,  62,  63],\n",
              "        [ 43,  46,  45],\n",
              "        [ 50,  48,  43],\n",
              "        ...,\n",
              "        [158, 132, 108],\n",
              "        [152, 125, 102],\n",
              "        [148, 124, 103]],\n",
              "\n",
              "       [[ 16,  20,  20],\n",
              "        [  0,   0,   0],\n",
              "        [ 18,   8,   0],\n",
              "        ...,\n",
              "        [123,  88,  55],\n",
              "        [119,  83,  50],\n",
              "        [122,  87,  57]],\n",
              "\n",
              "       [[ 25,  24,  21],\n",
              "        [ 16,   7,   0],\n",
              "        [ 49,  27,   8],\n",
              "        ...,\n",
              "        [118,  84,  50],\n",
              "        [120,  84,  50],\n",
              "        [109,  73,  42]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[208, 170,  96],\n",
              "        [201, 153,  34],\n",
              "        [198, 161,  26],\n",
              "        ...,\n",
              "        [160, 133,  70],\n",
              "        [ 56,  31,   7],\n",
              "        [ 53,  34,  20]],\n",
              "\n",
              "       [[180, 139,  96],\n",
              "        [173, 123,  42],\n",
              "        [186, 144,  30],\n",
              "        ...,\n",
              "        [184, 148,  94],\n",
              "        [ 97,  62,  34],\n",
              "        [ 83,  53,  34]],\n",
              "\n",
              "       [[177, 144, 116],\n",
              "        [168, 129,  94],\n",
              "        [179, 142,  87],\n",
              "        ...,\n",
              "        [216, 184, 140],\n",
              "        [151, 118,  84],\n",
              "        [123,  92,  72]]], dtype=uint8)"
            ],
            "text/html": [
              "<style>\n",
              "      .ndarray_repr .ndarray_raw_data {\n",
              "        display: none;\n",
              "      }\n",
              "      .ndarray_repr.show_array .ndarray_raw_data {\n",
              "        display: block;\n",
              "      }\n",
              "      .ndarray_repr.show_array .ndarray_image_preview {\n",
              "        display: none;\n",
              "      }\n",
              "      </style>\n",
              "      <div id=\"id-c6ef2929-be49-4954-b01c-6dc2ca46673d\" class=\"ndarray_repr\"><pre>ndarray (32, 32, 3) <button style=\"padding: 0 2px;\">show data</button></pre><img src=\"data:image/png;base64,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\" class=\"ndarray_image_preview\" /><pre class=\"ndarray_raw_data\">array([[[ 59,  62,  63],\n",
              "        [ 43,  46,  45],\n",
              "        [ 50,  48,  43],\n",
              "        ...,\n",
              "        [158, 132, 108],\n",
              "        [152, 125, 102],\n",
              "        [148, 124, 103]],\n",
              "\n",
              "       [[ 16,  20,  20],\n",
              "        [  0,   0,   0],\n",
              "        [ 18,   8,   0],\n",
              "        ...,\n",
              "        [123,  88,  55],\n",
              "        [119,  83,  50],\n",
              "        [122,  87,  57]],\n",
              "\n",
              "       [[ 25,  24,  21],\n",
              "        [ 16,   7,   0],\n",
              "        [ 49,  27,   8],\n",
              "        ...,\n",
              "        [118,  84,  50],\n",
              "        [120,  84,  50],\n",
              "        [109,  73,  42]],\n",
              "\n",
              "       ...,\n",
              "\n",
              "       [[208, 170,  96],\n",
              "        [201, 153,  34],\n",
              "        [198, 161,  26],\n",
              "        ...,\n",
              "        [160, 133,  70],\n",
              "        [ 56,  31,   7],\n",
              "        [ 53,  34,  20]],\n",
              "\n",
              "       [[180, 139,  96],\n",
              "        [173, 123,  42],\n",
              "        [186, 144,  30],\n",
              "        ...,\n",
              "        [184, 148,  94],\n",
              "        [ 97,  62,  34],\n",
              "        [ 83,  53,  34]],\n",
              "\n",
              "       [[177, 144, 116],\n",
              "        [168, 129,  94],\n",
              "        [179, 142,  87],\n",
              "        ...,\n",
              "        [216, 184, 140],\n",
              "        [151, 118,  84],\n",
              "        [123,  92,  72]]], dtype=uint8)</pre></div><script>\n",
              "      (() => {\n",
              "      const titles = ['show data', 'hide data'];\n",
              "      let index = 0\n",
              "      document.querySelector('#id-c6ef2929-be49-4954-b01c-6dc2ca46673d button').onclick = (e) => {\n",
              "        document.querySelector('#id-c6ef2929-be49-4954-b01c-6dc2ca46673d').classList.toggle('show_array');\n",
              "        index = (++index) % 2;\n",
              "        document.querySelector('#id-c6ef2929-be49-4954-b01c-6dc2ca46673d button').textContent = titles[index];\n",
              "        e.preventDefault();\n",
              "        e.stopPropagation();\n",
              "      }\n",
              "      })();\n",
              "    </script>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from re import X\n",
        "# convert images and labels to numpy arrays\n",
        "\n",
        "X = np.array(data)\n",
        "y = np.array(labels)"
      ],
      "metadata": {
        "id": "OWyRAjLoT3pR"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "QgHlzskdUTpv"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_scaled = X_train / 255\n",
        "X_test_scaled = X_test / 255"
      ],
      "metadata": {
        "id": "sEfPU5_yUkjw"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Building the Neural Network\n",
        "from tensorflow import keras"
      ],
      "metadata": {
        "id": "52ZPDhvGVFQE"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "num_of_classes = 10\n",
        "model = tf.keras.Sequential([\n",
