{ "cells": [ { "cell_type": "markdown", "id": "5dba5871", "metadata": {}, "source": [ "# In-Distribution = hem" ] }, { "cell_type": "markdown", "id": "de7c031b", "metadata": {}, "source": [ "## combined" ] }, { "cell_type": "code", "execution_count": 129, "id": "7c21eb48", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0152\t0.0130\t0.0105\t0.0135\n", "weight_shi:\t-0.0578\t0.1014\t0.1178\t0.1034\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5853569764733287\n", "CNMC 1.9901 +- 0.1085 q0: 1.7212 q10: 1.8609 q20: 1.9042 q30: 1.9291 q40: 1.9549 q50: 1.9800 q60: 2.0013 q70: 2.0351 q80: 2.0786 q90: 2.1427 q100: 2.3180\n", "one_class_0 1.9561 +- 0.0829 q0: 1.6679 q10: 1.8555 q20: 1.8869 q30: 1.9128 q40: 1.9357 q50: 1.9564 q60: 1.9747 q70: 1.9978 q80: 2.0224 q90: 2.0600 q100: 2.2041\n", "[one_class_0 CSI 0.5854] [one_class_0 best 0.5854] \n", "[one_class_mean CSI 0.5854] [one_class_mean best 0.5854] \n", "0.5854\t0.5854\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur_randpers\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# randpers : 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --distortion_scale 0.8 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_randpers_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 130, "id": "846efb49", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0109\t0.0072\t0.0133\t0.0129\n", "weight_shi:\t0.4840\t0.0844\t0.4048\t0.2004\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4842849583244716\n", "CNMC 1.9963 +- 0.4334 q0: 0.3449 q10: 1.4686 q20: 1.6647 q30: 1.7749 q40: 1.8802 q50: 1.9851 q60: 2.0904 q70: 2.2032 q80: 2.3314 q90: 2.5160 q100: 3.5596\n", "one_class_0 2.0168 +- 0.3659 q0: 0.5032 q10: 1.5638 q20: 1.7269 q30: 1.8222 q40: 1.9245 q50: 2.0083 q60: 2.0883 q70: 2.1776 q80: 2.3057 q90: 2.4967 q100: 3.3674\n", "[one_class_0 CSI 0.4843] [one_class_0 best 0.4843] \n", "[one_class_mean CSI 0.4843] [one_class_mean best 0.4843] \n", "0.4843\t0.4843\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur_sharp\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# randpers : 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --sharpness_factor 128 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_sharp_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 131, "id": "ebf2e296", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0019\t0.0039\t0.0042\t0.0047\n", "weight_shi:\t0.0159\t0.3020\t1.0707\t0.5438\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.43598274238142987\n", "CNMC 1.9968 +- 0.4243 q0: 1.0210 q10: 1.5387 q20: 1.6392 q30: 1.7221 q40: 1.7914 q50: 1.8964 q60: 2.0368 q70: 2.1923 q80: 2.3638 q90: 2.6239 q100: 3.6290\n", "one_class_0 2.0836 +- 0.4325 q0: 1.0885 q10: 1.6040 q20: 1.7218 q30: 1.8127 q40: 1.9018 q50: 1.9885 q60: 2.1022 q70: 2.2500 q80: 2.4798 q90: 2.6977 q100: 3.7788\n", "[one_class_0 CSI 0.4360] [one_class_0 best 0.4360] \n", "[one_class_mean CSI 0.4360] [one_class_mean best 0.4360] \n", "0.4360\t0.4360\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers_sharp\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# randpers : 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --distortion_scale 0.8 --resize_factor 0.08 --sharpness_factor 128 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_sharp_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 132, "id": "a7b553d3", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0011\t0.0008\t0.0009\t0.0009\n", "weight_shi:\t-0.0836\t0.1015\t0.0813\t0.0787\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5724992151024417\n", "CNMC 2.0160 +- 0.0836 q0: 1.8554 q10: 1.9224 q20: 1.9466 q30: 1.9663 q40: 1.9854 q50: 2.0042 q60: 2.0232 q70: 2.0465 q80: 2.0759 q90: 2.1259 q100: 2.3440\n", "one_class_0 1.9930 +- 0.0670 q0: 1.8047 q10: 1.9141 q20: 1.9399 q30: 1.9557 q40: 1.9704 q50: 1.9843 q60: 2.0012 q70: 2.0244 q80: 2.0475 q90: 2.0793 q100: 2.2942\n", "[one_class_0 CSI 0.5725] [one_class_0 best 0.5725] \n", "[one_class_mean CSI 0.5725] [one_class_mean best 0.5725] \n", "0.5725\t0.5725\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur_randpers_sharp\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# randpers : 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --sharpness_factor 128 --distortion_scale 0.8 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_randpers_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_randpers_sharp_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "markdown", "id": "b5d5f05f", "metadata": {}, "source": [ "## sharp" ] }, { "cell_type": "code", "execution_count": 17, "id": "13c15d92", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0082\t0.0048\t0.0035\t0.0035\n", "weight_shi:\t-0.0162\t0.0291\t0.0264\t0.0261\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.46516067612594825\n", "CNMC 2.0611 +- 0.2843 q0: 1.4233 q10: 1.7048 q20: 1.8158 q30: 1.8910 q40: 1.9831 q50: 2.0498 q60: 2.1209 q70: 2.1990 q80: 2.3022 q90: 2.4508 q100: 3.0255\n", "one_class_0 2.0896 +- 0.2109 q0: 1.5218 q10: 1.8407 q20: 1.9143 q30: 1.9720 q40: 2.0252 q50: 2.0691 q60: 2.1174 q70: 2.1761 q80: 2.2568 q90: 2.3717 q100: 2.9418\n", "[one_class_0 CSI 0.4652] [one_class_0 best 0.4652] \n", "[one_class_mean CSI 0.4652] [one_class_mean best 0.4652] \n", "0.4652\t0.4652\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 4096\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 4096 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor4096.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 18, "id": "25951e79", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0095\t0.0075\t0.0068\t0.0072\n", "weight_shi:\t-0.0480\t0.0769\t0.0704\t0.0693\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4025752235692077\n", "CNMC 1.9780 +- 0.1552 q0: 1.6133 q10: 1.7905 q20: 1.8304 q30: 1.8774 q40: 1.9265 q50: 1.9698 q60: 2.0166 q70: 2.0610 q80: 2.1123 q90: 2.1776 q100: 2.5595\n", "one_class_0 2.0255 +- 0.1272 q0: 1.6800 q10: 1.8659 q20: 1.9179 q30: 1.9585 q40: 1.9884 q50: 2.0210 q60: 2.0530 q70: 2.0845 q80: 2.1202 q90: 2.1844 q100: 2.7354\n", "[one_class_0 CSI 0.4026] [one_class_0 best 0.4026] \n", "[one_class_mean CSI 0.4026] [one_class_mean best 0.4026] \n", "0.4026\t0.4026\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 2048\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 2048 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor2048.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 133, "id": "4fc12b02", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0089\t0.0059\t0.0064\t0.0063\n", "weight_shi:\t-0.0361\t0.0765\t0.0742\t0.0727\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4227749420188578\n", "CNMC 2.0207 +- 0.1832 q0: 1.5627 q10: 1.7726 q20: 1.8618 q30: 1.9226 q40: 1.9811 q50: 2.0217 q60: 2.0627 q70: 2.1123 q80: 2.1832 q90: 2.2560 q100: 2.6861\n", "one_class_0 2.0632 +- 0.1200 q0: 1.6644 q10: 1.9104 q20: 1.9645 q30: 2.0071 q40: 2.0386 q50: 2.0633 q60: 2.0887 q70: 2.1181 q80: 2.1534 q90: 2.2160 q100: 2.5742\n", "[one_class_0 CSI 0.4228] [one_class_0 best 0.4228] \n", "[one_class_mean CSI 0.4228] [one_class_mean best 0.4228] \n", "0.4228\t0.4228\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 1024\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 1024 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor1024.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 20, "id": "99698eb6", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0067\t0.0032\t0.0035\t0.0038\n", "weight_shi:\t-0.0499\t0.0682\t0.0675\t0.0722\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3898554522529092\n", "CNMC 1.9663 +- 0.1069 q0: 1.6970 q10: 1.8437 q20: 1.8799 q30: 1.9043 q40: 1.9235 q50: 1.9537 q60: 1.9831 q70: 2.0145 q80: 2.0505 q90: 2.1087 q100: 2.5004\n", "one_class_0 2.0038 +- 0.0970 q0: 1.7568 q10: 1.8902 q20: 1.9239 q30: 1.9445 q40: 1.9657 q50: 1.9897 q60: 2.0196 q70: 2.0483 q80: 2.0868 q90: 2.1398 q100: 2.3773\n", "[one_class_0 CSI 0.3899] [one_class_0 best 0.3899] \n", "[one_class_mean CSI 0.3899] [one_class_mean best 0.3899] \n", "0.3899\t0.3899\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 512\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 512 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor512.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 21, "id": "01e6d61a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0053\t0.0084\t0.0092\t0.0087\n", "weight_shi:\t0.4300\t0.0647\t0.0695\t0.0685\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5784846919656873\n", "CNMC 2.1270 +- 0.9610 q0: -0.9326 q10: 0.9101 q20: 1.3880 q30: 1.6010 q40: 1.8639 q50: 2.1067 q60: 2.3374 q70: 2.5413 q80: 2.8893 q90: 3.3775 q100: 5.1585\n", "one_class_0 1.8950 +- 0.7309 q0: -0.2104 q10: 1.0100 q20: 1.3020 q30: 1.4936 q40: 1.6684 q50: 1.8373 q60: 2.0139 q70: 2.2017 q80: 2.4870 q90: 2.8570 q100: 4.5441\n", "[one_class_0 CSI 0.5785] [one_class_0 best 0.5785] \n", "[one_class_mean CSI 0.5785] [one_class_mean best 0.5785] \n", "0.5785\t0.5785\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 256\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 256 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor256.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 22, "id": "65cc4fcd", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0089\t0.0063\t0.0075\t0.0065\n", "weight_shi:\t-0.0184\t0.0363\t0.0371\t0.0371\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3679688370350115\n", "CNMC 1.9800 +- 0.0919 q0: 1.7207 q10: 1.8629 q20: 1.8911 q30: 1.9241 q40: 1.9548 q50: 1.9755 q60: 2.0034 q70: 2.0354 q80: 2.0631 q90: 2.1071 q100: 2.2242\n", "one_class_0 2.0217 +- 0.0794 q0: 1.7727 q10: 1.9194 q20: 1.9543 q30: 1.9779 q40: 1.9999 q50: 2.0212 q60: 2.0423 q70: 2.0650 q80: 2.0906 q90: 2.1259 q100: 2.2548\n", "[one_class_0 CSI 0.3680] [one_class_0 best 0.3680] \n", "[one_class_mean CSI 0.3680] [one_class_mean best 0.3680] \n", "0.3680\t0.3680\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 150\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 150 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor150.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 23, "id": "e13b48db", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0083\t0.0053\t0.0056\t0.0053\n", "weight_shi:\t-0.1256\t0.0869\t0.0823\t0.0921\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4935733347512128\n", "CNMC 2.0389 +- 0.1184 q0: 1.7300 q10: 1.8883 q20: 1.9358 q30: 1.9771 q40: 2.0079 q50: 2.0342 q60: 2.0657 q70: 2.0974 q80: 2.1469 q90: 2.1945 q100: 2.5086\n", "one_class_0 2.0418 +- 0.0930 q0: 1.7624 q10: 1.9334 q20: 1.9610 q30: 1.9867 q40: 2.0125 q50: 2.0354 q60: 2.0608 q70: 2.0915 q80: 2.1163 q90: 2.1599 q100: 2.3964\n", "[one_class_0 CSI 0.4936] [one_class_0 best 0.4936] \n", "[one_class_mean CSI 0.4936] [one_class_mean best 0.4936] \n", "0.4936\t0.4936\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 140\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 140 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor140.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 24, "id": "29cf690f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0045\t0.0043\t0.0070\t0.0053\n", "weight_shi:\t-0.0813\t0.0676\t0.0710\t0.0626\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4419042880725954\n", "CNMC 2.0129 +- 0.1195 q0: 1.5835 q10: 1.8643 q20: 1.9252 q30: 1.9581 q40: 1.9900 q50: 2.0157 q60: 2.0378 q70: 2.0653 q80: 2.1055 q90: 2.1542 q100: 2.4828\n", "one_class_0 2.0362 +- 0.1010 q0: 1.6891 q10: 1.9098 q20: 1.9486 q30: 1.9817 q40: 2.0087 q50: 2.0351 q60: 2.0576 q70: 2.0853 q80: 2.1206 q90: 2.1651 q100: 2.3927\n", "[one_class_0 CSI 0.4419] [one_class_0 best 0.4419] \n", "[one_class_mean CSI 0.4419] [one_class_mean best 0.4419] \n", "0.4419\t0.4419\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 130\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 130 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor130.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 25, "id": "dfaa2119", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0130\t0.0032\t0.0032\t0.0028\n", "weight_shi:\t-0.0796\t0.1288\t0.1192\t0.1286\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.47003337080586194\n", "CNMC 1.9969 +- 0.1287 q0: 1.5279 q10: 1.8373 q20: 1.9073 q30: 1.9387 q40: 1.9663 q50: 1.9928 q60: 2.0270 q70: 2.0640 q80: 2.0993 q90: 2.1517 q100: 2.4161\n", "one_class_0 2.0110 +- 0.1133 q0: 1.6407 q10: 1.8709 q20: 1.9143 q30: 1.9536 q40: 1.9857 q50: 2.0121 q60: 2.0374 q70: 2.0675 q80: 2.1043 q90: 2.1554 q100: 2.3778\n", "[one_class_0 CSI 0.4700] [one_class_0 best 0.4700] \n", "[one_class_mean CSI 0.4700] [one_class_mean best 0.4700] \n", "0.4700\t0.4700\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 120\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 120 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor120.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 26, "id": "e3eecf30", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0091\t0.0036\t0.0042\t0.0040\n", "weight_shi:\t0.2410\t0.5432\t0.2487\t0.3103\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5940902277722075\n", "CNMC 2.0988 +- 0.5314 q0: 1.0497 q10: 1.4954 q20: 1.6747 q30: 1.8162 q40: 1.9078 q50: 2.0314 q60: 2.1299 q70: 2.2698 q80: 2.4594 q90: 2.8458 q100: 4.3420\n", "one_class_0 1.9324 +- 0.3714 q0: 1.0642 q10: 1.5287 q20: 1.6460 q30: 1.7249 q40: 1.8095 q50: 1.8731 q60: 1.9535 q70: 2.0458 q80: 2.1797 q90: 2.4138 q100: 3.6869\n", "[one_class_0 CSI 0.5941] [one_class_0 best 0.5941] \n", "[one_class_mean CSI 0.5941] [one_class_mean best 0.5941] \n", "0.5941\t0.5941\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 128\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 128 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor128.