GeneratedImages.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import PIL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 610,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/fdWpvz/QqHOuKY53UdZTvbLnTdbT9zVo2PYZ2nXfLA0fmaXKYS7lFfY+QIRD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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=780x390 at 0x10FAE1630>"
      ]
     },
     "execution_count": 610,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "from PIL import ImageFont\n",
    "from PIL import ImageDraw \n",
    "img = Image.open(\"base_image.png\")\n",
    "draw = ImageDraw.Draw(img)\n",
    "# font = ImageFont.truetype(<font-file>, <font-size>)\n",
    "font = ImageFont.truetype(\"Montserrat-Black.ttf\", 80)\n",
    "# draw.text((x, y),\"Sample Text\",(r,g,b))\n",
    "draw.text((img.size[0]*.04, img.size[1]*0.04),\"DENUNCIA\\nCORRUPCIÓN\",(255,255,255),font=font)\n",
    "img.save('sample-out.png')\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 557,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import shutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 597,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "from requests_oauthlib import OAuth1\n",
    "\n",
    "def get_icon(term):\n",
    "    auth = OAuth1(\"secret\", \"app\")\n",
    "    endpoint = \"http://api.thenounproject.com/icon/\"+term\n",
    "    response = requests.get(endpoint, auth=auth)\n",
    "    name = response.json()[\"icon\"][\"preview_url\"]\n",
    "    r = requests.get(name)\n",
    "    print(r)\n",
    "    i = Image.open(BytesIO(r.content))\n",
    "    i = i.resize((300,300))\n",
    "    return(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "icon_dir = \"icons\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from io import BytesIO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def replace_color_icon(img):\n",
    "    img = img.convert(\"RGBA\")\n",
    "\n",
    "    pixdata = img.load()\n",
    "\n",
    "    # Clean the background noise, if color != white, then set to black.\n",
    "    # change with your color\n",
    "    for y in range(img.size[1]):\n",
    "        for x in range(img.size[0]):\n",
    "            i = 0\n",
    "            while i<60:\n",
    "                if pixdata[x,y][3]<255:\n",
    "                    current_data = list(pixdata[x,y])\n",
    "                    current_data[3] = 0\n",
    "                    pixdata[x,y] = tuple(current_data)\n",
    "                if pixdata[x, y] == (i, i, i, 255):\n",
    "                    pixdata[x, y] = (61,52,154, 255)\n",
    "                i = i +1\n",
    "    return(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def replace_color_transparency(img):\n",
    "    img = img.convert(\"RGBA\")\n",
    "\n",
    "    pixdata = img.load()\n",
    "\n",
    "    # Clean the background noise, if color != white, then set to black.\n",
    "    # change with your color\n",
    "    for y in range(img.size[1]):\n",
    "        for x in range(img.size[0]):\n",
    "            if pixdata[x, y] == (255, 255, 255, 255):\n",
    "                pixdata[x, y] = (255,255,255, 0)\n",
    "    return(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 611,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Response [200]>\n"
     ]
    }
   ],
   "source": [
    "image_2 = replace_color_icon(get_icon(\"money\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 612,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final2 = Image.new(\"RGBA\", img.size)\n",
    "final2.paste(image_2, (int(img.size[0]*.55), int(img.size[1]*.4)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 613,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final_2_transp = replace_color_transparency(final2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 614,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "final3 = Image.new(\"RGBA\", img.size)\n",
    "final3 = Image.alpha_composite(final3, img)\n",
    "final3 =  Image.alpha_composite(final3, final_2_transp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 615,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "img.paste(final3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 616,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+dvdKnX55udNFWUPdkt6VrMfuaNaoLXO0/e55Gj02TzWjslRc1vcAIhGXGpZH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\nQJCn4iqU7QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=780x390 at 0x10FAE1630>"
      ]
     },
     "execution_count": 616,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}