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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"%load_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import copy\n",
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"import pprint\n",
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"from benchmark_nerfstudio_paper import ablations_table_rows\n",
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"from collections import defaultdict\n",
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"\n",
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"# methods sorted in the same order we want in the paper tables\n",
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"methods = [row[0] for row in ablations_table_rows]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"def csv_filename_to_results(csv_filename, num_decimals=2, num_rows_to_consider=None):\n",
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" # code to read the csv file\n",
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" # and return a dictionary\n",
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"\n",
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" df = pd.read_csv(csv_filename)\n",
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"\n",
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" column_titles = list(df.columns.values)\n",
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"\n",
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" # iterate as long as the value is not None\n",
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" if num_rows_to_consider is None:\n",
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" rows = list(df.values)\n",
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" else:\n",
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" rows = list(df.values)[:num_rows_to_consider]\n",
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" valid_row = list(df.values[-1])\n",
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" for row in rows:\n",
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" for i in range(len(row)):\n",
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" value = row[i]\n",
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" if not pd.isnull(value):\n",
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" valid_row[i] = value\n",
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" last_row = valid_row\n",
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" # last_row will be the row that's valid\n",
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"\n",
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" from collections import defaultdict\n",
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"\n",
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" results = defaultdict(dict)\n",
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" for column_title, last_row_value in zip(column_titles, last_row):\n",
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" if column_title == \"Step\" or \"__MAX\" in column_title or \"__MIN\" in column_title:\n",
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" continue\n",
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" name = column_title.split(\" - \")[0]\n",
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" capture_name, method = name.split(\"_\")\n",
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" metric = float(last_row_value)\n",
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" # format to have 2 decimal places\n",
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" if num_decimals == 2:\n",
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" metric = f\"{metric:.2f}\"\n",
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" elif num_decimals == 3:\n",
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" metric = f\"{metric:.3f}\"\n",
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" else:\n",
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" metric = f\"{metric}\"\n",
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" results[capture_name][method] = metric\n",
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"\n",
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" # import pprint\n",
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" # pprint.pprint(results)\n",
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" # print(len(results))\n",
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"\n",
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" results = dict(results)\n",
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" return results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"metadata": {},
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"outputs": [],
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"source": [
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"# the csv filenames\n",
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"# these are generated from exporting CSVs from wandb graphs\n",
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"csv_filename_psrn = \"/home/ethanweber/nerfactory/wandb-psnr.csv\"\n",
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"csv_filename_ssim = \"/home/ethanweber/nerfactory/wandb-ssim.csv\"\n",
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"csv_filename_lpips = \"/home/ethanweber/nerfactory/wandb-lpips.csv\"\n",
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"results_psrn = csv_filename_to_results(csv_filename_psrn, num_decimals=None)\n",
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"results_ssim = csv_filename_to_results(csv_filename_ssim, num_decimals=None)\n",
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"results_lpips = csv_filename_to_results(csv_filename_lpips, num_decimals=None)\n",
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"\n",
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"\n",
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"csv_filename_psrn = \"/home/ethanweber/nerfactory/wandb-jan9-psnr.csv\"\n",
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"csv_filename_ssim = \"/home/ethanweber/nerfactory/wandb-jan9-ssim.csv\"\n",
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"csv_filename_lpips = \"/home/ethanweber/nerfactory/wandb-jan9-lpips.csv\"\n",
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"results_psrn_2 = csv_filename_to_results(csv_filename_psrn, num_decimals=None)\n",
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"results_ssim_2 = csv_filename_to_results(csv_filename_ssim, num_decimals=None)\n",
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"results_lpips_2 = csv_filename_to_results(csv_filename_lpips, num_decimals=None)\n",
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"\n",
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"# merge the results\n",
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"for capture_name, results in results_psrn_2.items():\n",
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" results_psrn[capture_name].update(results)\n",
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"for capture_name, results in results_ssim_2.items():\n",
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" results_ssim[capture_name].update(results)\n",
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"for capture_name, results in results_lpips_2.items():\n",
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" results_lpips[capture_name].update(results)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 45,
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_averages_from_results(results):\n",
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" averages = defaultdict(list)\n",
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" for capture_name, methods in results.items():\n",
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" for method, metric in methods.items():\n",
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" averages[method].append(float(metric))\n",
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" for method, metrics in averages.items():\n",
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" val = sum(metrics) / len(metrics)\n",