        "    keras.layers.Flatten(input_shape=(32,32,3)),\n",
        "    keras.layers.Dense(64,activation='relu'),\n",
        "    keras.layers.Dense(num_of_classes,activation='softmax')\n",
        "]\n",
        ")"
      ],
      "metadata": {
        "id": "E1rfK_a9VROE"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Compiling and Optimizing model\n",
        "model.compile(optimizer='adam',\n",
        "              loss='sparse_categorical_crossentropy',\n",
        "              metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "7GXnsv5SWCNG"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X_train_scaled, y_train, epochs=10, validation_split=0.1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XLSDrc9jWsQa",
        "outputId": "4733c12f-a5fe-40ad-a847-d88b3bad037a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "1125/1125 [==============================] - 5s 3ms/step - loss: 1.9979 - accuracy: 0.2591 - val_loss: 1.9853 - val_accuracy: 0.2645\n",
            "Epoch 2/10\n",
            "1125/1125 [==============================] - 3s 3ms/step - loss: 1.8741 - accuracy: 0.3179 - val_loss: 1.8634 - val_accuracy: 0.3282\n",
            "Epoch 3/10\n",
            "1125/1125 [==============================] - 4s 4ms/step - loss: 1.8328 - accuracy: 0.3347 - val_loss: 1.8011 - val_accuracy: 0.3467\n",
            "Epoch 4/10\n",
            "1125/1125 [==============================] - 5s 4ms/step - loss: 1.8040 - accuracy: 0.3483 - val_loss: 1.7999 - val_accuracy: 0.3498\n",
            "Epoch 5/10\n",
            "1125/1125 [==============================] - 4s 3ms/step - loss: 1.7824 - accuracy: 0.3550 - val_loss: 1.7845 - val_accuracy: 0.3548\n",
            "Epoch 6/10\n",
            "1125/1125 [==============================] - 3s 3ms/step - loss: 1.7724 - accuracy: 0.3630 - val_loss: 1.7795 - val_accuracy: 0.3602\n",
            "Epoch 7/10\n",
            "1125/1125 [==============================] - 3s 3ms/step - loss: 1.7624 - accuracy: 0.3661 - val_loss: 1.7614 - val_accuracy: 0.3618\n",
            "Epoch 8/10\n",
            "1125/1125 [==============================] - 3s 3ms/step - loss: 1.7567 - accuracy: 0.3689 - val_loss: 1.7898 - val_accuracy: 0.3458\n",
            "Epoch 9/10\n",
            "1125/1125 [==============================] - 4s 4ms/step - loss: 1.7448 - accuracy: 0.3734 - val_loss: 1.7595 - val_accuracy: 0.3660\n",
            "Epoch 10/10\n",
            "1125/1125 [==============================] - 4s 4ms/step - loss: 1.7410 - accuracy: 0.3752 - val_loss: 1.9633 - val_accuracy: 0.3072\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7b118e52dc90>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#ResNet50\n",
        "from tensorflow.keras import Sequential,models,layers\n",
        "from tensorflow.keras.layers import Dense,Flatten,Dropout\n",
        "from tensorflow.keras.layers import BatchNormalization\n",
        "from tensorflow.keras.models import load_model\n",
        "from tensorflow.keras.models import Model\n",
        "from tensorflow.keras.applications import ResNet50\n",
        "from tensorflow.keras import optimizers"
      ],
      "metadata": {
        "id": "N3GcOd4KXPuO"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "convolutional_base = ResNet50(weights='imagenet',include_top=False,input_shape=(256,256,3))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NvvrGuJDYZyJ",
        "outputId": "ce8d479c-9a80-407e-f51c-77c58eecd9b4"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "94765736/94765736 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "convolutional_base.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L_2GARhnYsbM",
        "outputId": "9ee3b909-bb35-4e97-8c51-148e1330d20c"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"resnet50\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                Output Shape                 Param #   Connected to                  \n",
            "==================================================================================================\n",
            " input_1 (InputLayer)        [(None, 256, 256, 3)]        0         []                            \n",
            "                                                                                                  \n",
            " conv1_pad (ZeroPadding2D)   (None, 262, 262, 3)          0         ['input_1[0][0]']             \n",
            "                                                                                                  \n",
            " conv1_conv (Conv2D)         (None, 128, 128, 64)         9472      ['conv1_pad[0][0]']           \n",
            "                                                                                                  \n",
            " conv1_bn (BatchNormalizati  (None, 128, 128, 64)         256       ['conv1_conv[0][0]']          \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv1_relu (Activation)     (None, 128, 128, 64)         0         ['conv1_bn[0][0]']            \n",
            "                                                                                                  \n",
            " pool1_pad (ZeroPadding2D)   (None, 130, 130, 64)         0         ['conv1_relu[0][0]']          \n",
            "                                                                                                  \n",
            " pool1_pool (MaxPooling2D)   (None, 64, 64, 64)           0         ['pool1_pad[0][0]']           \n",
            "                                                                                                  \n",
