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-rw-r--r--evaluation/clevrer/evaluation_loci_looped.ipynb164
-rw-r--r--evaluation/clevrer/evaluation_loci_unlooped.ipynb171
-rw-r--r--evaluation/clevrer/evaluation_savi.ipynb171
3 files changed, 506 insertions, 0 deletions
diff --git a/evaluation/clevrer/evaluation_loci_looped.ipynb b/evaluation/clevrer/evaluation_loci_looped.ipynb
new file mode 100644
index 0000000..75ba075
--- /dev/null
+++ b/evaluation/clevrer/evaluation_loci_looped.ipynb
@@ -0,0 +1,164 @@
+{
+ "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
+}
diff --git a/evaluation/clevrer/evaluation_loci_unlooped.ipynb b/evaluation/clevrer/evaluation_loci_unlooped.ipynb
new file mode 100644
index 0000000..51edd3c
--- /dev/null
+++ b/evaluation/clevrer/evaluation_loci_unlooped.ipynb
@@ -0,0 +1,171 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import os"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Data Loading"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# set path to resutls files\n",
+ "path = '../../out/pretrained/clevrer/loci_unlooped/results/net_loci_unlooped'\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": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "msecomplete_average: 13.490\n",
+ "msecomplete_std: 10.810\n",
+ "\n",
+ "mseblackout_average: 28.232\n",
+ "mseblackout_std: 7.041\n",
+ "\n",
+ "msevisible_average: 9.688\n",
+ "msevisible_std: 7.981\n",
+ "\n",
+ "ssimcomplete_average: 0.829\n",
+ "ssimcomplete_std: 0.096\n",
+ "\n",
+ "ssimblackout_average: 0.709\n",
+ "ssimblackout_std: 0.055\n",
+ "\n",
+ "ssimvisible_average: 0.860\n",
+ "ssimvisible_std: 0.078\n",
+ "\n",
+ "psnrcomplete_average: 26.774\n",
+ "psnrcomplete_std: 4.724\n",
+ "\n",
+ "psnrblackout_average: 21.757\n",
+ "psnrblackout_std: 1.126\n",
+ "\n",
+ "psnrvisible_average: 28.068\n",
+ "psnrvisible_std: 4.425\n",
+ "\n",
+ "percept_distcomplete_average: 0.300\n",
+ "percept_distcomplete_std: 0.138\n",
+ "\n",
+ "percept_distblackout_average: 0.474\n",
+ "percept_distblackout_std: 0.053\n",
+ "\n",
+ "percept_distvisible_average: 0.255\n",
+ "percept_distvisible_std: 0.116\n",
+ "\n",
+ "aricomplete_average: 0.365\n",
+ "aricomplete_std: 0.334\n",
+ "\n",
+ "ariblackout_average: -0.022\n",
+ "ariblackout_std: 0.038\n",
+ "\n",
+ "arivisible_average: 0.465\n",
+ "arivisible_std: 0.302\n",
+ "\n",
+ "faricomplete_average: 0.305\n",
+ "faricomplete_std: 0.281\n",
+ "\n",
+ "fariblackout_average: 0.018\n",
+ "fariblackout_std: 0.049\n",
+ "\n",
+ "farivisible_average: 0.378\n",
+ "farivisible_std: 0.269\n",
+ "\n",
+ "mioucomplete_average: 0.163\n",
+ "mioucomplete_std: 0.142\n",
+ "\n",
+ "mioublackout_average: 0.012\n",
+ "mioublackout_std: 0.015\n",
+ "\n",
+ "miouvisible_average: 0.202\n",
+ "miouvisible_std: 0.134\n",
+ "\n",
+ "apcomplete_average: 0.289\n",
+ "apcomplete_std: 0.295\n",
+ "\n",
+ "apblackout_average: 0.000\n",
+ "apblackout_std: 0.006\n",
+ "\n",
+ "apvisible_average: 0.363\n",
+ "apvisible_std: 0.287\n",
+ "\n",
