image_sentiment_analysis_ver2_(in_progress).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "image sentiment analysis_ver2 (in progress).ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "ahmfK-5qodGN"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import cv2\n",
        "import tqdm as tqdm"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EYYr_5bMotVy"
      },
      "source": [
        "from tensorflow.keras.preprocessing.image import load_img\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O1Ix2SJFowYo"
      },
      "source": [
        "import os"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BrzlLyySqYQD"
      },
      "source": [
        "디렉토리 안의 파일 접근 test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 345
        },
        "id": "p-Y69c45o5s4",
        "outputId": "6aa76fef-fe6a-40cd-c4a1-33b9f1d998dd"
      },
      "source": [
        "def print_files_in_dir(root_dir, prefix):\n",
        "  files = os.listdir(root_dir) # root_dir의 모든 파일 출력\n",
        "  print(files)\n",
        "  for files in files:\n",
        "    path = os.path.join(root_dir, file) # => 여기서 오류남\n",
        "    print(prefix + path)\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "  root_dir = \"/content/sample_data\"\n",
        "  print_files_in_dir(root_dir, \"\")"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['anscombe.json', 'README.md', 'mnist_train_small.csv', 'california_housing_train.csv', 'mnist_test.csv', 'california_housing_test.csv']\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-9-729c470f5eb1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0m__name__\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"__main__\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m   \u001b[0mroot_dir\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"/content/sample_data\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m   \u001b[0mprint_files_in_dir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroot_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-9-729c470f5eb1>\u001b[0m in \u001b[0;36mprint_files_in_dir\u001b[0;34m(root_dir, prefix)\u001b[0m\n\u001b[1;32m      3\u001b[0m   \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0;32mfor\u001b[0m \u001b[0mfiles\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0mpath\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroot_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprefix\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mpath\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'file' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rJ8ptbqQqXLs",
        "outputId": "e523fe43-e983-4bdc-ef04-1c430b39a8bf"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p1lZ2yF6q85D"
      },
      "source": [
        "# train_dir = '/content/drive/MyDrive/images_crawling/train'\n",
        "# test_dir='/content/drive/MyDrive/images_crawling/validation'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5-TrocBE2fTm"
      },
      "source": [
        "데이터셋 load"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TY0iY7LzrfLk",
        "outputId": "f0c71c23-c464-4006-8007-b39524e45eda"
      },
      "source": [
        "for dirname, _, filenames in os.walk('/content/drive/MyDrive/dataset'):\n",
        "  for filename in filenames:\n",
        "    print(os.path.join(dirname, filename))"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/dataset/test.csv\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_4.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_1.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/Cloud_3.jpeg\n",
            "/content/drive/MyDrive/dataset/alien_test/Cloud_4.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_9.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_6.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/Cloud_2.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_2.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/rain_1.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/rain_3.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_10.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_3.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_7.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_8.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/foggy_5.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/Cloud_1.png\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_3.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/shine_2.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_2.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_5.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/rain_4.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/rain_5.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/rain_6.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_6.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/shine_3.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_7.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/shine_1.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_1.jpg\n",
            "/content/drive/MyDrive/dataset/alien_test/sunrise_4.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy1.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy10.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy8.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy233.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy150.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy131.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy278.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy175.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy25.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy236.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy253.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy199.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy160.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy264.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy163.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy134.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy283.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy68.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy63.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy62.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy213.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy71.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy173.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy177.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy12.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy121.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy245.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy193.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy110.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy96.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy34.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy26.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy6.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy117.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy142.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy204.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy92.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy260.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy290.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy19.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy40.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy57.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy43.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy222.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy115.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy39.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy78.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy247.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy103.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy114.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy229.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy42.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy237.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy70.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy79.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy174.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy239.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy216.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy200.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy287.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy95.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy276.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy225.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy66.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy123.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy24.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy130.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy101.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy269.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy108.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy241.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy65.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy140.