{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import os \n",
"import glob\n",
"from datasets import Dataset\n",
"\n",
"path_folder = \"report/result/IJBC\"\n",
"\n",
"csv_score_files = glob.glob(os.path.join(path_folder, \"**/*verification*.csv\"))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"dataframe = None\n",
"for csv_score_file in csv_score_files: \n",
" if dataframe is None:\n",
" dataframe = pd.read_csv(csv_score_file)\n",
" else: \n",
" dataframe.loc[len(dataframe.index)] = pd.read_csv(csv_score_file).iloc[0]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_ir50_webface4m-IJBC</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_vsait17_0-IJBC</td>\n",
" <td>23.12</td>\n",
" <td>33.76</td>\n",
" <td>46.85</td>\n",
" <td>61.97</td>\n",
" <td>77.36</td>\n",
" <td>90.88</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_digiface1m_0-IJBC</td>\n",
" <td>16.44</td>\n",
" <td>24.13</td>\n",
" <td>35.80</td>\n",
" <td>50.66</td>\n",
" <td>67.07</td>\n",
" <td>83.93</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ada_digiface1m_7-IJBC</td>\n",
" <td>24.21</td>\n",
" <td>36.11</td>\n",
" <td>48.52</td>\n",
" <td>63.20</td>\n",
" <td>77.58</td>\n",
" <td>90.61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ada_digiface1m_8gpu_0-IJBC</td>\n",
" <td>0.02</td>\n",
" <td>0.02</td>\n",
" <td>0.07</td>\n",
" <td>49.45</td>\n",
" <td>68.60</td>\n",
" <td>83.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>ada_digiface1m_codeformer_0-IJBC</td>\n",
" <td>25.83</td>\n",
" <td>33.56</td>\n",
" <td>47.35</td>\n",
" <td>63.38</td>\n",
" <td>78.36</td>\n",
" <td>91.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>ada_digiface1m_1-IJBC</td>\n",
" <td>15.76</td>\n",
" <td>26.65</td>\n",
" <td>39.72</td>\n",
" <td>55.27</td>\n",
" <td>71.67</td>\n",
" <td>88.12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>ada_digiface1m_codeformer_1-IJBC</td>\n",
" <td>19.82</td>\n",
" <td>27.72</td>\n",
" <td>41.01</td>\n",
" <td>58.05</td>\n",
" <td>75.09</td>\n",
" <td>89.57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_0-IJBC</td>\n",
" <td>17.16</td>\n",
" <td>28.12</td>\n",
" <td>41.10</td>\n",
" <td>57.72</td>\n",
" <td>74.02</td>\n",
" <td>89.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_1-IJBC</td>\n",
" <td>17.31</td>\n",
" <td>28.81</td>\n",
" <td>42.91</td>\n",
" <td>59.87</td>\n",
" <td>75.92</td>\n",
" <td>90.74</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>ada_casiawebface_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>ada_idffface_ca-cpd25_0-IJBC</td>\n",
" <td>33.19</td>\n",
" <td>44.43</td>\n",
" <td>57.70</td>\n",
" <td>72.21</td>\n",
" <td>85.92</td>\n",
" <td>95.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>ada_idffface_ca-cpd25_8gpu_0-IJBC</td>\n",
" <td>25.24</td>\n",
" <td>39.12</td>\n",
" <td>54.68</td>\n",
" <td>70.63</td>\n",
" <td>85.27</td>\n",
" <td>95.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>ada_casiawebface_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>ada_casiawebface_8gpu_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>ada_dcface_1-2M_oversample_1-IJBC</td>\n",
" <td>41.09</td>\n",
" <td>60.51</td>\n",
" <td>73.22</td>\n",
" <td>83.80</td>\n",
" <td>91.86</td>\n",
" <td>97.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>ada_dcface_1-2M_oversample_8gpu_0-IJBC</td>\n",
" <td>40.68</td>\n",
" <td>56.64</td>\n",
" <td>72.16</td>\n",
" <td>83.79</td>\n",
" <td>92.09</td>\n",
" <td>97.23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>ada_casiawebface_8gpu_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>ada_casiawebface_adaface_repo-IJBC</td>\n",
" <td>0.16</td>\n",
" <td>0.85</td>\n",
" <td>15.79</td>\n",
" <td>74.55</td>\n",
" <td>94.92</td>\n",
" <td>98.48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>ada_digiface1m_8gpu_0_roc-IJBC</td>\n",
" <td>0.02</td>\n",
" <td>0.02</td>\n",
" <td>0.07</td>\n",
