40_image_clss.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "mount_file_id": "1JSs3cn0Q4aPFv0yQXX4tHvxRnkVZxBry",
      "authorship_tag": "ABX9TyN07LzRmSoBobla5pMiBNEa",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/krisnaarun/ImageClassification/blob/main/40_image_clss.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "k310uzQD8et7"
      },
      "outputs": [],
      "source": [
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "os.listdir('/content/drive/MyDrive/Data')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R-RLEkIE9OBQ",
        "outputId": "03404553-fdc1-478c-a411-179c88848d40"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Dog', 'Cat']"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "os.listdir('/content/drive/MyDrive/Data/Dog')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bXM8jjTJ9bc9",
        "outputId": "a26e0465-09ad-4e71-f527-2cad1ab04ccf"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['dog.15.jpg',\n",
              " 'dog.14.jpg',\n",
              " 'dog.12.jpg',\n",
              " 'dog.13.jpg',\n",
              " 'dog.19.jpg',\n",
              " 'dog.16.jpg',\n",
              " 'dog.24.jpg',\n",
              " 'dog.21.jpg',\n",
              " 'dog.18.jpg',\n",
              " 'dog.20.jpg',\n",
              " 'dog.23.jpg',\n",
              " 'dog.17.jpg',\n",
              " 'dog.22.jpg',\n",
              " 'dog.33.jpg',\n",
              " 'dog.30.jpg',\n",
              " 'dog.28.jpg',\n",
              " 'dog.31.jpg',\n",
              " 'dog.32.jpg',\n",
              " 'dog.26.jpg',\n",
              " 'dog.27.jpg',\n",
              " 'dog.25.jpg',\n",
              " 'dog.55.jpg',\n",
              " 'dog.47.jpg',\n",
              " 'dog.51.jpg',\n",
              " 'dog.38.jpg',\n",
              " 'dog.46.jpg',\n",
              " 'dog.44.jpg',\n",
              " 'dog.39.jpg',\n",
              " 'dog.40.jpg',\n",
              " 'dog.56.jpg',\n",
              " 'dog.48.jpg',\n",
              " 'dog.42.jpg',\n",
              " 'dog.60.jpg',\n",
              " 'dog.36.jpg',\n",
              " 'dog.34.jpg',\n",
              " 'dog.45.jpg',\n",
              " 'dog.58.jpg',\n",
              " 'dog.35.jpg',\n",
              " 'dog.57.jpg',\n",
              " 'dog.77.jpg',\n",
              " 'dog.64.jpg',\n",
              " 'dog.76.jpg',\n",
              " 'dog.67.jpg',\n",
              " 'dog.63.jpg',\n",
              " 'dog.78.jpg',\n",
              " 'dog.80.jpg',\n",
              " 'dog.65.jpg',\n",
              " 'dog.61.jpg',\n",
              " 'dog.68.jpg',\n",
              " 'dog.70.jpg',\n",
              " 'dog.71.jpg',\n",
              " 'dog.82.jpg',\n",
              " 'dog.81.jpg',\n",
              " 'dog.69.jpg',\n",
              " 'dog.66.jpg',\n",
              " 'dog.79.jpg',\n",
              " 'download1.jpeg',\n",
              " 'download2.jpeg',\n",
              " 'download3.jpeg',\n",
              " 'download4.jpeg',\n",
              " 'download5.jpeg',\n",
              " 'download6.jpeg',\n",
              " 'images.jpeg',\n",
              " 'images1.jpeg',\n",
              " 'download7.jpeg',\n",
              " 'download8.jpeg']"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "os.listdir('/content/drive/MyDrive/Data/Cat')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kuxm0GLZ9oZ0",
        "outputId": "35278176-b8df-4bac-8340-1498300bb7fb"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['cat.1 - Copy.jpg',\n",
              " 'cat.10.jpg',\n",
              " 'cat.11.jpg',\n",
              " 'cat.2 - Copy.jpg',\n",
              " 'cat.17.jpg',\n",
              " 'cat.12.jpg',\n",
              " 'cat.15.jpg',\n",
              " 'cat.14.jpg',\n",
              " 'cat.21.jpg',\n",
              " 'cat.20.jpg',\n",
              " 'cat.13.jpg',\n",
              " 'cat.16.jpg',\n",
              " 'cat.18.jpg',\n",
              " 'cat.27.jpg',\n",
              " 'cat.24.jpg',\n",
              " 'cat.3 - Copy.jpg',\n",
              " 'cat.28.jpg',\n",
              " 'cat.29.jpg',\n",
              " 'cat.31.jpg',\n",
              " 'cat.30.jpg',\n",
              " 'cat.33.jpg',\n",
              " 'cat.36.jpg',\n",
              " 'cat.38.jpg',\n",
              " 'cat.34.jpg',\n",
              " 'cat.39.jpg',\n",
              " 'cat.51.jpg',\n",
              " 'cat.44.jpg',\n",
              " 'cat.46.jpg',\n",
              " 'cat.50.jpg',\n",
              " 'cat.4 - Copy.jpg',\n",
              " 'cat.47.jpg',\n",
              " 'cat.37.jpg',\n",
              " 'cat.32.jpg',\n",
              " 'cat.54.jpg',\n",
              " 'cat.43.jpg',\n",
              " 'cat.42.jpg',\n",
              " 'cat.53.jpg',\n",
              " 'cat.40.jpg',\n",
              " 'cat.48.jpg',\n",
              " 'cat.5.jpg',\n",
              " 'cat.52.jpg',\n",
              " 'cat.35.jpg',\n",
              " 'cat.49.jpg',\n",
              " 'cat.41.jpg',\n",
              " 'cat.5 - Copy.jpg',\n",
              " 'cat.9.jpg',\n",
              " 'cat.8.jpg',\n",
              " 'cat.7.jpg',\n",
              " 'download.jpeg',\n",
              " 'download1.jpeg',\n",
              " 'download2.jpeg',\n",
              " 'download3.jpeg',\n",
              " 'download4.jpeg',\n",
              " 'download5.jpeg',\n",
              " 'download6.jpeg',\n",
              " 'download7.jpeg',\n",
              " 'download8.jpeg',\n",
              " 'images9.jpeg',\n",
              " 'images.jpeg',\n",
              " 'downloadcat.jpeg']"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(os.listdir('/content/drive/MyDrive/Data/Dog'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4845KWAD9yCX",
        "outputId": "909c5feb-910c-4349-d1e6-6ce6589930b7"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "66"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(os.listdir('/content/drive/MyDrive/Data/Cat'))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZiK0ZFXz-eg9",