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy64.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy27.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy82.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy111.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy231.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy169.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy155.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy271.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy162.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy218.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy261.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy180.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy273.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy102.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy2.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy152.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy176.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy30.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy104.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy31.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy206.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy143.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy136.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy118.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy88.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy279.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy83.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy81.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy295.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy154.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy46.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy234.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy100.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy219.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy240.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy235.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy89.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy156.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy32.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy284.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy282.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy59.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy170.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy168.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy166.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy191.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy161.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy113.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy298.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy167.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy99.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy291.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy205.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy246.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy48.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy44.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy129.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy262.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy124.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy119.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy76.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy69.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy86.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy109.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy188.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy3.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy194.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy250.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy73.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy192.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy151.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy144.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy181.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy106.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy217.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy58.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy13.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy215.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy274.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy158.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy41.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy220.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy75.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy242.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy80.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy208.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy258.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy120.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy28.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy145.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy251.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy171.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy147.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy132.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy226.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy252.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy186.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy243.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy36.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy20.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy18.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy277.jpg\n",
            "/content/drive/MyDrive/dataset/cloudy/cloudy275.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise130.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise127.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise126.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise123.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise125.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise131.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise13.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise124.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise122.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise118.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise120.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise119.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise12.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise115.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise113.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise114.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise228.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise223.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise222.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise220.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise22.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise219.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise216.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise217.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise214.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise215.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise221.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise218.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise213.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise212.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise208.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise210.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise21.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise206.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise205.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise204.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise203.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise211.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise202.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise207.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise2.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise200.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise201.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise193.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise196.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise20.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise198.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise194.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise187.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise19.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise189.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise191.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise185.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise181.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise183.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise182.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise188.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise186.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise180.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise176.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise179.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise178.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise18.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise170.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise173.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise172.jpg\n",