+ "arcomplete_average: 0.301\n",
+ "arcomplete_std: 0.329\n",
+ "\n",
+ "arblackout_average: 0.000\n",
+ "arblackout_std: 0.007\n",
+ "\n",
+ "arvisible_average: 0.378\n",
+ "arvisible_std: 0.327\n",
+ "\n",
+ "blackoutcomplete_average: 0.205\n",
+ "blackoutcomplete_std: 0.404\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('')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "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
+}
diff --git a/evaluation/clevrer/evaluation_savi.ipynb b/evaluation/clevrer/evaluation_savi.ipynb
new file mode 100644
index 0000000..c802408
--- /dev/null
+++ b/evaluation/clevrer/evaluation_savi.ipynb
@@ -0,0 +1,171 @@
+{
+ "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/savi/results/net_savi'\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: 3.352\n",
+ "msecomplete_std: 5.657\n",
+ "\n",
+ "mseblackout_average: 13.360\n",
+ "mseblackout_std: 5.790\n",
+ "\n",
+ "msevisible_average: 0.849\n",
+ "msevisible_std: 0.543\n",
+ "\n",
+ "ssimcomplete_average: 0.934\n",
+ "ssimcomplete_std: 0.065\n",
+ "\n",
+ "ssimblackout_average: 0.814\n",
+ "ssimblackout_std: 0.052\n",
+ "\n",
+ "ssimvisible_average: 0.964\n",
+ "ssimvisible_std: 0.009\n",
+ "\n",
+ "psnrcomplete_average: 35.079\n",
+ "psnrcomplete_std: 5.418\n",
+ "\n",
+ "psnrblackout_average: 25.306\n",
+ "psnrblackout_std: 2.048\n",
+ "\n",
+ "psnrvisible_average: 37.524\n",
+ "psnrvisible_std: 2.404\n",
+ "\n",
+ "percept_distcomplete_average: 0.249\n",
+ "percept_distcomplete_std: 0.114\n",
+ "\n",
+ "percept_distblackout_average: 0.468\n",
+ "percept_distblackout_std: 0.035\n",
+ "\n",
+ "percept_distvisible_average: 0.194\n",
+ "percept_distvisible_std: 0.029\n",
+ "\n",
+ "aricomplete_average: 0.456\n",
+ "aricomplete_std: 0.266\n",
+ "\n",
+ "ariblackout_average: -0.002\n",
+ "ariblackout_std: 0.009\n",
+ "\n",
+ "arivisible_average: 0.571\n",
+ "arivisible_std: 0.152\n",
+ "\n",
+ "faricomplete_average: 0.726\n",
+ "faricomplete_std: 0.377\n",
+ "\n",
+ "fariblackout_average: 0.009\n",
+ "fariblackout_std: 0.094\n",
+ "\n",
+ "farivisible_average: 0.905\n",
+ "farivisible_std: 0.120\n",
+ "\n",
+ "mioucomplete_average: 0.285\n",
+ "mioucomplete_std: 0.144\n",
+ "\n",
+ "mioublackout_average: 0.005\n",
+ "mioublackout_std: 0.003\n",
+ "\n",
+ "miouvisible_average: 0.355\n",
+ "miouvisible_std: 0.038\n",
+ "\n",
+ "apcomplete_average: 0.248\n",
+ "apcomplete_std: 0.196\n",
+ "\n",
+ "apblackout_average: 0.000\n",
+ "apblackout_std: 0.011\n",
+ "\n",
+ "apvisible_average: 0.309\n",
+ "apvisible_std: 0.170\n",
+ "\n",
+ "arcomplete_average: 0.374\n",
+ "arcomplete_std: 0.302\n",
+ "\n",
+ "arblackout_average: 0.000\n",
+ "arblackout_std: 0.005\n",
+ "\n",
+ "arvisible_average: 0.467\n",
+ "arvisible_std: 0.265\n",
+ "\n",
+ "blackoutcomplete_average: 0.200\n",
+ "blackoutcomplete_std: 0.400\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('')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "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
+}