forgetest5
/
PaddleOCR
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

fix ci and output

This commit is contained in:
LDOUBLEV 2021-07-05 03:51:14 +00:00
parent 65118f3099
commit 4042247c97
3 changed files with 8 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
test/ocr_det_params.txt
View File

@ -1,7 +1,7 @@
model_name:ocr_det
python:python3.7
gpu_list:-1|0|0,1
Global.auto_cast:False|True
gpu_list:0
Global.auto_cast:False
Global.epoch_num:10
Global.save_model_dir:./output/
Global.save_inference_dir:./output/
@ -9,7 +9,7 @@ Train.loader.batch_size_per_card:
Global.use_gpu
Global.pretrained_model
trainer:norm|pact|fpgm
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

4
test/test.sh
View File

@ -110,7 +110,7 @@ function func_inference(){
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_${batch_size}"
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${cpu_threads_key}=${threads} ${model_dir_key}=${_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
@ -124,7 +124,7 @@ function func_inference(){
fi
for batch_size in ${batch_size_list[*]}; do
_save_log_path="${_log_path}/infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}"
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${model_dir_key}=${_model_dir} ${batch_size_key}=${batch_size} ${image_dir_key}=${_img_dir} ${save_log_key}=${_save_log_path} --benchmark=True"
command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_trt_key}=${use_trt} ${precision_key}=${precision} ${model_dir_key}=${_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

7
tools/infer/predict_det.py
View File

@ -106,7 +106,7 @@ class TextDetector(object):
model_precision=args.precision,
batch_size=1,
data_shape="dynamic",
save_path="./output/auto_log.lpg",
save_path=args.save_log_path,
inference_config=self.config,
pids=pid,
process_name=None,
@ -174,7 +174,7 @@ class TextDetector(object):
data = {'image': img}
st = time.time()
if args.benchmark:
self.autolog.times.start()
@ -262,7 +262,6 @@ if __name__ == "__main__":
"det_res_{}".format(img_name_pure))
cv2.imwrite(img_path, src_im)
logger.info("The visualized image saved in {}".format(img_path))
if args.benchmark:
text_detector.autolog.report()