EDL_3_5_EvoLisa_GA.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "EDL_3_5_EvoLisa_GA.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMLX8a2UmN7EscsYKi/FTRs",
      "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/cxbxmxcx/EvolutionaryDeepLearning/blob/main/EDL_3_5_EvoLisa_GA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QA0DAcx1b-Zk"
      },
      "source": [
        "#@title Install DEAP\n",
        "!pip install deap --quiet"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L6P5gIVNYj-f"
      },
      "source": [
        "#@title Imports\n",
        "import random\n",
        "import numpy as np\n",
        "\n",
        "from deap import algorithms\n",
        "from deap import base\n",
        "from deap import creator\n",
        "from deap import tools\n",
        "\n",
        "import os\n",
        "import cv2\n",
        "import urllib.request\n",
        "import matplotlib.pyplot as plt\n",
        "from IPython.display import clear_output"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Es3IZavnIjS7"
      },
      "source": [
        "#@title Image Helpers\n",
        "def load_target_image(image_url, color=True, size=None):\n",
        "  image_path = \"target_image\"    \n",
        "  urllib.request.urlretrieve(image_url,image_path)\n",
        "  if color:\n",
        "      target = cv2.imread(image_path, cv2.IMREAD_COLOR)\n",
        "      # Switch from bgr to rgb\n",
        "      target = cv2.cvtColor(target, cv2.COLOR_BGR2RGB)\n",
        "  else:\n",
        "      target = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)\n",
        "\n",
        "  if size:\n",
        "      # Only resizes image if it is needed!\n",
        "      target = cv2.resize(src=target, dsize=size, interpolation=cv2.INTER_AREA)\n",
        "  return target\n",
        "\n",
        "def show_image(img_arr):    \n",
        "    plt.figure(figsize=(10,10))\n",
        "    plt.axis(\"off\")\n",
        "    plt.imshow(img_arr/255)\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "xX-PazxIeD3v",
        "outputId": "34acc982-1830-4870-cfc3-0beadbcddb82"
      },
      "source": [
        "#@title Default title text { run: \"auto\" }\n",
        "polygons = 128 #@param {type:\"slider\", min:10, max:1000, step:1}\n",
        "size = 40 #@param {type:\"slider\", min:25, max:1000, step:5}\n",
        "target_image = \"Mona Lisa\" #@param [\"Mona Lisa\", \"Stop Sign\", \"Landscape\", \"Celebrity\", \"Art\", \"Abstract\"]\n",
        "\n",
        "\n",
        "POLYGONS = polygons\n",
        "SIZE = (size, size)\n",
        "\n",
        "target_urls = { \"Mona Lisa\" : 'https://upload.wikimedia.org/wikipedia/commons/b/b7/Mona_Lisa_face_800x800px.jpg',\n",
        "               \"Stop Sign\" : 'https://images.uline.com/is/image//content/dam/images/H/H2500/H-2381.jpg',\n",
        "               \"Landscape\" : 'https://www.adorama.com/alc/wp-content/uploads/2018/11/landscape-photography-tips-yosemite-valley-feature.jpg',\n",
        "               \"Celebrity\" : 'https://s.abcnews.com/images/Entertainment/WireAP_91d6741d1954459f9993bd7a2f62b6bb_16x9_992.jpg',\n",
        "               \"Art\" : \"http://www.indianruminations.com/wp-content/uploads/what-is-modern-art-definition-2.jpg\",\n",
        "               \"Abstract\" : \"https://scx2.b-cdn.net/gfx/news/2020/abstractart.jpg\"\n",
        "               }\n",
        "\n",
        "target_image_url = target_urls[target_image]\n",
        "target = load_target_image(target_image_url, size=SIZE)\n",
        "show_image(target)\n",
        "print(target.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "URLError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[1;31mSSLCertVerificationError\u001b[0m                  Traceback (most recent call last)",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mdo_open\u001b[1;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[0;32m   1353\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1354\u001b[1;33m                 h.request(req.get_method(), req.selector, req.data, headers,\n\u001b[0m\u001b[0;32m   1355\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36mrequest\u001b[1;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[0;32m   1255\u001b[0m         \u001b[1;34m\"\"\"Send a complete request to the server.