testing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image, ImageFont, ImageDraw \n",
    "from pilmoji import Pilmoji\n",
    "import sys\n",
    "import datetime\n",
    "import os\n",
    "from tkinter import Tk, filedialog\n",
    "from ctypes import windll\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generating All Required Images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "windll.shcore.SetProcessDpiAwareness(1) # 4k resolution\n",
    "root = Tk()\n",
    "root.withdraw()\n",
    "root.attributes('-topmost', True)\n",
    "open_file = filedialog.askopenfilename()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:/Users/lukep/Videos/youtube_disc13/script.txt'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "open_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(open_file, encoding=\"utf8\") as f:\n",
    "    lines = f.read().splitlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "prof_pic_dict = {'Billy': 'profile_pictures/billy.PNG',\n",
    "                'Shregory': 'profile_pictures/shregory.PNG',\n",
    "                'Teacher': 'profile_pictures/teacher.PNG',\n",
    "                'Professor': 'profile_pictures/professor.PNG'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get current time\n",
    "current_time = datetime.datetime.now()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'path' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_21100\\276719027.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf'cd {path} && mkdir chat'\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      2\u001b[0m \u001b[0mname_up_next\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mcurrent_name\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mcurrent_lines\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[0;32m      5\u001b[0m \u001b[0mfinished_message\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'path' is not defined"
     ]
    }
   ],
   "source": [
    "os.system(f'mkdir chat')\n",
    "name_up_next = False\n",
    "current_name = None\n",
    "current_lines = []\n",
    "finished_message = False\n",
    "ims = []\n",
    "msg_number = 1\n",
    "\n",
    "for line in lines:\n",
    "    # If line is empty (signifying end of message chain)\n",
    "    if line=='':\n",
    "        name_up_next=True\n",
    "        current_lines = []\n",
    "        continue\n",
    "    # lines that are commented out\n",
    "    if line[0]=='#':\n",
    "        continue\n",
    "    # If currently on a name line\n",
    "    if name_up_next:\n",
    "        current_name = line.split(':')[0]\n",
    "        name_up_next = False\n",
    "        continue\n",
    "    # otherwise append message\n",
    "    current_lines.append(line)\n",
    "    generate_chat(current_lines,\n",
    "                  current_name,\n",
    "                  f'{current_time.hour % 12}:{current_time.minute}',\n",
    "                  prof_pic_dict[current_name]).save(f'{path}\\\\chat\\\\{msg_number:03d}{current_name[0]}.png')\n",
    "    # update time and msg_number for saving\n",
    "    current_time+=datetime.timedelta(0,30)\n",
    "    msg_number+=1\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing Individual Messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "messages = ['Nope. <:rooThink:596576798351949847>']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=1777x231>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "im = generate_chat(messages, 'Shregory', '9:43', 'profile_pictures/shregory.PNG')\n",
    "im"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "ename": "OSError",
     "evalue": "cannot open resource",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_17204\\2609584829.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     28\u001b[0m \u001b[0mMESSAGE_POSITIONS\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mMESSAGE_X\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mMESSAGE_Y_INIT\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mMESSAGE_DY\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\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     29\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 30\u001b[1;33m \u001b[0mname_font\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImageFont\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtruetype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'PT Sans Regular.ttf'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNAME_FONT_SIZE\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     31\u001b[0m \u001b[0mtime_font\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImageFont\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtruetype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'PT Sans Regular.ttf'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTIME_FONT_SIZE\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     32\u001b[0m \u001b[0mmessage_font\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mImageFont\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtruetype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'PT Sans Regular.ttf'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mMESSAGE_FONT_SIZE\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\Users\\lukep\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\u001b[0m in \u001b[0;36mtruetype\u001b[1;34m(font, size, index, encoding, layout_engine)\u001b[0m\n\u001b[0;32m    957\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    958\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--> 959\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mfreetype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfont\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    960\u001b[0m     \u001b[1;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    961\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mis_path\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfont\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;32mc:\\Users\\lukep\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\u001b[0m in \u001b[0;36mfreetype\u001b[1;34m(font)\u001b[0m\n\u001b[0;32m    954\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    955\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mfreetype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfont\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--> 956\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mFreeTypeFont\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfont\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlayout_engine\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    957\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    958\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;32mc:\\Users\\lukep\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, font, size, index, encoding, layout_engine)\u001b[0m\n\u001b[0;32m    245\u001b[0m                         \u001b[0mload_from_bytes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\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;32mreturn\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 247\u001b[1;33m             self.font = core.getfont(\n\u001b[0m\u001b[0;32m    248\u001b[0m                 \u001b[0mfont\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlayout_engine\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlayout_engine\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    249\u001b[0m             )\n",
      "\u001b[1;31mOSError\u001b[0m: cannot open resource"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image, ImageFont, ImageDraw \n",
    "import sys\n",
    "\n",
    "# CONSTANTS\n",
    "WORLD_WIDTH = 1777\n",
    "WORLD_Y_INIT = 231\n",
    "WORLD_DY = 80\n",
    "\n",
    "WORLD_HEIGHTS = [WORLD_Y_INIT+i*WORLD_DY for i in range(5)] # for how many messages there are\n",
    "WORLD_COLOR = (54,57,63,255)\n",
    "\n",
    "PROFPIC_WIDTH = 120\n",
    "PROFPIC_POSITION = (36,45)\n",
    "\n",
    "NAME_FONT_SIZE = 50\n",
    "TIME_FONT_SIZE = 30\n",
    "MESSAGE_FONT_SIZE = 50\n",
    "NAME_FONT_COLOR = (255,255,255)\n",
    "TIME_FONT_COLOR = (180,180,180)\n",
    "MESSAGE_FONT_COLOR = (210,210,210)\n",
    "NAME_POSITION = (190,53)\n",
    "TIME_POSITION = (310,67)\n",
    "MESSAGE_X = 190\n",
    "MESSAGE_Y_INIT = 130\n",
    "MESSAGE_DY = 80\n",
    "MESSAGE_POSITIONS = [(MESSAGE_X, MESSAGE_Y_INIT+i*MESSAGE_DY) for i in range(5)]\n",
    "\n",
    "name_font = ImageFont.truetype('PT Sans Regular.ttf', NAME_FONT_SIZE)\n",
    "time_font = ImageFont.truetype('PT Sans Regular.ttf', TIME_FONT_SIZE)\n",
    "message_font = ImageFont.truetype('PT Sans Regular.ttf', MESSAGE_FONT_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "190 310"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "285"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "190+95"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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