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 27, "id": "d7d86bff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0077\t0.0039\t0.0057\t0.0045\n", "weight_shi:\t-0.0543\t0.1223\t0.1116\t0.1079\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4230414273995078\n", "CNMC 1.9898 +- 0.1931 q0: 1.3874 q10: 1.7331 q20: 1.8325 q30: 1.9150 q40: 1.9682 q50: 2.0080 q60: 2.0511 q70: 2.1020 q80: 2.1509 q90: 2.2176 q100: 2.4975\n", "one_class_0 2.0442 +- 0.1594 q0: 1.5034 q10: 1.8378 q20: 1.9120 q30: 1.9673 q40: 2.0118 q50: 2.0508 q60: 2.0920 q70: 2.1314 q80: 2.1747 q90: 2.2473 q100: 2.5530\n", "[one_class_0 CSI 0.4230] [one_class_0 best 0.4230] \n", "[one_class_mean CSI 0.4230] [one_class_mean best 0.4230] \n", "0.4230\t0.4230\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 100\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 100 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor100.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 28, "id": "d60476b1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0071\t0.0035\t0.0055\t0.0033\n", "weight_shi:\t-0.7731\t-0.4426\t3.0750\t-1.0296\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3861885880958892\n", "CNMC 1.8504 +- 1.7281 q0: -3.9915 q10: -0.3957 q20: 0.3727 q30: 1.0483 q40: 1.6967 q50: 2.0760 q60: 2.4763 q70: 2.8382 q80: 3.3079 q90: 3.8465 q100: 5.6520\n", "one_class_0 2.5429 +- 1.3399 q0: -4.5019 q10: 0.9296 q20: 1.4679 q30: 1.9042 q40: 2.2539 q50: 2.5979 q60: 2.9289 q70: 3.3053 q80: 3.6585 q90: 4.1959 q100: 6.6848\n", "[one_class_0 CSI 0.3862] [one_class_0 best 0.3862] \n", "[one_class_mean CSI 0.3862] [one_class_mean best 0.3862] \n", "0.3862\t0.3862\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 80\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 80 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor80.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 29, "id": "b367669a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0083\t0.0112\t0.0076\t0.0136\n", "weight_shi:\t-0.0567\t0.1140\t0.0842\t0.1028\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.376367240907848\n", "CNMC 1.9968 +- 0.0768 q0: 1.7939 q10: 1.9005 q20: 1.9341 q30: 1.9569 q40: 1.9751 q50: 1.9937 q60: 2.0157 q70: 2.0367 q80: 2.0629 q90: 2.0964 q100: 2.2761\n", "one_class_0 2.0289 +- 0.0677 q0: 1.8223 q10: 1.9439 q20: 1.9701 q30: 1.9928 q40: 2.0111 q50: 2.0279 q60: 2.0448 q70: 2.0625 q80: 2.0815 q90: 2.1167 q100: 2.3343\n", "[one_class_0 CSI 0.3764] [one_class_0 best 0.3764] \n", "[one_class_mean CSI 0.3764] [one_class_mean best 0.3764] \n", "0.3764\t0.3764\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 64\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 64 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor64.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 30, "id": "dce638a8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0150\t0.0058\t0.0129\t0.0054\n", "weight_shi:\t-0.0982\t0.1165\t0.1059\t0.0929\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4102051874132815\n", "CNMC 1.9836 +- 0.2025 q0: 1.4858 q10: 1.7023 q20: 1.8012 q30: 1.8770 q40: 1.9428 q50: 2.0013 q60: 2.0495 q70: 2.0936 q80: 2.1462 q90: 2.2425 q100: 2.5144\n", "one_class_0 2.0499 +- 0.1863 q0: 1.5414 q10: 1.8119 q20: 1.8950 q30: 1.9488 q40: 1.9984 q50: 2.0487 q60: 2.0962 q70: 2.1512 q80: 2.2168 q90: 2.2846 q100: 2.6101\n", "[one_class_0 CSI 0.4102] [one_class_0 best 0.4102] \n", "[one_class_mean CSI 0.4102] [one_class_mean best 0.4102] \n", "0.4102\t0.4102\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 32\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 32 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor32.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 31, "id": "28387a64", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0088\t0.0070\t0.0079\t0.0070\n", "weight_shi:\t-0.0517\t0.1752\t0.1985\t0.2796\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4567964532758079\n", "CNMC 2.0252 +- 0.2349 q0: 1.3683 q10: 1.7184 q20: 1.8035 q30: 1.8906 q40: 1.9540 q50: 2.0153 q60: 2.0821 q70: 2.1619 q80: 2.2506 q90: 2.3384 q100: 2.6113\n", "one_class_0 2.0617 +- 0.2072 q0: 1.5917 q10: 1.7983 q20: 1.8819 q30: 1.9423 q40: 1.9904 q50: 2.0477 q60: 2.1076 q70: 2.1646 q80: 2.2533 q90: 2.3431 q100: 2.6298\n", "[one_class_0 CSI 0.4568] [one_class_0 best 0.4568] \n", "[one_class_mean CSI 0.4568] [one_class_mean best 0.4568] \n", "0.4568\t0.4568\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 16\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 16 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor16.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 32, "id": "424cd4b8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0167\t0.0112\t0.0119\t0.0098\n", "weight_shi:\t-0.1065\t0.1467\t0.1401\t0.1203\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4809307872269316\n", "CNMC 2.0080 +- 0.2589 q0: 1.4062 q10: 1.6813 q20: 1.7879 q30: 1.8753 q40: 1.9309 q50: 1.9964 q60: 2.0601 q70: 2.1217 q80: 2.2165 q90: 2.3636 q100: 3.0258\n", "one_class_0 2.0288 +- 0.2475 q0: 1.4597 q10: 1.7282 q20: 1.8162 q30: 1.8799 q40: 1.9422 q50: 1.9987 q60: 2.0671 q70: 2.1423 q80: 2.2336 q90: 2.3568 q100: 3.5008\n", "[one_class_0 CSI 0.4809] [one_class_0 best 0.4809] \n", "[one_class_mean CSI 0.4809] [one_class_mean best 0.4809] \n", "0.4809\t0.4809\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 8 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor8.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 33, "id": "b30452ce", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0033\t0.0030\t0.0025\t0.0028\n", "weight_shi:\t-0.0191\t0.0502\t0.0455\t0.0473\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4414099292073041\n", "CNMC 1.9717 +- 0.1514 q0: 1.4512 q10: 1.7885 q20: 1.8443 q30: 1.8923 q40: 1.9275 q50: 1.9674 q60: 2.0006 q70: 2.0525 q80: 2.0992 q90: 2.1705 q100: 2.4112\n", "one_class_0 1.9985 +- 0.1198 q0: 1.6117 q10: 1.8478 q20: 1.9013 q30: 1.9366 q40: 1.9671 q50: 1.9967 q60: 2.0257 q70: 2.0616 q80: 2.0994 q90: 2.1570 q100: 2.3699\n", "[one_class_0 CSI 0.4414] [one_class_0 best 0.4414] \n", "[one_class_mean CSI 0.4414] [one_class_mean best 0.4414] \n", "0.4414\t0.4414\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 5\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 5 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor5.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 34, "id": "61511c88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0048\t0.0048\t0.0033\t0.0040\n", "weight_shi:\t-0.0216\t0.0573\t0.0466\t0.0474\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3330541883146477\n", "CNMC 1.9613 +- 0.1613 q0: 1.4001 q10: 1.7205 q20: 1.8317 q30: 1.8884 q40: 1.9420 q50: 1.9740 q60: 2.0204 q70: 2.0591 q80: 2.1023 q90: 2.1507 q100: 2.3497\n", "one_class_0 2.0506 +- 0.1298 q0: 1.5709 q10: 1.8729 q20: 1.9474 q30: 2.0023 q40: 2.0388 q50: 2.0668 q60: 2.0970 q70: 2.1272 q80: 2.1610 q90: 2.1981 q100: 2.4918\n", "[one_class_0 CSI 0.3331] [one_class_0 best 0.3331] \n", "[one_class_mean CSI 0.3331] [one_class_mean best 0.3331] \n", "0.3331\t0.3331\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 4\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 4 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor4.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 35, "id": "9aa87298", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0025\t0.0027\t0.0023\t0.0026\n", "weight_shi:\t-0.0247\t0.0743\t0.0809\t0.0786\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.32097499468295204\n", "CNMC 1.9756 +- 0.0921 q0: 1.6810 q10: 1.8631 q20: 1.9010 q30: 1.9281 q40: 1.9493 q50: 1.9693 q60: 1.9932 q70: 2.0205 q80: 2.0561 q90: 2.0987 q100: 2.2881\n", "one_class_0 2.0291 +- 0.0715 q0: 1.8113 q10: 1.9469 q20: 1.9690 q30: 1.9889 q40: 2.0060 q50: 2.0221 q60: 2.0372 q70: 2.0598 q80: 2.0847 q90: 2.1253 q100: 2.3137\n", "[one_class_0 CSI 0.3210] [one_class_0 best 0.3210] \n", "[one_class_mean CSI 0.3210] [one_class_mean best 0.3210] \n", "0.3210\t0.3210\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor3.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 36, "id": "ed261f4c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0016\t0.0017\t0.0018\t0.0018\n", "weight_shi:\t-0.0191\t0.0634\t0.0692\t0.0681\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5479179959286604\n", "CNMC 2.0439 +- 0.2491 q0: 1.3671 q10: 1.7149 q20: 1.8289 q30: 1.9114 q40: 1.9969 q50: 2.0563 q60: 2.1157 q70: 2.1758 q80: 2.2482 q90: 2.3551 q100: 2.6738\n", "one_class_0 2.0114 +- 0.1906 q0: 1.4681 q10: 1.7626 q20: 1.8467 q30: 1.9083 q40: 1.9608 q50: 2.0043 q60: 2.0576 q70: 2.1069 q80: 2.1710 q90: 2.2558 q100: 2.5480\n", "[one_class_0 CSI 0.5479] [one_class_0 best 0.5479] \n", "[one_class_mean CSI 0.5479] [one_class_mean best 0.5479] \n", "0.5479\t0.5479\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharpness : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --sharpness_factor 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor2.0_one_class_1/last.model\"" ] }, { "cell_type": "markdown", "id": "3f347111", "metadata": {}, "source": [ "## randpers" ] }, { "cell_type": "code", "execution_count": 37, "id": "6954e9f3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0027\t0.0028\t0.0028\t0.0029\n", "weight_shi:\t0.0396\t-0.1267\t-0.1178\t-0.1344\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.35701318627897793\n", "CNMC 1.9933 +- 0.0426 q0: 1.7637 q10: 1.9470 q20: 1.9683 q30: 1.9825 q40: 1.9896 q50: 1.9981 q60: 2.0059 q70: 2.0119 q80: 2.0228 q90: 2.0391 q100: 2.1039\n", "one_class_0 2.0107 +- 0.0300 q0: 1.8398 q10: 1.9753 q20: 1.9909 q30: 2.0006 q40: 2.0073 q50: 2.0134 q60: 2.0197 q70: 2.0245 q80: 2.0323 q90: 2.0429 q100: 2.0991\n", "[one_class_0 CSI 0.3570] [one_class_0 best 0.3570] \n", "[one_class_mean CSI 0.3570] [one_class_mean best 0.3570] \n", "0.3570\t0.3570\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.95\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.95 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.95_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 38, "id": "7ef390e9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0079\t0.0098\t0.0115\t0.0104\n", "weight_shi:\t-0.2285\t-6.8399\t0.4918\t0.3229\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5641122049038374\n", "CNMC 1.9712 +- 0.8313 q0: -4.4253 q10: 0.9802 q20: 1.5045 q30: 1.8002 q40: 1.9917 q50: 2.1173 q60: 2.2353 q70: 2.3608 q80: 2.5048 q90: 2.7707 q100: 4.2407\n", "one_class_0 1.9180 +- 0.6218 q0: -3.1624 q10: 1.2584 q20: 1.5541 q30: 1.7231 q40: 1.8312 q50: 1.9474 q60: 2.0646 q70: 2.2017 q80: 2.3455 q90: 2.6130 q100: 4.2616\n", "[one_class_0 CSI 0.5641] [one_class_0 best 0.5641] \n", "[one_class_mean CSI 0.5641] [one_class_mean best 0.5641] \n", "0.5641\t0.5641\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.9\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.9 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.9_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 39, "id": "1205e882", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0034\t0.0047\t0.0029\t0.0041\n", "weight_shi:\t0.1303\t-0.3875\t-0.1777\t-0.3820\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.34714879632161555\n", "CNMC 1.9226 +- 0.3041 q0: 0.5031 q10: 1.4958 q20: 1.7161 q30: 1.8443 q40: 1.9245 q50: 1.9879 q60: 2.0373 q70: 2.0889 q80: 2.1566 q90: 2.2287 q100: 2.5521\n", "one_class_0 2.0685 +- 0.2043 q0: 1.1682 q10: 1.8203 q20: 1.9473 q30: 2.0089 q40: 2.0513 q50: 2.0872 q60: 2.1284 q70: 2.1701 q80: 2.2162 q90: 2.2834 q100: 2.6224\n", "[one_class_0 CSI 0.3471] [one_class_0 best 0.3471] \n", "[one_class_mean CSI 0.3471] [one_class_mean best 0.3471] \n", "0.3471\t0.3471\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.85\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.85 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.85_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 40, "id": "8887546c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0020\t0.0037\t0.0026\t0.0039\n", "weight_shi:\t0.1393\t2.5299\t-1.4218\t1.2437\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6913884078226435\n", "CNMC 2.0752 +- 0.3123 q0: 0.7320 q10: 1.7083 q20: 1.8297 q30: 1.9220 q40: 2.0047 q50: 2.0690 q60: 2.1391 q70: 2.2162 q80: 2.3010 q90: 2.4549 q100: 3.2842\n", "one_class_0 1.8917 +- 0.2289 q0: 0.7422 q10: 1.6150 q20: 1.7197 q30: 1.7818 q40: 1.8380 q50: 1.8923 q60: 1.9400 q70: 1.9926 q80: 2.0616 q90: 2.1731 q100: 2.9070\n", "[one_class_0 CSI 0.6914] [one_class_0 best 0.6914] \n", "[one_class_mean CSI 0.6914] [one_class_mean best 0.6914] \n", "0.6914\t0.6914\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.8 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.8_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 41, "id": "b65d2295", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0080\t0.0036\t0.0038\t0.0054\n", "weight_shi:\t-0.0669\t-0.5647\t-0.7888\t0.5885\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.35124039133473095\n", "CNMC 1.9592 +- 0.1769 q0: 1.1540 q10: 1.7506 q20: 1.8287 q30: 1.8809 q40: 1.9227 q50: 1.9622 q60: 1.9930 q70: 2.0505 q80: 2.0959 q90: 2.1715 q100: 2.7656\n", "one_class_0 2.0376 +- 0.1423 q0: 1.0198 q10: 1.8838 q20: 1.9409 q30: 1.9806 q40: 2.0144 q50: 2.0407 q60: 2.0708 q70: 2.0989 q80: 2.1348 q90: 2.1967 q100: 2.6480\n", "[one_class_0 CSI 0.3512] [one_class_0 best 0.3512] \n", "[one_class_mean CSI 0.3512] [one_class_mean best 0.3512] \n", "0.3512\t0.3512\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.75 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.75_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 42, "id": "2a818378", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0034\t0.0037\t0.0024\t0.0028\n", "weight_shi:\t0.5181\t-2.5612\t-0.2828\t-0.4473\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3594818156959256\n", "CNMC 1.5977 +- 1.3081 q0: -2.9399 q10: -0.2131 q20: 0.5889 q30: 1.0500 q40: 1.4828 q50: 1.7567 q60: 2.0337 q70: 2.3642 q80: 2.6741 q90: 3.1919 q100: 4.5132\n", "one_class_0 2.2261 +- 1.0824 