food_classifcation.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/freyaldi/ML/blob/main/food_classifcation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LkCQL-d0mds-"
      },
      "source": [
        "# Roadmap\n",
        "1. Convolution Layer\n",
        "2. Max Pooling\n",
        "3. 1 Hidden Layer Consist of 100 Neurons ReLu\n",
        "4. Output Layer 2 Neurons, Softmax activiton function\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cg4FArXTqdj-"
      },
      "source": [
        "## Import Required Libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ieO44V57NTQC"
      },
      "outputs": [],
      "source": [
        "import tensorflow as tf\n",
        "import matplotlib.pyplot as plt\n",
        "import pathlib\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "import numpy as np\n",
        "from google.colab import files\n",
        "from keras.preprocessing import image\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.image as mpimg\n",
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NXgZDYJLd5TO"
      },
      "source": [
        "##Download The Inception V3 Weights"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gssqNHTsd_DD",
        "outputId": "250b8e91-4e8d-4081-b1d7-e05e4f872ace"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2022-06-12 02:08:23--  https://storage.googleapis.com/mledu-datasets/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "Resolving storage.googleapis.com (storage.googleapis.com)... 172.253.117.128, 74.125.197.128, 74.125.135.128, ...\n",
            "Connecting to storage.googleapis.com (storage.googleapis.com)|172.253.117.128|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 87910968 (84M) [application/x-hdf]\n",
            "Saving to: ‘/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5’\n",
            "\n",
            "/tmp/inception_v3_w 100%[===================>]  83.84M   331MB/s    in 0.3s    \n",
            "\n",
            "2022-06-12 02:08:24 (331 MB/s) - ‘/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5’ saved [87910968/87910968]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget --no-check-certificate \\\n",
        "    https://storage.googleapis.com/mledu-datasets/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5 \\\n",
        "    -O /tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "APJCGBRVeeB8"
      },
      "outputs": [],
      "source": [
        "# Import the inception model  \n",
        "from tensorflow.keras.applications.inception_v3 import InceptionV3\n",
        "\n",
        "# Create an instance of the inception model from the local pre-trained weights\n",
        "local_weights_file = '/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5'"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TYfKEIIme35w"
      },
      "source": [
        "##Pre-trained Model Function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KNx-IIzFefYh"
      },
      "outputs": [],
      "source": [
        "def create_pre_trained_model(local_weights_file):\n",
        "\n",
        "  pre_trained_model = InceptionV3(input_shape = (256, 256, 3),\n",
        "                                  include_top = False, \n",
        "                                  weights = None) \n",
        "\n",
        "  pre_trained_model.load_weights(local_weights_file)\n",
        "\n",
        "  # Make all the layers in the pre-trained model non-trainable\n",
        "  for layer in pre_trained_model.layers:\n",
        "    layer.trainable = False\n",
        "\n",
        "  return pre_trained_model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f8sX7bqqe-W0",
        "outputId": "f8a5d30a-3030-4df1-b877-fee11339c32f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"inception_v3\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                   Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            " input_2 (InputLayer)           [(None, 256, 256, 3  0           []                               \n",
            "                                )]                                                                \n",
            "                                                                                                  \n",
            " conv2d_98 (Conv2D)             (None, 127, 127, 32  864         ['input_2[0][0]']                \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " batch_normalization_94 (BatchN  (None, 127, 127, 32  96         ['conv2d_98[0][0]']              \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " activation_94 (Activation)     (None, 127, 127, 32  0           ['batch_normalization_94[0][0]'] \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " conv2d_99 (Conv2D)             (None, 125, 125, 32  9216        ['activation_94[0][0]']          \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " batch_normalization_95 (BatchN  (None, 125, 125, 32  96         ['conv2d_99[0][0]']              \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " activation_95 (Activation)     (None, 125, 125, 32  0           ['batch_normalization_95[0][0]'] \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " conv2d_100 (Conv2D)            (None, 125, 125, 64  18432       ['activation_95[0][0]']          \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " batch_normalization_96 (BatchN  (None, 125, 125, 64  192        ['conv2d_100[0][0]']             \n",
            " ormalization)                  )                                                                 \n",
            "                                                                                                  \n",
            " activation_96 (Activation)     (None, 125, 125, 64  0           ['batch_normalization_96[0][0]'] \n",
            "                                )                                                                 \n",
            "                                                                                                  \n",
            " max_pooling2d_8 (MaxPooling2D)  (None, 62, 62, 64)  0           ['activation_96[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_101 (Conv2D)            (None, 62, 62, 80)   5120        ['max_pooling2d_8[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_97 (BatchN  (None, 62, 62, 80)  240         ['conv2d_101[0][0]']             \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_97 (Activation)     (None, 62, 62, 80)   0           ['batch_normalization_97[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_102 (Conv2D)            (None, 60, 60, 192)  138240      ['activation_97[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_98 (BatchN  (None, 60, 60, 192)  576        ['conv2d_102[0][0]']             \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_98 (Activation)     (None, 60, 60, 192)  0           ['batch_normalization_98[0][0]'] \n",
            "                                                                                                  \n",
            " max_pooling2d_9 (MaxPooling2D)  (None, 29, 29, 192)  0          ['activation_98[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_106 (Conv2D)            (None, 29, 29, 64)   12288       ['max_pooling2d_9[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_102 (Batch  (None, 29, 29, 64)  192         ['conv2d_106[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_102 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_102[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_104 (Conv2D)            (None, 29, 29, 48)   9216        ['max_pooling2d_9[0][0]']        \n",
            "                                                                                                  \n",
            " conv2d_107 (Conv2D)            (None, 29, 29, 96)   55296       ['activation_102[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_100 (Batch  (None, 29, 29, 48)  144         ['conv2d_104[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_103 (Batch  (None, 29, 29, 96)  288         ['conv2d_107[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_100 (Activation)    (None, 29, 29, 48)   0           ['batch_normalization_100[0][0]']\n",
            "                                                                                                  \n",
            " activation_103 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_103[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_9 (AveragePo  (None, 29, 29, 192)  0          ['max_pooling2d_9[0][0]']        \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_103 (Conv2D)            (None, 29, 29, 64)   12288       ['max_pooling2d_9[0][0]']        \n",
            "                                                                                                  \n",
            " conv2d_105 (Conv2D)            (None, 29, 29, 64)   76800       ['activation_100[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_108 (Conv2D)            (None, 29, 29, 96)   82944       ['activation_103[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_109 (Conv2D)            (None, 29, 29, 32)   6144        ['average_pooling2d_9[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_99 (BatchN  (None, 29, 29, 64)  192         ['conv2d_103[0][0]']             \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_101 (Batch  (None, 29, 29, 64)  192         ['conv2d_105[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_104 (Batch  (None, 29, 29, 96)  288         ['conv2d_108[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_105 (Batch  (None, 29, 29, 32)  96          ['conv2d_109[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_99 (Activation)     (None, 29, 29, 64)   0           ['batch_normalization_99[0][0]'] \n",
            "                                                                                                  \n",
            " activation_101 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_101[0][0]']\n",
            "                                                                                                  \n",
            " activation_104 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_104[0][0]']\n",
            "                                                                                                  \n",
            " activation_105 (Activation)    (None, 29, 29, 32)   0           ['batch_normalization_105[0][0]']\n",
            "                                                                                                  \n",
            " mixed0 (Concatenate)           (None, 29, 29, 256)  0           ['activation_99[0][0]',          \n",
            "                                                                  'activation_101[0][0]',         \n",
            "                                                                  'activation_104[0][0]',         \n",
            "                                                                  'activation_105[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_113 (Conv2D)            (None, 29, 29, 64)   16384       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_109 (Batch  (None, 29, 29, 64)  192         ['conv2d_113[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_109 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_109[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_111 (Conv2D)            (None, 29, 29, 48)   12288       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_114 (Conv2D)            (None, 29, 29, 96)   55296       ['activation_109[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_107 (Batch  (None, 29, 29, 48)  144         ['conv2d_111[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_110 (Batch  (None, 29, 29, 96)  288         ['conv2d_114[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_107 (Activation)    (None, 29, 29, 48)   0           ['batch_normalization_107[0][0]']\n",
            "                                                                                                  \n",
            " activation_110 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_110[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_10 (AverageP  (None, 29, 29, 256)  0          ['mixed0[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_110 (Conv2D)            (None, 29, 29, 64)   16384       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_112 (Conv2D)            (None, 29, 29, 64)   76800       ['activation_107[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_115 (Conv2D)            (None, 29, 29, 96)   82944       ['activation_110[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_116 (Conv2D)            (None, 29, 29, 64)   16384       ['average_pooling2d_10[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_106 (Batch  (None, 29, 29, 64)  192         ['conv2d_110[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_108 (Batch  (None, 29, 29, 64)  192         ['conv2d_112[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_111 (Batch  (None, 29, 29, 96)  288         ['conv2d_115[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_112 (Batch  (None, 29, 29, 64)  192         ['conv2d_116[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_106 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_106[0][0]']\n",
            "                                                                                                  \n",
            " activation_108 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_108[0][0]']\n",
            "                                                                                                  \n",
            " activation_111 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_111[0][0]']\n",
            "                                                                                                  \n",
            " activation_112 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_112[0][0]']\n",
            "                                                                                                  \n",
            " mixed1 (Concatenate)           (None, 29, 29, 288)  0           ['activation_106[0][0]',         \n",
            "                                                                  'activation_108[0][0]',         \n",
            "                                                                  'activation_111[0][0]',         \n",
            "                                                                  'activation_112[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_120 (Conv2D)            (None, 29, 29, 64)   18432       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_116 (Batch  (None, 29, 29, 64)  192         ['conv2d_120[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_116 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_116[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_118 (Conv2D)            (None, 29, 29, 48)   13824       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_121 (Conv2D)            (None, 29, 29, 96)   55296       ['activation_116[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_114 (Batch  (None, 29, 29, 48)  144         ['conv2d_118[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_117 (Batch  (None, 29, 29, 96)  288         ['conv2d_121[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_114 (Activation)    (None, 29, 29, 48)   0           ['batch_normalization_114[0][0]']\n",
            "                                                                                                  \n",
            " activation_117 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_117[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_11 (AverageP  (None, 29, 29, 288)  0          ['mixed1[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_117 (Conv2D)            (None, 29, 29, 64)   18432       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_119 (Conv2D)            (None, 29, 29, 64)   76800       ['activation_114[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_122 (Conv2D)            (None, 29, 29, 96)   82944       ['activation_117[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_123 (Conv2D)            (None, 29, 29, 64)   18432       ['average_pooling2d_11[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_113 (Batch  (None, 29, 29, 64)  192         ['conv2d_117[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_115 (Batch  (None, 29, 29, 64)  192         ['conv2d_119[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_118 (Batch  (None, 29, 29, 96)  288         ['conv2d_122[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_119 (Batch  (None, 29, 29, 64)  192         ['conv2d_123[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_113 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_113[0][0]']\n",
