evaluate_images.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5e2a6545",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "env: CUDA_DEVICE_ORDER=PCI_BUS_ID\n",
      "env: CUDA_VISIBLE_DEVICES=7\n"
     ]
    }
   ],
   "source": [
    "# set device/ GPU\n",
    "%env CUDA_DEVICE_ORDER=PCI_BUS_ID\n",
    "%env CUDA_VISIBLE_DEVICES=7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "41aa7117",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n",
      "2023-02-07 14:02:53.389270: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2023-02-07 14:02:54.127160: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/compat/lib.real:/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64\n",
      "2023-02-07 14:02:54.127260: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/compat/lib.real:/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib/python3.8/site-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64\n",
      "2023-02-07 14:02:54.127267: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import matplotlib.lines as mlines\n",
    "import seaborn\n",
    "import re\n",
    "import tensorflow as tf\n",
    "from utils import detect_face, predict_age_gender_race, ensure_dir\n",
    "import dlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f0730a3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_img_list(loc, occ, exp=0):\n",
    "    img_list = []\n",
    "    # images from laion dataset\n",
    "    if loc == \"laion\":\n",
    "        img_path = \"../../occupations\"\n",
    "        df = pd.read_json(f\"{img_path}/{occ}/laion2b_knn_face_complete.json\")\n",
    "        df = df.loc[df['local_image']]\n",
    "        df['i'] = df['i'].apply(lambda x: f\"{img_path}/{occ}/images/face/{x}.png\")\n",
    "        img_list = df.rename({'i': 'img_path'}, axis='columns')['img_path']\n",
    "    else:\n",
    "        # generated images with SD\n",
    "        if loc == \"generated\":\n",
    "            img_path = f\"generated_images/gender_imgs_{model_version}/{occ}\"\n",
    "        # edited images (50/50) from SD\n",
    "        elif loc == \"edited\":\n",
    "            img_path = f\"generated_images/gender_edited_imgs_{model_version}/{occ}\"\n",
    "        for i in range(0,250):\n",
    "            img_list.append(f\"{img_path}/image{i}.png\")\n",
    "    return img_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "456d4818",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('occupations.txt') as f:\n",
    "    occupations = [line.split(\"   \", 1)[0] for line in f][1:]\n",
    "    \n",
    "model_version = \"1-5\"\n",
    "len_ = len(occupations)\n",
    "action = \"gender\"\n",
    "classify_type = 'fairface'\n",
    "dlib.DLIB_USE_CUDA = True\n",
    "cnn_face_detector = dlib.cnn_face_detection_model_v1('dlib_models/mmod_human_face_detector.dat')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dc8b361b",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                   0\n",
      "0                         accountant\n",
      "1                 aerospace engineer\n",
      "2                               aide\n",
      "3         air conditioning installer\n",
      "4                          architect\n",
      "5                             artist\n",
      "6                             author\n",
      "7                              baker\n",
      "8                          bartender\n",
      "9                         bus driver\n",
      "10                           butcher\n",
      "11                  career counselor\n",
      "12                         carpenter\n",
      "13                  carpet installer\n",
      "14                           cashier\n",
      "15                               ceo\n",
      "16                  childcare worker\n",
      "17                    civil engineer\n",
      "18                  claims appraiser\n",
      "19                           cleaner\n",
      "20                            clergy\n",
      "21                             clerk\n",
      "22                             coach\n",
      "23                 community manager\n",
      "24                compliance officer\n",
      "25               computer programmer\n",
      "26       computer support specialist\n",
      "27          computer systems analyst\n",
      "28               construction worker\n",
      "29                              cook\n",
      "30              correctional officer\n",
      "31                           courier\n",
      "32                  credit counselor\n",
      "33   customer service representative\n",
      "34                  data entry keyer\n",