        "outputId": "adb2ea85-a856-4f0e-96ac-73da797f8464"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "60"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "datadir='/content/drive/MyDrive/Data'\n",
        "dogpath=os.path.join(datadir,'Dog')\n",
        "dogpath"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "IT1aqeFv-y_N",
        "outputId": "08d2c60e-1cc4-44ef-cb13-002f93909ef9"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/drive/MyDrive/Data/Dog'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "os.listdir(dogpath)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EYi0cT_F_HK7",
        "outputId": "684317d1-92dd-4e92-fff7-ddb9213ad599"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['dog.15.jpg',\n",
              " 'dog.14.jpg',\n",
              " 'dog.12.jpg',\n",
              " 'dog.13.jpg',\n",
              " 'dog.19.jpg',\n",
              " 'dog.16.jpg',\n",
              " 'dog.24.jpg',\n",
              " 'dog.21.jpg',\n",
              " 'dog.18.jpg',\n",
              " 'dog.20.jpg',\n",
              " 'dog.23.jpg',\n",
              " 'dog.17.jpg',\n",
              " 'dog.22.jpg',\n",
              " 'dog.33.jpg',\n",
              " 'dog.30.jpg',\n",
              " 'dog.28.jpg',\n",
              " 'dog.31.jpg',\n",
              " 'dog.32.jpg',\n",
              " 'dog.26.jpg',\n",
              " 'dog.27.jpg',\n",
              " 'dog.25.jpg',\n",
              " 'dog.55.jpg',\n",
              " 'dog.47.jpg',\n",
              " 'dog.51.jpg',\n",
              " 'dog.38.jpg',\n",
              " 'dog.46.jpg',\n",
              " 'dog.44.jpg',\n",
              " 'dog.39.jpg',\n",
              " 'dog.40.jpg',\n",
              " 'dog.56.jpg',\n",
              " 'dog.48.jpg',\n",
              " 'dog.42.jpg',\n",
              " 'dog.60.jpg',\n",
              " 'dog.36.jpg',\n",
              " 'dog.34.jpg',\n",
              " 'dog.45.jpg',\n",
              " 'dog.58.jpg',\n",
              " 'dog.35.jpg',\n",
              " 'dog.57.jpg',\n",
              " 'dog.77.jpg',\n",
              " 'dog.64.jpg',\n",
              " 'dog.76.jpg',\n",
              " 'dog.67.jpg',\n",
              " 'dog.63.jpg',\n",
              " 'dog.78.jpg',\n",
              " 'dog.80.jpg',\n",
              " 'dog.65.jpg',\n",
              " 'dog.61.jpg',\n",
              " 'dog.68.jpg',\n",
              " 'dog.70.jpg',\n",
              " 'dog.71.jpg',\n",
              " 'dog.82.jpg',\n",
              " 'dog.81.jpg',\n",
              " 'dog.69.jpg',\n",
              " 'dog.66.jpg',\n",
              " 'dog.79.jpg',\n",
              " 'download1.jpeg',\n",
              " 'download2.jpeg',\n",
              " 'download3.jpeg',\n",
              " 'download4.jpeg',\n",
              " 'download5.jpeg',\n",
              " 'download6.jpeg',\n",
              " 'images.jpeg',\n",
              " 'images1.jpeg',\n",
              " 'download7.jpeg',\n",
              " 'download8.jpeg']"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "catpath=os.path.join(datadir,'Cat')\n",
        "catpath"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "pVMPlE9q_19C",
        "outputId": "ce4d086e-6d28-4e7f-91a2-bd96011451d1"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content/drive/MyDrive/Data/Cat'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "datadir='/content/drive/MyDrive/Data'"
      ],
      "metadata": {
        "id": "SkSdGTrlADTw"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in os.listdir(datadir):\n",
        "   spath=os.path.join(datadir,i)\n",
        "   print(os.listdir(spath))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vrYw7VVgALxm",
        "outputId": "dd5b1cf0-bcba-48e5-91fa-07633a7cc96e"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['dog.15.jpg', 'dog.14.jpg', 'dog.12.jpg', 'dog.13.jpg', 'dog.19.jpg', 'dog.16.jpg', 'dog.24.jpg', 'dog.21.jpg', 'dog.18.jpg', 'dog.20.jpg', 'dog.23.jpg', 'dog.17.jpg', 'dog.22.jpg', 'dog.33.jpg', 'dog.30.jpg', 'dog.28.jpg', 'dog.31.jpg', 'dog.32.jpg', 'dog.26.jpg', 'dog.27.jpg', 'dog.25.jpg', 'dog.55.jpg', 'dog.47.jpg', 'dog.51.jpg', 'dog.38.jpg', 'dog.46.jpg', 'dog.44.jpg', 'dog.39.jpg', 'dog.40.jpg', 'dog.56.jpg', 'dog.48.jpg', 'dog.42.jpg', 'dog.60.jpg', 'dog.36.jpg', 'dog.34.jpg', 'dog.45.jpg', 'dog.58.jpg', 'dog.35.jpg', 'dog.57.jpg', 'dog.77.jpg', 'dog.64.jpg', 'dog.76.jpg', 'dog.67.jpg', 'dog.63.jpg', 'dog.78.jpg', 'dog.80.jpg', 'dog.65.jpg', 'dog.61.jpg', 'dog.68.jpg', 'dog.70.jpg', 'dog.71.jpg', 'dog.82.jpg', 'dog.81.jpg', 'dog.69.jpg', 'dog.66.jpg', 'dog.79.jpg', 'download1.jpeg', 'download2.jpeg', 'download3.jpeg', 'download4.jpeg', 'download5.jpeg', 'download6.jpeg', 'images.jpeg', 'images1.jpeg', 'download7.jpeg', 'download8.jpeg']\n",
            "['cat.1 - Copy.jpg', 'cat.10.jpg', 'cat.11.jpg', 'cat.2 - Copy.jpg', 'cat.17.jpg', 'cat.12.jpg', 'cat.15.jpg', 'cat.14.jpg', 'cat.21.jpg', 'cat.20.jpg', 'cat.13.jpg', 'cat.16.jpg', 'cat.18.jpg', 'cat.27.jpg', 'cat.24.jpg', 'cat.3 - Copy.jpg', 'cat.28.jpg', 'cat.29.jpg', 'cat.31.jpg', 'cat.30.jpg', 'cat.33.jpg', 'cat.36.jpg', 'cat.38.jpg', 'cat.34.jpg', 'cat.39.jpg', 'cat.51.jpg', 'cat.44.jpg', 'cat.46.jpg', 'cat.50.jpg', 'cat.4 - Copy.jpg', 'cat.47.jpg', 'cat.37.jpg', 'cat.32.jpg', 'cat.54.jpg', 'cat.43.jpg', 'cat.42.jpg', 'cat.53.jpg', 'cat.40.jpg', 'cat.48.jpg', 'cat.5.jpg', 'cat.52.jpg', 'cat.35.jpg', 'cat.49.jpg', 'cat.41.jpg', 'cat.5 - Copy.jpg', 'cat.9.jpg', 'cat.8.jpg', 'cat.7.jpg', 'download.jpeg', 'download1.jpeg', 'download2.jpeg', 'download3.jpeg', 'download4.jpeg', 'download5.jpeg', 'download6.jpeg', 'download7.jpeg', 'download8.jpeg', 'images9.jpeg', 'images.jpeg', 'downloadcat.jpeg']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in os.listdir(datadir):\n",
        "   spath=os.path.join(datadir,i)\n",
        "   for j in os.listdir(spath):\n",
        "      npath=os.path.join(spath,j)\n",
        "      print(npath)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lRmhWbtWBaJs",
