diff --git a/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml b/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml index 8e9315d2488ad187eb12708d094c5be57cb48eac..4b7340ac59851aa54effa49f73196ad863d02a95 100644 --- a/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml +++ b/test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml @@ -62,7 +62,7 @@ Train: data_dir: ./train_data/icdar2015/text_localization/ label_file_list: - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt - ratio_list: [0.1, 0.45, 0.3, 0.15] + ratio_list: [1.0] transforms: - DecodeImage: # load image img_mode: BGR diff --git a/test_tipc/configs/en_server_pgnetA/train_infer_python.txt b/test_tipc/configs/en_server_pgnetA/train_infer_python.txt index d70776998c4e326905920586e90f2833fe42e89b..1a25eccb3a192823d58af1c6cf089ea15b6d394c 100644 --- a/test_tipc/configs/en_server_pgnetA/train_infer_python.txt +++ b/test_tipc/configs/en_server_pgnetA/train_infer_python.txt @@ -4,7 +4,7 @@ python:python3.7 gpu_list:0|0,1 Global.use_gpu:True|True Global.auto_cast:null -Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500 +Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=500 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=14 Global.pretrained_model:null @@ -42,7 +42,7 @@ inference:tools/infer/predict_e2e.py --enable_mkldnn:True|False --cpu_threads:1|6 --rec_batch_num:1 ---use_tensorrt:False|True +--use_tensorrt:False --precision:fp32|fp16|int8 --e2e_model_dir: --image_dir:./inference/ch_det_data_50/all-sum-510/ diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh index 8876157ef8f4b44b227c171d25bdfd1060007910..daf12f429ac81ebfb165ee68c0c42433a05691bc 100644 --- a/test_tipc/prepare.sh +++ b/test_tipc/prepare.sh @@ -25,7 +25,7 @@ if [ ${MODE} = "lite_train_lite_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 --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate - if [ ${model_name} == "ch_PPOCRv2_det" ]; then + if [ ${model_name} =~ "ch_PPOCRv2_det" ]; then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../ fi @@ -50,7 +50,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then if [ ${model_name} == "det_r50_vd_sast_icdar15_v2.0" ] || [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate wget -nc -P ./train_data/ wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate - cd ./train_data && tar xf total_text_lite.tar && ln -s total_text && cd ../ + cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text && cd ../ fi if [ ${model_name} == "det_mv3_db_v2.0" ]; then wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate @@ -78,15 +78,15 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../ fi if [ ${model_name} == "en_server_pgnetA" ]; then - wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/total_text.tar --no-check-certificate + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../ - cd ./train_data && tar xf total_text.tar && ln -s total_text && cd ../ + cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../ fi if [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate - wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/total_text.tar --no-check-certificate - cd ./train_data && tar xf total_text.tar && ln -s total_text && cd ../ + wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate + cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text && cd ../ fi elif [ ${MODE} = "lite_train_whole_infer" ];then wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate @@ -135,7 +135,7 @@ elif [ ${MODE} = "whole_infer" ];then wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate cd ./inference && tar xf ${eval_model_name}.tar && tar xf rec_inference.tar && cd ../ fi - if [ ${model_name} = "ch_PPOCRv2_det" ]; then + if [ ${model_name} =~ "ch_PPOCRv2_det" ]; then eval_model_name="ch_PP-OCRv2_det_infer" wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate diff --git a/tools/infer/utility.py b/tools/infer/utility.py index d7e058c2b7c0eaf6bd40dd197a3cb1417bc7bb7d..21bbee098ef19456d05165969a9ad400400f1264 100644 --- a/tools/infer/utility.py +++ b/tools/infer/utility.py @@ -195,6 +195,7 @@ def create_predictor(args, mode, logger): max_batch_size=args.max_batch_size, min_subgraph_size=args.min_subgraph_size) # skip the minmum trt subgraph + use_dynamic_shape = True if mode == "det": min_input_shape = { "x": [1, 3, 50, 50], @@ -260,6 +261,8 @@ def create_predictor(args, mode, logger): max_input_shape.update(max_pact_shape) opt_input_shape.update(opt_pact_shape) elif mode == "rec": + if args.rec_algorithm != "CRNN": + use_dynamic_shape = False min_input_shape = {"x": [1, 3, 32, 10]} max_input_shape = {"x": [args.rec_batch_num, 3, 32, 1536]} opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]} @@ -268,14 +271,8 @@ def create_predictor(args, mode, logger): max_input_shape = {"x": [args.rec_batch_num, 3, 48, 1024]} opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]} else: - min_input_shape = {"x": [1, 3, 10, 10]} - max_input_shape = {"x": [1, 3, 512, 512]} - opt_input_shape = {"x": [1, 3, 256, 256]} - if mode == "rec": - if args.rec_algorithm == "CRNN": - config.set_trt_dynamic_shape_info( - min_input_shape, max_input_shape, opt_input_shape) - else: + use_dynamic_shape = False + if use_dynamic_shape: config.set_trt_dynamic_shape_info( min_input_shape, max_input_shape, opt_input_shape)