q0: -1.7685 q10: 0.7646 q20: 1.4013 q30: 1.7643 q40: 2.0621 q50: 2.3193 q60: 2.5929 q70: 2.8838 q80: 3.1160 q90: 3.5429 q100: 5.0474\n", "[one_class_0 CSI 0.3595] [one_class_0 best 0.3595] \n", "[one_class_mean CSI 0.3595] [one_class_mean best 0.3595] \n", "0.3595\t0.3595\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.6\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.6 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.6_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 43, "id": "09a15dda", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0043\t0.0115\t0.0075\t0.0087\n", "weight_shi:\t12.1609\t0.3968\t2.0101\t0.4812\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.36039204367068733\n", "CNMC 1.4531 +- 7.5510 q0: -28.7074 q10: -8.1564 q20: -3.7419 q30: -1.3692 q40: 0.5754 q50: 2.0721 q60: 3.7007 q70: 5.1638 q80: 7.3805 q90: 10.4019 q100: 20.0002\n", "one_class_0 4.8084 +- 5.1144 q0: -14.2655 q10: -1.2285 q20: 1.1701 q30: 2.5734 q40: 3.7262 q50: 4.8972 q60: 5.9430 q70: 7.0902 q80: 8.7584 q90: 11.3302 q100: 19.8412\n", "[one_class_0 CSI 0.3604] [one_class_0 best 0.3604] \n", "[one_class_mean CSI 0.3604] [one_class_mean best 0.3604] \n", "0.3604\t0.3604\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --distortion_scale 0.3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.3_one_class_1/last.model\"" ] }, { "cell_type": "markdown", "id": "47013663", "metadata": {}, "source": [ "## blur" ] }, { "cell_type": "code", "execution_count": 134, "id": "958ecba3", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0038\t0.0072\t0.0039\t0.0044\n", "weight_shi:\t-0.1658\t0.1714\t0.2799\t0.2838\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4812004375170905\n", "CNMC 1.9384 +- 0.2410 q0: 1.5304 q10: 1.7013 q20: 1.7508 q30: 1.7894 q40: 1.8299 q50: 1.8827 q60: 1.9243 q70: 1.9999 q80: 2.0841 q90: 2.2637 q100: 2.8485\n", "one_class_0 1.9219 +- 0.1651 q0: 1.5451 q10: 1.7386 q20: 1.7816 q30: 1.8174 q40: 1.8548 q50: 1.8945 q60: 1.9407 q70: 1.9846 q80: 2.0549 q90: 2.1446 q100: 2.6371\n", "[one_class_0 CSI 0.4812] [one_class_0 best 0.4812] \n", "[one_class_mean CSI 0.4812] [one_class_mean best 0.4812] \n", "0.4812\t0.4812\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 180\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 180 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma180.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 135, "id": "a3f7ef72", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0025\t0.0058\t0.0024\t0.0029\n", "weight_shi:\t-0.0568\t0.0831\t0.1701\t0.1303\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6192537902956279\n", "CNMC 2.0247 +- 0.0991 q0: 1.8346 q10: 1.9155 q20: 1.9404 q30: 1.9652 q40: 1.9879 q50: 2.0067 q60: 2.0291 q70: 2.0625 q80: 2.1019 q90: 2.1563 q100: 2.4786\n", "one_class_0 1.9853 +- 0.0765 q0: 1.7917 q10: 1.9064 q20: 1.9276 q30: 1.9429 q40: 1.9598 q50: 1.9743 q60: 1.9887 q70: 2.0055 q80: 2.0343 q90: 2.0845 q100: 2.3701\n", "[one_class_0 CSI 0.6193] [one_class_0 best 0.6193] \n", "[one_class_mean CSI 0.6193] [one_class_mean best 0.6193] \n", "0.6193\t0.6193\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 120\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 120 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma120.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 147, "id": "2f2a8808", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0030\t0.0043\t0.0026\t0.0028\n", "weight_shi:\t-0.0889\t0.1756\t0.3138\t0.2610\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5952460527248604\n", "CNMC 2.0008 +- 0.0139 q0: 1.9745 q10: 1.9866 q20: 1.9900 q30: 1.9930 q40: 1.9955 q50: 1.9986 q60: 2.0019 q70: 2.0048 q80: 2.0099 q90: 2.0166 q100: 2.0896\n", "one_class_0 1.9964 +- 0.0119 q0: 1.9575 q10: 1.9833 q20: 1.9872 q30: 1.9899 q40: 1.9925 q50: 1.9948 q60: 1.9973 q70: 2.0007 q80: 2.0051 q90: 2.0119 q100: 2.0732\n", "[one_class_0 CSI 0.5952] [one_class_0 best 0.5952] \n", "[one_class_mean CSI 0.5952] [one_class_mean best 0.5952] \n", "0.5952\t0.5952\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 110\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 110 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma110.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 136, "id": "08a6959c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0067\t0.0043\t0.0047\t0.0049\n", "weight_shi:\t-0.0583\t0.0915\t0.2051\t0.1700\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.633952896018797\n", "CNMC 1.9904 +- 0.1692 q0: 1.5494 q10: 1.7849 q20: 1.8442 q30: 1.9005 q40: 1.9430 q50: 1.9786 q60: 2.0203 q70: 2.0602 q80: 2.1209 q90: 2.2064 q100: 2.5511\n", "one_class_0 1.9167 +- 0.1098 q0: 1.5787 q10: 1.7796 q20: 1.8329 q30: 1.8646 q40: 1.8922 q50: 1.9150 q60: 1.9402 q70: 1.9662 q80: 1.9991 q90: 2.0546 q100: 2.2965\n", "[one_class_0 CSI 0.6340] [one_class_0 best 0.6340] \n", "[one_class_mean CSI 0.6340] [one_class_mean best 0.6340] \n", "0.6340\t0.6340\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 105\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 105 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma105.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 137, "id": "a4a4eee1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0091\t0.0045\t0.0091\t0.0070\n", "weight_shi:\t-0.0676\t0.0975\t0.1849\t0.1972\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5476483456385015\n", "CNMC 1.9769 +- 0.2661 q0: 1.3171 q10: 1.6312 q20: 1.7272 q30: 1.8319 q40: 1.9118 q50: 1.9776 q60: 2.0460 q70: 2.1125 q80: 2.1924 q90: 2.3278 q100: 2.8173\n", "one_class_0 1.9268 +- 0.2241 q0: 1.2928 q10: 1.6165 q20: 1.7138 q30: 1.8152 q40: 1.8859 q50: 1.9465 q60: 2.0048 q70: 2.0580 q80: 2.1179 q90: 2.1973 q100: 2.5704\n", "[one_class_0 CSI 0.5476] [one_class_0 best 0.5476] \n", "[one_class_mean CSI 0.5476] [one_class_mean best 0.5476] \n", "0.5476\t0.5476\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 100\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 100 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma100.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 138, "id": "8f0ceb15", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0018\t0.0028\t0.0016\t0.0018\n", "weight_shi:\t-0.2029\t0.1970\t1.0597\t0.4185\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5393334953767002\n", "CNMC 1.9749 +- 0.3046 q0: 1.1986 q10: 1.5960 q20: 1.7089 q30: 1.8060 q40: 1.8905 q50: 1.9696 q60: 2.0356 q70: 2.1233 q80: 2.2217 q90: 2.3752 q100: 3.1061\n", "one_class_0 1.9275 +- 0.2387 q0: 1.1897 q10: 1.6222 q20: 1.7266 q30: 1.8084 q40: 1.8732 q50: 1.9343 q60: 1.9958 q70: 2.0464 q80: 2.1172 q90: 2.2327 q100: 2.6893\n", "[one_class_0 CSI 0.5393] [one_class_0 best 0.5393] \n", "[one_class_mean CSI 0.5393] [one_class_mean best 0.5393] \n", "0.5393\t0.5393\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 95\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 95 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma95.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 139, "id": "7d89e279", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0075\t0.0041\t0.0071\t0.0059\n", "weight_shi:\t-0.0360\t0.0714\t0.1079\t0.0991\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5292488277175179\n", "CNMC 1.9774 +- 0.1920 q0: 1.5068 q10: 1.7357 q20: 1.8106 q30: 1.8745 q40: 1.9206 q50: 1.9753 q60: 2.0197 q70: 2.0694 q80: 2.1299 q90: 2.2192 q100: 2.6272\n", "one_class_0 1.9507 +- 0.1545 q0: 1.4789 q10: 1.7436 q20: 1.8103 q30: 1.8750 q40: 1.9239 q50: 1.9683 q60: 2.0050 q70: 2.0411 q80: 2.0780 q90: 2.1379 q100: 2.3968\n", "[one_class_0 CSI 0.5292] [one_class_0 best 0.5292] \n", "[one_class_mean CSI 0.5292] [one_class_mean best 0.5292] \n", "0.5292\t0.5292\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 90\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 90 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma90.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 140, "id": "ebb47e6b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0050\t0.0117\t0.0038\t0.0049\n", "weight_shi:\t-0.2427\t0.2328\t1.3692\t0.7248\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.557083573866456\n", "CNMC 2.0005 +- 0.1926 q0: 1.3343 q10: 1.8135 q20: 1.8631 q30: 1.9060 q40: 1.9410 q50: 1.9699 q60: 2.0110 q70: 2.0589 q80: 2.1204 q90: 2.2186 q100: 3.1284\n", "one_class_0 1.9634 +- 0.1487 q0: 1.4064 q10: 1.8025 q20: 1.8544 q30: 1.8886 q40: 1.9192 q50: 1.9463 q60: 1.9749 q70: 2.0096 q80: 2.0594 q90: 2.1522 q100: 2.5877\n", "[one_class_0 CSI 0.5571] [one_class_0 best 0.5571] \n", "[one_class_mean CSI 0.5571] [one_class_mean best 0.5571] \n", "0.5571\t0.5571\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 80\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 80 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma80.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 141, "id": "7d6e0050", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0062\t0.0053\t0.0066\t0.0062\n", "weight_shi:\t-0.0434\t0.0771\t0.1221\t0.1065\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5821104122990916\n", "CNMC 1.9984 +- 0.0869 q0: 1.7841 q10: 1.8832 q20: 1.9216 q30: 1.9505 q40: 1.9768 q50: 1.9991 q60: 2.0230 q70: 2.0443 q80: 2.0710 q90: 2.1126 q100: 2.2334\n", "one_class_0 1.9740 +- 0.0685 q0: 1.7594 q10: 1.8780 q20: 1.9143 q30: 1.9428 q40: 1.9641 q50: 1.9808 q60: 1.9973 q70: 2.0131 q80: 2.0305 q90: 2.0551 q100: 2.1770\n", "[one_class_0 CSI 0.5821] [one_class_0 best 0.5821] \n", "[one_class_mean CSI 0.5821] [one_class_mean best 0.5821] \n", "0.5821\t0.5821\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 60\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 60 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma60.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 142, "id": "df7becce", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0045\t0.0051\t0.0033\t0.0041\n", "weight_shi:\t-0.1512\t0.2745\t0.6510\t0.4026\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6940311072625811\n", "CNMC 2.0096 +- 0.0626 q0: 1.8488 q10: 1.9389 q20: 1.9597 q30: 1.9741 q40: 1.9884 q50: 2.0031 q60: 2.0185 q70: 2.0342 q80: 2.0520 q90: 2.0853 q100: 2.2770\n", "one_class_0 1.9718 +- 0.0446 q0: 1.8450 q10: 1.9219 q20: 1.9383 q30: 1.9495 q40: 1.9584 q50: 1.9680 q60: 1.9769 q70: 1.9880 q80: 2.0015 q90: 2.0244 q100: 2.2023\n", "[one_class_0 CSI 0.6940] [one_class_0 best 0.6940] \n", "[one_class_mean CSI 0.6940] [one_class_mean best 0.6940] \n", "0.6940\t0.6940\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma40.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 143, "id": "b7036b42", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0017\t0.0020\t0.0015\t0.0016\n", "weight_shi:\t0.0317\t-0.1164\t-0.0840\t-0.0812\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.39877986408612603\n", "CNMC 1.9759 +- 0.1316 q0: 1.4471 q10: 1.8010 q20: 1.8983 q30: 1.9382 q40: 1.9698 q50: 1.9932 q60: 2.0241 q70: 2.0528 q80: 2.0799 q90: 2.1197 q100: 2.2278\n", "one_class_0 2.0210 +- 0.0942 q0: 1.5614 q10: 1.8968 q20: 1.9555 q30: 1.9874 q40: 2.0148 q50: 2.0364 q60: 2.0551 q70: 2.0753 q80: 2.0963 q90: 2.1246 q100: 2.2320\n", "[one_class_0 CSI 0.3988] [one_class_0 best 0.3988] \n", "[one_class_mean CSI 0.3988] [one_class_mean best 0.3988] \n", "0.3988\t0.3988\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 20\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 20 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma20.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 144, "id": "e7b68654", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0020\t0.0035\t0.0027\t0.0027\n", "weight_shi:\t0.1013\t-0.5641\t-0.5419\t-0.3880\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.33394542683235595\n", "CNMC 1.9739 +- 0.2803 q0: 1.2318 q10: 1.5933 q20: 1.7359 q30: 1.8196 q40: 1.9141 q50: 1.9863 q60: 2.0640 q70: 2.1425 q80: 2.2339 q90: 2.3203 q100: 2.6037\n", "one_class_0 2.1309 +- 0.1875 q0: 1.4830 q10: 1.8910 q20: 1.9714 q30: 2.0347 q40: 2.0807 q50: 2.1311 q60: 2.1754 q70: 2.2372 q80: 2.3011 q90: 2.3743 q100: 2.6831\n", "[one_class_0 CSI 0.3339] [one_class_0 best 0.3339] \n", "[one_class_mean CSI 0.3339] [one_class_mean best 0.3339] \n", "0.3339\t0.3339\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# shift_tr : blur\n", "# id_class : hem\n", "# epoch : 100\n", "# res : 450px\n", "# crop : 0.08\n", "# blur_sigma : 6\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 6 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma6.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 145, "id": "5a20ddb8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0029\t0.0062\t0.0034\t0.0030\n", "weight_shi:\t0.2169\t2.1291\t-0.6997\t-0.6317\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5895074388033098\n", "CNMC 2.0596 +- 0.2877 q0: 1.0222 q10: 1.6929 q20: 1.8375 q30: 1.9167 q40: 2.0096 q50: 2.0851 q60: 2.1435 q70: 2.2065 q80: 2.2951 q90: 2.4044 q100: 3.0604\n", "one_class_0 1.9839 +- 0.2326 q0: 1.1067 q10: 1.6760 q20: 1.7908 q30: 1.8756 q40: 1.9429 q50: 2.0082 q60: 2.0584 q70: 2.1101 q80: 2.1732 q90: 2.2584 q100: 3.0116\n", "[one_class_0 CSI 0.5895] [one_class_0 best 0.5895] \n", "[one_class_mean CSI 0.5895] [one_class_mean best 0.5895] \n", "0.5895\t0.5895\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 4\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 4 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma4.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 146, "id": "f014e06d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0047\t0.0065\t0.0046\t0.0045\n", "weight_shi:\t0.2645\t-12.1918\t-1.1354\t-0.9111\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.43248488439218546\n", "CNMC 1.5307 +- 2.2981 q0: -6.2860 q10: -1.3964 q20: -0.1077 q30: 0.5774 q40: 1.2354 q50: 1.7091 q60: 2.1039 q70: 2.7068 q80: 3.3782 q90: 4.4476 q100: 6.9377\n", "one_class_0 2.0424 +- 1.5916 q0: -5.1678 q10: 0.0924 q20: 0.8505 q30: 1.3834 q40: 1.7445 q50: 2.1476 q60: 2.4484 q70: 2.8574 q80: 3.3216 q90: 3.9483 q100: 6.4052\n", "[one_class_0 CSI 0.4325] [one_class_0 best 0.4325] \n", "[one_class_mean CSI 0.4325] [one_class_mean best 0.4325] \n", "0.4325\t0.4325\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma3.