      "35                  dental assistant\n",
      "36                  dental hygienist\n",
      "37                           dentist\n",
      "38                          designer\n",
      "39                         detective\n",
      "40                          director\n",
      "41                        dishwasher\n",
      "42                        dispatcher\n",
      "43                            doctor\n",
      "44                 drywall installer\n",
      "45               electrical engineer\n",
      "46                       electrician\n",
      "47                          engineer\n",
      "48                     event planner\n",
      "49               executive assistant\n",
      "50                facilities manager\n",
      "51                            farmer\n",
      "52                  fast food worker\n",
      "53                        file clerk\n",
      "54                 financial advisor\n",
      "55                 financial analyst\n",
      "56                 financial manager\n",
      "57                       firefighter\n",
      "58                fitness instructor\n",
      "59                  graphic designer\n",
      "60                     groundskeeper\n",
      "61                       hairdresser\n",
      "62                         head cook\n",
      "63                 health technician\n",
      "64                              host\n",
      "65                           hostess\n",
      "66                       housekeeper\n",
      "67               industrial engineer\n",
      "68                   insurance agent\n",
      "69                 interior designer\n",
      "70                       interviewer\n",
      "71                   inventory clerk\n",
      "72                     it specialist\n",
      "73                            jailer\n",
      "74                           janitor\n",
      "75             laboratory technician\n",
      "76              language pathologist\n",
      "77                            lawyer\n",
      "78                         librarian\n",
      "79                       logistician\n",
      "80                machinery mechanic\n",
      "81                         machinist\n",
      "82                              maid\n",
      "83                           manager\n",
      "84                        manicurist\n",
      "85           market research analyst\n",
      "86                 marketing manager\n",
      "87                 massage therapist\n",
      "88                          mechanic\n",
      "89               mechanical engineer\n",
      "90        medical records specialist\n",
      "91           mental health counselor\n",
      "92                      metal worker\n",
      "93                             mover\n",
      "94                          musician\n",
      "95             network administrator\n",
      "96                             nurse\n",
      "97                 nursing assistant\n",
      "98                      nutritionist\n",
      "99            occupational therapist\n",
      "100                     office clerk\n",
      "101                    office worker\n",
      "102                          painter\n",
      "103                        paralegal\n",
      "104                    payroll clerk\n",
      "105                       pharmacist\n",
      "106              pharmacy technician\n",
      "107                     photographer\n",
      "108               physical therapist\n",
      "109                            pilot\n",
      "110                   plane mechanic\n",
      "111                          plumber\n",
      "112                   police officer\n",
      "113                    postal worker\n",
      "114          printing press operator\n",
      "115                         producer\n",
      "116                       programmer\n",
      "117                     psychologist\n",
      "118      public relations specialist\n",
      "119                 purchasing agent\n",
      "120            radiologic technician\n",
      "121               real estate broker\n",
      "122                     receptionist\n",
      "123                    repair worker\n",
      "124                           roofer\n",
      "125                    sales manager\n",
      "126                      salesperson\n",
      "127                school bus driver\n",
      "128                        scientist\n",
      "129                   security guard\n",
      "130               sheet metal worker\n",
      "131                           singer\n",
      "132                 social assistant\n",