            " conv2_block1_1_conv (Conv2  (None, 64, 64, 64)           4160      ['pool1_pool[0][0]']          \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_1_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block1_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block1_1_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block1_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block1_2_conv (Conv2  (None, 64, 64, 64)           36928     ['conv2_block1_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_2_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block1_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block1_2_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block1_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block1_0_conv (Conv2  (None, 64, 64, 256)          16640     ['pool1_pool[0][0]']          \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_3_conv (Conv2  (None, 64, 64, 256)          16640     ['conv2_block1_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block1_0_bn (BatchNo  (None, 64, 64, 256)          1024      ['conv2_block1_0_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block1_3_bn (BatchNo  (None, 64, 64, 256)          1024      ['conv2_block1_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block1_add (Add)      (None, 64, 64, 256)          0         ['conv2_block1_0_bn[0][0]',   \n",
            "                                                                     'conv2_block1_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv2_block1_out (Activati  (None, 64, 64, 256)          0         ['conv2_block1_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv2_block2_1_conv (Conv2  (None, 64, 64, 64)           16448     ['conv2_block1_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block2_1_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block2_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block2_1_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block2_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block2_2_conv (Conv2  (None, 64, 64, 64)           36928     ['conv2_block2_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block2_2_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block2_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block2_2_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block2_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block2_3_conv (Conv2  (None, 64, 64, 256)          16640     ['conv2_block2_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block2_3_bn (BatchNo  (None, 64, 64, 256)          1024      ['conv2_block2_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block2_add (Add)      (None, 64, 64, 256)          0         ['conv2_block1_out[0][0]',    \n",
            "                                                                     'conv2_block2_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv2_block2_out (Activati  (None, 64, 64, 256)          0         ['conv2_block2_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv2_block3_1_conv (Conv2  (None, 64, 64, 64)           16448     ['conv2_block2_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block3_1_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block3_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block3_1_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block3_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block3_2_conv (Conv2  (None, 64, 64, 64)           36928     ['conv2_block3_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block3_2_bn (BatchNo  (None, 64, 64, 64)           256       ['conv2_block3_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block3_2_relu (Activ  (None, 64, 64, 64)           0         ['conv2_block3_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv2_block3_3_conv (Conv2  (None, 64, 64, 256)          16640     ['conv2_block3_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv2_block3_3_bn (BatchNo  (None, 64, 64, 256)          1024      ['conv2_block3_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv2_block3_add (Add)      (None, 64, 64, 256)          0         ['conv2_block2_out[0][0]',    \n",
            "                                                                     'conv2_block3_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv2_block3_out (Activati  (None, 64, 64, 256)          0         ['conv2_block3_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv3_block1_1_conv (Conv2  (None, 32, 32, 128)          32896     ['conv2_block3_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_1_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block1_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block1_1_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block1_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block1_2_conv (Conv2  (None, 32, 32, 128)          147584    ['conv3_block1_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_2_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block1_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block1_2_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block1_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block1_0_conv (Conv2  (None, 32, 32, 512)          131584    ['conv2_block3_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_3_conv (Conv2  (None, 32, 32, 512)          66048     ['conv3_block1_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block1_0_bn (BatchNo  (None, 32, 32, 512)          2048      ['conv3_block1_0_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block1_3_bn (BatchNo  (None, 32, 32, 512)          2048      ['conv3_block1_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block1_add (Add)      (None, 32, 32, 512)          0         ['conv3_block1_0_bn[0][0]',   \n",
            "                                                                     'conv3_block1_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv3_block1_out (Activati  (None, 32, 32, 512)          0         ['conv3_block1_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv3_block2_1_conv (Conv2  (None, 32, 32, 128)          65664     ['conv3_block1_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block2_1_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block2_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block2_1_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block2_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block2_2_conv (Conv2  (None, 32, 32, 128)          147584    ['conv3_block2_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block2_2_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block2_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block2_2_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block2_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block2_3_conv (Conv2  (None, 32, 32, 512)          66048     ['conv3_block2_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block2_3_bn (BatchNo  (None, 32, 32, 512)          2048      ['conv3_block2_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block2_add (Add)      (None, 32, 32, 512)          0         ['conv3_block1_out[0][0]',    \n",