" <td>49.45</td>\n",
" <td>68.60</td>\n",
" <td>83.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0_roc-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_0_roc-IJBC</td>\n",
" <td>17.16</td>\n",
" <td>28.12</td>\n",
" <td>41.10</td>\n",
" <td>57.72</td>\n",
" <td>74.02</td>\n",
" <td>89.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>ada_dcface_1-2M_oversample_8gpu_0_roc-IJBC</td>\n",
" <td>40.68</td>\n",
" <td>56.64</td>\n",
" <td>72.16</td>\n",
" <td>83.79</td>\n",
" <td>92.09</td>\n",
" <td>97.23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>ada_idffface_ca-cpd25_8gpu_0_roc-IJBC</td>\n",
" <td>25.24</td>\n",
" <td>39.12</td>\n",
" <td>54.68</td>\n",
" <td>70.63</td>\n",
" <td>85.27</td>\n",
" <td>95.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>ada_webface4m_roc-IJBC</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.40</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 0.0001 0.001 \\\n",
"0 ada_ir50_webface4m-IJBC 91.78 95.22 96.98 98.14 \n",
"1 ada_digiface1m_vsait17_0-IJBC 23.12 33.76 46.85 61.97 \n",
"2 ada_digiface1m_0-IJBC 16.44 24.13 35.80 50.66 \n",
"3 ada_digiface1m_7-IJBC 24.21 36.11 48.52 63.20 \n",
"4 ada_digiface1m_8gpu_0-IJBC 0.02 0.02 0.07 49.45 \n",
"5 ada_digiface1m_codeformer_0-IJBC 25.83 33.56 47.35 63.38 \n",
"6 ada_digiface1m_1-IJBC 15.76 26.65 39.72 55.27 \n",
"7 ada_digiface1m_codeformer_1-IJBC 19.82 27.72 41.01 58.05 \n",
"8 ada_digiface1m_codeformer_8gpu_0-IJBC 25.52 36.17 49.28 63.78 \n",
"9 ada_digiface1m_vsait17_8gpu_0-IJBC 17.16 28.12 41.10 57.72 \n",
"10 ada_digiface1m_vsait17_8gpu_1-IJBC 17.31 28.81 42.91 59.87 \n",
"11 ada_casiawebface_1-IJBC 0.08 0.24 2.47 28.07 \n",
"12 ada_idffface_ca-cpd25_0-IJBC 33.19 44.43 57.70 72.21 \n",
"13 ada_idffface_ca-cpd25_8gpu_0-IJBC 25.24 39.12 54.68 70.63 \n",
"14 ada_casiawebface_0-IJBC 0.08 0.24 2.47 28.07 \n",
"15 ada_casiawebface_8gpu_0-IJBC 0.08 0.26 2.99 39.77 \n",
"16 ada_dcface_1-2M_oversample_1-IJBC 41.09 60.51 73.22 83.80 \n",
"17 ada_dcface_1-2M_oversample_8gpu_0-IJBC 40.68 56.64 72.16 83.79 \n",
"18 ada_casiawebface_8gpu_1-IJBC 0.08 0.26 2.99 39.77 \n",
"19 ada_casiawebface_adaface_repo-IJBC 0.16 0.85 15.79 74.55 \n",
"20 ada_digiface1m_8gpu_0_roc-IJBC 0.02 0.02 0.07 49.45 \n",
"21 ada_digiface1m_codeformer_8gpu_0_roc-IJBC 25.52 36.17 49.28 63.78 \n",
"22 ada_digiface1m_vsait17_8gpu_0_roc-IJBC 17.16 28.12 41.10 57.72 \n",
"23 ada_dcface_1-2M_oversample_8gpu_0_roc-IJBC 40.68 56.64 72.16 83.79 \n",
"24 ada_idffface_ca-cpd25_8gpu_0_roc-IJBC 25.24 39.12 54.68 70.63 \n",
"25 ada_webface4m_roc-IJBC 91.78 95.22 96.98 98.14 \n",
"\n",
" 0.01 0.1 \n",
"0 98.84 99.40 \n",
"1 77.36 90.88 \n",
"2 67.07 83.93 \n",
"3 77.58 90.61 \n",
"4 68.60 83.17 \n",
"5 78.36 91.21 \n",
"6 71.67 88.12 \n",
"7 75.09 89.57 \n",
"8 78.35 91.37 \n",
"9 74.02 89.54 \n",
"10 75.92 90.74 \n",
"11 79.21 94.77 \n",
"12 85.92 95.41 \n",
"13 85.27 95.46 \n",
"14 79.21 94.77 \n",
"15 88.47 98.16 \n",
"16 91.86 97.28 \n",
"17 92.09 97.23 \n",
"18 88.47 98.16 \n",
"19 94.92 98.48 \n",
"20 68.60 83.17 \n",
"21 78.35 91.37 \n",
"22 74.02 89.54 \n",
"23 92.09 97.23 \n",
"24 85.27 95.46 \n",
"25 98.84 99.40 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.display import display, HTML \n",
"\n",
"display(dataframe)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Removing ada_digiface1m_vsait17_8gpu_1-IJBC\n",
"Removing ada_digiface1m_8gpu_0-IJBC\n"
]
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_ir50_webface4m-IJBC</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_vsait17_0-IJBC</td>\n",
" <td>23.12</td>\n",
" <td>33.76</td>\n",
" <td>46.85</td>\n",
" <td>61.97</td>\n",
" <td>77.36</td>\n",
" <td>90.88</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_digiface1m_0-IJBC</td>\n",
" <td>16.44</td>\n",
" <td>24.13</td>\n",
" <td>35.80</td>\n",
" <td>50.66</td>\n",
" <td>67.07</td>\n",
" <td>83.93</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ada_digiface1m_7-IJBC</td>\n",