        "outputId": "38fec75d-9aee-420c-9615-44bca7741287"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/Data/Dog/dog.15.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.14.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.12.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.13.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.19.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.16.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.24.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.21.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.18.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.20.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.23.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.17.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.22.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.33.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.30.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.28.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.31.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.32.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.26.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.27.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.25.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.55.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.47.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.51.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.38.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.46.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.44.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.39.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.40.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.56.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.48.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.42.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.60.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.36.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.34.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.45.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.58.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.35.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.57.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.77.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.64.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.76.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.67.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.63.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.78.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.80.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.65.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.61.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.68.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.70.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.71.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.82.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.81.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.69.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.66.jpg\n",
            "/content/drive/MyDrive/Data/Dog/dog.79.jpg\n",
            "/content/drive/MyDrive/Data/Dog/download1.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download2.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download3.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download4.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download5.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download6.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/images.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/images1.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download7.jpeg\n",
            "/content/drive/MyDrive/Data/Dog/download8.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/cat.1 - Copy.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.10.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.11.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.2 - Copy.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.17.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.12.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.15.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.14.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.21.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.20.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.13.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.16.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.18.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.27.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.24.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.3 - Copy.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.28.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.29.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.31.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.30.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.33.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.36.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.38.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.34.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.39.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.51.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.44.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.46.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.50.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.4 - Copy.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.47.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.37.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.32.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.54.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.43.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.42.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.53.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.40.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.48.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.5.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.52.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.35.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.49.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.41.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.5 - Copy.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.9.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.8.jpg\n",