            "                                                                                                  \n",
            " activation_115 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_115[0][0]']\n",
            "                                                                                                  \n",
            " activation_118 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_118[0][0]']\n",
            "                                                                                                  \n",
            " activation_119 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_119[0][0]']\n",
            "                                                                                                  \n",
            " mixed2 (Concatenate)           (None, 29, 29, 288)  0           ['activation_113[0][0]',         \n",
            "                                                                  'activation_115[0][0]',         \n",
            "                                                                  'activation_118[0][0]',         \n",
            "                                                                  'activation_119[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_125 (Conv2D)            (None, 29, 29, 64)   18432       ['mixed2[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_121 (Batch  (None, 29, 29, 64)  192         ['conv2d_125[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_121 (Activation)    (None, 29, 29, 64)   0           ['batch_normalization_121[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_126 (Conv2D)            (None, 29, 29, 96)   55296       ['activation_121[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_122 (Batch  (None, 29, 29, 96)  288         ['conv2d_126[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_122 (Activation)    (None, 29, 29, 96)   0           ['batch_normalization_122[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_124 (Conv2D)            (None, 14, 14, 384)  995328      ['mixed2[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_127 (Conv2D)            (None, 14, 14, 96)   82944       ['activation_122[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_120 (Batch  (None, 14, 14, 384)  1152       ['conv2d_124[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_123 (Batch  (None, 14, 14, 96)  288         ['conv2d_127[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_120 (Activation)    (None, 14, 14, 384)  0           ['batch_normalization_120[0][0]']\n",
            "                                                                                                  \n",
            " activation_123 (Activation)    (None, 14, 14, 96)   0           ['batch_normalization_123[0][0]']\n",
            "                                                                                                  \n",
            " max_pooling2d_10 (MaxPooling2D  (None, 14, 14, 288)  0          ['mixed2[0][0]']                 \n",
            " )                                                                                                \n",
            "                                                                                                  \n",
            " mixed3 (Concatenate)           (None, 14, 14, 768)  0           ['activation_120[0][0]',         \n",
            "                                                                  'activation_123[0][0]',         \n",
            "                                                                  'max_pooling2d_10[0][0]']       \n",
            "                                                                                                  \n",
            " conv2d_132 (Conv2D)            (None, 14, 14, 128)  98304       ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_128 (Batch  (None, 14, 14, 128)  384        ['conv2d_132[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_128 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_128[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_133 (Conv2D)            (None, 14, 14, 128)  114688      ['activation_128[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_129 (Batch  (None, 14, 14, 128)  384        ['conv2d_133[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_129 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_129[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_129 (Conv2D)            (None, 14, 14, 128)  98304       ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_134 (Conv2D)            (None, 14, 14, 128)  114688      ['activation_129[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_125 (Batch  (None, 14, 14, 128)  384        ['conv2d_129[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_130 (Batch  (None, 14, 14, 128)  384        ['conv2d_134[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_125 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_125[0][0]']\n",
            "                                                                                                  \n",
            " activation_130 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_130[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_130 (Conv2D)            (None, 14, 14, 128)  114688      ['activation_125[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_135 (Conv2D)            (None, 14, 14, 128)  114688      ['activation_130[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_126 (Batch  (None, 14, 14, 128)  384        ['conv2d_130[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_131 (Batch  (None, 14, 14, 128)  384        ['conv2d_135[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_126 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_126[0][0]']\n",
            "                                                                                                  \n",
            " activation_131 (Activation)    (None, 14, 14, 128)  0           ['batch_normalization_131[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_12 (AverageP  (None, 14, 14, 768)  0          ['mixed3[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_128 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_131 (Conv2D)            (None, 14, 14, 192)  172032      ['activation_126[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_136 (Conv2D)            (None, 14, 14, 192)  172032      ['activation_131[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_137 (Conv2D)            (None, 14, 14, 192)  147456      ['average_pooling2d_12[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_124 (Batch  (None, 14, 14, 192)  576        ['conv2d_128[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_127 (Batch  (None, 14, 14, 192)  576        ['conv2d_131[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_132 (Batch  (None, 14, 14, 192)  576        ['conv2d_136[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_133 (Batch  (None, 14, 14, 192)  576        ['conv2d_137[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_124 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_124[0][0]']\n",
            "                                                                                                  \n",
            " activation_127 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_127[0][0]']\n",
            "                                                                                                  \n",
            " activation_132 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_132[0][0]']\n",
            "                                                                                                  \n",
            " activation_133 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_133[0][0]']\n",
            "                                                                                                  \n",
            " mixed4 (Concatenate)           (None, 14, 14, 768)  0           ['activation_124[0][0]',         \n",
            "                                                                  'activation_127[0][0]',         \n",
            "                                                                  'activation_132[0][0]',         \n",
            "                                                                  'activation_133[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_142 (Conv2D)            (None, 14, 14, 160)  122880      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_138 (Batch  (None, 14, 14, 160)  480        ['conv2d_142[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_138 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_138[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_143 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_138[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_139 (Batch  (None, 14, 14, 160)  480        ['conv2d_143[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_139 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_139[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_139 (Conv2D)            (None, 14, 14, 160)  122880      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_144 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_139[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_135 (Batch  (None, 14, 14, 160)  480        ['conv2d_139[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_140 (Batch  (None, 14, 14, 160)  480        ['conv2d_144[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_135 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_135[0][0]']\n",
            "                                                                                                  \n",
            " activation_140 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_140[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_140 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_135[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_145 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_140[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_136 (Batch  (None, 14, 14, 160)  480        ['conv2d_140[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_141 (Batch  (None, 14, 14, 160)  480        ['conv2d_145[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_136 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_136[0][0]']\n",
            "                                                                                                  \n",
            " activation_141 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_141[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_13 (AverageP  (None, 14, 14, 768)  0          ['mixed4[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_138 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_141 (Conv2D)            (None, 14, 14, 192)  215040      ['activation_136[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_146 (Conv2D)            (None, 14, 14, 192)  215040      ['activation_141[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_147 (Conv2D)            (None, 14, 14, 192)  147456      ['average_pooling2d_13[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_134 (Batch  (None, 14, 14, 192)  576        ['conv2d_138[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_137 (Batch  (None, 14, 14, 192)  576        ['conv2d_141[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_142 (Batch  (None, 14, 14, 192)  576        ['conv2d_146[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_143 (Batch  (None, 14, 14, 192)  576        ['conv2d_147[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_134 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_134[0][0]']\n",
            "                                                                                                  \n",
            " activation_137 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_137[0][0]']\n",
            "                                                                                                  \n",
            " activation_142 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_142[0][0]']\n",
            "                                                                                                  \n",
            " activation_143 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_143[0][0]']\n",
            "                                                                                                  \n",
            " mixed5 (Concatenate)           (None, 14, 14, 768)  0           ['activation_134[0][0]',         \n",
            "                                                                  'activation_137[0][0]',         \n",
            "                                                                  'activation_142[0][0]',         \n",
            "                                                                  'activation_143[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_152 (Conv2D)            (None, 14, 14, 160)  122880      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_148 (Batch  (None, 14, 14, 160)  480        ['conv2d_152[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_148 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_148[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_153 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_148[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_149 (Batch  (None, 14, 14, 160)  480        ['conv2d_153[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_149 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_149[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_149 (Conv2D)            (None, 14, 14, 160)  122880      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_154 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_149[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_145 (Batch  (None, 14, 14, 160)  480        ['conv2d_149[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_150 (Batch  (None, 14, 14, 160)  480        ['conv2d_154[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_145 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_145[0][0]']\n",
            "                                                                                                  \n",
            " activation_150 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_150[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_150 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_145[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_155 (Conv2D)            (None, 14, 14, 160)  179200      ['activation_150[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_146 (Batch  (None, 14, 14, 160)  480        ['conv2d_150[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_151 (Batch  (None, 14, 14, 160)  480        ['conv2d_155[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_146 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_146[0][0]']\n",
            "                                                                                                  \n",
            " activation_151 (Activation)    (None, 14, 14, 160)  0           ['batch_normalization_151[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_14 (AverageP  (None, 14, 14, 768)  0          ['mixed5[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_148 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_151 (Conv2D)            (None, 14, 14, 192)  215040      ['activation_146[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_156 (Conv2D)            (None, 14, 14, 192)  215040      ['activation_151[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_157 (Conv2D)            (None, 14, 14, 192)  147456      ['average_pooling2d_14[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_144 (Batch  (None, 14, 14, 192)  576        ['conv2d_148[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_147 (Batch  (None, 14, 14, 192)  576        ['conv2d_151[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_152 (Batch  (None, 14, 14, 192)  576        ['conv2d_156[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_153 (Batch  (None, 14, 14, 192)  576        ['conv2d_157[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_144 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_144[0][0]']\n",
            "                                                                                                  \n",
            " activation_147 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_147[0][0]']\n",