" <td>24.21</td>\n",
" <td>36.11</td>\n",
" <td>48.52</td>\n",
" <td>63.20</td>\n",
" <td>77.58</td>\n",
" <td>90.61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>ada_digiface1m_codeformer_0-IJBC</td>\n",
" <td>25.83</td>\n",
" <td>33.56</td>\n",
" <td>47.35</td>\n",
" <td>63.38</td>\n",
" <td>78.36</td>\n",
" <td>91.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>ada_digiface1m_1-IJBC</td>\n",
" <td>15.76</td>\n",
" <td>26.65</td>\n",
" <td>39.72</td>\n",
" <td>55.27</td>\n",
" <td>71.67</td>\n",
" <td>88.12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>ada_digiface1m_codeformer_1-IJBC</td>\n",
" <td>19.82</td>\n",
" <td>27.72</td>\n",
" <td>41.01</td>\n",
" <td>58.05</td>\n",
" <td>75.09</td>\n",
" <td>89.57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_0-IJBC</td>\n",
" <td>17.16</td>\n",
" <td>28.12</td>\n",
" <td>41.10</td>\n",
" <td>57.72</td>\n",
" <td>74.02</td>\n",
" <td>89.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>ada_casiawebface_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>ada_idffface_ca-cpd25_0-IJBC</td>\n",
" <td>33.19</td>\n",
" <td>44.43</td>\n",
" <td>57.70</td>\n",
" <td>72.21</td>\n",
" <td>85.92</td>\n",
" <td>95.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>ada_idffface_ca-cpd25_8gpu_0-IJBC</td>\n",
" <td>25.24</td>\n",
" <td>39.12</td>\n",
" <td>54.68</td>\n",
" <td>70.63</td>\n",
" <td>85.27</td>\n",
" <td>95.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>ada_casiawebface_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>ada_casiawebface_8gpu_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>ada_dcface_1-2M_oversample_1-IJBC</td>\n",
" <td>41.09</td>\n",
" <td>60.51</td>\n",
" <td>73.22</td>\n",
" <td>83.80</td>\n",
" <td>91.86</td>\n",
" <td>97.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>ada_dcface_1-2M_oversample_8gpu_0-IJBC</td>\n",
" <td>40.68</td>\n",
" <td>56.64</td>\n",
" <td>72.16</td>\n",
" <td>83.79</td>\n",
" <td>92.09</td>\n",
" <td>97.23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>ada_casiawebface_8gpu_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>ada_casiawebface_adaface_repo-IJBC</td>\n",
" <td>0.16</td>\n",
" <td>0.85</td>\n",
" <td>15.79</td>\n",
" <td>74.55</td>\n",
" <td>94.92</td>\n",
" <td>98.48</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>ada_digiface1m_8gpu_0_roc-IJBC</td>\n",
" <td>0.02</td>\n",
" <td>0.02</td>\n",
" <td>0.07</td>\n",
" <td>49.45</td>\n",
" <td>68.60</td>\n",
" <td>83.17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0_roc-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 0.0001 0.001 \\\n",
"0 ada_ir50_webface4m-IJBC 91.78 95.22 96.98 98.14 \n",
"1 ada_digiface1m_vsait17_0-IJBC 23.12 33.76 46.85 61.97 \n",
"2 ada_digiface1m_0-IJBC 16.44 24.13 35.80 50.66 \n",
"3 ada_digiface1m_7-IJBC 24.21 36.11 48.52 63.20 \n",
"5 ada_digiface1m_codeformer_0-IJBC 25.83 33.56 47.35 63.38 \n",
"6 ada_digiface1m_1-IJBC 15.76 26.65 39.72 55.27 \n",
"7 ada_digiface1m_codeformer_1-IJBC 19.82 27.72 41.01 58.05 \n",
"8 ada_digiface1m_codeformer_8gpu_0-IJBC 25.52 36.17 49.28 63.78 \n",
"9 ada_digiface1m_vsait17_8gpu_0-IJBC 17.16 28.12 41.10 57.72 \n",
"11 ada_casiawebface_1-IJBC 0.08 0.24 2.47 28.07 \n",
"12 ada_idffface_ca-cpd25_0-IJBC 33.19 44.43 57.70 72.21 \n",
"13 ada_idffface_ca-cpd25_8gpu_0-IJBC 25.24 39.12 54.68 70.63 \n",
"14 ada_casiawebface_0-IJBC 0.08 0.24 2.47 28.07 \n",
"15 ada_casiawebface_8gpu_0-IJBC 0.08 0.26 2.99 39.77 \n",
"16 ada_dcface_1-2M_oversample_1-IJBC 41.09 60.51 73.22 83.80 \n",
"17 ada_dcface_1-2M_oversample_8gpu_0-IJBC 40.68 56.64 72.16 83.79 \n",
"18 ada_casiawebface_8gpu_1-IJBC 0.08 0.26 2.99 39.77 \n",
"19 ada_casiawebface_adaface_repo-IJBC 0.16 0.85 15.79 74.55 \n",
"20 ada_digiface1m_8gpu_0_roc-IJBC 0.02 0.02 0.07 49.45 \n",
"21 ada_digiface1m_codeformer_8gpu_0_roc-IJBC 25.52 36.17 49.28 63.78 \n",
"\n",
