eda_anime_1m.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1596415"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_files = glob.glob(\"/home/ai/leo-crawler/data/*.txt\")\n",
    "len(data_files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1596415/1596415 [00:46<00:00, 34026.65it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "prompts = []\n",
    "for file in tqdm(data_files):\n",
    "    with open(file) as f:\n",
    "        prompts.append(f.readline())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['R15+, sekirei, hikari (sekirei), hibiki (sekirei), high resolution, wallpaper, 16:10 aspect ratio, tagme',\n",
       " 'G, mahou shoujo madoka magica, miki sayaka, sakura kyouko, muunyan (yumenekoya), mu-nyako, 1girl, 2girls, blue eyes, blue hair, casual, duo, face, female, food, frown, hands, long hair, mouth hold, multiple girls, pocky, ponytail, red eyes, red hair, serious, short hair, solo, sweets, tied hair, v, photoshop (medium), foreshortening',\n",
       " \"G, kuroko's basketball, animedia, gakken, kuroko tetsuya, kagami taiga, 2boys, ball, basketball uniform, blue hair, clothing, duo, male, multiple boys, red hair, seirin high, sports uniform, sportswear, high resolution, japanese language, text, official art, japanese text, scan, magazine (source)\",\n",
       " 'G, love live! (series), love live! school idol project, minami kotori, clearite, 1girl, animal costume, animal ears, bell, blush, boots, brown eyes, brown hair, clothing, cow bell, female, fluffy legwear, footwear, horns, long hair, navel, open mouth, ribbon-trimmed underwear, ribbon trim, sheep costume, sheep ears, sheep horns, sitting, solo, underwear, high resolution',\n",
       " 'R15+, vocaloid, hatsune miku, mochimomomo, 1girl, aqua eyes, aqua hair, ass, black legwear, black thighhighs, blush, bottomless, bottoms down, breath, clothes pull, clothing, detached sleeves, earmuffs, embarrassed, female, from behind, legwear, long hair, looking back, neckwear, panties down, pantsu, panty pull, red neckwear, red scarf, scarf, skirt, solo, thighhighs, thighs, tied hair, twintails, underwear, underwear pull, upskirt, very long hair, zettai ryouiki, simple background, white background',\n",
       " 'G, kill la kill, kirby (series), kirby, jakuzure nonon, jakuzure nonon (cosplay), kojima keisuke, cosplay, blonde hair, blue eyes, breasts, clothing, copy ability, hat, headwear, no humans, shako cap, skull, solo, staff, 4:3 aspect ratio, bad twitter id',\n",
       " 'R15+, idolmaster, idolmaster (classic), kikuchi makoto, nekopuchi, 1girl, ahoge, bare shoulders, bikini, bikini top, black eyes, black hair, blush, brown hair, clavicle, clothing, female, female only, looking at viewer, open mouth, short hair, solo, straight hair, striped, striped bikini, striped print, striped swimsuit, swimsuit, upper body, simple background, bust',\n",
       " 'G, original, sadakage, 1girl, ass, bare shoulders, belt, blue eyes, boots, bracelet, breasts, bridal garter, brown hair, casual, clothing, cross, denim, denim shorts, female, fingernails, footwear, garter, green eyes, high heels, jewelry, large breasts, lipstick, long fingernails, long hair, long sleeves, makeup, midriff, nail art, nail polish, navel, necklace, no bra, pendant, shoes, shorts, sleeves past wrists, smile, solo, thigh strap, thighhighs, twisted torso, very long hair, photoshop (medium)',\n",
       " 'G, manyako (mohumohu), manyako, clothing, dress, high resolution, tagme, potential duplicate',\n",
       " 'G, blade & soul, lyn (blade & soul), sosan, 1girl, animal ear fluff, animal ears, ass, blue eyes, chair, classroom, clothing, day, desk, earrings, fang, female, fox ears, from behind, indoors, jewelry, kneeling, long hair, looking back, school desk, short shorts, shorts, silver hair, sky, smile, solo, tail, white hair, window, high resolution, very high resolution, photoshop (medium)']"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prompts[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "levels = {}\n",
    "for prompt in prompts:\n",
    "    level = prompt.split(\" \")[0].strip()\n",
    "    levels[level] = levels.get(level, 0) + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the distribution of levels in pie\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(10, 10))\n",
    "plt.pie(list(levels.values()), labels=list(levels.keys()), autopct='%1.1f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"/home/ai/edward/luantt/data/animagine_character.txt\") as f:\n",
    "    animagine_characters = f.readlines()\n",
    "animagine_characters = [character.strip() for character in animagine_characters]\n",
    "animagine_character_dicts = []\n",
    "for character in animagine_characters:\n",
    "    character = character.split(\",\") \n",