            "/content/drive/MyDrive/Data/Cat/cat.7.jpg\n",
            "/content/drive/MyDrive/Data/Cat/download.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download1.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download2.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download3.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download4.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download5.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download6.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download7.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/download8.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/images9.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/images.jpeg\n",
            "/content/drive/MyDrive/Data/Cat/downloadcat.jpeg\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from skimage.transform import resize\n",
        "from skimage.io import imread\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report,ConfusionMatrixDisplay"
      ],
      "metadata": {
        "id": "CChUjWFE8Exb"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "3YCK5o-o6_6P"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data_array=[]\n",
        "target_array=[]\n",
        "Categories=['Cat','Dog']\n",
        "datadir='/content/drive/MyDrive/Data'\n",
        "for i in Categories:\n",
        "  sub_path=os.path.join(datadir,i)\n",
        "  images=os.listdir(sub_path)\n",
        "  for j in images:\n",
        "    img_path=os.path.join(sub_path,j)\n",
        "    img_array=imread(img_path)\n",
        "    img_resized=resize(img_array,(150,150,3))\n",
        "    data_array.append(img_resized.flatten())\n",
        "    target_array.append(Categories.index(i))\n",
        "  print('loaded category:',i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zj97ch7-9-a5",
        "outputId": "dc6a80fe-ff27-494a-cb28-73b69f95f0bb"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "loaded category: Cat\n",
            "loaded category: Dog\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data=np.array(data_array)\n",
        "data.shape            #150*150*3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "It2EV-vrDpvb",
        "outputId": "bc1f0e98-3528-474a-fe8f-95e69d3654e3"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(126, 67500)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target=np.array(target_array)\n",
        "target.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3SPVEkwzGkJ8",
        "outputId": "198883e5-e53d-44af-e48d-8af0a69283cb"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(126,)"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.DataFrame(data)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "KVtg0zfkFaHx",
        "outputId": "08d37463-12c0-40ac-f2f7-7828c2853439"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        0         1         2         3         4         5         6      \\\n",
              "0    0.154919  0.174317  0.159262  0.158661  0.174557  0.174348  0.160470   \n",
              "1    0.112229  0.128222  0.163382  0.068747  0.084740  0.125080  0.088116   \n",
              "2    0.890555  0.917245  0.909245  0.909860  0.948941  0.944676  0.925683   \n",
              "3    0.258697  0.202976  0.211065  0.224392  0.171795  0.183491  0.200546   \n",
              "4    0.102460  0.102460  0.102460  0.109354  0.109354  0.109354  0.106019   \n",
              "..        ...       ...       ...       ...       ...       ...       ...   \n",
              "121  0.540430  0.592002  0.587192  0.536907  0.582837  0.564881  0.473051   \n",
              "122  0.525404  0.515404  0.385404  0.541982  0.531982  0.401980  0.549706   \n",
              "123  0.180388  0.305878  0.211760  0.179468  0.304958  0.210840  0.176474   \n",
              "124  0.265494  0.194915  0.165522  0.289091  0.236930  0.201553  0.297122   \n",
              "125  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
              "\n",
              "        7         8         9      ...     67490     67491     67492  \\\n",
              "0    0.174195  0.189462  0.162110  ...  0.224704  0.197318  0.138913   \n",
              "1    0.103733  0.150911  0.149698  ...  0.008552  0.756716  0.752803   \n",
              "2    0.980147  0.980362  0.749868  ...  0.947478  0.774726  0.836644   \n",
              "3    0.154476  0.171791  0.216943  ...  0.231418  0.141433  0.087680   \n",
              "4    0.106019  0.106019  0.113694  ...  0.211287  0.318348  0.331493   \n",
              "..        ...       ...       ...  ...       ...       ...       ...   \n",
              "121  0.511448  0.474642  0.414647  ...  0.187970  0.070573  0.083511   \n",
              "122  0.539706  0.408779  0.541766  ...  0.327961  0.547997  0.553535   \n",
              "123  0.301964  0.207846  0.174089  ...  0.170797  0.407024  0.567886   \n",
              "124  0.270173  0.230698  0.270863  ...  0.152773  0.311343  0.311343   \n",
              "125  1.000000  1.000000  1.000000  ...  1.000000  1.000000  1.000000   \n",
              "\n",
              "        67493     67494     67495     67496     67497     67498     67499  \n",
              "0    0.111461  0.190055  0.138656  0.107701  0.180396  0.134622  0.101754  \n",
              "1    0.014710  0.728919  0.718809  0.021388  0.675097  0.656312  0.013387  \n",
              "2    0.941021  0.761761  0.824506  0.923488  0.784133  0.846879  0.942937  \n",
              "3    0.141854  0.313445  0.264257  0.285725  0.778475  0.734729  0.725754  \n",
              "4    0.318138  0.265920  0.293626  0.276704  0.363970  0.375376  0.367386  \n",
              "..        ...       ...       ...       ...       ...       ...       ...  \n",
              "121  0.048696  0.227812  0.231461  0.175383  0.065175  0.065175  0.027635  \n",
