multi_model_ResNet_VGG.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "multi_model_ResNet_VGG.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyO5rBlF0Bs8GMdPOyiWEqyc",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jvishnuvardhan/Stackoverflow_Questions/blob/master/multi_model_ResNet_VGG.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Vly7ex3DiGg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 632
        },
        "outputId": "4d48af03-9362-44f9-f210-2303ba507843"
      },
      "source": [
        "!pip install tensorflow==2.1"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: tensorflow==2.1 in /usr/local/lib/python3.6/dist-packages (2.1.0)\n",
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            "Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (46.1.3)\n",
            "Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (1.7.2)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (0.4.1)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (1.0.1)\n",
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            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (1.3.0)\n",
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            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (2020.4.5.1)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.6/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (0.4.8)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow==2.1) (3.1.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZvrgDMcYDnQb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import tensorflow as tf\n",
        "from tensorflow.keras.applications import ResNet50, VGG16"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KnMGwE4vLBah",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "model = tf.keras.Sequential()\n",
        "img_shape = (164, 164, 3)\n",
        "model.add(ResNet50(include_top=False, input_shape=img_shape, weights = None))\n",
        "\n",
        "model.add(tf.keras.layers.Reshape(target_shape=(64,64,18)))\n",
        "model.add(tf.keras.layers.Conv2D(3,kernel_size=(3,3),name='Conv2d'))\n",
        "\n",
        "VGG_model = VGG16(include_top=False, weights=None)\n",
        "model.add(VGG_model)\n",
        "\n",
        "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AGeTpxmlD5DZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "56dec8af-d744-4945-ea98-c8802d28bb5c"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "resnet50 (Model)             (None, 6, 6, 2048)        23587712  \n",
            "_________________________________________________________________\n",
            "reshape (Reshape)            (None, 64, 64, 18)        0         \n",
            "_________________________________________________________________\n",
            "Conv2d (Conv2D)              (None, 62, 62, 3)         489       \n",
            "_________________________________________________________________\n",
            "vgg16 (Model)                multiple                  14714688  \n",
            "=================================================================\n",
            "Total params: 38,302,889\n",
            "Trainable params: 38,249,769\n",
            "Non-trainable params: 53,120\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}