check_inference_gender.ipynb

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   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import random"
   ]
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    "img_dir_path = '/opt/ml/input/data/eval/images/'"
   ]
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   "source": [
    "file_name = 'output_gender'\n",
    "df = pd.read_csv(f'./output_gender/{file_name}.csv')\n",
    "df.head()"
   ]
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   "source": [
    "gender = 1    # ~30 : 0  //  30~60 : 1  //  60~ : 2 \n",
    "check_stat = ['~30', '30~60', '60~']\n",
    "num_imgs=10\n",
    "img_info = df[df['ans']==gender].sample(num_imgs)\n",
    "file_names = img_info['ImageID'].tolist()\n",
    "imgs=[]\n",
    "for file_name in file_names:\n",
    "    imgs.append(plt.imread(img_dir_path + file_name))\n",
    "col = 4\n",
    "row = num_imgs // (col-1)\n",
    "\n",
    "fig = plt.figure(figsize=(25, row*5))\n",
    "plt.title(check_stat[gender]], fontsize=40)\n",
    "plt.axis('off')\n",
    "for i in range(num_imgs):\n",
    "    ax = fig.add_subplot(row, col+1, i+1)\n",
    "    plt.axis('off')\n",
    "    ax.imshow(imgs[i])\n",
    "plt.show()"
   ]
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      "5351 6057 1192\n"
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   ],
   "source": [
    "print(len(df[df['ans']==0]), len(df[df['ans']==1]), len(df[df['ans']==2]))"
   ]
  }
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