              "122  0.311182  0.547216  0.562070  0.275076  0.673287  0.665615  0.441600  \n",
              "123  0.167792  0.393432  0.571711  0.150718  0.392157  0.572549  0.149020  \n",
              "124  0.115264  0.383767  0.383767  0.187688  0.405936  0.405936  0.209857  \n",
              "125  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  \n",
              "\n",
              "[126 rows x 67500 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fc6b38a7-dee3-4dc8-95f2-b8fed2f2766a\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>...</th>\n",
              "      <th>67490</th>\n",
              "      <th>67491</th>\n",
              "      <th>67492</th>\n",
              "      <th>67493</th>\n",
              "      <th>67494</th>\n",
              "      <th>67495</th>\n",
              "      <th>67496</th>\n",
              "      <th>67497</th>\n",
              "      <th>67498</th>\n",
              "      <th>67499</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.154919</td>\n",
              "      <td>0.174317</td>\n",
              "      <td>0.159262</td>\n",
              "      <td>0.158661</td>\n",
              "      <td>0.174557</td>\n",
              "      <td>0.174348</td>\n",
              "      <td>0.160470</td>\n",
              "      <td>0.174195</td>\n",
              "      <td>0.189462</td>\n",
              "      <td>0.162110</td>\n",
              "      <td>...</td>\n",
              "      <td>0.224704</td>\n",
              "      <td>0.197318</td>\n",
              "      <td>0.138913</td>\n",
              "      <td>0.111461</td>\n",
              "      <td>0.190055</td>\n",
              "      <td>0.138656</td>\n",
              "      <td>0.107701</td>\n",
              "      <td>0.180396</td>\n",
              "      <td>0.134622</td>\n",
              "      <td>0.101754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.112229</td>\n",
              "      <td>0.128222</td>\n",
              "      <td>0.163382</td>\n",
              "      <td>0.068747</td>\n",
              "      <td>0.084740</td>\n",
              "      <td>0.125080</td>\n",
              "      <td>0.088116</td>\n",
              "      <td>0.103733</td>\n",
              "      <td>0.150911</td>\n",
              "      <td>0.149698</td>\n",
              "      <td>...</td>\n",
              "      <td>0.008552</td>\n",
              "      <td>0.756716</td>\n",
              "      <td>0.752803</td>\n",
              "      <td>0.014710</td>\n",
              "      <td>0.728919</td>\n",
              "      <td>0.718809</td>\n",
              "      <td>0.021388</td>\n",
              "      <td>0.675097</td>\n",
              "      <td>0.656312</td>\n",
              "      <td>0.013387</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.890555</td>\n",
              "      <td>0.917245</td>\n",
              "      <td>0.909245</td>\n",
              "      <td>0.909860</td>\n",
              "      <td>0.948941</td>\n",
              "      <td>0.944676</td>\n",
              "      <td>0.925683</td>\n",
              "      <td>0.980147</td>\n",
              "      <td>0.980362</td>\n",
              "      <td>0.749868</td>\n",
              "      <td>...</td>\n",
              "      <td>0.947478</td>\n",
              "      <td>0.774726</td>\n",
              "      <td>0.836644</td>\n",
              "      <td>0.941021</td>\n",
              "      <td>0.761761</td>\n",
              "      <td>0.824506</td>\n",
              "      <td>0.923488</td>\n",
              "      <td>0.784133</td>\n",
              "      <td>0.846879</td>\n",
              "      <td>0.942937</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.258697</td>\n",
              "      <td>0.202976</td>\n",
              "      <td>0.211065</td>\n",
              "      <td>0.224392</td>\n",
              "      <td>0.171795</td>\n",
              "      <td>0.183491</td>\n",
              "      <td>0.200546</td>\n",
              "      <td>0.154476</td>\n",
              "      <td>0.171791</td>\n",
              "      <td>0.216943</td>\n",
              "      <td>...</td>\n",
              "      <td>0.231418</td>\n",
              "      <td>0.141433</td>\n",
              "      <td>0.087680</td>\n",
              "      <td>0.141854</td>\n",
              "      <td>0.313445</td>\n",
              "      <td>0.264257</td>\n",
              "      <td>0.285725</td>\n",
              "      <td>0.778475</td>\n",
              "      <td>0.734729</td>\n",
              "      <td>0.725754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.113694</td>\n",
              "      <td>...</td>\n",
              "      <td>0.211287</td>\n",
              "      <td>0.318348</td>\n",
              "      <td>0.331493</td>\n",
              "      <td>0.318138</td>\n",
              "      <td>0.265920</td>\n",
              "      <td>0.293626</td>\n",
              "      <td>0.276704</td>\n",
              "      <td>0.363970</td>\n",
              "      <td>0.375376</td>\n",
              "      <td>0.367386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>0.540430</td>\n",
              "      <td>0.592002</td>\n",
              "      <td>0.587192</td>\n",
              "      <td>0.536907</td>\n",
              "      <td>0.582837</td>\n",
              "      <td>0.564881</td>\n",
              "      <td>0.473051</td>\n",
              "      <td>0.511448</td>\n",
              "      <td>0.474642</td>\n",
              "      <td>0.414647</td>\n",
              "      <td>...</td>\n",
              "      <td>0.187970</td>\n",
              "      <td>0.070573</td>\n",
              "      <td>0.083511</td>\n",
              "      <td>0.048696</td>\n",
              "      <td>0.227812</td>\n",
              "      <td>0.231461</td>\n",
              "      <td>0.175383</td>\n",
              "      <td>0.065175</td>\n",
              "      <td>0.065175</td>\n",
              "      <td>0.027635</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>122</th>\n",