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" averages[method] = float(f\"{val:.4f}\")\n",
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" return averages"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 46,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"defaultdict(<class 'list'>,\n",
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" {'1-prop-network': 0.0668,\n",
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" 'l2-contraction': 0.0598,\n",
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" 'nerfacto': 0.0601,\n",
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" 'no-contraction': 0.1308,\n",
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" 'random-background-color': 0.0599,\n",
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" 'shared-prop-network': 0.0605,\n",
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" 'synthetic-on-real': 0.114,\n",
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" 'w/o-app': 0.0622,\n",
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" 'w/o-pose': 0.0614,\n",
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" 'w/o-pose-app': 0.0636})\n"
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]
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}
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],
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"source": [
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"pprint.pprint(get_averages_from_results(results_lpips))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 47,
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"metadata": {},
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"outputs": [],
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"source": [
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"def generate_row(method, capture_names):\n",
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" # remove spaces from method\n",
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" method_text = method.replace(\"-\", \" \")\n",
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" string = f\"{method_text}\"\n",
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" for idx, capture_name in enumerate(capture_names):\n",
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" psnr = results_psrn[capture_name][method]\n",
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" ssim = results_ssim[capture_name][method]\n",
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" lpips = results_lpips[capture_name][method]\n",
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" if idx == len(capture_names) - 1:\n",
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" string += \" & \\\\multicolumn{1}{r|}{\" + f\"{psnr} / {ssim} / {lpips}\" + \"}\"\n",
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" else:\n",
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" string += \" & \\\\multicolumn{1}{r}{\" + f\"{psnr} / {ssim} / {lpips}\" + \"}\"\n",
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" return string"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['Egypt', 'person', 'kitchen', 'plane', 'dozer']\n",
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"nerfacto & \\multicolumn{1}{r}{22.714982986450195 / 0.8457087874412537 / 0.0387668460607528} & \\multicolumn{1}{r}{26.58124351501465 / 0.8588576912879944 / 0.0272847861051559} & \\multicolumn{1}{r}{21.02389335632324 / 0.8730602860450745 / 0.0538232773542404} & \\multicolumn{1}{r}{23.30121612548828 / 0.8020055890083313 / 0.0444588512182235} & \\multicolumn{1}{r|}{21.23827743530273 / 0.8753665089607239 / 0.0552346743643283} \\\\ \n",
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"w/o pose & \\multicolumn{1}{r}{22.709941864013672 / 0.8510463237762451 / 0.0384077467024326} & \\multicolumn{1}{r}{26.875864028930664 / 0.875615656375885 / 0.0267722699791193} & \\multicolumn{1}{r}{20.83899688720703 / 0.8627068996429443 / 0.0561660341918468} & \\multicolumn{1}{r}{23.130054473876957 / 0.8018836975097656 / 0.0470539852976799} & \\multicolumn{1}{r|}{21.35797691345215 / 0.8832465410232544 / 0.0533054806292057} \\\\ \n",
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"w/o app & \\multicolumn{1}{r}{23.50516891479492 / 0.8450330495834351 / 0.0371274687349796} & \\multicolumn{1}{r}{29.19672203063965 / 0.8823416829109192 / 0.0238535590469837} & \\multicolumn{1}{r}{23.997222900390625 / 0.8697791695594788 / 0.0548945926129817} & \\multicolumn{1}{r}{23.31549835205078 / 0.7850948572158813 / 0.0470350570976734} & \\multicolumn{1}{r|}{24.386877059936523 / 0.8825743198394775 / 0.0454414412379264} \\\\ \n",
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"w/o pose app & \\multicolumn{1}{r}{23.166139602661133 / 0.837310791015625 / 0.0366224125027656} & \\multicolumn{1}{r}{29.16166877746582 / 0.8803766369819641 / 0.023823982104659} & \\multicolumn{1}{r}{23.605825424194336 / 0.8618716597557068 / 0.0610234178602695} & \\multicolumn{1}{r}{22.98196029663086 / 0.7747009992599487 / 0.0486842803657054} & \\multicolumn{1}{r|}{24.1285343170166 / 0.8762974143028259 / 0.0484496317803859} \\\\ \n",
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"1 prop network & \\multicolumn{1}{r}{22.29441261291504 / 0.8302732706069946 / 0.0457336418330669} & \\multicolumn{1}{r}{26.79549789428711 / 0.8694913983345032 / 0.0297231022268533} & \\multicolumn{1}{r}{20.88402557373047 / 0.8669102787971497 / 0.0568834841251373} & \\multicolumn{1}{r}{23.38462257385254 / 0.8012978434562683 / 0.0477019511163234} & \\multicolumn{1}{r|}{21.26655387878418 / 0.8781195878982544 / 0.0575154237449169} \\\\ \n",
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"l2 contraction & \\multicolumn{1}{r}{22.735132217407227 / 0.8507159352302551 / 0.0394952110946178} & \\multicolumn{1}{r}{26.3044490814209 / 0.8442776203155518 / 0.0297974403947591} & \\multicolumn{1}{r}{20.831445693969727 / 0.870667040348053 / 0.0538116246461868} & \\multicolumn{1}{r}{23.17695617675781 / 0.8045668601989746 / 0.0425091050565242} & \\multicolumn{1}{r|}{21.17496681213379 / 0.8793404698371887 / 0.0562350191175937} \\\\ \n",
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"shared prop network & \\multicolumn{1}{r}{22.72172737121582 / 0.8462676405906677 / 0.036957062780857} & \\multicolumn{1}{r}{26.2338924407959 / 0.8363291621208191 / 0.030552914366126} & \\multicolumn{1}{r}{20.846466064453125 / 0.8672903180122375 / 0.0565056912600994} & \\multicolumn{1}{r}{23.31382369995117 / 0.8025220036506653 / 0.0451882556080818} & \\multicolumn{1}{r|}{21.209640502929688 / 0.8794581890106201 / 0.0534685812890529} \\\\ \n",
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"random background color & \\multicolumn{1}{r}{22.50684356689453 / 0.8338311910629272 / 0.0386323854327201} & \\multicolumn{1}{r}{26.413747787475582 / 0.8475838899612427 / 0.0302980989217758} & \\multicolumn{1}{r}{20.803401947021484 / 0.8670746684074402 / 0.0552690662443637} & \\multicolumn{1}{r}{23.181974411010746 / 0.7954545021057129 / 0.0450066737830638} & \\multicolumn{1}{r|}{21.30900382995605 / 0.8826950192451477 / 0.0531600639224052} \\\\ \n",
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"no contraction & \\multicolumn{1}{r}{18.0621395111084 / 0.5198838710784912 / 0.1507363319396972} & \\multicolumn{1}{r}{21.95572662353516 / 0.511165201663971 / 0.1250636577606201} & \\multicolumn{1}{r}{19.351024627685547 / 0.764460563659668 / 0.0784180983901023} & \\multicolumn{1}{r}{18.450420379638672 / 0.5193044543266296 / 0.1613750755786895} & \\multicolumn{1}{r|}{19.532262802124023 / 0.7856844067573547 / 0.0809869393706321} \\\\ \n",
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"synthetic on real & \\multicolumn{1}{r}{18.51077651977539 / 0.5463988184928894 / 0.1192879229784011} & \\multicolumn{1}{r}{24.6822566986084 / 0.6670649647712708 / 0.0987291559576988} & \\multicolumn{1}{r}{20.980388641357425 / 0.745147705078125 / 0.0741989538073539} & \\multicolumn{1}{r}{19.319589614868164 / 0.5777738690376282 / 0.1021366342902183} & \\multicolumn{1}{r|}{21.40807342529297 / 0.7580105066299438 / 0.0801835656166076} \\\\ \\hline\n",
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"\n",
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"['floating-tree', 'aspen', 'stump', 'sculpture', 'Giannini-Hall']\n",
