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Hyunji
/
A-Performance-Evaluation-of-CNN-for-Brain-Age-Prediction-Using-Structural-MRI-Data
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Authored by
Hyunji
2021-12-20 04:29:20 +0900
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f72cf1a8579a328b32214bb5603192c17155318d
f72cf1a8
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2DCNN/src/shell/table5.sh
2DCNN/src/shell/table5.sh
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f72cf1a
#!/usr/bin/env sh
# DEFINE
DATA_ROOT_PATH
=
""
DEVICE
=
"cuda"
################################################################################
#### Commands for training with slice along other dimensions (Table 5)
#### we show the command for 2d-slice set network with mean operation and along
#### coronal axis.
#### for other models just use the command from table 1 section and add the
#### data.frame_dim parameter,
# 1 for sagittal (default)
# 2 for coronal
# 3 for axial
################################################################################
python3 -m src.scripts.main -c config/config.py
\
--exp_name 2d_slice_mean_frame_dim_2
\
-r result/2d_slice_mean_frame_dim_2
\
--device
$DEVICE
--wandb.use 0
\
--model.arch.file src/arch/brain_age_slice_set.py
\
--model.arch.attn_dim 32 --model.arch.attn_num_heads 1
\
--model.arch.attn_drop 1 --model.arch.agg_fn
"mean"
\
--data.root_path
"
$DATA_ROOT_PATH
"
\
--data.frame_dim 2
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