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            "/content/drive/MyDrive/dataset/sunrise/sunrise281.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise280.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise28.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise277.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise275.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise276.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise282.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise278.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise274.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise273.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise270.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise271.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise269.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise27.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise264.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise267.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise265.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise272.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise268.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise266.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise263.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise254.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise258.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise257.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise256.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise26.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise259.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise261.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise262.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise260.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise255.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise253.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise25.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise250.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise249.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise245.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise248.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise247.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise246.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise252.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise251.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise244.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise243.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise241.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise24.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise239.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise238.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise234.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise237.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise236.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise242.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise240.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise235.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise233.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise231.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise230.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise229.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise226.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise227.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise224.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise225.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise232.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise332.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise331.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise327.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise325.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise324.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise323.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise326.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise322.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise319.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise317.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise318.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise32.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise321.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise312.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise313.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise314.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise320.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise316.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise315.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise309.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise310.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise307.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise31.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise311.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise304.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise305.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise303.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise308.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise306.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise302.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise300.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise3.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise30.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise298.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise301.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise295.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise293.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise294.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise299.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise297.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise296.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise289.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise290.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise291.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise29.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise292.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise284.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise287.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise285.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise288.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise286.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise283.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise69.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise64.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise61.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise59.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise56.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise6.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise58.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise54.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise52.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise55.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise60.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise57.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise53.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise51.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise43.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise44.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise46.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise45.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise48.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise49.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise5.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise50.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise47.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise42.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise41.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise39.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise38.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise37.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise348.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise347.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise35.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise350.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise40.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise36.