              "      <td>0.525404</td>\n",
              "      <td>0.515404</td>\n",
              "      <td>0.385404</td>\n",
              "      <td>0.541982</td>\n",
              "      <td>0.531982</td>\n",
              "      <td>0.401980</td>\n",
              "      <td>0.549706</td>\n",
              "      <td>0.539706</td>\n",
              "      <td>0.408779</td>\n",
              "      <td>0.541766</td>\n",
              "      <td>...</td>\n",
              "      <td>0.327961</td>\n",
              "      <td>0.547997</td>\n",
              "      <td>0.553535</td>\n",
              "      <td>0.311182</td>\n",
              "      <td>0.547216</td>\n",
              "      <td>0.562070</td>\n",
              "      <td>0.275076</td>\n",
              "      <td>0.673287</td>\n",
              "      <td>0.665615</td>\n",
              "      <td>0.441600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>0.180388</td>\n",
              "      <td>0.305878</td>\n",
              "      <td>0.211760</td>\n",
              "      <td>0.179468</td>\n",
              "      <td>0.304958</td>\n",
              "      <td>0.210840</td>\n",
              "      <td>0.176474</td>\n",
              "      <td>0.301964</td>\n",
              "      <td>0.207846</td>\n",
              "      <td>0.174089</td>\n",
              "      <td>...</td>\n",
              "      <td>0.170797</td>\n",
              "      <td>0.407024</td>\n",
              "      <td>0.567886</td>\n",
              "      <td>0.167792</td>\n",
              "      <td>0.393432</td>\n",
              "      <td>0.571711</td>\n",
              "      <td>0.150718</td>\n",
              "      <td>0.392157</td>\n",
              "      <td>0.572549</td>\n",
              "      <td>0.149020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>0.265494</td>\n",
              "      <td>0.194915</td>\n",
              "      <td>0.165522</td>\n",
              "      <td>0.289091</td>\n",
              "      <td>0.236930</td>\n",
              "      <td>0.201553</td>\n",
              "      <td>0.297122</td>\n",
              "      <td>0.270173</td>\n",
              "      <td>0.230698</td>\n",
              "      <td>0.270863</td>\n",
              "      <td>...</td>\n",
              "      <td>0.152773</td>\n",
              "      <td>0.311343</td>\n",
              "      <td>0.311343</td>\n",
              "      <td>0.115264</td>\n",
              "      <td>0.383767</td>\n",
              "      <td>0.383767</td>\n",
              "      <td>0.187688</td>\n",
              "      <td>0.405936</td>\n",
              "      <td>0.405936</td>\n",
              "      <td>0.209857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>126 rows × 67500 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fc6b38a7-dee3-4dc8-95f2-b8fed2f2766a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fc6b38a7-dee3-4dc8-95f2-b8fed2f2766a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fc6b38a7-dee3-4dc8-95f2-b8fed2f2766a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['target']=target\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "Urck31DOFmZe",
        "outputId": "81804583-3497-4a84-a59a-f50177fe6cca"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            0         1         2         3         4         5         6  \\\n",
              "0    0.154919  0.174317  0.159262  0.158661  0.174557  0.174348  0.160470   \n",
              "1    0.112229  0.128222  0.163382  0.068747  0.084740  0.125080  0.088116   \n",
              "2    0.890555  0.917245  0.909245  0.909860  0.948941  0.944676  0.925683   \n",
              "3    0.258697  0.202976  0.211065  0.224392  0.171795  0.183491  0.200546   \n",
              "4    0.102460  0.102460  0.102460  0.109354  0.109354  0.109354  0.106019   \n",
              "..        ...       ...       ...       ...       ...       ...       ...   \n",
              "121  0.540430  0.592002  0.587192  0.536907  0.582837  0.564881  0.473051   \n",
              "122  0.525404  0.515404  0.385404  0.541982  0.531982  0.401980  0.549706   \n",
              "123  0.180388  0.305878  0.211760  0.179468  0.304958  0.210840  0.176474   \n",
              "124  0.265494  0.194915  0.165522  0.289091  0.236930  0.201553  0.297122   \n",
              "125  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
              "\n",
              "            7         8         9  ...     67491     67492     67493  \\\n",
              "0    0.174195  0.189462  0.162110  ...  0.197318  0.138913  0.111461   \n",
              "1    0.103733  0.150911  0.149698  ...  0.756716  0.752803  0.014710   \n",
              "2    0.980147  0.980362  0.749868  ...  0.774726  0.836644  0.941021   \n",
              "3    0.154476  0.171791  0.216943  ...  0.141433  0.087680  0.141854   \n",
              "4    0.106019  0.106019  0.113694  ...  0.318348  0.331493  0.318138   \n",
              "..        ...       ...       ...  ...       ...       ...       ...   \n",
              "121  0.511448  0.474642  0.414647  ...  0.070573  0.083511  0.048696   \n",
              "122  0.539706  0.408779  0.541766  ...  0.547997  0.553535  0.311182   \n",
              "123  0.301964  0.207846  0.174089  ...  0.407024  0.567886  0.167792   \n",
              "124  0.270173  0.230698  0.270863  ...  0.311343  0.311343  0.115264   \n",
              "125  1.000000  1.000000  1.000000  ...  1.000000  1.000000  1.000000   \n",
              "\n",
              "        67494     67495     67496     67497     67498     67499  target  \n",
              "0    0.190055  0.138656  0.107701  0.180396  0.134622  0.101754       0  \n",
              "1    0.728919  0.718809  0.021388  0.675097  0.656312  0.013387       0  \n",
              "2    0.761761  0.824506  0.923488  0.784133  0.846879  0.942937       0  \n",
              "3    0.313445  0.264257  0.285725  0.778475  0.734729  0.725754       0  \n",
              "4    0.265920  0.293626  0.276704  0.363970  0.375376  0.367386       0  \n",