            "                                                                                                  \n",
            " activation_152 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_152[0][0]']\n",
            "                                                                                                  \n",
            " activation_153 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_153[0][0]']\n",
            "                                                                                                  \n",
            " mixed6 (Concatenate)           (None, 14, 14, 768)  0           ['activation_144[0][0]',         \n",
            "                                                                  'activation_147[0][0]',         \n",
            "                                                                  'activation_152[0][0]',         \n",
            "                                                                  'activation_153[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_162 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_158 (Batch  (None, 14, 14, 192)  576        ['conv2d_162[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_158 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_158[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_163 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_158[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_159 (Batch  (None, 14, 14, 192)  576        ['conv2d_163[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_159 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_159[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_159 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_164 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_159[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_155 (Batch  (None, 14, 14, 192)  576        ['conv2d_159[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_160 (Batch  (None, 14, 14, 192)  576        ['conv2d_164[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_155 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_155[0][0]']\n",
            "                                                                                                  \n",
            " activation_160 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_160[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_160 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_155[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_165 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_160[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_156 (Batch  (None, 14, 14, 192)  576        ['conv2d_160[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_161 (Batch  (None, 14, 14, 192)  576        ['conv2d_165[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_156 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_156[0][0]']\n",
            "                                                                                                  \n",
            " activation_161 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_161[0][0]']\n",
            "                                                                                                  \n",
            " average_pooling2d_15 (AverageP  (None, 14, 14, 768)  0          ['mixed6[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_158 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_161 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_156[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_166 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_161[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_167 (Conv2D)            (None, 14, 14, 192)  147456      ['average_pooling2d_15[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_154 (Batch  (None, 14, 14, 192)  576        ['conv2d_158[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_157 (Batch  (None, 14, 14, 192)  576        ['conv2d_161[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_162 (Batch  (None, 14, 14, 192)  576        ['conv2d_166[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_163 (Batch  (None, 14, 14, 192)  576        ['conv2d_167[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_154 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_154[0][0]']\n",
            "                                                                                                  \n",
            " activation_157 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_157[0][0]']\n",
            "                                                                                                  \n",
            " activation_162 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_162[0][0]']\n",
            "                                                                                                  \n",
            " activation_163 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_163[0][0]']\n",
            "                                                                                                  \n",
            " mixed7 (Concatenate)           (None, 14, 14, 768)  0           ['activation_154[0][0]',         \n",
            "                                                                  'activation_157[0][0]',         \n",
            "                                                                  'activation_162[0][0]',         \n",
            "                                                                  'activation_163[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_170 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed7[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_166 (Batch  (None, 14, 14, 192)  576        ['conv2d_170[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_166 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_166[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_171 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_166[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_167 (Batch  (None, 14, 14, 192)  576        ['conv2d_171[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_167 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_167[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_168 (Conv2D)            (None, 14, 14, 192)  147456      ['mixed7[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_172 (Conv2D)            (None, 14, 14, 192)  258048      ['activation_167[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_164 (Batch  (None, 14, 14, 192)  576        ['conv2d_168[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_168 (Batch  (None, 14, 14, 192)  576        ['conv2d_172[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_164 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_164[0][0]']\n",
            "                                                                                                  \n",
            " activation_168 (Activation)    (None, 14, 14, 192)  0           ['batch_normalization_168[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_169 (Conv2D)            (None, 6, 6, 320)    552960      ['activation_164[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_173 (Conv2D)            (None, 6, 6, 192)    331776      ['activation_168[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_165 (Batch  (None, 6, 6, 320)   960         ['conv2d_169[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_169 (Batch  (None, 6, 6, 192)   576         ['conv2d_173[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_165 (Activation)    (None, 6, 6, 320)    0           ['batch_normalization_165[0][0]']\n",
            "                                                                                                  \n",
            " activation_169 (Activation)    (None, 6, 6, 192)    0           ['batch_normalization_169[0][0]']\n",
            "                                                                                                  \n",
            " max_pooling2d_11 (MaxPooling2D  (None, 6, 6, 768)   0           ['mixed7[0][0]']                 \n",
            " )                                                                                                \n",
            "                                                                                                  \n",
            " mixed8 (Concatenate)           (None, 6, 6, 1280)   0           ['activation_165[0][0]',         \n",
            "                                                                  'activation_169[0][0]',         \n",
            "                                                                  'max_pooling2d_11[0][0]']       \n",
            "                                                                                                  \n",
            " conv2d_178 (Conv2D)            (None, 6, 6, 448)    573440      ['mixed8[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_174 (Batch  (None, 6, 6, 448)   1344        ['conv2d_178[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_174 (Activation)    (None, 6, 6, 448)    0           ['batch_normalization_174[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_175 (Conv2D)            (None, 6, 6, 384)    491520      ['mixed8[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_179 (Conv2D)            (None, 6, 6, 384)    1548288     ['activation_174[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_171 (Batch  (None, 6, 6, 384)   1152        ['conv2d_175[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_175 (Batch  (None, 6, 6, 384)   1152        ['conv2d_179[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_171 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_171[0][0]']\n",
            "                                                                                                  \n",
            " activation_175 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_175[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_176 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_171[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_177 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_171[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_180 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_175[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_181 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_175[0][0]']         \n",
            "                                                                                                  \n",
            " average_pooling2d_16 (AverageP  (None, 6, 6, 1280)  0           ['mixed8[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_174 (Conv2D)            (None, 6, 6, 320)    409600      ['mixed8[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_172 (Batch  (None, 6, 6, 384)   1152        ['conv2d_176[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_173 (Batch  (None, 6, 6, 384)   1152        ['conv2d_177[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_176 (Batch  (None, 6, 6, 384)   1152        ['conv2d_180[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_177 (Batch  (None, 6, 6, 384)   1152        ['conv2d_181[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " conv2d_182 (Conv2D)            (None, 6, 6, 192)    245760      ['average_pooling2d_16[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_170 (Batch  (None, 6, 6, 320)   960         ['conv2d_174[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_172 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_172[0][0]']\n",
            "                                                                                                  \n",
            " activation_173 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_173[0][0]']\n",
            "                                                                                                  \n",
            " activation_176 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_176[0][0]']\n",
            "                                                                                                  \n",
            " activation_177 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_177[0][0]']\n",
            "                                                                                                  \n",
            " batch_normalization_178 (Batch  (None, 6, 6, 192)   576         ['conv2d_182[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_170 (Activation)    (None, 6, 6, 320)    0           ['batch_normalization_170[0][0]']\n",
            "                                                                                                  \n",
            " mixed9_0 (Concatenate)         (None, 6, 6, 768)    0           ['activation_172[0][0]',         \n",
            "                                                                  'activation_173[0][0]']         \n",
            "                                                                                                  \n",
            " concatenate_2 (Concatenate)    (None, 6, 6, 768)    0           ['activation_176[0][0]',         \n",
            "                                                                  'activation_177[0][0]']         \n",
            "                                                                                                  \n",
            " activation_178 (Activation)    (None, 6, 6, 192)    0           ['batch_normalization_178[0][0]']\n",
            "                                                                                                  \n",
            " mixed9 (Concatenate)           (None, 6, 6, 2048)   0           ['activation_170[0][0]',         \n",
            "                                                                  'mixed9_0[0][0]',               \n",
            "                                                                  'concatenate_2[0][0]',          \n",
            "                                                                  'activation_178[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_187 (Conv2D)            (None, 6, 6, 448)    917504      ['mixed9[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_183 (Batch  (None, 6, 6, 448)   1344        ['conv2d_187[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_183 (Activation)    (None, 6, 6, 448)    0           ['batch_normalization_183[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_184 (Conv2D)            (None, 6, 6, 384)    786432      ['mixed9[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_188 (Conv2D)            (None, 6, 6, 384)    1548288     ['activation_183[0][0]']         \n",
            "                                                                                                  \n",
            " batch_normalization_180 (Batch  (None, 6, 6, 384)   1152        ['conv2d_184[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_184 (Batch  (None, 6, 6, 384)   1152        ['conv2d_188[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_180 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_180[0][0]']\n",
            "                                                                                                  \n",
            " activation_184 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_184[0][0]']\n",
            "                                                                                                  \n",
            " conv2d_185 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_180[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_186 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_180[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_189 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_184[0][0]']         \n",
            "                                                                                                  \n",
            " conv2d_190 (Conv2D)            (None, 6, 6, 384)    442368      ['activation_184[0][0]']         \n",
            "                                                                                                  \n",
            " average_pooling2d_17 (AverageP  (None, 6, 6, 2048)  0           ['mixed9[0][0]']                 \n",
            " ooling2D)                                                                                        \n",
            "                                                                                                  \n",