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"nerfacto & \\multicolumn{1}{r}{20.39972686767578 / 0.854109525680542 / 0.0524107255041599} & \\multicolumn{1}{r}{18.57237243652344 / 0.6354746222496033 / 0.1751366555690765} & \\multicolumn{1}{r}{21.928449630737305 / 0.7976410388946533 / 0.0387384481728076} & \\multicolumn{1}{r}{22.58584213256836 / 0.7889150381088257 / 0.0407779291272163} & \\multicolumn{1}{r|}{19.99639129638672 / 0.7731102108955383 / 0.0745075196027755} \\\\ \n",
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"w/o pose & \\multicolumn{1}{r}{20.298728942871094 / 0.8402881622314453 / 0.0546704977750778} & \\multicolumn{1}{r}{18.61675453186035 / 0.6382865905761719 / 0.1753666847944259} & \\multicolumn{1}{r}{21.633838653564453 / 0.7653179168701172 / 0.0428420193493366} & \\multicolumn{1}{r}{22.506526947021484 / 0.7845871448516846 / 0.0455470941960811} & \\multicolumn{1}{r|}{19.97289276123047 / 0.7722745537757874 / 0.0739260166883468} \\\\ \n",
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"w/o app & \\multicolumn{1}{r}{22.46498680114746 / 0.8535845279693604 / 0.0616657771170139} & \\multicolumn{1}{r}{18.27329635620117 / 0.6129483580589294 / 0.1905485093593597} & \\multicolumn{1}{r}{25.68264579772949 / 0.8736064434051514 / 0.0317401029169559} & \\multicolumn{1}{r}{23.268043518066406 / 0.7738019227981567 / 0.0487339384853839} & \\multicolumn{1}{r|}{21.44996833801269 / 0.7652416825294495 / 0.0814294144511222} \\\\ \n",
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"w/o pose app & \\multicolumn{1}{r}{22.154300689697266 / 0.8340064287185669 / 0.0661337822675705} & \\multicolumn{1}{r}{18.28131675720215 / 0.611172080039978 / 0.1861454993486404} & \\multicolumn{1}{r}{25.562631607055664 / 0.8677808046340942 / 0.0340047031641006} & \\multicolumn{1}{r}{22.98941802978516 / 0.76247638463974 / 0.0532486699521541} & \\multicolumn{1}{r|}{21.344554901123047 / 0.7619099020957947 / 0.0781947895884513} \\\\ \n",
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"1 prop network & \\multicolumn{1}{r}{20.28233528137207 / 0.8498139977455139 / 0.0570690296590328} & \\multicolumn{1}{r}{18.41587829589844 / 0.6070924401283264 / 0.2094678878784179} & \\multicolumn{1}{r}{22.85092544555664 / 0.8734478950500488 / 0.0329417251050472} & \\multicolumn{1}{r}{22.60772132873535 / 0.8046638369560242 / 0.0431603491306304} & \\multicolumn{1}{r|}{19.89984703063965 / 0.759652853012085 / 0.0880114957690239} \\\\ \n",
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"l2 contraction & \\multicolumn{1}{r}{20.49176979064941 / 0.8501678109169006 / 0.0527788065373897} & \\multicolumn{1}{r}{18.66337013244629 / 0.6445528268814087 / 0.1680227816104889} & \\multicolumn{1}{r}{22.26547622680664 / 0.8150904178619385 / 0.0378103740513324} & \\multicolumn{1}{r}{22.462072372436523 / 0.7815755009651184 / 0.0426461324095726} & \\multicolumn{1}{r|}{19.985918045043945 / 0.7727018594741821 / 0.0751706212759018} \\\\ \n",
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"shared prop network & \\multicolumn{1}{r}{20.333086013793945 / 0.8504053950309753 / 0.0537901557981967} & \\multicolumn{1}{r}{18.6508731842041 / 0.6390713453292847 / 0.1719826906919479} & \\multicolumn{1}{r}{22.207321166992188 / 0.805411696434021 / 0.0403469167649745} & \\multicolumn{1}{r}{22.50098991394043 / 0.7922176718711853 / 0.0416620261967182} & \\multicolumn{1}{r|}{19.98356437683105 / 0.7727880477905273 / 0.0745216161012649} \\\\ \n",
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"random background color & \\multicolumn{1}{r}{20.243900299072266 / 0.8465315699577332 / 0.0529390051960945} & \\multicolumn{1}{r}{18.56953430175781 / 0.636640191078186 / 0.1718863695859909} & \\multicolumn{1}{r}{22.578887939453125 / 0.8352341055870056 / 0.0351601541042327} & \\multicolumn{1}{r}{22.478111267089844 / 0.7781183123588562 / 0.0417613536119461} & \\multicolumn{1}{r|}{20.105976104736328 / 0.7749199867248535 / 0.0752039030194282} \\\\ \n",
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"no contraction & \\multicolumn{1}{r}{18.98202896118164 / 0.6787521839141846 / 0.0879055261611938} & \\multicolumn{1}{r}{15.803391456604004 / 0.3301353752613067 / 0.3417288959026336} & \\multicolumn{1}{r}{20.686363220214844 / 0.7041175365447998 / 0.0748037695884704} & \\multicolumn{1}{r}{21.432249069213867 / 0.7197808623313904 / 0.0730623304843902} & \\multicolumn{1}{r|}{17.751110076904297 / 0.5955697298049927 / 0.1335323601961136} \\\\ \n",
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"synthetic on real & \\multicolumn{1}{r}{21.130878448486328 / 0.7259055376052856 / 0.0717189684510231} & \\multicolumn{1}{r}{15.527592658996582 / 0.3011459112167358 / 0.3317984342575073} & \\multicolumn{1}{r}{23.858999252319336 / 0.7855907678604126 / 0.0529582537710666} & \\multicolumn{1}{r}{22.620250701904297 / 0.7056115865707397 / 0.0756969302892685} & \\multicolumn{1}{r|}{18.407384872436523 / 0.5756094455718994 / 0.1331061422824859} \\\\ \\hline\n"
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]
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}
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],
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"source": [
|
||||
"capture_names_row1 = [\"Egypt\", \"person\", \"kitchen\", \"plane\", \"dozer\"]\n",
|
||||
"capture_names_row2 = [\"floating-tree\", \"aspen\", \"stump\", \"sculpture\", \"Giannini-Hall\"]\n",
|
||||
"\n",
|
||||
"print(capture_names_row1)\n",
|
||||
"for method in methods[:-1]:\n",
|
||||
" # print(generate_row(method, capture_names_row1) + ' \\\\\\ \\cline{1-1}')\n",
|
||||
" print(generate_row(method, capture_names_row1) + \" \\\\\\ \")\n",
|
||||
"print(generate_row(methods[-1], capture_names_row1) + \" \\\\\\ \\hline\")\n",
|
||||
"\n",
|
||||
"print()\n",
|
||||
"\n",
|
||||
"print(capture_names_row2)\n",
|
||||
"for method in methods[:-1]:\n",
|
||||
" # print(generate_row(method, capture_names_row2) + ' \\\\\\ \\cline{1-1}')\n",
|
||||
" print(generate_row(method, capture_names_row2) + \" \\\\\\ \")\n",
|
||||
"print(generate_row(methods[-1], capture_names_row2) + \" \\\\\\ \\hline\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# mipnerf360 experiments\n",
|
||||
"\n",
|
||||
"csv_filename_psrn = \"results/mipnerf360-nerfacto-psnr.csv\"\n",
|
||||
"csv_filename_ssim = \"results/mipnerf360-nerfacto-ssim.csv\"\n",
|
||||
"csv_filename_lpips = \"results/mipnerf360-nerfacto-lpips.csv\"\n",
|
||||
"\n",
|
||||
"results_psrn_5K = csv_filename_to_results(csv_filename_psrn, num_decimals=2, num_rows_to_consider=1)\n",
|
||||
"results_ssim_5K = csv_filename_to_results(csv_filename_ssim, num_decimals=3, num_rows_to_consider=1)\n",
|
||||
"results_lpips_5K = csv_filename_to_results(csv_filename_lpips, num_decimals=3, num_rows_to_consider=1)\n",
|
||||
"\n",
|
||||
"results_psrn_30K = csv_filename_to_results(csv_filename_psrn, num_decimals=2)\n",
|
||||
"results_ssim_30K = csv_filename_to_results(csv_filename_ssim, num_decimals=3)\n",
|
||||
"results_lpips_30K = csv_filename_to_results(csv_filename_lpips, num_decimals=3)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"psnr\n",
|
||||
"[('bicycle', {'nerfacto-w/o-pose-app': '22.36'}),\n",
|
||||
" ('garden', {'nerfacto-w/o-pose-app': '24.05'}),\n",
|
||||
" ('stump', {'nerfacto-w/o-pose-app': '18.94'}),\n",
|
||||
" ('room', {'nerfacto-w/o-pose-app': '29.36'}),\n",
|
||||
" ('counter', {'nerfacto-w/o-pose-app': '25.92'}),\n",
|
||||
" ('kitchen', {'nerfacto-w/o-pose-app': '28.17'}),\n",
|
||||
" ('bonsai', {'nerfacto-w/o-pose-app': '28.98'})]\n",
|
||||
"\n",
|
||||
"ssim\n",
|
||||
"[('bicycle', {'nerfacto-w/o-pose-app': '0.474'}),\n",
|
||||
" ('garden', {'nerfacto-w/o-pose-app': '0.617'}),\n",
|
||||
" ('stump', {'nerfacto-w/o-pose-app': '0.364'}),\n",
|
||||
" ('room', {'nerfacto-w/o-pose-app': '0.866'}),\n",
|
||||
" ('counter', {'nerfacto-w/o-pose-app': '0.776'}),\n",
|
||||
" ('kitchen', {'nerfacto-w/o-pose-app': '0.838'}),\n",
|
||||
" ('bonsai', {'nerfacto-w/o-pose-app': '0.880'})]\n",
|
||||
"\n",
|
||||
"lpips\n",
|
||||
"[('bicycle', {'nerfacto-w/o-pose-app': '0.551'}),\n",
|
||||
" ('garden', {'nerfacto-w/o-pose-app': '0.385'}),\n",
|
||||
" ('stump', {'nerfacto-w/o-pose-app': '0.669'}),\n",
|
||||
" ('room', {'nerfacto-w/o-pose-app': '0.302'}),\n",
|
||||
" ('counter', {'nerfacto-w/o-pose-app': '0.346'}),\n",
