Face Similarity.ipynb

face-similarity.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNLtnKbAS2cMI7PjdNkuHSt",
      "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/ryf123/3b0fa30e0b50272fa11dfca5025b5103/face-similarity.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "auRTfckTSHNp"
      },
      "outputs": [],
      "source": [
        "!pip install insightface\n",
        "!pip install onnxruntime"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from insightface.app import FaceAnalysis\n",
        "import cv2\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "slDnIwBuThuZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def face_similarity(face_analyser, img1, img2):\n",
        "  f1 = face_analyser.get(img1)[0]\n",
        "  f2 = face_analyser.get(img2)[0]\n",
        "  return np.sum(np.square(f1.normed_embedding - f2.normed_embedding))"
      ],
      "metadata": {
        "id": "__-ZsblqSS5h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# how to use\n",
        "providers = ['CPUExecutionProvider']\n",
        "app = FaceAnalysis(providers=providers, name='buffalo_l')\n",
        "app.prepare(ctx_id=0, det_size=(640, 640))\n",
        "app.prepare(ctx_id=0)\n",
        "\n",
        "child_image_path = '/content/child.png' # @param {type:\"string\"}\n",
        "father_image_path = '/content/father.png' # @param {type:\"string\"}\n",
        "mother_image_path = '/content/mother.png' # @param {type:\"string\"}\n",
        "similarity_1 = face_similarity(\n",
        "    app,\n",
        "    cv2.imread(child_image_path),\n",
        "    cv2.imread(father_image_path)\n",
        ")\n",
        "similarity_2 = face_similarity(\n",
        "    app,\n",
        "    cv2.imread(child_image_path),\n",
        "    cv2.imread(mother_image_path)\n",
        ")\n",
        "print(f'father similarity {similarity_1}, mother similarity {similarity_2}')"
      ],
      "metadata": {
        "id": "dzxHN89AT5-P"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}