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https://github.com/PaddlePaddle/PaddleOCR.git
synced 2025-12-27 15:08:17 +00:00
fix seed
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tink2123
parent
d7e7e9e408
commit
ee6fe424e9
@ -53,7 +53,7 @@ def compute_partial_repr(input_points, control_points):
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1]
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repr_matrix = 0.5 * pairwise_dist * paddle.log(pairwise_dist)
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# fix numerical error for 0 * log(0), substitute all nan with 0
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mask = repr_matrix != repr_matrix
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mask = np.array(repr_matrix != repr_matrix)
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repr_matrix[mask] = 0
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return repr_matrix
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@ -0,0 +1,110 @@
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Global:
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use_gpu: True
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epoch_num: 400
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log_smooth_window: 20
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print_batch_step: 10
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save_model_dir: ./output/rec/seed
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save_epoch_step: 3
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# evaluation is run every 5000 iterations after the 4000th iteration
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eval_batch_step: [0, 2000]
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cal_metric_during_train: True
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pretrained_model:
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checkpoints:
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save_inference_dir:
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use_visualdl: False
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infer_img: doc/imgs_words_en/word_10.png
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# for data or label process
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character_dict_path: ppocr/utils/EN_symbol_dict.txt
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max_text_length: 100
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infer_mode: False
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use_space_char: False
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save_res_path: ./output/rec/predicts_seed.txt
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Optimizer:
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name: Adadelta
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weight_deacy: 0.0
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momentum: 0.9
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lr:
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name: Piecewise
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decay_epochs: [4,5,8]
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values: [1.0, 0.1, 0.01]
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regularizer:
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name: 'L2'
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factor: 2.0e-05
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Architecture:
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model_type: rec
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algorithm: SEED
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Transform:
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name: STN_ON
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tps_inputsize: [32, 64]
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tps_outputsize: [32, 100]
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num_control_points: 20
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tps_margins: [0.05,0.05]
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stn_activation: none
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Backbone:
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name: ResNet_ASTER
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Head:
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name: AsterHead # AttentionHead
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sDim: 512
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attDim: 512
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max_len_labels: 100
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Loss:
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name: AsterLoss
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PostProcess:
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name: SEEDLabelDecode
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Metric:
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name: RecMetric
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main_indicator: acc
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is_filter: True
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Train:
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dataset:
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name: SimpleDataSet
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data_dir: ./train_data/ic15_data/
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label_file_list: ["./train_data/ic15_data/rec_gt_train.txt"]
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transforms:
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- Fasttext:
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path: "./cc.en.300.bin"
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- SEEDLabelEncode: # Class handling label
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- RecResizeImg:
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character_type: en
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image_shape: [3, 64, 256]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', 'length', 'fast_label'] # dataloader will return list in this order
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loader:
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shuffle: True
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batch_size_per_card: 256
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drop_last: True
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num_workers: 6
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Eval:
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dataset:
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name: SimpleDataSet
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data_dir: ./train_data/ic15_data
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label_file_list: ["./train_data/ic15_data/rec_gt_test.txt"]
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transforms:
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- DecodeImage: # load image
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img_mode: BGR
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channel_first: False
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- SEEDLabelEncode: # Class handling label
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- RecResizeImg:
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character_type: en
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image_shape: [3, 64, 256]
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padding: False
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- KeepKeys:
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keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
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loader:
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shuffle: False
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drop_last: True
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batch_size_per_card: 256
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num_workers: 4
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@ -0,0 +1,51 @@
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===========================train_params===========================
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model_name:rec_resnet_stn_bilstm_att_v2.0
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python:python3.7
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gpu_list:0|0,1
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Global.use_gpu:True|True
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Global.auto_cast:null
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Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=100
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Global.save_model_dir:./output/
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Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128
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Global.pretrained_model:null
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train_model_name:latest
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train_infer_img_dir:./inference/rec_inference
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null:null
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##
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trainer:norm_train
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norm_train:tools/train.py -c test_tipc/configs/rec_resnet_stn_bilstm_att_v2.0/rec_icdar15_train.yml -o
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pact_train:null
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fpgm_train:null
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distill_train:null
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null:null
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null:null
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##
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===========================eval_params===========================
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eval:tools/eval.py -c test_tipc/configs/rec_resnet_stn_bilstm_att_v2.0/rec_icdar15_train.yml -o
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null:null
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##
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===========================infer_params===========================
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Global.save_inference_dir:./output/
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Global.pretrained_model:
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norm_export:tools/export_model.py -c test_tipc/configs/rec_resnet_stn_bilstm_att_v2.0/rec_icdar15_train.yml -o
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quant_export:null
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fpgm_export:null
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distill_export:null
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export1:null
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export2:null
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##
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infer_model:null
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infer_export:tools/export_model.py -c test_tipc/configs/rec_resnet_stn_bilstm_att_v2.0/rec_icdar15_train.yml -o
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infer_quant:False
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inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ic15_dict.txt --rec_image_shape="3,32,100"
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--use_gpu:True|False
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--enable_mkldnn:True|False
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--cpu_threads:1|6
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--rec_batch_num:1|6
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--use_tensorrt:True|False
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--precision:fp32|fp16|int8
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--rec_model_dir:
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--image_dir:./inference/rec_inference
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--save_log_path:./test/output/
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--benchmark:True
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null:null
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@ -52,7 +52,10 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
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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
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cd ./train_data && tar xf total_text_lite.tar && ln -s total_text && cd ../
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fi
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if [ ${model_name} == "rec_resnet_stn_bilstm_att_v2.0" ]; then
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wget -nc https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.en.300.bin.gz
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gunzip cc.en.300.bin.gz
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fi
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elif [ ${MODE} = "whole_train_whole_infer" ];then
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wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate
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rm -rf ./train_data/icdar2015
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@ -128,11 +131,6 @@ elif [ ${MODE} = "whole_infer" ];then
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wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate
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cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../
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fi
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elif [ ${model_name} = "ch_PPOCRv2_det" ]; then
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wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
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wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/e2e_server_pgnetA_infer.tar --no-check-certificate
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cd ./inference && tar xf e2e_server_pgnetA_infer.tar && tar xf ch_det_data_50.tar && cd ../
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fi
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if [ ${model_name} == "en_server_pgnetA" ]; then
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wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate
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cd ./inference && tar xf en_server_pgnetA.tar && cd ../
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