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise349.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise4.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise346.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise344.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise342.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise343.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise337.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise340.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise34.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise338.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise345.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise341.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise339.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise334.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise335.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise333.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise336.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise330.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise33.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise328.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise329.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise95.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise94.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise93.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise99.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise98.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise97.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise89.jpeg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise90.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise9.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise91.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise92.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise85.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise84.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise83.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise88.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise87.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise86.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise78.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise80.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise8.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise77.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise82.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise74.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise75.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise76.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise79.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise72.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise73.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise67.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise68.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise66.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise70.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise65.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise62.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise63.jpg\n",
            "/content/drive/MyDrive/dataset/sunrise/sunrise71.jpg\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6BMIqK4Arzq2",
        "outputId": "50e7fd95-9c6a-4fee-9e20-77afdb73531e"
      },
      "source": [
        "root_dir = '/content/drive/MyDrive/dataset'\n",
        "os.listdir(root_dir)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['test.csv', 'alien_test', 'cloudy', 'shine', 'foggy', 'rainy', 'sunrise']"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BhbKnPjzruZE"
      },
      "source": [
        "foggy = root_dir + '/foggy'\n",
        "sunrise = root_dir + '/sunrise'\n",
        "shine = root_dir + '/shine'\n",
        "rainy = root_dir + '/rainy'\n",
        "cloudy = root_dir + '/cloudy'\n",
        "test = root_dir + '/alien_test'\n"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fNEVaGPNsGho",
        "outputId": "9d126639-131e-40b6-d031-c9862fe693e0"
      },
      "source": [
        "print(\"Number of images in each directory:\")\n",
        "print(f\"Foggy: {len(os.listdir(foggy))}\")\n",
        "print(f\"Sunrise: {len(os.listdir(sunrise))}\")\n",
        "print(f\"Shine: {len(os.listdir(shine))}\")\n",
        "print(f\"Rainy: {len(os.listdir(rainy))}\")\n",
        "print(f\"Cloudy: {len(os.listdir(cloudy))}\")"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of images in each directory:\n",
            "Foggy: 300\n",
            "Sunrise: 339\n",
            "Shine: 250\n",
            "Rainy: 292\n",
            "Cloudy: 300\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "49W5B1LFsrTP"
      },
      "source": [
        "데이터 전처리"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9rPFG8Raso9n"
      },
      "source": [
        "x= []\n",
        "y= []\n",
        "dataset = []"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yfwuyyK9svfH"
      },
      "source": [
        "def create_dataset(dir, dir_name):\n",
        "  for i in tqdm.tqdm(os.listdir(dir)): # 진행률 표시\n",
        "    full_path = os.path.join(dir, i)\n",
        "\n",
        "    try:\n",
        "      img = cv2.imread(full_path)\n",
        "      img = cv2.resize(img, (150, 150))\n",
        "\n",
        "    except:\n",
        "      continue\n",
        "\n",
        "    x.append(img)\n",
        "    y.append(dir_name)\n",
        "  return x, y"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lKRIgrJTtA98",
        "outputId": "1a9f49c8-93ae-4114-cbf0-e0ecb014d1d4"
      },
      "source": [
        "x,y= create_dataset(foggy,\"foggy\")\n",
        "x,y= create_dataset(sunrise,\"sunrise\")\n",
        "x,y= create_dataset(shine,\"shine\")\n",
        "x,y= create_dataset(rainy,\"rainy\")\n",
        "x,y= create_dataset(cloudy,\"cloudy\")"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 300/300 [01:34<00:00,  3.16it/s]\n",
            "100%|██████████| 339/339 [01:39<00:00,  3.40it/s]\n",
            "100%|██████████| 250/250 [01:08<00:00,  3.66it/s]\n",
            "100%|██████████| 292/292 [01:42<00:00,  2.85it/s]\n",
            "100%|██████████| 300/300 [01:21<00:00,  3.66it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oRlwFn2YtJT7"
      },
      "source": [
        "numpy를 이용해서 배열로 변환"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8Qmbrt-rtC6d",
        "outputId": "bf8f2210-6506-4f39-e6df-0eb84e76fa67"
      },
      "source": [
        "x = np.array(x)\n",
        "y = np.array(y)\n",
        "x.shape, y.shape"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1479, 150, 150, 3), (1479,))"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "744cyJhf3FSa"
      },
      "source": [
        "seaborn으로 데이터분포 시각화"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NFFE79KUvBT0"
      },
      "source": [
        "import seaborn as sns"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8qKw4gVMzMZm",
        "outputId": "f33ccff8-0017-4f8b-c0ac-8a8370ab17af"
      },
      "source": [
        "print(plt.style.available) # style.use로 테마 바꾸기"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Solarize_Light2', '_classic_test_patch', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 512
        },
        "id": "UUHXFKU6tPfz",
        "outputId": "37e82e97-f4aa-460e-ca4d-4a1ffd0e4536"
      },
      "source": [
        "plt.figure(figsize = (9, 7))\n",
        "plt.style.use(\"fivethirtyeight\")\n",
        "sns.countplot(y)\n",
        "plt.show()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x504 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oMvhoaGsvQYl"
      },
      "source": [
        "import random"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QDGHbyncvSyD"
      },
      "source": [
        "샘플 이미지 출력 (test)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oPwoqIiCvDAZ"
      },
      "source": [
        "fig = plt.figure(figsize= (12, 7))\n",
        "for i in range(15):\n",
        "  sample = random.choice(range(len(x)))\n",
        "  image = x[sample]\n",
        "  category = y[sample]\n",
        "  plt.subplot(3, 5, i+1)\n",
        "  plt.subplots_adjust(hspace=0.3)\n",
        "  plt.imshow(image)\n",
        "  plt.xlabel(category)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UidXXhPxu-ep"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "le = LabelEncoder()\n",
        "y = le.fit_transform(y)"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fcezj5GvvsDr"
      },
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZFnVw2BevyW8"
      },
      "source": [
        "# test_size= 0.2, random_state=42\n",
        "\n",
        "x_train, x_test, y_train, y_test = train_test_split(x, y, \n",
        "                                                    test_size=0.2, \n",
        "                                                    random_state=42)"
      ],
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v6I0MeYfv8fO"
      },
      "source": [
        "img_size = 150\n",
        "\n",
        "# rescale\n",
        "x_train = np.array(x_train)/255.0\n",
        "x_test = np.array(x_test)/255.0\n",
        "\n",