              "..        ...       ...       ...       ...       ...       ...     ...  \n",
              "121  0.227812  0.231461  0.175383  0.065175  0.065175  0.027635       1  \n",
              "122  0.547216  0.562070  0.275076  0.673287  0.665615  0.441600       1  \n",
              "123  0.393432  0.571711  0.150718  0.392157  0.572549  0.149020       1  \n",
              "124  0.383767  0.383767  0.187688  0.405936  0.405936  0.209857       1  \n",
              "125  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000       1  \n",
              "\n",
              "[126 rows x 67501 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-dce2422b-ba25-4061-bfd2-7e64d4f0cc48\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>...</th>\n",
              "      <th>67491</th>\n",
              "      <th>67492</th>\n",
              "      <th>67493</th>\n",
              "      <th>67494</th>\n",
              "      <th>67495</th>\n",
              "      <th>67496</th>\n",
              "      <th>67497</th>\n",
              "      <th>67498</th>\n",
              "      <th>67499</th>\n",
              "      <th>target</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.154919</td>\n",
              "      <td>0.174317</td>\n",
              "      <td>0.159262</td>\n",
              "      <td>0.158661</td>\n",
              "      <td>0.174557</td>\n",
              "      <td>0.174348</td>\n",
              "      <td>0.160470</td>\n",
              "      <td>0.174195</td>\n",
              "      <td>0.189462</td>\n",
              "      <td>0.162110</td>\n",
              "      <td>...</td>\n",
              "      <td>0.197318</td>\n",
              "      <td>0.138913</td>\n",
              "      <td>0.111461</td>\n",
              "      <td>0.190055</td>\n",
              "      <td>0.138656</td>\n",
              "      <td>0.107701</td>\n",
              "      <td>0.180396</td>\n",
              "      <td>0.134622</td>\n",
              "      <td>0.101754</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.112229</td>\n",
              "      <td>0.128222</td>\n",
              "      <td>0.163382</td>\n",
              "      <td>0.068747</td>\n",
              "      <td>0.084740</td>\n",
              "      <td>0.125080</td>\n",
              "      <td>0.088116</td>\n",
              "      <td>0.103733</td>\n",
              "      <td>0.150911</td>\n",
              "      <td>0.149698</td>\n",
              "      <td>...</td>\n",
              "      <td>0.756716</td>\n",
              "      <td>0.752803</td>\n",
              "      <td>0.014710</td>\n",
              "      <td>0.728919</td>\n",
              "      <td>0.718809</td>\n",
              "      <td>0.021388</td>\n",
              "      <td>0.675097</td>\n",
              "      <td>0.656312</td>\n",
              "      <td>0.013387</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.890555</td>\n",
              "      <td>0.917245</td>\n",
              "      <td>0.909245</td>\n",
              "      <td>0.909860</td>\n",
              "      <td>0.948941</td>\n",
              "      <td>0.944676</td>\n",
              "      <td>0.925683</td>\n",
              "      <td>0.980147</td>\n",
              "      <td>0.980362</td>\n",
              "      <td>0.749868</td>\n",
              "      <td>...</td>\n",
              "      <td>0.774726</td>\n",
              "      <td>0.836644</td>\n",
              "      <td>0.941021</td>\n",
              "      <td>0.761761</td>\n",
              "      <td>0.824506</td>\n",
              "      <td>0.923488</td>\n",
              "      <td>0.784133</td>\n",
              "      <td>0.846879</td>\n",
              "      <td>0.942937</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.258697</td>\n",
              "      <td>0.202976</td>\n",
              "      <td>0.211065</td>\n",
              "      <td>0.224392</td>\n",
              "      <td>0.171795</td>\n",
              "      <td>0.183491</td>\n",
              "      <td>0.200546</td>\n",
              "      <td>0.154476</td>\n",
              "      <td>0.171791</td>\n",
              "      <td>0.216943</td>\n",
              "      <td>...</td>\n",
              "      <td>0.141433</td>\n",
              "      <td>0.087680</td>\n",
              "      <td>0.141854</td>\n",
              "      <td>0.313445</td>\n",
              "      <td>0.264257</td>\n",
              "      <td>0.285725</td>\n",
              "      <td>0.778475</td>\n",
              "      <td>0.734729</td>\n",
              "      <td>0.725754</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.102460</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.109354</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.106019</td>\n",
              "      <td>0.113694</td>\n",
              "      <td>...</td>\n",
              "      <td>0.318348</td>\n",
              "      <td>0.331493</td>\n",
              "      <td>0.318138</td>\n",
              "      <td>0.265920</td>\n",
              "      <td>0.293626</td>\n",
              "      <td>0.276704</td>\n",
              "      <td>0.363970</td>\n",
              "      <td>0.375376</td>\n",
              "      <td>0.367386</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>0.540430</td>\n",
              "      <td>0.592002</td>\n",
              "      <td>0.587192</td>\n",
              "      <td>0.536907</td>\n",
              "      <td>0.582837</td>\n",
              "      <td>0.564881</td>\n",
              "      <td>0.473051</td>\n",
              "      <td>0.511448</td>\n",
              "      <td>0.474642</td>\n",
              "      <td>0.414647</td>\n",
              "      <td>...</td>\n",
              "      <td>0.070573</td>\n",
              "      <td>0.083511</td>\n",
              "      <td>0.048696</td>\n",
              "      <td>0.227812</td>\n",
              "      <td>0.231461</td>\n",
              "      <td>0.175383</td>\n",
              "      <td>0.065175</td>\n",