\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1256\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_send_request\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mheaders\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1257\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36m_send_request\u001b[1;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[0;32m   1301\u001b[0m             \u001b[0mbody\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_encode\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'body'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1302\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mendheaders\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1303\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36mendheaders\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m   1250\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mCannotSendHeader\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1251\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_send_output\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmessage_body\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencode_chunked\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencode_chunked\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1252\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36m_send_output\u001b[1;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[0;32m   1010\u001b[0m         \u001b[1;32mdel\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_buffer\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1011\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1012\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, data)\u001b[0m\n\u001b[0;32m    950\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mauto_open\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 951\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconnect\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    952\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\http\\client.py\u001b[0m in \u001b[0;36mconnect\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1424\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1425\u001b[1;33m             self.sock = self._context.wrap_socket(self.sock,\n\u001b[0m\u001b[0;32m   1426\u001b[0m                                                   server_hostname=server_hostname)\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\ssl.py\u001b[0m in \u001b[0;36mwrap_socket\u001b[1;34m(self, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, session)\u001b[0m\n\u001b[0;32m    499\u001b[0m         \u001b[1;31m# ctx._wrap_socket()\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 500\u001b[1;33m         return self.sslsocket_class._create(\n\u001b[0m\u001b[0;32m    501\u001b[0m             \u001b[0msock\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msock\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\ssl.py\u001b[0m in \u001b[0;36m_create\u001b[1;34m(cls, sock, server_side, do_handshake_on_connect, suppress_ragged_eofs, server_hostname, context, session)\u001b[0m\n\u001b[0;32m   1039\u001b[0m                         \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"do_handshake_on_connect should not be specified for non-blocking sockets\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1040\u001b[1;33m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdo_handshake\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1041\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mOSError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\ssl.py\u001b[0m in \u001b[0;36mdo_handshake\u001b[1;34m(self, block)\u001b[0m\n\u001b[0;32m   1308\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msettimeout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1309\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdo_handshake\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1310\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;31mSSLCertVerificationError\u001b[0m: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: certificate has expired (_ssl.c:1131)",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[1;31mURLError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_224928/2239299486.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[0mtarget_image_url\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtarget_urls\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtarget_image\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m \u001b[0mtarget\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mload_target_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtarget_image_url\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mSIZE\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     20\u001b[0m \u001b[0mshow_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtarget\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_224928/444168750.py\u001b[0m in \u001b[0;36mload_target_image\u001b[1;34m(image_url, color, size)\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mload_target_image\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimage_url\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m   \u001b[0mimage_path\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m\"target_image\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m   \u001b[0murllib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0murlretrieve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimage_url\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mimage_path\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m   \u001b[1;32mif\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m       \u001b[0mtarget\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimage_path\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIMREAD_COLOR\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36murlretrieve\u001b[1;34m(url, filename, reporthook, data)\u001b[0m\n\u001b[0;32m    245\u001b[0m     \u001b[0murl_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpath\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_splittype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    246\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 247\u001b[1;33m     \u001b[1;32mwith\u001b[0m \u001b[0mcontextlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclosing\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murlopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    248\u001b[0m         \u001b[0mheaders\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36murlopen\u001b[1;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[0;32m    220\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    221\u001b[0m         \u001b[0mopener\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 222\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    223\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    224\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mopen\u001b[1;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[0;32m    523\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    524\u001b[0m         \u001b[0msys\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maudit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'urllib.Request'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_method\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 525\u001b[1;33m         \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    526\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    527\u001b[0m         \u001b[1;31m# post-process response\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36m_open\u001b[1;34m(self, req, data)\u001b[0m\n\u001b[0;32m    540\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    541\u001b[0m         \u001b[0mprotocol\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 542\u001b[1;33m         result = self._call_chain(self.handle_open, protocol, protocol +\n\u001b[0m\u001b[0;32m    543\u001b[0m                                   '_open', req)\n\u001b[0;32m    544\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[1;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[0;32m    500\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    501\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 502\u001b[1;33m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    503\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    504\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mhttps_open\u001b[1;34m(self, req)\u001b[0m\n\u001b[0;32m   1395\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1396\u001b[0m         \u001b[1;32mdef\u001b[0m \u001b[0mhttps_open\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1397\u001b[1;33m             return self.do_open(http.client.HTTPSConnection, req,\n\u001b[0m\u001b[0;32m   1398\u001b[0m                 context=self._context, check_hostname=self._check_hostname)\n\u001b[0;32m   1399\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;32m~\\.conda\\envs\\jup\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mdo_open\u001b[1;34m(self, http_class, req, **http_conn_args)\u001b[0m\n\u001b[0;32m   1355\u001b[0m                           encode_chunked=req.has_header('Transfer-encoding'))\n\u001b[0;32m   1356\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[1;33m:\u001b[0m \u001b[1;31m# timeout error\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1357\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mURLError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1358\u001b[0m             \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1359\u001b[0m         \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;31mURLError\u001b[0m: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: certificate has expired (_ssl.c:1131)>"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "form",
        "id": "5MNv6EWeeWYO",
        "outputId": "2ae0ca9f-f601-43c3-a36b-aa53f5cc59c8"
      },
      "source": [
        "#@title Setup Polylines\n",
        "\n",
        "#polygon genes\n",
        "GENE_LENGTH = 10\n",
        "NUM_GENES = POLYGONS * GENE_LENGTH\n",
        "\n",
        "#create a sample invidiual\n",
        "individual = np.random.uniform(0,1,NUM_GENES)\n",
        "print(individual)\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.082519   0.61400162 0.35414182 ... 0.22840391 0.79089374 0.40262348]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 575
