fontvolve/fontvolve.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# fontvolve: Generic algorithm to evolve a letter outline\n",
    "\n",
    "The outline of the letter is encoded into a gene as a sequence of angles and distances, just like how [Logo](https://en.wikipedia.org/wiki/Logo_(programming_language) instructions code the movement of a turtle.  The fitness function compares the drawn letter with the true letter, xor-ing the images and counting the black pixels representing a match."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAGQAAABkAQAAAABYmaj5AAAAl0lEQVR4nO1UMQ6DQAxz4AaewAY/\nKU87fsZTGBnp1gHhDik9IqGIoi4IMsWyleRs6YRI9cywrhsdRK2ISAAgBKgCqruzyqIqJ2fKS9vO\ncI2/HSTHpRsTl3+VD5LT7y86HUpOVMaJwSg9J+bd+zKHCwaVWOfQ795wPZTyE5Mfo1F2zpR+iyu2\nlLWiYLgP3+gtjMst8pcf8w3YQDiJN+vPcQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.Image.Image image mode=1 size=100x100 at 0x2017F057630>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from PIL import Image, ImageFont, ImageDraw, ImageChops\n",
    "size = 100\n",
    "black_and_white_format = '1'\n",
    "gene_image = Image.new(black_and_white_format, (size,size), 0)\n",
    "letter_image = Image.new(black_and_white_format, (size,size), 1)\n",
    "usr_font = ImageFont.truetype(\"ARLRDBD.TTF\", size)\n",
    "drawing = ImageDraw.Draw(letter_image)\n",
    "drawing.text((20,0), \"E\", fill=0, font=usr_font)\n",
    "letter_image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import math\n",
    "\n",
    "def draw(gene):\n",
    "    drawing = ImageDraw.Draw(gene_image) #to draw on an image\n",
    "    drawing.rectangle((0,0,size,size), \"white\")\n",
    "    coords = []\n",
    "    x,y = (size/2,size/2)\n",
    "    degreeToRadians = 360/(2*math.pi)\n",
    "    for (angle, dist) in gene:\n",
    "        x+=dist*math.sin(angle/degreeToRadians)\n",
    "        y+=dist*math.cos(angle/degreeToRadians)\n",
    "        coords.append((x,y))\n",
    "    #print(coords)\n",
    "    drawing.polygon(coords, fill=\"black\")\n",
    "    return gene_image\n",
    "\n",
    "#fitness function: calculate a percentage of image matching the letter, with a small correction to favour shorter genes\n",
    "def match_letter(gene):\n",
    "    return float(ImageChops.logical_xor(draw(gene), letter_image).histogram()[0]-5*len(gene))/size/size\n",
    "\n",
    "def draw_all(gene_pool):\n",
    "    image = Image.new(\"1\", (size*10,size*10), 1)\n",
    "    for i in range(0,10):\n",
    "        for j in range(0,10):\n",
    "            image.paste(draw(gene_pool[i*10+j]), (j*size, i*size))\n",
    "            #image.paste(ImageChops.logical_xor(draw(gene_pool[i*10+j]), letter_image), (i*size, j*size))\n",
    "    return image\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from random import random, randint, choice, seed\n",
    "\n",
    "def mutate(gene):\n",
    "    new_gene = []\n",
    "    variation = 2\n",
    "    for pair in gene:\n",
    "        rand = random()\n",
    "        if rand<0.1: #add pair\n",
    "            new_gene.append((pair[0]+randint(-20,20), pair[1]/2))\n",
    "            new_gene.append((pair[0]+randint(-20,20), pair[1]/2))\n",
    "        elif rand<0.2: #remove gene\n",
    "            None\n",
    "        elif rand<0.6: #mutate angle \n",
    "            new_gene.append( (pair[0]+randint(-20,20), pair[1]) )\n",
    "        else: #mutate distance\n",
    "            new_gene.append( (pair[0], pair[1]+randint(-variation,variation)) )\n",
    "    return new_gene if len(new_gene)>=2 else gene\n",
    "\n",
    "#combine random part of gene1 with random part of gene2 in random order\n",
    "def combine(gene1, gene2):\n",
    "    if random()<0.5:\n",
    "        return gene1[:randint(2,len(gene1))] + gene2[randint(0,len(gene2)):]\n",
    "    else:\n",
    "        return gene2[:randint(2,len(gene2))] + gene1[randint(0,len(gene1)):]\n",
    "\n",
    "from heapq import nlargest\n",
    "\n",
    "def evolve(gene_pool):\n",
    "    indices = range(0,len(gene_pool))\n",
    "    scores = [match_letter(gene) for gene in gene_pool]\n",
    "    mutate_fraction = 0.1\n",
    "    largest = nlargest(max(int(len(gene_pool)*mutate_fraction),1), indices, key=lambda i: scores[i])\n",
    "    #print([scores[large] for large in largest])\n",
    "    new_genes = [gene_pool[n] for n in nlargest(2, indices, key=lambda i: scores[i])]\n",
    "    for large in largest:\n",
    "        #print(match_letter(gene_pool[large]), gene_pool[large])\n",
    "        new_genes.append(gene_pool[large])\n",
    "        mutated = mutate(gene_pool[large])\n",
    "        #print(match_letter(mutated), mutated)\n",
    "        new_genes.append(mutated)\n",
    "    while len(new_genes)<len(gene_pool):\n",
    "        new_genes.append(combine(gene_pool[choice(largest)],choice(gene_pool)))\n",
    "        \n",
    "    return new_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pool_size = 200\n",
    "seed(1)\n",
    "gene_pool = [[(randint(-90,90), randint(0,size/2)) for pairs in range(0, randint(3,20))] for genes in range(0,pool_size)]\n",
    "orig_pool = gene_pool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9242\n"
     ]
    },
    {
     "data": {
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f9S/ZDPCBLyyr1mNdH7r0eVsg1oirpiWRA9Ai6gDMBdZaz7iJLe49EQDfdwKc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\ngg==\n",
      "text/plain": [
       "<PIL.Image.Image image mode=1 size=1000x1000 at 0x2017F1F69E8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "generations= gene_pool[0:10]\n",
    "for gen in range(0,10):\n",
    "    for i in range(0,300):\n",
    "        #print(gene_pool[0])\n",
    "        gene_pool = evolve(gene_pool)\n",
    "    generations += gene_pool[0:10]\n",
    "    \n",
    "#print(orig_pool[0])\n",
    "print(match_letter(gene_pool[0]))\n",
    "#ImageChops.logical_xor(draw(gene_pool[0]), letter_image)\n",
    "#draw(gene_pool[0])\n",
    "\n",
    "draw_all(generations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sample evolved fonts\n",
    "![A](http://nbviewer.jupyter.org/github/terryspitz/ipython_notebooks/blob/master/fontvolve/fontA.png)\n",
    "![B](http://nbviewer.jupyter.org/github/terryspitz/ipython_notebooks/blob/master/fontvolve/fontB.png)\n",
    "![S](http://nbviewer.jupyter.org/github/terryspitz/ipython_notebooks/blob/master/fontvolve/fontS.png) (not very well matched - I think needed to rerun a few times to get a good starting point for it to work.)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
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