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 148, "id": "469197e2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0083\t0.0100\t0.0115\t0.0075\n", "weight_shi:\t2.4798\t0.7962\t-4.3631\t-2.5771\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.37173128145920054\n", "CNMC 1.8398 +- 0.7107 q0: -1.6740 q10: 0.9741 q20: 1.3853 q30: 1.6153 q40: 1.8033 q50: 1.9486 q60: 2.1053 q70: 2.2304 q80: 2.3601 q90: 2.5741 q100: 3.5645\n", "one_class_0 2.1409 +- 0.5323 q0: -0.7020 q10: 1.4665 q20: 1.7704 q30: 1.9274 q40: 2.0616 q50: 2.1799 q60: 2.2918 q70: 2.4188 q80: 2.5430 q90: 2.7544 q100: 3.8279\n", "[one_class_0 CSI 0.3717] [one_class_0 best 0.3717] \n", "[one_class_mean CSI 0.3717] [one_class_mean best 0.3717] \n", "0.3717\t0.3717\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma2.0_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 149, "id": "b8ccee0f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0078\t0.0116\t0.0095\t0.0106\n", "weight_shi:\t0.1768\t-0.5198\t-0.4439\t-0.3696\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3392225969475081\n", "CNMC 1.9808 +- 0.1438 q0: 1.5735 q10: 1.8230 q20: 1.8637 q30: 1.8908 q40: 1.9230 q50: 1.9577 q60: 1.9928 q70: 2.0435 q80: 2.1120 q90: 2.1900 q100: 2.4139\n", "one_class_0 2.0502 +- 0.1152 q0: 1.7554 q10: 1.9134 q20: 1.9501 q30: 1.9799 q40: 2.0064 q50: 2.0376 q60: 2.0668 q70: 2.1043 q80: 2.1520 q90: 2.2170 q100: 2.4357\n", "[one_class_0 CSI 0.3392] [one_class_0 best 0.3392] \n", "[one_class_mean CSI 0.3392] [one_class_mean best 0.3392] \n", "0.3392\t0.3392\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1.5\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 1.5 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma1.5_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 150, "id": "3ba56d85", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0021\t0.0031\t0.0026\t0.0026\n", "weight_shi:\t0.3756\t9.2614\t-0.9536\t-0.8326\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6796440616169901\n", "CNMC 2.2897 +- 0.8188 q0: -0.1330 q10: 1.2176 q20: 1.6025 q30: 1.8640 q40: 2.0833 q50: 2.2961 q60: 2.5135 q70: 2.7109 q80: 2.9502 q90: 3.3024 q100: 4.9905\n", "one_class_0 1.8212 +- 0.6476 q0: -0.7580 q10: 1.0215 q20: 1.3188 q30: 1.4821 q40: 1.6494 q50: 1.7908 q60: 1.9457 q70: 2.1147 q80: 2.3124 q90: 2.6421 q100: 4.3585\n", "[one_class_0 CSI 0.6796] [one_class_0 best 0.6796] \n", "[one_class_mean CSI 0.6796] [one_class_mean best 0.6796] \n", "0.6796\t0.6796\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 1 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma1.0_one_class_1/last.model\"" ] }, { "cell_type": "markdown", "id": "9fd03e0e", "metadata": {}, "source": [ "## other transformations" ] }, { "cell_type": "code", "execution_count": 151, "id": "beda234d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0022\t0.0048\t0.0029\t0.0028\n", "weight_shi:\t-3.2909\t-2.8657\t12.5482\t8.7034\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5285322922047013\n", "CNMC 2.0914 +- 0.5227 q0: 0.3459 q10: 1.3730 q20: 1.6394 q30: 1.8216 q40: 1.9820 q50: 2.1814 q60: 2.2788 q70: 2.3999 q80: 2.5247 q90: 2.7229 q100: 3.6842\n", "one_class_0 2.0687 +- 0.3844 q0: 0.9708 q10: 1.5495 q20: 1.7411 q30: 1.8523 q40: 1.9633 q50: 2.0755 q60: 2.1823 q70: 2.2948 q80: 2.4057 q90: 2.5591 q100: 3.3615\n", "[one_class_0 CSI 0.5285] [one_class_0 best 0.5285] \n", "[one_class_mean CSI 0.5285] [one_class_mean best 0.5285] \n", "0.5285\t0.5285\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : rotation\n", "# crop : 0.08\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type rotation --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_rotation_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "code", "execution_count": 152, "id": "025aedc5", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3581 3581 3581 3581\n", "weight_sim:\t0.0030\t0.0034\t0.0036\t0.0040\n", "weight_shi:\t-0.0433\t0.5499\t-0.7289\t0.1057\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4115717953392276\n", "CNMC 2.0156 +- 0.1922 q0: 1.5401 q10: 1.7668 q20: 1.8500 q30: 1.9196 q40: 1.9652 q50: 2.0074 q60: 2.0619 q70: 2.1144 q80: 2.1791 q90: 2.2713 q100: 2.6170\n", "one_class_0 2.0726 +- 0.1608 q0: 1.6384 q10: 1.8757 q20: 1.9493 q30: 1.9876 q40: 2.0244 q50: 2.0556 q60: 2.0929 q70: 2.1446 q80: 2.2026 q90: 2.3007 q100: 2.7631\n", "[one_class_0 CSI 0.4116] [one_class_0 best 0.4116] \n", "[one_class_mean CSI 0.4116] [one_class_mean best 0.4116] \n", "0.4116\t0.4116\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : hem\n", "# epoch : 100\n", "# shift_tr : cutperm\n", "# crop : 0.08\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type cutperm --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 1 --load_path \"logs/id_hem/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_cutperm_resize_factor0.08_color_dist0.5_one_class_1/last.model\"" ] }, { "cell_type": "markdown", "id": "7def804c", "metadata": {}, "source": [ "# In-Distribution = ALL" ] }, { "cell_type": "markdown", "id": "4d826eb3", "metadata": {}, "source": [ "# Combined shiftings" ] }, { "cell_type": "code", "execution_count": 153, "id": "ed1501cd", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0099\t0.0102\t0.0065\t0.0102\n", "weight_shi:\t-0.2651\t0.3988\t-0.4352\t-0.9217\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.39018776775134445\n", "CNMC 1.9696 +- 0.3172 q0: 1.0059 q10: 1.5824 q20: 1.7007 q30: 1.7852 q40: 1.8767 q50: 1.9557 q60: 2.0335 q70: 2.1270 q80: 2.2281 q90: 2.3851 q100: 3.0697\n", "one_class_1 2.1059 +- 0.3583 q0: 1.1658 q10: 1.6595 q20: 1.8070 q30: 1.9152 q40: 2.0053 q50: 2.0849 q60: 2.1740 q70: 2.2650 q80: 2.3979 q90: 2.5818 q100: 3.4632\n", "[one_class_1 CSI 0.3902] [one_class_1 best 0.3902] \n", "[one_class_mean CSI 0.3902] [one_class_mean best 0.3902] \n", "0.3902\t0.3902\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur_randpers\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --distortion_scale 0.75 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_randpers_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 154, "id": "b471436b", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0067\t0.0129\t0.0065\t0.0086\n", "weight_shi:\t-0.0850\t0.2249\t0.1729\t0.1702\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4909736780805963\n", "CNMC 2.1838 +- 0.3670 q0: 0.9506 q10: 1.6677 q20: 1.8649 q30: 2.0015 q40: 2.1242 q50: 2.2193 q60: 2.3160 q70: 2.4125 q80: 2.5084 q90: 2.6376 q100: 3.1795\n", "one_class_1 2.1670 +- 0.4888 q0: 0.7892 q10: 1.4646 q20: 1.7498 q30: 1.9466 q40: 2.1070 q50: 2.2393 q60: 2.3641 q70: 2.4747 q80: 2.6032 q90: 2.7386 q100: 3.1321\n", "[one_class_1 CSI 0.4910] [one_class_1 best 0.4910] \n", "[one_class_mean CSI 0.4910] [one_class_mean best 0.4910] \n", "0.4910\t0.4910\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur_sharp\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --sharpness_factor 5 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_sharp_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 155, "id": "5c08667d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0058\t0.0071\t0.0060\t0.0060\n", "weight_shi:\t-0.0229\t0.0795\t0.0649\t0.0666\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.45186742320663564\n", "CNMC 2.0290 +- 0.0922 q0: 1.7841 q10: 1.9115 q20: 1.9486 q30: 1.9769 q40: 2.0011 q50: 2.0200 q60: 2.0479 q70: 2.0788 q80: 2.1081 q90: 2.1556 q100: 2.4408\n", "one_class_1 2.0462 +- 0.1034 q0: 1.7679 q10: 1.9185 q20: 1.9546 q30: 1.9876 q40: 2.0171 q50: 2.0410 q60: 2.0679 q70: 2.0985 q80: 2.1328 q90: 2.1914 q100: 2.3683\n", "[one_class_1 CSI 0.4519] [one_class_1 best 0.4519] \n", "[one_class_mean CSI 0.4519] [one_class_mean best 0.4519] \n", "0.4519\t0.4519\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers_sharp\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --sharpness_factor 5 --distortion_scale 0.75 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_sharp_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 156, "id": "e1be886d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0069\t0.0188\t0.0166\t0.0120\n", "weight_shi:\t-0.1581\t0.1971\t0.2342\t0.3190\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.32064141322071316\n", "CNMC 1.9454 +- 0.0810 q0: 1.7576 q10: 1.8630 q20: 1.8860 q30: 1.9012 q40: 1.9140 q50: 1.9316 q60: 1.9461 q70: 1.9640 q80: 1.9905 q90: 2.0476 q100: 2.4165\n", "one_class_1 2.0265 +- 0.1592 q0: 1.7834 q10: 1.8887 q20: 1.9115 q30: 1.9346 q40: 1.9614 q50: 1.9884 q60: 2.0114 q70: 2.0559 q80: 2.1059 q90: 2.2091 q100: 3.1080\n", "[one_class_1 CSI 0.3206] [one_class_1 best 0.3206] \n", "[one_class_mean CSI 0.3206] [one_class_mean best 0.3206] \n", "0.3206\t0.3206\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur_randpers_sharp\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --sharpness_factor 5 --distortion_scale 0.75 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur_randpers_sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_randpers_sharp_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "d8cd9c5a", "metadata": {}, "source": [ "# Rotation" ] }, { "cell_type": "code", "execution_count": 157, "id": "3f9748c5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0058\t0.0091\t0.0059\t0.0061\n", "weight_shi:\t-20.2520\t5.6794\t4.4756\t-13.8486\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6155293247855458\n", "CNMC 2.2941 +- 0.4851 q0: 0.6171 q10: 1.6977 q20: 1.9170 q30: 2.0537 q40: 2.1467 q50: 2.2525 q60: 2.3680 q70: 2.5004 q80: 2.6952 q90: 2.9333 q100: 4.0615\n", "one_class_1 2.0566 +- 0.6054 q0: 0.2141 q10: 1.2573 q20: 1.5313 q30: 1.7431 q40: 1.8966 q50: 2.0426 q60: 2.2221 q70: 2.3685 q80: 2.6045 q90: 2.8399 q100: 3.9073\n", "[one_class_1 CSI 0.6155] [one_class_1 best 0.6155] \n", "[one_class_mean CSI 0.6155] [one_class_mean best 0.6155] \n", "0.6155\t0.6155\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : rotation\n", "# crop : 0.08\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type rotation --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_rotation_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "ed7a3ca6", "metadata": {}, "source": [ "# Cutperm" ] }, { "cell_type": "code", "execution_count": 158, "id": "47382eef", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0033\t0.0040\t0.0048\t0.0059\n", "weight_shi:\t-0.0422\t-0.2956\t0.3071\t0.0913\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5637665967854647\n", "CNMC 2.1340 +- 0.2713 q0: 1.5092 q10: 1.8054 q20: 1.8955 q30: 1.9635 q40: 2.0281 q50: 2.0900 q60: 2.1689 q70: 2.2729 q80: 2.3753 q90: 2.5306 q100: 2.8713\n", "one_class_1 2.0681 +- 0.3216 q0: 1.3818 q10: 1.6678 q20: 1.7728 q30: 1.8582 q40: 1.9368 q50: 2.0391 q60: 2.1288 q70: 2.2616 q80: 2.3884 q90: 2.5307 q100: 2.8915\n", "[one_class_1 CSI 0.5638] [one_class_1 best 0.5638] \n", "[one_class_mean CSI 0.5638] [one_class_mean best 0.5638] \n", "0.5638\t0.5638\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : cutperm\n", "# crop : 0.08\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type cutperm --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_cutperm_resize_factor0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "e338538b", "metadata": {}, "source": [ "# Rotated Dataset 4" ] }, { "cell_type": "code", "execution_count": 69, "id": "18aa1694", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0089\t0.0071\t0.0082\t0.0060\n", "weight_shi:\t-0.0826\t0.1155\t0.1144\t0.1138\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6829627857280305\n", "CNMC 2.0823 +- 0.1590 q0: 1.4861 q10: 1.8867 q20: 1.9512 q30: 1.9962 q40: 2.0434 q50: 2.0844 q60: 2.1284 q70: 2.1653 q80: 2.2150 q90: 2.2784 q100: 2.7066\n", "one_class_1 1.9798 +- 0.1471 q0: 1.4589 q10: 1.7996 q20: 1.8601 q30: 1.9145 q40: 1.9503 q50: 1.9828 q60: 2.0164 q70: 2.0541 q80: 2.1007 q90: 2.1670 q100: 2.3931\n", "[one_class_1 CSI 0.6830] [one_class_1 best 0.6830] \n", "[one_class_mean CSI 0.6830] [one_class_mean best 0.6830] \n", "0.6830\t0.6830\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC_ROT4\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 64\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 64 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/dataset_rotated_4/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor64.