            "                                                                     'conv3_block2_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv3_block2_out (Activati  (None, 32, 32, 512)          0         ['conv3_block2_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv3_block3_1_conv (Conv2  (None, 32, 32, 128)          65664     ['conv3_block2_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block3_1_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block3_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block3_1_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block3_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block3_2_conv (Conv2  (None, 32, 32, 128)          147584    ['conv3_block3_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block3_2_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block3_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block3_2_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block3_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block3_3_conv (Conv2  (None, 32, 32, 512)          66048     ['conv3_block3_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block3_3_bn (BatchNo  (None, 32, 32, 512)          2048      ['conv3_block3_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block3_add (Add)      (None, 32, 32, 512)          0         ['conv3_block2_out[0][0]',    \n",
            "                                                                     'conv3_block3_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv3_block3_out (Activati  (None, 32, 32, 512)          0         ['conv3_block3_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv3_block4_1_conv (Conv2  (None, 32, 32, 128)          65664     ['conv3_block3_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block4_1_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block4_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block4_1_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block4_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block4_2_conv (Conv2  (None, 32, 32, 128)          147584    ['conv3_block4_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block4_2_bn (BatchNo  (None, 32, 32, 128)          512       ['conv3_block4_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block4_2_relu (Activ  (None, 32, 32, 128)          0         ['conv3_block4_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv3_block4_3_conv (Conv2  (None, 32, 32, 512)          66048     ['conv3_block4_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv3_block4_3_bn (BatchNo  (None, 32, 32, 512)          2048      ['conv3_block4_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv3_block4_add (Add)      (None, 32, 32, 512)          0         ['conv3_block3_out[0][0]',    \n",
            "                                                                     'conv3_block4_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv3_block4_out (Activati  (None, 32, 32, 512)          0         ['conv3_block4_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block1_1_conv (Conv2  (None, 16, 16, 256)          131328    ['conv3_block4_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block1_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block1_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block1_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block1_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block1_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block1_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block1_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block1_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block1_0_conv (Conv2  (None, 16, 16, 1024)         525312    ['conv3_block4_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block1_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block1_0_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block1_0_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block1_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block1_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block1_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block1_0_bn[0][0]',   \n",
            "                                                                     'conv4_block1_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block1_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block1_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block2_1_conv (Conv2  (None, 16, 16, 256)          262400    ['conv4_block1_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block2_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block2_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block2_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block2_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block2_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block2_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block2_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block2_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block2_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block2_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block2_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block2_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block2_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block2_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block2_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block1_out[0][0]',    \n",
