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pose_opt_all2.sh
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pose_opt_all2.sh
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data_set_path=$1
echo "[POSE OPT] Test view pose optimizatin started."
folders=("DayaTemple" "HaiyanHall" "Library" "MemorialHall" "Museum" "PeonyGarden" "ScienceSquare" "theOldGate")
image_nums=(83 25 53 17 54 42 32 47)
int_mode=("off" "fixed" "fixed" "fixed" "fixed" "off" "fixed" "fixed")
opt_modes=("" "_colmap" "_colmap" "_colmap" "_colmap" "_colmap" "_colmap" "_colmap")
opt_ids=(4 5 6 7)
for idx in ${opt_ids[@]}; do
folder=${folders[$idx]}
opt_mode=${opt_modes[$idx]}
image_num=${image_nums[$idx]}
CUDA_VISIBLE_DEVICES=1 ns-train depth-nerfacto \
--data ${data_set_path}${folder}_opt/transforms${opt_mode}_opt.json \
--load-dir ./outputs/$folder/depth-nerfacto/${folder}${opt_mode}/nerfstudio_models/ \
--timestamp ${folder} \
--logging.local-writer.max-log-size 10 \
--pipeline.model.num-nerf-samples-per-ray 96 \
--pipeline.model.log2-hashmap-size 19 \
--pipeline.model.hidden-dim 64 \
--pipeline.model.near-plane 0.0 \
--pipeline.model.far-plane 80 \
--pipeline.model.num-levels 17 \
--pipeline.model.background-color last_sample \
--pipeline.model.original-image-num $image_num \
--pipeline.datamanager.skip-eval True \
--pipeline.datamanager.intrinsic-scale-factor 0.125 \
--viewer.quit-on-train-completion True \
--vis viewer+tensorboard \
--pipeline.model.freeze-field True \
--optimizers.fields.optimizer.lr 0 \
--optimizers.proposal-networks.optimizer.lr 0 \
--pipeline.datamanager.camera-optimizer.mode SE3 \
--pipeline.datamanager.camera-optimizer.intrinsic-opt ${int_mode[$idx]} \
--pipeline.datamanager.camera-optimizer.distortion-opt ${int_mode[$idx]} \
--pipeline.datamanager.camera-optimizer.scheduler.lr-final 5e-5 \
--pipeline.datamanager.camera-optimizer.scheduler.max-steps 9000 \
--pipeline.datamanager.transform_path ./outputs/$folder/depth-nerfacto/${folder}${opt_mode}/dataparser_transforms.json \
--max-num-iterations 12000
done
echo "[POSE OPT] Test view pose optimizatin completed."