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- Global:
- use_gpu: true
- epoch_num: 100
- log_smooth_window: 20
- print_batch_step: 20
- save_model_dir: ./output/SLANet
- save_epoch_step: 400
- # evaluation is run every 1000 iterations after the 0th iteration
- eval_batch_step: [0, 1000]
- cal_metric_during_train: True
- pretrained_model:
- checkpoints:
- save_inference_dir: ./output/SLANet/infer
- use_visualdl: False
- infer_img: ppstructure/docs/table/table.jpg
- # for data or label process
- character_dict_path: ppocr/utils/dict/table_structure_dict.txt
- character_type: en
- max_text_length: &max_text_length 500
- box_format: &box_format 'xyxy' # 'xywh', 'xyxy', 'xyxyxyxy'
- infer_mode: False
- use_sync_bn: True
- save_res_path: 'output/infer'
- Optimizer:
- name: Adam
- beta1: 0.9
- beta2: 0.999
- clip_norm: 5.0
- lr:
- name: Piecewise
- learning_rate: 0.001
- decay_epochs : [40, 50]
- values : [0.001, 0.0001, 0.00005]
- regularizer:
- name: 'L2'
- factor: 0.00000
- Architecture:
- model_type: table
- algorithm: SLANet
- Backbone:
- name: PPLCNet
- scale: 1.0
- pretrained: true
- use_ssld: true
- Neck:
- name: CSPPAN
- out_channels: 96
- Head:
- name: SLAHead
- hidden_size: 256
- max_text_length: *max_text_length
- loc_reg_num: &loc_reg_num 4
- Loss:
- name: SLALoss
- structure_weight: 1.0
- loc_weight: 2.0
- loc_loss: smooth_l1
- PostProcess:
- name: TableLabelDecode
- merge_no_span_structure: &merge_no_span_structure True
- Metric:
- name: TableMetric
- main_indicator: acc
- compute_bbox_metric: False
- loc_reg_num: *loc_reg_num
- box_format: *box_format
- Train:
- dataset:
- name: PubTabDataSet
- data_dir: train_data/table/pubtabnet/train/
- label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_train.jsonl]
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - TableLabelEncode:
- learn_empty_box: False
- merge_no_span_structure: *merge_no_span_structure
- replace_empty_cell_token: False
- loc_reg_num: *loc_reg_num
- max_text_length: *max_text_length
- - TableBoxEncode:
- in_box_format: *box_format
- out_box_format: *box_format
- - ResizeTableImage:
- max_len: 488
- - NormalizeImage:
- scale: 1./255.
- mean: [0.485, 0.456, 0.406]
- std: [0.229, 0.224, 0.225]
- order: 'hwc'
- - PaddingTableImage:
- size: [488, 488]
- - ToCHWImage:
- - KeepKeys:
- keep_keys: [ 'image', 'structure', 'bboxes', 'bbox_masks', 'shape' ]
- loader:
- shuffle: True
- batch_size_per_card: 48
- drop_last: True
- num_workers: 1
- Eval:
- dataset:
- name: PubTabDataSet
- data_dir: train_data/table/pubtabnet/val/
- label_file_list: [train_data/table/pubtabnet/PubTabNet_2.0.0_val.jsonl]
- transforms:
- - DecodeImage: # load image
- img_mode: BGR
- channel_first: False
- - TableLabelEncode:
- learn_empty_box: False
- merge_no_span_structure: *merge_no_span_structure
- replace_empty_cell_token: False
- loc_reg_num: *loc_reg_num
- max_text_length: *max_text_length
- - TableBoxEncode:
- in_box_format: *box_format
- out_box_format: *box_format
- - ResizeTableImage:
- max_len: 488
- - NormalizeImage:
- scale: 1./255.
- mean: [0.485, 0.456, 0.406]
- std: [0.229, 0.224, 0.225]
- order: 'hwc'
- - PaddingTableImage:
- size: [488, 488]
- - ToCHWImage:
- - KeepKeys:
- keep_keys: [ 'image', 'structure', 'bboxes', 'bbox_masks', 'shape' ]
- loader:
- shuffle: False
- drop_last: False
- batch_size_per_card: 48
- num_workers: 1
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