            "                                                                     'conv4_block2_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block2_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block2_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block3_1_conv (Conv2  (None, 16, 16, 256)          262400    ['conv4_block2_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block3_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block3_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block3_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block3_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block3_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block3_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block3_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block3_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block3_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block3_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block3_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block3_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block3_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block3_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block3_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block2_out[0][0]',    \n",
            "                                                                     'conv4_block3_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block3_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block3_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block4_1_conv (Conv2  (None, 16, 16, 256)          262400    ['conv4_block3_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block4_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block4_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block4_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block4_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block4_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block4_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block4_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block4_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block4_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block4_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block4_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block4_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block4_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block4_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block4_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block3_out[0][0]',    \n",
            "                                                                     'conv4_block4_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block4_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block4_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block5_1_conv (Conv2  (None, 16, 16, 256)          262400    ['conv4_block4_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block5_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block5_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block5_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block5_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block5_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block5_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block5_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block5_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block5_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block5_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block5_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block5_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block5_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block5_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block5_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block4_out[0][0]',    \n",
            "                                                                     'conv4_block5_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block5_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block5_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv4_block6_1_conv (Conv2  (None, 16, 16, 256)          262400    ['conv4_block5_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block6_1_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block6_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block6_1_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block6_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block6_2_conv (Conv2  (None, 16, 16, 256)          590080    ['conv4_block6_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block6_2_bn (BatchNo  (None, 16, 16, 256)          1024      ['conv4_block6_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block6_2_relu (Activ  (None, 16, 16, 256)          0         ['conv4_block6_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv4_block6_3_conv (Conv2  (None, 16, 16, 1024)         263168    ['conv4_block6_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv4_block6_3_bn (BatchNo  (None, 16, 16, 1024)         4096      ['conv4_block6_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv4_block6_add (Add)      (None, 16, 16, 1024)         0         ['conv4_block5_out[0][0]',    \n",
            "                                                                     'conv4_block6_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv4_block6_out (Activati  (None, 16, 16, 1024)         0         ['conv4_block6_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv5_block1_1_conv (Conv2  (None, 8, 8, 512)            524800    ['conv4_block6_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_1_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block1_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block1_1_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block1_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block1_2_conv (Conv2  (None, 8, 8, 512)            2359808   ['conv5_block1_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_2_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block1_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block1_2_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block1_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block1_0_conv (Conv2  (None, 8, 8, 2048)           2099200   ['conv4_block6_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_3_conv (Conv2  (None, 8, 8, 2048)           1050624   ['conv5_block1_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block1_0_bn (BatchNo  (None, 8, 8, 2048)           8192      ['conv5_block1_0_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block1_3_bn (BatchNo  (None, 8, 8, 2048)           8192      ['conv5_block1_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block1_add (Add)      (None, 8, 8, 2048)           0         ['conv5_block1_0_bn[0][0]',   \n",
