Lesion_Exploratory_Analysis.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Lesion-Exploratory-Analysis.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNcgdN5m0oX5Dfqe9sd0etH",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/akibkhan1/skin-lesion-classification/blob/main/Lesion_Exploratory_Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gv1DoealQR2z"
      },
      "source": [
        "Import libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FFSQKfcY_9dw"
      },
      "source": [
        "import numpy as np\n",
        "import os\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import cv2\n",
        "from IPython.display import clear_output\n",
        "from google.colab.patches import cv2_imshow\n",
        "import seaborn as sns"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "avIKC46tQaiB"
      },
      "source": [
        "Download dataset and labels"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V3bBxVnOOnqe"
      },
      "source": [
        "!gdown --id 1YkYnPgkRLDIQAbrnP81z8S1rDtEBEguj\n",
        "\n",
        "!unzip lesion-full.zip; rm lesion-full.zip;\n",
        "clear_output()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "80ySmon7APIg",
        "outputId": "e4a66ff8-7930-4287-bd75-d0605f0eff19"
      },
      "source": [
        "!gdown --id 1IJW5WfPmBS8G5Nt3EF-VlPwd2yQgxZ_W\n",
        "\n",
        "!gdown --id 1XrieFe-vJFfcg1-NGUrtvz63QTiukiTi"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1XrieFe-vJFfcg1-NGUrtvz63QTiukiTi\n",
            "To: /content/path_label.csv\n",
            "\r  0% 0.00/56.9k [00:00<?, ?B/s]\r100% 56.9k/56.9k [00:00<00:00, 3.81MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1bUBTFq7RJp5"
      },
      "source": [
        "Exploring class frequency"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "MvFvNM6SAUAJ",
        "outputId": "ff3d0a3f-cf5e-4397-fd8f-84f7eaabd8a0"
      },
      "source": [
        "metadata=pd.read_csv('path_label.csv')\n",
        "\n",
        "metadata.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>img_id</th>\n",
              "      <th>diagnostic</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>PAT_1516_1765_530.png</td>\n",
              "      <td>NEV</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>PAT_46_881_939.png</td>\n",
              "      <td>BCC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>PAT_1545_1867_547.png</td>\n",
              "      <td>ACK</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>PAT_1989_4061_934.png</td>\n",
              "      <td>ACK</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>PAT_684_1302_588.png</td>\n",
              "      <td>BCC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  img_id diagnostic\n",
              "0  PAT_1516_1765_530.png        NEV\n",
              "1     PAT_46_881_939.png        BCC\n",
              "2  PAT_1545_1867_547.png        ACK\n",
              "3  PAT_1989_4061_934.png        ACK\n",
              "4   PAT_684_1302_588.png        BCC"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 276
        },
        "id": "4J6Hoet0AkT4",
        "outputId": "35f2f9fa-3fb3-4c58-bf94-bb035c29e98e"
      },
      "source": [
        "class_labels= metadata['diagnostic'].value_counts()\n",
        "plt.xticks(rotation=90)\n",
        "plt.bar(x=class_labels.keys(),height= class_labels);"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M9sncoIvDRAw"
      },
      "source": [
        "metadata.info()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fEZCRop4VY4s"
      },
      "source": [
        "img = cv2.imread('/content/lesion-full/PAT_1019_110_194.png')\n",
        "cv2_imshow(img)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "YF_EGOHkVcdy",
        "outputId": "0c206e92-a4ef-4217-97f4-95de2b48d5ba"
      },
      "source": [
        "histr = cv2.calcHist([img],[0],None,[256],[0,256])\n",
        "  \n",
        "# show the plotting graph of an image\n",
        "plt.plot(histr)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IaajzDzbWKnP"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}