From a4fe159bc07acfc4c3d277448f9103599a54391b Mon Sep 17 00:00:00 2001 From: LDOUBLEV Date: Wed, 9 Jun 2021 09:42:41 +0000 Subject: [PATCH] fix infer bug --- test/infer.sh | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/test/infer.sh b/test/infer.sh index 49f0c4f7..324c346b 100644 --- a/test/infer.sh +++ b/test/infer.sh @@ -45,10 +45,12 @@ IFS='|' for train_model in ${train_model_list[*]}; do if [ ${train_model} = "ocr_det" ];then model_name="det" - yml_file="configs/det/det_mv3_db.yml" + 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-50" + 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="rec" yml_file="configs/rec/rec_mv3_none_bilstm_ctc.yml" @@ -102,9 +104,8 @@ for train_model in ${train_model_list[*]}; do fi save_log_path="${log_path}/${eval_model_name}" - eval_img="Eval.dataset.data_dir=./inference/ch_det_data_50/ Eval.dataset.label_file_list=./inference/ch_det_data_50/test_gt_50.txt" - command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img}" - ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} ${eval_img} + command="${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model='./inference/${eval_model_name}/best_accuracy' Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir} Eval.dataset.label_file_list=${data_label_file}" + ${python} tools/eval.py -c ${yml_file} -o Global.pretrained_model=./inference/${eval_model_name}/best_accuracy Global.save_model_dir=${save_log_path} Eval.dataset.data_dir=${data_dir} Eval.dataset.label_file_list=${data_label_file} status_check $? "${trainer}" "${command}" "${status_log}" command="${python} tools/export_model.py -c ${yml_file} -o Global.pretrained_model="${eval_model_name}/best_accuracy" Global.save_inference_dir=${log_path}/${eval_model_name}_infer Global.save_model_dir=${save_log_path}" @@ -120,11 +121,11 @@ for train_model in ${train_model_list[*]}; do if [ "${model_name}" = "det" ]; then export rec_batch_size_list=( "1" ) inference="tools/infer/predict_det.py" - det_model_dir="./inference/${log_path}/${eval_model_name}_infer" + det_model_dir="${log_path}/${eval_model_name}_infer" rec_model_dir="" elif [ "${model_name}" = "rec" ]; then inference="tools/infer/predict_rec.py" - rec_model_dir="./inference/${log_path}/${eval_model_name}_infer" + rec_model_dir="${log_path}/${eval_model_name}_infer" det_model_dir="" fi # inference @@ -140,8 +141,8 @@ for train_model in ${train_model_list[*]}; do done done done - else - env="CUDA_VISIBLE_DEVICES=${infer_gpu_id}" + else + # env="export CUDA_VISIBLE_DEVICES=${infer_gpu_id}" for use_trt in ${gpu_trt_list[*]}; do for precision in ${gpu_precision_list[*]}; do if [ ${use_trt} = "False" ] && [ ${precision} != "fp32" ]; then @@ -149,8 +150,8 @@ for train_model in ${train_model_list[*]}; do fi for rec_batch_size in ${rec_batch_size_list[*]}; do save_log_path="${log_path}/${model_name}_${slim_trainer}_gpu_usetensorrt_${use_trt}_usefp16_${precision}_recbatchnum_${rec_batch_size}_infer.log" - command="${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt} --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}" - ${env} ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt} --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path} + command="${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt} --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path}" + ${python} ${inference} --use_gpu=True --use_tensorrt=${use_trt} --precision=${precision} --benchmark=True --det_model_dir=${log_path}/${eval_model_name}_infer --rec_batch_num=${rec_batch_size} --rec_model_dir=${rec_model_dir} --image_dir=${img_dir} --save_log_path=${save_log_path} status_check $? "${trainer}" "${command}" "${status_log}" done done -- GitLab