prepare.sh

#!/bin/bash
FILENAME=$1
# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', 'infer', 'serving_infer']
MODE=$2

dataline=$(cat ${FILENAME})

# parser params
IFS=$'\n'
lines=(${dataline})
function func_parser_key(){
    strs=$1
    IFS=":"
    array=(${strs})
    tmp=${array[0]}
    echo ${tmp}
}
function func_parser_value(){
    strs=$1
    IFS=":"
    array=(${strs})
    tmp=${array[1]}
    echo ${tmp}
}
IFS=$'\n'
# The training params
model_name=$(func_parser_value "${lines[1]}")

trainer_list=$(func_parser_value "${lines[14]}")

# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer']
MODE=$2

if [ ${MODE} = "lite_train_infer" ];then
    # pretrain lite train data
    wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
    rm -rf ./train_data/icdar2015
    rm -rf ./train_data/ic15_data
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar # todo change to bcebos
    wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar
    cd ./train_data/ && tar xf icdar2015_lite.tar && tar xf ic15_data.tar
    ln -s ./icdar2015_lite ./icdar2015
    cd ../
    cd ./inference && tar xf rec_inference.tar && cd ../
elif [ ${MODE} = "whole_train_infer" ];then
    wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
    rm -rf ./train_data/icdar2015
    rm -rf ./train_data/ic15_data
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015.tar
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar
    cd ./train_data/ && tar xf icdar2015.tar && tar xf ic15_data.tar && cd ../
elif [ ${MODE} = "whole_infer" ];then
    wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
    rm -rf ./train_data/icdar2015
    rm -rf ./train_data/ic15_data
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_infer.tar
    wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar
    cd ./train_data/ && tar xf icdar2015_infer.tar && tar xf ic15_data.tar
    ln -s ./icdar2015_infer ./icdar2015
    cd ../
else
    if [ ${model_name} = "ocr_det" ]; then
        eval_model_name="ch_ppocr_mobile_v2.0_det_infer"
        rm -rf ./train_data/icdar2015
        wget -nc -P ./train_data https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
        wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
        cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../
    else 
        rm -rf ./train_data/ic15_data
        eval_model_name="ch_ppocr_mobile_v2.0_rec_infer"
        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar
        wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar
        cd ./inference && tar xf ${eval_model_name}.tar && tar xf rec_inference.tar && cd ../
    fi 
fi

if [ ${MODE} = "serving_infer" ];then
    # prepare serving env
    python_name=$(func_parser_value "${lines[2]}")
    ${python_name} -m pip install install paddle-serving-server-gpu==0.6.1.post101
    ${python_name} -m pip install paddle_serving_client==0.6.1
    ${python_name} -m pip install paddle-serving-app==0.6.1
    wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar
    wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar
    cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_ppocr_mobile_v2.0_rec_infer.tar
fi