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 70, "id": "95e84b59", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0076\t0.0081\t0.0080\t0.0086\n", "weight_shi:\t-0.1382\t1.2588\t2.1567\t0.5287\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3485907290938738\n", "CNMC 1.8551 +- 0.4346 q0: 0.8263 q10: 1.3471 q20: 1.5032 q30: 1.6156 q40: 1.7119 q50: 1.8134 q60: 1.9097 q70: 2.0306 q80: 2.1600 q90: 2.4047 q100: 4.4743\n", "one_class_1 2.1133 +- 0.5033 q0: 0.9826 q10: 1.5132 q20: 1.7004 q30: 1.8184 q40: 1.9124 q50: 2.0310 q60: 2.1594 q70: 2.3078 q80: 2.5394 q90: 2.7696 q100: 4.0888\n", "[one_class_1 CSI 0.3486] [one_class_1 best 0.3486] \n", "[one_class_mean CSI 0.3486] [one_class_mean best 0.3486] \n", "0.3486\t0.3486\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC_ROT4\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randpers : 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.75 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/dataset_rotated_4/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.75_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 159, "id": "982cf5a4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0137\t0.0152\t0.0140\t0.0126\n", "weight_shi:\t-0.1440\t0.3135\t0.4775\t0.4211\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3167783246741409\n", "CNMC 1.9366 +- 0.1773 q0: 1.4437 q10: 1.7285 q20: 1.7909 q30: 1.8431 q40: 1.8862 q50: 1.9192 q60: 1.9569 q70: 2.0073 q80: 2.0694 q90: 2.1765 q100: 2.5655\n", "one_class_1 2.0674 +- 0.2071 q0: 1.6099 q10: 1.8331 q20: 1.8954 q30: 1.9420 q40: 1.9859 q50: 2.0320 q60: 2.0882 q70: 2.1432 q80: 2.2308 q90: 2.3727 q100: 2.8015\n", "[one_class_1 CSI 0.3168] [one_class_1 best 0.3168] \n", "[one_class_mean CSI 0.3168] [one_class_mean best 0.3168] \n", "0.3168\t0.3168\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC_ROT4\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/dataset_rotated_4/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "c9c8f555", "metadata": {}, "source": [ "# Sharpness Factor" ] }, { "cell_type": "code", "execution_count": 72, "id": "ac35a164", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0050\t0.0011\t0.0010\t0.0009\n", "weight_shi:\t-0.0433\t0.0726\t0.2303\t0.0769\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5375965930382118\n", "CNMC 1.9981 +- 0.1008 q0: 1.5969 q10: 1.8641 q20: 1.9163 q30: 1.9503 q40: 1.9776 q50: 2.0056 q60: 2.0329 q70: 2.0563 q80: 2.0814 q90: 2.1226 q100: 2.2687\n", "one_class_1 1.9867 +- 0.1056 q0: 1.6492 q10: 1.8484 q20: 1.8943 q30: 1.9323 q40: 1.9603 q50: 1.9909 q60: 2.0131 q70: 2.0457 q80: 2.0783 q90: 2.1193 q100: 2.2764\n", "[one_class_1 CSI 0.5376] [one_class_1 best 0.5376] \n", "[one_class_mean CSI 0.5376] [one_class_mean best 0.5376] \n", "0.5376\t0.5376\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 4096\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 4096 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor4096.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 73, "id": "49250ae3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0099\t0.0038\t0.0037\t0.0035\n", "weight_shi:\t-0.0601\t0.0628\t0.0572\t0.0620\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5004063743809436\n", "CNMC 2.1367 +- 0.2510 q0: 1.4456 q10: 1.8346 q20: 1.9233 q30: 1.9922 q40: 2.0485 q50: 2.1189 q60: 2.1860 q70: 2.2597 q80: 2.3425 q90: 2.4668 q100: 3.2275\n", "one_class_1 2.1346 +- 0.3755 q0: 1.1971 q10: 1.6290 q20: 1.8287 q30: 1.9361 q40: 2.0319 q50: 2.1191 q60: 2.2264 q70: 2.3246 q80: 2.4509 q90: 2.6481 q100: 3.1412\n", "[one_class_1 CSI 0.5004] [one_class_1 best 0.5004] \n", "[one_class_mean CSI 0.5004] [one_class_mean best 0.5004] \n", "0.5004\t0.5004\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 2048\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 2048 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor2048.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 74, "id": "0bd84a7e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0242\t0.0050\t0.0046\t0.0044\n", "weight_shi:\t-0.0828\t0.0645\t0.0669\t0.0596\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.521132733772876\n", "CNMC 2.1385 +- 0.2030 q0: 1.5179 q10: 1.8773 q20: 1.9648 q30: 2.0325 q40: 2.0825 q50: 2.1336 q60: 2.1808 q70: 2.2389 q80: 2.3102 q90: 2.3997 q100: 2.7902\n", "one_class_1 2.1145 +- 0.2767 q0: 1.3283 q10: 1.7725 q20: 1.8865 q30: 1.9760 q40: 2.0428 q50: 2.1166 q60: 2.1976 q70: 2.2709 q80: 2.3529 q90: 2.4697 q100: 2.8054\n", "[one_class_1 CSI 0.5211] [one_class_1 best 0.5211] \n", "[one_class_mean CSI 0.5211] [one_class_mean best 0.5211] \n", "0.5211\t0.5211\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 1024\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 1024 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor1024.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 75, "id": "7084a03f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0059\t0.0055\t0.0051\t0.0051\n", "weight_shi:\t-0.0132\t0.0371\t0.0377\t0.0376\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5495593179999798\n", "CNMC 2.0729 +- 0.0917 q0: 1.7983 q10: 1.9554 q20: 1.9947 q30: 2.0222 q40: 2.0461 q50: 2.0659 q60: 2.0930 q70: 2.1220 q80: 2.1540 q90: 2.1973 q100: 2.3686\n", "one_class_1 2.0536 +- 0.1203 q0: 1.7288 q10: 1.9078 q20: 1.9506 q30: 1.9885 q40: 2.0186 q50: 2.0481 q60: 2.0860 q70: 2.1206 q80: 2.1548 q90: 2.2130 q100: 2.3754\n", "[one_class_1 CSI 0.5496] [one_class_1 best 0.5496] \n", "[one_class_mean CSI 0.5496] [one_class_mean best 0.5496] \n", "0.5496\t0.5496\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 512\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 512 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor512.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 76, "id": "7609406d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0033\t0.0016\t0.0015\t0.0015\n", "weight_shi:\t-0.0626\t0.0548\t0.0482\t0.0476\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5079350611207324\n", "CNMC 2.1463 +- 0.2056 q0: 1.5154 q10: 1.8902 q20: 1.9661 q30: 2.0278 q40: 2.0864 q50: 2.1497 q60: 2.1995 q70: 2.2608 q80: 2.3272 q90: 2.4144 q100: 2.8480\n", "one_class_1 2.1363 +- 0.2821 q0: 1.3866 q10: 1.7738 q20: 1.8962 q30: 1.9787 q40: 2.0632 q50: 2.1372 q60: 2.2119 q70: 2.2966 q80: 2.3999 q90: 2.5028 q100: 2.7673\n", "[one_class_1 CSI 0.5079] [one_class_1 best 0.5079] \n", "[one_class_mean CSI 0.5079] [one_class_mean best 0.5079] \n", "0.5079\t0.5079\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 256\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 256 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor256.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 77, "id": "aad2a734", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0048\t0.0080\t0.0087\t0.0057\n", "weight_shi:\t-0.0840\t0.0954\t0.0919\t0.0779\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5942041645145282\n", "CNMC 2.0494 +- 0.1428 q0: 1.7036 q10: 1.8748 q20: 1.9344 q30: 1.9773 q40: 2.0081 q50: 2.0436 q60: 2.0718 q70: 2.1122 q80: 2.1561 q90: 2.2278 q100: 2.7563\n", "one_class_1 2.0001 +- 0.1729 q0: 1.5526 q10: 1.7899 q20: 1.8590 q30: 1.9109 q40: 1.9589 q50: 1.9977 q60: 2.0327 q70: 2.0653 q80: 2.1332 q90: 2.2229 q100: 2.6275\n", "[one_class_1 CSI 0.5942] [one_class_1 best 0.5942] \n", "[one_class_mean CSI 0.5942] [one_class_mean best 0.5942] \n", "0.5942\t0.5942\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 128\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 128 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor128.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 78, "id": "eceb0082", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0055\t0.0037\t0.0058\t0.0037\n", "weight_shi:\t-0.1448\t0.1735\t0.1588\t0.1423\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7104164767720962\n", "CNMC 2.0883 +- 0.1055 q0: 1.7978 q10: 1.9497 q20: 1.9997 q30: 2.0352 q40: 2.0642 q50: 2.0925 q60: 2.1162 q70: 2.1440 q80: 2.1764 q90: 2.2198 q100: 2.4996\n", "one_class_1 1.9981 +- 0.1273 q0: 1.6099 q10: 1.8403 q20: 1.8878 q30: 1.9263 q40: 1.9618 q50: 1.9937 q60: 2.0157 q70: 2.0606 q80: 2.1110 q90: 2.1738 q100: 2.4795\n", "[one_class_1 CSI 0.7104] [one_class_1 best 0.7104] \n", "[one_class_mean CSI 0.7104] [one_class_mean best 0.7104] \n", "0.7104\t0.7104\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 64\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 64 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor64.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 79, "id": "7c881700", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0028\t0.0085\t0.0044\t0.0097\n", "weight_shi:\t-0.0235\t0.0638\t0.0549\t0.0541\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5937648750746918\n", "CNMC 2.0002 +- 0.1702 q0: 1.6494 q10: 1.8157 q20: 1.8583 q30: 1.8929 q40: 1.9291 q50: 1.9695 q60: 2.0094 q70: 2.0576 q80: 2.1345 q90: 2.2419 q100: 2.8225\n", "one_class_1 1.9446 +- 0.1597 q0: 1.5613 q10: 1.7697 q20: 1.8122 q30: 1.8531 q40: 1.8816 q50: 1.9188 q60: 1.9583 q70: 2.0091 q80: 2.0737 q90: 2.1568 q100: 2.5480\n", "[one_class_1 CSI 0.5938] [one_class_1 best 0.5938] \n", "[one_class_mean CSI 0.5938] [one_class_mean best 0.5938] \n", "0.5938\t0.5938\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 32\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 32 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor32.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 80, "id": "afaa2706", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0030\t0.0048\t0.0042\t0.0054\n", "weight_shi:\t-0.0352\t0.0883\t0.0761\t0.0693\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5747906095868907\n", "CNMC 2.0814 +- 0.1200 q0: 1.7198 q10: 1.9284 q20: 1.9790 q30: 2.0137 q40: 2.0462 q50: 2.0794 q60: 2.1084 q70: 2.1462 q80: 2.1929 q90: 2.2480 q100: 2.3614\n", "one_class_1 2.0319 +- 0.1736 q0: 1.4826 q10: 1.8007 q20: 1.8786 q30: 1.9545 q40: 1.9968 q50: 2.0343 q60: 2.0956 q70: 2.1409 q80: 2.1917 q90: 2.2512 q100: 2.3875\n", "[one_class_1 CSI 0.5748] [one_class_1 best 0.5748] \n", "[one_class_mean CSI 0.5748] [one_class_mean best 0.5748] \n", "0.5748\t0.5748\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 16\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 16 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor16.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 81, "id": "374eec9c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0040\t0.0039\t0.0044\t0.0039\n", "weight_shi:\t-0.0360\t0.1191\t0.0847\t0.0773\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.47723417292052783\n", "CNMC 2.1169 +- 0.2902 q0: 1.3060 q10: 1.7390 q20: 1.8614 q30: 1.9501 q40: 2.0312 q50: 2.1085 q60: 2.1828 q70: 2.2782 q80: 2.3917 q90: 2.5189 q100: 3.0332\n", "one_class_1 2.1411 +- 0.3676 q0: 1.2368 q10: 1.6509 q20: 1.8257 q30: 1.9349 q40: 2.0555 q50: 2.1498 q60: 2.2467 q70: 2.3477 q80: 2.4742 q90: 2.6155 q100: 3.2105\n", "[one_class_1 CSI 0.4772] [one_class_1 best 0.4772] \n", "[one_class_mean CSI 0.4772] [one_class_mean best 0.4772] \n", "0.4772\t0.4772\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 8 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor8.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 82, "id": "2b907319", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0120\t0.0137\t0.0113\t0.0151\n", "weight_shi:\t-0.0230\t0.0744\t0.0702\t0.0797\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7440512360870578\n", "CNMC 2.0897 +- 0.1280 q0: 1.6279 q10: 1.9253 q20: 1.9937 q30: 2.0344 q40: 2.0646 q50: 2.0929 q60: 2.1235 q70: 2.1514 q80: 2.1925 q90: 2.2452 q100: 2.5109\n", "one_class_1 1.9564 +- 0.1648 q0: 1.2763 q10: 1.7402 q20: 1.8197 q30: 1.8821 q40: 1.9240 q50: 1.9604 q60: 2.0013 q70: 2.0434 q80: 2.0908 q90: 2.1604 q100: 2.4535\n", "[one_class_1 CSI 0.7441] [one_class_1 best 0.7441] \n", "[one_class_mean CSI 0.7441] [one_class_mean best 0.7441] \n", "0.7441\t0.7441\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 5\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 5 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor5.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 83, "id": "eadc9f63", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0044\t0.0050\t0.0036\t0.0045\n", "weight_shi:\t-0.0174\t0.0520\t0.0435\t0.0457\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6856960015799229\n", "CNMC 2.0337 +- 0.0637 q0: 1.7790 q10: 1.9526 q20: 1.9802 q30: 2.0010 q40: 2.0182 q50: 2.0348 q60: 2.0490 q70: 2.0674 q80: 2.0882 q90: 2.1155 q100: 2.2475\n", "one_class_1 1.9842 +- 0.0803 q0: 1.6728 q10: 1.8819 q20: 1.9195 q30: 1.9483 q40: 1.9679 q50: 1.9875 q60: 2.0072 q70: 2.0236 q80: 2.0479 q90: 2.0840 q100: 2.2335\n", "[one_class_1 CSI 0.6857] [one_class_1 best 0.6857] \n", "[one_class_mean CSI 0.6857] [one_class_mean best 0.6857] \n", "0.6857\t0.6857\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 4\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 4 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor4.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 84, "id": "66a30bac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0096\t0.0088\t0.0090\t0.0096\n", "weight_shi:\t-0.0320\t0.1007\t0.1076\t0.0998\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.49014067389785193\n", "CNMC 2.0877 +- 0.2810 q0: 1.3173 q10: 1.7265 q20: 1.8460 q30: 1.9306 q40: 2.0048 q50: 2.0768 q60: 2.1398 q70: 2.2252 q80: 2.3252 q90: 2.4627 q100: 3.0835\n", "one_class_1 2.0957 +- 0.3295 q0: 1.1248 q10: 1.6700 q20: 1.8185 q30: 1.9197 q40: 2.0144 q50: 2.0849 q60: 2.1813 q70: 2.2611 q80: 2.3718 q90: 2.5219 q100: 3.0920\n", "[one_class_1 CSI 0.4901] [one_class_1 best 0.4901] \n", "[one_class_mean CSI 0.4901] [one_class_mean best 0.4901] \n", "0.4901\t0.4901\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 3 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor3.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 85, "id": "e8fde266", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0051\t0.0046\t0.0048\t0.0045\n", "weight_shi:\t-0.0137\t0.0407\t0.0450\t0.0411\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4467181154356435\n", "CNMC 2.0176 +- 0.0689 q0: 1.7903 q10: 1.9308 q20: 1.9620 q30: 1.9833 q40: 1.9998 q50: 2.0144 q60: 2.0329 q70: 2.0534 q80: 2.0752 q90: 2.1054 q100: 2.2461\n", "one_class_1 2.0300 +- 0.0917 q0: 1.7417 q10: 1.9114 q20: 1.9580 q30: 1.9866 q40: 2.0089 q50: 2.0337 q60: 2.0591 q70: 2.0798 q80: 2.1052 q90: 2.1409 q100: 2.2672\n", "[one_class_1 CSI 0.4467] [one_class_1 best 0.4467] \n", "[one_class_mean CSI 0.4467] [one_class_mean best 0.4467] \n", "0.4467\t0.4467\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : sharp\n", "# crop : 0.08\n", "# sharp : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --sharpness_factor 2 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type sharp --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/sharp/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_sharp_resize_factor0.08_color_dist0.5_sharpness_factor2.