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To train and test a Faster R-CNN detector using the alternating optimization algorithm from our NIPS 2015 paper, use experiments/scripts/faster_rcnn_alt_opt.sh

#!/bin/bash# Usage:# ./experiments/scripts/faster_rcnn_alt_opt.sh GPU NET DATASET [options args to {train,test}_net.py]# DATASET is only pascal_voc for now## Example:# ./experiments/scripts/faster_rcnn_alt_opt.sh 0 VGG_CNN_M_1024 pascal_voc \#   --set EXP_DIR foobar RNG_SEED 42 TRAIN.SCALES "[400, 500, 600, 700]"set -xset -eexport PYTHONUNBUFFERED="True"GPU_ID=$1NET=$2NET_lc=${NET,,}DATASET=$3array=( $@ )len=${#array[@]}EXTRA_ARGS=${array[@]:3:$len}EXTRA_ARGS_SLUG=${EXTRA_ARGS// /_}case $DATASET in  pascal_voc)    TRAIN_IMDB="voc_2007_trainval"    TEST_IMDB="voc_2007_test"    PT_DIR="pascal_voc"    ITERS=40000    ;;  coco)    echo "Not implemented: use experiments/scripts/faster_rcnn_end2end.sh for coco"    exit    ;;  *)    echo "No dataset given"    exit    ;;esacLOG="experiments/logs/faster_rcnn_alt_opt_${NET}_${EXTRA_ARGS_SLUG}.txt.`date +'%Y-%m-%d_%H-%M-%S'`"exec &> >(tee -a "$LOG")echo Logging output to "$LOG"time ./tools/train_faster_rcnn_alt_opt.py --gpu ${GPU_ID} \  --net_name ${NET} \  --weights data/imagenet_models/${NET}.v2.caffemodel \  --imdb ${TRAIN_IMDB} \  --cfg experiments/cfgs/faster_rcnn_alt_opt.yml \  ${EXTRA_ARGS}set +xNET_FINAL=`grep "Final model:" ${LOG} | awk '{print $3}'`set -xtime ./tools/test_net.py --gpu ${GPU_ID} \  --def models/${PT_DIR}/${NET}/faster_rcnn_alt_opt/faster_rcnn_test.pt \  --net ${NET_FINAL} \  --imdb ${TEST_IMDB} \  --cfg experiments/cfgs/faster_rcnn_alt_opt.yml \  ${EXTRA_ARGS}

set -x    #启动”-x”选项
要跟踪的程序段
set +x     #关闭”-x”选项

$0 是脚本本身的名字$1是传递给该shell脚本的第一个参数$2是传递给该shell脚本的第二个参数$@ 是传给脚本的所有参数的列表
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