|
||||
" ('kitchen', {'nerfacto-w/o-pose-app': '0.223'}),\n",
|
||||
" ('bonsai', {'nerfacto-w/o-pose-app': '0.252'})]\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mipnerf360_nerfacto_capture_names = [\"bicycle\", \"garden\", \"stump\", \"room\", \"counter\", \"kitchen\", \"bonsai\"]\n",
|
||||
"\n",
|
||||
"print(\"psnr\")\n",
|
||||
"s = [(key, results_psrn[key]) for key in mipnerf360_nerfacto_capture_names]\n",
|
||||
"pprint.pprint(s)\n",
|
||||
"print()\n",
|
||||
"\n",
|
||||
"print(\"ssim\")\n",
|
||||
"s = [(key, results_ssim[key]) for key in mipnerf360_nerfacto_capture_names]\n",
|
||||
"pprint.pprint(s)\n",
|
||||
"print()\n",
|
||||
"\n",
|
||||
"print(\"lpips\")\n",
|
||||
"s = [(key, results_lpips[key]) for key in mipnerf360_nerfacto_capture_names]\n",
|
||||
"pprint.pprint(s)\n",
|
||||
"print()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 27,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"psnr\n",
|
||||
"\\begin{tabular}[c]{@{}c@{}}Nerfacto (ours) w/o pose \\& app\\end{tabular} & \\multicolumn{1}{c|}{23.44 / 22.36} & \\multicolumn{1}{c|}{25.58 / 24.05} & \\multicolumn{1}{c|}{19.02 / 18.94} & \\multicolumn{1}{c|}{30.74 / 29.36} & \\multicolumn{1}{c|}{27.09 / 25.92} & \\multicolumn{1}{c|}{30.09 / 28.17} & \\multicolumn{1}{c|}{31.31 / 28.98}\\\\ \\hline\n",
|
||||
"mean 30K psnr\n",
|
||||
"mean 5K psnr\n",
|
||||
"26.752857142857142 / 25.397142857142857\n",
|
||||
"ssim\n",
|
||||
"\\begin{tabular}[c]{@{}c@{}}Nerfacto (ours) w/o pose \\& app\\end{tabular} & \\multicolumn{1}{c|}{0.563 / 0.474} & \\multicolumn{1}{c|}{0.732 / 0.617} & \\multicolumn{1}{c|}{0.387 / 0.364} & \\multicolumn{1}{c|}{0.901 / 0.866} & \\multicolumn{1}{c|}{0.832 / 0.776} & \\multicolumn{1}{c|}{0.895 / 0.838} & \\multicolumn{1}{c|}{0.927 / 0.880}\\\\ \\hline\n",
|
||||
"mean 30K ssim\n",
|
||||
"mean 5K ssim\n",
|
||||
"0.7481428571428571 / 0.687857142857143\n",
|
||||
"lpips\n",
|
||||
"\\begin{tabular}[c]{@{}c@{}}Nerfacto (ours) w/o pose \\& app\\end{tabular} & \\multicolumn{1}{c|}{0.457 / 0.551} & \\multicolumn{1}{c|}{0.279 / 0.385} & \\multicolumn{1}{c|}{0.630 / 0.669} & \\multicolumn{1}{c|}{0.218 / 0.302} & \\multicolumn{1}{c|}{0.262 / 0.346} & \\multicolumn{1}{c|}{0.149 / 0.223} & \\multicolumn{1}{c|}{0.155 / 0.252}\\\\ \\hline\n",
|
||||
"mean 30K lpips\n",
|
||||
"mean 5K lpips\n",
|
||||
"0.3071428571428571 / 0.3897142857142857\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mipnerf360_nerfacto_capture_names = [\"bicycle\", \"garden\", \"stump\", \"room\", \"counter\", \"kitchen\", \"bonsai\"]\n",
|
||||
"method = \"nerfacto-w/o-pose-app\"\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"# create the rows for a metrics\n",
|
||||
"def generate_row(results_30K, results_5K):\n",
|
||||
" string = \"\"\"\\\\begin{tabular}[c]{@{}c@{}}Nerfacto (ours) w/o pose \\& app\\end{tabular} & \"\"\"\n",
|
||||
"\n",
|
||||
" # \\multicolumn{1}{c|}{0.602 / 0.504} & \\multicolumn{1}{c|}{0.778 / 0.614} & \\multicolumn{1}{c|}{0.436 / 0.395} & \\multicolumn{1}{c|}{0.912 / 0.865} & \\multicolumn{1}{c|}{0.846 / 0.774} & \\multicolumn{1}{c|}{0.907 / 0.842} & 0.940 / 0.884\n",
|
||||
"\n",
|
||||
" for idx, capture_name in enumerate(mipnerf360_nerfacto_capture_names):\n",
|
||||
" psnr_30K = results_30K[capture_name][method]\n",
|
||||
" psnr_5K = results_5K[capture_name][method]\n",
|
||||
" string += \"\"\"\\multicolumn{1}{c|}{\"\"\" + f\"{psnr_30K} / {psnr_5K}\" + \"}\"\n",
|
||||
" if idx != len(mipnerf360_nerfacto_capture_names) - 1:\n",
|
||||
" string += \" & \"\n",
|
||||
"\n",
|
||||
" string += \"\"\"\\\\\\ \\hline\"\"\"\n",
|
||||
" return string\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"print(\"psnr\")\n",
|
||||
"string = generate_row(results_psrn_30K, results_psrn_5K)\n",
|
||||
"print(string)\n",
|
||||
"print(\"mean 30K psnr\")\n",
|
||||
"psnr_30K = np.mean(\n",
|
||||
" [float(results_psrn_30K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names]\n",
|
||||
")\n",
|
||||
"print(\"mean 5K psnr\")\n",
|
||||
"psnr_5K = np.mean([float(results_psrn_5K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names])\n",
|
||||
"print(f\"{psnr_30K} / {psnr_5K}\")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"print(\"ssim\")\n",
|
||||
"string = generate_row(results_ssim_30K, results_ssim_5K)\n",
|
||||
"print(string)\n",
|
||||
"print(\"mean 30K ssim\")\n",
|
||||
"ssim_30K = np.mean(\n",
|
||||
" [float(results_ssim_30K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names]\n",
|
||||
")\n",
|
||||
"print(\"mean 5K ssim\")\n",
|
||||
"ssim_5K = np.mean([float(results_ssim_5K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names])\n",
|
||||
"print(f\"{ssim_30K} / {ssim_5K}\")\n",
|
||||
"\n",
|
||||
"print(\"lpips\")\n",
|
||||
"string = generate_row(results_lpips_30K, results_lpips_5K)\n",
|
||||
"print(string)\n",
|
||||
"print(\"mean 30K lpips\")\n",
|
||||
"lpips_30K = np.mean(\n",
|
||||
" [float(results_lpips_30K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names]\n",
|
||||
")\n",
|
||||
"print(\"mean 5K lpips\")\n",
|
||||
"lpips_5K = np.mean(\n",
|
||||
" [float(results_lpips_5K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names]\n",
|
||||
")\n",
|
||||
"print(f\"{lpips_30K} / {lpips_5K}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 25,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['23.44', '25.58', '19.02', '30.74', '27.09', '30.09', '31.31']"
|
||||
]
|
||||
},
|
||||
"execution_count": 25,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"[results_psrn_30K[capture_name][method] for capture_name in mipnerf360_nerfacto_capture_names]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 28,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[23.44, 25.58, 19.02, 30.74, 27.09, 30.09, 31.31]"
|
||||
]
|
||||
},
|
||||
"execution_count": 28,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"[float(results_psrn_30K[capture_name][method]) for capture_name in mipnerf360_nerfacto_capture_names]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 29,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"27.464285714285715"
|
||||
]
|
||||
},
|
||||
"execution_count": 29,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"a = [23.44, 25.58, 24, 30.74, 27.09, 30.09, 31.31]\n",
|
||||
"np.mean(a)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "nerfactory",
|
||||
"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": "3.10.6 (main, Oct 7 2022, 20:19:58) [GCC 11.2.0]"
|
||||
},
|
||||
"orig_nbformat": 4,
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "b7b86c17c0dfd6b313529972d424f2e075cc198a46cda005757126afe8133c7b"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
@@ -1,7 +0,0 @@
|
||||
"Step","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MIN","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/lpips__MAX"
|
||||
"5000","0.2519197463989258","0.2519197463989258","0.2519197463989258","0.22290439903736115","0.22290439903736115","0.22290439903736115","0.3463352918624878","0.3463352918624878","0.3463352918624878","0.30166396498680115","0.30166396498680115","0.30166396498680115","0.6690490245819092","0.6690490245819092","0.6690490245819092","0.38469502329826355","0.38469502329826355","0.38469502329826355","0.5510148406028748","0.5510148406028748","0.5510148406028748"
|
||||
"10000","0.20537590980529785","0.20537590980529785","0.20537590980529785","0.1862574815750122","0.1862574815750122","0.1862574815750122","0.3060450553894043","0.3060450553894043","0.3060450553894043","0.264473021030426","0.264473021030426","0.264473021030426","0.6549886465072632","0.6549886465072632","0.6549886465072632","0.3379896581172943","0.3379896581172943","0.3379896581172943","0.5165897607803345","0.5165897607803345","0.5165897607803345"
|
||||
"15000","0.18232251703739166","0.18232251703739166","0.18232251703739166","0.1694253832101822","0.1694253832101822","0.1694253832101822","0.28753527998924255","0.28753527998924255","0.28753527998924255","0.24498172104358673","0.24498172104358673","0.24498172104358673","0.6469297409057617","0.6469297409057617","0.6469297409057617","0.3143976628780365","0.3143976628780365","0.3143976628780365","0.49204298853874207","0.49204298853874207","0.49204298853874207"
|
||||