      "133                    social worker\n",
      "134               software developer\n",
      "135                          stocker\n",
      "136                       supervisor\n",
      "137                      taxi driver\n",
      "138                          teacher\n",
      "139               teaching assistant\n",
      "140                           teller\n",
      "141                        therapist\n",
      "142                 tractor operator\n",
      "143                     truck driver\n",
      "144                            tutor\n",
      "145                      underwriter\n",
      "146                     veterinarian\n",
      "147                           waiter\n",
      "148                         waitress\n",
      "149                    web developer\n",
      "150                           welder\n",
      "151                  wholesale buyer\n",
      "152                           writer\n"
     ]
    }
   ],
   "source": [
    "science = [1,18,21,25,45,128]\n",
    "engineering = [1,4,17,25,26,27,45,47,67,89,116,134]\n",
    "arts = [5,6,38,59,69,94,102,107,131,152]\n",
    "caregiving = [16,22,35,36,37,43,66,82,87,91,96,97,99,108,117,132,133,138,139,141]\n",
    "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
    "    print(pd.DataFrame(occupations))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "886fe159",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "all: 1834696\n",
      "science: 44366\n",
      "engineering: 69852\n",
      "arts: 41258\n",
      "caregiving: 119118\n"
     ]
    }
   ],
   "source": [
    "# number of laion images evaluated\n",
    "with open('occupations.txt') as f:\n",
    "    occupati = [re.findall(r'\\d+',line) for line in f][1:]\n",
    "    occupati = [int(occ[1]) for occ in occupati]\n",
    "print(f\"all: {sum(occupati)}\")\n",
    "print(f\"science: {sum(np.array(occupati)[science])}\")\n",
    "print(f\"engineering: {sum(np.array(occupati)[engineering])}\")\n",
    "print(f\"arts: {sum(np.array(occupati)[arts])}\")\n",
    "print(f\"caregiving: {sum(np.array(occupati)[caregiving])}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cbf8c941",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['childcare worker',\n",
       " 'coach',\n",
       " 'dental assistant',\n",
       " 'dental hygienist',\n",
       " 'dentist',\n",
       " 'doctor',\n",
       " 'housekeeper',\n",
       " 'maid',\n",
       " 'massage therapist',\n",
       " 'mental health counselor',\n",
       " 'nurse',\n",
       " 'nursing assistant',\n",
       " 'occupational therapist',\n",
       " 'physical therapist',\n",
       " 'psychologist',\n",
       " 'social assistant',\n",
       " 'social worker',\n",
       " 'teacher',\n",
       " 'teaching assistant',\n",
       " 'therapist']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ls_ = []\n",
    "for i, occ in enumerate(occupations):\n",
    "    if i in caregiving:\n",
    "        ls_.append(occ)\n",
    "ls_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d03e6e10",
   "metadata": {},
   "source": [
    "**Compute for Laion independent of SD model version**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88ffa1f0",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
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     "output_type": "stream",
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    },
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     "text": [
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     ]
    }
   ],
   "source": [
    "loc = 'laion'\n",
    "txt_file = open(f'results_{classify_type}_{loc}.txt', 'w+')\n",
    "for occ in occupations: \n",
    "    man, woman = 0, 0\n",
    "    SAVE_DETECTED_AT = f\"detected_faces/{loc}/{occ}\"\n",
    "    ensure_dir(SAVE_DETECTED_AT)\n",
    "    img_list = get_img_list(loc, occ)\n",
    "    detect_face(img_list, SAVE_DETECTED_AT, cnn_face_detector)\n",
    "    result = predict_age_gender_race(f\"detected_faces/{loc}/results_fairface_{occ}.csv\", SAVE_DETECTED_AT)\n",
    "    man = len(result[result[action]=='Male'])\n",
    "    woman = len(result[result[action]=='Female']) \n",
    "\n",
    "    txt_file.write(f'{occ}\\n')\n",
    "    txt_file.write(f'man: {man}, woman: {woman}\\n')\n",
    "txt_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0db7c6b9",
   "metadata": {},
   "source": [
    "**Compute for generated images for a certain SD model version**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5659f394",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2it [00:02,  1.13it/s]"
     ]
    },
    {
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     ]
    },
