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espdnet_uest_2_1.sh
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mr=0.1
tgt_port=0.5
#for mr in 0.1 0.3 0.5; do
#for tgt_port in 0.5; do
# Uncertainty + NID
#CUDA_VISIBLE_DEVICES=0 python uest_seg.py \
# --random-mirror \
# --test-scale 1.0 \
# --rm-prob \
# --test-flipping \
# --num-classes 5 \
# --learning-rate 0.00001 \
# --save /tmp/runs/uest \
# --data-path ./vision_datasets/ \
# --data-src greenhouse \
# --data-src-list ./vision_datasets/camvid/train_camvid.txt \
# --data-tgt-train-list ./vision_datasets/greenhouse/train_greenhouse_more.txt \
# --data-tgt-test-list ./vision_datasets/greenhouse/val_greenhouse_more.txt \
# --batch-size 24 \
# --gpu 0 \
# --model espdnetue \
# --restore-from /tmp/runs/model_espdnetue_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb/20200630-111157/espdnetue_5_2.0_480_best.pth \
# --runs-root /tmp/runs/uest \
# --epr 5 \
# --num-rounds 20 \
# --use-uncertainty true \
# --use-nid true \
# --nid-bin 64 \
# --outsource camvid \
# --outsource-weights /tmp/runs/model_espdnet_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb/20200630-161402/espdnet_2.0_480_best.pth
# --use-depth true \
# --trainable-fusion true \
# Uncertainty
CUDA_VISIBLE_DEVICES=0 python uest_seg.py \
--random-mirror \
--test-scale 1.0 \
--rm-prob \
--test-flipping \
--num-classes 5 \
--learning-rate 0.00001 \
--save /tmp/runs/uest \
--data-path ./vision_datasets/ \
--data-src greenhouse \
--data-src-list ./vision_datasets/camvid/train_camvid.txt \
--data-tgt-train-list ./vision_datasets/greenhouse/train_greenhouse_more.lst \
--data-tgt-test-list ./vision_datasets/greenhouse/val_greenhouse_more.lst \
--batch-size 24 \
--gpu 0 \
--model espdnetue \
--restore-from /tmp/runs/uest/model_espdnetue_greenhouse/s_2.0_res_480_uest_rgb_os_camvid_ue/20200702-015902/espdnetue_best.pth \
--runs-root /tmp/runs/uest \
--epr 5 \
--num-rounds 20 \
--use-uncertainty true \
--outsource camvid \
--outsource-weights /tmp/runs/model_espdnet_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb/20200630-161402/espdnet_2.0_480_best.pth
# CE + NID
#CUDA_VISIBLE_DEVICES=1 python uest_seg.py \
# --random-mirror \
# --test-scale 1.0 \
# --rm-prob \
# --test-flipping \
# --num-classes 5 \
# --learning-rate 0.00001 \
# --save /tmp/runs/results_segmentation/uest \
# --data-path ./vision_datasets/ \
# --data-src greenhouse \
# --data-src-list ./vision_datasets/camvid/train_camvid.txt \
# --data-tgt-train-list ./vision_datasets/greenhouse/train_greenhouse_more.txt \
# --data-tgt-test-list ./vision_datasets/greenhouse/val_greenhouse_more.txt \
# --batch-size 32 \
# --gpu 0 \
# --model espdnetue \
# --restore-from /tmp/runs/results_segmentation/model_espdnetue_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb/20200603-141809/espdnetue_2.0_480_best.pth \
# --runs-root /tmp/runs/results_segmentation/uest \
# --epr 5 \
# --num-rounds 20 \
# --use-nid true \
# --nid-bin 64 \
# --outsource camvid \
# --outsource-weights ./results_segmentation/model_espdnet_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb_/20200420-095339/espdnet_2.0_480_best.pth
#
## CE
#CUDA_VISIBLE_DEVICES=1 python uest_seg.py \
# --random-mirror \
# --test-scale 1.0 \
# --rm-prob \
# --test-flipping \
# --num-classes 5 \
# --learning-rate 0.00001 \
# --save /tmp/runs/results_segmentation/uest \
# --data-path ./vision_datasets/ \
# --data-src greenhouse \
# --data-src-list ./vision_datasets/camvid/train_camvid.txt \
# --data-tgt-train-list ./vision_datasets/greenhouse/train_greenhouse_more.txt \
# --data-tgt-test-list ./vision_datasets/greenhouse/val_greenhouse_more.txt \
# --batch-size 32 \
# --gpu 0 \
# --model espdnetue \
# --restore-from /tmp/runs/results_segmentation/model_espdnetue_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb/20200603-141809/espdnetue_2.0_480_best.pth \
# --runs-root /tmp/runs/results_segmentation/uest \
# --epr 5 \
# --num-rounds 20 \
# --outsource camvid \
# --outsource-weights ./results_segmentation/model_espdnet_camvid/s_2.0_sch_hybrid_loss_ce_res_480_sc_0.5_2.0_rgb_/20200420-095339/espdnet_2.0_480_best.pth
#