            " conv2d_183 (Conv2D)            (None, 6, 6, 320)    655360      ['mixed9[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_181 (Batch  (None, 6, 6, 384)   1152        ['conv2d_185[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_182 (Batch  (None, 6, 6, 384)   1152        ['conv2d_186[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_185 (Batch  (None, 6, 6, 384)   1152        ['conv2d_189[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " batch_normalization_186 (Batch  (None, 6, 6, 384)   1152        ['conv2d_190[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " conv2d_191 (Conv2D)            (None, 6, 6, 192)    393216      ['average_pooling2d_17[0][0]']   \n",
            "                                                                                                  \n",
            " batch_normalization_179 (Batch  (None, 6, 6, 320)   960         ['conv2d_183[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_181 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_181[0][0]']\n",
            "                                                                                                  \n",
            " activation_182 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_182[0][0]']\n",
            "                                                                                                  \n",
            " activation_185 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_185[0][0]']\n",
            "                                                                                                  \n",
            " activation_186 (Activation)    (None, 6, 6, 384)    0           ['batch_normalization_186[0][0]']\n",
            "                                                                                                  \n",
            " batch_normalization_187 (Batch  (None, 6, 6, 192)   576         ['conv2d_191[0][0]']             \n",
            " Normalization)                                                                                   \n",
            "                                                                                                  \n",
            " activation_179 (Activation)    (None, 6, 6, 320)    0           ['batch_normalization_179[0][0]']\n",
            "                                                                                                  \n",
            " mixed9_1 (Concatenate)         (None, 6, 6, 768)    0           ['activation_181[0][0]',         \n",
            "                                                                  'activation_182[0][0]']         \n",
            "                                                                                                  \n",
            " concatenate_3 (Concatenate)    (None, 6, 6, 768)    0           ['activation_185[0][0]',         \n",
            "                                                                  'activation_186[0][0]']         \n",
            "                                                                                                  \n",
            " activation_187 (Activation)    (None, 6, 6, 192)    0           ['batch_normalization_187[0][0]']\n",
            "                                                                                                  \n",
            " mixed10 (Concatenate)          (None, 6, 6, 2048)   0           ['activation_179[0][0]',         \n",
            "                                                                  'mixed9_1[0][0]',               \n",
            "                                                                  'concatenate_3[0][0]',          \n",
            "                                                                  'activation_187[0][0]']         \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 21,802,784\n",
            "Trainable params: 0\n",
            "Non-trainable params: 21,802,784\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "pre_trained_model = create_pre_trained_model(local_weights_file)\n",
        "\n",
        "pre_trained_model.summary()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dJh-ZDHvfP6I"
      },
      "source": [
        "##Pipelining the pre-trained model with our own layers architecture"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dJOJXsIlfPPD"
      },
      "outputs": [],
      "source": [
        "# GRADED FUNCTION: output_of_last_layer\n",
        "def output_of_last_layer(pre_trained_model):\n",
        "\n",
        "  last_desired_layer = pre_trained_model.get_layer('mixed7')\n",
        "  print('last layer output shape: ', last_desired_layer.output_shape)\n",
        "  last_output = last_desired_layer.output\n",
        "  print('last layer output: ', last_output)\n",
        "\n",
        "  return last_output"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Axyq2Larfmpa",
        "outputId": "500e86bb-6172-4190-cb76-538afdcee068"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "last layer output shape:  (None, 14, 14, 768)\n",
            "last layer output:  KerasTensor(type_spec=TensorSpec(shape=(None, 14, 14, 768), dtype=tf.float32, name=None), name='mixed7/concat:0', description=\"created by layer 'mixed7'\")\n"
          ]
        }
      ],
      "source": [
        "last_output = output_of_last_layer(pre_trained_model)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OIjZaKp2fwVq"
      },
      "source": [
        "## Final Food Classification Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SWhJeuQ_fq1d"
      },
      "outputs": [],
      "source": [
        "def create_final_model(pre_trained_model, last_output):\n",
        "  \n",
        "  x = tf.keras.layers.Conv2D(128, 2, activation='relu')(last_output)\n",
        "  x = tf.keras.layers.MaxPool2D(pool_size=(2, 2))(x)\n",
        "  x = tf.keras.layers.Conv2D(256, 5, activation='relu')(x)\n",
        "  x = tf.keras.layers.MaxPool2D(pool_size=(2,2))(x)\n",
        "  x = tf.keras.layers.Dropout(0.5)(x)\n",
        "  x = tf.keras.layers.Flatten()(x)\n",
        "  x = tf.keras.layers.Dense(1024, activation='relu')(x)\n",
        "  x = tf.keras.layers.Dropout(0.2)(x)\n",
        "  x = tf.keras.layers.Dense(9, activation='softmax')(x)\n",
        "\n",
        "  # Create the complete model by using the Model class\n",
        "  model = tf.keras.Model(inputs=pre_trained_model.input, outputs=x)\n",
        "\n",
        "  # Compile the model\n",
        "  model.compile(tf.keras.optimizers.RMSprop(lr=0.0001), \n",
        "                loss='categorical_crossentropy', \n",
        "                metrics=['accuracy'])\n",
        "  \n",
        "  return model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rm830cr7gmkZ"
      },
      "source": [
        "## CallBack Function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qIUIq6QkgmLO"
      },
      "outputs": [],
      "source": [
        "class Callback(tf.keras.callbacks.Callback): \n",
        "    def on_epoch_end(self, epoch, logs={}): \n",
        "        if(logs.get('accuracy') >= 0.99):   \n",
        "          self.model.stop_training = True"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tAIezeHgnDCz"
      },
      "source": [
        "## Image Data Generator"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ro-QkDrfnjGQ"
      },
      "outputs": [],
      "source": [
        "def generators(TRAIN_DIR, VAL_DIR):\n",
        "\n",
        "  train_datagen = ImageDataGenerator(rescale=1./255,\n",
        "                                     rotation_range=40,\n",
        "                                     width_shift_range=0.2,\n",
        "                                     height_shift_range=0.2,\n",
        "                                     shear_range=0.2,\n",
        "                                     zoom_range=0.2,\n",
        "                                     horizontal_flip=True,\n",
        "                                     fill_mode='nearest')\n",
        "  \n",
        "  val_datagen = ImageDataGenerator(rescale=1./255)\n",
        "\n",
        "  ##rotation range until fill_mode values were still placeholder\n",
        "\n",
        "  train_generator = train_datagen.flow_from_directory(directory=TRAIN_DIR,\n",
        "                                                      batch_size=20,\n",
        "                                                      class_mode='categorical',\n",
        "                                                      target_size=(256, 256))\n",
        "  \n",
        "  val_generator = val_datagen.flow_from_directory(directory=VAL_DIR,\n",
        "                                                  batch_size=20,\n",
        "                                                  class_mode='categorical',\n",
        "                                                  target_size=(256, 256))\n",
        "  \n",
        "  return train_generator, val_generator"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-itTzMi8qJLX",
        "outputId": "708b49f0-435b-4959-e929-a8c1774d7d0e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zrBGRs4KqJ9U",
        "outputId": "3643e946-9c6f-4e0d-877d-49f13269a7d9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Found 6840 images belonging to 9 classes.\n",
            "Found 1710 images belonging to 9 classes.\n"
          ]
        }
      ],
      "source": [
        "TRAIN_DIR='/content/drive/MyDrive/Capstone Project/DATASET/BALANCED/RATIO : 0.8/TRAINING'\n",
        "VAL_DIR='/content/drive/MyDrive/Capstone Project/DATASET/BALANCED/RATIO : 0.8/VALIDATION'\n",
        "\n",
        "# Test the generators\n",
        "train_generator, val_generator = generators(TRAIN_DIR, VAL_DIR)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GGOMfzfBKqRh"
      },
      "source": [
        "## Train Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true,
          "base_uri": "https://localhost:8080/"
        },
        "id": "CuoLGTpYKoO3",
        "outputId": "ae5a46f2-4161-400b-bc7c-ed329c7cee26"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/rmsprop.py:130: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
            "  super(RMSprop, self).__init__(name, **kwargs)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Epoch 1/40\n",
            "342/342 [==============================] - 237s 685ms/step - loss: 1.5160 - accuracy: 0.4642 - val_loss: 0.6048 - val_accuracy: 0.8181\n",
            "Epoch 2/40\n",
            "342/342 [==============================] - 230s 671ms/step - loss: 0.6582 - accuracy: 0.7738 - val_loss: 0.3437 - val_accuracy: 0.8942\n",
            "Epoch 3/40\n",
            "342/342 [==============================] - 229s 670ms/step - loss: 0.4767 - accuracy: 0.8431 - val_loss: 0.2765 - val_accuracy: 0.9099\n",
            "Epoch 4/40\n",
            "342/342 [==============================] - 227s 665ms/step - loss: 0.3999 - accuracy: 0.8735 - val_loss: 0.2634 - val_accuracy: 0.9140\n",
            "Epoch 5/40\n",
            "342/342 [==============================] - 229s 669ms/step - loss: 0.3587 - accuracy: 0.8882 - val_loss: 0.2348 - val_accuracy: 0.9228\n",
            "Epoch 6/40\n",
            "342/342 [==============================] - 229s 669ms/step - loss: 0.3375 - accuracy: 0.8965 - val_loss: 0.2589 - val_accuracy: 0.9181\n",
            "Epoch 7/40\n",
            "342/342 [==============================] - 228s 668ms/step - loss: 0.3036 - accuracy: 0.9022 - val_loss: 0.2225 - val_accuracy: 0.9269\n",
            "Epoch 8/40\n",
            "342/342 [==============================] - 230s 673ms/step - loss: 0.2866 - accuracy: 0.9110 - val_loss: 0.2169 - val_accuracy: 0.9386\n",
            "Epoch 9/40\n",
            "342/342 [==============================] - 230s 673ms/step - loss: 0.2654 - accuracy: 0.9168 - val_loss: 0.2228 - val_accuracy: 0.9316\n",
            "Epoch 10/40\n",
            "342/342 [==============================] - 230s 674ms/step - loss: 0.2632 - accuracy: 0.9186 - val_loss: 0.2386 - val_accuracy: 0.9304\n",
            "Epoch 11/40\n",
            "342/342 [==============================] - 231s 675ms/step - loss: 0.2423 - accuracy: 0.9257 - val_loss: 0.1986 - val_accuracy: 0.9444\n",
            "Epoch 12/40\n",
            "342/342 [==============================] - 229s 669ms/step - loss: 0.2376 - accuracy: 0.9216 - val_loss: 0.2302 - val_accuracy: 0.9327\n",
            "Epoch 13/40\n",
            "342/342 [==============================] - 229s 671ms/step - loss: 0.2165 - accuracy: 0.9325 - val_loss: 0.2154 - val_accuracy: 0.9439\n",
            "Epoch 14/40\n",
            "342/342 [==============================] - 229s 669ms/step - loss: 0.2150 - accuracy: 0.9367 - val_loss: 0.2319 - val_accuracy: 0.9409\n",
            "Epoch 15/40\n",
            "342/342 [==============================] - 230s 673ms/step - loss: 0.2040 - accuracy: 0.9371 - val_loss: 0.2404 - val_accuracy: 0.9368\n",
            "Epoch 16/40\n",
            "342/342 [==============================] - 231s 675ms/step - loss: 0.1970 - accuracy: 0.9409 - val_loss: 0.2217 - val_accuracy: 0.9444\n",
            "Epoch 17/40\n",
            "342/342 [==============================] - 229s 671ms/step - loss: 0.1806 - accuracy: 0.9430 - val_loss: 0.2403 - val_accuracy: 0.9427\n",
            "Epoch 18/40\n",
            "342/342 [==============================] - 229s 669ms/step - loss: 0.1858 - accuracy: 0.9453 - val_loss: 0.2377 - val_accuracy: 0.9439\n",
            "Epoch 19/40\n",
            "342/342 [==============================] - 228s 666ms/step - loss: 0.1748 - accuracy: 0.9475 - val_loss: 0.2546 - val_accuracy: 0.9345\n",
            "Epoch 20/40\n",
            "342/342 [==============================] - 229s 670ms/step - loss: 0.1793 - accuracy: 0.9443 - val_loss: 0.2435 - val_accuracy: 0.9439\n",
            "Epoch 21/40\n",
            "342/342 [==============================] - 228s 668ms/step - loss: 0.1728 - accuracy: 0.9453 - val_loss: 0.2472 - val_accuracy: 0.9363\n",
            "Epoch 22/40\n",
            "342/342 [==============================] - 228s 667ms/step - loss: 0.1749 - accuracy: 0.9466 - val_loss: 0.2386 - val_accuracy: 0.9450\n",
            "Epoch 23/40\n",
            "288/342 [========================>.....] - ETA: 31s - loss: 0.1589 - accuracy: 0.9503"
          ]
        }
      ],
      "source": [
        "model = create_final_model(pre_trained_model, last_output)\n",
        "history = model.fit(train_generator, epochs=40, verbose=1, validation_data=val_generator, callbacks=[Callback()])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O0CFR44bL0tD"
      },
      "source": [
        "## Visualization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 562
        },
        "id": "53nYBZmaL-Bz",
        "outputId": "8a6f4dba-d87b-4ec0-d3e3-6935c222e76c"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "data": {