        },
        "id": "sTzsqLjtDxWQ",
        "outputId": "d7b9127d-9eb4-4fc9-e5be-9d488c394aed"
      },
      "source": [
        "#@title Render an Individual\n",
        "def extract_genes(genes, length): \n",
        "    for i in range(0, len(genes), length): \n",
        "        yield genes[i:i + length]\n",
        "\n",
        "def render_individual(individual):\n",
        "  if isinstance(individual,list):\n",
        "    individual = np.array(individual)\n",
        "  canvas = np.zeros(SIZE+(3,))\n",
        "  radius_avg = (SIZE[0] + SIZE[1]) / 2 / 6\n",
        "  genes = extract_genes(individual, GENE_LENGTH)\n",
        "  for gene in genes:\n",
        "    try:\n",
        "      overlay = canvas.copy()\n",
        "      # alternative drawing methods circle or rectangle\n",
        "      # circle brush uses a GENE_LENGTH of 7\n",
        "      # center = (0, 1) [2]\n",
        "      # radius = (2) [3]\n",
        "      # color = (3,4,5) [6]\n",
        "      # alpha = (6) [7]\n",
        "      #cv2.circle(\n",
        "      #    overlay,\n",
        "      #    center=(int(gene[1] * SIZE[1]), int(gene[0] * SIZE[0])),\n",
        "      #    radius=int(gene[2] * radius_avg),\n",
        "      #    color=color,\n",
        "      #    thickness=-1,\n",
        "      #)\n",
        "\n",
        "      # rectangle brush uses GENE_LENGTH = 8\n",
        "      # top left = (0, 1) [2]\n",
        "      # btm right = (2, 3) [4]\n",
        "      # color = (4, 5, 6) [7]\n",
        "      # alpha = (7) [8]\n",
        "      #cv2.rectangle(overlay, (x1, y1), (x2, y2), color, -1)    \n",
        "\n",
        "      # polyline brush uses GENE_LENGTH = 10\n",
        "      # pts = (0, 1), (2, 3), (4, 5) [6]      \n",
        "      # color = (6, 7, 8) [9]\n",
        "      # alpha = (9) [10]\n",
        "      x1 = int(gene[0] * SIZE[0])\n",
        "      x2 = int(gene[2] * SIZE[0])\n",
        "      x3 = int(gene[4] * SIZE[0])\n",
        "      y1 = int(gene[1] * SIZE[1])\n",
        "      y2 = int(gene[3] * SIZE[1])\n",
        "      y3 = int(gene[5] * SIZE[1])\n",
        "      color = (gene[6:-1] * 255).astype(int).tolist() \n",
        "      pts = np.array([[x1,y1],[x2,y2],[x3,y3]], np.int32)  \n",
        "      pts = pts.reshape((-1, 1, 2))\n",
        "      pts = np.array([[x1,y1],[x2,y2],[x3,y3]])\n",
        "\n",
        "      cv2.fillPoly(overlay, [pts], color)\n",
        "      alpha = gene[-1]\n",
        "      canvas = cv2.addWeighted(overlay, alpha, canvas, 1 - alpha, 0)  \n",
        "    except:\n",
        "      pass\n",
        "  return canvas\n",
        "\n",
        "render = render_individual(individual)\n",
        "show_image(render)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 232
        },
        "id": "626salpU3bCa",
        "outputId": "0415c1e0-386d-4d86-9e0d-09a2871ad768"
      },
      "source": [
        "from skimage.metrics import structural_similarity as ss\n",
        "#@title Fitness Function\n",
        "def fitness_mse(render):\n",
        "  \"\"\"Calculates Mean Square Error Fitness for a render\"\"\"\n",
        "  error = (np.square(render - target)).mean(axis=None)\n",
        "  return error\n",
        "\n",
        "def fitness_ss(render):\n",
        "  \"\"\"Calculated Structural Similiarity Fitness\"\"\"\n",
        "  index = ss(render, target, multichannel=True)\n",
        "  return 1-index\n",
        "\n",
        "print(fitness_mse(render))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_224928/1068988182.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mskimage\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmetrics\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mstructural_similarity\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mss\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[1;31m#@title Fitness Function\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mfitness_mse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrender\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m   \u001b[1;34m\"\"\"Calculates Mean Square Error Fitness for a render\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m   \u001b[0merror\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msquare\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrender\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mtarget\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
            "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'skimage'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZRvse58ccZpI"
      },
      "source": [
        "#@title Setting up the Creator\n",
        "creator.create(\"FitnessMax\", base.Fitness, weights=(-1.0,))\n",
        "creator.create(\"Individual\", list, fitness=creator.FitnessMax)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NeEjluAhcysa"
