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PaddleOCR
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fix ci error

This commit is contained in:
LDOUBLEV 2021-06-09 11:59:04 +08:00
parent 1203276fbd
commit 0f84fc1e5a
3 changed files with 68 additions and 65 deletions
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17
test/infer.sh
View File

@ -1,5 +1,5 @@
#!/bin/bash
FILENAME=$1
dataline=$(cat ${FILENAME})
# parser params
IFS=$'\n'
@ -17,7 +17,7 @@ train_model_list=$(func_parser "${lines[0]}")
slim_trainer_list=$(func_parser "${lines[3]}")
python=$(func_parser "${lines[4]}")
# inference params
inference=$(func_parser "${lines[5]}")
# inference=$(func_parser "${lines[5]}")
devices=$(func_parser "${lines[6]}")
use_mkldnn_list=$(func_parser "${lines[7]}")
cpu_threads_list=$(func_parser "${lines[8]}")
@ -40,14 +40,15 @@ function status_check(){
echo -e "\033[33m $case failed with command - ${run_command}! \033[0m" | tee -a ${save_log}
fi
}
IFS='|'
for train_model in ${train_model_list[*]}; do
if [ ${train_model} = "det" ];then
if [ ${train_model} = "ocr_det" ];then
model_name="det"
yml_file="configs/det/det_mv3_db.yml"
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar && tar xf ./inference/ch_det_data_50.tar
# wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
tar xf ./inference/ch_det_data_50.tar
img_dir="./inference/ch_det_data_50/"
elif [ ${train_model} = "rec" ];then
elif [ ${train_model} = "ocr_rec" ];then
model_name="rec"
yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml"
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar && tar xf ./inference/ch_rec_data_200.tar
@ -89,13 +90,14 @@ for train_model in ${train_model_list[*]}; do
wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
fi
fi
save_log_path="${log_path}/${eval_model_name}"
command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}"
${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_model_dir=${save_log_path}
status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}"
${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}
${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model=${eval_model_name} Global.save_inference_dir="${log_path}/${eval_model_name}_infer" Global.save_model_dir=${save_log_path}
status_check $? "${trainer}" "${command}" "${save_log_path}/train.log"
if [ $? -eq 0 ]; then
@ -145,3 +147,4 @@ for train_model in ${train_model_list[*]}; do
fi
done
done
done

2
test/params.txt
View File

@ -1,7 +1,7 @@
train_model_list: ocr_det
gpu_list: -1|0|0,1
auto_cast_list: False
trainer_list: norm|quant|prune
trainer_list: norm|quant
python: python3.7
inference: python

10
test/test.sh
View File

@ -78,7 +78,7 @@ function status_check(){
fi
}
IFS="|"
for train_model in ${train_model_list[*]}; do
if [ ${train_model} = "ocr_det" ];then
model_name="det"
@ -107,7 +107,7 @@ for train_model in ${train_model_list[*]}; do
env="CUDA_VISIBLE_DEVICES=${array[0]}"
IFS="|"
fi
IFS="|"
for auto_cast in ${auto_cast_list[*]}; do
for slim_trainer in ${slim_trainer_list[*]}; do
if [ ${slim_trainer} = "norm" ]; then
@ -126,13 +126,13 @@ for train_model in ${train_model_list[*]}; do
trainer="tools/train.py"
export_model="tools/export_model.py"
fi
save_log=${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}
save_log="${log_path}/${model_name}_${slim_trainer}_autocast_${auto_cast}_gpuid_${gpu}"
command="${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}"
${env} ${python} ${launch} ${trainer} -c ${yml_file} -o Global.epoch_num=${epoch} Global.eval_batch_step=${eval_batch_step} Global.auto_cast=${auto_cast} Global.save_model_dir=${save_log} Global.use_gpu=${use_gpu}
status_check $? "${trainer}" "${command}" "${save_log}/train.log"
command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/best_accuracy Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}
command="${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}"
${env} ${python} ${export_model} -c ${yml_file} -o Global.pretrained_model=${save_log}/latest Global.save_inference_dir=${save_log}/export_inference/ Global.save_model_dir=${save_log}
status_check $? "${trainer}" "${command}" "${save_log}/train.log"
if [ "${model_name}" = "det" ]; then