diff --git a/configs/rec/rec_icdar15_train.yml b/configs/rec/rec_icdar15_train.yml index 20f758c20da9547486d7492d6a09cceb2b937e4e..500d2333f217008b2abf352b0ccd29a43ec24fd5 100644 --- a/configs/rec/rec_icdar15_train.yml +++ b/configs/rec/rec_icdar15_train.yml @@ -10,7 +10,7 @@ Global: cal_metric_during_train: True pretrained_model: checkpoints: - save_inference_dir: + save_inference_dir: ./ use_visualdl: False infer_img: doc/imgs_words_en/word_10.png # for data or label process @@ -60,8 +60,8 @@ Metric: Train: dataset: name: SimpleDataSet - data_dir: ./train_data/ - label_file_list: ["./train_data/train_list.txt"] + data_dir: ./train_data/ic15_data/ + label_file_list: ["./train_data/ic15_data/rec_gt_train.txt"] transforms: - DecodeImage: # load image img_mode: BGR @@ -81,8 +81,8 @@ Train: Eval: dataset: name: SimpleDataSet - data_dir: ./train_data/ - label_file_list: ["./train_data/val_list.txt"] + data_dir: ./train_data/ic15_data + label_file_list: ["./train_data/ic15_data/rec_gt_test.txt"] transforms: - DecodeImage: # load image img_mode: BGR diff --git a/test/ocr_det_params.txt b/test/ocr_det_params.txt deleted file mode 100644 index bdfd4d4f47431bca97437963e1dc56d1b57838bb..0000000000000000000000000000000000000000 --- a/test/ocr_det_params.txt +++ /dev/null @@ -1,35 +0,0 @@ -model_name:ocr_det -python:python3.7 -gpu_list:0|0,1 -Global.auto_cast:null -Global.epoch_num:10 -Global.save_model_dir:./output/ -Train.loader.batch_size_per_card: -Global.use_gpu: -Global.pretrained_model:null - -trainer:norm|pact -norm_train:tools/train.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained -quant_train:deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy -fpgm_train:null -distill_train:null - -eval:tools/eval.py -c configs/det/det_mv3_db.yml -o - -Global.save_inference_dir:./output/ -Global.pretrained_model: -norm_export:tools/export_model.py -c configs/det/det_mv3_db.yml -o -quant_export:deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o -fpgm_export:deploy/slim/prune/export_prune_model.py -distill_export:null - -inference:tools/infer/predict_det.py ---use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1 ---use_tensorrt:True|False ---precision:fp32|fp16|int8 ---det_model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/ ---image_dir:./inference/ch_det_data_50/all-sum-510/ ---save_log_path:./test/output/ diff --git a/test/ocr_rec_params.txt b/test/ocr_rec_params.txt deleted file mode 100644 index 6ce081ec0523e86ee22c192cde5e631ebe1f63b0..0000000000000000000000000000000000000000 --- a/test/ocr_rec_params.txt +++ /dev/null @@ -1,35 +0,0 @@ -model_name:ocr_rec -python:python -gpu_list:0|0,1 -Global.auto_cast:null -Global.epoch_num:10 -Global.save_model_dir:./output/ -Train.loader.batch_size_per_card: -Global.use_gpu: -Global.pretrained_model:null - -trainer:norm|pact -norm_train:tools/train.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml -quant_train:deploy/slim/quantization/quant.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml -fpgm_train:null -distill_train:null - -eval:tools/eval.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml -o - -Global.save_inference_dir:./output/ -Global.pretrained_model: -norm_export:tools/export_model.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml -o -quant_export:deploy/slim/quantization/export_model.py -c configs/rec/rec_mv3_none_bilstm_ctc.yml -o -fpgm_export:null -distill_export:null - -inference:tools/infer/predict_rec.py ---use_gpu:True|False ---enable_mkldnn:True|False ---cpu_threads:1|6 ---rec_batch_num:1 ---use_tensorrt:True|False ---precision:fp32|fp16|int8 ---rec_model_dir:./inference/ch_ppocr_mobile_v2.0_rec_infer/ ---image_dir:./inference/rec_inference ---save_log_path:./test/output/ \ No newline at end of file diff --git a/test/prepare.sh b/test/prepare.sh deleted file mode 100644 index f6941b9ced8eb3b2fc6dda2a7ac76d025f7a18e1..0000000000000000000000000000000000000000 --- a/test/prepare.sh +++ /dev/null @@ -1,146 +0,0 @@ -#!