/
MICCAI2023_ProtoASNet_Deploy.sh
65 lines (49 loc) · 2.69 KB
/
MICCAI2023_ProtoASNet_Deploy.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
#!/bin/bash
# use this line to run the main.py file with a specified config file
# example: python3 run.py --config_path="path/to/file"
# selecting your GPU
# use this to enforce visibility of certain GPUs to the python code
# export CUDA_VISIBLE_DEVICES=2,3
# or
# as an argument to python run command
GPUS="0"
<< Baseline_XProtoNet_Image :
Baselines using XprotoNet base network, trained end2end, 224x224 resolution,
Baseline_XProtoNet_Image
CONFIG_YML="src/configs/Baseline_XProtoNet_Image.yml"
NAME="Baseline_XProtoNet_Image_224"
SAVE_DIR="logs/"$NAME
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name=$NAME --CUDA_VISIBLE_DEVICES=$GPUS
#### TEST ######
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name="Test/"$NAME --CUDA_VISIBLE_DEVICES=$GPUS \
--eval_only=True --eval_data_type='test' --model.checkpoint_path=$SAVE_DIR"/model_best.pth" # --wandb_mode="disabled"
<< Ours_ProtoASNet_Image :
Our network. ProtoASNet, trained end2end, 224x224 resolution,
Ours_ProtoASNet_Image
CONFIG_YML="src/configs/Ours_ProtoASNet_Image.yml"
NAME="Ours_ProtoASNet_Image"
SAVE_DIR="logs/"$NAME
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name=$NAME --CUDA_VISIBLE_DEVICES=$GPUS
##### TEST ######
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name="Test/"$NAME --CUDA_VISIBLE_DEVICES=$GPUS \
--eval_only=True --eval_data_type='test' --model.checkpoint_path=$SAVE_DIR"/model_best.pth" # --wandb_mode="disabled"
<< Baseline_XProtoNet_Video :
Baselines using XprotoNet base network, modified for Video data, trained end2end, 32x112x112 resolution,
Baseline_XProtoNet_Video
CONFIG_YML="src/configs/Baseline_XprotoNet_Video.yml"
NAME="Baseline_XprotoNet_Video"
SAVE_DIR="logs/"$NAME
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name=$NAME --CUDA_VISIBLE_DEVICES=$GPUS
##### TEST ######
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name="Test/"$NAME --CUDA_VISIBLE_DEVICES=$GPUS \
--eval_only=True --eval_data_type='test' --model.checkpoint_path=$SAVE_DIR"/model_best.pth" # --wandb_mode="disabled"
<< Ours_ProtoASNet_Video :
Our network. ProtoASNet video based, trained end2end, 32x112x112 resolution,
Ours_ProtoASNet_Video
CONFIG_YML="src/configs/Ours_ProtoASNet_Video.yml"
NAME="Ours_ProtoASNet_Video"
SAVE_DIR="logs/"$NAME
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name=$NAME --CUDA_VISIBLE_DEVICES=$GPUS
##### TEST ######
python main.py --config_path=$CONFIG_YML --save_dir=$SAVE_DIR --run_name="Test/"$NAME --CUDA_VISIBLE_DEVICES=$GPUS \
--eval_only=True --eval_data_type='test' --model.checkpoint_path=$SAVE_DIR"/model_best.pth" # --wandb_mode="disabled"