generate_certificate.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sharp-complaint",
   "metadata": {},
   "outputs": [],
   "source": [
    "#https://medium.com/analytics-vidhya/generate-certificates-using-python-a7685985ed77\n",
    "#https://docs.google.com/presentation/d/1oF2EE9ZYOLW-U4gBF9PrWosjA-Iza6I2/edit#slide=id.g10fe440eedb_0_0\n",
    "#https://itnext.io/how-to-wrap-text-on-image-using-python-8f569860f89e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "oriented-closer",
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image, ImageDraw, ImageFont\n",
    "import pandas as pd\n",
    "import matplotlib.font_manager as fm\n",
    "import matplotlib\n",
    "import pylab as plt\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "orange-perry",
   "metadata": {},
   "source": [
    "## Checking here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "described-difficulty",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Open blank image\n",
    "im = Image.open(\"./blank.jpg\")\n",
    "#Now start drawing on Image\n",
    "d = ImageDraw.Draw(im)\n",
    "font = ImageFont.truetype('tahoma.ttf',38)\n",
    "font2 = ImageFont.truetype('tahoma.ttf',20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "developing-examination",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Specify location for name\n",
    "# location = [315, 320]\n",
    "# text_color = (128, 0, 0)\n",
    "# font = ImageFont.truetype('tahoma.ttf',38)\n",
    "# d.text(location, dummy_list, fill=text_color,font=font)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "humanitarian-portal",
   "metadata": {},
   "outputs": [],
   "source": [
    "# #Specify location for Title\n",
    "# #title=\"Study of something that is nothing because something happens\"\n",
    "# title=\"Study of something that is nothing because something is nothing however that is not the case all the time because shit happens\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "pursuant-fleece",
   "metadata": {},
   "outputs": [],
   "source": [
    "#word=title.split(' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "organizational-programmer",
   "metadata": {},
   "outputs": [],
   "source": [
    "# empty=[]\n",
    "# empty2=[]\n",
    "# sum=0\n",
    "# for i in word:\n",
    "#     sum = sum + len(i)\n",
    "#     if sum <=65:\n",
    "#         empty.append(i)\n",
    "#     else:\n",
    "#         empty2.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "varying-omaha",
   "metadata": {},
   "outputs": [],
   "source": [
    "# line1=' '.join(empty)\n",
    "# line2=' '.join(empty2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bibliographic-sweet",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "pressing-stable",
   "metadata": {},
   "outputs": [],
   "source": [
    "# if len(line2)==0:\n",
    "#     location2 = [125, 420]\n",
    "#     d.text(location2, line1, fill=text_color,font=font2)\n",
    "# else:\n",
    "#     location2 = [125, 405]\n",
    "#     location3 = [125, 435]\n",
    "#     d.text(location2, line1, fill=text_color,font=font2)\n",
    "#     d.text(location3, line2, fill=text_color,font=font2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "micro-trial",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import os\n",
    "# !dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "indian-arrangement",
   "metadata": {},
   "outputs": [],
   "source": [
    "#path_to_save = \"C:\\\\Users\\\\plasm\\\\Downloads\\\\AutoCertificate-main\\\\AutoCertificate-main\\\\certificates\\\\\"\n",
    "path_to_save = \"./\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "medieval-cooking",
   "metadata": {},
   "outputs": [],
   "source": [
    "# im.save('certificate_' + dummy_list + '.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18609069",
   "metadata": {},
   "outputs": [],
   "source": [
    "name, title = \"abc\", \"def\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ced370f",
   "metadata": {},
   "outputs": [],
   "source": [
    "im = Image.open(\"./blank.jpg\")\n",
    "d = ImageDraw.Draw(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0e799e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "location = [860, 320]; \n",