/bin/bash -FILENAME=$1 -# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', '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[0]}") -train_model_list=$(func_parser_value "${lines[0]}") - -trainer_list=$(func_parser_value "${lines[10]}") - -# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer'] -MODE=$2 -# prepare pretrained weights and dataset -if [ ${train_model_list[*]} = "ocr_det" ]; then - wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams - wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar - cd pretrain_models && tar xf det_mv3_db_v2.0_train.tar && cd ../ - fi -if [ ${MODE} = "lite_train_infer" ];then - # pretrain lite train data - rm -rf ./train_data/icdar2015 - 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 - - cd ./train_data/ && tar xf icdar2015_lite.tar && tar xf ic15_data.tar - ln -s ./icdar2015_lite ./icdar2015 - cd ../ - epoch=10 - eval_batch_step=10 -elif [ ${MODE} = "whole_train_infer" ];then - rm -rf ./train_data/icdar2015 - 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 ../ - epoch=500 - eval_batch_step=200 -elif [ ${MODE} = "whole_infer" ];then - rm -rf ./train_data/icdar2015 - 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 ../ - epoch=10 - eval_batch_step=10 -else - rm -rf ./train_data/icdar2015 - wget -nc -P ./train_data https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar - if [ ${model_name} = "ocr_det" ]; then - eval_model_name="ch_ppocr_mobile_v2.0_det_infer" - 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 && cd ../ - else - eval_model_name="ch_ppocr_mobile_v2.0_rec_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - fi -fi - - -IFS='|' -for train_model in ${train_model_list[*]}; do - if [ ${train_model} = "ocr_det" ];then - model_name="ocr_det" - yml_file="configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar - cd ./inference && tar xf ch_det_data_50.tar && cd ../ - img_dir="./inference/ch_det_data_50/all-sum-510" - data_dir=./inference/ch_det_data_50/ - data_label_file=[./inference/ch_det_data_50/test_gt_50.txt] - elif [ ${train_model} = "ocr_rec" ];then - model_name="ocr_rec" - yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar - cd ./inference && tar xf rec_inference.tar && cd ../ - img_dir="./inference/rec_inference/" - data_dir=./inference/rec_inference - data_label_file=[./inference/rec_inference/rec_gt_test.txt] - fi - - # eval - for slim_trainer in ${trainer_list[*]}; do - if [ ${slim_trainer} = "norm" ]; then - if [ ${model_name} = "det" ]; then - eval_model_name="ch_ppocr_mobile_v2.0_det_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - else - eval_model_name="ch_ppocr_mobile_v2.0_rec_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - fi - elif [ ${slim_trainer} = "pact" ]; then - if [ ${model_name} = "det" ]; then - eval_model_name="ch_ppocr_mobile_v2.0_det_quant_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - else - eval_model_name="ch_ppocr_mobile_v2.0_rec_quant_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - fi - elif [ ${slim_trainer} = "distill" ]; then - if [ ${model_name} = "det" ]; then - eval_model_name="ch_ppocr_mobile_v2.0_det_distill_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - else - eval_model_name="ch_ppocr_mobile_v2.0_rec_distill_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - fi - elif [ ${slim_trainer} = "fpgm" ]; then - if [ ${model_name} = "det" ]; then - eval_model_name="ch_ppocr_mobile_v2.0_det_prune_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - else - eval_model_name="ch_ppocr_mobile_v2.0_rec_prune_train" - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ - fi - fi - done -done diff --git a/test/test.sh b/test/test.sh deleted file mode 100644 index f2ac3f8b29af1be08e8eb5b836133dc53ad3d5b2..0000000000000000000000000000000000000000 --- a/test/test.sh +++ /dev/null @@ -1,237 +0,0 @@ -#!/bin/bash -FILENAME=$1 -# MODE be one of ['lite_train_infer' 'whole_infer' 'whole_train_infer', '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} -} -function status_check(){ - last_status=$1 # the exit code - run_command=$2 - run_log=$3 - if [ $last_status -eq 0 ]; then - echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log} - else - echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log} - fi -} - -IFS=$'\n' -# The training params -model_name=$(func_parser_value "${lines[0]}") -python=$(func_parser_value "${lines[1]}") -gpu_list=$(func_parser_value "${lines[2]}") -autocast_list=$(func_parser_value "${lines[3]}") -autocast_key=$(func_parser_key "${lines[3]}") -epoch_key=$(func_parser_key "${lines[4]}") -epoch_num=$(func_parser_value "${lines[4]}") -save_model_key=$(func_parser_key "${lines[5]}") -train_batch_key=$(func_parser_key "${lines[6]}") -train_use_gpu_key=$(func_parser_key "${lines[7]}") -pretrain_model_key=$(func_parser_key "${lines[8]}") -pretrain_model_value=$(func_parser_value "${lines[8]}") - -trainer_list=$(func_parser_value "${lines[9]}") -norm_trainer=$(func_parser_value "${lines[10]}") -pact_trainer=$(func_parser_value "${lines[11]}") -fpgm_trainer=$(func_parser_value "${lines[12]}") -distill_trainer=$(func_parser_value "${lines[13]}") - -eval_py=$(func_parser_value "${lines[14]}") - -save_infer_key=$(func_parser_key "${lines[15]}") -export_weight=$(func_parser_key "${lines[16]}") -norm_export=$(func_parser_value "${lines[17]}") -pact_export=$(func_parser_value "${lines[18]}") -fpgm_export=$(func_parser_value "${lines[19]}") -distill_export=$(func_parser_value "${lines[20]}") - -inference_py=$(func_parser_value "${lines[21]}") -use_gpu_key=$(func_parser_key "${lines[22]}") -use_gpu_list=$(func_parser_value "${lines[22]}") -use_mkldnn_key=$(func_parser_key "${lines[23]}") -use_mkldnn_list=$(func_parser_value "${lines[23]}") -cpu_threads_key=$(func_parser_key "${lines[24]}") -cpu_threads_list=$(func_parser_value "${lines[24]}") -batch_size_key=$(func_parser_key "${lines[25]}") -batch_size_list=$(func_parser_value "${lines[25]}") -use_trt_key=$(func_parser_key "${lines[26]}") -use_trt_list=$(func_parser_value "${lines[26]}") -precision_key=$(func_parser_key "${lines[27]}") -precision_list=$(func_parser_value "${lines[27]}") -infer_model_key=$(func_parser_key "${lines[28]}") -infer_model=$(func_parser_value "${lines[28]}") -image_dir_key=$(func_parser_key "${lines[29]}") -infer_img_dir=$(func_parser_value "${lines[29]}") -save_log_key=$(func_parser_key "${lines[30]}") - -LOG_PATH="./test/output" -mkdir -p ${LOG_PATH} -status_log="${LOG_PATH}/results.log" - - -function func_inference(){ - IFS='|' - _python=$1 - _script=$2 - _model_dir=$3 - _log_path=$4 - _img_dir=$5 - - # inference - for use_gpu in ${use_gpu_list[*]}; do - if [ ${use_gpu} = "False" ]; then - for use_mkldnn in ${use_mkldnn_list[*]}; do - for threads in ${cpu_threads_list[*]}; do - for batch_size in ${batch_size_list[*]}; do - _save_log_path="${_log_path}/infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_batchsize_${batch_size}.log" - command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${infer_model_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True" - eval $command - status_check $? "${command}" "${status_log}" - done - done - done - else - for use_trt in ${use_trt_list[*]}; do - for precision in ${precision_list[*]}; do - if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then - continue - fi - for batch_size in ${batch_size_list[*]}; do - _save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log" - command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${infer_model_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True" - eval $command - status_check $? "${command}" "${status_log}" - done - done - done - fi - done -} - -if [ ${MODE} != "infer" ]; then - -IFS="|" -for gpu in ${gpu_list[*]}; do - use_gpu=True - if [ ${gpu} = "-1" ];then - use_gpu=False - env="" - elif [ ${#gpu} -le 1 ];then - env="export CUDA_VISIBLE_DEVICES=${gpu}" - eval ${env} - elif [ ${#gpu} -le 15 ];then - IFS="," - array=(${gpu}) - env="export CUDA_VISIBLE_DEVICES=${array[0]}" - IFS="|" - else - IFS=";" - array=(${gpu}) - ips=${array[0]} - gpu=${array[1]} - IFS="|" - env=" " - fi - for autocast in ${autocast_list[*]}; do - for trainer in ${trainer_list[*]}; do - if [ ${trainer} = "pact" ]; then - run_train=${pact_trainer} - run_export=${pact_export} - elif [ ${trainer} = "fpgm" ]; then - run_train=${fpgm_trainer} - run_export=${fpgm_export} - elif [ ${trainer} = "distill" ]; then - run_train=${distill_trainer} - run_export=${distill_export} - else - run_train=${norm_trainer} - run_export=${norm_export} - fi - - if [ ${run_train} = "null" ]; then - continue - fi - if [ ${run_export} = "null" ]; then - continue - fi - - # not set autocast when autocast is null - if [ ${autocast} = "null" ]; then - set_autocast=" " - else - set_autocast="${autocast_key}=${autocast}" - fi - # not set epoch when whole_train_infer - if [ ${MODE} != "whole_train_infer" ]; then - set_epoch="${epoch_key}=${epoch_num}" - else - set_epoch=" " - fi - # set pretrain - if [ ${pretrain_model_value} != "null" ]; then - set_pretrain="${pretrain_model_key}=${pretrain_model_value}" - else - set_pretrain=" " - fi - - save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}" - if [ ${#gpu} -le 2 ];then # train with cpu or single gpu - cmd="${python} ${run_train} ${train_use_gpu_key}=${use_gpu} ${save_model_key}=${save_log} ${set_epoch} ${set_pretrain} ${set_autocast}" - elif [ ${#gpu} -le 15 ];then # train with multi-gpu - cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${save_model_key}=${save_log} ${set_epoch} ${set_pretrain} ${set_autocast}" - else # train with multi-machine - cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${save_model_key}=${save_log} ${set_pretrain} ${set_epoch} ${set_autocast}" - fi - # run train - eval $cmd - status_check $? "${cmd}" "${status_log}" - - # run eval - eval_cmd="${python} ${eval_py} ${save_model_key}=${save_log} ${pretrain_model_key}=${save_log}/latest" - eval $eval_cmd - status_check $? "${eval_cmd}" "${status_log}" - - # run export model - save_infer_path="${save_log}" - export_cmd="${python} ${run_export} ${save_model_key}=${save_log} ${export_weight}=${save_log}/latest ${save_infer_key}=${save_infer_path}" - eval $export_cmd - status_check $? "${export_cmd}" "${status_log}" - - #run inference - eval $env - save_infer_path="${save_log}" - func_inference "${python}" "${inference_py}" "${save_infer_path}" "${LOG_PATH}" "${infer_img_dir}" - eval "unset