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run_hrt_base_ocr_v2_ohem.sh
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run_hrt_base_ocr_v2_ohem.sh
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#!/usr/bin/env bash
SCRIPTPATH="$( cd "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"
cd $SCRIPTPATH
cd ../../../
. config.profile
# check the enviroment info
nvidia-smi
${PYTHON} -m pip install yacs
${PYTHON} -m pip install torchcontrib
${PYTHON} -m pip install git+https://github.com/lucasb-eyer/pydensecrf.git
${PYTHON} -m pip install timm
${PYTHON} -m pip install einops
export PYTHONPATH="$PWD":$PYTHONPATH
DATA_DIR="${DATA_ROOT}/coco_stuff_10k"
SAVE_DIR="${DATA_ROOT}/seg_result/coco_stuff/"
BACKBONE="hrt_base"
CONFIGS="configs/coco_stuff/H_48_D_4.json"
CONFIGS_TEST="configs/coco_stuff/H_48_D_4_TEST_MS3x.json"
MODEL_NAME="hrt_base_ocr_v2"
LOSS_TYPE="fs_auxohemce_loss"
CHECKPOINTS_NAME="${MODEL_NAME}_${BACKBONE}_ohem_$(date +%F_%H-%M-%S)"
LOG_FILE="./log/coco_stuff/${CHECKPOINTS_NAME}.log"
echo "Logging to $LOG_FILE"
mkdir -p `dirname $LOG_FILE`
PRETRAINED_MODEL="./hrt_pretrained_models/hrt_base.pth" # Replace with the path to pre-trained backbone
MAX_ITERS=60000
BATCH_SIZE=16
OPTIM_METHOD='adamw'
BASE_LR=0.0001
LR_POLICY='warm_lambda_poly' # linear warmup
GROUP_METHOD='decay' # no weight decay on norm and pos embed
if [ "$1"x == "train"x ]; then
${PYTHON} -u main.py --configs ${CONFIGS} \
--drop_last y \
--nbb_mult 10 \
--phase train \
--gathered n \
--loss_balance y \
--log_to_file n \
--backbone ${BACKBONE} \
--model_name ${MODEL_NAME} \
--gpu 0 1 2 3 4 5 6 7 \
--data_dir ${DATA_DIR} \
--loss_type ${LOSS_TYPE} \
--max_iters ${MAX_ITERS} \
--checkpoints_name ${CHECKPOINTS_NAME} \
--pretrained ${PRETRAINED_MODEL} \
--train_batch_size ${BATCH_SIZE} \
--optim_method ${OPTIM_METHOD} \
--base_lr ${BASE_LR} \
--lr_policy ${LR_POLICY} \
--group_method ${GROUP_METHOD} \
--distributed \
--test_interval 10000 \
2>&1 | tee ${LOG_FILE}
elif [ "$1"x == "local"x ]; then
${PYTHON} -u main.py --configs ${CONFIGS} \
--drop_last y \
--nbb_mult 10 \
--phase train \
--gathered n \
--loss_balance y \
--log_to_file n \
--backbone ${BACKBONE} \
--model_name ${MODEL_NAME} \
--gpu 0 1 2 3 \
--data_dir ${DATA_DIR} \
--loss_type ${LOSS_TYPE} \
--optim_method ${OPTIM_METHOD} \
--base_lr ${BASE_LR} \
--lr_policy ${LR_POLICY} \
--group_method ${GROUP_METHOD} \
--max_iters ${MAX_ITERS} \
--checkpoints_name ${CHECKPOINTS_NAME} \
--pretrained ${PRETRAINED_MODEL} \
--train_batch_size 4 \
--distributed \
--test_interval 10000 \
2>&1 | tee ${LOG_FILE}
elif [ "$1"x == "resume"x ]; then
${PYTHON} -u main.py --configs ${CONFIGS} \
--drop_last y \
--nbb_mult 10 \
--phase train \
--gathered n \
--loss_balance y \
--log_to_file n \
--backbone ${BACKBONE} \
--model_name ${MODEL_NAME} \
--max_iters ${MAX_ITERS} \
--data_dir ${DATA_DIR} \
--loss_type ${LOSS_TYPE} \
--gpu 0 1 2 3 \
--resume_continue y \
--resume ./checkpoints/coco_stuff/${CHECKPOINTS_NAME}_latest.pth \
--checkpoints_name ${CHECKPOINTS_NAME} \
2>&1 | tee -a ${LOG_FILE}
elif [ "$1"x == "val"x ]; then
${PYTHON} -u main.py --configs ${CONFIGS_TEST} \
--data_dir ${DATA_DIR} \
--backbone ${BACKBONE} \
--model_name ${MODEL_NAME} \
--checkpoints_name ${CHECKPOINTS_NAME} \
--phase test \
--gpu 0 1 2 3 4 5 6 7 \
--resume ./checkpoints/coco_stuff/${CHECKPOINTS_NAME}_latest.pth \
--test_dir ${DATA_DIR}/val/image \
--log_to_file n \
--out_dir ${SAVE_DIR}${CHECKPOINTS_NAME}_val_ms
cd lib/metrics
${PYTHON} -u cocostuff_evaluator.py --configs ../../${CONFIGS_TEST} \
--pred_dir ${SAVE_DIR}${CHECKPOINTS_NAME}_val_ms/label \
--gt_dir ${DATA_DIR}/val/label
elif [ "$1"x == "test"x ]; then
if [ "$3"x == "ss"x ]; then
echo "[single scale] test"
${PYTHON} -u main.py --configs ${CONFIGS} --drop_last y --data_dir ${DATA_DIR} \
--backbone ${BACKBONE} --model_name ${MODEL_NAME} --checkpoints_name ${CHECKPOINTS_NAME} \
--phase test --gpu 0 1 2 3 --resume ./checkpoints/coco_stuff/${CHECKPOINTS_NAME}_latest.pth \
--test_dir ${DATA_DIR}/val/image --log_to_file n \
--out_dir ${SAVE_DIR}${CHECKPOINTS_NAME}_test_ss
else
echo "[multiple scale + flip] test"
${PYTHON} -u main.py --configs ${CONFIGS_TEST} --drop_last y --data_dir ${DATA_DIR} \
--backbone ${BACKBONE} --model_name ${MODEL_NAME} --checkpoints_name ${CHECKPOINTS_NAME} \
--phase test --gpu 0 1 2 3 --resume ./checkpoints/coco_stuff/${CHECKPOINTS_NAME}_latest.pth \
--test_dir ${DATA_DIR}/val/image --log_to_file n \
--out_dir ${SAVE_DIR}${CHECKPOINTS_NAME}_test_ms
fi
else
echo "$1"x" is invalid..."
fi