" 0.01 0.1 \n",
"0 98.84 99.40 \n",
"1 77.36 90.88 \n",
"2 67.07 83.93 \n",
"3 77.58 90.61 \n",
"5 78.36 91.21 \n",
"6 71.67 88.12 \n",
"7 75.09 89.57 \n",
"8 78.35 91.37 \n",
"9 74.02 89.54 \n",
"11 79.21 94.77 \n",
"12 85.92 95.41 \n",
"13 85.27 95.46 \n",
"14 79.21 94.77 \n",
"15 88.47 98.16 \n",
"16 91.86 97.28 \n",
"17 92.09 97.23 \n",
"18 88.47 98.16 \n",
"19 94.92 98.48 \n",
"20 68.60 83.17 \n",
"21 78.35 91.37 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_ir50_webface4m-IJBC</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_vsait17_0-IJBC</td>\n",
" <td>23.12</td>\n",
" <td>33.76</td>\n",
" <td>46.85</td>\n",
" <td>61.97</td>\n",
" <td>77.36</td>\n",
" <td>90.88</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_digiface1m_0-IJBC</td>\n",
" <td>16.44</td>\n",
" <td>24.13</td>\n",
" <td>35.80</td>\n",
" <td>50.66</td>\n",
" <td>67.07</td>\n",
" <td>83.93</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ada_digiface1m_7-IJBC</td>\n",
" <td>24.21</td>\n",
" <td>36.11</td>\n",
" <td>48.52</td>\n",
" <td>63.20</td>\n",
" <td>77.58</td>\n",
" <td>90.61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>ada_digiface1m_codeformer_0-IJBC</td>\n",
" <td>25.83</td>\n",
" <td>33.56</td>\n",
" <td>47.35</td>\n",
" <td>63.38</td>\n",
" <td>78.36</td>\n",
" <td>91.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>ada_digiface1m_1-IJBC</td>\n",
" <td>15.76</td>\n",
" <td>26.65</td>\n",
" <td>39.72</td>\n",
" <td>55.27</td>\n",
" <td>71.67</td>\n",
" <td>88.12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>ada_digiface1m_codeformer_1-IJBC</td>\n",
" <td>19.82</td>\n",
" <td>27.72</td>\n",
" <td>41.01</td>\n",
" <td>58.05</td>\n",
" <td>75.09</td>\n",
" <td>89.57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_0-IJBC</td>\n",
" <td>17.16</td>\n",
" <td>28.12</td>\n",
" <td>41.10</td>\n",
" <td>57.72</td>\n",
" <td>74.02</td>\n",
" <td>89.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>ada_casiawebface_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>ada_idffface_ca-cpd25_0-IJBC</td>\n",
" <td>33.19</td>\n",
" <td>44.43</td>\n",
" <td>57.70</td>\n",
" <td>72.21</td>\n",
" <td>85.92</td>\n",
" <td>95.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>ada_idffface_ca-cpd25_8gpu_0-IJBC</td>\n",
" <td>25.24</td>\n",
" <td>39.12</td>\n",
" <td>54.68</td>\n",
" <td>70.63</td>\n",
" <td>85.27</td>\n",
" <td>95.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>ada_casiawebface_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>ada_casiawebface_8gpu_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>ada_dcface_1-2M_oversample_1-IJBC</td>\n",
" <td>41.09</td>\n",
" <td>60.51</td>\n",
" <td>73.22</td>\n",
" <td>83.80</td>\n",
" <td>91.86</td>\n",
" <td>97.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>ada_dcface_1-2M_oversample_8gpu_0-IJBC</td>\n",
" <td>40.68</td>\n",
" <td>56.64</td>\n",
" <td>72.16</td>\n",
" <td>83.79</td>\n",
" <td>92.09</td>\n",
" <td>97.23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>ada_casiawebface_8gpu_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>ada_casiawebface_adaface_repo-IJBC</td>\n",
" <td>0.16</td>\n",
" <td>0.85</td>\n",
" <td>15.79</td>\n",
" <td>74.55</td>\n",
" <td>94.92</td>\n",
" <td>98.48</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 0.0001 0.001 \\\n",
"0 ada_ir50_webface4m-IJBC 91.78 95.22 96.98 98.14 \n",
"1 ada_digiface1m_vsait17_0-IJBC 23.12 33.76 46.85 61.97 \n",
"2 ada_digiface1m_0-IJBC 16.44 24.13 35.80 50.66 \n",
"3 ada_digiface1m_7-IJBC 24.21 36.11 48.52 63.20 \n",
"5 ada_digiface1m_codeformer_0-IJBC 25.83 33.56 47.35 63.38 \n",
"6 ada_digiface1m_1-IJBC 15.76 26.65 39.72 55.27 \n",
"7 ada_digiface1m_codeformer_1-IJBC 19.82 27.72 41.01 58.05 \n",
"8 ada_digiface1m_codeformer_8gpu_0-IJBC 25.52 36.17 49.28 63.78 \n",
"9 ada_digiface1m_vsait17_8gpu_0-IJBC 17.16 28.12 41.10 57.72 \n",
"11 ada_casiawebface_1-IJBC 0.08 0.24 2.47 28.07 \n",
