Untitled0.ipynb

untitled0.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNH3bCM/SJ3ggfIGhxhm29D",
      "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/gist/J0onYEong/803f382e2be32cd08b32a69201c184d7/untitled0.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import dlib\n",
        "import cv2\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# 얼굴 검출기와 랜드마크 검출기 초기화\n",
        "detector = dlib.get_frontal_face_detector()\n",
        "predictor = dlib.shape_predictor(\"shape_predictor_68_face_landmarks.dat\")\n",
        "\n",
        "# 이미지 로드\n",
        "image = cv2.imread(\"face_image.jpg\")\n",
        "gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
        "\n",
        "# 얼굴 검출\n",
        "faces = detector(gray_image)\n",
        "\n",
        "for face in faces:\n",
        "    x1, y1, x2, y2 = face.left(), face.top(), face.right(), face.bottom()\n",
        "    cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 3)\n",
        "\n",
        "    # 랜드마크 검출\n",
        "    landmarks = predictor(gray, face)\n",
        "\n",
        "    # 코 교량의 양쪽 끝점\n",
        "    nose_start = landmarks.part(28)\n",
        "    nose_end = landmarks.part(31)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "    for n in range(0, 68):\n",
        "        x = landmarks.part(n).x\n",
        "        y = landmarks.part(n).y\n",
        "        cv2.putText(image, str(n+1), (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1, cv2.LINE_AA)\n",
        "\n",
        "\n",
        "# BGR 이미지를 RGB로 변환\n",
        "image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
        "\n",
        "# matplotlib를 사용해 이미지 표시\n",
        "plt.figure(figsize=(10, 10))\n",
        "plt.imshow(image_rgb)\n",
        "plt.axis(\"off\")  # 축을 표시하지 않음\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "iSqk3DY_-rHD",
        "outputId": "d53beb25-f87c-48b5-a8c2-926dca4329dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "RuntimeError",
          "evalue": "Error deserializing object of type short\n   while deserializing a floating point number.\n   while deserializing a dlib::matrix\n   while deserializing object of type std::vector\n   while deserializing object of type std::vector\n   while deserializing object of type std::vector",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-4-bedd7c6031a7>\u001b[0m in \u001b[0;36m<cell line: 7>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# 얼굴 검출기와 랜드마크 검출기 초기화\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mdetector\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_frontal_face_detector\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[0;32m----> 7\u001b[0;31m \u001b[0mpredictor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape_predictor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"shape_predictor_68_face_landmarks.dat\"\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      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;31m# 이미지 로드\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mRuntimeError\u001b[0m: Error deserializing object of type short\n   while deserializing a floating point number.\n   while deserializing a dlib::matrix\n   while deserializing object of type std::vector\n   while deserializing object of type std::vector\n   while deserializing object of type std::vector"
          ]
        }
      ]
    }
  ]
}