            "                                                                     'conv5_block1_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv5_block1_out (Activati  (None, 8, 8, 2048)           0         ['conv5_block1_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv5_block2_1_conv (Conv2  (None, 8, 8, 512)            1049088   ['conv5_block1_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block2_1_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block2_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block2_1_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block2_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block2_2_conv (Conv2  (None, 8, 8, 512)            2359808   ['conv5_block2_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block2_2_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block2_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block2_2_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block2_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block2_3_conv (Conv2  (None, 8, 8, 2048)           1050624   ['conv5_block2_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block2_3_bn (BatchNo  (None, 8, 8, 2048)           8192      ['conv5_block2_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block2_add (Add)      (None, 8, 8, 2048)           0         ['conv5_block1_out[0][0]',    \n",
            "                                                                     'conv5_block2_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv5_block2_out (Activati  (None, 8, 8, 2048)           0         ['conv5_block2_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            " conv5_block3_1_conv (Conv2  (None, 8, 8, 512)            1049088   ['conv5_block2_out[0][0]']    \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block3_1_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block3_1_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block3_1_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block3_1_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block3_2_conv (Conv2  (None, 8, 8, 512)            2359808   ['conv5_block3_1_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block3_2_bn (BatchNo  (None, 8, 8, 512)            2048      ['conv5_block3_2_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block3_2_relu (Activ  (None, 8, 8, 512)            0         ['conv5_block3_2_bn[0][0]']   \n",
            " ation)                                                                                           \n",
            "                                                                                                  \n",
            " conv5_block3_3_conv (Conv2  (None, 8, 8, 2048)           1050624   ['conv5_block3_2_relu[0][0]'] \n",
            " D)                                                                                               \n",
            "                                                                                                  \n",
            " conv5_block3_3_bn (BatchNo  (None, 8, 8, 2048)           8192      ['conv5_block3_3_conv[0][0]'] \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " conv5_block3_add (Add)      (None, 8, 8, 2048)           0         ['conv5_block2_out[0][0]',    \n",
            "                                                                     'conv5_block3_3_bn[0][0]']   \n",
            "                                                                                                  \n",
            " conv5_block3_out (Activati  (None, 8, 8, 2048)           0         ['conv5_block3_add[0][0]']    \n",
            " on)                                                                                              \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 23587712 (89.98 MB)\n",
            "Trainable params: 23534592 (89.78 MB)\n",
            "Non-trainable params: 53120 (207.50 KB)\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = models.Sequential()\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(layers.UpSampling2D((2,2)))\n",
        "model.add(convolutional_base)\n",
        "model.add(Flatten())\n",
        "model.add(BatchNormalization())\n",
        "model.add(Dense(128, activation='relu'))\n",
        "model.add(Dropout(0.5))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Dense(64, activation='relu'))\n",
        "model.add(Dropout(0.5))\n",
        "model.add(BatchNormalization())\n",
        "model.add(Dense(10, activation='softmax'))"
      ],
      "metadata": {
        "id": "kQmG6oqvZjEs"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(loss='sparse_categorical_crossentropy',optimizer=optimizers.RMSprop(lr=2e-5),metrics=['acc'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6mz7qjwWbBJB",
        "outputId": "3497ac02-2d88-4df1-e0de-733d1fce48ca"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:`lr` is deprecated in Keras optimizer, please use `learning_rate` or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.RMSprop.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "history = model.fit(X_train_scaled, y_train, epochs=10, validation_split=0.1)"
      ],
      "metadata": {
        "id": "iKZaCVRBfGn1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "h = history\n",
        "plt.plot(h.history['loss'], label='train loss')\n",
        "plt.plot(h.history['val_loss'], label='validation loss')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "\n",
        "plt.plot(h.history['acc'], label='train acc')\n",
        "plt.plot(h.history['val_acc'], label='validation acc')\n",
        "plt.legend()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "uUc6ioVMcecn"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}