    "text_color = (128, 0, 0)\n",
    "\n",
    "font = ImageFont.truetype('tahoma.ttf',38)\n",
    "d.text(location, name, fill=text_color,font=font)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31409171",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = \"Mr Ganesh Kumar Paudel\"\n",
    "title = \"abc_cddasdsa daskljadsdklajs_daskljadl nesh Kumar Paudel\"*2\n",
    "\n",
    "im = Image.open(\"./blank.jpg\")\n",
    "d = ImageDraw.Draw(im)\n",
    "\n",
    "text_color = (128, 0, 0)\n",
    "# Specify location for name\n",
    "\n",
    "size = im.size\n",
    "dim = (size[0])//2\n",
    "\n",
    "name_len_pix = font.getmask(name).getbbox()[2]\n",
    "location_name = [dim - name_len_pix/2, 320]\n",
    "\n",
    "font = ImageFont.truetype('tahoma.ttf',38)\n",
    "d.text(location_name, name, fill=text_color,font=font)\n",
    "## Split title to multiple lines if required"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88eade4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "title = \"abc_cddasdsa daskljadsdklajs_daskljadl nesh Kumar Paudel\"#*2\n",
    "tsp = title.split()\n",
    "\n",
    "line1 = ''\n",
    "line2 = ''\n",
    "for i, t in enumerate(tsp):\n",
    "    line1_tmp = line1+\" \"+t\n",
    "    \n",
    "    line1_pix_tmp = font.getmask(line1_tmp).getbbox()[2]\n",
    "    \n",
    "    if line1_pix_tmp < 960:\n",
    "        line1 = line1_tmp\n",
    "    else:\n",
    "        line2 = ''.join(tsp[i:])\n",
    "        break\n",
    "        \n",
    "print (line1, line2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bdfa5a58",
   "metadata": {},
   "outputs": [],
   "source": [
    "if len(line2)==0:\n",
    "    \n",
    "    line1_pix = font.getmask(line1).getbbox()[2]\n",
    "        \n",
    "    print (f\"line1_pix = {line1_pix}\")\n",
    "    #location2 = [125, 420]\n",
    "    location2 = [2*dim - line1_pix/2, 420]\n",
    "    d.text(location2, line1, fill=text_color,font=font2)\n",
    "else:\n",
    "    #location2 = [135, 400]\n",
    "    #location3 = [135, 430]\n",
    "    line1_pix = font.getmask(line1).getbbox()[2]\n",
    "    line2_pix = font.getmask(line2).getbbox()[2]\n",
    "    \n",
    "    print (f\"line1_pix = {line1_pix}\")\n",
    "    print (f\"line2_pix = {line2_pix}\")\n",
    "    print (f\"dim = {dim}\")\n",
    "    loc2 = dim - line1_pix/4\n",
    "    loc3 = dim - line2_pix/4\n",
    "    location2 = [loc2 , 410]\n",
    "    location3 = [loc3 , 440]\n",
    "    \n",
    "    print (loc2, loc3)\n",
    "    d.text(location2, line1, fill=text_color,font=font2)\n",
    "    d.text(location3, line2, fill=text_color,font=font2)\n",
    "plt.imshow(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd420b34",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02e044d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "word=title.split(' ')\n",
    "empty=[]\n",
    "empty2=[]\n",
    "sum=0\n",
    "for i in word:\n",
    "    sum = sum + len(i)\n",
    "    if sum <=70:\n",
    "        empty.append(i)\n",
    "    else:\n",
    "        empty2.append(i)\n",
    "\n",
    "line1=' '.join(empty)\n",
    "line2=' '.join(empty2)\n",
    "font2 = ImageFont.truetype('tahoma.ttf',21)\n",
    "if len(line2)==0:\n",
    "    \n",
    "    line1_pix = font.getmask(line1).getbbox()[2]\n",
    "        \n",
    "    print (f\"line1_pix = {line1_pix}\")\n",
    "    #location2 = [125, 420]\n",
    "    location2 = [2*dim - line1_pix/2, 420]\n",
    "    d.text(location2, line1, fill=text_color,font=font2)\n",
    "else:\n",
    "    #location2 = [135, 400]\n",
    "    #location3 = [135, 430]\n",
    "    line2_pix = font.getmask(line2).getbbox()[2]\n",
    "    \n",
    "    print (f\"line1_pix = {line1_pix}\")\n",
    "    print (f\"line2_pix = {line2_pix}\")\n",
    "    print (f\"dim = {dim}\")\n",
    "    loc2 = dim - line1_pix/2\n",
    "    loc3 = dim - line2_pix/2\n",
    "    location2 = [loc2 , 400]\n",
    "    location3 = [loc3 , 430]\n",
    "    \n",
    "    print (loc2, loc3)\n",
    "    d.text(location2, line1, fill=text_color,font=font2)\n",
    "    d.text(location3, line2, fill=text_color,font=font2)\n",