    "    character = [item.strip() for item in character]\n",
    "    char_type, char_name, series = character\n",
    "    char_name = char_name.split(\" \\(\")[0]\n",
    "    series = series.split(\" \\(\")[0]\n",
    "    animagine_character_dicts.append({\"type\": char_type, \"name\": char_name, \"series\": series})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': '1girl', 'name': 'artoria pendragon', 'series': 'fate'},\n",
       " {'type': '1girl', 'name': 'mash kyrielight', 'series': 'fate/grand order'},\n",
       " {'type': '1girl', 'name': 'ganyu', 'series': 'genshin impact'},\n",
       " {'type': '1girl', 'name': 'raiden shogun', 'series': 'genshin impact'},\n",
       " {'type': '1girl', 'name': \"jeanne d'arc alter\", 'series': 'fate/grand order'},\n",
       " {'type': '1girl', 'name': 'houshou marine', 'series': 'hololive'},\n",
       " {'type': '1girl', 'name': 'fujimaru ritsuka', 'series': 'fate/grand order'},\n",
       " {'type': '1boy', 'name': 'fujimaru ritsuka', 'series': 'fate/grand order'},\n",
       " {'type': '1girl', 'name': 'lumine', 'series': 'genshin impact'},\n",
       " {'type': '1girl', 'name': 'abigail williams', 'series': 'fate/grand order'}]"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animagine_character_dicts[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2880\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2016"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animagine_characters = [character[\"name\"] for character in animagine_character_dicts]\n",
    "print(len(animagine_characters))\n",
    "animagine_characters = list(set(animagine_characters))\n",
    "# animagine_characters = [character.strip() for character in animagine_characters if character != \"\"]\n",
    "len(animagine_characters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ppsh-41',\n",
       " 'kenmochi touko',\n",
       " 'gascogne',\n",
       " 'hermione',\n",
       " 'pollux',\n",
       " 'hoshizora rin',\n",
       " 'kumbhira',\n",
       " 'tokoyami towa',\n",
       " 'yuni',\n",
       " 'phantom']"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "animagine_characters[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "def count_overlap_characters(prompt, ref_characters):\n",
    "    overlap_characters = {}\n",
    "    for character in ref_characters:\n",
    "        character = character.split(\" \")\n",
    "        if len(character) > 1:\n",
    "            character = \" \".join(character)\n",
    "            if character in prompt:\n",
    "                overlap_characters[character] = overlap_characters.get(character, 0) + 1\n",
    "        else:\n",
    "            character = character[0]\n",
    "            if character in re.split(r'[ ,()]', prompt):\n",
    "                overlap_characters[character] = overlap_characters.get(character, 0) + 1\n",
    "    return overlap_characters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000000/1000000 [10:50<00:00, 1537.79it/s]\n"
     ]
    }
   ],
   "source": [
    "# check how many characters are in the prompts\n",
    "import re\n",
    "from multiprocessing import Pool\n",
    "from functools import partial\n",
    "N_PROMPT = 1000000\n",
    "with Pool(32) as p:\n",
    "    overlap_characters = list(tqdm(p.imap(partial(count_overlap_characters, ref_characters=animagine_characters), prompts[:N_PROMPT]), total=len(prompts[:N_PROMPT])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge overlap_characters\n",
    "from collections import Counter\n",
    "overlap_characters_ = Counter()\n",
    "for character in overlap_characters:\n",
    "    overlap_characters_.update(character)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Characters: 960 / 2016 = 47.62%\n",
      "Total prompts that be covered: 627635 / 1000000 = 62.76%\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total Characters: {len(overlap_characters_)} / {len(animagine_characters)} = {len(overlap_characters_)/len(animagine_characters)*100:.2f}%\")\n",
    "sum_all_count = 0\n",
    "for character in overlap_characters_:\n",
    "    sum_all_count += overlap_characters_[character]\n",
    "print(f\"Total prompts that be covered: {sum_all_count} / {N_PROMPT} = {sum_all_count/N_PROMPT*100:.2f}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sort by frequency, plot the distribution of overlap_characters in bar of top 50\n",
    "import matplotlib.pyplot as plt\n",
    "overlap_characters_ = dict(sorted(overlap_characters_.items(), key=lambda item: item[1], reverse=True))\n",
    "plt.figure(figsize=(20, 10))\n",
    "plt.bar(list(overlap_characters_.keys())[:50], list(overlap_characters_.values())[:50])\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}