"20000","0.16992567479610443","0.16992567479610443","0.16992567479610443","0.1603987067937851","0.1603987067937851","0.1603987067937851","0.2758496105670929","0.2758496105670929","0.2758496105670929","0.2337770015001297","0.2337770015001297","0.2337770015001297","0.6356087923049927","0.6356087923049927","0.6356087923049927","0.2970008850097656","0.2970008850097656","0.2970008850097656","0.477325439453125","0.477325439453125","0.477325439453125"
|
||||
"25000","0.16045209765434265","0.16045209765434265","0.16045209765434265","0.15450946986675262","0.15450946986675262","0.15450946986675262","0.2683956027030945","0.2683956027030945","0.2683956027030945","0.2252463847398758","0.2252463847398758","0.2252463847398758","0.6341891884803772","0.6341891884803772","0.6341891884803772","0.28854474425315857","0.28854474425315857","0.28854474425315857","0.4702630937099457","0.4702630937099457","0.4702630937099457"
|
||||
"30000","0.1552095264196396","0.1552095264196396","0.1552095264196396","0.14859946072101593","0.14859946072101593","0.14859946072101593","0.26168495416641235","0.26168495416641235","0.26168495416641235","0.21848224103450775","0.21848224103450775","0.21848224103450775","0.6303073167800903","0.6303073167800903","0.6303073167800903","0.27927762269973755","0.27927762269973755","0.27927762269973755","0.45694661140441895","0.45694661140441895","0.45694661140441895"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
"Step","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MIN","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/psnr__MAX"
|
||||
"5000","28.984577178955078","28.984577178955078","28.984577178955078","28.172439575195312","28.172439575195312","28.172439575195312","25.917695999145508","25.917695999145508","25.917695999145508","29.36033821105957","29.36033821105957","29.36033821105957","18.943880081176758","18.943880081176758","18.943880081176758","24.045259475708008","24.045259475708008","24.045259475708008","22.35852813720703","22.35852813720703","22.35852813720703"
|
||||
"10000","30.010135650634766","30.010135650634766","30.010135650634766","29.070581436157227","29.070581436157227","29.070581436157227","26.49431610107422","26.49431610107422","26.49431610107422","29.885282516479492","29.885282516479492","29.885282516479492","19.130979537963867","19.130979537963867","19.130979537963867","24.74232292175293","24.74232292175293","24.74232292175293","22.801597595214844","22.801597595214844","22.801597595214844"
|
||||
"15000","30.6047306060791","30.6047306060791","30.6047306060791","29.542308807373047","29.542308807373047","29.542308807373047","26.782276153564453","26.782276153564453","26.782276153564453","30.297269821166992","30.297269821166992","30.297269821166992","19.193822860717773","19.193822860717773","19.193822860717773","25.023618698120117","25.023618698120117","25.023618698120117","23.096738815307617","23.096738815307617","23.096738815307617"
|
||||
"20000","30.892518997192383","30.892518997192383","30.892518997192383","29.758039474487305","29.758039474487305","29.758039474487305","26.81525993347168","26.81525993347168","26.81525993347168","30.452899932861328","30.452899932861328","30.452899932861328","19.138933181762695","19.138933181762695","19.138933181762695","25.29572868347168","25.29572868347168","25.29572868347168","23.274446487426758","23.274446487426758","23.274446487426758"
|
||||
"25000","30.987964630126953","30.987964630126953","30.987964630126953","29.747432708740234","29.747432708740234","29.747432708740234","26.988618850708008","26.988618850708008","26.988618850708008","30.530561447143555","30.530561447143555","30.530561447143555","19.102785110473633","19.102785110473633","19.102785110473633","25.39276695251465","25.39276695251465","25.39276695251465","23.29694175720215","23.29694175720215","23.29694175720215"
|
||||
"30000","31.31144142150879","31.31144142150879","31.31144142150879","30.09200668334961","30.09200668334961","30.09200668334961","27.089460372924805","27.089460372924805","27.089460372924805","30.7379093170166","30.7379093170166","30.7379093170166","19.015052795410156","19.015052795410156","19.015052795410156","25.584802627563477","25.584802627563477","25.584802627563477","23.43606948852539","23.43606948852539","23.43606948852539"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
"Step","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","bonsai_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","kitchen_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","counter_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","room_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","stump_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","garden_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MIN","bicycle_nerfacto-w/o-pose-app - Eval Images Metrics Dict (all images)/ssim__MAX"
|
||||
"5000","0.8803925514221191","0.8803925514221191","0.8803925514221191","0.8378414511680603","0.8378414511680603","0.8378414511680603","0.7761771082878113","0.7761771082878113","0.7761771082878113","0.8659623265266418","0.8659623265266418","0.8659623265266418","0.36448878049850464","0.36448878049850464","0.36448878049850464","0.6166963577270508","0.6166963577270508","0.6166963577270508","0.47419044375419617","0.47419044375419617","0.47419044375419617"
|
||||
"10000","0.9040232300758362","0.9040232300758362","0.9040232300758362","0.8688313364982605","0.8688313364982605","0.8688313364982605","0.8034861087799072","0.8034861087799072","0.8034861087799072","0.8819292783737183","0.8819292783737183","0.8819292783737183","0.3767551779747009","0.3767551779747009","0.3767551779747009","0.6668679714202881","0.6668679714202881","0.6668679714202881","0.5085462331771851","0.5085462331771851","0.5085462331771851"
|
||||
"15000","0.9146127700805664","0.9146127700805664","0.9146127700805664","0.8816289305686951","0.8816289305686951","0.8816289305686951","0.8156216740608215","0.8156216740608215","0.8156216740608215","0.8901710510253906","0.8901710510253906","0.8901710510253906","0.3841424286365509","0.3841424286365509","0.3841424286365509","0.696258544921875","0.696258544921875","0.696258544921875","0.5283700823783875","0.5283700823783875","0.5283700823783875"
|
||||
"20000","0.9193230867385864","0.9193230867385864","0.9193230867385864","0.8883754014968872","0.8883754014968872","0.8883754014968872","0.8225901126861572","0.8225901126861572","0.8225901126861572","0.8937950134277344","0.8937950134277344","0.8937950134277344","0.3865121901035309","0.3865121901035309","0.3865121901035309","0.7125813961029053","0.7125813961029053","0.7125813961029053","0.5453415513038635","0.5453415513038635","0.5453415513038635"
|
||||
"25000","0.9222889542579651","0.9222889542579651","0.9222889542579651","0.8918511271476746","0.8918511271476746","0.8918511271476746","0.8282744288444519","0.8282744288444519","0.8282744288444519","0.8977230787277222","0.8977230787277222","0.8977230787277222","0.38814979791641235","0.38814979791641235","0.38814979791641235","0.7231001853942871","0.7231001853942871","0.7231001853942871","0.5515201687812805","0.5515201687812805","0.5515201687812805"
|
||||
"30000","0.9268288612365723","0.9268288612365723","0.9268288612365723","0.8953068256378174","0.8953068256378174","0.8953068256378174","0.8316792249679565","0.8316792249679565","0.8316792249679565","0.9009016156196594","0.9009016156196594","0.9009016156196594","0.3872043490409851","0.3872043490409851","0.3872043490409851","0.7320837378501892","0.7320837378501892","0.7320837378501892","0.5632787942886353","0.5632787942886353","0.5632787942886353"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