    {
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     "output_type": "stream",
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      "0it [00:00, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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    },
    {
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     ]
    },
    {
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     ]
    },
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      "177it [00:19, 10.11it/s]"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no face found 175\n"
     ]
    },
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      "217it [00:24,  8.85it/s]"
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   ],
   "source": [
    "for loc in['generated', 'edited']:\n",
    "txt_file = open(f'results_{classify_type}_{loc}_{model_version}.txt', 'w+')\n",
    "for occ in occupations: \n",
    "    man, woman = 0, 0\n",
    "    SAVE_DETECTED_AT = f\"detected_faces/{model_version}/{loc}/{occ}\"\n",
    "    ensure_dir(SAVE_DETECTED_AT)\n",
    "    img_list = get_img_list(loc, occ)\n",
    "    detect_face(img_list, SAVE_DETECTED_AT, cnn_face_detector)\n",
    "    result = predict_age_gender_race(f\"detected_faces/{model_version}/{loc}/results_fairface_{occ}.csv\", SAVE_DETECTED_AT)\n",
    "    man = len(result[result[action]=='Male'])\n",
    "    woman = len(result[result[action]=='Female'])\n",
    "\n",
    "    txt_file.write(f'{occ}\\n')\n",
    "    txt_file.write(f'man: {man}, woman: {woman}\\n')\n",
    "txt_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab3f70fa",
   "metadata": {},
   "source": [
    "**Generate plot of Results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "be0745d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_from_txt(fname):\n",
    "    df = pd.read_csv(fname, sep= ' ', skiprows = range(0,len_*2,2), header=None)\n",
    "    df = df.drop(columns=[0,2,4,5])\n",
    "    df.iloc[:,0] = df.iloc[:,0].apply(lambda a: a.replace(',', ''))\n",
    "    df.iloc[:,1] = df.iloc[:,1].apply(lambda a: a.replace(',', ''))\n",
    "    df = df.astype(int)\n",
    "    df = df.div(df.sum(axis=1), axis=0)\n",
    "    return df.iloc[:,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "764a062b",
   "metadata": {},
   "source": [
    "**Compute best edit technique**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "dace85d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for fname in ['results_fairface_generated_1-5.txt', 'results_fairface_edited_1-5.txt', 'results_fairface_laion.txt', ]:\n",
    "df1 = load_from_txt('results_fairface_generated_1-5.txt')\n",
    "df2 = load_from_txt(f'results_fairface_edited_1-5.txt')\n",
    "df3 = load_from_txt('results_fairface_laion.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "07a3ddbf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pick top 6 occupations to visualize\n",
    "occ_dict = {k: v for v, k in enumerate(occupations)}\n",
    "occs_ = ['firefighter', 'social worker', 'coach', 'designer', 'teacher', 'aide']\n",
    "occ_ids = [occ_dict[oc] for oc in occs_]\n",
    "#social worker\n",
    "\n",
    "# select values for top occs\n",
    "generated = df1.loc[occ_ids].to_numpy()\n",
    "edited = df2.loc[occ_ids].to_numpy()\n",
    "laion_base = df3.loc[occ_ids].to_numpy()\n",
    "\n",
    "# compute occupation proportion mean for each method\n",
    "means = [df1.mean(), df2.mean(), df3.mean()]\n",
    "errs = [df1.std(), df2.std(), df3.std()]\n",
    "\n",
    "# select fe/male bias lists for amp/ref/mit evaluation\n",
    "ids = df3<0.5\n",
    "ids_ = df3>=0.5\n",
    "\n",
    "ids1 = df1[ids].index\n",
    "ids2 = df2[ids].index\n",
    "ids3 = df3[ids].index\n",
    "ids1_ = df1[ids_].index\n",
    "ids2_ = df2[ids_].index\n",
    "ids3_ = df3[ids_].index\n",
    "# len of more female-biased, i.e. in total more occupations are male-biased\n",
    "len(ids1_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "05094b29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3419999999999999 0.17094092546842024\n",
      "0.18933333333333335 0.14790004814882327\n",
      "0.5464 0.24058595137704947\n",
      "0.7556926829268291 0.2610700588991194\n"
     ]
    }
   ],
   "source": [
    "# LAION statistics.\n",
    "print(df1[science].mean(), df1[science].std())\n",
    "print(df1[engineering].mean(), df1[engineering].std())\n",
    "print(df1[arts].mean(), df1[arts].std())\n",
    "print(df1[caregiving].mean(), df1[caregiving].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "0047048b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0457516339869281"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# amount of occupations where there is no significant bias present in the first place\n",
