Mask_Dilation.ipynb

mask_dilation.ipynb

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  "metadata": {
    "colab": {
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      "authorship_tag": "ABX9TyM8jK716fultWhedClHWlVd",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/gist/ritwikraha/74534c168784f90680ff734a3a8fdcf3/mask_dilation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5kX3hjY7Tqm3"
      },
      "outputs": [],
      "source": [
        "import cv2\n",
        "import PIL\n",
        "import matplotlib as plt\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# seg_mask = PIL.Image.open('image.jpg')\n",
        "seg_mask = cv2.cvtColor(numpy.array(seg_mask), cv2.COLOR_RGB2BGR)"
      ],
      "metadata": {
        "id": "7o8R-vDrT7-u"
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      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "kernel = np.ones((5, 5), np.uint8)\n",
        "\n",
        "seg_mask_dilated = cv2.dilate(img, kernel, iterations=3)"
      ],
      "metadata": {
        "id": "Sadm3fpCUJuI"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}