File size: 4,212 Bytes
e4b9a7b | 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 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 | #!/bin/bash
set -e
# script for running the examples
# install necessary packages
pip install numpy
pip install torch
pip install 'monai[nibabel]'
# home directory
homedir="$( cd -P "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
TEMP_LOG="temp.txt"
cd "$homedir"
find "$homedir" -type f -name $TEMP_LOG -delete
# download data to specific directory
if [ -e "./testing_ixi_t1.tar.gz" ] && [ -d "./workspace/" ]; then
echo "1" >> $TEMP_LOG
else
wget https://www.dropbox.com/s/y890gb6axzzqff5/testing_ixi_t1.tar.gz?dl=1
mv testing_ixi_t1.tar.gz?dl=1 testing_ixi_t1.tar.gz
mkdir -p ./workspace/data/medical/ixi/IXI-T1/
tar -C ./workspace/data/medical/ixi/IXI-T1/ -xf testing_ixi_t1.tar.gz
fi
# run training files in examples/classification_3d
for file in "examples/classification_3d"/*train*
do
python "$file"
done
# check training files generated from examples/classification_3d
[ -e "./best_metric_model_classification3d_array.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples classification_3d: model file not generated" | tee $TEMP_LOG && exit 0)
[ -e "./best_metric_model_classification3d_dict.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples classification_3d: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval files in examples/classification_3d
for file in "examples/classification_3d"/*eval*
do
python "$file"
done
# run training files in examples/classification_3d_ignite
for file in "examples/classification_3d_ignite"/*train*
do
python "$file"
done
# check training files generated from examples/classification_3d_ignite
[ -e "./runs_array/net_checkpoint_20.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples classification_3d_ignite: model file not generated" | tee $TEMP_LOG && exit 0)
[ -e "./runs_dict/net_checkpoint_20.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples classification_3d_ignite: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval files in examples/classification_3d_ignite
for file in "examples/classification_3d_ignite"/*eval*
do
python "$file"
done
# run training files in examples/segmentation_3d
for file in "examples/segmentation_3d"/*train*
do
python "$file"
done
# check training files generated from examples/segmentation_3d
[ -e "./best_metric_model_segmentation3d_array.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples segmentation_3d: model file not generated" | tee $TEMP_LOG && exit 0)
[ -e "./best_metric_model_segmentation3d_dict.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples segmentation_3d: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval files in examples/segmentation_3d
for file in "examples/segmentation_3d"/*eval*
do
python "$file"
done
# run training files in examples/segmentation_3d_ignite
for file in "examples/segmentation_3d_ignite"/*train*
do
python "$file"
done
# check training files generated from examples/segmentation_3d_ignite
[ -e "./runs_array/net_checkpoint_100.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples segmentation_3d_ignite: model file not generated" | tee $TEMP_LOG && exit 0)
[ -e "./runs_dict/net_checkpoint_50.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples segmentation_3d_ignite: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval files in examples/segmentation_3d_ignite
for file in "examples/segmentation_3d_ignite"/*eval*
do
python "$file"
done
# run training file in examples/workflows
for file in "examples/workflows"/*train*
do
python "$file"
done
# check training file generated from examples/workflows
[ -e "./runs/net_key_metric*.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples workflows: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval file in examples/workflows
for file in "examples/workflows"/*eval*
do
python "$file"
done
# run training file in examples/synthesis
for file in "examples/synthesis"/*train*
do
python "$file"
done
# check training file generated from examples/synthesis
[ -e "./model_out/*.pth" ] && echo "1" >> $TEMP_LOG || (echo "examples synthesis: model file not generated" | tee $TEMP_LOG && exit 0)
# run eval file in examples/synthesis
for file in "examples/synthesis"/*eval*
do
python "$file"
done
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