    "plt.imshow(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "519e06e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_certificate2(name,title):\n",
    "    \n",
    "    name = name.strip()\n",
    "    title = title.strip()\n",
    "    \n",
    "    path_to_save = \"./certs\"\n",
    "    font = ImageFont.truetype('tahoma.ttf',38)\n",
    "    font2 = ImageFont.truetype('tahoma.ttf',20)\n",
    "    \n",
    "    im = Image.open(\"./blank.jpg\")\n",
    "    d = ImageDraw.Draw(im)\n",
    "\n",
    "    text_color = (128, 0, 0)\n",
    "    # Specify location for name\n",
    "\n",
    "    size = im.size\n",
    "    dim = (size[0])//2\n",
    "\n",
    "    name_len_pix = font.getmask(name).getbbox()[2]\n",
    "    location_name = [dim - name_len_pix/2, 320]\n",
    "\n",
    "    d.text(location_name, name, fill=text_color,font=font)\n",
    "    ## Split title to multiple lines if required\n",
    "\n",
    "    tsp = title.split()\n",
    "\n",
    "    line1 = ''\n",
    "    line2 = ''\n",
    "    for i, t in enumerate(tsp):\n",
    "        line1_tmp = line1+\" \"+t\n",
    "\n",
    "        line1_pix_tmp = font2.getmask(line1_tmp).getbbox()[2]\n",
    "\n",
    "        if line1_pix_tmp < 740:\n",
    "            line1 = line1_tmp\n",
    "        else:\n",
    "            line2 = ''.join(tsp[i:])\n",
    "            break\n",
    "\n",
    "\n",
    "    if len(line2)==0:\n",
    "        line1_pix = font.getmask(line1).getbbox()[2]\n",
    "        #location2 = [125, 420]\n",
    "        location2 = [dim - line1_pix/4, 420]\n",
    "        d.text(location2, line1, fill=text_color,font=font2)\n",
    "    else:\n",
    "        #location2 = [135, 400]\n",
    "        #location3 = [135, 430]\n",
    "        line1_pix = font.getmask(line1).getbbox()[2]\n",
    "        line2_pix = font.getmask(line2).getbbox()[2]\n",
    "\n",
    "        loc2 = dim - line1_pix/4\n",
    "        loc3 = dim - line2_pix/4\n",
    "        location2 = [loc2 , 410]\n",
    "        location3 = [loc3 , 440]\n",
    "\n",
    "        d.text(location2, line1, fill=text_color,font=font2)\n",
    "        d.text(location3, line2, fill=text_color,font=font2)\n",
    "\n",
    "    #savename = path_to_save + 'certificate2_' + name + '.png'\n",
    "    \n",
    "    savename = os.path.join(path_to_save, \"certificate_\"+name+\".png\")\n",
    "    im.save(savename) \n",
    "    #print (savename, \"saved.\")    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "294b89d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./certs/certificate_Ashok Timsina.png saved.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x121432d30>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#name = \"Mr Ganesh Kumar Paudel\"\n",
    "#title = \"abc_cddasdsa daskljadsdklajs_daskljadl nesh Kumar Paudel\"#*2\n",
    "\n",
    "name ='Ashok Timsina'\n",
    "title = 'Cell charging effect and the binding energy measurement of ions on a plastic surface in cryogenic liquids. '\n",
    "\n",
    "create_certificate2(name, title)\n",
    "    \n",
    "path_to_save = \"./certs\"\n",
    "savename = os.path.join(path_to_save, \"certificate_\"+name+\".png\")\n",
    "\n",
    "\n",
    "im = Image.open(savename)\n",
    "plt.imshow(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b7608ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "english-iraqi",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_certificate(name,title):\n",
    "    im = Image.open(\"./blank.jpg\")\n",
    "    d = ImageDraw.Draw(im)\n",
    "    # Specify location for name\n",
    "\n",
    "    #size = im.size\n",
    "\n",
    "    location = [(size[0]-50)//2, 320]\n",
    "    text_color = (128, 0, 0)\n",
    "    font = ImageFont.truetype('tahoma.ttf',38)\n",
    "    d.text(location, name, fill=text_color,font=font)\n",
    "    ## Split title to multiple lines if required\n",
    "    word=title.split(' ')\n",
    "    empty=[]\n",
    "    empty2=[]\n",
    "    sum=0\n",
    "    for i in word:\n",
    "        sum = sum + len(i)\n",
    "        if sum <=55:\n",
    "            empty.append(i)\n",