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "bac55a6b", "metadata": {}, "source": [ "# Random Perspective" ] }, { "cell_type": "code", "execution_count": 86, "id": "acb8e0cf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0046\t0.0037\t0.0045\t0.0046\n", "weight_shi:\t0.1028\t-0.1896\t-0.2910\t-0.3483\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6587695844600411\n", "CNMC 2.0386 +- 0.2243 q0: 1.1465 q10: 1.7463 q20: 1.8820 q30: 1.9641 q40: 2.0161 q50: 2.0690 q60: 2.1137 q70: 2.1678 q80: 2.2188 q90: 2.2888 q100: 2.5369\n", "one_class_1 1.8805 +- 0.3066 q0: 0.7440 q10: 1.4384 q20: 1.6744 q30: 1.7753 q40: 1.8640 q50: 1.9389 q60: 1.9992 q70: 2.0643 q80: 2.1327 q90: 2.2159 q100: 2.4966\n", "[one_class_1 CSI 0.6588] [one_class_1 best 0.6588] \n", "[one_class_mean CSI 0.6588] [one_class_mean best 0.6588] \n", "0.6588\t0.6588\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.95\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.95 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.95_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 87, "id": "38406c45", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0036\t0.0043\t0.0044\t0.0045\n", "weight_shi:\t0.0940\t-0.3354\t-0.3010\t-0.4613\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6866549691611218\n", "CNMC 2.0701 +- 0.1458 q0: 1.3353 q10: 1.9029 q20: 1.9897 q30: 2.0319 q40: 2.0558 q50: 2.0795 q60: 2.1028 q70: 2.1319 q80: 2.1715 q90: 2.2439 q100: 2.4895\n", "one_class_1 1.9579 +- 0.2070 q0: 0.9880 q10: 1.6843 q20: 1.8208 q30: 1.8972 q40: 1.9508 q50: 1.9923 q60: 2.0252 q70: 2.0622 q80: 2.0986 q90: 2.1886 q100: 2.4493\n", "[one_class_1 CSI 0.6867] [one_class_1 best 0.6867] \n", "[one_class_mean CSI 0.6867] [one_class_mean best 0.6867] \n", "0.6867\t0.6867\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.9\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.9 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.9_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 88, "id": "79e43776", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0058\t0.0098\t0.0051\t0.0075\n", "weight_shi:\t0.7573\t0.7158\t-0.4403\t3.1769\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6343618023273478\n", "CNMC 2.2964 +- 0.4564 q0: 0.6867 q10: 1.7046 q20: 1.9085 q30: 2.0619 q40: 2.1922 q50: 2.3256 q60: 2.4368 q70: 2.5468 q80: 2.6813 q90: 2.8610 q100: 3.7183\n", "one_class_1 1.9670 +- 0.7117 q0: -1.6022 q10: 1.0639 q20: 1.4591 q30: 1.7160 q40: 1.8807 q50: 2.0547 q60: 2.2023 q70: 2.3776 q80: 2.5617 q90: 2.7902 q100: 3.2754\n", "[one_class_1 CSI 0.6344] [one_class_1 best 0.6344] \n", "[one_class_mean CSI 0.6344] [one_class_mean best 0.6344] \n", "0.6344\t0.6344\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.85\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.85 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.85_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 89, "id": "b5045a90", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0044\t0.0059\t0.0035\t0.0046\n", "weight_shi:\t0.1149\t-0.5921\t-0.2913\t-0.4212\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6980790265244736\n", "CNMC 2.0586 +- 0.0926 q0: 1.6907 q10: 1.9416 q20: 1.9891 q30: 2.0146 q40: 2.0367 q50: 2.0567 q60: 2.0821 q70: 2.1041 q80: 2.1311 q90: 2.1727 q100: 2.4236\n", "one_class_1 1.9890 +- 0.1129 q0: 1.6747 q10: 1.8586 q20: 1.8947 q30: 1.9326 q40: 1.9579 q50: 1.9848 q60: 2.0103 q70: 2.0342 q80: 2.0767 q90: 2.1413 q100: 2.4328\n", "[one_class_1 CSI 0.6981] [one_class_1 best 0.6981] \n", "[one_class_mean CSI 0.6981] [one_class_mean best 0.6981] \n", "0.6981\t0.6981\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.8\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.8 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.8_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 90, "id": "5d4659ac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0020\t0.0024\t0.0019\t0.0028\n", "weight_shi:\t0.0839\t-0.1992\t-0.1714\t-0.2720\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7161709152411915\n", "CNMC 2.0766 +- 0.1562 q0: 1.4380 q10: 1.8760 q20: 1.9670 q30: 2.0275 q40: 2.0724 q50: 2.1054 q60: 2.1342 q70: 2.1645 q80: 2.2012 q90: 2.2452 q100: 2.4108\n", "one_class_1 1.9367 +- 0.2053 q0: 1.1357 q10: 1.6437 q20: 1.7718 q30: 1.8741 q40: 1.9299 q50: 1.9756 q60: 2.0202 q70: 2.0576 q80: 2.1027 q90: 2.1710 q100: 2.3247\n", "[one_class_1 CSI 0.7162] [one_class_1 best 0.7162] \n", "[one_class_mean CSI 0.7162] [one_class_mean best 0.7162] \n", "0.7162\t0.7162\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.75\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.75 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.75_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 91, "id": "43c01d76", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0049\t0.0060\t0.0045\t0.0072\n", "weight_shi:\t-1.4937\t0.4193\t-0.5923\t0.9519\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.272612645459241\n", "CNMC 1.3428 +- 1.3765 q0: -2.6822 q10: -0.1317 q20: 0.2430 q30: 0.5766 q40: 0.8777 q50: 1.1651 q60: 1.4791 q70: 1.7858 q80: 2.3163 q90: 3.1566 q100: 7.5281\n", "one_class_1 2.6219 +- 1.7311 q0: -1.5026 q10: 0.6189 q20: 1.1608 q30: 1.6420 q40: 2.0065 q50: 2.4546 q60: 2.8590 q70: 3.3026 q80: 3.9411 q90: 5.0125 q100: 8.8420\n", "[one_class_1 CSI 0.2726] [one_class_1 best 0.2726] \n", "[one_class_mean CSI 0.2726] [one_class_mean best 0.2726] \n", "0.2726\t0.2726\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.6\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.6 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.6_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 92, "id": "b3c2bb68", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0040\t0.0080\t0.0069\t0.0094\n", "weight_shi:\t0.2243\t2.4831\t-1.1810\t8.3228\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.28934109115952156\n", "CNMC 1.5171 +- 0.6417 q0: -1.0892 q10: 0.6963 q20: 1.0163 q30: 1.2147 q40: 1.3800 q50: 1.5239 q60: 1.6610 q70: 1.8232 q80: 2.0413 q90: 2.3147 q100: 3.5528\n", "one_class_1 2.0698 +- 0.8043 q0: -0.3686 q10: 0.9775 q20: 1.4094 q30: 1.6626 q40: 1.9406 q50: 2.1430 q60: 2.3291 q70: 2.4725 q80: 2.7776 q90: 3.0563 q100: 4.2509\n", "[one_class_1 CSI 0.2893] [one_class_1 best 0.2893] \n", "[one_class_mean CSI 0.2893] [one_class_mean best 0.2893] \n", "0.2893\t0.2893\n" ] } ], "source": [ "###### EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : randpers\n", "# crop : 0.08\n", "# randper_dist: 0.3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --distortion_scale 0.3 --color_distort 0.5 --resize_factor 0.08 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type randpers --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/randpers/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_randpers_resize_factor0.08_color_dist0.5_distortion_scale0.3_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "5cfed222", "metadata": {}, "source": [ "# Color Distortion = 0.8" ] }, { "cell_type": "markdown", "id": "009f41d0", "metadata": {}, "source": [ "## Examine crop" ] }, { "cell_type": "code", "execution_count": 196, "id": "0c216c1d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0109\t0.0127\t0.0131\t0.0112\n", "weight_shi:\t-0.3601\t0.8696\t0.8266\t1.2633\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3773116499053059\n", "CNMC 1.9315 +- 0.0895 q0: 1.6857 q10: 1.8069 q20: 1.8435 q30: 1.8794 q40: 1.9068 q50: 1.9359 q60: 1.9582 q70: 1.9849 q80: 2.0138 q90: 2.0465 q100: 2.2963\n", "one_class_1 1.9880 +- 0.1336 q0: 1.7198 q10: 1.8075 q20: 1.8598 q30: 1.9006 q40: 1.9419 q50: 1.9827 q60: 2.0260 q70: 2.0729 q80: 2.1099 q90: 2.1645 q100: 2.4634\n", "[one_class_1 CSI 0.3773] [one_class_1 best 0.3773] \n", "[one_class_mean CSI 0.3773] [one_class_mean best 0.3773] \n", "0.3773\t0.3773\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.5\n", "# blur_sigma : 2\n", "# color_dist : 0.8\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.5 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.5_color_dist0.8_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 197, "id": "6320eef5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0076\t0.0076\t0.0074\t0.0074\n", "weight_shi:\t0.9058\t0.5362\t0.6368\t-14.1887\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5917127477491163\n", "CNMC 2.8214 +- 1.0315 q0: -1.2486 q10: 1.3987 q20: 1.9532 q30: 2.3459 q40: 2.7058 q50: 2.9513 q60: 3.1875 q70: 3.4447 q80: 3.7111 q90: 4.0288 q100: 5.9040\n", "one_class_1 2.3812 +- 1.3314 q0: -2.1268 q10: 0.5397 q20: 1.2181 q30: 1.7456 q40: 2.2246 q50: 2.5793 q60: 2.9176 q70: 3.1949 q80: 3.5267 q90: 3.9124 q100: 4.9106\n", "[one_class_1 CSI 0.5917] [one_class_1 best 0.5917] \n", "[one_class_mean CSI 0.5917] [one_class_mean best 0.5917] \n", "0.5917\t0.5917\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.3\n", "# blur_sigma : 2\n", "# color_dist : 0.8\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.3 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.3_color_dist0.8_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 198, "id": "451c90e5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0110\t0.0071\t0.0102\t0.0101\n", "weight_shi:\t-0.2335\t0.3455\t0.5920\t0.5756\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4148462107171432\n", "CNMC 1.8587 +- 0.2019 q0: 1.3001 q10: 1.5984 q20: 1.6837 q30: 1.7477 q40: 1.8032 q50: 1.8568 q60: 1.9066 q70: 1.9618 q80: 2.0281 q90: 2.1033 q100: 2.4803\n", "one_class_1 1.9549 +- 0.3011 q0: 1.3374 q10: 1.5829 q20: 1.6833 q30: 1.7648 q40: 1.8483 q50: 1.9432 q60: 2.0105 q70: 2.0860 q80: 2.2017 q90: 2.3676 q100: 3.0008\n", "[one_class_1 CSI 0.4148] [one_class_1 best 0.4148] \n", "[one_class_mean CSI 0.4148] [one_class_mean best 0.4148] \n", "0.4148\t0.4148\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.02\n", "# blur_sigma : 2\n", "# color_dist : 0.8\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.02 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.02_color_dist0.8_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 199, "id": "54fef60e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0055\t0.0047\t0.0063\t0.0070\n", "weight_shi:\t-1.5156\t2.2142\t13.3925\t216.9532\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3877887663435927\n", "CNMC -9.2248 +- 14.9978 q0: -31.8010 q10: -22.8496 q20: -20.5631 q30: -18.8369 q40: -16.1600 q50: -13.7478 q60: -10.1906 q70: -5.6572 q80: 0.0581 q90: 9.1230 q100: 77.4578\n", "one_class_1 0.7817 +- 24.0001 q0: -33.6751 q10: -22.8505 q20: -20.2689 q30: -16.3248 q40: -11.6706 q50: -5.3667 q60: 0.3825 q70: 6.7728 q80: 17.5805 q90: 39.7293 q100: 83.7649\n", "[one_class_1 CSI 0.3878] [one_class_1 best 0.3878] \n", "[one_class_mean CSI 0.3878] [one_class_mean best 0.3878] \n", "0.3878\t0.3878\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.008\n", "# blur_sigma : 2\n", "# color_dist : 0.8\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.008 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.008_color_dist0.8_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "2dccb685", "metadata": {}, "source": [ "## Examine blur_sigma" ] }, { "cell_type": "code", "execution_count": 200, "id": "0c13892c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0059\t0.0053\t0.0052\t0.0054\n", "weight_shi:\t-0.0908\t0.2339\t0.2553\t0.2459\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.46215401209248624\n", "CNMC 1.9646 +- 0.0814 q0: 1.7239 q10: 1.8537 q20: 1.8937 q30: 1.9247 q40: 1.9510 q50: 1.9695 q60: 1.9918 q70: 2.0122 q80: 2.0334 q90: 2.0642 q100: 2.1895\n", "one_class_1 1.9790 +- 0.1048 q0: 1.6906 q10: 1.8438 q20: 1.8841 q30: 1.9178 q40: 1.9505 q50: 1.9783 q60: 2.0103 q70: 2.0393 q80: 2.0700 q90: 2.1155 q100: 2.2617\n", "[one_class_1 CSI 0.4622] [one_class_1 best 0.4622] \n", "[one_class_mean CSI 0.4622] [one_class_mean best 0.4622] \n", "0.4622\t0.4622\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma40.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 201, "id": "7b24db11", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0172\t0.0135\t0.0226\t0.0192\n", "weight_shi:\t-0.0741\t0.1495\t0.1978\t0.1718\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4793875773503884\n", "CNMC 1.9531 +- 0.1138 q0: 1.6474 q10: 1.8092 q20: 1.8542 q30: 1.8878 q40: 1.9235 q50: 1.9532 q60: 1.9802 q70: 2.0102 q80: 2.0447 q90: 2.0976 q100: 2.3859\n", "one_class_1 1.9692 +- 0.1523 q0: 1.6030 q10: 1.7796 q20: 1.8318 q30: 1.8785 q40: 1.9130 q50: 1.9548 q60: 1.9983 q70: 2.0455 q80: 2.0996 q90: 2.1848 q100: 2.3561\n", "[one_class_1 CSI 0.4794] [one_class_1 best 0.4794] \n", "[one_class_mean CSI 0.4794] [one_class_mean best 0.4794] \n", "0.4794\t0.4794\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 20\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 20 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma20.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 202, "id": "352c0a41", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0025\t0.0040\t0.0022\t0.0025\n", "weight_shi:\t1.2410\t0.6755\t-1.1582\t-3.5877\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6594658645520007\n", "CNMC 2.1628 +- 0.3004 q0: 0.7838 q10: 1.7714 q20: 1.9641 q30: 2.0468 q40: 2.1213 q50: 2.1830 q60: 2.2509 q70: 2.3213 q80: 2.4001 q90: 2.5014 q100: 3.3713\n", "one_class_1 1.9514 +- 0.4284 q0: -0.1104 q10: 1.4546 q20: 1.6765 q30: 1.7941 q40: 1.8892 q50: 2.0071 q60: 2.0917 q70: 2.1785 q80: 2.2711 q90: 2.4356 q100: 2.9090\n", "[one_class_1 CSI 0.6595] [one_class_1 best 0.6595] \n", "[one_class_mean CSI 0.6595] [one_class_mean best 0.6595] \n", "0.6595\t0.6595\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 6\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 6 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma6.