forked from JiangWenPL/multiperson
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathset_env.sh
89 lines (69 loc) · 3.47 KB
/
set_env.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
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
#!/usr/bin/env bash
conda env create -f environment.yml
source activate multiperson
cd pyopengl
pip install .
cd neural_renderer/
python3 setup.py install
cd ../mmcv
python3 setup.py install
cd ../mmdetection
./compile.sh
python setup.py develop
cd ../sdf
python3 setup.py install
rsync -avzu --progress /home/wzeng/mycodes/Transformer_related/multiperson/mmdetection/data wzeng:/home/wzeng/mycodes/transformer/multiperson/mmdetection/
rsync -avzu --progress /home/wzeng/mydata/H36Mnew/c2f_vol/rcnn/ wzeng:/home/wzeng/mydata/H36Mnew/c2f_vol/
rsync -avzu --progress /home/wzeng/mydata/coco/annotations wzeng:/home/wzeng/mydata/coco/
rsync -avzu --progress /home/wzeng/mydata/lsp_dataset_original/train.pkl wzeng:/home/wzeng/mydata/lsp_dataset_original/
rsync -avzu --progress /home/wzeng/mydata/lspet_dataset/train.pkl wzeng:/home/wzeng/mydata/lsp_dataset/
rsync -avzu --progress /home/wzeng/mydata/lsp_dataset_original/images_pretrain wzeng:/home/wzeng/mydata/lsp_dataset_original/
rsync -avzu --progress /home/wzeng/mydata/mpii/rcnn wzeng:/home/wzeng/mydata/mpii/
rsync -avzu --progress /home/wzeng/mydata/mpi_inf_3dhp_new/rcnn wzeng:/home/wzeng/mydata/mpi_inf_3dhp_new/
rsync -avzu --progress /home/wzeng/mydata/panoptic/processed wzeng:/home/wzeng/mydata/panoptic/
python3 tools/train.py configs/smpl/my_pretrain.py --create_dummy
while true; do
python3 tools/train.py configs/smpl/my_pretrain.py --gpus=8
done
python3 tools/train.py configs/smpl/my_baseline.py --load_pretrain ./work_dirs/pretrain/latest.pth
while true;
do
python3 tools/train.py configs/smpl/my_baseline.py --gpus=8
done
python3 tools/train.py configs/smpl/my_tune.py --load_pretrain ./work_dirs/baseline/latest.pth
while true;
do
python3 tools/train.py configs/smpl/my_tune.py --gpus=8
done
# 240k // 4 = 60k iteration
# 11348 * 6
python3 tools/train.py configs/smpl/my_pretrain.py --create_dummy
while true; do
python3 tools/train.py configs/smpl/my_pretrain.py --gpus=8
done
# 180k // 4 = 45k iteration
# 15055 * 3
python3 tools/train.py configs/smpl/my_baseline.py --load_pretrain ./work_dirs/my_pretrain/latest.pth
while true;
do
python3 tools/train.py configs/smpl/my_baseline.py --gpus=8
done
# 100k // 4 = 25k iteration
# 15055 * 2
python3 tools/train.py configs/smpl/my_tune.py --load_pretrain ./work_dirs/my_baseline/latest.pth
while true;
do
python3 tools/train.py configs/smpl/my_tune.py --gpus=8
done
# 240k iteration # 45393 * 6
CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_pretrain.py --create_dummy
while true; do CUDA_VISIBLE_DEVICES=2,3 python3 tools/train.py configs/smpl/gpu2/my_pretrain.py --gpus=2; done
# 180k iteration # 60220 * 3
CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_baseline.py --load_pretrain ./work_dirs/gpu2/pretrain/latest.pth
while true; do CUDA_VISIBLE_DEVICES=6,7 python3 tools/train.py configs/smpl/gpu2/my_baseline.py --gpus=2; done
# 100k iteration # 60220 * 2
CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_tune.py --load_pretrain ./work_dirs/gpu2/baseline/latest.pth
while true; do CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_tune.py --gpus=2; done
CUDA_VISIBLE_DEVICES=0,1 python3 tools/train.py configs/smpl/my_tune.py --load_pretrain data/checkpoint.pt
CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_tune2.py --load_pretrain ./work_dirs/gpu2/baseline/latest.pth
while true; do CUDA_VISIBLE_DEVICES=4,5 python3 tools/train.py configs/smpl/gpu2/my_tune2.py --gpus=2; done