            "image/png": 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Zv349L7/8cr3bOPHEE3nuuef44osv2LZtGy+88MLex7Zt20avXr3Ys2cPTz755N77O3XqxLZaziQfOHAgK1euZNmyZQD89re/ZeLEic36jJkwzW5u7KEXF4eTjBToIhnroosu4qyzztrbehk6dCjDhw/nmGOOoW/fvowfP77e148YMYILLriAoUOH0rNnz2pT4N59992MGTOGHj16MGbMmL0hfuGFF3LFFVfw4IMP7j0YCtCuXTsef/xxzjvvPCoqKhg1ahRXXdW4RdgycZrd7J0+t6Z774XbboONG6F79/RtVyTLafrc7JU/0+fWFIuFPzUeXUTyVO4EekkJtG+vtouI5K3cCfS2beFLX1Kgi9QiqtaqNF1T/s5yJ9AhtF0WLYING6KuRCRjtGvXjs2bNyvUs4i7s3nzZtq1a9eo1+XGKJeE0tLw51tvwXnnRVqKSKbo06cP5eXlbNy4MepSpBHatWtXbRRNKnIr0EeOhI4dQ9tFgS4CQFFREf3794+6DGkFDbZczOwxM9tgZh/U8fjFZvaemb1vZrPMbGj6y0xRURFMmKCJukQkL6XSQ38COLWex1cAE919CHA38Ega6mq6WAyWLIF16yItQ0SktTUY6O4+A6hz1it3n+Xun8VvzgYa1/RJt0QfXXvpIpJn0j3K5VtAnRMymNmVZlZmZmUtdoBm+HDo3FnDF0Uk76Qt0M0sRgj0m+t6jrs/4u4l7l7So0ePdL11dYWFcOKJ2kMXkbyTlkA3s+OBXwGT3H1zOrbZLKWl8NFHsGZN1JWIiLSaZge6mR0G/AH4F3f/qPklpUFiXhe1XUQkj6QybPEp4G1goJmVm9m3zOwqM0vMNXk70A14yMwWmlkap1BsoqFDoUsXtV1EJK80eGKRu9e7NLe7Xw5cnraK0qGgIPTRtYcuInkkt+ZySRaLwccfw6pVUVciItIqcjvQQW0XEckbuRvoQ4bAQQep7SIieSN3A71NG5g4UYEuInkjdwMdQttl5cpwERHJcbkf6KA+uojkhdwO9EGDoHt3tV1EJC/kdqC3aROmAXjzTdDyWyKS43I70CG0XVatghUroq5ERKRF5X6gJ+ZHV9tFRHJc7gf6scfCwQcr0EUk5+V+oJuFvfTp09VHF5GclvuBDiHQV6+GZcuirkREpMXkR6BrfnQRyQP5EehHHw29einQRSSn5Uegq48uInkgPwIdQttl3TpYujTqSkREWkR+BTqo7SIiOSt/Av2II6BPH03UJSI5K38CXX10Eclx+RPoENouGzbA4sVRVyIiknb5F+igtouI5KT8CvR+/eCww3RgVERyUn4FulnYS58+Haqqoq5GRCStGgx0M3vMzDaY2Qd1PG5m9qCZLTOz98xsRPrLTKNYDDZvhg9q/TgiIlkrlT30J4BT63n8q8BR8cuVwMPNL6sFJeZHVx9dRHJMg4Hu7jOAT+t5yiTgNx7MBrqYWa90FZh2hx8O/furjy4iOScdPfTewKqk2+Xx+/ZjZleaWZmZlW3cuDENb91EsRi89Zb66CKSU1r1oKi7P+LuJe5e0qNHj9Z86+piMfjsM3jvvehqEBFJs3QE+mqgb9LtPvH7MpfWGRWRHJSOQH8e+GZ8tMtYYIu7r03DdltOnz5w5JEKdBHJKYUNPcHMngJKge5mVg7cARQBuPsvgZeA04BlwA7g0pYqNq1iMZg2DSoroaAg6mpERJqtwUB394saeNyB76atotZSWgqPPgoLF8LIkVFXIyLSbPl1pmgyzY8uIjkmfwO9Vy8YOFCBLiI5I38DHULbZeZMqKiIuhIRkWbL70CPxWDbNliwIOpKRESaLb8DXePRRSSH5HegH3wwHHusJuoSkZyQ34EOoe0ycybs2RN1JSIizaJAj8Xg88+hrCzqSkREmkWBPnFi+FNtFxHJcgr0Hj1g8GAdGBWRrKdAh9B2+etfYffuqCsREWkyBTqEQN+xA+bOjboSEZEmU6ADnHgimKmPLiJZTYEO0K0bHH+8+ugiktUU6AmxGMyaBbt2RV2JiEiTKNATSkth506YMyfqSkREmkSBnpDoo6vtIiJZSoGe0LUrDB+uQBeRrKVATxaLwezZofUiIpJlFOjJSkvDQdG33466EhGRRlOgJ5swAdq0UdtFRLKSAj3ZgQfCyJEKdBHJSgr0mkpLw9DFHTuirkREpFEU6DXFYmGxi1mzoq5ERKRRUgp0MzvVzJaa2TIzu6WWxw8zszfN7B0ze8/MTkt/qa3kS1+CggK1XUQk6zQY6GZWAPwC+CowCLjIzAbVeNptwDR3Hw5cCDyU7kJbTadOUFKiibpEJOuksoc+Gljm7svdfTcwBZhU4zkOdI5fPxBYk74SIxCLhal0t2+PuhIRkZSlEui9gVVJt8vj9yW7E/iGmZUDLwHX1rYhM7vSzMrMrGzjxo1NKLeVxGJQUREWvRARyRLpOih6EfCEu/cBTgN+a2b7bdvdH3H3Encv6dGjR5reugWMGweFhWq7iEhWSSXQVwN9k273id+X7FvANAB3fxtoB3RPR4GR6NgRRo/WgVERySqpBPo84Cgz629mbQkHPZ+v8ZxPgJMBzOxYQqBncE8lBbEYlJXBtm1RVyIikpIGA93dK4BrgFeBJYTRLIvM7C4zOzP+tBuAK8zsXeApYLK7e0sV3SpiMaishJkzo65ERCQlhak8yd1fIhzsTL7v9qTri4Hx6S0tYiecAEVFoY9+WvYOqxeR/KEzRevSvj2MHas+uohkDQV6fWIxWLAAtmyJuhIRkQYp0OtTWgpVVeqji0hWUKDX54QToLhYbRcRyQoK9Pq0axdCXYEuIllAgd6Q0lJYuBA++yzqSkRE6qVAb0gsBu4wY0bUlYiI1EuB3pAxY0LrRW0XEclwCvSGFBeHyboU6CKS4RToqYjF4L33YPPmqCsREamTAj0VsVj48623oq1DRKQeCvRUjBoVpgJQ20VEMpgCPRVt28L48VrwQkQymgI9VbEYfPABZPLSeSKS1xToqUr00bWXLiIZSoGeqpEjoUMHBbqIZCwFeqqKimDCBB0YFZGMpUBvjFgMliyBdeuirkREZD8K9MYoLQ1/qu0iIhlIgd4YI0ZAp04KdBHJSAr0xigshBNPVB9dRDKSAr2xYjH46CNYsybqSkREqlGgN5b66CKSoRTojTVsGHTporaLiGSclALdzE41s6VmtszMbqnjOeeb2WIzW2Rmv09vmRmkoEB9dBHJSA0GupkVAL8AvgoMAi4ys0E1nnMU8K/AeHc/DvheC9SaOUpL4eOPYdWqqCsREdkrlT300cAyd1/u7ruBKcCkGs+5AviFu38G4O4b0ltmhtG8LiKSgVIJ9N5A8q5oefy+ZEcDR5vZX81stpmdWtuGzOxKMyszs7KN2Txr4fHHQ9euaruISEZJ10HRQuAooBS4CHjUzLrUfJK7P+LuJe5e0qNHjzS9dQTatIGJE+Evf4GtW6OuRkQESC3QVwN9k273id+XrBx43t33uPsK4CNCwOeuyy+HtWth7NgwLl1EJGKpBPo84Cgz629mbYELgedrPOc5wt45Ztad0IJZnsY691q/Hr77Xdi5syW23ginnw6vvRYWvBg9Gl56KeKCRCTfNRjo7l4BXAO8CiwBprn7IjO7y8zOjD/tVWCzmS0G3gRudPfNLVHw//wPPPwwnH027NrVEu/QCKWlUFYGAwbAGWfAffeBe8RFiUi+Mo8ogEpKSrysrKxJr330UbjySpg0CZ5+OkxVHqkdO0IL5qmn4Lzz4PHHw2IYIiJpZmbz3b2ktsey8kzRK66A//t/4b//G77+daioiLig9u3hySfhpz+FZ5+FceNgxYqIixKRfJOVgQ6hj/6zn8Ezz8A3vwmVlREXZAY/+EHopX/yCZSUwOuvR1yUiOSTrA10gOuvhx//OHQ6Lr8cqqqirgj4p3+CefOgV69w/YEH1FcXkVZRGHUBzXXLLbB7N9xxR+il//KXYZh4pI48Et5+Gy65JPzUWbAA/uu/4IADIi5MRHJZ1NGXFj/6Edx6azhYet11GbJD3KlT6AfdfTf89rdhQi/N/SIiLSgnAt0M7rkHbrgBfvGL0MrOiFBv0wZuuw2efx6WLg199Zkzo65KRHJUTgQ6hFD/6U/h2mvDwdIf/jBDQh3gn/8Z5syBAw+Ek04KA+kzpjgRyRVZ30NPZgb/8R+hp/7jH0NxceitZ4Rjj4W5c+Hii+E734F33oH//M9QpIhIGuTMHnqCGTz0EFx6Kdx5Zwj2jNGlS2i/JBr+sViYD0ZEJA1yLtAhtK4ffTTsDN96a2jBZIyCArj3Xpg2Dd59N/TV58yJuioRyQE5GegQcvOJJ8KZ+DfcEM4szSjnnReGNhYXhxEwjz8edUUikuVyNtABCgvDGflf+1o4WPrII1FXVMPxx4eTkCZMgMsuC2Mu9+yJuioRyVI5HegQTjaaMgVOOw2+/e2w155RunWDV16B738/HCT98pfDlLwiIo2U84EOoavx7LMhKy+7DH7/+6grqqGwEP7938MJSHPmhL76O+9EXZWIZJm8CHSAdu3guefCynHf/GaYdjfjfOMbYcL3qioYPz5MUiMikqK8CXQIs9y+8EJYNe7rXw/T72ackSPDohklJaHIm27KgKkkRSQb5FWgA3TsGGa4HTkyDDTJyJXjDj44LG/3ne+E019POw0+/TTqqkQkw+VdoAN07hyOQw4ZEpay+8tfoq6oFm3bholpHn0U3nwzrFv6wQdRVyUiGSwvAx3CSZt/+QsMHAhnngnTp0ddUR0uvzwU9/nnoVf0hz9EXZGIZKi8DXSAgw4KnY3EGs9//WvUFdVh3LjQVz/uODjnHLj99gxZzUNEMkleBzpAjx5hpbjeveGrX83gs/B794a33gqT1Nx9dzhbauvWqKsSkQyS94EOcMgh8MYb0LNnWDVuwYKoK6pDu3bw61+HE5BeegnGjAnzrIuIoEDfq3fvEOpduoQTkN59N+qK6mAG11wTekWbNoWDpU88ob11EVGgJzvssBDq7dvDKafA4sVRV1SP0tLQVz/yyNCG6dYtFP3AA/Dxx1FXJyIRSCnQzexUM1tqZsvM7JZ6nneOmbmZlaSvxNY1YEAI9cLCsLhQRnc0Dj88LJoxc2aYUnLt2rAo9ZFHhgU1brwRZsyAioqoKxWRVmDewFJoZlYAfAR8GSgH5gEXufviGs/rBLwItAWucfey+rZbUlLiZWX1PiVSS5aEaQKKikImHnFE1BWlaPlyePHFcErs9Olh9sYuXcIR33/+Zzj1VOjaNeoqRaSJzGy+u9e605zKHvpoYJm7L3f33cAUYFItz7sb+Amws8mVZpBjjw2jX3btCnvqf/971BWlaMCAMFfwn/8MmzeHWcm+9rXQc//618OwnokT4f774cMPtbapSA5JJdB7A6uSbpfH79vLzEYAfd39xfo2ZGZXmlmZmZVtzIIpYocMCScfbd0aVosrL4+6okbq1CmcCvv447BuHcyeDbfcAlu2hHbMscfCUUeFNs3rr4fFWEUkazX7oKiZtQF+BtzQ0HPd/RF3L3H3kh49ejT3rVvF8OH7dnZPOimLlwBt0yYMc7znHli4MPzK8dBD4VTZhx8OB1R79IDzz4ff/EZzsotkoVQCfTXQN+l2n/h9CZ2AwcB0M1sJjAWez+YDozWNGgUvvwxr1sDJJ8OGDVFXlAaHHQZXXx367Zs3h6knL7ggTN97ySVhgrDx48Mq2++/r9aMSBZI5aBoIeGg6MmEIJ8HfN3dF9Xx/OnAD7L9oGhtZswIxxSPPDLMl9WtW9QVtYCqqrC4xp/+FC6Jv6PDDw/zI5xxRhgy2a5dpGWK5KtmHRR19wrgGuBVYAkwzd0XmdldZnZmekvNbCeeCM8/Dx99FE4++uyzqCtqAW3ahLmF77gjrHe6enWY8XHoUHjssTBapnt3OOuscNbqunVRVywicQ3uobeUbNxDT3jlFZg0KeypX3NNmC+rZ8+oq2oFX3wRhkK+8ELYe18VP1Y+alTYcz/ppHDQoUOHSMsUyWX17aEr0Jvo5ZfDuTxLloSd2pNPDi3os84KszjmPPfQW0+E+5w54b42bcLomVGjwqpLJSVh714tGpG0UKC3EPew5k8YfWQAAAvRSURBVMSUKTB1ajjjvqgIvvKVEO6TJoXFNPLCxo0h1MvKwmXevH1HjwsLwxjQRMCXlMDgwWERDxFpFAV6K3APszROmQLTpsEnn0BxcVg97oILQkcirzoR7mHgfiLcE0GfOPBQXBz23BMBP2oUHHNMCH8RqZMCvZVVVYWd1SlT4Omnw9j19u3DmfcXXBCOK+ZlB8IdVqyoHvDz58O2beHx9u1DDz4R8CUl4cSnNppDTiRBgR6hysowd9bUqfDMM2HG206dwtn4F1wQRsvkdeehqioMG0pu1bzzTjgAC6FnNXJk9XZN//5hGmGRPKRAzxAVFWEmx6lTw9Kg//hHmCfr7LNDuMdi6jgA4YtasqR6u+bdd/dNTXDQQdUDftSoMKG9Ql7ygAI9A+3eHaYUmDo1nKS5bVs48/7cc0O4T5igTkM1u3eHI9DJ7Zr33w+/AkE4szUR8EcdBX37hkvv3nn+K5DkGgV6hvviizAMcurUMArwiy/g0EPhvPPgwgvDFCza+azFF1+EPffkds2SJdWnKTALawz27RumO0gEfeL6YYeFkwj001OyhAI9i2zfHoZ1T50alg3dvTucdX/++WHPfcQIhXu9duwIQ4xWrdr3Z83rO3ZUf01REfTpU3vgJ64feKC+eMkICvQstWVLaMdMnRraMxUV4ezUCy4Ie+6DB0ddYRZyh08/rT3oE9dXr95/laeOHesP/D594IADovlMklcU6Dlg82b44x9DuL/xRhgcMmhQCPfS0jAYpHPnMIKmU6cwzFs7lE1UWRnmqKkv9Nev3/913btXD/o+ffZdevcOF4W+NJMCPcesXx8WIpo6NQyJrO2vsKhoX7h36lQ97Ou6Xtdj7dvrh8N+du0KJ07VF/pbtuz/um7dQrAnB33N65076wuXOinQc9jq1bB4cRglk3zZurXu28nXU/nrb9MmdBwa+kFw5JHhAO6xx+oYIxAOiKxeHYI/8WfN67VNrt+xY8Oh3727vuQ8VV+ga9Rzlkv8Jt8U7uH4YKrhX/P2+vX7bm/duq/t3LkzjB4NY8eGgB8zJgzJzDsdO4YVoQYOrPs5u3aFU4nrCv033ggrqySGZyYUFe0L97rCv1cvndiQZ7SHLmnhDn/7W1i2NHF57719OXTEEfsCfuzYMI2LhoenqLIy7MnXt6dfXg47a6zPbhbG59e8HHLI/vd17w4FBdF8PmkUtVwkEjt2hKlaZs8Oc9u8/XbY2YRw0HbkyH0BP3ZsOI6o1nETuYeJz2oL/fXrq1927dr/9W3ahFCv7QdAzUuPHuE3BImEAl0yRnn5voCfPTucD5TYsezVq3rAl5Tk2QyVrcE99MdqhnzNy7p14c/EnDo1deuWWvgffLB+FUszBbpkrD17QmsmOeT/9rfwWJs2YRr1RMCPHQtHH61jga3GPRzYbSj8E5ft22vfTteuIdh79Qrtnrr+POgg/YqWAgW6ZJXNm2Hu3H29+Dlz9o0APPDA6nvxo0fn6GLd2ejzz0OvP7F3X3OPP3FZu7b2Pf+iovoDv1evcMnyvf7KytD1at++aa9XoEtWq6qCpUv37cHPnh3m5aqqCo8fddS+gB8zBgYMgC5dtLOXsdzD0Ki1a/cFfF1/btpU+za6dWs4/A85JPIpG9zDYYy5c8O/37lzQ5vxxhvh9tubtk0FuuSc7dv3HXBNXNat2/d427b7BnMcckj1S8371KfPYHv2hL3+VMK/toO97drtH/R1/aMoLm52uVu2hMBODvC1a8NjRUUwbFj4rfKss8I6xE2hQJec5x5Ozpw7d9+Z+cm/5a9fH3IhsVefrEOHhkP/kEPCpIxp+D+fc9xDt2Xz5jBNTvIlcZ9ZGLp65JHh0rdvmkdJuoc0rS/w164N/xA2b659G127NvyP4JBD9g7x3L07HP+ZO3dfgH/44b7NHX10CO/EZdiw9Pz7UaCLEHqXmzZVD/nk0E++79NPa99GKv/nEyP7sm1Yd6ITUlco13ffnj11b7d9+/CDNHmYfFFRaI0lAj75cvjhLTwqcvfufb3++v4xrFu390CvA8s4krmMZi5jmFM0nncqhrDbQy+/Z/ttjOm/gdGDPmf0KGfUiQfQdWDPFmn5KNBFGmnXrvB/vr7Qr/F/fj9t2+67FBdXv53qY819rVkYnl5bCNcW1DUnmUzWoUNoXR90UPVLffd17Rq6HlVVYQd52bLaL8nfYUEB9OtXe9j37986vyVt2BDf8/6f3cydVcHchUV8ti38lGlftJuSbisZ3eEDRjOP0Tumc9jG+VhFLT/Viotr/+kfi4VZ9Zqg2YFuZqcC/wEUAL9y9/tqPP594HKgAtgIXObuf69vmwp0yRWff75/yG/YEH4o7N6971LzdmMfq3n2f1N16tS4UE4Ec0sFqXv4vmoL+r/9rfocZ2ZhQsvawn7AgKaNHEmcAJdoncydCytXhscSQ2eTWyeDBtUyo0LixK6G9vjXrYONG+GHP4S7727S99WsQDezAuAj4MtAOTAPuMjdFyc9JwbMcfcdZnY1UOruF9S3XQW6SONUVobWRmN+ELhXD+muXbNrxF9i+vragn7Zsv3b4b171x72RxwRfpBVVobJ7BIHLOfODSsbJn5Y9utXPbxHjGiBg+YVFeEvsolTKTd3cq7RwDJ3Xx7f2BRgErA30N39zaTnzwa+0aRKRaROBQXh0q5d1JW0HrPwm0K3bmFIak2ffQYff7x/4P/pT/tPWd+zZ/ht6vPPw+2uXUNon3nmvgDv2bPlPxOFhS02aVoqW+0NrEq6XQ7U8tXu9S3g5doeMLMrgSsBDjvssBRLFBGpXdeu+9YGr2nbtv3DvkOHENxjxoS99lw7VyGtPybM7BtACTCxtsfd/RHgEQgtl3S+t4hIsk6dwlDBYcOirqT1pBLoq4G+Sbf7xO+rxsxOAX4ITHT3Wkb4i4hIS0plmqN5wFFm1t/M2gIXAs8nP8HMhgP/BZzp7rUswSIiIi2twUB39wrgGuBVYAkwzd0XmdldZnZm/Gk/BToCT5vZQjN7vo7NiYhIC0mph+7uLwEv1bjv9qTrp6S5LhERaSTNLC0ikiMU6CIiOUKBLiKSIxToIiI5IrLZFs1sI1DvBF716A7UsZRJXtL3UZ2+j330XVSXC9/H4e7eo7YHIgv05jCzsromp8lH+j6q0/exj76L6nL9+1DLRUQkRyjQRURyRLYG+iNRF5Bh9H1Up+9jH30X1eX095GVPXQREdlftu6hi4hIDQp0EZEckXWBbmanmtlSM1tmZrdEXU+UzKyvmb1pZovNbJGZ/a+oa4qamRWY2Ttm9qeoa4mamXUxs2fM7EMzW2JmJ0RdU1TM7Pr4/5EPzOwpM8vJhfyyKtDjC1b/AvgqMAi4yMwGRVtVpCqAG9x9EDAW+G6efx8A/4swzbPAfwCvuPsxwFDy9Hsxs97AdUCJuw8GCgjrOuScrAp0khasdvfdQGLB6rzk7mvdfUH8+jbCf9je0VYVHTPrA5wO/CrqWqJmZgcCJwK/BnD33e7+j2irilQhcICZFQLtgTUR19Misi3Qa1uwOm8DLJmZ9QOGA3OirSRSDwA3AVVRF5IB+gMbgcfjLahfmVmHqIuKgruvBu4HPgHWAlvc/c/RVtUysi3QpRZm1hF4Fvieu2+Nup4omNkZwAZ3nx91LRmiEBgBPOzuw4HPgbw85mRmXQm/yfcHDgU6xBe0zznZFugpLVidT8ysiBDmT7r7H6KuJ0LjgTPNbCWhFXeSmf0u2pIiVQ6Uu3viN7ZnCAGfj04BVrj7RnffA/wBGBdxTS0i2wK9wQWr84mZGaFHusTdfxZ1PVFy93919z7u3o/w7+INd8/JvbBUuPs6YJWZDYzfdTKwOMKSovQJMNbM2sf/z5xMjh4gTmlN0Uzh7hVmlliwugB4zN0XRVxWlMYD/wK8b2YL4/fdGl8DVuRa4Mn4zs9y4NKI64mEu88xs2eABYSRYe+Qo1MA6NR/EZEckW0tFxERqYMCXUQkRyjQRURyhAJdRCRHKNBFRHKEAl1EJEco0EVEcsT/B6mBhu4/Ed4xAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "acc = history.history['accuracy']\n",
        "val_acc = history.history['val_accuracy']\n",
        "loss = history.history['loss']\n",
        "val_loss = history.history['val_loss']\n",
        "\n",
        "\n",
        "epochs = range(len(acc))\n",
        "\n",
        "\n",
        "plt.plot(epochs, acc, 'r', label='Training Accuracy')\n",
        "plt.plot(epochs, val_acc, 'b', label='Validation Accuracy')\n",
        "plt.title('Accuracy Comparison')\n",
        "plt.legend()\n",
        "plt.show()\n",
        "plt.figure()\n",
        "print('')\n",
        "\n",
        "\n",
        "plt.plot(epochs, loss, 'r', label='Training Loss')\n",
        "plt.plot(epochs, val_loss, 'b', label='Validation Loss')\n",
        "plt.title('Loss Comparison')\n",
        "plt.legend()\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4PJlv1nKt5Dx"
      },
      "source": [
        "## Testing Code"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3EwOpAAkt9Of"
      },
      "outputs": [],
      "source": [
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  path = fn\n",
        "  img = image.load_img(path, target_size = (256, 256))\n",
        "  imgplot = plt.imshow(img)\n",
        "  x = image.img_to_array(img)\n",
        "  x = np.expand_dims(x, axis = 0)\n",
        "\n",
        "  images = np.vstack([x])\n",
        "  classes = model.predict(images, batch_size = 10)\n",
        "\n",
        "  print(fn)\n",
        "  if classes[0][0] == 1:\n",
        "    print(\"AYAM_GORENG\")\n",
        "  elif classes[0][1] == 1:\n",
        "    print(\"BAKSO\")\n",
        "  elif classes[0][2] == 1:\n",
        "    print(\"BURGER\")\n",
        "  elif classes[0][3] == 1:\n",
        "    print(\"MIE\")\n",
        "  elif classes[0][4] == 1:\n",
        "    print(\"NASI_GORENG\")\n",
        "  elif classes[0][5] == 1:\n",
        "    print(\"PIZZA\")\n",
        "  elif classes[0][6] == 1:\n",
        "    print(\"RENDANG\")\n",
        "  elif classes[0][7] == 1:\n",
        "    print(\"SALAD\")\n",
        "  elif classes[0][8] == 1:\n",
        "    print(\"SATE\")\n",
        "  else:\n",
        "    print(\"Image Not Valid\")\n",
        "\n",
        "  print(classes[0])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qXqdUwvCSqkg"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c-_F83tfudLr"
      },
      "source": [
        "## Load the Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Rl1oxFpuYTG",
        "outputId": "3049a9e8-4dfd-4b12-9b23-33c1775d876e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model: \"model\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                   Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            " input_1 (InputLayer)           [(None, 128, 128, 3  0           []                               \n",
            "                                )]                                                                \n",
            "                                                                                                  \n",
            " conv2d (Conv2D)                (None, 63, 63, 32)   864         ['input_1[0][0]']                \n",
            "                                                                                                  \n",
            " batch_normalization (BatchNorm  (None, 63, 63, 32)  96          ['conv2d[0][0]']                 \n",
            " alization)                                                                                       \n",
            "                                                                                                  \n",
            " activation (Activation)        (None, 63, 63, 32)   0           ['batch_normalization[0][0]']    \n",
            "                                                                                                  \n",
            " conv2d_1 (Conv2D)              (None, 61, 61, 32)   9216        ['activation[0][0]']             \n",
            "                                                                                                  \n",
            " batch_normalization_1 (BatchNo  (None, 61, 61, 32)  96          ['conv2d_1[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_1 (Activation)      (None, 61, 61, 32)   0           ['batch_normalization_1[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_2 (Conv2D)              (None, 61, 61, 64)   18432       ['activation_1[0][0]']           \n",
            "                                                                                                  \n",
            " batch_normalization_2 (BatchNo  (None, 61, 61, 64)  192         ['conv2d_2[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_2 (Activation)      (None, 61, 61, 64)   0           ['batch_normalization_2[0][0]']  \n",
            "                                                                                                  \n",
            " max_pooling2d (MaxPooling2D)   (None, 30, 30, 64)   0           ['activation_2[0][0]']           \n",
            "                                                                                                  \n",
            " conv2d_3 (Conv2D)              (None, 30, 30, 80)   5120        ['max_pooling2d[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_3 (BatchNo  (None, 30, 30, 80)  240         ['conv2d_3[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_3 (Activation)      (None, 30, 30, 80)   0           ['batch_normalization_3[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_4 (Conv2D)              (None, 28, 28, 192)  138240      ['activation_3[0][0]']           \n",
            "                                                                                                  \n",
            " batch_normalization_4 (BatchNo  (None, 28, 28, 192)  576        ['conv2d_4[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_4 (Activation)      (None, 28, 28, 192)  0           ['batch_normalization_4[0][0]']  \n",
            "                                                                                                  \n",
            " max_pooling2d_1 (MaxPooling2D)  (None, 13, 13, 192)  0          ['activation_4[0][0]']           \n",
            "                                                                                                  \n",
            " conv2d_8 (Conv2D)              (None, 13, 13, 64)   12288       ['max_pooling2d_1[0][0]']        \n",
            "                                                                                                  \n",
            " batch_normalization_8 (BatchNo  (None, 13, 13, 64)  192         ['conv2d_8[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_8 (Activation)      (None, 13, 13, 64)   0           ['batch_normalization_8[0][0]']  \n",
            "                                                                                                  \n",
            " conv2d_6 (Conv2D)              (None, 13, 13, 48)   9216        ['max_pooling2d_1[0][0]']        \n",
            "                                                                                                  \n",
            " conv2d_9 (Conv2D)              (None, 13, 13, 96)   55296       ['activation_8[0][0]']           \n",
            "                                                                                                  \n",
            " batch_normalization_6 (BatchNo  (None, 13, 13, 48)  144         ['conv2d_6[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " batch_normalization_9 (BatchNo  (None, 13, 13, 96)  288         ['conv2d_9[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " activation_6 (Activation)      (None, 13, 13, 48)   0           ['batch_normalization_6[0][0]']  \n",
            "                                                                                                  \n",
            " activation_9 (Activation)      (None, 13, 13, 96)   0           ['batch_normalization_9[0][0]']  \n",
            "                                                                                                  \n",
            " average_pooling2d (AveragePool  (None, 13, 13, 192)  0          ['max_pooling2d_1[0][0]']        \n",
            " ing2D)                                                                                           \n",