              "      <td>0.065175</td>\n",
              "      <td>0.027635</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>122</th>\n",
              "      <td>0.525404</td>\n",
              "      <td>0.515404</td>\n",
              "      <td>0.385404</td>\n",
              "      <td>0.541982</td>\n",
              "      <td>0.531982</td>\n",
              "      <td>0.401980</td>\n",
              "      <td>0.549706</td>\n",
              "      <td>0.539706</td>\n",
              "      <td>0.408779</td>\n",
              "      <td>0.541766</td>\n",
              "      <td>...</td>\n",
              "      <td>0.547997</td>\n",
              "      <td>0.553535</td>\n",
              "      <td>0.311182</td>\n",
              "      <td>0.547216</td>\n",
              "      <td>0.562070</td>\n",
              "      <td>0.275076</td>\n",
              "      <td>0.673287</td>\n",
              "      <td>0.665615</td>\n",
              "      <td>0.441600</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>123</th>\n",
              "      <td>0.180388</td>\n",
              "      <td>0.305878</td>\n",
              "      <td>0.211760</td>\n",
              "      <td>0.179468</td>\n",
              "      <td>0.304958</td>\n",
              "      <td>0.210840</td>\n",
              "      <td>0.176474</td>\n",
              "      <td>0.301964</td>\n",
              "      <td>0.207846</td>\n",
              "      <td>0.174089</td>\n",
              "      <td>...</td>\n",
              "      <td>0.407024</td>\n",
              "      <td>0.567886</td>\n",
              "      <td>0.167792</td>\n",
              "      <td>0.393432</td>\n",
              "      <td>0.571711</td>\n",
              "      <td>0.150718</td>\n",
              "      <td>0.392157</td>\n",
              "      <td>0.572549</td>\n",
              "      <td>0.149020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>0.265494</td>\n",
              "      <td>0.194915</td>\n",
              "      <td>0.165522</td>\n",
              "      <td>0.289091</td>\n",
              "      <td>0.236930</td>\n",
              "      <td>0.201553</td>\n",
              "      <td>0.297122</td>\n",
              "      <td>0.270173</td>\n",
              "      <td>0.230698</td>\n",
              "      <td>0.270863</td>\n",
              "      <td>...</td>\n",
              "      <td>0.311343</td>\n",
              "      <td>0.311343</td>\n",
              "      <td>0.115264</td>\n",
              "      <td>0.383767</td>\n",
              "      <td>0.383767</td>\n",
              "      <td>0.187688</td>\n",
              "      <td>0.405936</td>\n",
              "      <td>0.405936</td>\n",
              "      <td>0.209857</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>125</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>126 rows × 67501 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dce2422b-ba25-4061-bfd2-7e64d4f0cc48')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-dce2422b-ba25-4061-bfd2-7e64d4f0cc48 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-dce2422b-ba25-4061-bfd2-7e64d4f0cc48');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X=df.iloc[:,:-1]\n",
        "y=df.iloc[:,-1]"
      ],
      "metadata": {
        "id": "SuKJvvfkHGLV"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=1)\n"
      ],
      "metadata": {
        "id": "uKXVIQTfHQH2"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sv=SVC(kernel='poly')\n",
        "sv.fit(X_train,y_train)\n",
        "y_pred=sv.predict(X_test)\n",
        "y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2L7evGkpHpcJ",
        "outputId": "ea91b40a-c337-43f5-ff1d-25db99893d27"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0,\n",
              "       1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1])"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(classification_report(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HFYR5yfDIB_W",
        "outputId": "54ea028a-bc26-4bc1-d357-ec11645f31df"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.53      0.67      0.59        15\n",
            "           1       0.74      0.61      0.67        23\n",
            "\n",
            "    accuracy                           0.63        38\n",
            "   macro avg       0.63      0.64      0.63        38\n",
            "weighted avg       0.65      0.63      0.64        38\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(ConfusionMatrixDisplay.from_predictions(y_test,y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "TWGZ5x8OIUHu",
        "outputId": "afb4545d-6931-4c72-a0ac-d4f5e4b35848"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay object at 0x7efcc33ec400>\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newc=imread('/content/drive/MyDrive/cat.jpg')\n",
        "plt.imshow(newc)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "vzYRljQGJPzn",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 434
        },
        "outputId": "b07bf01a-9d4c-491c-fece-6cdf1d281330"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newc=resize(newc,(150,150,3))\n",
        "newimg=newc.flatten()\n",
        "newimg.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VXg85TznL5Vn",
        "outputId": "c04add15-0153-46d1-9fc8-75eed8eb9abc"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(67500,)"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newimg=newimg.reshape(1,-1)\n",
        "newimg.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kjcMuwJpMZ4n",
        "outputId": "cab360da-fe08-427a-c278-786bbb21b427"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 67500)"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=sv.predict(newimg)\n",
        "if y==0:\n",
        "  print('cat')\n",
        "else:\n",
        "  print('dog')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O45iCdAiM4nq",
        "outputId": "fcb86cf6-ef15-4c64-cd46-fda845db22fc"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "dog\n"
          ]
        }
      ]
    }
  ]
}