"12 ada_idffface_ca-cpd25_0-IJBC 33.19 44.43 57.70 72.21 \n",
"13 ada_idffface_ca-cpd25_8gpu_0-IJBC 25.24 39.12 54.68 70.63 \n",
"14 ada_casiawebface_0-IJBC 0.08 0.24 2.47 28.07 \n",
"15 ada_casiawebface_8gpu_0-IJBC 0.08 0.26 2.99 39.77 \n",
"16 ada_dcface_1-2M_oversample_1-IJBC 41.09 60.51 73.22 83.80 \n",
"17 ada_dcface_1-2M_oversample_8gpu_0-IJBC 40.68 56.64 72.16 83.79 \n",
"18 ada_casiawebface_8gpu_1-IJBC 0.08 0.26 2.99 39.77 \n",
"19 ada_casiawebface_adaface_repo-IJBC 0.16 0.85 15.79 74.55 \n",
"\n",
" 0.01 0.1 \n",
"0 98.84 99.40 \n",
"1 77.36 90.88 \n",
"2 67.07 83.93 \n",
"3 77.58 90.61 \n",
"5 78.36 91.21 \n",
"6 71.67 88.12 \n",
"7 75.09 89.57 \n",
"8 78.35 91.37 \n",
"9 74.02 89.54 \n",
"11 79.21 94.77 \n",
"12 85.92 95.41 \n",
"13 85.27 95.46 \n",
"14 79.21 94.77 \n",
"15 88.47 98.16 \n",
"16 91.86 97.28 \n",
"17 92.09 97.23 \n",
"18 88.47 98.16 \n",
"19 94.92 98.48 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# There is probably some problem with \n",
"# \n",
"# ada_digiface1m_8gpu_0-IJBC\t\n",
"\n",
"remove_list = [\n",
" \"ada_digiface1m_vsait17_8gpu_1-IJBC\",\n",
" \"ada_digiface1m_8gpu_0-IJBC\"\n",
"]\n",
"\n",
"for remove_entry in remove_list: \n",
" print(f\"Removing {remove_entry}\")\n",
" dataframe = dataframe[dataframe['Methods'] != remove_entry]\n",
"\n",
"display(dataframe)\n",
"\n",
"dataframe = dataframe.iloc[0:18]\n",
"\n",
"display(dataframe)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "bedd2a72e46f402c815b4eeef9d71110",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_ir50_webface4m-IJBC</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.4</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>91.78</td>\n",
" <td>95.22</td>\n",
" <td>96.98</td>\n",
" <td>98.14</td>\n",
" <td>98.84</td>\n",
" <td>99.4</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>91.78±0.00</td>\n",
" <td>95.22±0.00</td>\n",
" <td>96.98±0.00</td>\n",
" <td>98.14±0.00</td>\n",
" <td>98.84±0.00</td>\n",
" <td>99.40±0.00</td>\n",
" <td>0.00±0.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 0.0001 \\\n",
"0 ada_ir50_webface4m-IJBC 91.78 95.22 96.98 \n",
"mean NaN 91.78 95.22 96.98 \n",
"std NaN 0.0 0.0 0.0 \n",
"error_bars NaN 91.78±0.00 95.22±0.00 96.98±0.00 \n",
"\n",
" 0.001 0.01 0.1 __index_level_0__ \n",
"0 98.14 98.84 99.4 0.0 \n",
"mean 98.14 98.84 99.4 0.0 \n",
"std 0.0 0.0 0.0 0.0 \n",
"error_bars 98.14±0.00 98.84±0.00 99.40±0.00 0.00±0.00 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "fac9436d06894566a770fd612c58ea05",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_digiface1m_vsait17_0-IJBC</td>\n",
" <td>23.12</td>\n",
" <td>33.76</td>\n",
" <td>46.85</td>\n",
" <td>61.97</td>\n",
" <td>77.36</td>\n",
" <td>90.88</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_vsait17_8gpu_0-IJBC</td>\n",
" <td>17.16</td>\n",
" <td>28.12</td>\n",
" <td>41.1</td>\n",
" <td>57.72</td>\n",
" <td>74.02</td>\n",
" <td>89.54</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>20.14</td>\n",
" <td>30.94</td>\n",
" <td>43.975</td>\n",
" <td>59.845</td>\n",
" <td>75.69</td>\n",
" <td>90.21</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>2.98</td>\n",
" <td>2.82</td>\n",
" <td>2.875</td>\n",
" <td>2.125</td>\n",
" <td>1.67</td>\n",
" <td>0.67</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>20.14±2.98</td>\n",
" <td>30.94±2.82</td>\n",
" <td>43.98±2.88</td>\n",
" <td>59.84±2.12</td>\n",
" <td>75.69±1.67</td>\n",
" <td>90.21±0.67</td>\n",
" <td>5.00±4.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 \\\n",
"0 ada_digiface1m_vsait17_0-IJBC 23.12 33.76 \n",
"1 ada_digiface1m_vsait17_8gpu_0-IJBC 17.16 28.12 \n",
"mean NaN 20.14 30.94 \n",
"std NaN 2.98 2.82 \n",
"error_bars NaN 20.14±2.98 30.94±2.82 \n",
"\n",
" 0.0001 0.001 0.01 0.1 __index_level_0__ \n",
"0 46.85 61.97 77.36 90.88 1.0 \n",
"1 41.1 57.72 74.02 89.54 9.0 \n",
"mean 43.975 59.845 75.69 90.21 5.0 \n",