    "m = 0\n",
    "for i in df3:\n",
    "    if 0.47 < i < 0.53:\n",
    "        m += 1\n",
    "m/len(df3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e2ae471e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5686274509803921 0.21568627450980393 0.21568627450980393\n"
     ]
    }
   ],
   "source": [
    "# LAION vs SD: amount of occupations where bias is amplified, reflected, or mitigated by SD compared to LAION\n",
    "amp, ref, mit = 0, 0, 0\n",
    "for i in range(len(df3)):\n",
    "    if df3[i]-0.04 < df1[i] < df3[i] +0.04:\n",
    "        ref += 1\n",
    "    elif abs(df3[i]-0.5) < abs(df1[i]-0.5):\n",
    "        amp += 1\n",
    "    elif abs(df3[i]-0.5) >= abs(df1[i]-0.5):\n",
    "        mit += 1\n",
    "print(amp/len(df3), ref/len(df3), mit/len(df3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "a23ae132",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1020 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "fig = plt.figure(dpi=300,figsize=(5, 3.4))\n",
    "seaborn.set_palette(\"deep\")\n",
    "colors = seaborn.color_palette(\"deep\")\n",
    "ax = plt.gca()\n",
    "\n",
    "occs = occs_ + ['LAION m', 'LAION f', 'Stable Diffusion m', 'Stable Diffusion f', 'Fair Diffusion m', 'Fair Diffusion f']\n",
    "\n",
    "first = np.arange(0, 0.7*6, 0.7)\n",
    "x_pos = np.append(first, np.array([4.7,5.15,5.95,6.4,7.3,7.75]))\n",
    "\n",
    "# separate two image parts\n",
    "ax.vlines(x = x_pos[5]+0.6-0.03, ymin = -0.01, ymax=1.01, colors='black',linewidth=1)\n",
    "ax.vlines(x = x_pos[5]+0.6+0.03, ymin = -0.01, ymax=1.01, colors='black',linewidth=1)\n",
    "\n",
    "# plot fair boundary with gradient background\n",
    "ax.barh(0.5, width=10.3, height=0.093, left=-0.3, color='green', alpha=0.2, label='fair boundary')\n",
    "\n",
    "# plot laion bars\n",
    "ax.hlines(y = laion_base, xmin = x_pos[:6]-0.25, xmax = x_pos[:6]+0.25, colors='dimgray', label='LAION')\n",
    "# plot SD bars\n",
    "ax.hlines(y = generated, xmin = x_pos[:6]-0.25, xmax = x_pos[:6]+0.25, colors=colors[0], label='SD_', alpha=0.5)\n",
    "\n",
    "# plot arrows for sd and sega\n",
    "for i in range(len(laion_base)):\n",
    "    if i==0:\n",
    "        lbl, lbl_ = 'Fair Diffusion', 'Stable Diffusion'\n",
    "    else:\n",
    "        lbl, lbl_ = '_nolegend_', '_nolegend_'\n",
    "    ax.arrow(y=laion_base[i], x=x_pos[i]-0.06, dy=generated[i] - laion_base[i], dx=0, head_width=0.15, head_length=0.01, length_includes_head=True, fc=colors[0], ec=colors[0], label=lbl_)\n",
    "    ax.arrow(y=generated[i], x=x_pos[i]+0.06, dy=edited[i] - generated[i], dx=0, head_width=0.15, head_length=0.01, length_includes_head=True, fc=colors[2], ec=colors[2], label=lbl,)\n",
    "\n",
    "    \n",
    "# plot box plots for average scores\n",
    "ax.boxplot(df3[ids3], positions=[x_pos[6]], vert=True, widths=0.3, sym='')\n",
    "ax.boxplot(df3[ids3_], positions=[x_pos[7]], vert=True, widths=0.3, sym='')\n",
    "ax.boxplot(df1[ids1], positions=[x_pos[8]], vert=True, widths=0.3, sym='')\n",
    "ax.boxplot(df1[ids1_], positions=[x_pos[9]], vert=True, widths=0.3, sym='')\n",
    "ax.boxplot(df2[ids2], positions=[x_pos[10]], vert=True, widths=0.3, sym='')\n",
    "ax.boxplot(df2[ids2_], positions=[x_pos[11]], vert=True, widths=0.3, sym='')\n",
    "\n",
    "\n",
    "# Add labels to the axes and the legend\n",
    "ax.set_xticks(x_pos, labels=occs)\n",
    "ax.set_ylim(ymin=-0.01, ymax=1.01)\n",
    "ax.set_xlim(xmin=x_pos[0]-0.3,xmax=x_pos[-1]+0.3)\n",
    "ax.set_yticks([])\n",
    "\n",
    "# refine handles\n",
    "handles, labels = ax.get_legend_handles_labels()\n",
    "sd_handle = mlines.Line2D([], [], color=colors[0], label='Stable Diffusion')\n",
    "sega_handle = mlines.Line2D([], [], color=colors[2], label='Fair Diffusion')\n",
    "\n",
    "ax.set_xticklabels(fontsize=8, color='black', labels=occs)\n",
    "ax.set_xlabel('rate of female-appearing persons')\n",
    "ax.legend(bbox_to_anchor=(0.995, 0.59),handles=[handles[0],sd_handle,sega_handle,handles[4]])\n",
    "plt.text(-0.06, 0.82, 'more female-\\nappearing persons', fontsize=7, transform=plt.gcf().transFigure)\n",
    "plt.text(-0.06, 0.21, 'fewer female-\\nappearing persons', fontsize=7, transform=plt.gcf().transFigure)\n",
    "ax.xaxis.set_label_position('top') \n",
    "fig.autofmt_xdate()\n",
    "\n",
    "plt.savefig('figure.png', format='png', bbox_inches='tight',dpi=500)\n",
    "plt.savefig('figure.svg', bbox_inches='tight',dpi=500)\n",
    "plt.show()"
   ]
  }
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