        "# train_data reshape\n",
        "x_train = x_train.reshape(-1, img_size, img_size, 3)\n",
        "y_train = np.array(y_train)\n",
        "\n",
        "# test_data reshape\n",
        "x_test = x_test.reshape(-1, img_size, img_size, 3)\n",
        "y_test = np.array(y_test)"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AEO6vDu2wVCB"
      },
      "source": [
        "from sklearn.preprocessing import LabelBinarizer"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XfkRSDuowYzF"
      },
      "source": [
        "lb = LabelBinarizer()\n",
        "\n",
        "y_train_lb = lb.fit_transform(y_train)\n",
        "y_test_lb = lb.fit_transform(y_test)"
      ],
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0HPJOGcbwhct",
        "outputId": "15127845-87e8-4ae3-94b9-8dd861f90b99"
      },
      "source": [
        "y_train_lb.shape, y_test_lb.shape"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((1183, 5), (296, 5))"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RhcekULpwlrM"
      },
      "source": [
        "모델 설계 및 디자인_ver2: VGG19 사용\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bPjsvwG7wkRX",
        "outputId": "855858ff-8047-4f71-d54f-0dcf86eb93d6"
      },
      "source": [
        "from tensorflow.keras.applications.vgg19 import VGG19\n",
        "vgg = VGG19(weights = \"imagenet\", \n",
        "            include_top=False, # 최상단의 fully connected layer 포함 시킬지 여부\n",
        "            input_shape=(img_size, img_size,3))"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg19/vgg19_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "80142336/80134624 [==============================] - 1s 0us/step\n",
            "80150528/80134624 [==============================] - 1s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mpxokmiiw1yZ"
      },
      "source": [
        "for layer in vgg.layers:\n",
        "  layer.trainable = False # 레이어 동결"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bqtnFxi3xGUh"
      },
      "source": [
        "from tensorflow.keras import Sequential\n",
        "from tensorflow.keras.layers import Flatten, Dense"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K0DHTuP5xV3d"
      },
      "source": [
        "# activation: softmax\n",
        "\n",
        "model = Sequential()\n",
        "model.add(vgg)\n",
        "model.add(Flatten())\n",
        "model.add(Dense(5, activation = \"softmax\"))"
      ],
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z6Q3UVP1xa8n",
        "outputId": "aed00650-1fa5-4266-c507-bd10bf9e121f"
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "vgg19 (Functional)           (None, 4, 4, 512)         20024384  \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 8192)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 5)                 40965     \n",
            "=================================================================\n",
            "Total params: 20,065,349\n",
            "Trainable params: 40,965\n",
            "Non-trainable params: 20,024,384\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OcSx9ucyxe2s"
      },
      "source": [
        "optimizer, compile 정보 설정"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ex7wHp22xb1L"
      },
      "source": [
        "model.compile(optimizer=\"adam\", \n",
        "              loss=\"categorical_crossentropy\", \n",
        "              metrics=\"accuracy\")"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xT2QcRSdxoza",
        "outputId": "a16af270-8902-4fe5-9395-69379979401c"
      },
      "source": [
        "unique, counts = np.unique(y_train_lb, return_counts=True)\n",
        "print(unique, counts)"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0 1] [4732 1183]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2WV_PQeS0dDR"
      },
      "source": [
        "데이터 연결 및 학습"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ktOwJThtyaBo",
        "outputId": "13a6e6c0-7bfe-4c7d-9bde-295370b1b651"
      },
      "source": [
        "# batch_size: 32\n",
        "# epochs: 15\n",
        "\n",
        "batch_size=32\n",
        "history= model.fit(x_train, y_train_lb, \n",
        "                   epochs=15, \n",
        "                   validation_data=(x_test,y_test_lb),\n",
        "                   batch_size=batch_size,\n",
        "                   verbose=1 # 학습 진행상황 보여지게 설정\n",
        "                   )"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/15\n",
            "37/37 [==============================] - 349s 9s/step - loss: 0.9679 - accuracy: 0.6610 - val_loss: 0.5847 - val_accuracy: 0.8007\n",
            "Epoch 2/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.4429 - accuracy: 0.8732 - val_loss: 0.4727 - val_accuracy: 0.8345\n",
            "Epoch 3/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.3158 - accuracy: 0.9155 - val_loss: 0.3862 - val_accuracy: 0.9088\n",
            "Epoch 4/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.2492 - accuracy: 0.9451 - val_loss: 0.3746 - val_accuracy: 0.8716\n",
            "Epoch 5/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.2092 - accuracy: 0.9459 - val_loss: 0.3567 - val_accuracy: 0.8784\n",
            "Epoch 6/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.1737 - accuracy: 0.9645 - val_loss: 0.3194 - val_accuracy: 0.9122\n",
            "Epoch 7/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.1454 - accuracy: 0.9763 - val_loss: 0.3214 - val_accuracy: 0.9088\n",
            "Epoch 8/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.1311 - accuracy: 0.9755 - val_loss: 0.3053 - val_accuracy: 0.8986\n",
            "Epoch 9/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.1104 - accuracy: 0.9831 - val_loss: 0.3068 - val_accuracy: 0.9054\n",
            "Epoch 10/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.1045 - accuracy: 0.9814 - val_loss: 0.2862 - val_accuracy: 0.9155\n",
            "Epoch 11/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.0912 - accuracy: 0.9848 - val_loss: 0.3091 - val_accuracy: 0.9020\n",
            "Epoch 12/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.0837 - accuracy: 0.9890 - val_loss: 0.3170 - val_accuracy: 0.9122\n",
            "Epoch 13/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.0760 - accuracy: 0.9882 - val_loss: 0.3073 - val_accuracy: 0.9088\n",
            "Epoch 14/15\n",
            "37/37 [==============================] - 348s 9s/step - loss: 0.0667 - accuracy: 0.9924 - val_loss: 0.2924 - val_accuracy: 0.9122\n",
            "Epoch 15/15\n",
            "37/37 [==============================] - 347s 9s/step - loss: 0.0609 - accuracy: 0.9941 - val_loss: 0.3031 - val_accuracy: 0.9088\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wWmxAaGS0fTI"
      },
      "source": [
        "test 데이터셋으로 모델 성능 평가"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k1PhOlUkyu98",
        "outputId": "63de44bc-c06b-4927-c8fe-2b4033dd3e07"
      },
      "source": [
        "loss, accuracy = model.evaluate(x_test, y_test_lb)\n",
        "print(f\"Loss: {loss}\")\n",
        "print(f\"Accuracy: {accuracy}\")"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10/10 [==============================] - 70s 7s/step - loss: 0.3031 - accuracy: 0.9088\n",
            "Loss: 0.3031231760978699\n",
            "Accuracy: 0.9087837934494019\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j8M2BPAIzb45"
      },
      "source": [
        "y_pred = model.predict_classes(x_test)\n",
        "y_pred[:15]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n47fC_B22XMJ"
      },
      "source": [
        "savedmodel 저장"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "14QJwsee2Whq",
        "outputId": "f46bf24b-4382-4d51-d5a9-ffef1b73f3f0"
      },
      "source": [
        "!mkdir -p saved_model\n",
        "model.save('saved_model/image_sentimental_analysis_ver2')"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO:tensorflow:Assets written to: saved_model/image_sentimental_analysis_ver2/assets\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ls7Hmb5kznFJ"
      },
      "source": [
        "학습 곡선 시각화"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "we7W-s5nzgfz",
        "outputId": "3611eda5-2a9f-4465-dd6b-ba596e242562"
      },
      "source": [
        "plt.style.use(\"ggplot\")\n",
        "fig = plt.figure(figsize=(12, 6))\n",
        "epochs = range(1,16)\n",
        "\n",
        "# accuracy 값\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(epochs, history.history[\"accuracy\"], \"go-\")\n",
        "plt.plot(epochs, history.history[\"val_accuracy\"], \"ro-\")\n",
        "plt.title(\"Accuracy\")\n",
        "\n",
        "plt.xlabel(\"epochs\")\n",
        "plt.ylabel(\"accuracy\")\n",
        "\n",
        "plt.legend([\"train\", \"val\"], loc = \"upper left\")\n",
        "\n",
        "# loss 값\n",
        "plt.subplot(1,2,2)\n",
        "plt.plot(epochs,history.history[\"loss\"],\"go-\")\n",
        "plt.plot(epochs,history.history[\"val_loss\"],\"ro-\")\n",
        "plt.title(\"Model Loss\")\n",
        "\n",
        "plt.xlabel(\"Epochs\")\n",
        "plt.ylabel(\"Loss\")\n",
        "\n",
        "plt.legend([\"Train\",\"val\"],loc = \"upper left\")\n",
        "plt.show()"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x432 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}