"Step","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/lpips","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","sculpture_no-contraction - Eval Images Metrics Dict (all images)/lpips","sculpture_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","sculpture_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","stump_no-contraction - Eval Images Metrics Dict (all images)/lpips","stump_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","stump_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","aspen_no-contraction - Eval Images Metrics Dict (all images)/lpips","aspen_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","aspen_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/lpips","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","dozer_no-contraction - Eval Images Metrics Dict (all images)/lpips","dozer_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","dozer_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","plane_no-contraction - Eval Images Metrics Dict (all images)/lpips","plane_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","plane_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","kitchen_no-contraction - Eval Images Metrics Dict (all images)/lpips","kitchen_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","kitchen_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","person_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","person_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","person_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","person_no-contraction - Eval Images Metrics Dict (all images)/lpips","person_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","person_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MIN","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/lpips__MAX","Egypt_no-contraction - Eval Images Metrics Dict (all images)/lpips","Egypt_no-contraction - Eval Images Metrics Dict (all images)/lpips__MIN","Egypt_no-contraction - Eval Images Metrics Dict (all images)/lpips__MAX"
|
||||
"5000","0.1760162115097046","0.1760162115097046","0.1760162115097046","0.2102298140525818","0.2102298140525818","0.2102298140525818","0.10590028762817383","0.10590028762817383","0.10590028762817383","0.12722763419151306","0.12722763419151306","0.12722763419151306","0.06853035092353821","0.06853035092353821","0.06853035092353821","0.08035052567720413","0.08035052567720413","0.08035052567720413","0.4116884469985962","0.4116884469985962","0.4116884469985962","0.4897172451019287","0.4897172451019287","0.4897172451019287","0.09578314423561096","0.09578314423561096","0.09578314423561096","0.11008867621421814","0.11008867621421814","0.11008867621421814","0.09896522015333176","0.09896522015333176","0.09896522015333176","0.12000244855880737","0.12000244855880737","0.12000244855880737","0.128322035074234","0.128322035074234","0.128322035074234","0.22804635763168335","0.22804635763168335","0.22804635763168335","0.0965556651353836","0.0965556651353836","0.0965556651353836","0.12933668494224548","0.12933668494224548","0.12933668494224548","0.13645659387111664","0.13645659387111664","0.13645659387111664","0.20632779598236084","0.20632779598236084","0.20632779598236084","0.15571025013923645","0.15571025013923645","0.15571025013923645","0.2129344791173935","0.2129344791173935","0.2129344791173935"
|
||||
"10000","0.16344334185123444","0.16344334185123444","0.16344334185123444","0.15878932178020477","0.15878932178020477","0.15878932178020477","0.09202758222818375","0.09202758222818375","0.09202758222818375","0.09222975373268127","0.09222975373268127","0.09222975373268127","0.05764570087194443","0.05764570087194443","0.05764570087194443","0.06865306198596954","0.06865306198596954","0.06865306198596954","0.37963607907295227","0.37963607907295227","0.37963607907295227","0.39304813742637634","0.39304813742637634","0.39304813742637634","0.08216632157564163","0.08216632157564163","0.08216632157564163","0.08176812529563904","0.08176812529563904","0.08176812529563904","0.08913181722164154","0.08913181722164154","0.08913181722164154","0.09483212232589722","0.09483212232589722","0.09483212232589722","0.12155257165431976","0.12155257165431976","0.12155257165431976","0.1863524168729782","0.1863524168729782","0.1863524168729782","0.08225806802511215","0.08225806802511215","0.08225806802511215","0.09628443419933319","0.09628443419933319","0.09628443419933319","0.1247154176235199","0.1247154176235199","0.1247154176235199","0.14701516926288605","0.14701516926288605","0.14701516926288605","0.14250078797340393","0.14250078797340393","0.14250078797340393","0.17241059243679047","0.17241059243679047","0.17241059243679047"
|
||||
"15000","0.15136146545410156","0.15136146545410156","0.15136146545410156","0.14545820653438568","0.14545820653438568","0.14545820653438568","0.08219514042139053","0.08219514042139053","0.08219514042139053","0.08278648555278778","0.08278648555278778","0.08278648555278778","0.058148737996816635","0.058148737996816635","0.058148737996816635","0.07180912792682648","0.07180912792682648","0.07180912792682648","0.35870322585105896","0.35870322585105896","0.35870322585105896","0.3648127317428589","0.3648127317428589","0.3648127317428589","0.07734914869070053","0.07734914869070053","0.07734914869070053","0.08005643635988235","0.08005643635988235","0.08005643635988235","0.08404481410980225","0.08404481410980225","0.08404481410980225","0.09017395228147507","0.09017395228147507","0.09017395228147507","0.10966705530881882","0.10966705530881882","0.10966705530881882","0.16996951401233673","0.16996951401233673","0.16996951401233673","0.08272098004817963","0.08272098004817963","0.08272098004817963","0.08713553100824356","0.08713553100824356","0.08713553100824356","0.1111171618103981","0.1111171618103981","0.1111171618103981","0.13010312616825104","0.13010312616825104","0.13010312616825104","0.1309850960969925","0.1309850960969925","0.1309850960969925","0.1618097871541977","0.1618097871541977","0.1618097871541977"
|
||||
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|
||||
"25000","0.14097948372364044","0.14097948372364044","0.14097948372364044","0.13744062185287476","0.13744062185287476","0.13744062185287476","0.07898176461458206","0.07898176461458206","0.07898176461458206","0.07725176960229874","0.07725176960229874","0.07725176960229874","0.052684806287288666","0.052684806287288666","0.052684806287288666","0.07319863140583038","0.07319863140583038","0.07319863140583038","0.34379279613494873","0.34379279613494873","0.34379279613494873","0.346294641494751","0.346294641494751","0.346294641494751","0.07311784476041794","0.07311784476041794","0.07311784476041794","0.08773695677518845","0.08773695677518845","0.08773695677518845","0.07814665883779526","0.07814665883779526","0.07814665883779526","0.08117035776376724","0.08117035776376724","0.08117035776376724","0.10521409660577774","0.10521409660577774","0.10521409660577774","0.15810814499855042","0.15810814499855042","0.15810814499855042","0.07686255127191544","0.07686255127191544","0.07686255127191544","0.07967425137758255","0.07967425137758255","0.07967425137758255","0.10225160419940948","0.10225160419940948","0.10225160419940948","0.12276865541934967","0.12276865541934967","0.12276865541934967","0.12226034700870514","0.12226034700870514","0.12226034700870514","0.15466775000095367","0.15466775000095367","0.15466775000095367"
|
||||
"30000","0.13310614228248596","0.13310614228248596","0.13310614228248596","0.1335323601961136","0.1335323601961136","0.1335323601961136","0.0756969302892685","0.0756969302892685","0.0756969302892685","0.07306233048439026","0.07306233048439026","0.07306233048439026","0.052958253771066666","0.052958253771066666","0.052958253771066666","0.07480376958847046","0.07480376958847046","0.07480376958847046","0.3317984342575073","0.3317984342575073","0.3317984342575073","0.34172889590263367","0.34172889590263367","0.34172889590263367","0.0717189684510231","0.0717189684510231","0.0717189684510231","0.08790552616119385","0.08790552616119385","0.08790552616119385","0.08018356561660767","0.08018356561660767","0.08018356561660767","0.08098693937063217","0.08098693937063217","0.08098693937063217","0.10213663429021835","0.10213663429021835","0.10213663429021835","0.16137507557868958","0.16137507557868958","0.16137507557868958","0.07419895380735397","0.07419895380735397","0.07419895380735397","0.07841809839010239","0.07841809839010239","0.07841809839010239","0.09872915595769882","0.09872915595769882","0.09872915595769882","0.12506365776062012","0.12506365776062012","0.12506365776062012","0.11928792297840118","0.11928792297840118","0.11928792297840118","0.15073633193969727","0.15073633193969727","0.15073633193969727"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