      },
      "source": [
        "def uniform(low, up, size=None):\n",
        "  try:\n",
        "    return [random.uniform(a, b) for a, b in zip(low, up)]\n",
        "  except TypeError:\n",
        "    return [random.uniform(a, b) for a, b in zip([low] * size, [up] * size)]\n",
        "\n",
        "toolbox = base.Toolbox()\n",
        "toolbox.register(\"attr_float\", uniform, 0, 1, NUM_GENES)\n",
        "toolbox.register(\"individual\", tools.initIterate, creator.Individual, toolbox.attr_float)\n",
        "toolbox.register(\"population\", tools.initRepeat, list, toolbox.individual)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kJYSqw0C49as"
      },
      "source": [
        "def evaluate(individual):\n",
        "  render = render_individual(individual)\n",
        "  print('.', end='')\n",
        "  return fitness_mse(render),  #using MSE for fitness"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "ln5Xp2RTDDnN"
      },
      "source": [
        "#@title Register the Choices\n",
        "def register_selection(choice):\n",
        "  choices = [\"Tournament\", \"Roulette\", \"Random\", \"Best\", \"Worst\", \"NSGA2\", \"SPEA2\"]\n",
        "  if choice == choices[0]:\n",
        "    toolbox.register(\"select\", tools.selTournament, tournsize=3)\n",
        "  elif choice == choices[1]:\n",
        "    toolbox.register(\"select\", tools.selRoulette)\n",
        "  elif choice == choices[2]:\n",
        "    toolbox.register(\"select\", tools.selRandom)\n",
        "  elif choice == choices[3]:\n",
        "    toolbox.register(\"select\", tools.selBest)\n",
        "  elif choice == choices[4]:\n",
        "    toolbox.register(\"select\", tools.selWorst)\n",
        "  elif choice == choices[5]:\n",
        "    toolbox.register(\"select\", tools.selNSGA2)\n",
        "  elif choice == choices[6]:\n",
        "    toolbox.register(\"select\", tools.selSPEA2)\n",
        "\n",
        "def register_mating(choice):\n",
        "  choices = [\"Partially Matched\", \"One Point\", \"Two Point\", \"Ordered\", \"ES Two Point\", \"Uniform\", \"Uniform Partially Matched\"]\n",
        "  if choice == choices[0]:\n",
        "    toolbox.register(\"mate\", tools.cxPartialyMatched)\n",
        "  elif choice == choices[1]:\n",
        "    toolbox.register(\"mate\", tools.cxOnePoint)\n",
        "  elif choice == choices[2]:\n",
        "    toolbox.register(\"mate\", tools.cxTwoPoint)\n",
        "  elif choice == choices[3]:\n",
        "    toolbox.register(\"mate\", tools.cxOrdered)\n",
        "  elif choice == choices[4]:\n",
        "    toolbox.register(\"mate\", tools.cxESTwoPoint)\n",
        "  elif choice == choices[5]:\n",
        "    toolbox.register(\"mate\", tools.cxUniform, indpb=.5)\n",
        "  elif choice == choices[6]:\n",
        "    toolbox.register(\"mate\", tools.cxUniformPartialyMatched, indpb=.5)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_AebxojWDN84"
      },
      "source": [
        "#@title Selecting the Genetic Operators { run: \"auto\" }\n",
        "selection = \"Tournament\" #@param [\"Tournament\", \"Random\", \"Best\", \"Worst\", \"NSGA2\", \"SPEA2\"]\n",
        "mating = \"One Point\" #@param [\"Partially Matched\", \"One Point\", \"Two Point\", \"Ordered\", \"Uniform\", \"Uniform Partially Matched\"]\n",
        "\n",
        "register_mating(mating)\n",
        "register_selection(selection)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "auv2mxKrdWDV"
      },
      "source": [
        "#@title Mutation and Evaluation\n",
        "toolbox.register(\"mutate\", tools.mutGaussian, mu=0.0, sigma=1, indpb=.05)\n",
        "toolbox.register(\"evaluate\", evaluate)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "th7zmZin5wiC"
      },
      "source": [
        "random.seed(64)\n",
        "    \n",
        "NGEN = 100000\n",
        "CXPB = .6\n",
        "MUTPB = .3\n",
        "MU = 2500\n",
        "pop = toolbox.population(n=MU)\n",
        "hof = tools.HallOfFame(1)\n",
        "stats = tools.Statistics(lambda ind: ind.fitness.values)\n",
        "stats.register(\"avg\", np.mean)\n",
        "stats.register(\"std\", np.std)\n",
        "stats.register(\"min\", np.min)\n",
        "stats.register(\"max\", np.max) "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pORryNkH73S_"
      },
      "source": [
        "best = None\n",
        "\n",
        "for g in range(NGEN):\n",
        "  pop, logbook = algorithms.eaSimple(pop, toolbox, \n",
        "            cxpb=CXPB, mutpb=MUTPB, ngen=1, stats=stats, halloffame=hof, verbose=False)\n",
        "  best = hof[0] \n",
        "  clear_output()\n",
        "  render = render_individual(best) \n",
        "  show_image(render) \n",
        "  print(f\"Gen ({g}) : fitness = {fitness_mse(render)}\")"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}