    "        else:\n",
    "            empty2.append(i)\n",
    "\n",
    "    line1=' '.join(empty)\n",
    "    line2=' '.join(empty2)\n",
    "    font2 = ImageFont.truetype('tahoma.ttf',21)\n",
    "    if len(line2)==0:\n",
    "        location2 = [125, 420]\n",
    "        d.text(location2, line1, fill=text_color,font=font2)\n",
    "    else:\n",
    "        location2 = [135, 400]\n",
    "        location3 = [135, 430]\n",
    "        d.text(location2, line1, fill=text_color,font=font2)\n",
    "        d.text(location3, line2, fill=text_color,font=font2)\n",
    "    return im.save(path_to_save + 'certificate2_' + name + '.png') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de38e00c",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "name = \"abc_cddasdsa_daskljadsdklajs_daskljads_prasad_paudel\"\n",
    "create_certificate(name, \"def\")\n",
    "\n",
    "imo = Image.open(\"certificate2_\"+name+\".png\")\n",
    "plt.imshow(imo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11b588d7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80326795",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "735a497b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bored-affiliate",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('schedule-2022_SB_PD.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "liberal-director",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Date', 'Session', 'StartDate', 'StartTime', 'EndDate', 'EndTime',\n",
       "       'Invited', 'Presenter', 'Presenter's Affiliation', 'In-Person/Remote',\n",
       "       'Coauthors', 'Coauthors affiliation', 'Paper Title', 'Abstract'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "functional-empty",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Presenter</th>\n",
       "      <th>Paper Title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Christopher Fischer</td>\n",
       "      <td>Helping traditionally under-served populations...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Arbin Thapaliya</td>\n",
       "      <td>Teaching ultrasound to undergraduates using pr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Puskar Chapgain</td>\n",
       "      <td>Does Peer-Assisted Instruction for University ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Simon Rees</td>\n",
       "      <td>Supplementing the Learning of Physics with the...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Anna Mederer</td>\n",
       "      <td>Scaffolding Writing in Physics Labs</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Presenter                                        Paper Title\n",
       "0  Christopher Fischer  Helping traditionally under-served populations...\n",
       "1      Arbin Thapaliya  Teaching ultrasound to undergraduates using pr...\n",
       "2      Puskar Chapgain  Does Peer-Assisted Instruction for University ...\n",
       "3           Simon Rees  Supplementing the Learning of Physics with the...\n",
       "4         Anna Mederer                Scaffolding Writing in Physics Labs"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[['Presenter','Paper Title']]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "29ba46f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Ashok Timsina',\n",
       " 'Cell charging effect and the binding energy measurement of ions on a plastic surface in cryogenic liquids. ')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = df[df.Presenter==\"Ashok Timsina\"].Presenter.values[0]\n",
    "title = df[df.Presenter==\"Ashok Timsina\"][\"Paper Title\"].values[0]\n",
    "name, title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "13769dee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(73, 2)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "convinced-latin",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "for i,rows in df.iterrows():\n",
    "    #print (rows['Presenter'],rows['Paper Title'])\n",
    "    create_certificate2(rows['Presenter'],rows['Paper Title'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "collect-career",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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