            "                                                                                                  \n",
            " conv2d_5 (Conv2D)              (None, 13, 13, 64)   12288       ['max_pooling2d_1[0][0]']        \n",
            "                                                                                                  \n",
            " conv2d_7 (Conv2D)              (None, 13, 13, 64)   76800       ['activation_6[0][0]']           \n",
            "                                                                                                  \n",
            " conv2d_10 (Conv2D)             (None, 13, 13, 96)   82944       ['activation_9[0][0]']           \n",
            "                                                                                                  \n",
            " conv2d_11 (Conv2D)             (None, 13, 13, 32)   6144        ['average_pooling2d[0][0]']      \n",
            "                                                                                                  \n",
            " batch_normalization_5 (BatchNo  (None, 13, 13, 64)  192         ['conv2d_5[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " batch_normalization_7 (BatchNo  (None, 13, 13, 64)  192         ['conv2d_7[0][0]']               \n",
            " rmalization)                                                                                     \n",
            "                                                                                                  \n",
            " batch_normalization_10 (BatchN  (None, 13, 13, 96)  288         ['conv2d_10[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_11 (BatchN  (None, 13, 13, 32)  96          ['conv2d_11[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_5 (Activation)      (None, 13, 13, 64)   0           ['batch_normalization_5[0][0]']  \n",
            "                                                                                                  \n",
            " activation_7 (Activation)      (None, 13, 13, 64)   0           ['batch_normalization_7[0][0]']  \n",
            "                                                                                                  \n",
            " activation_10 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_10[0][0]'] \n",
            "                                                                                                  \n",
            " activation_11 (Activation)     (None, 13, 13, 32)   0           ['batch_normalization_11[0][0]'] \n",
            "                                                                                                  \n",
            " mixed0 (Concatenate)           (None, 13, 13, 256)  0           ['activation_5[0][0]',           \n",
            "                                                                  'activation_7[0][0]',           \n",
            "                                                                  'activation_10[0][0]',          \n",
            "                                                                  'activation_11[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_15 (Conv2D)             (None, 13, 13, 64)   16384       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_15 (BatchN  (None, 13, 13, 64)  192         ['conv2d_15[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_15 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_15[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_13 (Conv2D)             (None, 13, 13, 48)   12288       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_16 (Conv2D)             (None, 13, 13, 96)   55296       ['activation_15[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_13 (BatchN  (None, 13, 13, 48)  144         ['conv2d_13[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_16 (BatchN  (None, 13, 13, 96)  288         ['conv2d_16[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_13 (Activation)     (None, 13, 13, 48)   0           ['batch_normalization_13[0][0]'] \n",
            "                                                                                                  \n",
            " activation_16 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_16[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_1 (AveragePo  (None, 13, 13, 256)  0          ['mixed0[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_12 (Conv2D)             (None, 13, 13, 64)   16384       ['mixed0[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_14 (Conv2D)             (None, 13, 13, 64)   76800       ['activation_13[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_17 (Conv2D)             (None, 13, 13, 96)   82944       ['activation_16[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_18 (Conv2D)             (None, 13, 13, 64)   16384       ['average_pooling2d_1[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_12 (BatchN  (None, 13, 13, 64)  192         ['conv2d_12[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_14 (BatchN  (None, 13, 13, 64)  192         ['conv2d_14[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_17 (BatchN  (None, 13, 13, 96)  288         ['conv2d_17[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_18 (BatchN  (None, 13, 13, 64)  192         ['conv2d_18[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_12 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_12[0][0]'] \n",
            "                                                                                                  \n",
            " activation_14 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_14[0][0]'] \n",
            "                                                                                                  \n",
            " activation_17 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_17[0][0]'] \n",
            "                                                                                                  \n",
            " activation_18 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_18[0][0]'] \n",
            "                                                                                                  \n",
            " mixed1 (Concatenate)           (None, 13, 13, 288)  0           ['activation_12[0][0]',          \n",
            "                                                                  'activation_14[0][0]',          \n",
            "                                                                  'activation_17[0][0]',          \n",
            "                                                                  'activation_18[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_22 (Conv2D)             (None, 13, 13, 64)   18432       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_22 (BatchN  (None, 13, 13, 64)  192         ['conv2d_22[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_22 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_22[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_20 (Conv2D)             (None, 13, 13, 48)   13824       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_23 (Conv2D)             (None, 13, 13, 96)   55296       ['activation_22[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_20 (BatchN  (None, 13, 13, 48)  144         ['conv2d_20[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_23 (BatchN  (None, 13, 13, 96)  288         ['conv2d_23[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_20 (Activation)     (None, 13, 13, 48)   0           ['batch_normalization_20[0][0]'] \n",
            "                                                                                                  \n",
            " activation_23 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_23[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_2 (AveragePo  (None, 13, 13, 288)  0          ['mixed1[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_19 (Conv2D)             (None, 13, 13, 64)   18432       ['mixed1[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_21 (Conv2D)             (None, 13, 13, 64)   76800       ['activation_20[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_24 (Conv2D)             (None, 13, 13, 96)   82944       ['activation_23[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_25 (Conv2D)             (None, 13, 13, 64)   18432       ['average_pooling2d_2[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_19 (BatchN  (None, 13, 13, 64)  192         ['conv2d_19[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_21 (BatchN  (None, 13, 13, 64)  192         ['conv2d_21[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_24 (BatchN  (None, 13, 13, 96)  288         ['conv2d_24[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_25 (BatchN  (None, 13, 13, 64)  192         ['conv2d_25[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_19 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_19[0][0]'] \n",
            "                                                                                                  \n",
            " activation_21 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_21[0][0]'] \n",
            "                                                                                                  \n",
            " activation_24 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_24[0][0]'] \n",
            "                                                                                                  \n",
            " activation_25 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_25[0][0]'] \n",
            "                                                                                                  \n",
            " mixed2 (Concatenate)           (None, 13, 13, 288)  0           ['activation_19[0][0]',          \n",
            "                                                                  'activation_21[0][0]',          \n",
            "                                                                  'activation_24[0][0]',          \n",
            "                                                                  'activation_25[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_27 (Conv2D)             (None, 13, 13, 64)   18432       ['mixed2[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_27 (BatchN  (None, 13, 13, 64)  192         ['conv2d_27[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_27 (Activation)     (None, 13, 13, 64)   0           ['batch_normalization_27[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_28 (Conv2D)             (None, 13, 13, 96)   55296       ['activation_27[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_28 (BatchN  (None, 13, 13, 96)  288         ['conv2d_28[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_28 (Activation)     (None, 13, 13, 96)   0           ['batch_normalization_28[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_26 (Conv2D)             (None, 6, 6, 384)    995328      ['mixed2[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_29 (Conv2D)             (None, 6, 6, 96)     82944       ['activation_28[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_26 (BatchN  (None, 6, 6, 384)   1152        ['conv2d_26[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_29 (BatchN  (None, 6, 6, 96)    288         ['conv2d_29[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_26 (Activation)     (None, 6, 6, 384)    0           ['batch_normalization_26[0][0]'] \n",
            "                                                                                                  \n",
            " activation_29 (Activation)     (None, 6, 6, 96)     0           ['batch_normalization_29[0][0]'] \n",
            "                                                                                                  \n",
            " max_pooling2d_2 (MaxPooling2D)  (None, 6, 6, 288)   0           ['mixed2[0][0]']                 \n",
            "                                                                                                  \n",
            " mixed3 (Concatenate)           (None, 6, 6, 768)    0           ['activation_26[0][0]',          \n",
            "                                                                  'activation_29[0][0]',          \n",
            "                                                                  'max_pooling2d_2[0][0]']        \n",
            "                                                                                                  \n",
            " conv2d_34 (Conv2D)             (None, 6, 6, 128)    98304       ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_34 (BatchN  (None, 6, 6, 128)   384         ['conv2d_34[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_34 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_34[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_35 (Conv2D)             (None, 6, 6, 128)    114688      ['activation_34[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_35 (BatchN  (None, 6, 6, 128)   384         ['conv2d_35[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_35 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_35[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_31 (Conv2D)             (None, 6, 6, 128)    98304       ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_36 (Conv2D)             (None, 6, 6, 128)    114688      ['activation_35[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_31 (BatchN  (None, 6, 6, 128)   384         ['conv2d_31[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_36 (BatchN  (None, 6, 6, 128)   384         ['conv2d_36[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_31 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_31[0][0]'] \n",
            "                                                                                                  \n",
            " activation_36 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_36[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_32 (Conv2D)             (None, 6, 6, 128)    114688      ['activation_31[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_37 (Conv2D)             (None, 6, 6, 128)    114688      ['activation_36[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_32 (BatchN  (None, 6, 6, 128)   384         ['conv2d_32[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_37 (BatchN  (None, 6, 6, 128)   384         ['conv2d_37[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_32 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_32[0][0]'] \n",
            "                                                                                                  \n",
            " activation_37 (Activation)     (None, 6, 6, 128)    0           ['batch_normalization_37[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_3 (AveragePo  (None, 6, 6, 768)   0           ['mixed3[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_30 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed3[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_33 (Conv2D)             (None, 6, 6, 192)    172032      ['activation_32[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_38 (Conv2D)             (None, 6, 6, 192)    172032      ['activation_37[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_39 (Conv2D)             (None, 6, 6, 192)    147456      ['average_pooling2d_3[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_30 (BatchN  (None, 6, 6, 192)   576         ['conv2d_30[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_33 (BatchN  (None, 6, 6, 192)   576         ['conv2d_33[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_38 (BatchN  (None, 6, 6, 192)   576         ['conv2d_38[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_39 (BatchN  (None, 6, 6, 192)   576         ['conv2d_39[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_30 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_30[0][0]'] \n",
            "                                                                                                  \n",
            " activation_33 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_33[0][0]'] \n",
            "                                                                                                  \n",
            " activation_38 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_38[0][0]'] \n",
            "                                                                                                  \n",
            " activation_39 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_39[0][0]'] \n",
            "                                                                                                  \n",