"Step","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/psnr","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","sculpture_no-contraction - Eval Images Metrics Dict (all images)/psnr","sculpture_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","sculpture_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","stump_no-contraction - Eval Images Metrics Dict (all images)/psnr","stump_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","stump_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","aspen_no-contraction - Eval Images Metrics Dict (all images)/psnr","aspen_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","aspen_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/psnr","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","dozer_no-contraction - Eval Images Metrics Dict (all images)/psnr","dozer_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","dozer_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","plane_no-contraction - Eval Images Metrics Dict (all images)/psnr","plane_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","plane_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","kitchen_no-contraction - Eval Images Metrics Dict (all images)/psnr","kitchen_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","kitchen_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","person_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","person_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","person_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","person_no-contraction - Eval Images Metrics Dict (all images)/psnr","person_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","person_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MIN","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/psnr__MAX","Egypt_no-contraction - Eval Images Metrics Dict (all images)/psnr","Egypt_no-contraction - Eval Images Metrics Dict (all images)/psnr__MIN","Egypt_no-contraction - Eval Images Metrics Dict (all images)/psnr__MAX"
|
||||
"5000","18.362504959106445","18.362504959106445","18.362504959106445","18.096677780151367","18.096677780151367","18.096677780151367","22.478546142578125","22.478546142578125","22.478546142578125","21.499540328979492","21.499540328979492","21.499540328979492","23.64402961730957","23.64402961730957","23.64402961730957","21.987220764160156","21.987220764160156","21.987220764160156","16.084623336791992","16.084623336791992","16.084623336791992","16.186025619506836","16.186025619506836","16.186025619506836","20.938323974609375","20.938323974609375","20.938323974609375","19.221168518066406","19.221168518066406","19.221168518066406","21.0407772064209","21.0407772064209","21.0407772064209","19.677867889404297","19.677867889404297","19.677867889404297","18.930198669433594","18.930198669433594","18.930198669433594","18.58513832092285","18.58513832092285","18.58513832092285","20.65243148803711","20.65243148803711","20.65243148803711","19.27729606628418","19.27729606628418","19.27729606628418","25.0496768951416","25.0496768951416","25.0496768951416","23.592557907104492","23.592557907104492","23.592557907104492","19.041812896728516","19.041812896728516","19.041812896728516","18.65505599975586","18.65505599975586","18.65505599975586"
|
||||
"10000","18.182497024536133","18.182497024536133","18.182497024536133","18.12276840209961","18.12276840209961","18.12276840209961","22.680496215820312","22.680496215820312","22.680496215820312","21.4115047454834","21.4115047454834","21.4115047454834","23.76669692993164","23.76669692993164","23.76669692993164","21.560001373291016","21.560001373291016","21.560001373291016","16.00229263305664","16.00229263305664","16.00229263305664","16.096864700317383","16.096864700317383","16.096864700317383","21.460935592651367","21.460935592651367","21.460935592651367","19.42638397216797","19.42638397216797","19.42638397216797","21.400897979736328","21.400897979736328","21.400897979736328","19.65334129333496","19.65334129333496","19.65334129333496","18.375104904174805","18.375104904174805","18.375104904174805","18.539196014404297","18.539196014404297","18.539196014404297","20.96162223815918","20.96162223815918","20.96162223815918","19.389822006225586","19.389822006225586","19.389822006225586","24.80574607849121","24.80574607849121","24.80574607849121","22.84902000427246","22.84902000427246","22.84902000427246","18.890893936157227","18.890893936157227","18.890893936157227","18.27381706237793","18.27381706237793","18.27381706237793"
|
||||
"15000","18.28525161743164","18.28525161743164","18.28525161743164","17.880399703979492","17.880399703979492","17.880399703979492","22.581972122192383","22.581972122192383","22.581972122192383","21.520532608032227","21.520532608032227","21.520532608032227","23.59893035888672","23.59893035888672","23.59893035888672","21.24063491821289","21.24063491821289","21.24063491821289","15.990221977233887","15.990221977233887","15.990221977233887","15.934891700744629","15.934891700744629","15.934891700744629","21.28774642944336","21.28774642944336","21.28774642944336","19.287498474121094","19.287498474121094","19.287498474121094","21.402149200439453","21.402149200439453","21.402149200439453","19.643274307250977","19.643274307250977","19.643274307250977","19.260986328125","19.260986328125","19.260986328125","18.53015899658203","18.53015899658203","18.53015899658203","20.702795028686523","20.702795028686523","20.702795028686523","19.27466583251953","19.27466583251953","19.27466583251953","24.886276245117188","24.886276245117188","24.886276245117188","22.796472549438477","22.796472549438477","22.796472549438477","18.830677032470703","18.830677032470703","18.830677032470703","18.232566833496094","18.232566833496094","18.232566833496094"
|
||||
"20000","18.252077102661133","18.252077102661133","18.252077102661133","17.872840881347656","17.872840881347656","17.872840881347656","22.69757652282715","22.69757652282715","22.69757652282715","21.47149658203125","21.47149658203125","21.47149658203125","23.92220687866211","23.92220687866211","23.92220687866211","20.882619857788086","20.882619857788086","20.882619857788086","15.909340858459473","15.909340858459473","15.909340858459473","15.816522598266602","15.816522598266602","15.816522598266602","21.336437225341797","21.336437225341797","21.336437225341797","19.329240798950195","19.329240798950195","19.329240798950195","21.314849853515625","21.314849853515625","21.314849853515625","19.496286392211914","19.496286392211914","19.496286392211914","18.891340255737305","18.891340255737305","18.891340255737305","18.58868980407715","18.58868980407715","18.58868980407715","20.983293533325195","20.983293533325195","20.983293533325195","19.43528938293457","19.43528938293457","19.43528938293457","24.81332778930664","24.81332778930664","24.81332778930664","22.198863983154297","22.198863983154297","22.198863983154297","18.853158950805664","18.853158950805664","18.853158950805664","18.080575942993164","18.080575942993164","18.080575942993164"
|
||||
"25000","17.98874855041504","17.98874855041504","17.98874855041504","17.777936935424805","17.777936935424805","17.777936935424805","22.6182918548584","22.6182918548584","22.6182918548584","21.3403263092041","21.3403263092041","21.3403263092041","24.116527557373047","24.116527557373047","24.116527557373047","20.631877899169922","20.631877899169922","20.631877899169922","15.786420822143555","15.786420822143555","15.786420822143555","15.806575775146484","15.806575775146484","15.806575775146484","21.11553955078125","21.11553955078125","21.11553955078125","18.985576629638672","18.985576629638672","18.985576629638672","21.322368621826172","21.322368621826172","21.322368621826172","19.730337142944336","19.730337142944336","19.730337142944336","18.78772735595703","18.78772735595703","18.78772735595703","18.61232566833496","18.61232566833496","18.61232566833496","20.728336334228516","20.728336334228516","20.728336334228516","19.389379501342773","19.389379501342773","19.389379501342773","24.655162811279297","24.655162811279297","24.655162811279297","22.154647827148438","22.154647827148438","22.154647827148438","18.988101959228516","18.988101959228516","18.988101959228516","18.168479919433594","18.168479919433594","18.168479919433594"
|
||||
