CAT-Net / data /exps /validation.sh
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#!/bin/bash
# test a model to segment abdominal/cardiac MRI
GPUID1=0
export CUDA_VISIBLE_DEVICES=$GPUID1
###### Shared configs ######
DATASET='CHAOST2'
#DATASET='CMR'
NWORKER=0
RUNS=1
ALL_EV=(0 1 2 3 4) # 5-fold cross validation (0, 1, 2, 3, 4)
TEST_LABEL=[1,2,3,4]
###### Training configs ######
NSTEP=30000
DECAY=0.98
MAX_ITER=1000 # defines the size of an epoch
SNAPSHOT_INTERVAL=10000 # interval for saving snapshot
SEED=2021
N_PART=3 # defines the number of chunks for evaluation
ALL_SUPP=(3) # CHAOST2: 0-4, CMR: 0-7
echo ========================================================================
for EVAL_FOLD in "${ALL_EV[@]}"
do
PREFIX="test_${DATASET}_cv${EVAL_FOLD}"
echo $PREFIX
LOGDIR="./results"
if [ ! -d $LOGDIR ]
then
mkdir -p $LOGDIR
fi
for SUPP_IDX in "${ALL_SUPP[@]}"
do
# RELOAD_PATH='please feed the absolute path to the trained weights here' # path to the reloaded model
RELOAD_MODEL_PATH="./exps_on_CHAOST2/CATNet_train_CHAOST2_cv${EVAL_FOLD}/1/snapshots/100000.pth"
cd D:/CV/Q-Net-main
python test.py with \
mode="test" \
dataset=$DATASET \
num_workers=$NWORKER \
n_steps=$NSTEP \
eval_fold=$EVAL_FOLD \
max_iters_per_load=$MAX_ITER \
supp_idx=$SUPP_IDX \
test_label=$TEST_LABEL \
seed=$SEED \
n_part=$N_PART \
reload_model_path=$RELOAD_MODEL_PATH \
save_snapshot_every=$SNAPSHOT_INTERVAL \
lr_step_gamma=$DECAY \
path.log_dir=$LOGDIR
done
done