            " mixed4 (Concatenate)           (None, 6, 6, 768)    0           ['activation_30[0][0]',          \n",
            "                                                                  'activation_33[0][0]',          \n",
            "                                                                  'activation_38[0][0]',          \n",
            "                                                                  'activation_39[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_44 (Conv2D)             (None, 6, 6, 160)    122880      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_44 (BatchN  (None, 6, 6, 160)   480         ['conv2d_44[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_44 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_44[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_45 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_44[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_45 (BatchN  (None, 6, 6, 160)   480         ['conv2d_45[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_45 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_45[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_41 (Conv2D)             (None, 6, 6, 160)    122880      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_46 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_45[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_41 (BatchN  (None, 6, 6, 160)   480         ['conv2d_41[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_46 (BatchN  (None, 6, 6, 160)   480         ['conv2d_46[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_41 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_41[0][0]'] \n",
            "                                                                                                  \n",
            " activation_46 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_46[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_42 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_41[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_47 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_46[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_42 (BatchN  (None, 6, 6, 160)   480         ['conv2d_42[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_47 (BatchN  (None, 6, 6, 160)   480         ['conv2d_47[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_42 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_42[0][0]'] \n",
            "                                                                                                  \n",
            " activation_47 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_47[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_4 (AveragePo  (None, 6, 6, 768)   0           ['mixed4[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_40 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed4[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_43 (Conv2D)             (None, 6, 6, 192)    215040      ['activation_42[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_48 (Conv2D)             (None, 6, 6, 192)    215040      ['activation_47[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_49 (Conv2D)             (None, 6, 6, 192)    147456      ['average_pooling2d_4[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_40 (BatchN  (None, 6, 6, 192)   576         ['conv2d_40[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_43 (BatchN  (None, 6, 6, 192)   576         ['conv2d_43[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_48 (BatchN  (None, 6, 6, 192)   576         ['conv2d_48[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_49 (BatchN  (None, 6, 6, 192)   576         ['conv2d_49[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_40 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_40[0][0]'] \n",
            "                                                                                                  \n",
            " activation_43 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_43[0][0]'] \n",
            "                                                                                                  \n",
            " activation_48 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_48[0][0]'] \n",
            "                                                                                                  \n",
            " activation_49 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_49[0][0]'] \n",
            "                                                                                                  \n",
            " mixed5 (Concatenate)           (None, 6, 6, 768)    0           ['activation_40[0][0]',          \n",
            "                                                                  'activation_43[0][0]',          \n",
            "                                                                  'activation_48[0][0]',          \n",
            "                                                                  'activation_49[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_54 (Conv2D)             (None, 6, 6, 160)    122880      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_54 (BatchN  (None, 6, 6, 160)   480         ['conv2d_54[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_54 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_54[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_55 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_54[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_55 (BatchN  (None, 6, 6, 160)   480         ['conv2d_55[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_55 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_55[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_51 (Conv2D)             (None, 6, 6, 160)    122880      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_56 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_55[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_51 (BatchN  (None, 6, 6, 160)   480         ['conv2d_51[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_56 (BatchN  (None, 6, 6, 160)   480         ['conv2d_56[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_51 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_51[0][0]'] \n",
            "                                                                                                  \n",
            " activation_56 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_56[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_52 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_51[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_57 (Conv2D)             (None, 6, 6, 160)    179200      ['activation_56[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_52 (BatchN  (None, 6, 6, 160)   480         ['conv2d_52[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_57 (BatchN  (None, 6, 6, 160)   480         ['conv2d_57[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_52 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_52[0][0]'] \n",
            "                                                                                                  \n",
            " activation_57 (Activation)     (None, 6, 6, 160)    0           ['batch_normalization_57[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_5 (AveragePo  (None, 6, 6, 768)   0           ['mixed5[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_50 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed5[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_53 (Conv2D)             (None, 6, 6, 192)    215040      ['activation_52[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_58 (Conv2D)             (None, 6, 6, 192)    215040      ['activation_57[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_59 (Conv2D)             (None, 6, 6, 192)    147456      ['average_pooling2d_5[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_50 (BatchN  (None, 6, 6, 192)   576         ['conv2d_50[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_53 (BatchN  (None, 6, 6, 192)   576         ['conv2d_53[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_58 (BatchN  (None, 6, 6, 192)   576         ['conv2d_58[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_59 (BatchN  (None, 6, 6, 192)   576         ['conv2d_59[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_50 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_50[0][0]'] \n",
            "                                                                                                  \n",
            " activation_53 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_53[0][0]'] \n",
            "                                                                                                  \n",
            " activation_58 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_58[0][0]'] \n",
            "                                                                                                  \n",
            " activation_59 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_59[0][0]'] \n",
            "                                                                                                  \n",
            " mixed6 (Concatenate)           (None, 6, 6, 768)    0           ['activation_50[0][0]',          \n",
            "                                                                  'activation_53[0][0]',          \n",
            "                                                                  'activation_58[0][0]',          \n",
            "                                                                  'activation_59[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_64 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " batch_normalization_64 (BatchN  (None, 6, 6, 192)   576         ['conv2d_64[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_64 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_64[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_65 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_64[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_65 (BatchN  (None, 6, 6, 192)   576         ['conv2d_65[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_65 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_65[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_61 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_66 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_65[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_61 (BatchN  (None, 6, 6, 192)   576         ['conv2d_61[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_66 (BatchN  (None, 6, 6, 192)   576         ['conv2d_66[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_61 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_61[0][0]'] \n",
            "                                                                                                  \n",
            " activation_66 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_66[0][0]'] \n",
            "                                                                                                  \n",
            " conv2d_62 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_61[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_67 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_66[0][0]']          \n",
            "                                                                                                  \n",
            " batch_normalization_62 (BatchN  (None, 6, 6, 192)   576         ['conv2d_62[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_67 (BatchN  (None, 6, 6, 192)   576         ['conv2d_67[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_62 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_62[0][0]'] \n",
            "                                                                                                  \n",
            " activation_67 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_67[0][0]'] \n",
            "                                                                                                  \n",
            " average_pooling2d_6 (AveragePo  (None, 6, 6, 768)   0           ['mixed6[0][0]']                 \n",
            " oling2D)                                                                                         \n",
            "                                                                                                  \n",
            " conv2d_60 (Conv2D)             (None, 6, 6, 192)    147456      ['mixed6[0][0]']                 \n",
            "                                                                                                  \n",
            " conv2d_63 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_62[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_68 (Conv2D)             (None, 6, 6, 192)    258048      ['activation_67[0][0]']          \n",
            "                                                                                                  \n",
            " conv2d_69 (Conv2D)             (None, 6, 6, 192)    147456      ['average_pooling2d_6[0][0]']    \n",
            "                                                                                                  \n",
            " batch_normalization_60 (BatchN  (None, 6, 6, 192)   576         ['conv2d_60[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_63 (BatchN  (None, 6, 6, 192)   576         ['conv2d_63[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_68 (BatchN  (None, 6, 6, 192)   576         ['conv2d_68[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " batch_normalization_69 (BatchN  (None, 6, 6, 192)   576         ['conv2d_69[0][0]']              \n",
            " ormalization)                                                                                    \n",
            "                                                                                                  \n",
            " activation_60 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_60[0][0]'] \n",
            "                                                                                                  \n",
            " activation_63 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_63[0][0]'] \n",
            "                                                                                                  \n",
            " activation_68 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_68[0][0]'] \n",
            "                                                                                                  \n",
            " activation_69 (Activation)     (None, 6, 6, 192)    0           ['batch_normalization_69[0][0]'] \n",
            "                                                                                                  \n",
            " mixed7 (Concatenate)           (None, 6, 6, 768)    0           ['activation_60[0][0]',          \n",
            "                                                                  'activation_63[0][0]',          \n",
            "                                                                  'activation_68[0][0]',          \n",
            "                                                                  'activation_69[0][0]']          \n",
            "                                                                                                  \n",
            " flatten (Flatten)              (None, 27648)        0           ['mixed7[0][0]']                 \n",
            "                                                                                                  \n",
            " dense (Dense)                  (None, 512)          14156288    ['flatten[0][0]']                \n",
            "                                                                                                  \n",
            " dropout (Dropout)              (None, 512)          0           ['dense[0][0]']                  \n",
            "                                                                                                  \n",
            " dense_1 (Dense)                (None, 9)            4617        ['dropout[0][0]']                \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 23,136,169\n",
            "Trainable params: 14,160,905\n",
            "Non-trainable params: 8,975,264\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "loaded_model = tf.keras.models.load_model('/content/drive/MyDrive/C22-PS335: Capstone Project/DATASET/my_model')\n",
        "\n",
        "loaded_model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6LSz0mlJvSkY",