"std 2.875 2.125 1.67 0.67 4.0 \n",
"error_bars 43.98±2.88 59.84±2.12 75.69±1.67 90.21±0.67 5.00±4.00 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "b8b747384f1540ca93b06ee48ef64b31",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_digiface1m_codeformer_0-IJBC</td>\n",
" <td>25.83</td>\n",
" <td>33.56</td>\n",
" <td>47.35</td>\n",
" <td>63.38</td>\n",
" <td>78.36</td>\n",
" <td>91.21</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_codeformer_1-IJBC</td>\n",
" <td>19.82</td>\n",
" <td>27.72</td>\n",
" <td>41.01</td>\n",
" <td>58.05</td>\n",
" <td>75.09</td>\n",
" <td>89.57</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_digiface1m_codeformer_8gpu_0-IJBC</td>\n",
" <td>25.52</td>\n",
" <td>36.17</td>\n",
" <td>49.28</td>\n",
" <td>63.78</td>\n",
" <td>78.35</td>\n",
" <td>91.37</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>23.723333</td>\n",
" <td>32.483333</td>\n",
" <td>45.88</td>\n",
" <td>61.736667</td>\n",
" <td>77.266667</td>\n",
" <td>90.716667</td>\n",
" <td>6.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>2.762973</td>\n",
" <td>3.532707</td>\n",
" <td>3.532601</td>\n",
" <td>2.611977</td>\n",
" <td>1.539141</td>\n",
" <td>0.813443</td>\n",
" <td>1.247219</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>23.72±2.76</td>\n",
" <td>32.48±3.53</td>\n",
" <td>45.88±3.53</td>\n",
" <td>61.74±2.61</td>\n",
" <td>77.27±1.54</td>\n",
" <td>90.72±0.81</td>\n",
" <td>6.67±1.25</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 \\\n",
"0 ada_digiface1m_codeformer_0-IJBC 25.83 33.56 \n",
"1 ada_digiface1m_codeformer_1-IJBC 19.82 27.72 \n",
"2 ada_digiface1m_codeformer_8gpu_0-IJBC 25.52 36.17 \n",
"mean NaN 23.723333 32.483333 \n",
"std NaN 2.762973 3.532707 \n",
"error_bars NaN 23.72±2.76 32.48±3.53 \n",
"\n",
" 0.0001 0.001 0.01 0.1 __index_level_0__ \n",
"0 47.35 63.38 78.36 91.21 5.0 \n",
"1 41.01 58.05 75.09 89.57 7.0 \n",
"2 49.28 63.78 78.35 91.37 8.0 \n",
"mean 45.88 61.736667 77.266667 90.716667 6.666667 \n",
"std 3.532601 2.611977 1.539141 0.813443 1.247219 \n",
"error_bars 45.88±3.53 61.74±2.61 77.27±1.54 90.72±0.81 6.67±1.25 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3144b135beba48bfa7b6d19cb22d9955",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_idffface_ca-cpd25_0-IJBC</td>\n",
" <td>33.19</td>\n",
" <td>44.43</td>\n",
" <td>57.7</td>\n",
" <td>72.21</td>\n",
" <td>85.92</td>\n",
" <td>95.41</td>\n",
" <td>12.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_idffface_ca-cpd25_8gpu_0-IJBC</td>\n",
" <td>25.24</td>\n",
" <td>39.12</td>\n",
" <td>54.68</td>\n",
" <td>70.63</td>\n",
" <td>85.27</td>\n",
" <td>95.46</td>\n",
" <td>13.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>29.215</td>\n",
" <td>41.775</td>\n",
" <td>56.19</td>\n",
" <td>71.42</td>\n",
" <td>85.595</td>\n",
" <td>95.435</td>\n",
" <td>12.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>3.975</td>\n",
" <td>2.655</td>\n",
" <td>1.51</td>\n",
" <td>0.79</td>\n",
" <td>0.325</td>\n",
" <td>0.025</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>29.21±3.97</td>\n",
" <td>41.77±2.66</td>\n",
" <td>56.19±1.51</td>\n",
" <td>71.42±0.79</td>\n",
" <td>85.59±0.33</td>\n",
" <td>95.44±0.02</td>\n",
" <td>12.50±0.50</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 \\\n",
"0 ada_idffface_ca-cpd25_0-IJBC 33.19 44.43 \n",
"1 ada_idffface_ca-cpd25_8gpu_0-IJBC 25.24 39.12 \n",
"mean NaN 29.215 41.775 \n",
"std NaN 3.975 2.655 \n",
"error_bars NaN 29.21±3.97 41.77±2.66 \n",
"\n",
" 0.0001 0.001 0.01 0.1 __index_level_0__ \n",
"0 57.7 72.21 85.92 95.41 12.0 \n",
"1 54.68 70.63 85.27 95.46 13.0 \n",
"mean 56.19 71.42 85.595 95.435 12.5 \n",
"std 1.51 0.79 0.325 0.025 0.5 \n",
"error_bars 56.19±1.51 71.42±0.79 85.59±0.33 95.44±0.02 12.50±0.50 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "054316f343c2441eb1017e58d67a6414",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_casiawebface_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" <td>11.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_casiawebface_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.24</td>\n",
