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optimize.sh
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optimize.sh
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# conda activate frozenrecon
# # change GT_ROOT if you would like to use gt priors
# export GT_ROOT='PATH_TO_GT_DATA_ROOT'
# # FrozenRecon with datasets
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --scene_name classroom_0004
# # FrozenRecon with partial gt labels
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_intrinsic_flag --save_suffix gt_intrinsic --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_pose_flag --save_suffix gt_pose --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_depth_flag --save_suffix gt_depth --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_intrinsic_flag --gt_pose_flag --save_suffix gt_intrinsic_gt_pose --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_pose_flag --gt_depth_flag --save_suffix gt_depth_gt_pose --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_intrinsic_flag --gt_depth_flag --save_suffix gt_intrinsic_gt_depth --scene_name classroom_0004
# python src/optimize.py --dataset_name NYUDepthVideo --gt_root $GT_ROOT --gt_intrinsic_flag --gt_pose_flag --gt_depth_flag --save_suffix gt_intrinsic_gt_depth_gt_pose --scene_name classroom_0004
# # FrozenRecon with in-the-wild video input
# python src/optimize.py --video_path PATH_TO_VIDEO --scene_name SCENE_NAME
# FrozenRecon with in-the-wild images input
python src/optimize.py --img_root PATH_TO_IMG_FOLDER --scene_name SCENE_NAME
# # Outdoor Scenes
# python src/optimize.py --dataset_name KITTI --gt_intrinsic_flag --scene_name 2011_09_26_drive_0001_sync --outdoor_scenes