CUDA_VISIBLE_DEVICES" - done - done -done - -else - GPUID=$3 - if [ ${#GPUID} -le 0 ];then - env=" " - else - env="export CUDA_VISIBLE_DEVICES=${GPUID}" - fi - echo $env - #run inference - func_inference "${python}" "${inference_py}" "${infer_model}" "${LOG_PATH}" "${infer_img_dir}" -fi diff --git a/tests/ocr_det_params.txt b/tests/ocr_det_params.txt index 6ef5230f6bbe2f0125d6d17a45c9036f7a7476df..6aff66c6aa8591c9f48c81cf857809f956a3cda2 100644 --- a/tests/ocr_det_params.txt +++ b/tests/ocr_det_params.txt @@ -49,3 +49,4 @@ inference:tools/infer/predict_det.py --save_log_path:null --benchmark:True null:null + diff --git a/tests/ocr_rec_params.txt b/tests/ocr_rec_params.txt new file mode 100644 index 0000000000000000000000000000000000000000..71d12f90b3bda128c3f6047c6740911dac417954 --- /dev/null +++ b/tests/ocr_rec_params.txt @@ -0,0 +1,51 @@ +===========================train_params=========================== +model_name:ocr_rec +python:python3.7 +gpu_list:0|2,3 +Global.use_gpu:True|True +Global.auto_cast:null +Global.epoch_num:lite_train_infer=2|whole_train_infer=300 +Global.save_model_dir:./output/ +Train.loader.batch_size_per_card:lite_train_infer=128|whole_train_infer=128 +Global.pretrained_model:null +train_model_name:latest +train_infer_img_dir:./train_data/ic15_data/train +null:null +## +trainer:norm_train|pact_train +norm_train:tools/train.py -c configs/rec/rec_icdar15_train.yml -o +pact_train:deploy/slim/quantization/quant.py -c configs/rec/rec_icdar15_train.yml -o +fpgm_train:null +distill_train:null +null:null +null:null +## +===========================eval_params=========================== +eval:tools/eval.py -c configs/rec/rec_icdar15_train.yml -o +null:null +## +===========================infer_params=========================== +Global.save_inference_dir:./output/ +Global.pretrained_model: +norm_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o +quant_export:deploy/slim/quantization/export_model.py -c configs/rec/rec_icdar15_train.yml -o +fpgm_export:null +distill_export:null +export1:null +export2:null +## +infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/ +infer_export:null +infer_quant:False +inference:tools/infer/predict_rec.py +--use_gpu:True|False +--enable_mkldnn:True|False +--cpu_threads:1|6 +--rec_batch_num:1 +--use_tensorrt:True|False +--precision:fp32|fp16|int8 +--rec_model_dir: +--image_dir:./inference/rec_inference +--save_log_path:./test/output/ +--benchmark:True +null:null diff --git a/tests/prepare.sh b/tests/prepare.sh index c105d8f43287a61dffbf813e0665a6200bccc348..aaf25ee421ebdea3deaf9a6d782f795de3022d10 100644 --- a/tests/prepare.sh +++ b/tests/prepare.sh @@ -35,32 +35,42 @@ 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 - cd ./train_data/ && tar xf icdar2015_lite.tar + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar # todo change to bcebos + + cd ./train_data/ && tar xf icdar2015_lite.tar && tar xf ic15_data.tar ln -s ./icdar2015_lite ./icdar2015 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 - cd ./train_data/ && tar xf icdar2015.tar && cd ../ + 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 - cd ./train_data/ && tar xf 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 - rm -rf ./train_data/icdar2015 - if [[ ${model_name} = "ocr_det" ]]; then - wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar + 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_train" + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar - cd ./inference && tar xf ${eval_model_name}.tar && cd ../ + cd ./inference && tar xf ${eval_model_name}.tar && tar xf ic15_data.tar && cd ../ fi fi +