" <td>2.47</td>\n",
" <td>28.07</td>\n",
" <td>79.21</td>\n",
" <td>94.77</td>\n",
" <td>14.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_casiawebface_8gpu_0-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ada_casiawebface_8gpu_1-IJBC</td>\n",
" <td>0.08</td>\n",
" <td>0.26</td>\n",
" <td>2.99</td>\n",
" <td>39.77</td>\n",
" <td>88.47</td>\n",
" <td>98.16</td>\n",
" <td>18.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ada_casiawebface_adaface_repo-IJBC</td>\n",
" <td>0.16</td>\n",
" <td>0.85</td>\n",
" <td>15.79</td>\n",
" <td>74.55</td>\n",
" <td>94.92</td>\n",
" <td>98.48</td>\n",
" <td>19.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>0.096</td>\n",
" <td>0.37</td>\n",
" <td>5.342</td>\n",
" <td>42.046</td>\n",
" <td>86.056</td>\n",
" <td>96.868</td>\n",
" <td>15.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>0.032</td>\n",
" <td>0.240167</td>\n",
" <td>5.229174</td>\n",
" <td>17.073532</td>\n",
" <td>6.065653</td>\n",
" <td>1.71699</td>\n",
" <td>2.87054</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>0.10±0.03</td>\n",
" <td>0.37±0.24</td>\n",
" <td>5.34±5.23</td>\n",
" <td>42.05±17.07</td>\n",
" <td>86.06±6.07</td>\n",
" <td>96.87±1.72</td>\n",
" <td>15.40±2.87</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 \\\n",
"0 ada_casiawebface_1-IJBC 0.08 0.24 \n",
"1 ada_casiawebface_0-IJBC 0.08 0.24 \n",
"2 ada_casiawebface_8gpu_0-IJBC 0.08 0.26 \n",
"3 ada_casiawebface_8gpu_1-IJBC 0.08 0.26 \n",
"4 ada_casiawebface_adaface_repo-IJBC 0.16 0.85 \n",
"mean NaN 0.096 0.37 \n",
"std NaN 0.032 0.240167 \n",
"error_bars NaN 0.10±0.03 0.37±0.24 \n",
"\n",
" 0.0001 0.001 0.01 0.1 __index_level_0__ \n",
"0 2.47 28.07 79.21 94.77 11.0 \n",
"1 2.47 28.07 79.21 94.77 14.0 \n",
"2 2.99 39.77 88.47 98.16 15.0 \n",
"3 2.99 39.77 88.47 98.16 18.0 \n",
"4 15.79 74.55 94.92 98.48 19.0 \n",
"mean 5.342 42.046 86.056 96.868 15.4 \n",
"std 5.229174 17.073532 6.065653 1.71699 2.87054 \n",
"error_bars 5.34±5.23 42.05±17.07 86.06±6.07 96.87±1.72 15.40±2.87 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3a248b6072a84be0b5cebbe539c37554",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_dcface_1-2M_oversample_1-IJBC</td>\n",
" <td>41.09</td>\n",
" <td>60.51</td>\n",
" <td>73.22</td>\n",
" <td>83.8</td>\n",
" <td>91.86</td>\n",
" <td>97.28</td>\n",
" <td>16.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_dcface_1-2M_oversample_8gpu_0-IJBC</td>\n",
" <td>40.68</td>\n",
" <td>56.64</td>\n",
" <td>72.16</td>\n",
" <td>83.79</td>\n",
" <td>92.09</td>\n",
" <td>97.23</td>\n",
" <td>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>40.885</td>\n",
" <td>58.575</td>\n",
" <td>72.69</td>\n",
" <td>83.795</td>\n",
" <td>91.975</td>\n",
" <td>97.255</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>0.205</td>\n",
" <td>1.935</td>\n",
" <td>0.53</td>\n",
" <td>0.005</td>\n",
" <td>0.115</td>\n",
" <td>0.025</td>\n",
" <td>0.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>40.89±0.21</td>\n",
" <td>58.58±1.93</td>\n",
" <td>72.69±0.53</td>\n",
" <td>83.80±0.00</td>\n",
" <td>91.97±0.12</td>\n",
" <td>97.25±0.02</td>\n",
" <td>16.50±0.50</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 \\\n",
"0 ada_dcface_1-2M_oversample_1-IJBC 41.09 60.51 \n",
"1 ada_dcface_1-2M_oversample_8gpu_0-IJBC 40.68 56.64 \n",
"mean NaN 40.885 58.575 \n",
"std NaN 0.205 1.935 \n",
"error_bars NaN 40.89±0.21 58.58±1.93 \n",
"\n",
" 0.0001 0.001 0.01 0.1 __index_level_0__ \n",
"0 73.22 83.8 91.86 97.28 16.0 \n",
"1 72.16 83.79 92.09 97.23 17.0 \n",
"mean 72.69 83.795 91.975 97.255 16.5 \n",
"std 0.53 0.005 0.115 0.025 0.5 \n",