"30000","18.407384872436523","18.407384872436523","18.407384872436523","17.751110076904297","17.751110076904297","17.751110076904297","22.620250701904297","22.620250701904297","22.620250701904297","21.432249069213867","21.432249069213867","21.432249069213867","23.858999252319336","23.858999252319336","23.858999252319336","20.686363220214844","20.686363220214844","20.686363220214844","15.527592658996582","15.527592658996582","15.527592658996582","15.803391456604004","15.803391456604004","15.803391456604004","21.130878448486328","21.130878448486328","21.130878448486328","18.98202896118164","18.98202896118164","18.98202896118164","21.40807342529297","21.40807342529297","21.40807342529297","19.532262802124023","19.532262802124023","19.532262802124023","19.319589614868164","19.319589614868164","19.319589614868164","18.450420379638672","18.450420379638672","18.450420379638672","20.980388641357422","20.980388641357422","20.980388641357422","19.351024627685547","19.351024627685547","19.351024627685547","24.6822566986084","24.6822566986084","24.6822566986084","21.955726623535156","21.955726623535156","21.955726623535156","18.51077651977539","18.51077651977539","18.51077651977539","18.0621395111084","18.0621395111084","18.0621395111084"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
"Step","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","Giannini-Hall_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/ssim","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","Giannini-Hall_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","sculpture_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","sculpture_no-contraction - Eval Images Metrics Dict (all images)/ssim","sculpture_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","sculpture_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","stump_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","stump_no-contraction - Eval Images Metrics Dict (all images)/ssim","stump_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","stump_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","aspen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","aspen_no-contraction - Eval Images Metrics Dict (all images)/ssim","aspen_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","aspen_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","floating-tree_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/ssim","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","floating-tree_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","dozer_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","dozer_no-contraction - Eval Images Metrics Dict (all images)/ssim","dozer_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","dozer_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","plane_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","plane_no-contraction - Eval Images Metrics Dict (all images)/ssim","plane_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","plane_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","kitchen_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","kitchen_no-contraction - Eval Images Metrics Dict (all images)/ssim","kitchen_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","kitchen_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","person_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","person_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","person_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","person_no-contraction - Eval Images Metrics Dict (all images)/ssim","person_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","person_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MIN","Egypt_synthetic-on-real - Eval Images Metrics Dict (all images)/ssim__MAX","Egypt_no-contraction - Eval Images Metrics Dict (all images)/ssim","Egypt_no-contraction - Eval Images Metrics Dict (all images)/ssim__MIN","Egypt_no-contraction - Eval Images Metrics Dict (all images)/ssim__MAX"
|
||||
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||||
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||||
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|
||||
"20000","0.5621583461761475","0.5621583461761475","0.5621583461761475","0.6039221286773682","0.6039221286773682","0.6039221286773682","0.7071369290351868","0.7071369290351868","0.7071369290351868","0.7234301567077637","0.7234301567077637","0.7234301567077637","0.7984806895256042","0.7984806895256042","0.7984806895256042","0.7263915538787842","0.7263915538787842","0.7263915538787842","0.32767626643180847","0.32767626643180847","0.32767626643180847","0.3321668207645416","0.3321668207645416","0.3321668207645416","0.7364911437034607","0.7364911437034607","0.7364911437034607","0.7243889570236206","0.7243889570236206","0.7243889570236206","0.7491315007209778","0.7491315007209778","0.7491315007209778","0.7850586771965027","0.7850586771965027","0.7850586771965027","0.5565969944000244","0.5565969944000244","0.5565969944000244","0.5230870246887207","0.5230870246887207","0.5230870246887207","0.7448252439498901","0.7448252439498901","0.7448252439498901","0.7637325525283813","0.7637325525283813","0.7637325525283813","0.6828808784484863","0.6828808784484863","0.6828808784484863","0.5383646488189697","0.5383646488189697","0.5383646488189697","0.5621162056922913","0.5621162056922913","0.5621162056922913","0.5188120603561401","0.5188120603561401","0.5188120603561401"
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||||
"25000","0.5487070083618164","0.5487070083618164","0.5487070083618164","0.5941022038459778","0.5941022038459778","0.5941022038459778","0.7055608034133911","0.7055608034133911","0.7055608034133911","0.7152494788169861","0.7152494788169861","0.7152494788169861","0.807205319404602","0.807205319404602","0.807205319404602","0.6968534588813782","0.6968534588813782","0.6968534588813782","0.3233805000782013","0.3233805000782013","0.3233805000782013","0.34123650193214417","0.34123650193214417","0.34123650193214417","0.7315167188644409","0.7315167188644409","0.7315167188644409","0.6809759736061096","0.6809759736061096","0.6809759736061096","0.7578228712081909","0.7578228712081909","0.7578228712081909","0.7896640300750732","0.7896640300750732","0.7896640300750732","0.5566552877426147","0.5566552877426147","0.5566552877426147","0.5295083522796631","0.5295083522796631","0.5295083522796631","0.7326600551605225","0.7326600551605225","0.7326600551605225","0.7631698250770569","0.7631698250770569","0.7631698250770569","0.6702176928520203","0.6702176928520203","0.6702176928520203","0.526925265789032","0.526925265789032","0.526925265789032","0.5785836577415466","0.5785836577415466","0.5785836577415466","0.5277501940727234","0.5277501940727234","0.5277501940727234"
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||||
"30000","0.5756094455718994","0.5756094455718994","0.5756094455718994","0.5955697298049927","0.5955697298049927","0.5955697298049927","0.7056115865707397","0.7056115865707397","0.7056115865707397","0.7197808623313904","0.7197808623313904","0.7197808623313904","0.7855907678604126","0.7855907678604126","0.7855907678604126","0.7041175365447998","0.7041175365447998","0.7041175365447998","0.30114591121673584","0.30114591121673584","0.30114591121673584","0.33013537526130676","0.33013537526130676","0.33013537526130676","0.7259055376052856","0.7259055376052856","0.7259055376052856","0.6787521839141846","0.6787521839141846","0.6787521839141846","0.7580105066299438","0.7580105066299438","0.7580105066299438","0.7856844067573547","0.7856844067573547","0.7856844067573547","0.5777738690376282","0.5777738690376282","0.5777738690376282","0.5193044543266296","0.5193044543266296","0.5193044543266296","0.745147705078125","0.745147705078125","0.745147705078125","0.764460563659668","0.764460563659668","0.764460563659668","0.6670649647712708","0.6670649647712708","0.6670649647712708","0.511165201663971","0.511165201663971","0.511165201663971","0.5463988184928894","0.5463988184928894","0.5463988184928894","0.5198838710784912","0.5198838710784912","0.5198838710784912"
|
||||
|
@@ -1,7 +0,0 @@
|
||||
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|
||||
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ine truncated
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@@ -1,7 +0,0 @@
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truncated
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ine truncated
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ine truncated
|
||||
Reference in new issue
Block a user