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 203, "id": "d22c485a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0050\t0.0078\t0.0052\t0.0062\n", "weight_shi:\t0.4106\t0.4163\t-2.7425\t-3.5688\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6272255643666637\n", "CNMC 2.1200 +- 0.6206 q0: -0.0284 q10: 1.2949 q20: 1.5957 q30: 1.8155 q40: 2.0312 q50: 2.1755 q60: 2.3270 q70: 2.4960 q80: 2.6611 q90: 2.8534 q100: 4.1276\n", "one_class_1 1.8269 +- 0.6667 q0: -0.9521 q10: 0.9740 q20: 1.3397 q30: 1.5917 q40: 1.7532 q50: 1.8870 q60: 2.0460 q70: 2.2002 q80: 2.3477 q90: 2.5711 q100: 3.5803\n", "[one_class_1 CSI 0.6272] [one_class_1 best 0.6272] \n", "[one_class_mean CSI 0.6272] [one_class_mean best 0.6272] \n", "0.6272\t0.6272\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 4\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 4 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma4.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 204, "id": "00a8d2ac", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0047\t0.0072\t0.0056\t0.0047\n", "weight_shi:\t0.3757\t1.6655\t5.1831\t-1.0361\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.49718323053707253\n", "CNMC 1.9914 +- 0.1852 q0: 1.3248 q10: 1.7612 q20: 1.8463 q30: 1.9021 q40: 1.9490 q50: 1.9936 q60: 2.0285 q70: 2.0851 q80: 2.1355 q90: 2.2233 q100: 2.6945\n", "one_class_1 1.9965 +- 0.2132 q0: 1.1855 q10: 1.7487 q20: 1.8267 q30: 1.8843 q40: 1.9394 q50: 1.9881 q60: 2.0429 q70: 2.1000 q80: 2.1632 q90: 2.2481 q100: 2.8524\n", "[one_class_1 CSI 0.4972] [one_class_1 best 0.4972] \n", "[one_class_mean CSI 0.4972] [one_class_mean best 0.4972] \n", "0.4972\t0.4972\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 3\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma3.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 205, "id": "cdab5a91", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0019\t0.0026\t0.0019\t0.0022\n", "weight_shi:\t0.2520\t-1.0379\t-0.8245\t-0.8299\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7393317230273752\n", "CNMC 2.1093 +- 0.1696 q0: 1.2392 q10: 1.9016 q20: 2.0068 q30: 2.0585 q40: 2.1066 q50: 2.1333 q60: 2.1667 q70: 2.1958 q80: 2.2352 q90: 2.2885 q100: 2.5315\n", "one_class_1 1.9282 +- 0.2660 q0: 0.4865 q10: 1.6153 q20: 1.7843 q30: 1.8731 q40: 1.9295 q50: 1.9714 q60: 2.0108 q70: 2.0668 q80: 2.1224 q90: 2.2106 q100: 2.5011\n", "[one_class_1 CSI 0.7393] [one_class_1 best 0.7393] \n", "[one_class_mean CSI 0.7393] [one_class_mean best 0.7393] \n", "0.7393\t0.7393\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma2.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 206, "id": "76bdab2e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0044\t0.0059\t0.0046\t0.0046\n", "weight_shi:\t0.2676\t-0.5492\t-0.7697\t-0.6319\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6709070124267007\n", "CNMC 2.0490 +- 0.0659 q0: 1.6783 q10: 1.9728 q20: 1.9995 q30: 2.0151 q40: 2.0347 q50: 2.0501 q60: 2.0654 q70: 2.0818 q80: 2.1012 q90: 2.1296 q100: 2.2543\n", "one_class_1 1.9948 +- 0.1054 q0: 1.5066 q10: 1.8893 q20: 1.9323 q30: 1.9563 q40: 1.9732 q50: 1.9993 q60: 2.0219 q70: 2.0484 q80: 2.0819 q90: 2.1226 q100: 2.2211\n", "[one_class_1 CSI 0.6709] [one_class_1 best 0.6709] \n", "[one_class_mean CSI 0.6709] [one_class_mean best 0.6709] \n", "0.6709\t0.6709\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1.5\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 1.5 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma1.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 207, "id": "0c1efb9f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0058\t0.0159\t0.0080\t0.0086\n", "weight_shi:\t0.5438\t-2.8363\t-21.1928\t-1.9421\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6621902186572681\n", "CNMC 2.2408 +- 0.8449 q0: -0.8843 q10: 1.1519 q20: 1.6038 q30: 1.9076 q40: 2.1231 q50: 2.3416 q60: 2.5656 q70: 2.7323 q80: 2.9607 q90: 3.2092 q100: 3.9264\n", "one_class_1 1.6402 +- 1.1251 q0: -2.9414 q10: 0.0207 q20: 0.8939 q30: 1.3058 q40: 1.6627 q50: 1.9102 q60: 2.1044 q70: 2.2975 q80: 2.5539 q90: 2.8038 q100: 3.7386\n", "[one_class_1 CSI 0.6622] [one_class_1 best 0.6622] \n", "[one_class_mean CSI 0.6622] [one_class_mean best 0.6622] \n", "0.6622\t0.6622\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1\n", "# color_dist : 0.8 \n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.8 --resize_factor 0.08 --blur_sigma 1 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.8/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.8_blur_sigma1.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "f676267b", "metadata": {}, "source": [ "# Color Distortion = 1" ] }, { "cell_type": "markdown", "id": "744297b9", "metadata": {}, "source": [ "## Examine crop" ] }, { "cell_type": "code", "execution_count": 208, "id": "21a87be2", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0061\t0.0065\t0.0065\t0.0056\n", "weight_shi:\t1.6932\t-31.1268\t15.0080\t-10.2414\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7102132895816242\n", "CNMC 2.2522 +- 0.5226 q0: -0.3755 q10: 1.6169 q20: 1.9232 q30: 2.1160 q40: 2.2220 q50: 2.3245 q60: 2.4225 q70: 2.5144 q80: 2.6312 q90: 2.8060 q100: 3.9139\n", "one_class_1 1.8127 +- 0.7110 q0: -1.7832 q10: 0.9329 q20: 1.3309 q30: 1.6150 q40: 1.7793 q50: 1.9225 q60: 2.0429 q70: 2.1887 q80: 2.3378 q90: 2.5668 q100: 3.4155\n", "[one_class_1 CSI 0.7102] [one_class_1 best 0.7102] \n", "[one_class_mean CSI 0.7102] [one_class_mean best 0.7102] \n", "0.7102\t0.7102\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.5\n", "# blur_sigma : 2\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.5 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.5_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 209, "id": "8dd1d6d5", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0092\t0.0099\t0.0099\t0.0096\n", "weight_shi:\t0.5734\t-1.4904\t-1.4266\t-2.6760\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5938636202513699\n", "CNMC 2.0102 +- 0.1072 q0: 1.4470 q10: 1.8844 q20: 1.9436 q30: 1.9761 q40: 2.0084 q50: 2.0343 q60: 2.0578 q70: 2.0757 q80: 2.0944 q90: 2.1139 q100: 2.2014\n", "one_class_1 1.9687 +- 0.1365 q0: 1.2909 q10: 1.8035 q20: 1.8848 q30: 1.9370 q40: 1.9730 q50: 2.0035 q60: 2.0287 q70: 2.0532 q80: 2.0725 q90: 2.0980 q100: 2.1942\n", "[one_class_1 CSI 0.5939] [one_class_1 best 0.5939] \n", "[one_class_mean CSI 0.5939] [one_class_mean best 0.5939] \n", "0.5939\t0.5939\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.3\n", "# blur_sigma : 2\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.3 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.3_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 210, "id": "80437a6c", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0086\t0.0090\t0.0096\t0.0084\n", "weight_shi:\t-0.6178\t0.6564\t1.4537\t1.9758\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.40624398667193307\n", "CNMC 1.9234 +- 0.1679 q0: 1.2990 q10: 1.6940 q20: 1.7902 q30: 1.8538 q40: 1.9027 q50: 1.9438 q60: 1.9742 q70: 2.0088 q80: 2.0543 q90: 2.1136 q100: 2.6046\n", "one_class_1 1.9913 +- 0.2119 q0: 1.3411 q10: 1.7247 q20: 1.8161 q30: 1.8739 q40: 1.9369 q50: 1.9987 q60: 2.0415 q70: 2.0979 q80: 2.1553 q90: 2.2420 q100: 2.6629\n", "[one_class_1 CSI 0.4062] [one_class_1 best 0.4062] \n", "[one_class_mean CSI 0.4062] [one_class_mean best 0.4062] \n", "0.4062\t0.4062\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.02\n", "# blur_sigma : 2\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.02 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.02_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 211, "id": "5ee4b03d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0077\t0.0063\t0.0079\t0.0085\n", "weight_shi:\t-0.5622\t1.4395\t2.1736\t5.1802\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.40242330791278014\n", "CNMC 1.7715 +- 0.3123 q0: 1.0132 q10: 1.4352 q20: 1.5132 q30: 1.5847 q40: 1.6416 q50: 1.7219 q60: 1.7995 q70: 1.8923 q80: 2.0104 q90: 2.1944 q100: 3.1272\n", "one_class_1 1.9377 +- 0.4535 q0: 1.0669 q10: 1.4215 q20: 1.5153 q30: 1.6260 q40: 1.7391 q50: 1.8745 q60: 1.9976 q70: 2.1337 q80: 2.2999 q90: 2.5968 q100: 3.2364\n", "[one_class_1 CSI 0.4024] [one_class_1 best 0.4024] \n", "[one_class_mean CSI 0.4024] [one_class_mean best 0.4024] \n", "0.4024\t0.4024\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.008\n", "# blur_sigma : 2\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.008 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.008_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "3993fc92", "metadata": {}, "source": [ "## Examine blur_sigma" ] }, { "cell_type": "code", "execution_count": 212, "id": "d11c9dcd", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0118\t0.0082\t0.0118\t0.0109\n", "weight_shi:\t-0.5332\t0.3382\t1.2635\t1.1178\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.513900282563121\n", "CNMC 1.8224 +- 0.5573 q0: 0.4695 q10: 1.0940 q20: 1.3195 q30: 1.5008 q40: 1.6572 q50: 1.8032 q60: 1.9693 q70: 2.1209 q80: 2.3099 q90: 2.5687 q100: 3.4860\n", "one_class_1 1.8135 +- 0.7140 q0: 0.2666 q10: 0.8849 q20: 1.1651 q30: 1.3949 q40: 1.5485 q50: 1.7703 q60: 1.9382 q70: 2.1803 q80: 2.4559 q90: 2.7728 q100: 4.0059\n", "[one_class_1 CSI 0.5139] [one_class_1 best 0.5139] \n", "[one_class_mean CSI 0.5139] [one_class_mean best 0.5139] \n", "0.5139\t0.5139\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_40.0_resize_factor_0.08_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 213, "id": "b5ffde5e", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0083\t0.0108\t0.0081\t0.0091\n", "weight_shi:\t-0.0827\t0.1462\t0.2242\t0.2133\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5305926482950001\n", "CNMC 1.9788 +- 0.0509 q0: 1.8514 q10: 1.9121 q20: 1.9387 q30: 1.9537 q40: 1.9657 q50: 1.9801 q60: 1.9904 q70: 2.0027 q80: 2.0193 q90: 2.0412 q100: 2.1780\n", "one_class_1 1.9783 +- 0.0729 q0: 1.8180 q10: 1.8943 q20: 1.9205 q30: 1.9377 q40: 1.9541 q50: 1.9673 q60: 1.9856 q70: 2.0070 q80: 2.0322 q90: 2.0712 q100: 2.2575\n", "[one_class_1 CSI 0.5306] [one_class_1 best 0.5306] \n", "[one_class_mean CSI 0.5306] [one_class_mean best 0.5306] \n", "0.5306\t0.5306\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 20\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 20 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_20.0_resize_factor_0.08_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 214, "id": "46c0a5be", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0121\t0.0090\t0.0108\t0.0115\n", "weight_shi:\t-0.1191\t0.1866\t0.3505\t0.3025\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5126887552031113\n", "CNMC 1.9350 +- 0.1456 q0: 1.5801 q10: 1.7447 q20: 1.8072 q30: 1.8557 q40: 1.8955 q50: 1.9330 q60: 1.9678 q70: 2.0099 q80: 2.0570 q90: 2.1285 q100: 2.4351\n", "one_class_1 1.9410 +- 0.1925 q0: 1.5534 q10: 1.7034 q20: 1.7718 q30: 1.8241 q40: 1.8672 q50: 1.9158 q60: 1.9602 q70: 2.0200 q80: 2.1069 q90: 2.2114 q100: 2.5473\n", "[one_class_1 CSI 0.5127] [one_class_1 best 0.5127] \n", "[one_class_mean CSI 0.5127] [one_class_mean best 0.5127] \n", "0.5127\t0.5127\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 6\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 6 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_6.0_resize_factor_0.08_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 215, "id": "9c074889", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0091\t0.0056\t0.0092\t0.0077\n", "weight_shi:\t1.7473\t1.4099\t-3.2623\t7.2654\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3547040683012791\n", "CNMC 1.6471 +- 0.5245 q0: 0.2048 q10: 0.9772 q20: 1.1761 q30: 1.3840 q40: 1.5410 q50: 1.6358 q60: 1.7534 q70: 1.8764 q80: 2.0524 q90: 2.3159 q100: 3.4153\n", "one_class_1 2.0065 +- 0.7329 q0: 0.2362 q10: 1.0671 q20: 1.3288 q30: 1.5682 q40: 1.7685 q50: 1.9697 q60: 2.1593 q70: 2.3883 q80: 2.6860 q90: 3.0258 q100: 4.4012\n", "[one_class_1 CSI 0.3547] [one_class_1 best 0.3547] \n", "[one_class_mean CSI 0.3547] [one_class_mean best 0.3547] \n", "0.3547\t0.3547\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 4\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 4 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist1.0_blur_sigma4.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 216, "id": "99c14a28", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0033\t0.0033\t0.0025\t0.0033\n", "weight_shi:\t0.2828\t-1.2986\t-0.7648\t-1.3398\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5759223812272759\n", "CNMC 1.9848 +- 0.2270 q0: 1.1862 q10: 1.7005 q20: 1.7975 q30: 1.8756 q40: 1.9360 q50: 1.9962 q60: 2.0534 q70: 2.1141 q80: 2.1839 q90: 2.2699 q100: 2.5657\n", "one_class_1 1.9048 +- 0.2961 q0: 0.9850 q10: 1.4973 q20: 1.6832 q30: 1.7788 q40: 1.8554 q50: 1.9257 q60: 1.9946 q70: 2.0781 q80: 2.1586 q90: 2.2805 q100: 2.6712\n", "[one_class_1 CSI 0.5759] [one_class_1 best 0.5759] \n", "[one_class_mean CSI 0.5759] [one_class_mean best 0.5759] \n", "0.5759\t0.5759\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 3\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist1.0_blur_sigma3.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 221, "id": "bd3e218a", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0050\t0.0049\t0.0049\t0.0050\n", "weight_shi:\t0.3094\t-1.0241\t-0.9471\t-0.9535\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5930793556750625\n", "CNMC 2.0015 +- 0.1074 q0: 1.5164 q10: 1.8705 q20: 1.9260 q30: 1.9607 q40: 1.9870 q50: 2.0109 q60: 2.0342 q70: 2.0588 q80: 2.0868 q90: 2.1264 q100: 2.2720\n", "one_class_1 1.9465 +- 0.1678 q0: 1.2629 q10: 1.7271 q20: 1.8484 q30: 1.9020 q40: 1.9374 q50: 1.9751 q60: 2.0018 q70: 2.0397 q80: 2.0761 q90: 2.1296 q100: 2.2873\n", "[one_class_1 CSI 0.5931] [one_class_1 best 0.5931] \n", "[one_class_mean CSI 0.5931] [one_class_mean best 0.5931] \n", "0.5931\t0.5931\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.08_color_dist1.