"error_bars 72.69±0.53 83.80±0.00 91.97±0.12 97.25±0.02 16.50±0.50 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ac61465e2a044c638c5b351dc86e57ac",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Filter: 0%| | 0/18 [00:00<?, ? examples/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>Methods</th>\n",
" <th>1e-06</th>\n",
" <th>1e-05</th>\n",
" <th>0.0001</th>\n",
" <th>0.001</th>\n",
" <th>0.01</th>\n",
" <th>0.1</th>\n",
" <th>__index_level_0__</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ada_digiface1m_0-IJBC</td>\n",
" <td>16.44</td>\n",
" <td>24.13</td>\n",
" <td>35.8</td>\n",
" <td>50.66</td>\n",
" <td>67.07</td>\n",
" <td>83.93</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ada_digiface1m_7-IJBC</td>\n",
" <td>24.21</td>\n",
" <td>36.11</td>\n",
" <td>48.52</td>\n",
" <td>63.2</td>\n",
" <td>77.58</td>\n",
" <td>90.61</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ada_digiface1m_1-IJBC</td>\n",
" <td>15.76</td>\n",
" <td>26.65</td>\n",
" <td>39.72</td>\n",
" <td>55.27</td>\n",
" <td>71.67</td>\n",
" <td>88.12</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>NaN</td>\n",
" <td>18.803333</td>\n",
" <td>28.963333</td>\n",
" <td>41.346667</td>\n",
" <td>56.376667</td>\n",
" <td>72.106667</td>\n",
" <td>87.553333</td>\n",
" <td>3.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>NaN</td>\n",
" <td>3.833157</td>\n",
" <td>5.157114</td>\n",
" <td>5.31878</td>\n",
" <td>5.178895</td>\n",
" <td>4.301785</td>\n",
" <td>2.756378</td>\n",
" <td>1.699673</td>\n",
" </tr>\n",
" <tr>\n",
" <th>error_bars</th>\n",
" <td>NaN</td>\n",
" <td>18.80±3.83</td>\n",
" <td>28.96±5.16</td>\n",
" <td>41.35±5.32</td>\n",
" <td>56.38±5.18</td>\n",
" <td>72.11±4.30</td>\n",
" <td>87.55±2.76</td>\n",
" <td>3.67±1.70</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Methods 1e-06 1e-05 0.0001 \\\n",
"0 ada_digiface1m_0-IJBC 16.44 24.13 35.8 \n",
"1 ada_digiface1m_7-IJBC 24.21 36.11 48.52 \n",
"2 ada_digiface1m_1-IJBC 15.76 26.65 39.72 \n",
"mean NaN 18.803333 28.963333 41.346667 \n",
"std NaN 3.833157 5.157114 5.31878 \n",
"error_bars NaN 18.80±3.83 28.96±5.16 41.35±5.32 \n",
"\n",
" 0.001 0.01 0.1 __index_level_0__ \n",
"0 50.66 67.07 83.93 2.0 \n",
"1 63.2 77.58 90.61 3.0 \n",
"2 55.27 71.67 88.12 6.0 \n",
"mean 56.376667 72.106667 87.553333 3.666667 \n",
"std 5.178895 4.301785 2.756378 1.699673 \n",
"error_bars 56.38±5.18 72.11±4.30 87.55±2.76 3.67±1.70 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hfd = Dataset.from_pandas(dataframe)\n",
"\n",
"methods = [\"ada_ir50_webface4m\", \"vsait\", \"codeformer\", \"ada_idffface_ca-cpd25\", \"ada_casiawebface\", \"ada_dcface_1-2M_oversample\"]\n",
"reporting_precision = 2\n",
"\n",
"def format_value(val, precision):\n",
" if pd.notna(val) and isinstance(val, (int, float)):\n",
" return f'{val:.{precision}f}'\n",
" else:\n",
" return val\n",
" \n",
"def add_error_bars(method_filter):\n",
" method_filter.loc['mean'] = method_filter.mean(numeric_only=True)\n",
" method_filter.loc['std'] = method_filter.std(numeric_only=True)\n",
" new_row = method_filter.loc['mean'].apply(lambda x: format_value(x, reporting_precision)) + '±' + method_filter.loc['std'].apply(lambda x: format_value(x, reporting_precision))\n",
" method_filter.loc['error_bars'] = new_row\n",
" return method_filter\n",
"\n",
"mean_std_dict = dict()\n",
"for method in methods: \n",
" method_filter = hfd.filter(lambda x: method in x['Methods'])\n",
" method_filter = method_filter.to_pandas()\n",
" method_filter = add_error_bars(method_filter)\n",
" display(method_filter)\n",
"\n",
"def filter_normal(x):\n",
" for method in methods: \n",
" if method in x['Methods']:\n",
" return False\n",
" return True\n",
" \n",
"method_filter = hfd.filter(filter_normal)\n",
"method_filter = method_filter.to_pandas()\n",
"display(add_error_bars(method_filter))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "realism",
"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": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}