-
Notifications
You must be signed in to change notification settings - Fork 5
/
Copy pathtest.sh
38 lines (35 loc) · 6.06 KB
/
test.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
gpu=$1
pkldir=$2
imagedir=$3
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 1 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 2 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 3 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 4 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 5 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 1 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 --batch-size 20
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 2 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 --batch-size 20
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 3 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 --batch-size 20
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 4 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 --batch-size 20
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 5 $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 --batch-size 20
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 1 -e --resume resnet34-5-1-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-1-compressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 2 -e --resume resnet34-5-2-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-2-compressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 3 -e --resume resnet34-5-3-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-3-compressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 4 -e --resume resnet34-5-4-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-4-compressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 5 -e --resume resnet34-5-5-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-5-compressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 1 -e --resume resnet34-5-1-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-1-uncompressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 2 -e --resume resnet34-5-2-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-2-uncompressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 3 -e --resume resnet34-5-3-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-3-uncompressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 4 -e --resume resnet34-5-4-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-4-uncompressed
python main.py -a resnet34 --gpu $gpu --fold-number 5 --current-fold-number 5 -e --resume resnet34-5-5-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > resnet34-5-5-uncompressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 1 -e --resume densenet121-5-1-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-1-compressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 2 -e --resume densenet121-5-2-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-2-compressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 3 -e --resume densenet121-5-3-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-3-compressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 4 -e --resume densenet121-5-4-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-4-compressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 5 -e --resume densenet121-5-5-model_best.pth.tar --use-compressed $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-5-compressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 1 -e --resume densenet121-5-1-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-1-uncompressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 2 -e --resume densenet121-5-2-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-2-uncompressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 3 -e --resume densenet121-5-3-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-3-uncompressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 4 -e --resume densenet121-5-4-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-4-uncompressed
python main.py -a densenet121 --gpu $gpu --fold-number 5 --current-fold-number 5 -e --resume densenet121-5-5-model_best.pth.tar $pkldir --prefix-image-dir-path $imagedir --image-size 960 640 > densenet121-5-5-uncompressed
python aggregate.py -a resnet34 --fold-number 5 # resnet34-5fold-result
python aggregate.py -a densenet121 --fold-number 5 # densenet121-5fold-result