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 218, "id": "c2f0113b", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0151\t0.0114\t0.0140\t0.0143\n", "weight_shi:\t0.3904\t-1.7955\t-0.8990\t-1.3060\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.6319476093539534\n", "CNMC 2.0984 +- 0.1571 q0: 1.7583 q10: 1.9064 q20: 1.9536 q30: 2.0042 q40: 2.0398 q50: 2.0803 q60: 2.1205 q70: 2.1755 q80: 2.2444 q90: 2.3124 q100: 2.6504\n", "one_class_1 2.0194 +- 0.1919 q0: 1.5830 q10: 1.7904 q20: 1.8384 q30: 1.8841 q40: 1.9493 q50: 1.9958 q60: 2.0566 q70: 2.1204 q80: 2.1982 q90: 2.2910 q100: 2.6254\n", "[one_class_1 CSI 0.6319] [one_class_1 best 0.6319] \n", "[one_class_mean CSI 0.6319] [one_class_mean best 0.6319] \n", "0.6319\t0.6319\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1.5\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 1.5 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist1.0_blur_sigma1.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 219, "id": "1a64397f", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0835\t0.0834\t0.0843\t0.0839\n", "weight_shi:\t0.6194\t-4.8322\t-1.4623\t-2.0319\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.5156447806844306\n", "CNMC 2.0671 +- 0.1604 q0: 1.6242 q10: 1.8621 q20: 1.9293 q30: 1.9753 q40: 2.0244 q50: 2.0641 q60: 2.0983 q70: 2.1559 q80: 2.2074 q90: 2.2798 q100: 2.5007\n", "one_class_1 2.0520 +- 0.2129 q0: 1.5274 q10: 1.7652 q20: 1.8656 q30: 1.9325 q40: 1.9996 q50: 2.0618 q60: 2.1083 q70: 2.1784 q80: 2.2379 q90: 2.3346 q100: 2.6253\n", "[one_class_1 CSI 0.5156] [one_class_1 best 0.5156] \n", "[one_class_mean CSI 0.5156] [one_class_mean best 0.5156] \n", "0.5156\t0.5156\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1\n", "# color_dist : 1\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 1 --resize_factor 0.08 --blur_sigma 1 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist1.0/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist1.0_blur_sigma1.0_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "c1bce058", "metadata": {}, "source": [ "# Color Distortion = 0.5" ] }, { "cell_type": "markdown", "id": "65e662af", "metadata": {}, "source": [ "## Examine crop" ] }, { "cell_type": "code", "execution_count": 184, "id": "fdaec3de", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0077\t0.0072\t0.0077\t0.0083\n", "weight_shi:\t-0.2495\t0.5029\t0.4407\t0.6284\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4545575962892069\n", "CNMC 1.9531 +- 0.0857 q0: 1.5656 q10: 1.8568 q20: 1.8889 q30: 1.9090 q40: 1.9290 q50: 1.9470 q60: 1.9664 q70: 1.9868 q80: 2.0131 q90: 2.0534 q100: 2.4858\n", "one_class_1 1.9770 +- 0.1276 q0: 1.5910 q10: 1.8422 q20: 1.8816 q30: 1.9115 q40: 1.9369 q50: 1.9621 q60: 1.9818 q70: 2.0174 q80: 2.0584 q90: 2.1323 q100: 2.7000\n", "[one_class_1 CSI 0.4546] [one_class_1 best 0.4546] \n", "[one_class_mean CSI 0.4546] [one_class_mean best 0.4546] \n", "0.4546\t0.4546\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.5\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.5 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.5_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 185, "id": "eaa5ec79", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0069\t0.0088\t0.0090\t0.0079\n", "weight_shi:\t2.7516\t0.9415\t1.1553\t-18.6953\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.580519095798013\n", "CNMC 2.6811 +- 1.0535 q0: -1.5616 q10: 1.2724 q20: 1.7695 q30: 2.1545 q40: 2.4883 q50: 2.7551 q60: 3.0169 q70: 3.2695 q80: 3.5643 q90: 3.8850 q100: 6.2124\n", "one_class_1 2.2993 +- 1.4215 q0: -2.7435 q10: 0.4967 q20: 1.2345 q30: 1.7164 q40: 2.0762 q50: 2.3752 q60: 2.6957 q70: 3.0288 q80: 3.4597 q90: 3.9539 q100: 6.3139\n", "[one_class_1 CSI 0.5805] [one_class_1 best 0.5805] \n", "[one_class_mean CSI 0.5805] [one_class_mean best 0.5805] \n", "0.5805\t0.5805\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.3\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.3 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.3_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 220, "id": "4a75f4d4", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0074\t0.0080\t0.0073\t0.0077\n", "weight_shi:\t-0.8732\t0.8498\t2.4905\t1.5653\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.2671803947781525\n", "CNMC 1.8416 +- 0.1772 q0: 1.2265 q10: 1.6388 q20: 1.7083 q30: 1.7532 q40: 1.7915 q50: 1.8242 q60: 1.8580 q70: 1.8990 q80: 1.9656 q90: 2.0775 q100: 2.5900\n", "one_class_1 2.0431 +- 0.2719 q0: 1.2846 q10: 1.7272 q20: 1.8128 q30: 1.8857 q40: 1.9439 q50: 2.0013 q60: 2.0829 q70: 2.1644 q80: 2.2684 q90: 2.4103 q100: 2.9156\n", "[one_class_1 CSI 0.2672] [one_class_1 best 0.2672] \n", "[one_class_mean CSI 0.2672] [one_class_mean best 0.2672] \n", "0.2672\t0.2672\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.02\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.02 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.02_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 187, "id": "9d31d62a", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0046\t0.0037\t0.0035\t0.0047\n", "weight_shi:\t0.4014\t-0.7791\t-0.6536\t-1.3711\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.611233276618155\n", "CNMC 1.9991 +- 0.2593 q0: 0.9291 q10: 1.6096 q20: 1.7794 q30: 1.9130 q40: 1.9994 q50: 2.0695 q60: 2.1203 q70: 2.1657 q80: 2.2124 q90: 2.2692 q100: 2.5149\n", "one_class_1 1.8852 +- 0.3136 q0: 0.6811 q10: 1.4317 q20: 1.6563 q30: 1.7768 q40: 1.8804 q50: 1.9566 q60: 2.0179 q70: 2.0924 q80: 2.1459 q90: 2.2152 q100: 2.4864\n", "[one_class_1 CSI 0.6112] [one_class_1 best 0.6112] \n", "[one_class_mean CSI 0.6112] [one_class_mean best 0.6112] \n", "0.6112\t0.6112\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.008\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.008 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.008_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "markdown", "id": "58a14458", "metadata": {}, "source": [ "## Examine blur_sigma" ] }, { "cell_type": "code", "execution_count": 188, "id": "c7c2318d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0050\t0.0073\t0.0050\t0.0055\n", "weight_shi:\t-0.3869\t0.3100\t0.7499\t0.9321\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4740262206422994\n", "CNMC 1.9842 +- 0.2291 q0: 1.4232 q10: 1.6950 q20: 1.7851 q30: 1.8500 q40: 1.9214 q50: 1.9744 q60: 2.0301 q70: 2.0950 q80: 2.1712 q90: 2.2769 q100: 3.0240\n", "one_class_1 2.0169 +- 0.2738 q0: 1.4504 q10: 1.6924 q20: 1.7765 q30: 1.8481 q40: 1.9251 q50: 1.9917 q60: 2.0673 q70: 2.1457 q80: 2.2342 q90: 2.3550 q100: 3.2798\n", "[one_class_1 CSI 0.4740] [one_class_1 best 0.4740] \n", "[one_class_mean CSI 0.4740] [one_class_mean best 0.4740] \n", "0.4740\t0.4740\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 40\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 40 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_40.0_resize_factor_0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 189, "id": "dbd4fb10", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0041\t0.0073\t0.0038\t0.0040\n", "weight_shi:\t-0.0807\t0.1383\t0.2679\t0.2225\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.3159839323874052\n", "CNMC 1.9782 +- 0.0390 q0: 1.8641 q10: 1.9344 q20: 1.9491 q30: 1.9576 q40: 1.9654 q50: 1.9735 q60: 1.9830 q70: 1.9942 q80: 2.0052 q90: 2.0239 q100: 2.1760\n", "one_class_1 2.0111 +- 0.0558 q0: 1.8790 q10: 1.9491 q20: 1.9646 q30: 1.9780 q40: 1.9912 q50: 2.0041 q60: 2.0170 q70: 2.0318 q80: 2.0532 q90: 2.0897 q100: 2.2666\n", "[one_class_1 CSI 0.3160] [one_class_1 best 0.3160] \n", "[one_class_mean CSI 0.3160] [one_class_mean best 0.3160] \n", "0.3160\t0.3160\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 20\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 20 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_20.0_resize_factor_0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 190, "id": "c0cd8374", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0021\t0.0037\t0.0024\t0.0027\n", "weight_shi:\t0.1478\t4.1795\t-0.4613\t-0.5806\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.4508957959874011\n", "CNMC 2.0731 +- 0.5687 q0: 0.4702 q10: 1.3853 q20: 1.5945 q30: 1.7650 q40: 1.9267 q50: 2.0493 q60: 2.1848 q70: 2.3330 q80: 2.5050 q90: 2.7946 q100: 4.6939\n", "one_class_1 2.1855 +- 0.7534 q0: 0.3032 q10: 1.1734 q20: 1.4954 q30: 1.7768 q40: 1.9835 q50: 2.1717 q60: 2.4165 q70: 2.5852 q80: 2.8103 q90: 3.1495 q100: 4.4871\n", "[one_class_1 CSI 0.4509] [one_class_1 best 0.4509] \n", "[one_class_mean CSI 0.4509] [one_class_mean best 0.4509] \n", "0.4509\t0.4509\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 6\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 6 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_6.0_resize_factor_0.08_color_dist0.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 191, "id": "1a733a07", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0019\t0.0025\t0.0018\t0.0018\n", "weight_shi:\t0.1207\t-0.4216\t-0.2927\t-0.2699\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.622416167876928\n", "CNMC 2.0481 +- 0.2777 q0: 0.5649 q10: 1.7109 q20: 1.8569 q30: 1.9499 q40: 2.0216 q50: 2.0813 q60: 2.1374 q70: 2.2010 q80: 2.2718 q90: 2.3476 q100: 2.6884\n", "one_class_1 1.8936 +- 0.3857 q0: 0.4436 q10: 1.4038 q20: 1.6226 q30: 1.7768 q40: 1.8682 q50: 1.9483 q60: 2.0252 q70: 2.1209 q80: 2.2012 q90: 2.3215 q100: 2.8144\n", "[one_class_1 CSI 0.6224] [one_class_1 best 0.6224] \n", "[one_class_mean CSI 0.6224] [one_class_mean best 0.6224] \n", "0.6224\t0.6224\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 4\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 4 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma4.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 192, "id": "c59e2e1d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0024\t0.0049\t0.0029\t0.0029\n", "weight_shi:\t0.3727\t0.6016\t-2.1896\t-1.0076\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7071838381996982\n", "CNMC 2.1791 +- 0.2772 q0: 0.2329 q10: 1.8709 q20: 2.0154 q30: 2.0976 q40: 2.1641 q50: 2.2225 q60: 2.2692 q70: 2.3190 q80: 2.3739 q90: 2.4494 q100: 2.9055\n", "one_class_1 1.9359 +- 0.4103 q0: -0.1517 q10: 1.4452 q20: 1.7034 q30: 1.8312 q40: 1.9334 q50: 2.0115 q60: 2.0642 q70: 2.1519 q80: 2.2408 q90: 2.3584 q100: 2.8261\n", "[one_class_1 CSI 0.7072] [one_class_1 best 0.7072] \n", "[one_class_mean CSI 0.7072] [one_class_mean best 0.7072] \n", "0.7072\t0.7072\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 3\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 3 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma3.0_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 193, "id": "5827615d", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0019\t0.0027\t0.0022\t0.0026\n", "weight_shi:\t0.1899\t-0.4837\t-0.3535\t-0.3448\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7415028509504856\n", "CNMC 2.1337 +- 0.1823 q0: 0.9904 q10: 1.9206 q20: 2.0374 q30: 2.0868 q40: 2.1243 q50: 2.1600 q60: 2.1945 q70: 2.2226 q80: 2.2642 q90: 2.3222 q100: 2.5460\n", "one_class_1 1.9400 +- 0.2874 q0: 0.6323 q10: 1.5817 q20: 1.7870 q30: 1.8866 q40: 1.9416 q50: 1.9843 q60: 2.0207 q70: 2.0829 q80: 2.1566 q90: 2.2468 q100: 2.5500\n", "[one_class_1 CSI 0.7415] [one_class_1 best 0.7415] \n", "[one_class_mean CSI 0.7415] [one_class_mean best 0.7415] \n", "0.7415\t0.7415\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 2\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 2 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_2.0_resize_factor_0.08_color_dist0.5_one_class_0_7415/last.model\"" ] }, { "cell_type": "code", "execution_count": 194, "id": "65baeab1", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0022\t0.0033\t0.0025\t0.0029\n", "weight_shi:\t0.4059\t-6.1160\t-2.6702\t-1.5404\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.7402292913641013\n", "CNMC 2.5607 +- 0.6482 q0: -0.8214 q10: 1.7859 q20: 2.1154 q30: 2.3402 q40: 2.5031 q50: 2.6399 q60: 2.7654 q70: 2.9084 q80: 3.0413 q90: 3.2796 q100: 4.2054\n", "one_class_1 1.8328 +- 0.9715 q0: -2.1220 q10: 0.6263 q20: 1.0844 q30: 1.4277 q40: 1.6691 q50: 1.8643 q60: 2.1102 q70: 2.3723 q80: 2.6504 q90: 3.0382 q100: 4.2076\n", "[one_class_1 CSI 0.7402] [one_class_1 best 0.7402] \n", "[one_class_mean CSI 0.7402] [one_class_mean best 0.7402] \n", "0.7402\t0.7402\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1.5\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 1.5 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma1.5_one_class_0/last.model\"" ] }, { "cell_type": "code", "execution_count": 195, "id": "a9c1c45f", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pre-compute global statistics...\n", "axis size: 3527 3527 3527 3527\n", "weight_sim:\t0.0077\t0.0092\t0.0076\t0.0081\n", "weight_shi:\t-0.2259\t0.4304\t0.6270\t0.7623\n", "Pre-compute features...\n", "Compute OOD scores... (score: CSI)\n", "One_class_real_mean: 0.36727255694305183\n", "CNMC 1.9613 +- 0.2117 q0: 1.4830 q10: 1.7342 q20: 1.7989 q30: 1.8500 q40: 1.8941 q50: 1.9317 q60: 1.9759 q70: 2.0278 q80: 2.0943 q90: 2.2144 q100: 3.2689\n", "one_class_1 2.0967 +- 0.3131 q0: 1.5468 q10: 1.7976 q20: 1.8621 q30: 1.9190 q40: 1.9608 q50: 2.0266 q60: 2.0831 q70: 2.1520 q80: 2.2654 q90: 2.5291 q100: 3.5407\n", "[one_class_1 CSI 0.3673] [one_class_1 best 0.3673] \n", "[one_class_mean CSI 0.3673] [one_class_mean best 0.3673] \n", "0.3673\t0.3673\n" ] } ], "source": [ "# EVALUATION\n", "# dataset : CNMC\n", "# res : 450px\n", "# id_class : all\n", "# epoch : 100\n", "# shift_tr : blur\n", "# crop : 0.08\n", "# blur_sigma : 1.0\n", "# color_dist : 0.5\n", "!CUDA_VISIBLE_DEVICES=0 python3 \"eval.py\" --color_distort 0.5 --resize_factor 0.08 --blur_sigma 1.0 --mode ood_pre --dataset CNMC --model resnet18_imagenet --ood_score CSI --shift_trans_type blur --print_score --save_score --ood_samples 10 --resize_fix --one_class_idx 0 --load_path \"logs/id_all/color_dist0.5/blur/CNMC_resnet18_imagenet_unsup_simclr_CSI_450px_shift_blur_resize_factor0.08_color_dist0.5_blur_sigma1.0_one_class_0/last.model\"" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 5 }