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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import os"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Loading"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# set path to resutls files\n",
"path = '../../out/pretrained/clevrer/loci_looped/results/net_loci_looped'\n",
"\n",
"# load pkl file with results\n",
"df = pd.read_pickle(os.path.join(path, 'blackout_metric_average.pkl'))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"msecomplete_average: 1.281\n",
"msecomplete_std: 1.445\n",
"\n",
"mseblackout_average: 1.724\n",
"mseblackout_std: 1.611\n",
"\n",
"msevisible_average: 1.172\n",
"msevisible_std: 1.379\n",
"\n",
"ssimcomplete_average: 0.963\n",
"ssimcomplete_std: 0.020\n",
"\n",
"ssimblackout_average: 0.954\n",
"ssimblackout_std: 0.023\n",
"\n",
"ssimvisible_average: 0.965\n",
"ssimvisible_std: 0.018\n",
"\n",
"psnrcomplete_average: 35.934\n",
"psnrcomplete_std: 2.344\n",
"\n",
"psnrblackout_average: 34.605\n",
"psnrblackout_std: 2.415\n",
"\n",
"psnrvisible_average: 36.260\n",
"psnrvisible_std: 2.208\n",
"\n",
"percept_distcomplete_average: 0.106\n",
"percept_distcomplete_std: 0.032\n",
"\n",
"percept_distblackout_average: 0.114\n",
"percept_distblackout_std: 0.033\n",
"\n",
"percept_distvisible_average: 0.104\n",
"percept_distvisible_std: 0.031\n",
"\n",
"aricomplete_average: 0.874\n",
"aricomplete_std: 0.065\n",
"\n",
"ariblackout_average: 0.861\n",
"ariblackout_std: 0.072\n",
"\n",
"arivisible_average: 0.878\n",
"arivisible_std: 0.062\n",
"\n",
"faricomplete_average: 0.803\n",
"faricomplete_std: 0.091\n",
"\n",
"fariblackout_average: 0.779\n",
"fariblackout_std: 0.106\n",
"\n",
"farivisible_average: 0.809\n",
"farivisible_std: 0.086\n",
"\n",
"mioucomplete_average: 0.429\n",
"mioucomplete_std: 0.048\n",
"\n",
"mioublackout_average: 0.420\n",
"mioublackout_std: 0.052\n",
"\n",
"miouvisible_average: 0.431\n",
"miouvisible_std: 0.047\n",
"\n",
"apcomplete_average: 0.647\n",
"apcomplete_std: 0.124\n",
"\n",
"apblackout_average: 0.621\n",
"apblackout_std: 0.136\n",
"\n",
"apvisible_average: 0.654\n",
"apvisible_std: 0.120\n",
"\n",
"arcomplete_average: 0.915\n",
"arcomplete_std: 0.140\n",
"\n",
"arblackout_average: 0.880\n",
"arblackout_std: 0.162\n",
"\n",
"arvisible_average: 0.924\n",
"arvisible_std: 0.132\n",
"\n",
"blackoutcomplete_average: 0.197\n",
"blackoutcomplete_std: 0.398\n",
"\n",
"blackoutblackout_average: 1.000\n",
"blackoutblackout_std: 0.000\n",
"\n",
"blackoutvisible_average: 0.000\n",
"blackoutvisible_std: 0.000\n",
"\n"
]
}
],
"source": [
"for key,value in df.items():\n",
" print(f\"{key}: {value:.3f}\")\n",
" if 'std' in key:\n",
" print('')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "loci23",
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
