heart

heart.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x124b83510>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qp1f2ee8KqoC0ujMjIvalOkV0e2Z+f5gy0rzzy0aj4u+SFpgd5mrFEfE44Fiq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\nw4skSSrK/w9YvdZFMgKAlwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c8aeb50>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 255,
       "width": 279
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "w = 2000\n",
    "h = 2000\n",
    "img = np.ones((h*2, w*2, 3))\n",
    "for i in range(w*2):\n",
    "    for j in range(h*2):\n",
    "        ii = (w-i) / float(w/2)\n",
    "        jj = (h-j) / float(h/2)\n",
    "        if (ii**2+jj**2-1)**3 < ii**2*jj**3:\n",
    "            img[j, i, 1:] = 0\n",
    "\n",
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import cv2\n",
    "cv2.imwrite('heart.png', img[:,:,::-1]*255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
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