        "outputId": "f655d925-002e-4302-92f5-ad2df0414908"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[<tf.Variable 'dense/kernel:0' shape=(27648, 512) dtype=float32, numpy=\n",
            "array([[-0.01182645,  0.00769994,  0.00041237, ...,  0.00055744,\n",
            "        -0.00526027, -0.00038307],\n",
            "       [ 0.006112  ,  0.01240237, -0.01094166, ...,  0.00849507,\n",
            "         0.01304137, -0.01553278],\n",
            "       [-0.00537173, -0.01711446,  0.00822724, ..., -0.01317008,\n",
            "         0.00904069, -0.01656249],\n",
            "       ...,\n",
            "       [-0.01230238,  0.00797593,  0.01051713, ..., -0.02112387,\n",
            "        -0.05268655,  0.01532251],\n",
            "       [ 0.00404068, -0.01584794, -0.00787112, ..., -0.01193231,\n",
            "         0.0592573 ,  0.00534009],\n",
            "       [-0.00358953, -0.01110109,  0.00377554, ..., -0.01266326,\n",
            "        -0.0293951 , -0.00363391]], dtype=float32)>, <tf.Variable 'dense/bias:0' shape=(512,) dtype=float32, numpy=\n",
            "array([-6.51925802e-07, -4.02473286e-03, -3.16217449e-03, -3.16221756e-03,\n",
            "       -3.16215237e-03, -6.31749351e-03,  1.29011460e-05, -8.13743100e-07,\n",
            "       -3.16211488e-03,  5.31785190e-07, -2.78831692e-03, -4.86063585e-02,\n",
            "       -4.19991761e-02, -4.84983400e-02,  5.56209125e-06, -3.75419157e-03,\n",
            "       -7.17314892e-03, -8.31634179e-02,  8.26083124e-06, -4.04051039e-03,\n",
            "       -8.19343980e-03, -6.32351171e-03, -4.08699922e-02, -6.72907196e-03,\n",
            "        5.74602745e-06, -3.16219334e-03,  5.96325845e-06, -6.56294376e-02,\n",
            "       -7.96027109e-03, -6.32071216e-03, -6.32106420e-03, -1.54203735e-06,\n",
            "       -1.65093541e-02, -9.95407579e-04, -6.31323783e-03,  3.74158844e-07,\n",
            "       -1.45320455e-02, -3.16218310e-03, -4.29912843e-02, -8.45204853e-03,\n",
            "       -3.16208345e-03, -5.41561842e-03, -9.50915646e-03,  5.24078496e-06,\n",
            "        2.95182690e-06, -6.99883029e-02,  3.87430191e-07, -6.32152986e-03,\n",
            "       -3.16222804e-03,  2.48546712e-06, -3.16220266e-03, -5.43310307e-06,\n",
            "       -1.28774345e-02, -1.55135756e-02, -4.22112644e-05, -6.58678785e-02,\n",
            "       -6.20674714e-03, -3.23356525e-03,  4.04450111e-06,  4.43309546e-07,\n",
            "        2.80886889e-06, -3.80202429e-03,  1.97882764e-06, -3.76434159e-03,\n",
            "       -3.12126568e-03, -3.58753875e-02, -6.93387259e-03,  3.66871245e-06,\n",
            "        1.25051010e-05, -4.98929014e-03, -1.04134595e-02, -7.35829845e-02,\n",
            "       -6.02784269e-02, -3.16219195e-03, -3.63371777e-03, -3.16211488e-03,\n",
            "        7.04079866e-06, -1.85460178e-03,  4.47645289e-05, -7.79330637e-03,\n",
            "       -6.11423030e-02, -5.73590398e-02, -9.29167587e-03, -3.16217798e-03,\n",
            "       -5.25563732e-02, -3.97092290e-03, -4.04096209e-02, -4.52673249e-03,\n",
            "       -3.16207786e-03, -3.16219265e-03, -3.16219428e-03,  1.47670507e-05,\n",
            "       -3.16213933e-03, -3.82307917e-07, -1.78208575e-06,  5.67268580e-06,\n",
            "        3.12295742e-06, -3.16221663e-03, -5.35620637e-02, -3.16216960e-03,\n",
            "       -6.60677068e-03, -7.39052445e-02, -3.16212792e-03, -3.16216168e-03,\n",
            "       -3.54662314e-02,  9.44575877e-05,  3.96743417e-06,  2.06574332e-05,\n",
            "       -7.31592700e-02, -3.09338816e-03,  1.84122473e-06,  8.12090002e-06,\n",
            "       -4.75321012e-03, -4.21791337e-03, -3.16216936e-03,  3.20468098e-06,\n",
            "       -3.16216098e-03, -3.81045118e-02,  8.47037882e-07, -3.98314977e-03,\n",
            "       -5.21338265e-03, -3.16209299e-03, -4.57468629e-03, -3.16221337e-03,\n",
            "       -5.16275652e-02, -3.16220266e-03, -1.10501423e-06, -3.16208601e-03,\n",
            "       -3.16207041e-03, -3.16219009e-03, -3.16194771e-03, -6.90998463e-03,\n",
            "       -9.59395198e-04, -8.98768939e-03,  1.07758724e-05, -6.25156462e-02,\n",
            "       -3.16194445e-03, -9.69356857e-03, -7.59887770e-02, -3.73725593e-02,\n",
            "       -8.41618553e-02, -6.02812394e-02, -1.68380402e-02, -9.99319367e-03,\n",
            "       -6.32083835e-03, -5.22902887e-03, -6.82953279e-03, -5.15271164e-03,\n",
            "       -3.16206808e-03, -3.16222804e-03, -6.30286187e-02, -5.85787781e-02,\n",
            "       -3.45529579e-02, -3.16221220e-03, -5.53100146e-02, -3.16219591e-03,\n",
            "       -9.82351787e-03, -2.17814138e-03, -8.41449946e-07, -9.82902199e-03,\n",
            "       -2.44472176e-08, -6.32149540e-03, -3.16211232e-03, -3.56525257e-02,\n",
            "       -6.25796616e-02, -5.43126538e-02, -3.63350324e-02, -2.14518746e-03,\n",
            "       -4.99867322e-03, -4.69972976e-02, -4.60568443e-03, -1.79041997e-02,\n",
            "       -3.16189416e-03, -3.16219078e-03, -1.93299837e-02, -3.16212722e-03,\n",
            "       -6.71323687e-02, -3.48518323e-03, -2.78931111e-07, -3.16218892e-03,\n",
            "        1.35875307e-05, -1.88628212e-04, -3.16216913e-03, -8.02958682e-02,\n",
            "       -4.22614962e-02, -7.37021491e-03,  3.41935083e-06, -6.35703281e-03,\n",
            "        2.55019404e-06,  8.00424628e-03, -6.32062089e-03, -3.16209672e-03,\n",
            "       -5.70497289e-02, -3.16214259e-03, -3.16211488e-03, -3.25745600e-03,\n",
            "        1.77416950e-07, -3.16219660e-03, -3.16218962e-03, -4.24496224e-03,\n",
            "       -3.16219614e-03, -3.16218077e-03, -1.64491720e-02,  2.61748210e-06,\n",
            "       -3.03498693e-02, -5.29305190e-02, -5.18656243e-03, -7.00118858e-03,\n",
            "       -6.73268661e-02,  1.90781429e-06, -6.24038205e-02,  1.94553286e-06,\n",
            "        3.03075649e-06, -3.28640454e-06, -3.16213281e-03,  5.62511152e-04,\n",
            "       -3.77490697e-03, -2.60585286e-02, -5.50798550e-02, -2.04578973e-03,\n",
            "       -3.16166505e-03, -3.16220382e-03, -3.55038866e-02, -5.30104153e-02,\n",
            "       -6.32184371e-03,  1.71838328e-05, -5.01696067e-03, -3.16217938e-03,\n",
            "       -3.16221593e-03,  6.40028156e-06, -4.35155630e-03, -6.40282109e-02,\n",
            "       -6.24678563e-03, -4.83453311e-02, -7.04456121e-03, -6.28539994e-02,\n",
            "       -8.07374623e-03, -6.31920993e-03,  1.67993596e-03, -3.16210929e-03,\n",
            "        3.14856879e-06, -4.11140849e-04, -6.16537314e-03, -3.15616047e-03,\n",
            "       -3.16216634e-03, -4.95205708e-02, -5.42817563e-02, -3.16209416e-03,\n",
            "       -4.94202459e-03, -3.85784879e-02, -5.27481288e-02, -7.10545555e-02,\n",
            "       -3.16211907e-03, -5.30322231e-02, -3.16204224e-03, -3.16219754e-03,\n",
            "       -2.89038493e-04, -4.69039427e-03, -6.28111791e-03, -5.95056787e-02,\n",
            "       -1.32983336e-02, -6.32212218e-03,  4.95719723e-06,  6.39003702e-06,\n",
            "       -6.54971134e-03,  1.91878062e-05, -6.79718331e-02, -3.16218822e-03,\n",
            "       -4.69097961e-03, -4.30226624e-02, -6.99579902e-03, -3.16207367e-03,\n",
            "       -1.67358480e-02, -1.43657653e-02, -3.16217425e-03, -7.05908984e-02,\n",
            "       -5.92086976e-03, -3.16206669e-03, -4.25576158e-02, -3.34104476e-03,\n",
            "       -9.35883150e-02, -3.78623083e-02, -3.57941259e-04, -3.16221826e-03,\n",
            "       -2.76385192e-02, -5.56105375e-03, -8.11559334e-02, -6.56897202e-02,\n",
            "        4.45544720e-06, -3.30003351e-02, -5.78128546e-03, -6.42384514e-02,\n",
            "       -6.30586548e-03, -4.76253517e-02, -3.16219730e-03, -9.01676249e-03,\n",
            "       -3.47321816e-02, -2.56122835e-02, -3.16205574e-03, -5.88428415e-02,\n",
            "       -6.30807653e-02, -3.64650190e-02, -3.16219660e-03, -6.43800274e-02,\n",
            "       -3.16214631e-03, -6.52036071e-02, -6.25425763e-03,  2.14937609e-05,\n",
            "       -8.23020488e-02, -5.47782816e-02, -4.25530877e-03, -6.31230557e-03,\n",
            "       -5.07572945e-03,  7.76024535e-07,  1.85213758e-05, -1.67956023e-05,\n",
            "       -3.67529900e-03, -4.21822295e-02, -3.16202594e-03, -3.16208368e-03,\n",
            "       -5.32811461e-03, -4.77896668e-02, -3.16210743e-03, -6.31947163e-03,\n",
            "       -1.68522820e-06, -1.10300751e-02, -3.78279500e-02, -7.31057674e-03,\n",
            "       -3.39230825e-03,  3.47942114e-06, -5.86398039e-03,  1.60685740e-05,\n",
            "       -3.16214119e-03,  1.90590417e-05, -3.16219847e-03, -2.53660628e-03,\n",
            "       -3.63481864e-02, -6.32278295e-03, -4.97896411e-02, -3.16203688e-03,\n",
            "       -3.16221430e-03,  2.45741103e-05, -3.16211046e-03, -3.16218426e-03,\n",
            "       -2.74775061e-03, -3.16204969e-03, -3.16204410e-03, -2.11218130e-02,\n",
            "       -3.16221802e-03, -3.96508202e-02, -6.27064100e-03, -3.16214422e-03,\n",
            "       -3.16206412e-03, -7.16598779e-02, -4.10893001e-03, -4.78783175e-02,\n",
            "       -3.16214911e-03, -1.92318112e-07, -3.08324955e-03, -4.27613780e-03,\n",
            "        2.59574463e-05, -3.76590565e-02, -3.16221430e-03, -3.16219032e-03,\n",
            "       -4.74915653e-03, -3.16216005e-03, -4.07397468e-03, -5.09995362e-03,\n",
            "       -3.09681380e-03, -4.87780198e-07, -1.28764994e-02, -4.82512126e-03,\n",
            "       -7.36164302e-03, -3.16215679e-03, -6.31667860e-03, -4.36719321e-02,\n",
            "        3.05939466e-06, -3.16370139e-03, -2.95951441e-02, -3.16210883e-03,\n",
            "       -3.16216541e-03,  9.98610631e-06, -1.23953251e-02, -8.25778618e-02,\n",
            "       -5.95404431e-02, -3.16215423e-03, -2.52072793e-03, -3.96163166e-02,\n",
            "       -3.16204922e-03,  2.86032446e-05, -3.16221872e-03, -3.56207695e-03,\n",
            "       -3.30914482e-02, -8.56859386e-02, -4.02898863e-02, -5.75120300e-02,\n",
            "       -5.59807904e-02, -4.81524616e-02,  4.03398229e-03, -3.16213467e-03,\n",
            "       -1.65904697e-03, -5.93256438e-03, -3.16217542e-03, -6.31248672e-03,\n",
            "       -5.87619655e-02,  1.49477273e-06, -5.00036329e-02, -1.51828490e-03,\n",
            "        1.57055547e-05,  7.10319728e-06, -3.16216215e-03, -5.84052466e-02,\n",
            "       -3.16218217e-03, -4.63394623e-04, -6.06282381e-04,  7.92788342e-07,\n",
            "       -4.07451950e-02, -3.16216517e-03, -5.46154287e-03,  7.63617223e-04,\n",
            "       -1.20823029e-02, -6.54267147e-02, -4.89720292e-02, -5.18854968e-02,\n",
            "       -4.69435230e-02, -6.02653716e-03,  9.66945663e-07, -3.16213723e-03,\n",
            "       -3.16220336e-03, -7.05092680e-03, -3.16210114e-03, -6.31501107e-03,\n",
            "       -3.16215213e-03,  1.09458342e-05,  5.13298437e-06,  1.78272399e-04,\n",
            "        2.54740007e-06, -3.16209695e-03, -5.35385534e-02, -6.84986115e-02,\n",
            "       -4.34597507e-02, -5.08714430e-02, -3.16204596e-03, -1.22591318e-03,\n",
            "       -5.64293601e-02, -6.33303970e-02, -2.85111717e-03, -7.60110766e-02,\n",
            "       -2.93071028e-02,  5.00469469e-06, -3.16217518e-03, -6.31798524e-03,\n",
            "       -4.59263176e-02,  6.65220432e-06, -1.20169539e-02, -6.82184547e-02,\n",
            "       -3.16217542e-03, -5.71771786e-02, -3.16180941e-03,  1.68033876e-06,\n",
            "       -2.59173457e-02,  3.41522973e-05, -1.32075809e-02, -6.32026605e-03,\n",
            "       -6.31533563e-03, -1.99293206e-03, -3.16210231e-03, -3.84272449e-02,\n",
            "        5.30970283e-06, -5.45275994e-02, -7.87715763e-02,  9.01753083e-07,\n",
            "       -3.16213514e-03, -6.31554238e-03, -3.16212326e-03, -1.04664834e-02,\n",
            "        1.19016040e-05, -3.16218566e-03, -9.42543149e-03, -1.59594156e-02,\n",
            "       -2.22687516e-02, -3.16209905e-03, -6.19318709e-03,  1.00398902e-05,\n",
            "        6.39958307e-06,  7.15046190e-06, -3.16218450e-03, -3.16208578e-03,\n",
            "       -3.16212745e-03, -6.61142245e-02, -2.99466774e-06, -4.80896514e-03,\n",
            "       -2.06682808e-03, -3.16220685e-03, -7.74010876e-03, -6.31744880e-03,\n",
            "       -7.46714473e-02, -8.66802782e-03,  4.61773016e-06, -1.13015277e-02,\n",
            "       -2.40103365e-03,  1.39628537e-06, -4.65889312e-02, -3.16216401e-03,\n",
            "       -4.06551594e-03, -6.31975569e-03, -1.59171736e-03, -3.16212303e-03,\n",
            "        3.69781628e-06, -5.98984817e-03, -7.20102713e-02, -3.16217844e-03],\n",
            "      dtype=float32)>, <tf.Variable 'dense_1/kernel:0' shape=(512, 9) dtype=float32, numpy=\n",
            "array([[ 0.01361096,  0.00410464,  0.09013025, ..., -0.10285684,\n",
            "        -0.09323622, -0.03121788],\n",
            "       [-0.01820511, -0.0249368 , -0.09282466, ...,  0.02853641,\n",
            "        -0.04545238, -0.01104592],\n",
            "       [ 0.07783296, -0.09919071, -0.01933684, ...,  0.0565871 ,\n",
            "        -0.04473983,  0.07484408],\n",
            "       ...,\n",
            "       [-0.01571258,  0.09885543, -0.10876872, ..., -0.09489933,\n",
            "         0.04514091, -0.05090574],\n",
            "       [-0.14434797, -0.11133195,  0.07443414, ..., -0.122982  ,\n",
            "        -0.08881962,  0.00070426],\n",
            "       [ 0.01816493, -0.06417891, -0.06344062, ..., -0.02792441,\n",
            "        -0.03685046,  0.00039312]], dtype=float32)>, <tf.Variable 'dense_1/bias:0' shape=(9,) dtype=float32, numpy=\n",
            "array([ 0.10035665, -0.07050524, -0.00868733,  0.02450355,  0.21806483,\n",
            "       -0.15772   , -0.16148734, -0.06439823,  0.02517098], dtype=float32)>]\n"
          ]
        }
      ],
      "source": [
        "print(loaded_model.trainable_variables)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uIJfNDFdLV2X"
      },
      "source": [
        "## Save The Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o8VaOgu3w049",
        "outputId": "cea53169-276d-4a7c-8bd4-0a645e601747"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Assets written to: /content/drive/MyDrive/Capstone Project/my_model/assets\n",
            "INFO:tensorflow:Assets written to: /content/drive/MyDrive/Capstone Project/my_model/my_model_saved_model/assets\n"
          ]
        }
      ],
      "source": [
        "model.save('/content/drive/MyDrive/Capstone Project/my_model')\n",
        "model.save_weights('/content/drive/MyDrive/Capstone Project/my_weight')\n",
        "\n",
        "tf.saved_model.save(\n",
        "  model, '/content/drive/MyDrive/Capstone Project/my_model/my_model_saved_model')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O_3tQNaapBAV"
      },
      "source": [
        "## Convert Saved Model to TF-Lite"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cmx6aazypHbP"
      },
      "outputs": [],
      "source": [
        "# Select mode of optimization\n",
        "mode = \"balanced\" \n",
        "\n",
        "if mode == 'Storage':\n",
        "    optimization = tf.lite.Optimize.OPTIMIZE_FOR_SIZE\n",
        "elif mode == 'Speed':\n",
        "    optimization = tf.lite.Optimize.OPTIMIZE_FOR_LATENCY\n",
        "else:\n",
        "    optimization = tf.lite.Optimize.DEFAULT"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VaHWOeBVtCyJ"
      },
      "outputs": [],
      "source": [
        "# EXERCISE: Use the TFLiteConverter SavedModel API to initialize the converter\n",
        "export_dir = '/content/drive/MyDrive/Capstone Project/my_model'\n",
        "converter = tf.lite.TFLiteConverter.from_saved_model(export_dir)\n",
        "\n",
        "# Set the optimzations\n",
        "converter.optimizations = [optimization]\n",
        "\n",
        "# Invoke the converter to finally generate the TFLite model\n",
        "tflite_model = converter.convert()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "U85c2YmYtMyS"
      },
      "outputs": [],
      "source": [
        "tflite_model_file = pathlib.Path('/content/drive/MyDrive/Capstone Project/adhaar.tflite')\n",
        "tflite_model_file.write_bytes(tflite_model)"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "collapsed_sections": [],
      "name": "food_classifcation.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}